diff --git a/examples/basic_func_fun.py b/examples/basic_func_fun.py
index da06aa6..294b711 100644
--- a/examples/basic_func_fun.py
+++ b/examples/basic_func_fun.py
@@ -34,7 +34,7 @@
 
 #from pyrasa.irasa import irasa
 #%%
-freq_irasa, psd_ap, psd_p = irasa(sig, 
+irasa_result = irasa(sig, 
                                   fs=fs, 
                                   band=(1, 100), 
                                   psd_kwargs={'nperseg': duration*fs, 
@@ -44,26 +44,21 @@
 
 f, axes = plt.subplots(ncols=2, figsize=(8, 4))
 axes[0].set_title('Periodic')
-axes[0].plot(freq_irasa, psd_p[0,:])
+axes[0].plot(irasa_result.freqs, irasa_result.periodic[0,:])
 axes[0].set_ylabel('Power (a.u.)')
 axes[0].set_xlabel('Frequency (Hz)')
 axes[1].set_title('Aperiodic')
-axes[1].loglog(freq_irasa, psd_ap[0,:])
+axes[1].loglog(irasa_result.freqs, irasa_result.aperiodic[0,:])
 axes[1].set_ylabel('Power (a.u.)')
 axes[1].set_xlabel('Frequency (Hz)')
 
 f.tight_layout()
 
 # %% get periodic stuff
-from pyrasa.utils.peak_utils import get_peak_params
-get_peak_params(psd_p, freqs=freq_irasa)
-# %%
-from pyrasa.utils.aperiodic_utils import compute_slope
 
-ap_params, gof_params = compute_slope(aperiodic_spectrum=psd_ap,
-                                       freqs=freq_irasa-1, 
-                                       fit_func='fixed',
-                                       #fit_bounds=[0, 40]
-                                       )
-ap_params
+pe_params = irasa_result.get_peaks()
+pe_params
+#%% get aperiodics
+ap_params = irasa_result.get_slopes(fit_func='knee')
+ap_params.gof
 # %%
diff --git a/examples/custom_fit_functions.py b/examples/custom_fit_functions.py
new file mode 100644
index 0000000..7ef2e0c
--- /dev/null
+++ b/examples/custom_fit_functions.py
@@ -0,0 +1,50 @@
+#%%
+import scipy.signal as dsp
+from pyrasa.utils.aperiodic_utils import compute_slope
+from pyrasa.utils.fit_funcs import AbstractFitFun
+import numpy as np
+from neurodsp.sim import sim_powerlaw
+from typing import Any
+
+n_secs = 60
+fs=500
+f_range = [1.5, 300]
+exponent = -1.5
+
+sig = sim_powerlaw(n_seconds=n_secs, fs=fs, exponent=exponent)
+
+# test whether recombining periodic and aperiodic spectrum is equivalent to the original spectrum
+freqs, psd = dsp.welch(sig, fs, nperseg=int(4 * fs))
+freq_logical = np.logical_and(freqs >= f_range[0], freqs <= f_range[1])
+psd, freqs = psd[freq_logical], freqs[freq_logical]
+
+
+class CustomFitFun(AbstractFitFun):
+    def func(self, x: np.ndarray, a: float, b: float) -> np.ndarray:
+        """
+        Specparams fixed fitting function.
+        Use this to model aperiodic activity without a spectral knee
+        """
+        y_hat = a + b * x
+
+        return y_hat
+
+    @property
+    def curve_kwargs(self) -> dict[str, Any]:
+        aperiodic_nolog = 10**self.aperiodic_spectrum
+        off_guess = [aperiodic_nolog[0]]
+        exp_guess = [
+            np.abs(np.log10(aperiodic_nolog[0] / aperiodic_nolog[-1]) / np.log10(self.freq[-1] / self.freq[0]))
+        ]
+        return {
+            'maxfev': 10_000,
+            'ftol': 1e-5,
+            'xtol': 1e-5,
+            'gtol': 1e-5,
+            'p0': np.array(off_guess + exp_guess),
+            'bounds': ((-np.inf, -np.inf), (np.inf, np.inf)),
+        }
+
+#%%
+slope_fit = compute_slope(np.log10(psd), np.log10(freqs), fit_func=CustomFitFun)
+# %%
diff --git a/examples/irasa_mne.ipynb b/examples/irasa_mne.ipynb
index e4b2f5e..380c96f 100644
--- a/examples/irasa_mne.ipynb
+++ b/examples/irasa_mne.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -207,10 +207,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "aperiodic_mne, periodic_mne = irasa_raw(raw, band=(.25, 50), \n",
-    "                                duration=2, \n",
-    "                                hset_info=(1.,2.,.05),\n",
-    "                                as_array=False)"
+    "irasa_results = irasa_raw(raw, \n",
+    "                          band=(.25, 50), \n",
+    "                          duration=2, \n",
+    "                          hset_info=(1.,2.,.05))"
    ]
   },
   {
@@ -224,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -241,20 +241,18 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/6x/k2wvgw51691cj5qd77pzcrfw0000gn/T/ipykernel_52883/3776130424.py:4: FutureWarning: The value of `amplitude='auto'` will be removed in MNE 1.8.0, and the new default will be `amplitude=False`.\n",
-      "  raw.compute_psd(method='welch', n_per_seg=nperseg, n_overlap=nperseg//2, fmin=0.25, fmax=50).plot(axes=axes[0])\n",
-      "/var/folders/6x/k2wvgw51691cj5qd77pzcrfw0000gn/T/ipykernel_52883/3776130424.py:5: FutureWarning: The value of `amplitude='auto'` will be removed in MNE 1.8.0, and the new default will be `amplitude=False`.\n",
-      "  aperiodic_mne.plot(axes=axes[1])\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/irasa_mne/mne_objs.py:54: UserWarning: Zero value in PSD for channels MEG 0111, MEG 0121, MEG 0131, MEG 0141, MEG 0211, MEG 0221, MEG 0231, MEG 0241, MEG 0311, MEG 0321, MEG 0331, MEG 0341, MEG 0411, MEG 0421, MEG 0431, MEG 0441, MEG 0511, MEG 0521, MEG 0531, MEG 0541, MEG 0611, MEG 0621, MEG 0631, MEG 0641, MEG 0711, MEG 0721, MEG 0731, MEG 0741, MEG 0811, MEG 0821, MEG 0911, MEG 0921, MEG 0931, MEG 0941, MEG 1011, MEG 1021, MEG 1031, MEG 1041, MEG 1111, MEG 1121, MEG 1131, MEG 1141, MEG 1211, MEG 1221, MEG 1231, MEG 1241, MEG 1311, MEG 1321, MEG 1331, MEG 1341, MEG 1411, MEG 1421, MEG 1431, MEG 1441, MEG 1511, MEG 1521, MEG 1531, MEG 1541, MEG 1611, MEG 1621, MEG 1631, MEG 1641, MEG 1711, MEG 1721, MEG 1731, MEG 1741, MEG 1811, MEG 1821, MEG 1831, MEG 1841, MEG 1911, MEG 1921, MEG 1931, MEG 1941, MEG 2011, MEG 2021, MEG 2031, MEG 2041, MEG 2111, MEG 2121, MEG 2131, MEG 2141, MEG 2211, MEG 2221, MEG 2231, MEG 2241, MEG 2311, MEG 2321, MEG 2331, MEG 2341, MEG 2411, MEG 2421, MEG 2431, MEG 2441, MEG 2511, MEG 2521, MEG 2531, MEG 2541, MEG 2611, MEG 2621, MEG 2631, MEG 2641.\n",
+      "/Users/fabian.schmidt/git/pyrasa/.pixi/envs/default/lib/python3.12/site-packages/mne/viz/utils.py:167: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+      "  (fig or plt).show(**kwargs)\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/irasa_mne/mne_objs.py:64: UserWarning: Zero value in PSD for channels MEG 0111, MEG 0121, MEG 0131, MEG 0141, MEG 0211, MEG 0221, MEG 0231, MEG 0241, MEG 0311, MEG 0321, MEG 0331, MEG 0341, MEG 0411, MEG 0421, MEG 0431, MEG 0441, MEG 0511, MEG 0521, MEG 0531, MEG 0541, MEG 0611, MEG 0621, MEG 0631, MEG 0641, MEG 0711, MEG 0721, MEG 0731, MEG 0741, MEG 0811, MEG 0821, MEG 0911, MEG 0921, MEG 0931, MEG 0941, MEG 1011, MEG 1021, MEG 1031, MEG 1041, MEG 1111, MEG 1121, MEG 1131, MEG 1141, MEG 1211, MEG 1221, MEG 1231, MEG 1241, MEG 1311, MEG 1321, MEG 1331, MEG 1341, MEG 1411, MEG 1421, MEG 1431, MEG 1441, MEG 1511, MEG 1521, MEG 1531, MEG 1541, MEG 1611, MEG 1621, MEG 1631, MEG 1641, MEG 1711, MEG 1721, MEG 1731, MEG 1741, MEG 1811, MEG 1821, MEG 1831, MEG 1841, MEG 1911, MEG 1921, MEG 1931, MEG 1941, MEG 2011, MEG 2021, MEG 2031, MEG 2041, MEG 2111, MEG 2121, MEG 2131, MEG 2141, MEG 2211, MEG 2221, MEG 2231, MEG 2241, MEG 2311, MEG 2321, MEG 2331, MEG 2341, MEG 2411, MEG 2421, MEG 2431, MEG 2441, MEG 2511, MEG 2521, MEG 2531, MEG 2541, MEG 2611, MEG 2621, MEG 2631, MEG 2641.\n",
       "These channels might be dead.\n",
       "  super().plot(\n",
-      "/var/folders/6x/k2wvgw51691cj5qd77pzcrfw0000gn/T/ipykernel_52883/3776130424.py:12: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
+      "/var/folders/6x/k2wvgw51691cj5qd77pzcrfw0000gn/T/ipykernel_37697/1044382114.py:12: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
       "  f.tight_layout()\n"
      ]
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAGGCAYAAADmRxfNAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd7gkR3no/29Vx8kzJ5+zOe9qtco5IQQIkQQG4wQGY5Jt7IuNfc21sbHB2BgHjO2fbaIFGEw0QRICBAhJKIeVtNJqczw5T55OVfX7Y1Z70SVIC0K7K/rzPPOcObO9PW9N1+nptysJY4whlUqlUqlUKpVKpX4K8ngHkEqlUqlUKpVKpU5+aWKRSqVSqVQqlUqlfmppYpFKpVKpVCqVSqV+amlikUqlUqlUKpVKpX5q9vEO4MmK45ipqSna7Tb9/f309PQc75BSqVQqlUqlUqnUESd0i0Wz2eRDH/oQl19+OaVSiZUrV3LKKafQ39/PihUreOMb38i99957vMNMpVKpVCqVSqV+7okTdbrZf/qnf+Kv//qvWblyJVdffTXnnXceS5YsIZPJsLCwwCOPPML3vvc9vvzlL3PBBRfwr//6r6xbt+54h51KpVKpVCqVSv1cOmETi1e+8pW8853vZMuWLT92uzAM+djHPobrurzhDW94mqJLpVKpVCqVSqVS3++ETSxSqVQqlUqlUqnUyeOEHmORSqVSqWe+j3/84wghjj5s22bp0qW87nWvY3x8/Oh2O3bs4Nd//ddZvXo1vu/T19fHWWedxe/+7u9Sr9ePbvcbv/Ebj9tfLpc72q32mmuuIQzD41HMVCqVesY7KRKLK664gne9610/8Pri4iJXXHHFcYgolUqlUk+1a665hjvvvJNvfetbvPGNb+Qzn/kMl156Ka1WiwceeICzzz6bRx99lHe+85184xvf4IMf/CAvetGL+OY3v8nCwsLj9pXJZLjzzju58847uf7663n3u99NLpfjjW98I2effTZjY2PHqZSpVCr1zHVSdIWSUtLb28vFF1/Mpz/9aXK5HADT09OMjIyglDrOEaZSqVTqJ/Xxj3+c173uddx7772cc845R19/5zvfyV/91V/xqU99ihtvvJH/+Z//YXJykkKh8AP7MMYghAC6LRZf/OIXaTabP7DdjTfeyItf/GLOOuss7rrrrp9doVKpVOrn0EnRYgHw7W9/m6mpKS644AIOHjx4vMNJpVKp1M/YBRdcAMChQ4eYn5+nWCySz+d/6LaPJRVP5Morr+SNb3wjd999N7feeutTFmsqlUqlTqLEYnh4mFtuuYXTTjuNc889l5tvvvl4h5RKpVKpn6G9e/cC0N/fz4UXXsjk5CSvetWruOWWW+h0Oj/xfq+++mqANLFIpVKpp9hJsfL2Y3eiPM/j05/+NO95z3u46qqrePvb336cI0ulUqnUU0UpRZIkBEHALbfcwnve8x4KhQJXX3015XKZ++67j8985jN85jOfwbIsTjvtNF74whfy1re+lf7+/if9PitWrABgYmLiZ1WUVCqV+rl0UiQW/+8wkD/7sz9j06ZNvPa1rz1OEaVSqVTqqfZY16fHbNmyhf/4j/9gcHAQgC9/+cvs2LGDb37zm9x3333ccsst/PVf/zUf/OAHuf3229mwYcOTep+TYGhhKpVKnZROisTiwIED9PX1Pe61V7ziFWzYsIH777//OEWVSqVSqafSJz/5STZt2oRt2wwODjI8PPwD22zatIlNmzYB3QThAx/4AG9729v48z//cz7/+c8/qfc5dOgQACMjI09d8KlUKpU6sROLx+Ylr1QqP3R2j+XLl7N8+fKnO6xUKpVK/Qxs2rTpcbNCPREhBH/wB3/Au9/9bh555JEn/f+uvfZaAC6//PJjDTGVSqVSP8YJnViUy+UfO9PHY9MLptPNplKp1DPb5OTkD23BmJiYoF6vc/bZZz+p/XzrW9/iox/9KBdddBGXXHLJUx1mKpVK/Vw7oROL7373u0efG2N44QtfyEc/+lGWLFlyHKNKpVKp1NPtTW96E9VqlVe84hWceuqpWJbFzp07+ad/+ieklD8wmYfW+ug6FWEYcvjwYb7+9a/z+c9/nk2bNj3pblOpVCqVevJO6MTiWc961uN+tyyLCy64gNWrVx+niFKpVCp1PPze7/0en/vc5/jIRz7C+Pg4rVbr6DS0n/zkJ39g4Hen0+HCCy8Euqtw9/f3c/rpp/ORj3yEV73qVbiuezyKkUqlUs9oJ8XK248pFAo89NBDaWKRSqVSqVQqlUqdYE6aBfJSqVQqlUqlUqnUieukSyx+3GDuVCqVSqVSqVQqdXyc0GMsfuEXfuFxiUQQBPzWb/0WuVzucdt96UtferpDS6VSqVQqlUqlUt/nhE4syuXy435/9atffXwCSaVSqVQqlUqlUj/WCZ1YDA0N8bKXvYzzzz//eIeSSqVSqVQqlUqlfowTeozF1NQUL3nJSxgeHuZNb3oTN9xwA2EYHu+wUqlUKpVKpVKp1P/jhJ9u1hjDbbfdxnXXXce1117L+Pg4z3ve87j66qt58YtfTF9f3/EO8QdorZmYmKBQKKSDzVOpVCqVSqVSJy1jDI1Gg5GREaT88W0SJ3xi8f/asWMH1113HV/96le57777OP/887n66qv51V/91RNmRe6xsTGWLVt2vMNIpVKpVCqVSqWeEqOjoyxduvTHbnPSJRbfb3Z2lmuvvZZrr72WSy+9lD/6oz863iEBUKvVKJfLjI6OUiwWj3c4qROM1pqpqSmGhoaeMPNPpdL6kjoWaX1JHYu0vqSejHq9zrJly6hWq5RKpR+77Qk9ePuJ9Pf38/rXv57Xv/71xzuUx3ms+1OxWEwTi9QPSJKEmZkZ1q5di22f1H+CqadBWl9SxyKtL6ljkdaX1LF4Mt37T+j0dOvWrfzJn/wJCwsLAPzZn/3ZcY7oGBmDmt9G/Mj/h5q+63hHkzpB2LbNZZddlp7EU09KWl9SxyKtL6ljkdaX1FPthE4s3vjGN5LP53n5y19OtVrlpptuOt4hPWnPOrWA3PthTHsSe8PrMO0JkgNfwhh9vENLHWdaaw4dOoTWaV1IPbG0vqSORVpfUscirS+pp9oJnVi4rss73vEO/uEf/oE3vOENnEzDQco5G73mddjLno9wctirXo7ILSHZ8RFM0jne4aWOI6014+Pj6Yk89aSk9SV1LNL6kjoWaX1JPdVO6MHbV155JTfeeCMAH/vYx/jt3/5toig6zlE9sXq9TqlUorY4R752G2biO4jSesSGNx1pufgK9ppfQuZGjneoqVQqlUo9ZeZaCb1ZK51qPZV6Bjl6XVurPeHY4RO6U53jODQaDQqFAq9//evp7e093iE9aS88TeA8/C5Y/RLk+f8Ec/eh73sHctNv42x4Hcm+z2BK65Ejz05PwD9nlFIcOHCAVatWYVnW8Q4ndYJL60vqWBzP+nLnWJ3rDy+yvpDj1Zt7sWT63XaiS88vJydjDO9vfZnrktsZzrqU8RmUgrJyGDQdpMrRH7YomCYCmzWF11BxT31aYjuhu0J94xvfoNP5v92GXvaylx2/YI6RNhBv+UvkkuchpIUYOB95xp+i934SM/kdrI1vAmGR7PgQJqwe73BTTyNjDIuLiydV177U8ZPWl9SxOF71Za4Vcf3hRXwr4OFolvffO0UzVE9rDKljl55fTj7GGP5h4Vo+F9yGCcvMza3Biiqo2kq+/n++w3Xv24MOlzIjNtLuLKU0HzN/6KOEzX1PS3wndFcoKSVTU1MMDAwc71COyWNNRuNzEzw8/g32Td/KszOb2Xj2G8EvYg5fi5m9B7nxtzDSQe37PHLwQmT/OWnrRSqVSqVOKok2/O1d47TtOu5D86xas4Lt5SbZoMBrTxlgVdk73iGmUs8Ii1Gdj85+hw81b6KcWYGJerEDifOlm7n//f9DUGsAUBno49ff/jr+1xUdPNkdPyMM9I+8FqfnNITlH9P7HktXqBM+sZienqa/v/94h3JM6vU6p/zh6bzjly7nomKFvuxKtrYe5YxwkKVDl8K6yyGcR+/4D0RxLaz8RfTkzZjmYezVv4jweo53EVI/Q0op9uzZw7p169Km59QTSutL6lgcj/rywfun2WcWqNw6w5LZhGrQxLlyPbN9gijO8OfnLsV30rp7IkrPLye+++bu4xujX2c87vDpiVtwyuvRcZZVq84m2DHO6O99hObhMfL9fWw67yx0s8P+7TtYnJ3ltA2r+eg7f5PVPfNkOnci0CB9nN5TEH4fctObEbkfv5I2PIPGWACsX7/+Ce/iP7bOxYnks5efzSn9Z1Nc84uMuRbnhG1u3fGPPKtxH323PIS17grEGe+E6Vsx9/851obXY3rPINnzGWTPqcjhy9LWi2ew7+/il0o9kbS+pI7F01lfbj5Q44BqUBmNGJpo4+x9CGuwgHWjxD2/n3C15Et75vm1U06ungc/T9Lzy4ntkusuBiSitAUhKuhaBjB0Dkyy5zV/R2FgGb/yua+x4awh1tcd7LkyK5li16Nb+T/v/Qte/kf/zu3vW08mr0HH2NWHMPN3gpCoPR/H/tXRpzTeE77F4gMf+MATLh/+2te+9mmK6Mmp1+s8++Vn8epr/om52l627N5DT98GNmx+ITcc/C9+0fYpqWGseg255lLM4Dp49P+DwkpY9cuYqdvQ8w92E4yB8xFO/ngXKZVKpVKpxwljxV/dO4YbBCz91hhJcwcHX3aAwfuGydy7iFxzKaNn92CWDvLui1Yc73BTqZOSd42LMhaWdRrCWYGV7UUIQfKub2Hm6lz1gZuo9OVYOVhj6YMrKMYRGwe74ynqu7fzkj9+Ky+9IM8H37ASezFEqDbGmwK7m1Davxk/YQzPqBaLX/mVXznpxlgAzP/SIM7dn+eF7YReVzH90COYhRov7t/E/2Sm+KV8iG27ZOZ2I/feilj/YtDjmK3vRG5+K3LoYvTCIyR7Pg2Wh+zZgnCLYOe6iYaTQ4i02fJkpJRix44dbNq0KW16Tj2htL6kjsXTWV++tnuRyApZcWcNMT/N/ufuRb1vgv3PatD/4qUs+/JNLLOuZO/SfuJE4dhp/T3RpOeXE5/pGEzgEusYpycPWYHaXyN8YC8r3vz3eIUK7ZaA+1egWj59Vnechd9pssoyvP055/HnX7uZv3/2UnqyLuAi4iLY2zHeEycVx+qEnhXqZO4K9N7dFs8u2Hirh2gU1xOfdwZjE9voufu7XP3wHI/smEZkl9HMVgl7e9ATWxET04jVr0Y//I+YQ19F5pbgnPJm7JVXg47QjYPombtJDl1Lsv2DxLs/iV7cka7mnUqlUqmn3SO1FoXJBDE6xuGLHyL84ihO5RSGPrXA3L372PPrEhkvQBJy48Ha8Q43lTopxZMJerGOqe0knk5Qs4rwb74GQqAz51Ofiig/2EthPoenFYz5BONFnChEzGte1H8FiYarP7obEYOIQBiJrGaxxp/6TksnbIvFQw89dFJPf6Y3Z+lUB7AenUW1svS5eernlbh5YpErGmU27pjmwalJzl1zLmFPFZUp4CY+9kNfRyx/EWRszJ6Po8NFRO/pyOIaTBRDvAjtaYyOEV4JPbcVM/YtRH4p1sjl6cDvk4BlWZx66tMzn3Tq5JfWl9SxeLrqizaGAMOqe6dprdzJ9IHDOK11mJzLwatewsq7b2Jx/BB7XqMoHV7OfU6GF61Nv59ONOn55SShfGisg8VHCceAuRoIiZyNqN4QYdQCtazNs071YBYaOysIBVpmcE33Jv3dh5qI0e6NaJMBsiHiZ3CZfcK2WJx11llHp5pdvXo18/PzxzukYzJyz1kk1w3BQ5dwcPFUJnorLL1+C255BZ/ZEpM/5xJODW323XET7n2HkItNgniKuDiIWjyA2XkvwqxGLHsV5FdhmocRThEGL4N1v4lY/2ZEcTUymkN2xhHVnSS7P02851OYzvTxLn7qx1BK8cADD6BUOsd76oml9SV1LJ6u+nLngTraxBBPsat/J6VrM+RX9fK8N7W4Wkxw+IyLKTirUN9bJDO5j8AY9El8s/CZKj2/nAQM0BhAaAEGrGr5yOuaSj1PLsojQoU9FjF6Q4Px7TGN2Q75cIFicJiFmQMAeNb39QJqJZime2TnT60TNrEol8scOND9MA4ePIjWT313n/e+970IIfj93//9o68ZY/jLv/xLRkZGyGQyXH755Wzfvv2Y9926ZyV7D5S5rSmZ1Ivsv285t18VsfE7Kznz4Qz3OfvovPYPKL7itTwYzmN9ZyuZRY+ASXRbkxT6SDIFmDsAu+6F0UnM3m3w8I2I7V9HPPp1zK6tiHYPov9liMFnITtjSNUhOXQ98c6PoiZuQTcOYvRT34cu9dPJZDLHO4TUSSStL6lj8XTUl9sm62TnQnaedivlT0QsnH8Glz93ml2PrCX7wpBfXFen5ZeZml1CtXc/Wod8b7T+M48rdezS88uJzRoFe+EwsroNdypHtnk+ztAZAEQTD6IOjRIcPkRpscqyDjQ6homGT7XaJFzo8O1DDwDwW+v6CScgmqmjqw9jpqqo2ac+3hO2K9QrXvEKLrvsMkZGRhBCcM455/zIgUX79+8/5v3fe++9fPjDH+a000573Ot/93d/x/vf/34+/vGPs379et7znvfwvOc9j127dlEoFJ70/rf+To2wY1Gb8jiQWcGWym6e++Vb+d5pSzhn+hTUTJ2Z1sfJj2xi+W++j/+6/d95yd130Ns3TOvyXryOwDo4iiLA9A9hrTgL4eYQThaERDTGEeVVmKiJmN0LY9sx0SpELJHtHYglz8c4efTCdszoN0EncHTMypGfbgHh9SDcMsLvQWSGwC2d1GNbTgaWZbFx48bjHUbqJJHWl9SxeDrqizGGptEUdj/KbGOB1vAZvOSig9y5bS237xyi954yv/Ere7hqGL50ncW8aDM00eRWu8azlv/4WR5TT6/0/HLis5REoxHGIFQFjKR3zctYaDcY3fHP9C3/R5aEGVaUHIwxCCHwkxo99VGm4w4fGr2Xq3qH+ZvVSzAhmLAI7hLs7Bg0nvp4T9jE4sMf/jAvf/nL2bt3L//rf/0v3vjGNx7Thf2P02w2edWrXsVHPvIR3vOe9xx93RjDBz7wAd7xjnfw8pe/HIBPfOITDA4O8t///d+8+c1vftLvYd32bCZGIspBm0sfUTxw6WY+tjzPm26/AeU8woApYh9ezfwlu0hq+/m1Tb/CPesmyH71o2z6n3nE+efSWurjVc7Bnqph7rkR055F1MYg7mCkjxAx5LOIZacgV12MrKyG/bdh2ouYQ7eBqSIcF5lfCuVNCL8P3BK4ZYyTRyQBJlrEhIuY1jhq9n4IqyAEIjOAyC3tPrJDCHnCVpWjjDEQhhBFEEdHfsbdn4+9FobQbmHabVAKjAEpEPkClCtQ6YGlyxA/w9kxkiThgQce4Mwzz8S2T/zPNXV8pfUldSyejvqyY7JJLBKqeivhzmEuuqLOaLvE1u1LeRcf5sbBK/m3T5/Ca158mOe9sMp/78qyrnSAyaW9Ry98UieG9Pxy4tOPTdAjAJpkpnZgBW16l13J1PaPsOvAn7Ku8udoLw9eFj9YYGPtdmYyi/yvgx+moTv8/SnfP92zQMclYOxnEu8JXYuuuuoqAO6//37e+ta3PmWJxVve8hZe9KIX8dznPvdxicWBAweYmpriyiuvPPqa53k861nP4o477jimxKI59CCbpc+jTpVb/HtYtm8Ls2cP8lcX/xqv3b2dnTlBb+d2rvj6JFapxfiLp9nMObiv/Rdu/877WL71uwzcl8dz7yHss7A8CYkPpoI0ZcBHxhox00BPPIC5716o5JFX/DZiw3MR0zuhOoqpTWJmpmHsBowJAAUiBhNipAXlDYjhS2HoYhynu8S7MRrTmcG0xtCz92E6U6AVeCVkcS2ytA7h9z4lx+InpbWGQ/vg0F6YnYFarZtwCQOW6CYGtoVxPbRbQekCSc1C1TR4Hla2iOVopG+whosI10YoA1NT8MD90NsLm7cgep76cgohqFQq6Zdr6klJ60vqWHx/fdGRQjjyKa873zlYx+3ELJRnGD5/NbY3w3XXX8TvRV9g657ncdkZ02zoPch/fv1SXv0cRUG0qBb3oM1pPDjd4MyhHz8Pfurpk55fTg6C7n3Q3OwB3KCCMYKhxT4Kpeeyv34zn5p6DZsWLmT94OX0Nw/xpfAhvhs8RF76/NeK81juNI8m9cYYdBwSNQVub/Ypj/WETiwec8011zxl+/rsZz/L1q1buffee3/g36ampgAYHBx83OuDg4McOnToR+4zDEPCMDz6e71e5+DBXdymZ0myisvOv5BH79pBcPciuWcb/mnlqbw5WKA6egl/+LwqF+8KePHXJ2md9w0aN+7n0oFXELxgAw+O3c743jtZO9NgWdthrpJhYdChOLUbL2rSW+4hKypk1FqcjgNj+1DXvAuWLEFsfi66NIS9chNkCygvh+06mLCDClvYKHRzHjO7FfZ8CXP/36GNQHgD4AxinAGkkwXLA6eE5eVRiYWuTaGru9BRDWHnsIor0dlliNwybDdDkiQIIbAsiyRJkFIipTz6XABq9CBy1zaYGkMnASKJEXGEiUKwHURPBTU4gFy6HGwHHYbIJIYwQo8fRk5MQaeDyTiIsgt5B7PcReT7wXNJ4jp6OqbzsEYsVLEZx7ITLB+crAO4GOVjrAyq6hAe9rCyJWRPDktFiEiAEyPuvAOpEvT6jYg1a7Ec54eW6f99HscxlmUdfW7bNkKIo8+llKxYsQIpJcYYkiTBcZzHPddao5Q6+lxrjW3bP/K5UgpjzNHn0G3i/lHPn+g4HWuZoHvn6/ufp2V66sq0du1akiRBa/2MKdMz8TidCGUSQrBy5UqIDbO37kLms/SctRQc+ZSVaUEp/If3E+sC63oX+Mz1F/HLzh2MHtrAoU0BndFeVlQFf7r8q3zmkSvZvP4R9nsRPbMtvmHXOGOw8HN/nE6kMq1du5Y4jpFSPmPK9Ew6Tr97yVv40A3/hkzAb3ST8kKrgpNkKHvLuaL0O0y3HmR/dA8Pjn4bgGFR4ldLF/LaQi+rsgdpLkCxP8ZyXIxqE7cPEbfB+btvHf1sflyZjmVw/wk7ePtnYXR0lLe+9a186lOfwvf9H7nd/5u5P1HT7Xvf+15KpdLRx7JlyziwrMPARSsZ3uxx4O7PcOYLn02x47H2wY0YeRPvqGpaZ/Tzm/f3MGkX+LMlMYceHMAee4CJhU/R+uCnOOfbC1zw8BJG+q6iNryZzJ33cPpN97FxbCXeI0uY2V/intFZbpy5hR2ZWxlbk7Answkx3oavfJzg839P8q2PEN7yGSY+/370TZ8m+O7nGL3+v9D7H6E+Oc2D4xnEOX/B9Fkf5M6eP0Be+EfMlVYyVt+Ndg9Trd7B9OGb0DOPsLjtHma37sI63KT+6ByLjx6E0e3M3fExFm/+M6L73svUt/8Pc7f/Pcne/2H3dz/EzN2fQd/9BSb/8z0EH/xL9L/8Ka3Pf4Bw/EFMIWLCNOmsXgbPejb3LllDcMnlMLKU6W0Po2/8NuaGG6h/+cuYO+5AP7CVsUOH4LJLab/8ldzRtxRx9qW0C3kmD20neegB2l+8m+bH9pPcPI2MJogqU1gb+2mvXcrB7AAPbh/gths8bvovwU0fUnz739s8ev089e37CXc8QOvALuJKlgOdJjOHF1HzCZM33ULtvz6OeWQb9955J6OjowDccccdTE5OAnDrrbcyNzcHwE033US1WgXgxhtvpNHodmK84YYbCIKAIAh+4DlAo9HgxhtvBKBarXLTTTcBMDc3x6233grA5OQkd9xxx9H6fM899wDd1rYHHugO0Nqz9VEe+dpdBA9Ps+MLd7D9P28l3L/Itm3b2LNnDwAPPPDA0ckR7rnnnp+6TEmScMMNN5Akyc+mTHv2sG3bNgB27NjBjh07AH4uyrRv3z7uuOMO7r777mdMmZ6Jx+lEKdP4+Djf/MY3mbtjD+OHv0dj963M376bA/fvfkrKdOMt9xMJRW32JgYzBR56sJ/LiyGZ8SoTq32yfUtZXBuzXcXs3nY+qx74Dv29HjMHs/QcGKWhFJ1O5+f+OJ0oZapWq9xxxx3PqDI9046Tmo7JLEjcugAUQhnyTXl0SQZjCZ5rXcHbxCv5B/mrfMJ9A//o/jK/aly84CBaG4L2LPXZR+ks3k/U3AkmBmOYCO0nVaZdu3bxZAlzMi8WcYy+8pWv8Au/8AuPGwSulEIIgZSSXbt2sXbtWrZu3cqZZ555dJuXvvSllMtlPvGJT/zQ/f6wFostv3EaL3nWcxnOD7F6YBUHvnA/4eW/yNTDezj7XJsDC9/lxoULuag9ze8Venh0os29q8Y4o13hop5ZOEXiTHYo7KzjRgbsLLHoRQkXsxAi52OE52Dnc9iFDNpVVJ0ZonUhjb4hljQ30ledw6qPQhhgbAcyWUy5gOkpQqmEyfVgohAZBRB0ugmUNtCKEW2FCDVogbEF5AWYOgTToDRQAtmHkIXuwHCjEFqhtUKYGHSMUUm3+S4jMR7gAUIhOk1AQSGPNhoZJ4gjd2OFADJZdDEP5TJYFiaOkUoTRyFxrY5TbyLbChM6iCCPCi2MbCC9SYTdQbgCbB8hbHRbMnvIcGhHL4aEJcsO4zsRdsfBarmYtsNCu8RMvUIQZaiUIlZvtHFG8ljLCrhnbES3C5gD49hLejCdGnJwCLFhI6pcQR65o3Asd0+01hw6dOhoq8VTcfckSRLC3XNM/cc2mvfsxFVz2KaFJEASEiuIB1az7K9fRfHcFekdoZOoTMYYJiYmGB4ePtridbKX6Zl4nE6UMiVJwuFbH6W6/x6izs08Qsyp7kWsGTkLMbSC3rOWoo9MMfmTlOljt42zX7WpPvQXnDKynsPXXcDzax9nZ/+ZHNg7yAvqt7OzeDHhJRFTW5us3B2gf6fEA/UGq4Zs6qe+jLdsGmG44PxcH6cTpUxSSsbGxhgaGsJ13WdEmZ5px+nwxEEu/82zCeZq5Kp5lL2a/nkPxCbABgPnN1x6wq1UrAr91hKEEKzIbcMSEdnMLLYcw/Wg0gfQvYFun38l2b+//nHl+FFlqtfr9PT0UKvVKBZ/fFfGn6vEotFo/ECXpte97nVs3LiRt7/97WzevJmRkRH+4A/+gD/+4z8GIIoiBgYGeN/73vekx1jU63UGzyjx1U9+jedc+Hwsy+KPV22i501v5WC7QDRdRVzVg22+zn33LCdptHnn3GEqfefwcH2C2vAiazIrGRnIkVnVIjERelSTbWh8E9IYlMz25fEOWAzv0RQaCV4nwsmU8TItomQfjY1ZmgMFOoGLM+lQOqRwgw6uE2K7GscVWK7CKWaw+kagfxVowCSQdTG2gnABszgD7QY66kASHZlPyoDVAnsBnCaYIiQrwQyDsAAbYTvd9rB2FREHGCzwK5jMAGR6QXb/GDAGMj6mUkR4BmOFmGABUxslmhojDkK0MkglkFqCzmGSLDoWSDWGZe8HbxHV8dFNBxkLhJLIlmRhssyewyvJOAH9pTqt2GG+Y5F4mmx/nfxglWyxiYlzBHMrSSaHUbWExbZk/bJRhvpbyL4icmkJa3URKQfRix5y/Wqko6G6gBgagRUroX8AYT/9PQuNNsx//E7m/vN2vOAwmVxAbIfEGIRtY4SFNjaObfCMRtUbLM4fpvTy57L03X/xMx2knkqlnn6tw4tM3norexc/S29rGWVRo+23ucsa4GWVS8medz6FdcM/8f7/5ubDRPsOUxefYDBYTeW7dXpWZfn2zUv4JX0Ley9+HssP7mF2ZgkLLxGM3VQj15+jeNkUo/mYwuCrWDbQwxvP+MljSKV+3oxOHeKP//g3eOi272G0TU99Kdl4GpvLEBjWtabImzZZiqx2N4NwGfBuJ1E7AINrw2ARPL/7qLz5/5B9wzsR3o/uvfP96vU6pVIpTSyejMsvv5wzzjiDD3zgAwC8733v473vfS/XXHMN69at42/+5m+4+eabj2m62R92AG7+wD9zy7s+jvPhf2PXzffjNNvEz12PGP4O924tkSyWOH10G2+RZWacFYzH++lYc+StDKvyefrLLRQNMMvIjweYvIVYB3pEoqZj5CMRmdkGnlCw5Fn0tBewWofRuYjOqh6aq0sExQyJFJgkRkcRtDvY7Q52HGPpBBA42sYNPNxOBtPyEA0XUXcglAghwZLdaWsFIDSgEe4csucAsjCDtjPE1jLi7FJMj0cyVEHks9iWxJLySDIhukvKhxrRrCGCAB0okraNmrOQVRcrspHGQipQQIwmdqbxs4/gu/sQIiaKC8TaJaCX2WQ1ZsonO9PBalocmnSoUyEYHCGQNrZv4Q9U8As2mDaNTkC1HhDUW5hglpVLdrJ6YD+5vGAx2MDUV/pxlc+mlXX6SxN4hQ7W8hzWCg8hHEwti+hfinXKRhAeLCyAUohSGYaGu49i8Yd2oUuShDvuuIOLLrro6B0UAJNEMDOKmRmDxiJU5zGNGgQdhONDtgz5HnS2DOPjhHc+SLIwi2UHCDuiEypmFyskKHKVWdxcG78Q4udjGjM9TOxajS9tBooJshMysfdmCr/ySpb9yd9ged5P/keU+pn6UfUl9X/tqC9gScG6XPmkGYR60/Y6Y/WEF20p0pt/ao5rVO0w8537+Mr0v3Nx7RT+ct8c/W6Zl4xEnOtP8TU/5oria1nzmuf9RPufr4f884OT1K79/1h6JszcuZErevfz5S+t5kXeLVx37jJO22wxPp/nikM5atsT9q1SJIcNa94acP1ezZZ1FxMuXcNfXrTyKSlz6qeTnl9OHjd+/X9462+/EgwsXRBIYyhHm8npRXJ6AgDL2Jxrn44QRXqcmxHft7R2KQPlvEBkc6y7ZwKZyz/p937GJRbz8/P09nZn5xkdHeUjH/kInU6Hq6++mksvvfSn2vf/m1gYY3jXu97Fhz70IRYXFzn//PP5t3/7t2Na8v6HHYCw1eLdS84gv/xZqPf8MQduvY1wzw5yzzmLcMXdHKpXOfTIZgasiPP27uIFicfaYBY7aZPYGRK7B53pJRxYjaruQ8zvwXJ8hF/ELO9BnJWDgoZvj5PbtpOk3EN7eAPGz1MK5qk0RrGjFiBQdpbQGaSRW0Pol9BCII50Q1rMzLGQnWausIiTiVltS1YID1fk0CZLEpdRjTKm5aDqAmoKW8UIGdERTSwaZLKHyWQmsHSEaZTRi73odgWkjZAGIcAI3a3wloewM2BniJ0cnUyWuZzgoK2Ys2JG5BQrzRR5E5GoAdoMYWGhVYNmNUQu1BEdj0SUCLwhGnYv1PJoJ2YqVsy1NIGJCZIWUTRL5DZp+kV0voyVq+D7Bfotn0oi8AOwagEVMcnyJQ/hRXOM3buMYiWg3y4xIBrks9PYPeCMWMiSAGVhYguyGcRABTk0jHAqEEiIANtG9A9AXx/09UOhiDGGyclJhvr7EPU5GN2J2b2tm5y0Q4zp/j88B211gEVMUEVEdUzUwagYkwhQEh0Lpsb6OXxwOblCyMBqRS1ewWKjTLMlaYeClorJ+mOsHdjNQGGRufF+krDEppVVwuoYs/seopHfhHXqRWQ3nkp+/XqcXJ7O3By1gwdZ2LuX9thBiGoI1USqFsgYrCImM4g7uJry6jX0n3oqlfXryY2MINOWkKeM1prJyUmGh4ePDq5MddXjiD+6fyt3HYwRAnJ+wvNXlPntjesZ8HPHO7wf6dvb69xTXSCxA/w4x/JMjhdtLlLwf/ILO2MM0zc+zBcOfpDnN3r5wJTmuVcpOnMdvnyT4eKB1by8sIOp3BBnvuZPcItP7k7l9/vs96Z4iAbV297Bqes2cPj6UxAPL9BnP8yD62LeesFaVu8KebgS8lXX50Uz6xjbMccobXpfWOD+RoOVS7J0NryEv7lk1U9c1tRTJz2/nDyMMXzk3/+WT3/i/yPzaHdchq18VoYBR2+nGFgiC6yQS+jxdv7f/ywE+azF0LqlDP39f5K78PJjeu9nTGLx8MMP85KXvITR0VHWrVvHZz/7Wa666iparRZSSlqtFl/84hd52ctedrxDfZwfdQD+5bzLaO+Maf3iW/CvvpCZXTuY/O7XWHXqZpoXNRh3HmDbV3qobNhI2RK0VYyvFMu1xbBVRLbHWLvzdsbPXMPE5rXUDwiCWoPB1iynzc2wSSd4V1+Ik83h3XqI3PYd0FbEukToZMAC4Vi4riYjG+T0PJZIiP2lRIVTMU4RKbvTzYKipRuMWhPMiTlycUhJgWOFuDmDk3XQxSydkk/k2cRCknQkccOQNA1RQ6MSBfkqBb/KgN3GVxZJlCMJCqh2AdXKYxmDECHGlhjXQTo5bHsAY0pgQtpJyEKYJehoWknAvHFQ2kEIj3auh4aToWVCtG7gWTbSs4iLCZansAmRTkRTeyy089SDPEnDxo8jMlGHTLuGCKCR6aeZLZAUXKQvcAwUtMtQ6DGkLIbnIrJqhiVLH6BkHaJQreLH4CjouAWswQKVTISjIoQRGMvD2D44EhyBsV2MFt2xUrEBo7FUiOTILAvCRpFHGRttzyPtcaCJiBWmaWGqCWpaQFMihEElNkGjyeFpi0Odc4iG+2kv66HZdmlPN4ixULaPkQ4YEHGCNCX8jE8j9wjNzlZWE3JatIz1p9TpK9eIxZ3EaoZYQaAsAiT6sVODFAghUInEKIlRFkZJlFRIR2M5oI1BG0iQBJFFLDI42TzZvgr5gX6KwwP0rD0FN99/ZC2VEsItg98Hfh/CSltMUk+eMYYvje/n7+8fg8CmOdFAKkH/YIGmZ+johKvWFPi7c8863qH+gG8/WueO6jxhJ2RoPsv4cBuZ0eTDAuf2FXnehp9sAblgtskdX/kvhjr7uHZmOf0XT5C5yacyWMI+Y5EvfGuWQriS31hyiJELfpfeS0855vf4h++MMjM/jS/+FTV+GkMHytxz4wHkhu38xa+9lNJdBznQI1jdmudg2+OTfZIN380w7uZwevLkLp1isqhwV/wm77lwJZaVXsimUj+Jv/3NV3HzFz6LIyQrm4+fsakEDAHLPPAsul2eleKs/7me/ue/8Cd6v2dMYvGCF7wA27Z5+9vfzqc+9Smuv/56rrzySj760Y8C8Hu/93vcf//93HXXXcc50sf7UQfgvo9/nOt//+/JWGdSffUvk7t8M/WpKQ5eew1nZZZz8HeX0LLu4p5rDuGJ5VRWLKW4doCmcTHjbWiHNEs5/PkYpxGj/QwegkwnobzQpNJssnHhbtyVJXIvO59sxcHSMf74HIVD41jaxs4vRdt9iNBgVWcQURPHaZJhHuM7hKVewlwvoZshdixCxyNyXELPJdQG2jambSM64CYBfWFARQdYukViS6JcgTjvI/IaXI0RgjDyCed7ac33EtUFcRyhtSLSEQBSCISJEKZNEIXUopBIxsTZiAWvRd2RtL0BfBts2yIRJXJJwrLONEXP4DpZ7DqEEy7hVJ1afYJ9fSVm9FJMp4LfCsmaKXL5Ucp9NeIwQ21R0Wi0CMNphD+Ob83ixXlEsppecQ6qMsiYrDJZ8dArRujv9LBitpd+K08pL5H2Im6ynR5uZSAzTr/dRhqfR+1BDnkDnC4jVqkIX5ZwKJIkBVoUaYocTeUTtQR2PIdvtlPKHMRzQYe9mOYQutWDTAyW7GCJEAxoPMJmRKs2xkynn0n3HMJKkTinuwPuE01sCWKrRts6TDDcwSyxMCMC2Qeu8Un2Cxa2JkQ7JYUkxq7u5QxtsaI4wJbTGwhhqAYzOJ2HoVPHchws2wZkt/ebBOSRWdMEmChBxxqluolFogURENqSUCmCICYIY0JjaAlFjYSOJymWMgyPlBleOUjfUIVCKYOXy4PlglEYFdMO23TCNlGiiRJFnCRoJLbfi8iO4GRH8PLL8CsjZHqW4hYGEU7u6BzdkYoIkgBb2DjCxiiNShIy+fyP7CpjjIGkCZ1p6ExjOtMQzEFUx8R1OLpIkXUkKeoBrxfh9YDXfY5X6f77D3mPx061x9pVJ0kSbr31Vi677LK0qwIwE7Z56/1b2TFmyJsOh8cniOybkUZjVfrIRhvJtFYTlF3+64UbObd/4HiHfNQ3d9T4Xm0Ot6455UEfs3oOuXeQ9grJ3uEGYUZyWV+FF67pOeZ97/raHUwf/DQTtUuZPOUe4gf7mDwcUCtWeE68yJKXlLnn8GF6Dw5xycpVrH/DLyHkk6+LC/WQf31givFvfZzTLpjn4VsuoO+eMR7lNj74rt/HvvYeHmx1uE9dTG15yFuCb9Co+vxtMMeGydMxoWbFmwNuGINl57yAl6xay8XpKtzHXXp+ST0Zz5jEoq+vj5tuuonTTjuNZrNJsVjknnvu4ZxzzgFg586dXHDBBUen5DpR/KgDEDab/MOmC3Dr/Sx7+eu4v7eP0kUbaVXr7P3ONWxczLB2zRDfe/0cD92+A/2AR8/UPPmoQcUZwV+wwfao9y0jKQ4y4q5kuDSILigWRMR4XGU86pC0qhQXDlKszuF3EspDPj0jkoyTkCMipwN8mdDO5ZgtVzA2uFphBRGmHUEnIIkVSZIB0YtjVfCtErbvYBdC7EKElY3RImFxIWHscMT0pKITSqJiBlMsQrGC7RQQooTAQVkx2m3iehGWnYBOUIGNMQ5G2oANUuLbFr5l4wtJzkj8xKYniaiEMVbskQ0NVmuBoNFmYUFTP2TRqGviwiw1P0tT9GLnPUpunWJ+GqsQYglNJrHJKA/L+CQqAjFPplRHuhFz45rpcQ8RNPDVLqb0AaYybQrxCAPx2fRNLSEsGWbOK7HoLSdXhXy7h1KhRLmUx7ZsWlGLajhGM96BtEdxbI0xPpYu4lMmZ5XIyCKuXcS3MniWASOIlE2sJU7SIRs3qMSLlON5jJFEOLQjl3aomdMRcyZm3k2o5toEVot2fZZOu4GIIvxKhLk8T3J+kVKxgD4gUbsEYl8GSR+qkGCtXaR/aZZyqYiek+y69iDz0/dRrltsVD0MiSynDdlsGLJBakISFAqNxhiD0aCMQWtDog2zYYtHwjnuFxN4mZARVzKoJKV2jB1rojChrRVNDDUJxkhsJZCAdKAjNHU0zVDSTI60kqDQQncTGAmJDUqCsgxYYNsG3zFkbNF9CEHOluRtie9IIgRtrQkMhNp0ZzrDdN8TQ4+ULHUdRtws+XyJfKlMrlgmXyqTL5TQ0qUeKhY7irlmQL0ZENcj4vkGplrDDUKylofvS3xf4HngOeC6GsdReK7BcW1c38XxHBzXxrYtpCUQlkBgwMmCX0Tkl0BpLaK4GgqrITvyQ5MOrTVzc3P09fX9XHdVMMbw5YmD/MODo7SbCfXFvVSj72HCPVzuuGzKOjyaVFkMbXKql2rhlbQKy7n/V56NfQJ8bt/YWeXm2jz905JVO2zueN4u1GyZ0kCLM24foqMLNIYV+5YmbB7M8JrVQ09630kn4puf+BCZ9jruWvpNmocH6bn9AHgSs7aPPfNZliUdzro8yz3TdV4ha6x95V+TXVJ+0u/xhe9MstVtUfv2n7J58xr23HUp2276Iq8/bQmXhxlm3Rm+tPx8nr16G7UdV/CNAc2bWrewbdd+9k6uJVfIU3punnuTgKH1y+gbvJg/PH/pT/BJpp5K6fkl9WQ8YxILKSVTU1MMDHTvOBUKBR566CFWr14NwPT0NCMjI8e0cMfT4ccdgE8+/wWMbp8nE69g5MWv5N7+MpWz16H2hOyaux4Wp3mlu4726kMEy0N0w0Pt9piPfNobS+hVNnYfaN2kXWswO9aiOWFTDNYxVFrDIAMUYodF2ix05lhsjhNEMySxIAx84o5DLmziiza97XlKjTmUhkQLPOHSU1pOqbQUP1tAWB2kPYvtTmJZY2T0PNKyaXkV5t0RJsUy5tx+vCFNqb9FKRPgNQXWIQt3R4AarZEP5ygWyyTlVYT+MLGySYxD29EEmRipIpwoxooToqTJfLXB2FSVmponcBcI7EVCAVpW0CKPdJZQLq6kJ1+kN2fh2glJYrqL2ukmsTjMYnsnXthCDxaorhymnsQ0O21ajRqWY2PhkY0yyI7BhIa8W6Do++SzDr62ySQ+4XRMe3SUdnMPsxxEWBGVxXUMq424KyrMDJdp+nmWzCuGGwl4HVq9Hirfh7TyKB0jk4QMIYomi/Eks/EE1WCaalBHBR52kidDjqzwMFiEbpHAyaNkDmEEUsXY8Qx2PI8tEtz8APnZIvnxBBmFxD0BixcsIX5+gczSRaKJDvXb5lGlBLm2F1OqkGiLqNZB6QQhMyCyEEsKJVg3FDNyYCnR9TaTi1+k01hAiA7K0wR2iCUUjlBYUuEIjWMkLhaOsXCERSVv0Zt36fF8LARaGyIT05QRdS8CDxzLwjeCTAJJo0Z1ZpKgtnikFQPaEtqOJJQSISU5bZPRFr6xyWiBpwyeUnjKYGtD7BpCB+o2tC3o2BBahlBqhFD4QpBFkBWSDBbGAWMdmTMACKRhHMWEULSMQScakxhEBITd+QjMkdYZIUAKyCEoCoucEeS1oBBDKRYUY4GXCGRiQJvuG2iNMAqpNdIoDCCs7mrwxhJoG+KMhyllGBjqZd2KHvqXFrHKBax8DrK94BURVhbsDNhHflpZsLMIO9vtPpZfibCPvY/8yaoahfzhQw9w38GAdrydhckHiOT9LFF9/I6ymGy9iIWGYlnvAbYsGWNpT0RVtfiL6ptYvWoJn3z2TzcW76e1v9rmw4/OsHJCMrDf4p5THqDwtg+hOw3cnj7UVS+n/6zN9E72M7+xzcGSS6ai+K3VS1iIY/a1OxwOOzQThSslJceix7Hpcx3yluDrt9zCWWMB9+V3MFXzOO1r21lcPgIXnEXmjgeILcE+4yPzRVZePMP523tYuelZDP3CBU+6DP/yzTH2UWOo8/csjp2HvkXx4L77+c/V69HrH+FrmVM52JqhYSRnFA0r5q/iq6fEvPy2L/Hl8Ra98hzcgTzW5dPU80XcJS/nry5Z+bP70FOp1FPmGZVYTE9P09/fD3QTi23btrFqVXfQ18mYWGz95Cf55rs/xMj6pSxu9yhc+EK2r+mnvGU5zjSMbfse48kuVr/kpYhCL0Y0oTCJdNuYeh51MCE7HZH0r6KVjYFZvNohrOI0tWrI2EOaXDJEnhW4qpeyVaIvk0f4TWLnME17hqmcSz1noe0MbiDx6hFWo0lbaBZFQlMIEiOOdOmQCCM4Mg0UYBCANAYrCsjWZskuTmG36yQa7EKBkVVFRlbnqPRZBJFg9JBk317DxERMbCK06N5JjqwOsYzRMkagyRiPvHEoaAdfZ8hQRqsMKla4qkmQy+BaIT3hDIEpEKkMZdVkpHcGf/0kztp+/EQQ+jYzhQzNEFyvh3whg4gamGgRpTpoAa2OoNHK0OrkmZtTtGsd4naLKGzRCZrktM2gLDAkSvRme8gqi049ZGx+hvnWIrETorIJ8cgwqmcQvB5c5VBoKAqdCGkMKIFSAkQG6QygvAJhRgABkYnRGuwkARnRyQralkEZTaHeYdXUDtbMHGRKXERdLEdrQew6RE5Aa2CO4NwZhk+NKLgKb7/Ac7cwX1pNzWSJGxa0BZYR+L4gm5fYlkHFhpiEyA1ZNA2qQYKbabK+3ObU3UsoPTxMsDDPzMIOppp7KGIYsjx6jE9e+VhYJFrTiWOSOMZNEjLa4BiQQuM4IYV8k1yhheWHaEsjcwK3x8MtF8i4Hq7qdt0yWqPikKhVJ6otEC3MopMYIa3u40jdk9ICYSOEBQhUolFaoYxCiYiIkDBpEYYdjDYYcaSGCtmdqd+AQHRnQRaCOElQcYJRGrQmkNDJuASeTce3sC2LvLC7D+kgtaGtQlpxRJCENJKAqtRUbUPVNmgB5rGuYYLu34gQKNH9adGdCe2xNWKM0qAUXmLoDwz9IZQ1uFJQdxyivIPlu2Qti4ItyNgWlmUTJopsoYDlOORKPn0jeYoDfWQHluAMbMTuWYXIDkNmuDtm5SSZGemJGGP44sQhPvDIAaamJ6k2vkDYHqPiL+Hq2Tau6sXjJXh2g7BTpehmqIb9TDVjeoe+ya+cuci75n6Ztz73Up6/fPVxKcNiGPO3WycYqSmWbXN5+MB/0rrhWuL3bMCUfazJBvLWBey72my54HfQZ15E69yISTdDUIpwLZAionVwL2LPKNFwH9HKJWg3i9KSQGmGE8XCTI0B+z5U5wyEW0A3Ikav/w79m9axOq/I3bqV7f0lVl2ZRTyS4wUVizVv+B2k98TdX+ZmO3xw+yx77/wyl160k5u/92Kmv/YJnrO4it9+8RjXOy7fq8e8ZsRwWljnU7kRgiDP2pnLuKP3IPWt32CwfSWum9D72hZ3Rx59a34lHcB9AojjmJtuuokrrrgCx3GOdzipE9QzKrF4wQtegHdkKszrrruOK664glyuO9tHGIZ84xvfOKkSi7DZ5L8ufQ41fwm9DnSqQ+iVFzPX4xJevg4vW2Dm27sZvf8GMtk+lg2cTr6QgcEsYsUgdtFFBAFOrYllLFTeo9PnEuYEdjCO33yQzlydqUc0rVgROxFhEhF0FHHiovHwtKGU1CmYDm2vTOzn8f0iA24fFZ3HbkoaQZbFpEAn9DHKBWPR7WGusVWCoyOylsHzLDxP4vsWlm2oR4pap06rPYedzNLr1Rhc2aJnPWSXWhgrYL7VYGGhRXbGpRLkcVSRtsmzYGVZzLh0sgkyG2L5bfJ5g58X+FmDZydoVPfCUsUkOqYZxkzNw9y8RaOdQWSyJDpBm4SoXieYn8dRFgPLljN8yimUly3FFjlytiHvtck7dXJuFcdqY3RMu2Exc0CzY3eDqcYic51FWmFAIYpZWhUMtRxc6ZN1XaSyaC9aJJ3uZ0qcMOdK2q7EWAIcCyyJ1Aq7ESKaEjvUeAoySdy9o21LyDvEvoPtGwqVEN1vM1EeYLZUQdmCgmngWQrfdcn2Sdxh6FCkOreEeZ2jI8AKNT0mZMlAQP/SBN81OHEHux0imwmOMmjl0p7PEzazmGKBqMditm7YZdk0/Sq+W2VpnLD5/iEGx/rwXI0wGqKYuB3T6rRora2j1geYgZBMJ8FrxIhGTFKLcfaHlCYU3nSCDjRCxOTcBnl/gVxmAduHbF+RTP8w2utH2f1ICVKGSNnGKElkfCKTISKPwkEKgyRBorEJyIopPGYRhBiVYBKFVDFo9X1jILopMN93oX/055HWCCNA013sSCuFThJUkmC0hm6HJZASbBvteSS+Q+S7JLYgNIoGMVNJk+mkwaJpYUiQto0RLpEyhIkiUgZtNCaJkDrGMhpLQF7Y5EKFaTQIgoDFoMW8CtFG4yjIK/CMxDYCh26CKAxYSIQBqaCtDK3YYEtDT1FQLgh6izYDJZdi3sVIB2M5KOkTiiJWYRivfwW55ZsprTiVytLN2N6Tmz77eNnfqvM7d9/O7tEJmu17sDsPc67vs3yhxcLCIoPl/03fqn6Umid0EgpeQOXQPN50jVas2VU/leklX+CXz1jBvbWl/MkrfodCcfBpLUM9TvjrbaMUA8WmO112f/odjGf34PzlmTiPLLB8PmH7YkKyNkt+YwZrLua8/a9ldmIedZrH3GAPzCwiGwGWSbCsGBMlKHWkFS7jEJ56GnsXLC7s/yaHHzKcshgyu+MQh/crZtdfSkaOIvKCLS84k57PfYlD55yK1z/Ny6qSZc//XUqbn7g70pevm+DecofWTe/glDNX8s2vnUl85zf52/MUn8zU0M4p/KpcznB7L58Je3m9fyc3rullf62PVYfPZG7uvxmbP4PKUJbM5TkeKIYMrHsZbz99OeX8z0/L24lIa021WqVcLqddoVI/0jMmsXjd6173pLa75pprfsaRHJsnOgCf+4VfYPDsy9h6053kZutkBs6kvPEsZKWH3cTUzlyCRYbFQ3uZeuge3FKB3s2b0Tpmfv8szUNNkmpAYaRMflkJL+ciYonT04+1sg/HaeBGjyCbVWTDYITuthLkbCxPYkkXRAYdOphGTNwyLMRZ6iLGd9rkvBgn00FmI4RIANW9GJMCYx0ZF9F00Q0fvZiFWh6Jh/RdvGIeWc5jshaJY1BCkeiYSIfESYhUkqxukhNz5JwqrqOxXYNtaaTV7b+vIoFWgo7lU80WIIoQLUXcVsgkIuqT4GRxmzZeTSNzkmTQplWtU5uco31wFktIKluW0bNlBLtiIxyFsRTIBITuJihCkaBRsY0IC1hBAV9BWQaUrDqxsVkIelmYVsztOsCe2Tnm6nOEuoNfi+mZqmMrRYxCIZHY+MbHMQ4SidACoQVGg3TBy9g4GQuRAeHHWFZIRgf0tQNWJhZlp4+DqzezUF4KIodwJImT0MhpOn0d2kCzmaW9AFlqFM0sg36bpf0C15HoSKIDSRLYCCGxbI3laKQ03S5gfgbcArH2CRMPYh+1UOhOa6tDZhfa7BaKekFhuxG2SbBViG3aWDoiNg5hx0MkAl8oEjxCK4vlZ5CWRNgaKRSWTnBigxsJ/LqLt2Dhzdv4oaEYJ/SoiAoBJZHgWZoMIQ4JgpBAt2gnER0To42m1EnINg0iskjsAlSWQXEQx5FkTZWsrOOJGo5dQ8p2tyuSAqGOZA+WQdgxWAnCjhBuhJSK7mqQkseaGgw2RnQfyCMDPKTsttOZbhKI6U7JLCwJ0kJYbrdVzwiMASMMWoKwBFIIpBTd94nBJBqjFEYZQmFoYaipiJqO0LbGdwyOCaBRpdlpEUQhnSSirRRtHdNWCa0koqlCFlVERyUYlWAnmmKo8cIEPwYvEaChaUFLQGAbVBa0B5YHtguuIyi4ULYFOSlwbJsQi5ZyiE0OZImM209Pbim95eX4lUF6Vm9meONmSoODP9PWkHprjjsPXM91O29l10IFR2vOce4kl3TYO61pimF6lv4qVmE556rdLG4foxbM8qzn5FlY9IhLGaJCllJ1DhnHTN89wlfklzhny4u5KLqHi896If6WN/7M4v9+rUTxVzv2480pVt0+j79vnvuXX0+0JcG732btpSPU6x6enbBvG9QPTuGYOTY8b4hK4UzUNkn00C2gDrO4uo9afSkL+SGEDY6jsN2Ejl9A55fxylLEVvklln3sEe5afQqFUgWWaPK9NWbjQaYfPgM1uZ21z70Q8/DDLHlRxLoHTuG0pQMMv+b5P/aYGmP4jxvG2Z6psS78R6ZGL+H2L9/KhYfXsurZNzMx/VKev0GQscf5k8Nlzt6yhl337ueDuQfZtjHmu4eXsG6sxb31KhXOI78my/ylDZwV53FGaQu/tKX/aTkeP0+MMZhYoYIEHamjD5N0x8t1T1hHJpR4bKHaI7+bRKNjffS17klQIG2JcC2yy0o4P8FUxamT2zMmsThZPdEB2Pe973Hfu99N6cIXsX/3DuR9u1h5yfkUT72UxlRAflUvh5Iqe3Ztw350N53ZJrvwUSZB6oRs0CHjZjA+NEVAXYSoSoHSWZvJLh2h07bJLd9IrlDBFR5WkJAszhNN1Qjn67Rmx2kFcxgR4lgCz7PJFlwc6UHgENch1AEdp40pSjK9vWRyPbjCxYo06ASRiSAfIXojzECCcTVJYgjmEsLpkGAuJpwJSWoJNhausLCkBS74/Xm83jzSsTEGZBJj2x3ccoCV06iyhZIg2t2WGZNolJZo+8hFn5Tgyu48ar4NtoWwLeyMg130cQczGAeUNNjSJkeOCgUqskLWZAkSTUsldFRCnBhirbtd5GU38RBOGyObSB1SjDR+6BIFRRaCPvygAGoQLQXTzHIwqNLvK3p9i75mnZ7D83gT03gLU2Rac7hughQhjTBhsRFTayTMLShmFm0MGfKr+/DO7qG5zsfq0+SK4NgWYWhoNTStqqa1EGHVA3oKklzWQmPRbFtUqy7VeZdG3UcIB2kLHpu90cJ0u+HENkJbWEridAyqs4jtxJT6DENrPCojDlYmQxAWaM3H1GZbVKfbxLGhuDRLZUWO0oBFtihwjMFRQGRD4KLiOkrXiTotlNZI28LKZNFeHu1nSRwwTox0QrBjkkgSznkEe306ex2iRZs4liRaoI2FwODlQzKVFm5vG6uS0BAZmsIjkjbCQK6V0L/YZnAmpK/lQblInC0Quh6RI0hsSSIkSki0FPhofJngOzGeE5JFk0vAiQXEAiuysAOJjCQCCZYAB4SrkE6Ibbe7ibpTw7LrGBOBTtCNCDPTQc+3kPUQGgmWFNi+jfRspCuxCg7Ct9BSdgdruBbGtpCujeU4CCmwkgQiTRwmBLGhnWg62hAZaApDTRpmpWI8rOMUs2RtQdYYslrRKwQFNFEcECUhjbhDNWrTiiO8ROOGCW6skFFMHIQEShEgaEqLmjHUrISmiLvD84UBS+MIyNmGgiUo2oIeT1KxBZ4lQYHQAttIBAIjIVSCthLESJRtYTyLxLMh5+L2+Ng5C9sDY2kMBoU5OhzFQndncjIKS8WIJKJuhthmLqWue1jZvJfdjXHa2qV31bMY7D+T8oTN+bW9lONdfHK7YtWGPMvOTPjK5/Yw2FHM6RZTwqXWM8QpZ57KRSVY1lH85+GtVDb+Mr/tfJcl0Sy5S/4cd81TM+6iMTHBji9+kR0PbGVycIjFlatp9A+ibIc++hg+sMCS6gCPjnyK+zsFKqrIs3rnaf5ngCCHXxsj90t5qh2frQdKjBazDGzcQmekSiaxaaFxdYehcIZl7TG0lSeyyyiviJUkLHMSek45yOceHKc4k7B8UtE6IMkeEix1Bpl8+SwLssMO73XYd9/B8Nmn0Fs5RKad56WiwbJXvx2vkv2R5Rvbvcgnx5rseehannvRI1zz1Wdz5sPfpjxbYHS4xgXDhkedcW5eLHLmcAMRJbz06j/l3z92H//kHuTGgUPk587l3ok76aldRW5IYP16lVlvKfnic/mzi1c8Jcfh542OFEk7QrVjVCc++tNogwkVRoHQBmGAREEUY+IEtOq2ROvuw6iE6sI8lWIRYQzd5rDuNsZohNv9nhUZF1HIonoGEEjya/twSmmC8fMiTSyOsydzAK5729vIJQnj8w7OigqtHQs4B3eQLeYRa85HRJpkzzaipWvZJVqMtceICagtjOP3DRJFmrAe4hiPgZ4hVgysoZSvkJWCqq7T6fMIkphWM6TRCGkpTRLFCGHj5svkK4Pk8yX8gk8nr5mXi9i2S8XJk/NzJLkioWujdEKoAtpRk0A1gBiEAZ3gGEG+HSEXJuhM76PROIDrtRnMuwwUPbJlD52ThMLCtCz0nMGar+KpmJzn42VcOn1Z2q5DOBoRP9TBmjIMVKusaB5GaU27vJz8819KacsW3GKW/PJevJ4MdtlDu90LlIzl40sfT3g4wvmJ7qgaYwh0xERnnoOdeWbDNi1tCGRIJzuOZU+RbWbIBD5Sdbt0uRTIUcSRktgIOsbQUoYYm3aUoRFkCGMfKxZ4QYd8XCcnm7jZKuFwFTsfEJiEWgPUnEtnUtCZMLSaMZmiQ7aSIVdy8PMuOBW0LiONSxYLGYQEYYtGs8rU1AKL8wHzcwHVxZhOoIgig8EgHYnj20g3QVstpCUpZPoZKq2g4DlErWnCZp1iQTG4rELPYI5CWWJLje4USVplkmYR0yngYiN0tzVJKcAWGCHQQBwbwiSg2RqnE44RRJMgI3AMwjLYGZf8YJ7SSoviiMLPdUDoo1984sjdMaFtSFx0bJNEHvKxpTTMkeHXdkwkFNXYohbaaGUQSmNiEJHA82JcP8ZzElxbYxAoJdFJd/2NmCOJB6LbAidASzASNBJLaDwZ45Lgk+BqhW80vjG4QmALg0QghUFY3fmmEiOJkcS6u39ta4yt0YDSAoHGQiM0yMTgdxJKjTZ99UVyDY0nsshsEel7YAuko4EQGcZYQYTVVFgNgx1IBB7C9jG+T+Q4LBpFTQc0wubRR6QVnm2T9T2ylsA3CW7UIhu08IIAN4whjNBhgIoCIhWTSAmWRVsK5i3BtEmY1AETSZtFFRCphEBrbA2+6R73BEhsQWKLbksNAqkNsltwlDYIaYO0sR0Hx+6OYXEcC8eWPHY7NHQqNP0lzBVPw1ZthmsPUtZterMjZFZdRpIfYNX2KfREnXVb9iHHD/Cx0REuONNjcdDlxq/4jEytw+vxqaoeclGTspli+7oHGcxaDPVeyHNOP8B12/ezs+cS3jmyk7ULs2Skjyltxh45DWftuVg9y452BYl1TCtukXfyWMKivbhIfXKS+uHD1A4epDk6yuLoYUbHRxk9/zwWTj2DzK7DZPYexnEk9pp1WGtPJzM+RphUeHRVQH1ilEu3T7JlfYPpB0Y4NHA2JbfFVKvAkvlpNg4fRKye4f5/qDLhx1z2ordwaOxr9E8ewhvspbr2XIKelSSLs6iZvcj5HawcWMXghnXcan+F2/9d8exJw7w0iFKBwqbTcd3nMSTHCJd9lfmNM+zZdx6dekT/qmGWb9rDcw5uYMlpFzBw5ek/8tz41c+Ncc9wBA/9JWvXreCD1xd41d1jbLMMF24eo+IF6HCQpVlDtd3LoQi+Gj7AX7/tb/jbj93F74jvcY+Xwz5QZWpuCz3Le8i8uMXuTJ7K0Cv4q0tXHvP5+ueN6sQE0w3iWogOkm5Lg6bbWhoZ1GwHPdeBVoiMWkirAzLAILo3zBAoKboTSQjdPfeiidF0REJLxQTEBCYgMhFKhyQmRumElq1pZSVYDo5xuDBeymD/UszK9QhpU9w8iJVJx2Y80z0jEou3ve1tT3rb97///T/DSI7dkzkA7cVFvvzrv855r3s93/jXL3LmG17KyKZTuf3jX2KFG1Ie7Kf/6peT7Sni5Twmvv0NZrdu5cw/+iPcQgGtFGG9xeGD+7jz1tvYsW079VaDoBMSx4o4TgCDsSVuoUi2vxevkkd4LlgWKptBuw7S8/DsDJbjIuKYoLnI4twB2rM78MMmeemQL/ZRHFiB19NP7CiCuEFIgDYGH5cBux9Vi1mcmWFiboyoWiNbh2xN4zYVmSihMJTFX17AKxRIkgQtNbnBAZYNbGCofwn2/DjNW78Ju7dBoULPK17NyC+9Cm/g+M1Bb4xhNprn0foY+zsdqv4MJjdKqGPqi0uwF5dQCjyydE/cYBBWjGVFuFYb12nh2B2MTFBWQiANoWUIbENT57DaI7hBBUdIMkaQUzYZLDxjY0mQtkZY3YfnOOS9LHnHJ+u4FFyfvOshvy+JUkoxv7jIzOwci/U6E5N1xsYbTE23mJltslBtEwSaSEe0rRptFnBtnwF/GWW3F6yIqqnTIgBbECchAoOQEixIYkkUgIpAKpeszpEXOQpOgd5CGWlLlGPQnsHOgbEVEk0SRwStNraIsEVM1KwTtzsgLdyeHvz+AbyePkTORxir2yhlwCQJcatF3GqStFsk7TZJGKCTDp4bkM1pnIyLl8/hFX3cggcqg+HI7FfSw2iBShRaaXSi8QoFnHwWaQkkBiGPdG+i+0WrjUViHCJtEwpDIBStRNGOFJ0wIewoTEuhGwrR0bg6xjOPJR8KT2tMw2BaBlSEcDUqJxEFiSnayJJB5mOsbIzjx2T8iKwdUZYhRWKKSpGJDFJJRCxA2Ugt8FDk/JiMVDhJgh0o7KbBrsVYbRAdgdDAkel1kRIsu7vyu93tuoWwuomadaTlT0eYpIXpVNFRmyRqEQcNkriJUt3xJo8NhLcsG5ShiWJOR0QqwdYG60giYSOxHQ/LdhCWDbqb8Ol2Ah2Fjg3zmQqTuUHGi0PMZcogJBJDKW4y0FnktOo+8iqils3x4MbzGC2txH+kRd/sHtYO7GNwueHBrRU+2OnjlVe7zAeHmbs2w7pgKaflJJk4wjfzJHnJodxyvjm6mn3n3MWWxX3MmVdw1UXfRls9fG8qxwuGt+PbDgMdhROFODZIS9OUAZOmxt7xaeb2Nxib1czNGGQskFpiuXms4hBmy1n4a08hP9/Ge/AQ4Ug/i2efS5ztRSmJChaR0SLFno2MVPZR/5dvcEENlr88z9aDZyGVzeD0DUSFCNPJ4m26mIf3DbK5/2G2LN3Bo59Z5BF/JRde+WLm+/YzuzRC1mzy9zdJlCIOFUZlsRoeA1fu5IPf3sfme5/H/PAKzNoRzspVyTygiA59lc7I+ZT7L6FSuI6p5z/Crm/1oy+5ivUD32XV4Yu4LNtk4NW/ip3/wUUqdaT4yDcneSBT5Vz/X7nnzlNg5342PFhm4+n3cdCa5o7wMuJ1+1h24CxOWaI5I/sgY7MZ/vXgLH/35j/nho/fxkLpHs4PlnHL2CQldRGlKxwmNrbJDf8Sf33x6mfMZANPFWMMST0kmGoQzrdJOpJoAaJ5hepoko5GRQkGhZaGI3/6GPHY+LAQYQUgEgQKYRK6t04UQnd7Plj6yOuie4PEINBCoCwXJd0jk1EYLATSGKSJsE0Toe/le70Rm9jEKT2rMCMbyW8Ywh/M/9TljrXizoV91OMOzThgQbXIWz6/vuzCtI4cZ8+IxOLZz372436///77UUqxYcMGAHbv3o1lWZx99tncdNNNxyPEH+nJHoDtN9zArg9/mIve/Tdc/55/wwQxL3jn73Ng10HGtu9DCIHnu8TbbsPvH0L2r6a2f5z29AJBo4YxMSoJCYIGkYpQKuleHhlQSndnoDHgWC625WA5Nm4hQ663RHGwjJ11qM9PcuDAThaSFmVLslwJMktX0vuc5+Hlepg/PEb94C7C2UPY7QVynRhfSWIrw7y0aGmDji2IHYR28P08+XKZnuUjDG1ax+C6FbRr88yP7adTW6B39WqGBvqIH7ib1j13IOansKXA6u0nd9YFDPzab5I/9bQT7iSSmIR9zVEebMwwmyRETg3lLlK3GiTa6m6kJWj7yF2i7iDgbh99C1v5uNrH1z6O9vA6iqVemR5ZwBMeWd8m5zrkHA/fdrp99IVACoklBNZTOKiu0Wxy8PAYew8c4OHdu9kzfZjZThWlNHkvQ0+2SMnPI4FQRShL01IK25JIIbCERCWKqbkqi+2AdgiR8kiUg8DBEg6OdLprN0iD5wqyORs3K7EyAmNrMlmX3nwRLwRRDwnmW0SNgEQlRGFEEESEUUJiCWIhCLUmssHNZcgWivjFAn4+j5UYTCdCtUN0O8B0Egi7XQFkrLsX6MZGYiGMRdRudLtuJQnS8nDI4AU+pU6BcihxlUQbB4SFxkbZErMqg9iQxVriY1VsqGQh113AwjhHjrfRaAQYsKRAGrD0kS9kZbCVwYoVMlaQKJSJ0DqGpEMgNYuepGFrOkKhI4MTxZR1RI/VIe93yBXa5DKKrBfh+gG2bTDKImq7hIFPpDIEgUvY8SGW5JKAYtShkLToiVssbbcoqQjj2SgbYtshFjbd1A8yyianJJYyEHcTZSPs7kWHFBgTg2gTqxqNYKG7sGYU4hiNrQ1SC1ACqWyEkRgDM5bHfdkBHskNExtDf3uOkdoYwwuj9CxMgk5AG4xrY4ZL7NtyMQ+sfjatTplVk/s5PbiHSjiFaGucZsLBQ4qbVi3nyitsvnvXIub2jWzyy7hSU8luxc52iHIVTLKMbMejL5nha/EZfP2CeZbv3UZHPY81y75G/7NWE+1qsWViHMoC0WtR9xMW2wFz1YC5WkQ7MES2RtpNspmInFMgsjczmzmbmjWIng8wOkKvGSC3ZJCisuiZ3kV2eg/5MCTb149YMUCcVDn8L4d4tt5F+U3r+M7WC9loP4ztfpcPH4pxrJhlXoZzs5up5XIk5kKKGxWn6oj7H3QZe/QAKomxYoUz38Zv13B6BnH6hnACw9AWm8L5D/CWjy3wQq4gilxedvYAozsrDJTAyziM3vsVFpqHMWf9KQOZR5nf8nW2jW5g6Jx+ltizvLiWpf+cl9F3yfofOFfs+NY410rNvn3X8pyzd/L+L6/n7x7dxs1Vm+yKWxnlEtZU5hhoXs1Zp2rWbWyBl+fB+25gcg7+edcMVyx5DeXWVxju6eNb28fJTb6Y0sUewfNnSYav4rXLN7JhMPeUnd9OVDpSCEf+2O+2pB3TOlyjurdDY84maEDc0WhtkCbEkhG2jLFkjKUi7CjCEiGeWyXU4xg1jdQLSHsGW85jdJ3EKGKtSaQgcn0S28c4PsLJIIXfbbU1EGPoaMWiClmMOsyHmkbUbVF2JLgiQ04s4xznF6lEdYrRt7m3R5JzV3Hm0BX4G1ZQ2DBwTIsufr/5qMkv3/XP3Lf4ve5CqUe6YmFZ/O+Nv8efb3jpT/rRp54Cz4jE4vu9//3v5+abb+YTn/gElUoFgMXFRV73utdx6aWX8od/+IfHOcLHe7IHwBjDV3//9ykpxbP++Z+5+9rruP+ar7BmzRYGN69hYfcBDt90M7mVa/D6+uk7ZRVef5bvfeEaOkZhZXy8fIGB5SvpGV5KoVLBkRZSK0SS4PoututiOQ7SspC2jbTt7mrKQlAdG2Nm1y5aCwuIOEa028xPTdDQAd7UGMIYwv4+ghVLMYMDWK6LpUDWAtzpOfxqjWLGZXi4n8G+HnK+jU4SmtMz1Kcm6VSrSGPwpMSKI1Stiup0kLk8mU1b6HnOC6g894V4Q8NP49H56WmjqcctHmhPsa/VQGOwpYUrHXxh40uLjO3gSwtfSLLSoWR5ZLG7C8wZjVSaci7fHXdyAkiSBCklc/Uqe8YOMTo7RSto0+x0aAVtoiR+3PbmyEA/x7YZLPeStT1UnDBfW2RmYZ6puVkSpRBCoIRBaU0URUTR/92PbVn4GR/f9/AyLo7r4loOjrRxbAvLSIzWJLEiCmM6nZBW0KYTdYiShFDFhDqioyICHRGo+MgsT91uwlpZCG2jlI1KLJSy0fhYuDjGx2tZeI0YtxNiRZ3uAG0hHjeYEbrT3XYfDgiJMN2JBrI5Gz8jkZbEcroPYUmkOTIRFd3ZnISQOJkibr5EptRLz/AqsuVehAXC7TbPGGkwlsFYmsg3RK6hJQyNOCFSplueWKE6CTKMcYhxrQ49hSrFYpOsF5L1Qzw3RlgGBSgEsbFoxi4LkUct9qiGPnEkkJFEBhInkDgdi3IDekJBX6zoD6A/0fiAazSeleCJBq7VxjlyYdOdaMsisgSB7Ha/GbME45ZhWjosSp+81mxqt9nUaJMLRbe/mashk9Dus5gfyTFdKHDYDDDXKuGNKk4ZHWNpNEXOWaQYV6EZUs0Oc9/q5Vinx1h6nm/cFnHK0ivoMx1Ks5O0D1bZtXOauKkxcYJxmwi3znBU54zyKsbWnMO3lzTx986wJX8BxcwMnUs0w5kxgvFJzHSV/EKbCgKraEHBZTE3zGFviAnTwzR52q6DjKaJmtsoVyz6R07HEoNkOg0K7Z0UFw5THO9gSuvQxeUwOk57x052N1ex6dQ22StdDj60mY36v/nigRpJvcgfRUvIBnm2Feb4hJ6gKDRvWHkes2PrkVcq/H+tIxY0+aEevLWrWCx3WCiVcWsufhLguNtY9tL9/PPnDxDd92zW5zcyWAYO2DQb8yRuiJ1RFLxBipV5xu78DK1z3kLp5Q+x67uHWHjBb3Je7+c5f+y1bHAO0PeaX8TOukf/PptTdb51Y4t7V3bomXwvtp1h680jtLffypb5Ps7fPEnFr3H71IsZ3jiDOB0mKr2sQvDiVodtk/tZqFr8/cOTvITzmFuyi54Zi4N7NtK/ZQXeL08zV9zCcuc8fvuCZ+5CeUkjpL5zBqO7l1rd6a8FMuN0uwxGmqBmaC0KGjWLsAM6SFCJwqJNwa/il0MsmeC0YpxOiOMrfKtKNL+fIDxMOzeOdMe7rbpNi9DkqWbzzPkZOpZNIzHUg4SFdkw1TGiHmnZsaMWaREnQEqMtLGNhKQdLZPBFhoxwEUajTERiElqiw7wzxys3nMMFhdfQ095Lb3Azt/Vn6cmcyZY1l1O5cPUxd43aWZ/kZbe9i7P27uH39/Xj6u6pwlHQtBRXP7vGf1zyPl48dObP4hClnoRnXGKxZMkSbrzxRjZv3vy41x955BGuvPJKJiYmjlNkP9yxHIDaxAQ3vv3tDA8NkV+yBNXfx513fI8VPUvoHNzDuX/wVvpWraE2P8tX/vZvmNi7h+e+8c2c/5KXkXuCfR+LOAgYvf9+9t56K9VHH8XpdMjm8+QqJWTQwrSayFyOzPASckuXUli+kkxfH6rdYn7PXqYfeZiFRx+F6iKe0UjAdhysYonChg2UTjuDvvMvoLB+wwnXGvF0M8aQJAm2bZ/0n0WcJEzMzzA2O81cfZG52iILjRrNTgfbsqgUivQVK/QWy+T8DI5tY1s2tmURxzGL1SoLtRq1ep1Wp3Nkitgjve+FION53eTD9cj4PpVikVK+QMbz8RwXpVW3a4hKSJKEKInphCFRFNEOA+Y7deZaNeY7NaZqcxwcG2NmdoHmfETUcRHaxbJcbNvDcbJIbcGR1j5bgECicVBYaCnQwiDt7oxPhm73o+4Fg0EgcKSF0JCoGB1FJHGEiRUmjhAqBh3iBYZsYJEVveTVUnrDERztIozAlt0WKoFCqu5MVNmKR2FDEee0AmZNDlNwMZY8OnuVMN2Wse4CfaI7XkVIDAZQOE6A79XJOFUyXhXb7mAsRSgtWsamZQlaUtGKBe3AptXwCJseogNOx1CJQlyjEUqgtUOiu+OmQss+Mk5FYEtBj1SUpKFgaXzLQllWdzC9o0jcCKwQrQOStkAtWNRHc4gZw8rqFKv0GHnZwBcat2BTW55nekuZznILvADLNNi+u8rog0WWHx6i94DC4LJXHULkE1ZedBb2uvVI45Ora4ozhub4HHsO3EESdMidsZqFSp5D2++nYJdYVuynOTBEtt+h3NthqNwg47RpqAipW2STFqKcQRrw52LcjsNceSnVrEPit1BylGB+N839U4SLG+gEq6gvRCzOTBKxQE/GYY13CqtWbiTZfD318dMJ9n+RzkSZTNvhggPr2OoF1HsWuTSuM2Rnubfc4TZ3jtdftpKJe5fRurSH+c9OsKAslvTXOL1yCo69nEVzP5Vls/Se6tN5dIFX3rTIxsG3UUocnivWY8mAwRdVSEo2ex6tU7/pVioTMeXBClO3/zv2xa8nvvRL3DlzBhsuiFlXzXN6tIXV562m57zuuhJGab71uQl2VOARZ5Ln9l3Dxz47yJpDs3B3gd855VZ2DEXcEP0al112NnfnroPD27jK7mVteYTbyja/2Q54aHaM6QOC/9o7xIrBMV7an+OT9wb0R8+i+OYqs0NlSpkX8+eXPfPWs1BhQnP3HEE75I4gYa+2wYju36sWWEpSCCR+IPAicOLugOkYiSUTyqJGTjexmx1EqIhtEFaAazVI/Ihmtk1gtZGBptpO2F6tM9ppUI9CtDK40sWTWaTxsC0PS3pI6eMIpztOzEDGsshaNq4UeFLiSUlGuGS0wEkUQmnkkUVDYwsik3Bw7FGun9lKlJnlt7e8jLXu81g3/1GQGW4ZdCn4Z+MsHWDdxWexLN//hN9x1008wB/e/h7+bLviJW3Nth6bBVmkKbLUZZacMpx38BDPuSrhlss/yPrik1+RPvXUecYlFoVCga9+9atcccUVj3v9pptu4qUvfSmNRuM4RfbDHcsBAHjwS19iZvdutlx1FeHEBGN33sl0u0HfhRfQrNUYe/hhZnbu4Nmvfi0Xv+rXf+YXoypJmHj4YSa2bWNq61baY2Oo+fnuBU8SYyUxlgAdhiRhiFcqkRsYpLx+PZXTTqf3jDMprV2L5f1gn91Ud0GiG264gRe+8IXpgkTHQaISDk1Psmf8EFMLc4zPTDM2PcXU7DwqUZTyeforFfrLZYyB8blZphcXaLdDOkFEGCiSwHS7viFQJiHSIQqNASQSV3r4lo8vM9jSxnc8Mq6H0ZI9o7M0wiaxbmCHinzTphhmcdwC2KXu7FRGHRlaGWGMQscJlgGUQWgLR2fJqAx5U6BoF7CFhy89bC1xXAs/Z+NlHWTOILJgFVzsso/OuYi8i5N1sXMBbqGBk2+Cp7qrlNsKk4nQ2RDhBeCEaJIjiw12vyqk7g5e707bC0dXItQCpQVGgYohbmmCWVBzHmI+j1Mv4jZKeFUXT4UUMpP4xSqy3EH1hdRXOLQHMzQzHk0N9ckOc3fXmNxZZ34i4hTrDDaM9BMOz7A4MIqowLL2KQzObUIuSOJ6m7Zo0h5M6Kwoo60s+b1VmFtgduYeDtAk7ukjozLsjw8y7ICf68N1ypSkx0imwppsP3vX9DDamEUF+7B76/QOt+gpxHhG0zyYMH+von7YJRJZZNSmYs0wXBrDzzfA8yB/GSG9RDUbveIQ+fwQF926ky9MJ5gZl+XS4o6egAG9CtUpMu8fppCZ5bXeHm5VAtGX5/z1A6ikh8O9y5g+2Ed1rshsDJlCwMUXTlCpNpnZE3Jts8Gdo2s4038eRatMb8FlzaU5Jqe3sWn5cmrjNTq5AUbv2cvI7kex1RD1/d/B+aMiu+7awfRLf4tzvY9zUfP/MKImWfOa52BlHB65aYLb6oJGfpZo5qsMrjzMZ796LvrBa7h451XI5z7ITO9buNRdwS//5VosW6CU4osPf5PP3PzvvEMOcefyQd5YrfPgwd1cu8OjVw+zZMUot+80mEdexMCbNdHpTWTh155xA7ijxTb1R2c4KNvcGvksCEGpMUbT9YktC+UIYkuiHEleW5Qii2Ig8IxCKo3biLFbCmkr+pMJllV3UFZ7icoTjHlNVMtitm5zV92wt56gVEw5yaDr/URhHstyKGMoGU3OJORUQE6HeDoCYTCO1X1Y3W6ccRKTyXkI1yCcCDfvYpcz2HkHfJCOwhECR1tEi2to1pZw+8EH+Gb9QU5bVuD1a/6cnuY1LK8HICo0fIvxQoXPFKe5r7fDYP8KLh04g7N712Nh8WDtAHfN7ORAfRRn4lH+ZWeBFZkxPiAuYXR6kmwyj6UDhGqRlFZyyVAvPdNjvO7KMvdf8a/0eT/9eI7UsXnGJRavec1ruOWWW/jHf/xHLrjgAgDuuusu/vf//t9cdtllfOITnzjOET7esSYWAHP793Pff/83tuty9q/9GtlymUe//nUO3HknK847j80vehF+4fgtaKXimKBeB7p33KN6Hdt1KSxZctLfdX+6PZNaLH7e/P/s3XeYXGXZ+PHvqdPL9p5ssukJaSSU0BKaUqTqC4IKqOirgiJ2X34iKoK9vKjAS1FRROkgRVoKnYQU0pPNbrK9zk4vpz2/PyKrMbQIugk+n+uaKzNnzpy5z8yd2bnnaUIIsoU8iUyKRCZF0SpRHa+gpqyCcOD1p+z8R30Dwzzy5Is8unwVG7t2kiGL4vopz0UJigCKoSH03V2wPBVcBI4qcNXdgzb1vINWsNBKNqrtoHguAsGrU9Qru1cARMFAEbu72ykor96J4lkoCrvHzKg+hLK7Rcb965gKBRNV0fGHAkTjYSrLY0RjMULVMYxKE0VTUSwdBVDxUDQNLWCiGrunrVX8AjXkoEfy6ME0mi+NoudAyeEpOWzHIu9pZF2drKORtSDXI8htLlHc5iDyEFADTDAnMCkwgbAZpC+9lY6BTZTFKpk6/iBCIZV0cAPF5gFKDQEI16FqcbSCDy2t4o1YFOwgdimOvmoE69kOeqsH6G/MknkliRlM4JoJCn4H16dih8ophULUTTOpnhVHa1OZ0NfIeHcGIX8UU/QRC67GV9ONGvfwpQT6sJ/0QJThnmpstRonFqFoFVAjAUb8/TRN6mLyw/082pVhlzJCj1aHUbmAmlQjs45qZNxxlXStGWLN021sbt1OlZogEX+eT85RqNTKMf0h4hUBREwl4zMoCZPiyiQvppIU9Cp+tS3BJONkpiQrKUenYrpCqD5EWbWfafNrGT+5jMfv2kbK8tHa7hJ76TkCXXlEQwD37CdZmjiamfP7WZI2MN0PctAcE/+4cu5dkSFRnmSIAWaJ3/HYWpM1rTP53FOvkDB9LD35TI7xwpx+9iSmHB7fI7dH8ik+cuP5XG2M4/HGSs5p38y6jS6Pdk/AqNvBLMNl2dOzmbKoGePcPlKhs/jGvKn438IK4P/IcjzuXZ9hR6bElFiQI5sD1ETfeBzDv5pbcuhcsYXn1ATbjEZ8pSQnubfhN3KEsoPYhRDd8TkMlZfRH/KTG6lixIqRNwzihRL1xQJxvUBFdoCaRCe62ke3L8hOrYWSp7CrZz2t3W2U8kOELZOAMQ5V6NT6NMYJKLM9hE/FrQtDTQAtpqOHNfSgBqoOaLtnPxN/HbDtgu0JnN2TxWEXNeySRqmgYxVUfJkigWyBUCZLoJjHm+QSnmyhDU2k1FbBz3b8hVywlysXXEV5bgsx9UeErHFECrPQRRBXVRjWbV4KZXkikiWhu8woaszKadRaKtOLLqZvLd8pnsWmxCrqdtqEXRNTaPiFxoi+ndyh7+USY4CVbpqbjpvBs0dfjbGfdCP+T/GuKyzy+Txf/OIXueWWW7Dt3X20dV3nYx/7GD/4wQ9GV+LeX/wzhcWrErt2ser22ylls0x/73uZuGgRqib/A72bCCEoFov4/X5ZWEhYlsNjy1fym/sfYWP/Vjx1d3Ug/jpQXkHB89zRsR8KKj49RCgYIRiIoWgmthA4rrt7KmgXiiVn9wB4u4DtWoD31/5lu8eOmLoPvx7E1EyCnoahgqIIFMVBCIdcvoBVtHFKAreoouQ09KKCags0z+OvHcF4te+aUDwU1UFRAU3g+l3UEKhhDWGCo7kIoaAqGkEjTMAIYVgqhqVgOAomKn7TwB/0o/tUFEOhYGdxSkVQBIahM3vRfGYefDCmbqI4Am+4hN2exNo2RHHnVtzCdlwS2FUahYYgheYgxXoDL+LDiURxSnGUzghqq0Z/0MfIM0OUJgQw6tOYoRG06izBMgPjLxkyLxToUnwMKiVKuCiKQX2olrmx2UwINoFSxFc3hBpKE4ykiQaSmEYOv62gFUuYTpKwa6FvS/LAK2FusXXiyhymjptEbT6GfkwFoRoTkXHJqgLFVIlHdNZse5nE+l3s6FzO2TWTMNUuRlIKGjphv4XnS0Mkg2fO4N4tKoMllU9NPRcn5+fD32lhcMsIbc/0UD+7jPmnT8YX3N0iuv6FXpY/vIthtwzvvpeIZNrQL0ixdVs77UefzikzdlDb+x7K7UpGghE64xZFsY2ZQw+SmODwkz9NZNrWNuZsqCV8yXyWbTV5f0MLH7xq0mt+hvWmB7jwlgv5WWAyT0U1Jrz4Ep2DjWy3fZzU0s1NL1bSkjuO2Hd6SVQcRm1qFidNLmNyY+Ct/Z9xPO55JcPmXIZcIItP9bA9Dc0x0RydGjPIpw8uQ9PeuUkv3gohBL3PbuMub4RhKjgy/xcq/VtI+wyGFR/RmIOBC4kCWp9HY5sfvViGpfspmRqpAHREIvSH/QQLaXypIIWKKtJOB+vXrCTX20vWZ1DftJj6mhbiuiBeLBB286jYqH4HXREoRXD7FNwBFTup4yYV3HQJxSmgiN0XoeRBKaDpBTSjhC8Ahl+DMj92HHKaRVpY9OsaQ2aQTKAcJTCeFm0cDV2biEZ2EpzvR+2bwxOPvsgj2ja+tvBjtLgN1HTfhBpYiREvYYoyTGcCqlOHKgJ/Xc0mgUcfqjKE59h82TmN1twW6ooKapzdC7r+dTxoriCwNr9I5eEX8o3ceq6tzOEedzb/O++j/9b39j/du66weFUul2PHjh0IIZg0adJ+V1C86u0UFtK7n+wKJb2eXL5IKp3HcT1s2yFbyOF6LqtXvsTp7zuV8niEfKnIhh2trNm6iU3tbfQMDVCybGzbpmjZOJ5HyO+nPBqlsaqWuspqTN1AU1Q0VcO2XXb2dNPR20dvYohUPof31xEZr45bV9FB6KiKjhAqQtn96yaahuequ1c4Fw7Cs/HcEo4oIfDYvc6eiun50EomesnELBkEdD81DeXEa2PEKmIEgn70gIJiemg6GDqYiktQ1YiFA4SDAabPmMq4cQ2ja0u8EWuoQH5XmkLrELlNPeRe2Uaptx+vmMWzsjjCIj3Bx9CxtYzMriJX5sf2GagWeEOQb4Xscyqsc/EcHcN1CQkHQ/EQhobt10iqGTr8rfT5hqjQGlkYOpgKI46ruJhqllp/Bq/QQy7jks8YpCyVvPB4JNLKjMqj+cjhRxIRGgdf1MDGpSP0bMlR0xIk1W9RzDmULI+SBn8efg6bNNu2bOAbhzVRFhMMDm9nILMCzfSonHsS96+t4+XObj510keJPlfJks9VMGlafPdrYVnc/tP7iSTrqZ9RyYIPTMLwaaQTRf7wi3WsXS+YsHIDetxG+eiTPLdyKjUn5zis7mByI0djGToFYxOVA/dSZRT4s+Lx3MrT+fkjv+ex/Dx2/vdRNKzX+dxX59A08/W7pOwY2sUnfvcpfuZvoTO9k52vaGSLTRhV7WwdLhFb+z70r2bw1YTJVBxH3IrQUNJZUmdS2xBGDxoopjZauDiux5beEs/uLNBHjnQgR3kOyrZECeKRVBW8KhuqHPoMQdgK8vXD6tD/jcXF8KYObk3uRMPHUd5dDHs2T3WpLNtUTSaRpwKTRYFhjjrOpbIJEj4opm0mrC1Q2+ZSNG0SmodlFhipaeKF4Hja1m6gmmHCMyupbxxHWAkQHsoS3pGgMOzR449g2wK8AFmthpwWJqv5yDguBcdGtTP4rQwRq0DYUvHnBbploLshFNuPYgew8xphXxxdaBi2huk6+Mjj17NEKgaJNqQxyizS6T5Wb2ulf/rJMGMB/p2tzJixDb87n+wzq/nG4FYWNB7EqQ0nUeZtp27HY1QMpdEDGZRoASPioCoKTi6IUzDJZgVfaVhE3hqk2shSo5VzcuAjiCwUChbZYom10Rdo1XZQ6tnItHnv5+uDm/jw9CKfOe27HF970L/tvf1P964tLA4UsrCQJOlA5bgOiUyawWSCgZFheoYHSSSTjGTSDCVTDCdT+E0f46rrmFjfyNTmZqaMG0c8sn9/1rlFi8LWDoZf3sjOLdtIZYskN9Uy0DsBzXERdharIgyT6qjQA4RzDplomHxVmIhqU22n8LLDtPUOsb60nZ2+jYyoaXwEmUQVEygnjI+AEAjhkhYWt5gbmOmezIzJTdRNDBPwAuRaHSYcFaFmup+asiAtjfHRL8+ZIYsd61P84IE/k+hvIzbUTIPewJy5GRoaE6ihPH962Mey4gY+PuciFsQnsSrfxheuOHiPc00Ourz0aI7n79+FGBzgtK/PZe4J5RTzNr/49hp2PJ1mWm4QjnkOz2nnj9Ej+PgZedTMbAbVBgL99zPFHeKleID7lpVoHjyEU57eRttxi9jqhjijaQIf/tbe09MODVg8eHcfS06spLklyCu9W/jaH77Al5Vy1q/tocar54m8xszKdla/vICyI+uoOy1NcMvFjDQUyVW7VOTDxF2V3Z12di9MmUKQMF2ygSKOXqIiYVCzI4IwS+jBHPWuQV6AbenYjsGgotIxu0DADvL1Q+sx9X99cZHo7OWXPVsI2iHmlN3NPSvSrGhvxOnvwhh8kaCwELaC399MONJCeayOE+uSTDnCoVjnMqI4BAsu5UmLRHeetoKNEVDp8+sM+aegbXGYtmIbRrqc3pY5uBN0AqEcjm4w5IboLoWpNoI0AxPsIgHLoaQoFEMBSoEAdtAHpoLQbVQvjxAF8p6L5bkUPI2cq2ELFdXUMHUDVfgwLBOz08TsBn+ySJlIMyXcR1FdTeuWFyhMO5qOSdMwm9bTos/g4E0JHtjxCk9YLuXxSRwWb6KsbiXJXBdqAibkQE/leNkq8VzdQQyWTaa51IGX7eC0ysWI5yaTs57GTwqfm8WvCNSSy2MLykh6GfLFId43bTof6B3htENc/vSBm6jy7d+fO/sDIQRZJ09A86Grb73L4e7HlRi2srT393Nsy6wDu7Do6Ohg3Lhxb3n/7u5uGhoa/oURvXWysJDeiBCCTCZDJBKRXaGkNyXz5V9LCMHavyRZ8X/D2MMKGgKhFRGahWJ5aCUX1adiV5hYZTrRBj/NzSEiQ0l6uhOsGmpnbX4jA24vqqZgBnX8ZT50U2XihmOYX9GMV6eRSth4VQ4jwTyW7aLqCsl0kYLj0tAcZe5BNUxtKmNKQxmusPnuHfejiyGGEimcwShiKE7ED8szL/LBmf/FguBUNm8YpGl+kNM/3oJmqPTscFj/TIGB/hyJUonTz69i08oRnr9+M7WT61l84URcJcFD9w8w8tA26l2L+Om/5/HyQ6mK72ThxPkM5fLMHGxl20ST39y/Afgs16y7i0d2LSBw1RH032lx7fWHUTnOjxAC1xPomkrHzgIP3tXHmefWsfyJYYJBjZPOqObODQ+y+Zm7WDA8wNKNCgcHJpAuWDw8kOaw8iOIfTVNzfoqhmIHkUnVkm4uIvwgNEDbvao7eFQkDMr7fIiSDnqecrdIebGPDe5TZOvTmMMRIuoU6nwz0YvVjHh+Nh2cRXeCfHVBHcF/YgzHW7Wjp4PfdO8gptnMjqzgpzcX2D5QorHjBd7TVaJ5KEJGaWRdTRePjxtkQnYcCINcbTN6RSOnDa7h2IMd1hoK22oNfHUGPZks2zZlmLzJZa7lMDxuCv3xcQhNJSwyRKMVdKUn4O+C2nyOoL+IqApj15WRKQ+SiQawDR1FCBTLRZRcilmXgq3ieToKGn5UTFR8CoQ0BZ+hoGjgqgLbdSgWbKxiiZLjUnIEBdePU/DTUHQ5tHeAcOfTOMFhbDVN1/FBlHHzWT8QJxqyGe+U2Lq5QE/fMKrmUjYuR7gySBe1FDw/8eHNuMMdqGnBxeY5DGyAnuJ1mMGplNwYecVHMaijZXuYYWd48PAARiZLpqyWK2u6qR2o4mPHlvHAaT9FVf69Xd72R0IIhkoZHul6kQe7nmVzqo2sm8P1HBzPASEwdR9BM0DYjBDyBVAVlYgeJKQHCWghUnaJrkKSwVKanJvFEbsn74i6AS62L+KK/zr2wC4sampqOO2007j44os55JBDXnOfVCrFn/70J372s5/xyU9+kksvvfTfHOVrk4WF9EZs2+axxx7jxBNPlF2hpDcl8+Xfx7YEO1YVWf9IgVyng+4T+GIKmmpj9WYp9hewXY+CAlnbw3Z2//n06QqGInBMKHiCVMbGLWlEVZPyRdByRJSmqWGqqoJUV4ZIjTj09ZZQFIiWwaq1Paxc10u8OoC/ykcqVyJXyrGpYxuGZuC6ebL5IQYGRzi4cjFnTz4BJVJkxbqtHF47mR0vpgiWmcxYUkZfJsvmrVv49KWH4fcbxKpN0kmbX39tNekui1nvmUmq0M6qp2yaRvoI9bVTf+YT/HzWCXyhYh2BbYKuI4L86q4dVKbi2LHz+dxDd3Fv+RLSExqYVVVB/FidZLYEQMFyaI6UIXqCfOQTTQSDu8cEblqfYelfhnjvadV8/rnLuCin8MJTA8zyh7DUIA+0J1noLET7epGpkwfRi9A0oOLLWogceNkoXqkM167A80xUI4euZ/GTwzAH2D5+gI5oBblCHUFVkPUMso66e1V4tchhnUdSLM1i7cF5hOfj9FCe2eODoBkouonij6Ho/n86V0YciwcGd7Glv5OQksMXTLEg38nttyR4cniQC57poNw+hPaJM9jaEGN8yEdjIsZA506eCP2GQqCTySM+6iyPXVMOZyRWSUXbBvID2ymhMi4YpHFGBH1WDK0xjBBBVMePkoHcoIplmbiOoGS6JIMxUmYFjmWgOKCVQC96GI6HT9fw+w1CEYNouY/qsiAN8XIiWhmlkkHfYIY1r7QSCJaRGymQ7hnCzmbAyqN7JXQDzLCKaXjotkVVy3TKMg4DZgOJ6iB6sES4J03Tzg1MG78e9ZiZbP1LkZ6cTioUQy1vQlNNiukkQ6kNaOl2qgdhXCnCwYEGyoypvKgnsHtvwh9YwsZLj4MmHTWmgN+llFeo/vztTC05PDDHIjjYhzL+GK6LPk5fcgZ3nHM0Vx7y8bf/n38/JoQgZxdwhYfjOSRKOdYm2nisZxXrhrfTXewi76YRio2iCFTPRjg2wnUQrovqCfA8XEXFUb3dM4Opu7u2KpoG6l//BVQPNFdBt3U0W2WediT/pV/IC/mnuPHTnz2wC4tEIsF3v/tdbrnlFgzDYMGCBdTX1+P3+xkZGWHTpk1s3LiRBQsWcMUVV3DSSSeNdcijZGEhSZJ0YBNCkBn26Flv0b/JJtlpY9vgKYJSzsLNO6CAaqo4qkLR8SgmbHx5B03R0CsUoktMXE2hVPKwLQ9v90LCVFSZ1NT58Fxoa82Ry7qUletYapaewQTnfWAmldVBhlIFHNehZ2iI7T39FG2bT5y0mLWvDPDAgzs46fBZNE8OUtWos/GFJPf+opOmcQEax/vRzd2/4ib7LeadXEnz3DDL79zF079pY+rxM+nq3M6mF1ym6Uma+zfw+/OKzDs6zeSwza1/bMVqnwINi/l491NseqGJwRPnUNpl8tHvT2XO1CriYR+KovDCMwnuXraDQIPDx0+Zybjqv/3NKxRcbvu/LhadYvCxP1/M5btMbtzew5llk/FZJXZ1NrC5Jcri4xKMa0hiNQYpOnFC3eWEFIGpCFxFRytp+LDpKcuQ9adwFD+eG0FNFCmu2M7IhmEmTtapnxmF+nIS5RW0eVEW9AyhtX2A9TNUemJx6jM5Tu58jhqRQtUdFL+AkA8lGEEx/KCZuwsP1cBWTTo1P1tVk1Z0UoqOpSo4mo0wbHykiKkDaI5KxU6dyf4c9z/Sxd3tfZR19zOu4qMEs3CQFmJiJIqvPszaXB8RDAazLmt2vEjO2YoTSlLSE3iGglk2h3LfTKqSFs1tA9QlimiagTB8EFUp1SoUq1XcRpORmhC9wTAZ4adSSdNQSOB3oBSIUCQAgwL/1gF8W9soWSmSpk5a95M1/BTLAqhRDXy7Jw7QfCq6qWD6NMoqyghVxPCVhTHjIQKmi6/koaVtRM6m/8V++j0/Wu10JnZuJ9bXSCaSp6MhTVsghKIMccZim2JrjvSjWxhvNhKkGqVyGiQ8lGwen1kiVNlA0lFZ3ns/1W0rUMqOZ8VXFpPZ3I/oKaDnBXpJIesvUv3h8cz43K3EKqtYPjGBNZLg8PhMLq9exZrCFG47vIKTDz6Pk+sWvqUxWfsjIQSpUpau7ABtiR3s6FvPmuENdBX7SLgZCtgUEVh4OKrA81wUd/dU5DgCUXIZX3Q5zQ1wvBuhxfNjeDqKp+F5Co4QgI6laeQ0k4SmsksTtKoOu4RDh2cz5EBGDWJpUYQW4+DYkTQqDazLPE04WMHjn7n4wC4sXlUsFnn44Yd5+umn2blzJ4VCgcrKSubNm8d73vMeZs2aNdYh7kUWFtIb8TyPZDJJPB4/YD8EpX8fmS/7D6coSLTbDG23SXXtnoVL18DnE+iqR3JQIdJkMukEP7biYdsCn0/F51fRdeV1u7IJIUgM26xfk+bll4bpTvYzd345575/Oqah7bHfQ3/ZQW9fhgvPn41haAgheGZpgq2bc3zg/DoiUW2PfCnlXVY/NET/jgIHn1rJkw/sotCaworHyG4fIBmJkmtNMDv0ODccX0Zz6gm2p99HzFfNt7bej29bH7eo55GoauSL18zlyMV/63K8eUOGNStTfPDCBhKZIjc/spHGqjAfXPK3hVCHBiz+fG8/xdnP8+z6R6m8TyURWEWEWQwMe5wVrGLFUD/avGlEalUOnjZIeCq4AQ1XV0BRKLkaxbROKuljZEShuHUE54GXKAxBQ66GKAGGRIlBPYtiOkwJ5ik/q4XUWdMpL5aY+kwzKWM8z84pI+8L05hKU1voxu/lCLgFgl6RtD9MV7iW/mAZGS2Ih4auFjEDvWi+PgyviOq56LaCXlQxkwEqn04wodlHfgo89OIId6zsgZHVLMp+inETJ1HtjzHUX2JdOkFOD9FYGUaJKXiaSlWgnP5gjrYNL+L0bqex2UeVA0ZnLwwNM9zQSKY6jqe7+AsDhHN92JE4+YpqTFWhKjtMU7af8mCQZGAc2wI1JOIB1AqBr1ohUOERDHvoPlCyfoJboXx1jlDHIJqdQBVZVC+P4pVw0XE0Eyvox/IJCqEQebWckl1JsayFUk0tSlQQqCxROy6JvbKdncv7KTtiIcWwjzl1E8k85YDVTsHspX2oh1mnlVM9ziIz6Ke9rxtVhTkVizHcAL27Bigk8ojhpynbuo1OMY/t/+9Ipvm7mOGoWAVBIS3IJgy2bAuzJZCi7JQaDrv8RtIzJrK9pp9+u4KrCr0c3Jwkm5rCLtPlifoi2twFHDz5WKbHmqnxV7zj3aRKrsWOXBdBzU/ciBA1Qvv8HEII2tPdLO9bzQuDG1if2IpTHEJ1sph2ifGWwgLb4SBLoclSKSsFMBwToXh4qodQdk8vbjsKtqtiuwolF3KOoM8pMGjnSFp5PM9Gd2x8qAgjTtZnYvmDeGYYtBiWXkXWqKSkBgCVgGtR6WapcQoEGk4jWBrBl3iaLU2HYXsFvvKpj747CosDkSwspDdi2zZPPfUUxx57rOzaIr0pmS/7NyvnkRt0ySc8KloM/LG390VGCMGWjVnu/NMOdnQOEi/TKa/wMWFChFSmRMuEOCed0IKiKKRTNnf9vpeWKSGOPq4cRVFeN18KGYcX7x5A1RWef7aLxqDglbY8U5MFzMMraF+6iT/NyVCMR5nR2sbPeh9jeDDPstxJLIvN4qyLF3DR56eNHi+VtPn9zV18/NLxmObfzvnxlztY1zbIpWfMxffXoui+P/Uya06Uzzz9GcbtrCH9ygZCgRE6Osdzkn04WX+KvtZVaGU5SlNqGAzXIFyBioKuaYRLaeqH2ygbHmS4ABBnkn88ZXWNUBbCr5VAQKA0jJHuYU3XII7rUKOn2PStc2ieI2jI5BG99aSTc9jcVIaj7V7vQvy1AFKFQ6RYosoeIOhrxwkM4UvnqenKUzWYQSs42CNgpVRw/ARnVzK4sIktPWHuetajv201ncpyGgJnM2fgMPwjCinVxqqtZdo0k2mTVe64ZT1NDXVMnu6np3eE8eUVFLQgG/pdMsMlDBdCVo6Yl6U8WEIpZEh29uHZBQrlfoJFh4itka1sJKtoFHCwfC6enqZG7KBG7yQe9dMwvoXw5IPINExilxYiQ4ainsCJJhD+Ek7Kh9jiw9wEoayNnksTVBU0V6CHXEJqgYAygnCHUAsjxDWFkBEjKeKsqzyI0sFxJk5Lsu7WDvKlWkRVJYdoNUwK17Oj26Lod1Gq1mJV+zCjHdjeAJ7VRCFXhbOpk9lKDNOB5LCL02TCKRY2BsrdE1D6HWwrQVFP4UWSlM3Is25nI5vHJ/FNjPCer93GmkUTcGIJBpSp3Nj7GPHxAgIKXmk8GauMhOGyLVTi2XKHjdUmWmU9B1VMZ2H5dI6qmEWVP7ZP/ydtz+HJgVX8tv0R1oy0kraymIpOTAtQ5gsRNyMcXDmV0xsWMyv22lMwu57LI13Pckf7Y7yc2IJipYlaOYxiluaSxmGuyUJXocYCkQlSKCoMlwq0F9K0lzJkXQtTUdEVFUPV0IRCwAXTU3BdE9sxwfGT92K0BWsYiFZTDJWjmCFMoRArFilzLeK6TczMU6OkiBcHCdp9ZEWRPhR6XYMBEcesey8DI5vI5jvxNczHP9xKtJjkV7c9IQuLsSILC0mSJOntyudcOnbm2bEtx7btKVxHEI/+ba0HVVV472nV1De+9bECqx4YpLu9QGfHAOWGYN3WPEprimqrC6/hL7yoBPlusYOd2UacSIzf7TqYmoNn8qN7jxj9wuR5gpuu6+D0D9RSU+fb6znWtA7wwHNtfP7seURDPvI5l9/c2Ml7P2Lwgd99khlPnMtq36009tdySCbCUZNTtBYW0pVSSA28xDh/noBaxE8B08kyaDl02DFMtZ5gaDJKWRW1eicz2MAEtYhRCuMJnW6jjjZ9PD1aLXQ9hZZr4ygtx5MzWuj68KE0NVnMNvspGynhFkwsL4qjVOBqYeyyPHYsg1H08A2DklWxPYO85SdTCmErOnpQYJgC3RB0Z+OsfLFIx8vPk7F2sDM+QGO2hWOTn6LfS1GxZBaHH1HNiUcG2bi8hFUQTJwnuOZbSymlFRYvaqGtPU08pjNnSpTBoRRtXVlGLANHCZIpKoScfg6bqBIMCLr6cmx7ZRNu9y5CuRx+zYcSr0KLluNEyhHVjWjxejTHwc70kE9vxba2E/AXqatrJDR+MlZ1A27AxPBlELEUpeoCtqlQskK42RhqJkYkZeLPFVH6U2hZi+jEADRnSeS68G/JM75d0NeVZui4ZqJd2xgcGSIz/lgsv0lmuJZp8SrChSJiu06p/SUiTR0EF0xH6Xoco7kE/gAlM06hrJpoTYxBq472QhXRP1noisuk8c2Uhwxc2yGlKxRdgah7mNUr4+w8vkixlOXsax7igSV1hMIeVZk4l7U+jogGKasN4CsvgqGAU4FnVyHsKK6nkVJcdgRKPFteYktcxfSHqAvUM7F8ErWhGizVxdE8HFyG3RwbrE5aS70MWUnSTo5gCRb32pzU52NCMcCOsMWKygxrYznazBxZoVLtr6UmXMPsssmYikHazpGx8iTtDH2ZTnz5FDVph0PyZRzmhJjgWmAXyJc8MkVBdylHVyEFuSLVVoSiVU6/GqLTDyOKC45AsUBxdk8NnjN8lIIVuMFyrHAFRCMEfYImPUezP02ZkkFRi+Rcj5ztUsyXSCZdMimXVM7FLoFiKcQ8hTIBdeEq4gctpq5tNSYuPeMmMGHVMrAylFSLU5+ShcWYkYWF9EY8z2NoaIjKykrZtUV6UzJfpH3xVvLl5T8P8sLSBE3jHdz+FMNJh9XLOllQXEv9pB30dUylza5juxZGOCFufvksQvG/tX488sAAlVUmC/9h1e2/196b4qZHNnLJGXOoKw+x7PEhwhGdgdhGfnjrHTgv1jEQXUFTXzW3hYbRKJJH40V1PjtFGSVP4Hg2tudgGmEafRoNDFBHD5UMo3sKIMj5YSCmkzAUhlUY1jVcx4eaPojuHo9o4jkurnAxNNgZL+P+Q+fQNz5C2MzhE0UCxRz+YhG6FKxUjBKVYMaIuDpawUcp7WHnRvC8AiXNJa3kSboFdiVfIViM4s82sKVyM/nIIKenr2FIS1G2cD5furiGgQ0Owz024yZDdrDAcEcRX0jjpa2dbNzaz6LjxrHg5FoeebmDow9qoHs4S2tPClU38bQg6Y4ApaRHrW+IXa19OAWXiGNg5hx8iU703jWYpV6C5QFsI4KXVxHBMObBMzDmHw3FMGYih08MYxjtOOzACNiogTCivJa8v4y80LBNi3CdQA9nyIsk+aJNJm2SG9axX8kRW5MmmjbQawqkF1hM+MjhNG+czarWYczOl0mvfR7frEVM2vQiSm8aW42R88Wx9dkoTEKpGME3vwynp5u2YJbemI6+w0Jxy9COLqP6vi7qD1nMhCkmA1aBoqFCPovR04Ft2Sg106ioeYlV93u0X+QnvXIlp92xnfuW+PAFYrhiEgsyQ5zQ9xKV2WFEwCQQ8xOLC8xQCXwOKGFEsRqcchQvAEIfXbvH9RRcoeDsHuOMpwgMFXRVoKoCVQEVDyjgGD0QGEJTfShKAOH6cBwfPRj8pbzIU7EUOV85NSJMs20ytRSiyfIzvuQRtVIUnCz9doF2u0TKsVEshXA+QDatshPYFVEphASmqVAb9FFr+ImpEfK+ajL+EGlfmKy+u5gPC4sakaTWS1HrpDFSGfqHSwyP5Mkni+h5C6NUIOxYmK6N7tfw6suhqZxYXTmBqInPVMGL4DozKJhT0UpPk/Ug5WugZftzeCmVQtKjWKzitLuvlIXFWJGFhfRGHMdhxYoVHH300ej6v24KROndQeaLtC/ear6svH+Av9zTz6d+OJl8T5alP9vIusdeBtdlxAyQq6impaKGc740hTkn1o0+bvuWLKte2D2u4s0MJgv8/L61nLRwPIdMqeWGn+3i4s+OR1E9LjnzYR7z3YTeazDNqsWJBajyotTYDlXOMKHSMFErQ1SoKGjkfeCEDLyIwVDMzwvRyURbK4j2lbDdHCE1RFSPEtfK8asqmtPDcDTDC55CvvcVmkyTg5QsU4wCMVNgmCpWIEzBDFHSTLysRXYkQ0/JYlteJekqFKMKbn2MoFdLYCSAsB1sxcbSbVQnQmt5P4nwIDmtlRPsz5EJhPDXTees6VEGN+WJRh3i1Tr100I0zQpROc6/u/uVEDz8l1buvnMHWlZw3gXTcGs1WupiNNdGR1uG+gdy3Hr7dtq6whx9bIz3Hh2nMry7wOvtK3H/fR2se3gz/nUrMUbaMcIaVYvnEUgPkd2wE01zic2MoR40j0G3hVKpCuEF8Plc/OU5ArEkvlCWjtbNNNbXUnRtiJZTjJVjNBjEGkGEhxnIZMh36xQ2KKgP9qB1dBGZO55oZR399Y2IdbtIdL5MzZHHM8mn0qhEsYczbO9P05PWcLosdFvHPDyCXmFSSmbZcVCQUCzDlMd3weEfJLxrM5moxzi7n9qmOgrmOLJejFIpT3bdMvLjJlFTt5GtfxCs+2gI8eB9zHrZ4elDLObGfaQSGdrVBsL+CUwuZJiQ76cql6Ayk6Y8nSOgeYQqbPzVRfSwBYaLEAq4Kp5rongmimvguT4UoSFcBYGye/yE7uDFR3BdBa8vzvakIKEapEwdOz4NJT6NqmA5Zb7Q7pYksbvo9RDYCGwBI45DWyHJUD7BUD5B1iniAEJTCPl81AUrqdfLqSsFMIez7Ch2sjmQpTegoXgOkfQAocwQoVySoJVHqAaWHsTFh99WiVseZSWBDwVVNSgYARzXAdvG8zwQHobjoGERUj0CJuj109Eb5yJ0lVJtHLHhWTKGj+y4ScRfeAwzVk6kZhZmtBZfpI/DrrxMFhZjRRYWkiRJ0v7u6T/18eQf+6lq8nH06VU898ctbG1NMGfBZOafUM3MJWWo6u4vuZblsX5NmheeHuHjl4zD59fe5Oi72Y7LH5dtp28kx2F14yhm4PiTqli/dJifX/MCL488gRNZi0AwHCyQVy1AQUVFEwa6MNGFjuH58bkB/G6ASMmPvwQ+28DWNOygD7uYxbNL2FoRRfMIaWEaRQsNpQr8msJAvp+hYj9Fr4huluOoKo4ooiDQPZugoxN0/IhoOcWq+t0rx+c8XF3DiqgMV1mUIgaGESVs+RgYfo50rhs3l+e900+kc6QO16phfkhl3tER5p4Yo3ZSCEWFjvYCw0MWB82L7jEepX1Xkl/evJaRXo+JYY36uiCarpBMl+juy1IsOkyfXIGpa7QOBMiUDJoqLSwrR0/C4uCFVZx5RjNlFQGsosV9V9zN2t8/g+4kCM6fgXnkEgrPrcFr20Go2qGhxSDgA1cNUTRayKtNlLxyiMbwN/jRG/zYlT48FXw6+PxQUD1UzaG6coRefysJK0t6nc7wLx7C1+gye+4cttUdSjK/juIDz9I49zjCSzwCZo6srxKvWEskGUesq2Oqq7Kht4f+2R7lRonp+ThtQ2UYL74M86uozJsMhGqgugQhB91RwBREsgbmppcZGldDecUGRpZVsXKhoPz+3xIcbqK1UiFT00fAb1HhWZAvkCqpeEqckFGNzyjH73nEM4M0JjqpSg8TsvJEnDw+28NVwrg+E8sfxg74UQybqN6D6rlYoQoywTp6vXrWV1bwSjROygsQzCcxPQ8PF1VTKDl5FMXFrwoihoqd6aeYSYBlodkupqNjeAFCIZO5dTrT61XCnoe1M0XnjjTpviG6mqaxbepRFMon0ESU8RmFhhEFX2YEJdODmu/Bp+bwGRa64aGVRcnH47R7QbYWDLbkFbJWGp9uU1mu4jMUNEXg06NoahzdC1CuBomg43dcEsN9ZNUSseZx7Fi9BS8exWwcB5tS1IeqyYsSW90hinGbyojDb77/LpkVyrZtTjzxRG644QamTNl7pc/9kSwspDfieR69vb3U1dXJri3Sm5L5Iu2Lfc0XIQQrlyVYdu8AcV2leUqIhWdVoflUPBf6+0q8/GKSbMZl1twIcxfERteq2Bc7epL8+i+bKO708ckPTWHixDDfPX8lebWfbCxDUzCA+WiWkOFDL/dh6TZJI0232s1gcYBCMYPl5MipeUYCGTJhlUCuHl8xiusropYCOJE0xXgKW3gE+vyECyomGpahYRAg5IWI2yECBY+IaxJ1QhhKiJIvxkDYoMuXJ6MMUaAHtBKu6eCqDnrRQLFV8MAVDq5wMUoxnGCBebUnkytOwLZdvn75RI44LobrCF5+KcXWTVkKeZdxzQFiZQavrE5T1+DnyMXlVFSZABQKNrf87hU27cwzOFTAryvMnVHB4kPrmdAcRdFUNEPDcgVPvpTg2RfyBJUAC2f5CJKjt3UIO1+icWKMuUfWU10fYsVvnmXFzx9DDHZTPTHIzI+eSSKhs+vxtRSKWZyYhr8mgN9QIDOCk0qAqMRSx+HqDQQry6maX0u4xU8+IBjIOyRdF8vwmDIty3D5OmLuePrvX0NqWyfHHvxV1pcl6N7+Mk77WmLxWRgHH85h44McXl/G46+sYWCgm66ePAONTbw/Wk3X6nKS/Wliap7SlAAxXWOwSsHvCqJ5P35Hx+9T6OjMI+rBTChE25L0jfcIRJ9mZGsNA+VxKv58L2VRjYxRyVDSZCjWRzIySMkoEAuoNERMgjgUcjYqEwiFF2DblQyPJEkVCxSMEkLNo3ug2wpapAylogp0H4omUMmQ91IUig6lfImAozA3MJHushCe4TKnr4256x7FLoywMxRge6SMRDxKoHoSobIGIrqgnCx1fouIoeDlPDJpm2y6hIWGg8kmXxmdikl8aIjm7m78VgELBTNcTbhiAoFQFcJV8FyFkuMyYqcZsdMoXg6fmyGuFygzIKpXYtgxhONHCwbwVB/CNXBKHl7JIRNSGapUySt5LLtI3bg6nKJKptfFGG+ilsdwrBTDkSQ5LYdWUAlkDEoJk0zaz++uOeLdUVgAVFVV8dxzzzF58uS3dZxrrrmGe+65hy1bthAIBFi0aBHf+973mDp16ug+QgiuuuoqbrzxRkZGRjj00EP5xS9+wcyZM9/y88jCQnojjuPw3HPPsWjRItm1RXpTMl+kffHP5ovrCl56boQd2/KoKmiagqoplJUbzFsYo6LSfPuxuR73LN/B3X/eRXW9SWBAZceqYWpnB8h0ZzEVhaaUS8zQcDyB6wgcR2DZLo4PrJYwOR0KwyXKG0K0HFxFXUMUo6RgIBjsTdC+pYddbYOUagbp8LbRt6MPx0vhKCUUT0EoBorwIRQfrmIAu1ehVhRAc0FRiFoTCJTGYThlKKofz6fiGSpoHkL1UFSFnDrElJo60tk4AdXiyi8dyoKZZWTSDrff2s2c+VFmzY0Qjuz5Huxqy/PM0gSFgkvDuAANjX7qG/0ks1lqa8JkioINrVm27Mph2wJdV9A1BUNXWDAjxtzJYYSAzdtsOnscUhmPbNYjPVKiryONT+RZckIVhx9VzpqHXmH5L5dR2tlBNJRhxknzGbdoPvlBl65V7QjTgwi09e6gprYK8jmKQ4OU+ofJDpkUrDpKahWEDfQ6H8WJVQzXlRE4qJa6+a9QZkRp/83DRKZMojp3Ov0+m6G2DJ71AMVtNo3zJyLaXiaz4ES0CQ3Uqhr6YyNsfslPja9Iw/QghcAITS0TaA0Eieppxh3XwbCTpFhy8GwNT3HIb4lTqcwnP+xRt2aY1soAFWWPsy7hJz7UQM1WgVsYwRvZiO21UUDBdVwydoFuv00irqL4NcaVG0yogcqYQ65kMTAiyPb4yecCaBOmEJw+jzxJcqUERkknpMYxXZOBVC9DpQHmzplDTW0YLd1Lxc71mIkEG0OT2BVo4ERnO9PtHoxcAqdoQZmJq3hkcmGGvAaGqSKlRnFLKtpQBn9ihK3BGG1142kespguVKI15eh+HcXrQym2oznD+KIqesRD95lobhhVKQcvDp4BfgVhCvB7KKYFRh7Xs3B1B1c4aK6DKmwU10FxPVQbFF8AK1RN3l9GulQgrQnscB2Oo5DqHUEtgC+r47M0fI6F7ncpVWrYhstXP3LBu6ew+MIXvoBhGFx77bVv6zjvfe97Offcc1m4cCGO4/A///M/rF+/nk2bNhEKhQD43ve+x9VXX82vf/1rpkyZwne+8x1WrFjB1q1biUQib+l5ZGEhSZIkSa/NcQR3395DeYXJc79rQ59uY6VdUl15Bnam8FwPzVAJhHTicT8+v45VdInG/YyfXEY8GmSgI0cqY1FUXLSoSjTmQ9EViq6LZbukd2YZbstQWx2lviqMowrSlGgv7mJHcT0DhQ6yzhCWnUY4FhXZ6ZSlp+G3yzACPpRqG6qy6NEitpkmY49QcIs4ah5PzVAenIzdeQKLZzVw5eWHousa3Z1F7vtjL2edV0dd/RvP1GVZHr3dRXq7SvR0FRkeslAUePUbmWGqNI3zM2FykHHjA+jGm7c+WbZg67YCTzzcT+uOIpV1IVqmhCn19dL5zEacnl60QoKyckHDzEYqpzSj4KcwWMAplAjXx/GNb4DqKlIFnZGkSyGbJ909TG9rmuF+i7LCEHqqj8yk8QQ+WEKbnGf4zgFqasoJNzRQciH/goVT+Qptq4ZpOGoJNZEI0U0jqEo9CbOcmvokpaEOvHgN9ZEm2kMaxHfgVr6CfUcFbAqh5HR0XcVf7Sd8sUW6rpdxuSPpHfDT/OwGOic2Ux19kjUDjaQrwxjdQ1Tu9KgfqUJXfSi6AZqKpysUQh6JMpuuYjsdXZsZyg6ihgShcj/ldQ2EI40YQhDJlYgVPUpeio7cABlHEAxEaKqpp74UILMJBvuzDMRKlJqrMBpCxIwi0a4eeoZUmrb3ouaDjA8OoSZK+AqgewJbcSgqZSiBOohW0TWhis3NYWpUnYlYhJRewgwRjubRDBc7p2BrIbRoFC9nU+pLUMzksHQDVxWgeghTpRgwcKImXrmJFQphiQieiOD549hKCEtT0TWBZgg0TaA6UCo6KOk0ocEkvhzEKkIEt3ZRk+wm5i/hhPwITSEcVNHKBPgdhBBYOY0ln/6fd09hcemll/Lb3/6WSZMmsWDBgtEi4FU//vGP/6njDg4OUl1dzfLlyzn66KMRQlBfX89ll13GV77yFQBKpRI1NTV873vf45Of/ORbOq4sLKQ34nkenZ2dNDU1ya4t0puS+SLtiwMlX4QQLHt8mNZVaQI5j6pGHzOOLqNheggQJHsLtG8YYcfGBJblEq8M4ghBseBQzHkoqo6V8SilPGzbI50v4QVcorUGLTPjVNb7icZNerenaF07hGt75FMOuaSDlfNQUTENDU8IbE9QOynK7ONrGTczjK6q9A7n2NWbpqM/w1CqgALohkp5OICiaCxb3sYHT5zGuWdOR1EUXlmd5oVnRjjvooa9Win+GaWiS8euIu3bc3TsKuI6gkhUIxLViUR1ojGDymqT2nrfHuM2XuU6HptW9fPSij5SWagYV0ExW6S/tZ/hXSOU0kUMHPwhQHOJ11USiMcIqR5mPofp5rGFQyLnki16lFerVDdobE9PoSdhMj4yyMi2l/AWlcGcLAPrIkR7VZRohNLh1bDOxusokehej/DyTDrxeMprA+jdvcRryzn8sBYMwtyzdifZ8pV4m9M4T2sUSyki5eWE/VGUlCCxs4dg2RRih5RTOK6NgDOOQmIS5m1PYC05jMnNy7C6s/Qmy+jzN5GOBfBsC6/ooDgC1VUwXA1d1VF1DXQF3VEw1TC2a9O/dTN9Xe0UqxSi46NEgyFiapiyaC1G3oRECaFkEb4SeS+HUlLwq0E004eim2AYlGIGww0GA9tLNG0YYsraPJqtoqKCroOho3sJsuPS9MwLUBVIUe8mUFQdtxgi71YzEm4h66vGGspCIoevEEG14zhNOv4JFtGQQDgWllXAsUvYikbKX44d8FNSXAQ2iiYwNAh7gpgrKPP7KPOHCWsBgpgYqkpXLxSGbEQmixeFw0zwWzbDvcMMYmEU49QFTXoYpivikA2ruHj4rAyXfPI9757CYsmSJa97n6IoPPXUU//UcVtbW5k8eTLr169n1qxZtLW10dLSwurVq5k3b97ofqeffjrxeJzf/OY3r3mcUqlEqVQavZ1Op2lqaiKRSFBWVobrugBomrbHdcdxUBRl9Lqqqqiq+rrXbdtG07TR67qujy6I9GqTt+M4e1w3DAMhxOh1z/NwXXf0uud56Lr+utdd10UIMXr9tc5DntO+nZPjOLz44osceuiho7cP9HN6N75P+8s5ua7Lyy+/zPz58zFN811xTu/G92l/OSfLsli5ciWHHnooqqru9+e0dVOGTevTDHSUGNlRoDBg4wtohMt0ohU6FbV+hCMY6ixgF/86FWhUxYgaCB/YCui6RkW5TthUcHMeg50Z0gmbQtahZLnYlotmqAQrNSJ1OuEag6xVJJkpAQqu66Gqyl9nbPLQNQ2/X9/9emkamqqB4qFqCulcieFUgWMOH8eUcTVsWp9iV1uJ8kqDU86oxB8w/yW55zgOuZxLPidIjlikkw7DgzY9XQUcRxAM6UydEWT+wjiGued7ls0U2bxqgG1rh8hlimi6imoXSe7qJtU5QmZgBL/QMESekmqTtjQQEDeKRJUihgelrEqxKNANm6rp4+mKz6OjWI7PHWH6qSr2vHbanikwddHZxHsjDMeSjKxVKT42hJpcz1B+JaKqxOQjZu9eWbtKR5mhIfwZBn83jDGoUFYdIVYXpdjrkMsUKJSy2MIjmmrCH2ik+YhmsrO7sJv78Pqmk/nZRgamH0ZDi0J1bS/xiiFMn4Xr6Fi5IG4ugFoI4hAg6RbJpAp4aQs15aF0e3j1dagzg/iiGrGsDyOrM9A/QqKjm1CDStURBkLN0Lu5G9dRCdVCvCFPLFpCx0W1XLySjVtysId10rFq+gJV2AWNaq1IqJQmXEyjeTaJYJj0kA9jdQl1UEUpaBS8Mgb1Wmyfih5zIBzAHF+GXhmimC+Sc0t4Pg2EDp6C5oNwQCVkKugl8OVKBFJFwtkCRs5BG8ziDqQY6e4nNTyManloroemqag+HaU5gnbyLKKzpjB3aiXjo7B9Ww/9g0UyWwSpdd0kK1Xc2XG0ZBFzfQK6R7Bci5IB3136+bdUWOy/P2f8naVLl77u5Z8tKoQQXH755Rx55JHMmjULgL6+PgBqamr22Lempmb0vtdyzTXXEIvFRi9NTU0AbNiwAYDNmzezefNmAF555RW2b98OwJo1a2hvbwfgpZdeorOzE4DnnnuO3t5eAFasWMHQ0BAATz31FMlkEoDHHnuMTCYDwMMPP0yxWMRxHB5++GEcx6FYLPLwww8DkMlkeOyxxwBIJpOjr9nQ0BArVqwAoLe3l+eeew6Azs5OXnrpJQDa29tZs2YNANu3b+eVV16R5/Q2zwlgeHgY4F1zTu/G92l/OafOzk4WLVrE6tWr3zXn9G58n/aXcxocHMR1XXRdPyDOqa5RYIbX8skvTeQT361j0Sf7+ez10znsnCDFaBeOT2XYyVCsH+Dg82qYeqpGxZwh3vuheuYfY3PQwkHO/1gj0aoRetPdZDSVncUsiWCJyMxynDoPY5JB9fxq0rrFcMYjPRykY3MBkQpSadZD1iHkRYlSy0iHDZkweqGCnq1p1EKIuFnJrs2D5PsDBErV5DssNr3gsPL5BDs7Xub8j9Vy8hll/OWxR/5lubdlyxY6O7dTV++naO0gVjHAyWfUMOfQQY4/1eX959WzYf1Wfnj1Bp58ZJClT/3tfXpp5XOMn+nn/M/PZ/yhGU65sIUl587GmOLj0I8fwxGfOoXSlErUgw6ifMYCIrEGJk2ZQ/lBi+huPBj7qDNp+PiZ1H5kJpWHT2PX+vUUHruOw8zHmDlNsPnOLTT2HULFQQY7V/yZdPEvBO+/k/Dg3dR8cAeBy6I0/L+jaPjMwaQW5MkucSjESuTXd2OsTXHYyU3Uzo6SGArTsUlh0IZiPEBgShXh5hBDsXX453ax7rE/oz/fiHhkBlpFB6Hvh6jdtJzUdXew9uo13P8NizuuaeQv/1vHmrsc2l/qYqBnHbb3AmXmBprjnbSML1GxyIdyThRmpQkUsphWip3ak6yrvo2hI57G+UAfQ3MH2NzTR093mrImlXHT8gQ0h/RLgue+m+Key0b4w1eL3P3DMI/+OsrqF/vp3vIyemI5hrmOTrudl0tZHhZh7lFq2ehlGaluZ+CELrrO6aP9Y8P0XdqO+PyLmJ95AePclRjHP4lXcyelzC2Iwp/wOQ+jd92FtuXX+Db/H+bK/8N69AZSf7iZ9B2/o/eeO9jx+J9Z9fhDLHv8bh5/8SGWdjzFZnMjxdkuI/NUuudqdCz0sWWWwjojwYY/PM6Gz/6Kez/yC37yiT9y54/X8sTvtrBuYDttsxOMRLYT2vY8I2vuolt9hP65LzN07Hqyp2/hrTogWiwAnn76aW644Qba2tq48847aWho4LbbbmPChAkceeSR+3y8z3zmMzz00EM888wzNDY2Ars/MI844gh6enqoq/vbvN0XX3wxnZ2dPProo695LNliIc9pX87JdV127NhBS0vL6DEP9HN6N75P+8s5eZ5HR0cHTU1NGIbxrjind+P7tL+ck23btLe309LSgqIo74pz+le+T7YlGBkpEQzqRKIGruse0OekKApbNuR5dvkQwaDO5Glhmif5qKzyoWnaXuekKAo7d+6ksbER0zTp3FnkuRXDjPSXqNZLaJksqieonBijbmYcTdXIJgq0rdrFS79+kELvMG68mpTn48j3xchGOskbWcrOnItvapzKQDmaFaJ9i59UIo5l2fiVLAcFaxl+Yjur7n+GEStOw5QKGmuGmbKgCX8kiBn04yoG6zbtYsP2HvL2RibPO5SRp1VU5RhihwiiR/eTbepCLaqoIz6Ubh1vh4cjFNyIghsGNyRwKwTC76HrRcJqgbiZI6RbuI5LKgMjAyYU/KiWgmMNIhgkHDARIsDAgI/hbVGM7jwj3bsIV+hEa4ZxCj3Y+Qwq4Ck1pJXjEbaf6PBagrk8Xk05xfkNCFPBbBvCIkKueRJebQxTK2EmsugDBZRsEUERfBqKrqJ4BXQS+PwJfJqLXjkRpWEKXq4Iw0kojKAYNqg2is8Gv0AN+iAQwlH8WMLEM/woQQM1bIIH9pCN1ZvD7cmjZIp46QJK3sGo0FEm+aFCRxclVM9G9TQ01cRLhvAyQdy8H8UOopsBrvnp2e+erlB33303H/7whzn//PO57bbb2LRpExMnTuSXv/wlf/7zn0d/+XirLr30Uu677z5WrFjBhAkTRrf/s12h/pEcYyG9EcdxWLNmDfPmzRv9gyRJr0fmi7QvZL5Ir8qkHVq35WjdmiMxZKFpCrqhousKuq6gKFAsunR09FBTXYPrKjQ0+Tn0iDJq6nyjx/E8wUBrkp4Nid1dysp8BOM+gmU+dq16hgd/9heG3WkMDDlMObSFcKWge/P9TDjxfNTaGDgqPk2j2Jcg+8JaMq07GMn4EZE6qsbHaaodZvbRM5n/vqMx/b69zqN7xyA/++I9DHgvMu2syVQ01pPcmsRKH0L50QaO7uKYRVy9hKuVUHSBhoYuDHTbh9rjYe/MU9iRpFQoUHRHUBsCKGUR/HEPQy9gO0U8W1AYguyQwLahKh5EyxbYsWoruWGHsF5FONgMbhWu7UN4OsIVeMJF8TyEbpANV+A5DtglPAXcgECZpkPRIbBtB8GOdkxKqJoLhkpJ+ChYGoqiYhgKvvpKzMYqjMYyzEofPrVEoDgAdoGirwLbV46dAafXxtHCuLqG8CmoIR1N13aPK8nZaMUiSiaDz3TQNHX3jw5xi2JNEq+pBAEPJ1GisH4Qpz2P6DdxRjQQKkbAxjBH0BUL1dIQBQPVCvPjDT989xQW8+bN4/Of/zwf+chHiEQirFu3jokTJ7J27Vre+973vmE3pb8nhODSSy/l3nvvZdmyZXtNX/vq4O3Pf/7zfPnLXwbAsiyqq6vl4G1JkiRJkg5Ynrd7+l7HEbiuwHMFpk/FNFU0Tfmnj9u1bh0rrv8taWbTtnGAVMpBj0TJFXqJxcKIAtiZPL6giRErxwgHKY/lqa2FKYdOY9bxh9C69mXWrViKXSqCouDzByivq6d+QguzjjwaULjv+he599Y/UDVRY8JJE/FVxRFmkkAINE1H0zRQd68VYSVsXEtHCA09qqPHTRS/ClgYpks0phHyR+h9WaNztUUhoWDnbfLpPoZ7dpDo7wXXIRKNMGHSBN7zwROZd8xCCgWV9h15AgGVUEQnFNbwmwrCEwz1FRjqydHZUaBk2Vh5i1LBQlM8VAWE5yE8l1zWor/XIpvzqIwXqPAPIKwSxYJKqaiQSzlkkiUySQfPjGI0VWPUBFFDClpIQYtoqGETkc2gZIfw2RnCAQ9/UEEYGo6i4XhgFx2ckokQQTDiKJZGsGBi9PgRKRvbTOHFRiCeRAs5aEYJRbVAMdAJoxXKUNMVqJ4JwQKfve79757CIhgMsmnTJpqbm/coLNra2pgxY8Zov/U38+lPf5rbb7+d+++/f4+1K2KxGIFAANg93ew111zDrbfeyuTJk/nud7/LsmXL5HSz0jvGdV22b9/O5MmTd38QStIbkPki7QuZL9K+eKfyZXjnTpb//OfEGhpI9Q7Qva2PvvZBCorAMlz0YJS68dNpOWgyjVMrCZSHyGdS9OzYTmpokOmHHM7soxYTisUAKObzjPT30b7hFdY/u4IjTjuLmYcfwWBPlv/71j28/MyTNE+spXJSkMC4BvRICNVnopo6iuaCl6OYSjDSPUyqz6GUrSASiRH0BUn1ZxjoSlAq5tDNPK7Vj1NKomsuFVWVzFgwjyNOOp7GSZPx+UwyGYcNa9PsbCtQUWnSMiVIqeSRy7rksg7JEQer5DFtZpjZ86PEy4y9Xp+BvhJrVqZoa81TU+fjkMPjNI4P7LFPZjhJ7/YO+rZ1kBpIUMzkSQ1mSOzsJT+SwfD7CETDBKJhKsbVsPCsoxg/bwqq+sbDpdPDOXq39zHc1k7rszvpfCVPoWiiKVF0EUFTwyhCQ1ENNNWHYqgoukAPumgBC8OvoPkEF9/0Llogr6WlhRtuuIHjjz9+j8Lit7/9Lddeey2bNm16S8dRlNeuyG+99VYuvPBC4G8L5N1www17LJD36gDvt0IWFtIbcV2XV155hdmzZ8s//NKbkvki7QuZL9K+eCfzpZTL4RSLBMrK9vqym0ulWLdiKYNdnUTKy4mUlROOl1E9bjwVtXWvc8TdrGKRZ+6/m/YNr3DM+8+lZfZcBrqSXP3fP6GjrQu/PwCui3BtPMem6Niopg9/JEK8shrD8ON5/LWVxsYwbPxmAtwswUgZNRPnUDthLv5oNULsbtnxPBAeeEIQCGjMnBOheWLgdb9H2rbH1o1ZXlmTJp1y0PW/7ee6UF5pMH9hjImTg697jH83zxNYeZdizqWQdtB0Fd1UMHwquk9FeFDKuxTSNgOdSead0PTuKSy+//3v85vf/IZbbrmFE044gYcffphdu3bx+c9/nm984xtccsklYx3iHmRhIUmSJEmS9M7JpdM8e//d7NqyiaqGJmYdcRSh8jqSg2kK2TyZkRS5VIZomR+nlCY93EdyoA/XdYDd3aXCZWXUNU9k0tz5VDY07jdf8vd3+/K99oAoLAD+53/+h5/85Cej3Z58Ph9f/OIX+fa3vz3Gke1NFhbSG3Fdl82bNzN9+nT5i6L0pmS+SPtC5ou0Lw7UfBno7GDDc0+zc9OGv86KpROKxQiEI5RV11BeV095bR3lNbVochKDt21fvtceMK/21Vdfzf/8z/+wadMmPM9jxowZhMPhsQ5LkiRJkiRJ+jeqbhrHseecP9ZhSK/hgGmxOJDIFgtJkiRJkiTp3eBd12Jx/vnnc8wxx7B48WKmTJky1uG8qVdrtXQ6PcaRSPsj13XZsGEDs2bNOqCanqWxIfNF2hcyX6R9IfNFeite/T77VtoiDojCIhwO8+Mf/5j//u//pra2lmOOOWa00Jg2bdpYh7eXTCYDQFNT0xhHIkmSJEmSJElvXyaTIfbXKYFfzwHVFaqvr49ly5axbNkyli9fzrZt26iurqa3t3esQ9uD53n09PQQiUTkjAPSXtLpNE1NTXR2dsquctKbkvki7QuZL9K+kPkivRVCCDKZDPX19W+6bsYB0WLxqkgkQllZGWVlZcTjcXRdp7a2dqzD2ouqqjQ2No51GNJ+LhqNyg9y6S2T+SLtC5kv0r6Q+SK9mTdrqXjVG5cd+4mvfOUrHHbYYVRWVnLFFVdgWRZf+9rX6O/vZ82aNWMdniRJkiRJkiT9xzsgWix+8IMfUFVVxZVXXsnpp5/O9OnTxzokSZIkSZIkSZL+zgFRWKxZs4bly5ezbNkyfvSjH6Fp2ujg7cWLF8tCQzqg+Hw+rrzySnw+31iHIh0AZL5I+0Lmi7QvZL5I77QDavD2q9atW8dPf/pTfve73+F5Hq7rjnVIkiRJkiRJkvQf7YBosYDdrRavzgj19NNPk06nmTt3LkuWLBnr0CRJkiRJkiTpP94B0WJRVlZGNptlzpw5o92fjj76aDmDgSRJkiRJkiTtJw6IwuLPf/6zLCQkSZIkSZIkaT92QEw3e+qpp+J5Hj/60Y/4+Mc/zsUXX8yPf/xjUqnUWIcmSa9pxYoVvO9976O+vh5FUbjvvvv2uF8IwTe/+U3q6+sJBAIsXryYjRs3jk2w0pi75pprWLhwIZFIhOrqas444wy2bt26xz4yZ6RX/epXv2L27Nmjaw8cfvjhPPLII6P3y1yR3sg111yDoihcdtllo9tkzkjvlAOisFi1ahUtLS385Cc/IZFIMDQ0xE9+8hNaWlpYvXr1WIcnSXvJ5XLMmTOH66677jXv//73v8+Pf/xjrrvuOlauXEltbS0nnHACmUzm3xyptD9Yvnw5n/nMZ3jhhRd4/PHHcRyHE088kVwuN7qPzBnpVY2NjVx77bWsWrWKVatWceyxx3L66aePfhGUuSK9npUrV3LjjTcye/bsPbbLnJHeMeIAcOSRR4oLL7xQ2LY9us22bXHBBReIo446agwjk6Q3B4h777139LbneaK2tlZce+21o9uKxaKIxWLi+uuvH4MIpf3NwMCAAMTy5cuFEDJnpDdXVlYmbrrpJpkr0uvKZDJi8uTJ4vHHHxfHHHOM+NznPieEkJ8v0jvrgGmx+MpXvoKu/20SK13X+fKXv8yqVavGMDJJ2nft7e309fVx4oknjm7z+Xwcc8wxPPfcc2MYmbS/eLWbZ3l5OSBzRnp9rutyxx13kMvlOPzww2WuSK/rM5/5DKeccgrHH3/8HttlzkjvpANiutloNEpHRwfTpk3bY3tnZyeRSGSMopKkf05fXx8ANTU1e2yvqalh165dYxGStB8RQnD55Zdz5JFHMmvWLEDmjLS39evXc/jhh1MsFgmHw9x7773MmDFj9IugzBXp791xxx2sXr2alStX7nWf/HyR3kkHRGFxzjnn8LGPfYwf/vCHLFq0CEVReOaZZ/jSl77EBz/4wbEOT5L+KYqi7HFbCLHXNuk/zyWXXMIrr7zCM888s9d9MmekV02dOpW1a9eSTCa5++67ueCCC1i+fPno/TJXpFd1dnbyuc99jsceewy/3/+6+8mckd4JB0Rh8cMf/hBFUfjIRz6C4zgAGIbBpz71Ka699toxjk6S9k1tbS2w+1eiurq60e0DAwN7/WIk/We59NJLeeCBB1ixYgWNjY2j22XOSP/INE0mTZoEwIIFC1i5ciU/+9nP+MpXvgLIXJH+5uWXX2ZgYICDDz54dJvruqxYsYLrrrtudAY6mTPSO+GAGGNhmiY/+9nPGBkZYe3ataxZs4ZEIsFPfvITfD7fWIcnSftkwoQJ1NbW8vjjj49usyyL5cuXs2jRojGMTBorQgguueQS7rnnHp566ikmTJiwx/0yZ6Q3I4SgVCrJXJH2ctxxx7F+/XrWrl07elmwYAHnn38+a9euZeLEiTJnpHfMft1ikc/n+dKXvsR9992Hbdscf/zx/PznP6eysnKsQ5OkN5TNZmltbR293d7eztq1aykvL2fcuHFcdtllfPe732Xy5MlMnjyZ7373uwSDQc4777wxjFoaK5/5zGe4/fbbuf/++4lEIqN9nmOxGIFAYHTOeZkzEsDXv/51TjrpJJqamshkMtxxxx0sW7aMRx99VOaKtJdIJDI6XutVoVCIioqK0e0yZ6R3zBjOSPWmvvjFL4pgMCguvvhicemll4rKykrx/ve/f6zDkqQ3tXTpUgHsdbnggguEELun97vyyitFbW2t8Pl84uijjxbr168f26ClMfNauQKIW2+9dXQfmTPSqz760Y+K8ePHC9M0RVVVlTjuuOPEY489Nnq/zBXpzfz9dLNCyJyR3jmKEEKMUU3zplpaWrj66qs599xzAXjppZc44ogjKBaLaJo2xtFJkiRJkiRJkvSq/bqwME2T9vZ2GhoaRrcFAgG2bdtGU1PTGEYmSZIkSZIkSdLf268Hb7uui2mae2zTdX10ZihJkiRJkiRJkvYP+/XgbSEEF1544R4zPxWLRf77v/+bUCg0uu2ee+4Zi/AkSZIkSZIkSfqr/bqwuOCCC/ba9qEPfWgMIpEkSZIkSZIk6Y3s12MsJEmSJEmSJEk6MOzXYywkSZIkSZIkSTowyMJCkiRJkiRJkqS3TRYWkiRJkiRJkiS9bbKwkCRJkiRJkiTpbZOFhSRJkiRJkiRJb5ssLCRJkiRJkiRJettkYSFJkiRJkiRJ0tsmCwtJkiRJkiRJkt62/Xrl7b9n2zZ9fX3k83mqqqooLy8f65AkSZIkSZIkSfqr/brFIpvNcsMNN7B48WJisRjNzc3MmDGDqqoqxo8fz8UXX8zKlSvHOkxJkiRJkiRJ+o+nCCHEWAfxWn7yk59w9dVX09zczGmnncYhhxxCQ0MDgUCARCLBhg0bePrpp7n33ns57LDD+N///V8mT5481mFLkiRJkiRJ0n+k/baw+MAHPsA3vvENDjrooDfcr1QqcfPNN2OaJh//+Mf/TdFJkiRJkiRJkvT39tuuUHfeeeebFhUAPp+PT3/607KokCTpgPbzn/8cRVGYNWvWWIcCwLJly1AUhWXLlr1jx/zmN7+Joih7bGtububCCy98R45v2zY33HADCxcupLy8nGAwyPjx4zn99NO5995735HneDt6enr45je/ydq1a8c6FEmSpH+J/bawkCRJ+k9yyy23ALBx40ZefPHFMY4G5s+fz/PPP8/8+fP/pc9z77338v/+3/97R4714Q9/mEsvvZQlS5bwu9/9jgcffJArrrgCXdf5y1/+8o48x9vR09PDVVddJQsLSZLetQ6IWaGOPfZYjjnmGK688so9to+MjHD22Wfz1FNPjVFkkiRJb9+qVatYt24dp5xyCg899BA333wzhx566JjEYts2iqIQjUY57LDD/uXPN2/evHfkOO3t7fzxj3/kG9/4BlddddXo9uOOO46LL74Yz/Pekef5d8rn8wSDwbEOQ5Ik6S07IFosli1bxnXXXccZZ5xBLpcb3W5ZFsuXLx/DyCRJkt6+m2++GYBrr72WRYsWcccdd5DP5/fYZ+fOnSiKwve//32uvvpqxo0bh9/vZ8GCBTz55JN7HXP79u2cd955VFdX4/P5mD59Or/4xS/22OfV7k633XYbX/jCF2hoaMDn89Ha2vq6XaEeeOABDj/8cILBIJFIhBNOOIHnn39+r+d/6KGHmDt3Lj6fjwkTJvDDH/7wNc/9tbpCJZNJvvCFLzBx4kR8Ph/V1dWcfPLJbNmy5XVfw+HhYQDq6upe835V/dufu1fP7Xe/+x2XX345tbW1BAIBjjnmGNasWbPXY1etWsVpp51GeXk5fr+fefPm8ac//Wmv/bq7u/nEJz5BU1MTpmlSX1/P+9//fvr7+1m2bBkLFy4E4KKLLkJRFBRF4Zvf/CYAF154IeFwmPXr13PiiScSiUQ47rjjXvc1Ali8eDGLFy/e67xuv/12vvKVr1BXV0c4HOZ973sf/f39ZDIZPvGJT1BZWUllZSUXXXQR2Wz2dV9TSZKkfXVAFBYATzzxBH19fRx22GHs3LlzrMORJEl6RxQKBf7whz+wcOFCZs2axUc/+lEymQx33nnna+5/3XXX8eijj/LTn/6U3/3ud6iqykknnbTHl/tNmzaxcOFCNmzYwI9+9CP+/Oc/c8opp/DZz352j1/zX/W1r32Njo4Orr/+eh588EGqq6tf87lvv/12Tj/9dKLRKH/4wx+4+eabGRkZYfHixTzzzDOj+z355JOcfvrpRCIR7rjjDn7wgx/wpz/9iVtvvfVNX49MJsORRx7JDTfcwEUXXcSDDz7I9ddfz5QpU+jt7X3dx02fPp14PM5VV13FjTfe+Jb+Tnz961+nra2Nm266iZtuuomenh4WL15MW1vb6D5Lly7liCOOIJlMcv3113P//fczd+5czjnnHH7961+P7tfd3c3ChQu59957ufzyy3nkkUf46U9/SiwWY2RkhPnz54+e/xVXXMHzzz/P888/v8f4QMuyOO200zj22GO5//77X/O9eiu+/vWvMzAwwK9//Wt+9KMfsWzZMj74wQ9y9tlnE4vF+MMf/sCXv/xlbrvtNr7+9a//U88hSZL0msQBQFEU0d/fL4rFojjvvPNEZWWlWLp0qejr6xOqqo51eJIkSf+03/72twIQ119/vRBCiEwmI8LhsDjqqKP22K+9vV0Aor6+XhQKhdHt6XRalJeXi+OPP35023ve8x7R2NgoUqnUHse45JJLhN/vF4lEQgghxNKlSwUgjj766L3ievW+pUuXCiGEcF1X1NfXi4MOOki4rju6XyaTEdXV1WLRokWj2w499NDXjfMf/+yMHz9eXHDBBaO3v/WtbwlAPP7442/4ur2Whx56SFRWVgpAAKKiokJ84AMfEA888MBrntv8+fOF53mj23fu3CkMwxAf//jHR7dNmzZNzJs3T9i2vccxTj31VFFXVzf6Wnz0ox8VhmGITZs2vW58K1euFIC49dZb97rvggsuEIC45ZZb9rrvH1+jVx1zzDHimGOO2eu83ve+9+2x32WXXSYA8dnPfnaP7WeccYYoLy9/3XglSZL21QHRYvHqLCI+n4/f//73fO5zn+O9730vv/zlL8c4MkmSpLfn5ptvJhAIcO655wIQDof5wAc+wNNPP8327dv32v+ss87C7/eP3o5EIrzvfe9jxYoVuK5LsVjkySef5MwzzyQYDOI4zujl5JNPplgs8sILL+xxzLPPPvtN49y6dSs9PT18+MMf3qNbUTgc5uyzz+aFF14gn8+Ty+VYuXLl68b5Zh555BGmTJnC8ccf/6b7/qOTTz6Zjo4O7r33Xr74xS8yc+ZM7rvvPk477TQuueSSvfY/77zz9pilavz48SxatIilS5cC0NraypYtWzj//PMB9note3t72bp162jcS5YsYfr06fsc9997K+/Fmzn11FP3uP1qTKeccspe2xOJhOwOJUnSO+aAKCzEPyy1ccUVV/D73/+eH/3oR2MUkSRJ0tvX2trKihUrOOWUUxBCkEwmSSaTvP/97wf+NlPU36utrX3NbZZlkc1mGR4exnEc/vd//xfDMPa4nHzyyQAMDQ3t8fjXG5fw995oDEN9fT2e5zEyMsLIyAie571unG9mcHCQxsbGN93v9QQCAc444wx+8IMfsHz5clpbW5kxYwa/+MUv2Lhx45vGU1tbO3qu/f39AHzxi1/c67X89Kc/DfzttXy7cQMEg0Gi0ejbOgZAeXn5HrdN03zD7cVi8W0/pyRJEhwgs0K1t7dTWVm5x7azzz6bqVOn8vLLL49RVJIkSW/PLbfcghCCu+66i7vuumuv+3/zm9/wne98B03TRrf19fXttV9fXx+maRIOhzEMA03T+PCHP8xnPvOZ13zeCRMm7HH7H9eWeC0VFRUArznOoaenB1VVKSsrQwiBoiivG+ebqaqqoqur6033e6vGjRvHJz7xCS677DI2btzIzJkz3zCevr6+0XN99e/O1772Nc4666zXPP7UqVPfsbhf733w+/2USqW9tg8NDe31t1GSJGks7dctFul0mnQ6TVlZGdlsdvT2q5dx48Zx5plnjnWYkiRJ+8x1XX7zm9/Q0tLC0qVL97p84QtfoLe3l0ceeWSPx91zzz17/MKcyWR48MEHOeqoo9A0jWAwyJIlS1izZg2zZ89mwYIFe11e/eK8L6ZOnUpDQwO33377Hq3IuVyOu+++e3SmqFAoxCGHHPK6cb6Zk046iW3btu3zNOKZTOZ1u/Rs3rwZ2N2y8vf+8Ic/7HEuu3bt4rnnnhudaWnq1KlMnjyZdevWvebruGDBAiKRyGjcS5cuHe0a9Vp8Ph+we8D+vmhubuaVV17ZY9u2bdve8LkkSZLGwn7dYhGPx9/wl7RXfxlzXfffGJUkSdLb98gjj9DT08P3vve9PaYMfdWsWbO47rrruPnmm/foM69pGieccAKXX345nufxve99j3Q6vccMQj/72c848sgjOeqoo/jUpz5Fc3MzmUyG1tZWHnzwwX9q7R9VVfn+97/P+eefz6mnnsonP/lJSqUSP/jBD0gmk1x77bWj+37729/mve99LyeccAJf+MIXcF2X733ve4RCIRKJxBs+z2WXXcYf//hHTj/9dL761a9yyCGHUCgUWL58OaeeeipLlix5zcdt3bqV97znPZx77rkcc8wx1NXVMTIywkMPPcSNN97I4sWLWbRo0R6PGRgY4Mwzz+Tiiy8mlUpx5ZVX4vf7+drXvja6zw033MBJJ53Ee97zHi688EIaGhpIJBJs3ryZ1atXj87e9a1vfYtHHnmEo48+mq9//escdNBBJJNJHn30US6//HKmTZtGS0sLgUCA3//+90yfPp1wOEx9ff1eBc8/+vCHP8yHPvQhPv3pT3P22Weza9cuvv/971NVVfWGj5MkSfp3268Li1cH0MHuIuLkk0/mpptuoqGhYQyjkiRJevtuvvlmTNPkoosues37KysrOfPMM7nrrrtG+/oDXHLJJRSLRT772c8yMDDAzJkzeeihhzjiiCNG95kxYwarV6/m29/+NldccQUDAwPE43EmT548Os7in3HeeecRCoW45pprOOecc9A0jcMOO4ylS5fu8aX9hBNO4L777uOKK67gnHPOoba2lk9/+tMUCoU3nUI1EonwzDPP8M1vfpMbb7yRq666irKyMhYuXMgnPvGJ133cpEmTuPzyy3nqqae4//77GRwcxDAMJk+ezHe+8x0uv/zyPQadA3z3u99l5cqVXHTRRaTTaQ455BDuuOMOWlpaRvdZsmQJL730EldffTWXXXYZIyMjVFRUMGPGDP7rv/5rdL+GhgZeeuklrrzySq699lqGh4epqqriyCOPHB3bEAwGueWWW7jqqqs48cQTsW2bK6+8cnQtizd63Xt6erj++uu59dZbmTVrFr/61a/+6eloJUmS/lUU8Y8jo/djkUiEdevWMXHixLEORZIk6d9q586dTJgwgR/84Ad88YtfHOtwDmjLli1jyZIl3HnnnaMD5SVJkqS3b78eYyFJkiRJkiRJ0oFBFhaSJEmSJEmSJL1tB1xXqFdeeWWvqRIlSZIkSZIkSRpb+/Xg7TPPPHOPWaGKxSL//d//TSgU2mO/e+65598dmiRJkiRJkiRJf2e/Lizi8fgetz/0oQ+NTSCSJEmSJEmSJL2h/bqwqK2t5YwzzuDQQw8d61AkSZIkSZIkSXoD+/Xg7b6+Pt73vvdRV1fHJz7xCR5++GFKpdJYhyVJkiRJkiRJ0j/Y7wdvCyF45plnePDBB3nggQfo7u7mhBNO4LTTTuPUU0+lsrJyrEPci+d59PT0EIlE3nDlcEmSJEmSJEnanwkhyGQy1NfX77XQ6D/a7wuLf7R582YefPBB7r//flatWsWhhx7Kaaedxgc/+MH9ZkXurq4umpqaxjoMSZIkSZIkSXpHdHZ20tjY+Ib7HHCFxd8bHBzkgQce4IEHHuCoo47ab1ajTaVSxONxOjs7iUajYx2OtJ9xHIcXX3yRQw89FF3fr4c5SfsBmS/SvpD5Iu0LmS/SW5FOp2lqaiKZTBKLxd5w3wO6sNhfpdNpYrEYqWSSsJFHjGxCiTSjRlvGOjRJkiRJkiRJestGv9emUm/6g/l+PXh79erVfO1rXyORSABwxRVXjHFEb52hK6htt+L1PoMSqMEbXoe94Rd4+d6xDk0aY57nsWvXLjzPG+tQpAOAzBdpX8h8kfaFzBfpnbZfFxYXX3wx4XCYs846i2QyyVNPPTXWIb1lnzutFlF1BHrLB1DLZ6FPOAt9yodxd9yJl24b6/CkMeR5Ht3d3fKDXHpLZL5I+0Lmi7QvZL5I77T9uivU4YcfzvPPP8+qVau49tpr6e7u5vnnnx/rsN5UOp3m/OPH8/sndhHxeYjEOpRIM0p4PMIp4my9Fa3+GNSyGWMdqiRJkiRJkiS9rndNV6hIJALAggULOOmkk3j55ZfHOKK37tHVSfTNP0Rs/iU4OcSu+3BXfh1ynejTP47b+zReYsNYhymNAdd1aW1txXXdsQ5FOgDIfJH2hcwXaV/IfJHeafv1FACGYZDJZIhEInzsYx+joqJirEN6y750koJXvRh1wrGj24SdwVv3fdSmk9CnfQxn668Rbgmt6uAxjFT6dxNCMDIyQnNz81iHIh0AZL5I+0Lmi7QvZL4cmFYX27gk90tCukZEVNNgKlSIMvKr1lLlq6RpaguasKl1dhKzkvjVcibVfgVVNf/lse3XXaE0TaO3t5fq6uqxDmWfpNNpzjwszr0vJIlGo4hCEswwiqYjPAex8ecQaoLxZ+DtvAeMCFrTSXIxPUmSJEmSJOl1rc6186HunxGKxPFy40CozLTSrL7iT2y8/zlUTeW480/l3K+ezWFsJmalANB9tVRN+hKq5t/n59yXrlD7dWGhqip9fX0HZGERi8VY98JNuL0vIlSXqBZlYuVBKDNOgXA1ou2PUOhFmXEpXt+zeKmt6C0fRDEjYx2+9C/mui7bt29n8uTJaJo21uFI+zmZL9K+kPki7QuZL/s/27NpTbeS8xy+vflm1mk5LNWkrmIuXsEj9aMn2fm7exCOiz8cwnNcrGIRn9/H5z96JJ8+9wh8Xgp/fgs6Gnr1YeiNx6PoQSif/ZZ+1N6XwmK/7goFHLC/4p92fC3xgeeJNEzHF59A//AGNufWM/6lXkITl6BMPAf6n8VbfRXqnC+jRFuwt9yMVr8YrXLuWIcv/YsVCoWxDkE6gMh8kfaFzBdpX8h82b/NvWcO29LbMKKzUbUIaNNBCKpDHm0X/5zc6lYO/eSnWXjW8SysbsIcipFr3cCyR//A9371RzZuFdx2aRzdG0ERAjb+FG/dtwBQms9GO/aOdzTe/b7FIhaLvWlx8eo6F/uLdDpN290foXHRxZRPOYkhJ0OVHqUnsZ7khltp9rUQVMMw7xzId+Bt+T/UmZdCoA6381FEoR99wpko/sqxPhVJkiRJkiRpjPhv9eGioodmA41oZjUoCvqdG0nf+TzHfO92Jh86j4bqDBO3VaNnVWbG2wF44olH+ML3v81PLp7IJ99TiZbOopYGwEiBsvvrv/5R+01jeFe1WFx11VVvunz4/uj+VYOYRw5S99KPaErmQAtycMsJZGd9lC1bb2O6OQ3fM9ejzj4Ddc5XEZt/BaEmtJbzEKUEzq4HAQWt7miUyIQDtuVG2pvrumzevJnp06fLpmfpTcl8kfaFzBdpX8h82f95nofnmFhJD6M8hDAVSBZJ/fE5av7rQ1TNXEQyK6jNm2S6KplkDEAcdNviYxPHsfaweVz7p418ckY5uhcGwggthwht/ZfMDbvfFxbnnnvuATfGAuBPlX5uWvUsXqmVlJLC8IdYn97KjPAhlCacyMb0CmaVteDb+jhK+XiUuVfs7hq16uso9cejT/4IlBK4Ay8gOh4CXwVazWGyyJAkSZIkSfoPYXc44GXB3ImjL0CLKFg3vgiOg6/ig1gFl3hfjEgxSCBgoQ0buOU6YWsYJe/xielHcdsLa/jWg91cfUoTAIobQukJo+jvfDe4/bor1IE8K9Tzt12A8CUQ2pGUZ3KMiBwbJmU4cnCAg2pPZ6uholfmmSxqMf01KP3bUKadAFWTEV2PIPqe2b2oXv2xEJ2CKAzg9T+PyHagBGtRyw9CiU9BUeQvDJIkSZIkSe9Gyv9TQCiQH4fi1CGEH65bBsC4Ty+nRqmmuVBHY4XGQeNhXHsBJe8Q8/XRkG9j2Gpn1q+/hKaAddnBIIC4gkIruFmUb72zXaH22wXy1q1bx35c87ypkfwOypKTaEzuIi9KVEcrmLdTYb1RzrZdy5mV7sDekWXAGsKyBvAmHYXo24J45noUtxJl3lUoDScgepfjrfwKdD2CVjUffdalqHVH42U7cDZch9N2F16244B+rf7TuK7LmjVr5IJE0lsi80XaFzJfpH0h8+UAkW8AqwI8Gwq53dsUjVhfhEhvlOGRHK2b06x7Jktmm43XVSC6K4c7oBAZ3L12haYoYAE2KIMCii6KeOff9/22K9T8+fNHp5qdOHEiK1euPKAWyKtITsbaOZWcWU1teIiRcAG7Yh56pI+dyjZCXUPMNdM8zQSCwSJh1YdqmOizToZkL7z0a4QQKFWTYPLJ4CUQu+5F5HpQKuej1S2BxhMRuS68gRcRuXtRohNRK+ejBOtld6n9XCAQGOsQpAOIzBdpX8h8kfaFzJf9m5ZQIDMAShbFnYaZOoyCuQVhZVCG2vEwCBQc6ggzaShIDwB+Qv4SkwL9/KnzMQBmlgVw06BoORSvG3Il1AqFd/rb4n5bWMTjcdrb26murmbnzp14njfWIe0TX+sctm5aTFYz2VDyKJ+6kxm1G6lqC7PykIPZWL+TC7prOWpnO+sjrdRhEFUU3IKNMEBtPAi1fBJKLoHS8SIi1YMSKIfqQ8EoIbb/BlEaQalZhDbuFND8iEwbXv9zu4uPSDNq5TyUUJMsMvYzmqYxbdq0sQ5DOkDIfJH2hcwXaV/IfNn/KUkBWCAs9HwFmhqh7NAvM/L8tQxs+T1l9V9AtQSNRhDFL0BRQAjC+R5GRuCPu9pp9kd4dH4LzrAChNCCBpqZxetTeKc71O+3XaHOPvtsjj76aCZM2D1YecGCBUycOPE1L/+sa665BkVRuOyyy0a3CSH45je/SX19PYFAgMWLF7Nx48Z9Pva2jScwqGZx6USNjpDa1shIdSPP1wiOWC6Yu6GRq+bF6ZrzHg4qNaCufpDh9udw+zfj9XXCtk14q/6MvfMlnHgdHPxBxMxTUYSH0rkDkgEU82DIJvBWX4XY/CsUXwX6xA+gz/osavlsvMFVOBv+F3vz/+HsehB3cBVerhvhOf/0aya9fY7jsHLlShxHvg/Sm5P5Iu0LmS/SvpD5cgBRAFS09CCB1GYqJn6AvoF7SOy8lXFpB7+3e6yE6lpMSyzHV8ryv30P8XRmE9dOG0dY/1tbglus233lX9CNfr9tsbjxxhs566yzaG1t5bOf/SwXX3wxkcg7tyr1ypUrufHGG5k9e/Ye27///e/z4x//mF//+tdMmTKF73znO5xwwgls3bp1n55/WHNQfN10N/sRvTkqNZXuu8dz4vwN/HmOysGtQT59R44/HDvEKf/1CWZ29NHz0l2MrFxBmSZQghpO9TiUmlmo2W14G1cjfCrUNKPOeC9KuAYl2Ql9m6DUhMj2I9o/BvFpKDM+glo2FTU6AQDhlhD5fkS+B2/gJURhADxnd1WrB1HMOIoZQwnVo0TGo/wTy71Lb52iKJSVlcmWJOktkfki7QuZL9K+kPmy/1MVFU94IEAvbCU03IuCoMIah+qfwfrkTRRz61mQO4UFLedQNbSGdfkXuLLvCZ7JbOaLtYdzSpXF7lHbCkKAcASuBZr5zse7X88K9aqLLrqIn//85+9YYZHNZpk/fz6//OUv+c53vsPcuXP56U9/ihCC+vp6LrvsMr7yla8AUCqVqKmp4Xvf+x6f/OQn39Lx0+k0Pz/yz+QvSSO6eiEaovhECzW9E1jg38y4yU8y0pBjV2kKVSGLkKsQWbKIqQcdRi6msWz9naht6zliuEQk2QteCq8ihph/GppejxjqQDh5KKtBHT8bpWEWCiCyA9C1DLHzQYQ1gmKGQfdBpAmlfAaUTYXYFFR/GbC7dQYnh7DSYKXwcp2IzC5wLRR/OUpkAmp0Ivir5IeOJEmSJEnSv9mJ3zqWpZuXotpQuf0gFGHiK4WpTE5FCIGTH2Z7filZMbLH4yb6avhC1VG8L9aOLwThit2FpPj/7P15sG3pWZ8JPu83rGHPZ7rzzZujpJRSQhKpATACZEpYxgzuoSiXy6Zkl9ttu2mHjTEVHY6KsIsC3C5wuzrc3bRdYNzqaMrt7sJtLENiJyAgJTSiISXlnHnne+4Z97Cmb+o/1lHasoWUaQPKvOwnYsdZ55x91l7f+b699nrX+76/X0q41TMk5ox/6MfRf+yHvuox3FEGeQA/8zM/87u6v7/0l/4S3/md38m3f/u38yM/8iMv/vy5557j5s2bvOc973nxZ3me8y3f8i089thjLzmwAGjft+Dr/vaPcauxuJFl8No38Ezxp/hU9SBn9/Y5Kl7gm8yv8On4Zp69a8aljz2O//TTPDA6w3eMz9Cee5BHLl3mE4MD3qa2+NbHn2P8Sz9PHNSwtYF603fD9htJz3+W+IlHwGaonbuR8w+j/vD3gs2gPiJVB7D3Obj9OOnyh6C5iQ8VYiaQX4T8HKJKZLCB3rwbzn0nabiN+Dlx/hzh+q+Qmj1AwIwQZSAGUqhBZajxRWR0ERnf2/9uzVfFe89HPvIR3v72t2PM+n+25iuzXi9rXg7r9bLm5bBeL698vvuB7+Tjj/xaL+iTNJJgNh9ASogIZ/LX8M3xnVTNh1hxxJYWLsgmb8oSO91ziECzbCBdIy8VKVak2AIg7/jPf9eP9w/cKvq5n/s5PvGJT/DRj3703/vdzZs3ATh9+vSX/Pz06dO88MILv+M+27albdsXv5/P57zhZ/4uj1WReN9ZRpcPOP+FFzh/7pdZdv8pv+wv8C23J/zS5oQ3P7BA736U1eD1cFXzVHlEce4MF4uC7y4v8ke/kLE7TvyL+y/x+OsGvOuG4+HbR0wf+f+gup+C7Qfhwf8F6uxZYnuL+MSvIvUSSRZMjipGkA2I2VvQ2VtIgw4Q0DWJWxBu9C6O7TPw3K8izw8hjoh6E2UKSPHE9T1Cewu8B2WgGCBxiVy7RrC/RfILxBiSWCSfocbniMOzqNndqPFZQogopVBK4b1/cds5h9b6xW1jDCLy4jb0J75/e9ta20fpJ9sxRkIIL27HGDHG/I7bIQRSSi9uQ9/A9jtte+8RkRe3v9w4Xs6YRIQzZ868eOfgThjTnThPr5QxpZQ4f/78i/u5E8Z0J87TK2VMAGfOnEEpdceM6U6cp1fKmJRSnD9/nhDCi87br/Yx3Wnz9ObXfD0pJbQD2+2BnMb4Vd9zkRKH6hAdhPOpYlMP2Fa9MujEfpYYoa5rgv8CiYQxfRU8SiMbO6Tp9ov/m680ppcjR/yKbd7+veDKlSv85b/8l3n/+99PUfzOfQT/btlPOokKfyd+7Md+jOl0+uLj4sWLfP7KAXvf/+20/+lr+dQ3l1w7OGSjukaIT3Bc38Wjw2Meqt/Mb318yG3z3fy27vi/vvk6H9m8RvvpT3D7f/5FDv9/P8/qs4+x8fzn+V9/wfBf/nzkNf51fPyeN/K/v/d+/u53fC9XtxP1Y/8t4QN/Cx77JQ4++AnkpiMeBa4/fYV4fER742kOPvdB3I1P09x6nL2nfwt/6yrtMxVHn1TIZ0b43x6y+MwMdsc0V69QP/0viM//M9qnH2P+xBOkmyvm1xT7N0qodqiefIHmyU8Qr3+e6qlPsbg1QKUHuXU1Z3G5hs9/jtW/+Ed0P/d/IP6P30/9U99H+4/+JP7n/gL7/+gvUP2zv0X8lX/As//PH6X64P+L+Nu/ySfe//9g+czTpBj5wAc+QNM0eO/5wAc+gPeepmn4wAc+AMBiseCRR3oJtaOjIx599FEA9vb2+OAHPwjAjRs3eOyxx16c+4985CNAn5n65Cc/CcBTTz3Fpz/9aQA+//nP8/nPfx6AT3/60zz11FMAfPKTn+S5554D4CMf+QhXrlwB4LHHHuPGjRsAfPCDH2Rvbw+ARx99lKOjIwAeeeQRFosFwItjijHymc98hhjjHTOmO3GeXiljeuGFF7h06RIf+9jH7pgx3Ynz9EoZ061bt7h69SpKqTtmTHfiPL1SxrRarbh06RK/+Iu/eMeM6U6bp+ObK/77v/p/4Xy+Td5cw7ZXkXRM7j5MFipsXBDCxxD2aeKi7/FOiRBblu2zXLn9FPM6US2hWkIIUO3czegnf5GrN26+pDE98cQTvFReFT0Wv1v8/M//PH/8j//xF6Ny6M1hRASlFE888QT3338/n/jEJ3jLW97y4nO+53u+h9lsxs/+7M9+2f1+uYzFX/wrf4bq1JJvf+t7yEzOZ/7b/4FLcj/b8XVUp/5zPrL1ab4j3+PB8bdxWd/kg+f2ePPOiJv1R4nJcfqG5txeztkuZ1IotqaegV1gtjbRr3snUQ8Ih4fsuSOup2NS8xznVi9ghwNsucOwOE3mK3S7i5icmI1Rw22iHZAApSCKJypP0qEXBggJXTUQADQiBswS9BKxLTEuAY8oIQ3vQmYPgdmGw2uw/xh0S8gegvy1qMGIaCyCR7wjLueIayE0JLcE3/TbKSAqAhUpVYiL4ACVkSZj0taUdOoceuMuGOwQ9QQ73CHZCSHyir/T8OXunnjveeyxx/jGb/zGF79/Nd09uRPvCL2SxxRC4Ld+67d4+9vfTpZld8SY7sR5eqWMqes6PvShD/FN3/RNL2YtXu1juhPn6ZUyJoAPfehDvO1tb3vxhuurfUx34jwZY/jZ//Hv8n/8736IFBNnDzNs7Njs3oxNDdPwPJIcQ6a8yX4dyBYz8y9QUvNFtkYwOrmnfveHLlOcvfCSxzSfz9nc3HxJPRZ/oAKLxWLx75U0ve997+N1r3sdP/zDP8wb3vAGzp07x1/5K3+Fv/7X/zoAXddx6tSpl928ffYPT/ngT/8WX//GtwPw6CP/Mz//v/yvuOcb/ld0z72eo7d9A584+hne528y23ov5/R5ugR7uuWJ00s+9M2fZ3Ffx+Yzift/o+Jtz5dseENZBrZdR2YM7vQ26f57GN53N6PxmGQS+/uf5XjvcTi4jPIZWZqSJYuNUODIkkORgd0AW4LKoNwkTWbgaogNyXgoIOURVAsSEBSSFESBzpPamuRrkm8gBCSAEBF1GdG3AYWIAm1BG9A5WAPGIPkAshHkUxhcAHsWgoKqhi5CiqAFmgqObsHxLqQFFBpMJAUPKUCMvVRaAnSB5DOk2IbyNOSzXu5AZ/1ra9tPjpxoPCsFgyGpLIAIXQVH+/2jqaFpQQpQJer0GbhwEc6cRdR/fJIvxsiNGzc4e/Ys6ndhf2vubNbrZc3LYb1e1rwc1uvl1cNqueBPf9+38rnPfpJL+/3Pcr/Nhe4QIZxkKuB1+jzbapNZ9pkv+fthDttj2PqL/zU7f/1HX9Zrv5zm7VdFYLG/v/+i6/aVK1f4B//gH1DXNd/93d/NN3/zN/9H7ftbv/VbX1SFAvjbf/tv82M/9mP8zM/8DA888AA/+qM/yq/+6q++LLnZ+XzO1l1T9i9/6QT85Hf9MXY/dZUNvovhpbfxS18XeXb/n/OOYc1pd4m7uiXvYIMy3Y2KA3x7lWfGn+Yzb0vIa+7mqLVkn7oFjWNzEflD1zzblUIYkiSDIkcVA0yWo8ocnRKha/DG46wD5xAfkBjRsUVUJKiEpcZoD8Mp2fYlzNn7UOMpYgQh9Rf6IaJcIPkIqxVx/zJxdQA6IeMh5uF3IKdK0tEB6fCQeNyQ6g6sQzKPDAIQkTaQWg+xgVij/BGEI8S3EByiOgCSjBC7BeVZZHgBsgkSOlIIwCH4XQi7EBdA1zeUe9fL6JIAi+gMJAcZAENQY0QyQEAURPrgBAVagc2hHPSN70qBa6CtoOugc5AUTE/Bpdcj5+/vpX9t/h+1/tasWbNmzZo1a14Kzjk+//gn+Yn/4k9w+8pllAvc03zpcybAXQy5q1whcmJ/IcLd7/szXPrf/EWKh97yZfb8lbljAovPfOYzfNd3fRdXrlzhgQce4Od+7uf4I3/kj7BarVBKsVqt+Kf/9J/yvd/7vf/Br/HvBhYpJf7m3/yb/NRP/RSHh4e84x3v4O///b/PQw899JL3+TtNwO6zz/Lfv+EbGP3xH2T84QHd953hV44NN5/5FXbu2eVweD/LnbdBXnDv9iF/8oblvic1g1VDLZ9j317m+lZiunEfb77vYZ40z/C4e4bs6ifYPt7j+fJevDvL6UqxUUV2XMOWb7CpQKchlbEsjCGqRIoJnRRWDzA6IxdhGOeM3BLrGvCQUo5jTIw5wQWSa5HQ4lE0qqAzOSihdI5RU6OiJtohwY5oizEusyjvUdFhvEOIxELjxwoVIzpEbAILGBUR6TWWRYFkK1R5gLIH6GIPdNWbSQZI9ZjUbEDcIIUxuAIxCj2KqCEQPUIFcdU/7LIv6VLLfgeSehleNSTpCZgxmAm0BdQe6tg/ggaVIWe3UG+9FykU7N+CvRvQrCC0/b4yC8MpMt6BwSYUU8gHkI9gMIZ8CMr2fTraEIDHfuu3+MZ3vQtdFH0Gxfu+8NF78O7ffA/976czJF8HMX8Q8d7zwQ9+kHe9610vpvLXrPmdWK+XNS+H9XpZ81K4YwKL9773vRhj+OEf/mHe//738wu/8Au85z3v4R/+w38IwA/8wA/w8Y9/nA9/+MNf4yP9Ur7SBPzNe1/LLmNm7n/Lg2cOmX//Nr/yzBmuXH6ObPlpzm22+GDYnb2Wg9l5RhuKN57b59v3LnL++cRwXtMZjaSEBE9MoCQnw1CyjwmHeCIBR2VyVtkYkwpsMJS+I6MDMoIqQDlEVnRoVnGMx/a9FiKoCEXqGEiNUQ60B5VwNiMJaO9AKhIKFwsWesoyC4zTbWZhn8K36BARqREckixCTmhH0BSgFKIsQRIBT5scXnkG1jDSJdJmpFaTRKFsREwAAkkJYhQoD76D6EAHJERSk6BNkIRel0AQm6EGJTLKwWrEatSpKVrX0O2D24dwDBwjpgLVl0kJEckiGIeOHenQIG2JmpTIVgZZDsaC1qSkIJiTUrFwErxwUq7lkXBS3pXoS8mAeKKSdXIvoQ8eRH3J16RUXxJmdB/kkIEZI3YEwzGUQ2SyBbMdZDACa2E4grJc+47cQcQY2dvbY3t7e12qsOarsl4va14O6/Wy5qVwxwQW29vbPProo7zpTW9iuVwymUz4yEc+wsMPPwzAF77wBd75zne+2Dn/SuErTcAv/8RP8Ov/zf+N9p1/is1r7+Dcw+9noltW8S6efV5x4CJ16LBjIdxf8lG3z5E5y2j0Bs7iuef4Ju+qv8CD6QbX7voGPrZZgt/n1LJjUudENaFOQ5TL2KoaZlWD8g0pNHR4liLUySFyzCrPmBcbnJaWS1QolXOcTnEQRqwIVMpTKU9NxKGYMecS19lKBxwwou2mbDQtw1gxLffJSs98eJZde4G9dkzVKkJuiNaSxGCSUDZCWUeCrjHlAVbV5Dg2omFGQa6mSFL4uEflbhNCRRZychS5EoxxKOURNMEVxFAiSYNWRMkAhdYVRncY1aLEQ5uB639HMKQlxKDAKlKZg1GgBPEO8R5JETEK8YbkFCkmzGbCnvbo6e0+G5ICyoIeCmIixA5C08vznsQLSStSVoCUJKQPeGIiSUJ0RHQCk5AEqYvQur7sqm3BJwiQvtirUgIl/WsRkSR9KVdKJ+VcQDKQMoh53x+ic8iGkE2gnEEx7h1ypjswO40MZ73Len7iT4KAzhFlfx/fLWvWrFmzZs2aVzJ3TGChlOLmzZucOnUKgPF4zKc+9SnuvfdeoJfVO3fu3MvS1/394CtNQD2f8yN3PcgiexOj/E+yeekdXPv+DzM6uMyZQYa/qam/sMBef4Hh6hYuQshGPH1/zrMPbLN75hup6gm0gbsPL3NpcY1aj0kyZaA9anTEoLjJ1B9zOCuJmWGz6thcOBbFGY7MJqmN6FVHtmrIV13fA41i6mo2ugVlbNAp4LTGKyFqQBTBZ5jKYjuFiMbbHG81OiQGbcGwiRSyiy2PKHIPJqOSER2WTC0p5RBlNFHlVHGb2m8zT2dYqBlRZSRlcaLxCmbOsJ2EgoQhQgQXhOgAF0ECIfME7dGhRXlBgkVEo/MMlQna9OoKKfZLXIggEdEBozuyOCfze+hUQ3IkPSCqCcgIMRYxHWJbFCvMah+9P0e8wswmqPEEKTNQlqRUn10wCowmGQ1RgY/QVKjUQAxIpM+0qF59QhlDEtW3fJxkM5Iz4BWEPvkhknrtaXWElduYuED1FWOQByggljkMctLAoCYBGYc+w5McuND31oR4Ul518kgnmRUCfSrl5DQg8eRg6P1KVAl6BNkUBqeQwRYUQ8SaPigr8j6QSgHsyfOgz9QMz8P0tYhel3D9x+Cc49FHH+Xd73431q6DvjVfmfV6WfNyWK+XNS+FO8p5+98t6Xi1l3iUkwmn3vI67Kf2cRtP0O6e5dzPvYvn3r3H7t0vIGcMG29NbOx8PU/vjTj+eM3kE7/NfU9/gvNPXuXx8reZmpxvyBKjrZKDrTMsbIOsnuG2tjzXnsbvTfC1sDcq2N2waGkoqTBdh40NeTKM2GTYZJzZA9sMaJiwLIY8ObTMC0WnItZ1lG3AtB6JiRh7VSgbawrXoKuISkICOhtorUbptzF2icw7bKqpVaJBUSRFGTTjEMiTJyoh6oSmYcpNoCNKRxJPSImgO471isqtUG0gS45MWkQCKWj8yuKqCTEYkmkR02Eyhxm0xKKFXKOjQQeDUkKQnBQHBD/Dd6dwMqDNLI3ZppOKjg5DQxZvMQifYdAcEucT3HKDkCbABsX0HOPTOTtNQ1HNwS8g9eVTIgZBoYxBGYNkCjIgcwQL0Rq8yUjRQmeQJKg2Ic6hakdsHbFJpA4kdIjuZXiFhA8Nx/UxB8sjuhjwOmEKi50YskFOkUOe9aJbmZlQ2BHG5OAFmoh2hxhziC6WkDmwCqwhmRxyRSpryAOSBVSeY7MxSueQTprsvYfOQ3UZwnNA6su/0JAUCU0yBT5ThAyQPvC0pkPJAvICBhMoSmR8F5JN+hI2M4TBGaQ8DeUZMAPwNfgV+D4rhCkBgWaP1O5Dcxu6YxANZojMXgfje6G6RlpdQ7IZDM6AnfT76477vym2oTj1qjx/aK1529ve9iUy2WvW/E6s18ual8N6vaz53eYVn7F473vfS37StPrP//k/593vfjfD4RDo/SN+8Rd/8VWVsQB4/F/+S/7J9/3vWBTfwNnXvou4+xD59hZxqGlOJcLZRBhHVqbD64b84j7lqYh/cp9LH3iE5xdjfrn4enzSmARlFAZJYVFkCWzy2OTRKLRkiNi+eRjpS/8VoFui9XRZJEh/1zprQbzBRI1GEKVIRpGHjlFzjI01MVccbGxye7hJ8pHh4ZyyqhA8NjmGqwoTIikJzgyI+QCfZzRKaMXik0InIceSh5xxrRnUGhUFSQmV6I8yOGJ0RBpaadBRk8UBWjRahJjldOUIdIHxoHxExYAKAQkBSSeysqJJovteCPniiVP6kiUiIrHvqRB6xakYSDGSYoTYklKDigvELbG0WGkxrkGig8IgGxndZEVlD1jJgpA6RHlKlRgnwyjlDKPBeoFkUMEgMSNEIaSEV1CbyNJEGj8grAZwbEjVHqrbxaYrDNUuA+sp9RCtc4wy/YW1UnQJmih0MeEJuOhoUkeUiDYGpRXKQjIJk2UUZUlelOR5Tp4ZjNGE2MsJ52ZErnNAoxDKXFFYISNgaVBpgYjD+0BMCaUjKXNQOqRwYEEZRVSBzkSCUmiVoymw5JikUcqhJCBoRDyoALpFWJEkkCQn2TGyeQl19l4kUzTRU/tANb/JfO8p6tUeK5NTZwMmRcaMwKANlJ0jL7aw+Yyj557m8OoLtKtADJbBSCiHYGyOKUtUXiAmQw9nqGKCKiaY4QZ6tIEZb2KmZ1CjC5BvkXQBukTp9d28NWvWrFnzB487phTqfe9730t63s/8zM/8Hh/Jy+OrTUBX1/z4g1+HD/dyevN1uI23sDocgj+Dif1FnVYgm4rukiacHuKWA5ZpQXfxMheb3+auJz7Ms5fewue2HuLqtQOOjw5JXYsJLagBKR8QM0uSgPE1G80BFRnLmJG1nqL2zPyYDc4yNZcYqm2UFKAMSfV3dfuvJ3U3KaFCQqWI8i2b1eeYNk+hQk1MJSFMIVoEaM0mK3ser0YIfQ+B0FfYRIGQIJIIAq1RtLnBK0VIiZQiMXqU1iibYRFsSASJdJKI3kHbEn2LC4EQPTH2pTwCiPR/p41BVK+z5oPDJ4/Q90JLiEjwaB9REbQYFIpwcpBWwBJRYU7saggJpbO+l6N1ECIWITMJa2q0WpDSkhCWQAdakZQhKUPUOUkVRNEkbYAcHS2Zt5iUo1KBjS021WTpkJzrGI5JytCp06ziOdo4RseA8UtylmQckTPHSkvGITm3keQJFCQRtDHkpiPXDUqpXmI3KWJK+AhtEHwUOlLf/K8NURJNauiSJ6lEkIBLji61JOkNc4z0pkMmV2SFISsLcltSlmOKcsJwnDGYKPJhwliBoEitJraB0DVUiwUH+0cs5oes6iOadsmyqahbR9cEBoXB5jAcFWzMJgwGvZmj0Qqb2X4ZcmJDkilMpuiWnhghpkTrPMF1eO/I8sjmdoLoWC1qloua5bylqj1tJ3Qh4VKvjjYoLIOhRQx4H/AhYDNhsmEYjAxagbapVy1LiSQCSmOyHJ1lmCJH5zkpJkQriq1tyrP3YadnycenSUmIXUc5mZIPh5jM9ut1cA6mD0C28RUzKc45HnnkEd7znvesSxXWfFXW62XNy2G9Xta8FO6YwOLVykuZgPf/mT/L5V/4FN3d7+a+QiGnXoMZCVfdHnuHHTLfIi7PYv2MoWiyrQCnctJwSAyWUMHG3q+zXf0GN2dv4vrsLXgViaEhbxZszZ9la/UctlvhZINKX6SICRuEGAe06jQhGYiOVgbM9YQOjQR/EgwodFKoL6orSaSItxj5q+jUslJbzPVZOikJRNrk8dETkqNMu0zDlT7DIRovBSKKiKZhRJVGNJITiaiY0CkhyQFNr4YkBrCkqBAUSSuChqgS3gouMwRtiQib8Tpn/HNM/C4pJSKaAznLnE2CWCKGTg9wqsRLgUIhSvXNymJ6BazQoto50/o5dppnGfpDVGzITEtRCNYOEFWCElozoVEDVm5K1Z6h6TZPFKE0VluszsiMwRiFFiHR9zIkIKWIZollj4JbWPapEQ5lmwNOswgTOilPApBe10orjVEaHRU69IGQihElCmvL/jWTQitBKTDaoFNAxUSKGiGgqTBphfgOlTo0LSo1SOx7LVTqv9dU2DSntAeM7T6F6jC6wJgCJCepDE+GTzkuQtvNaf2S1ld0ocH5jtZ3xNiXcAEkEUQLymjyomAwGZONckyZkZUF5WjIaFpSjBSwQvsFqq1Iy5qwWODnh/iuI4ZEDLHvVU+JrvH4zlOUOcqqPhunhaAUKEjSB6NBJUQlCm3JTV/elZInEklEQvK40JffoRUxE+JASESM85gERa4RI3SxplMBZcBFz/Ey0iwjTQWNE3ymaZNQHUW8S+S5osg1mdJopXABfBSSBzGayQw2NwNF1quGqSyj2Nyk3NlhMJtRjsfo6TkoTnFc55DtUPkBw4FmO79OoStUuYnWCqlv9aVjm29Cxvf026HtRQVEw+QBJJ/9np/71nztSSmxWCwYj8evytK/Nb+/rNfLmpfCOrD4GvNSJuDJX/kV/qf/7M+z+S3fy/7zBX/4u96ALTNWx4HFgWf/2X0W8yP2L41ZoPDPC+X8EiZNyLcTdstjSoNuNYODXQaHt5AgEIWoLI3doZYdXNTE5Akq4nSHy1t87tDuqG8uTorcHTN0uxgaumJMk03okiX5DlvPyVdHKOeoZMDcTGmLEd7kaAImLkhU1FlLYxtEOzIlRNFEpbC2YawbTG7RuWbIEdNqj9HqgDolnpmMeWJzRFtuovMNyuIUeb5NbiZkekiid+TO53uYes7w6Dobe5c5tf88pl5xFDJuS8GhLWiHAzojjOpjBr7DK01UBqM0JYlJt8J2FXk9x7oGEyOSEkks2CG37QWeGbyV24PXE/JNkrKAEHRGMBk6JMahYhoWTMKCmd9l5m9iU4fHcJR2WIYZrR/gXQYRLA1FXGFTSxJFrcbUakKtpniyXjnKAEYQ5QAHSpGUJZgCpwqiyojakLRGTrIM4jxZtUK6DhUiIqCToLwnpb60LQGIQpscbTOiNSiJSLfExA5jMowdouwQYwdYU2CTxnYe3TpUCKjYoMMKE1eosMDEBZk/IItzdAwoIlZWZKwQnU5KnOgb57MSlQ8hZYQqYuKKnGMyXWF1g5IKSfVJ83dCxCJqBHpEsiUyHMF4CxnmRBt7WWFvUE5QdAgeyQMqD0hp+v+jFf6NF4qgdOrFwILCBUUioSUiKiECMXrargIfsC5Ct4L6EFJNNJGQHP7EWDLzCZzH+4boO/QX0ycIiUQgIFYTSksaGOoMapUwSjBEqu4YqGm853jlqYMDiVgrnC5GNPuw+0JNs1J4yWmDELPEYKjZnOZMxsJ4HGiayJXLwnyRKIYRoyPNonei39iA8VTwRU43HqFG22xsbHFhKzEZCvlsm2I4pGVCp86yfe8DZLk9MZakN6OcPtCfpNwS8o21StiaNWvW/AHnjggs/upf/asv+bk/+ZM/+Xt4JC+flzIBXV3zf/9j34W/prBv+waK4T10i47RuGS2MWSQGbplx+FTNzm6us+8HLA/tYRxiZURqz1Pu1hA7ckosMMCyRRipG8mNiCDhB4JMhAYgBoGyByKCqXnxBLisOibeVMkdh3F09cY3rrFqFog4xHN6y5Rvem1xNObKHHo0JLaluQCbt5gPn8Z/bnLyGGHeIvEhEoJuXgae9cZorX4CN3tfZpbN3DHc3zXkE6dQp29xFYM7Ny+QbY4xjQVsesIriHQkXyLbltwgUYZglY0ZUE9GrE8vUXanEKWkbpIWjak+YrUODAnWYkv2llYDaVFTYZIkSPJkiSjS7pXdl0GulVk0cJBG9nrErWAjyc+IWRoyVExR4LtsyokkkA6MRvMXWSr69jqWsa+pQgdEoU2DKhCSRMSNjbo2KKiQ0ILCrxVeK3pdEZtclpjCUoTtCJqBcYQs5wghpA0KQoqCaIEoyxDO6bUQ6weYtWATBeYpJAQUZ0ndS3S1EjnUW2EqEjISQBgQBIqRJTrernd+G+pRGmFsjmic0QMKkR06svNRBSiDaooUUkwMWCiw6QW3dUk1+JdB8khKaBxiIDRGVpLn6FKHqHBpgatOjLlyVKFIWJNTmELCpXIVcDg0Hic9/gYiGJAKTKtyLTGiGBIiERSL9ILSiMnzfQqz1CFBVEk3yttxdDBIMfMJr2KVndICi0RULnBTjQqE2KIeB1oB46Ye6wNKAko7QnaEUKkqwLMhWbZUrWHhPqAYb0i72pCCAQSVmmUCJJ6yeBMazSKBLjkEa3Q1pLGJXFzjB7lvcSyQAEopO/9EU4yIIm2S3QB9polu21FSjWqq1itIBwlZnFIbnPqumXRdQTdx0LH7gCGjuAiESHfGTI9u0E4XTOedphiSBzvMMhLSpMzzEZMsglaDCEGSlMyySdo0SQzRIbnMRtvRDZej5gBAMnXUN/qZY912Tfiq2x9V/T3GOccH/jAB/ijf/SPrktb1nxV1utlzUvhjggsvu3bvu1Lvv/4xz9OCIHXvva1ADz55JNorfn6r/96Hn300a/FIf6OvNQJ+Jd/62/x/C/9KsXsPso3fx3aGsrpjLZKVEcBZQo2zs7YubRJIZGjj3yca7/9CT5qbnM8y3nz3e+ikCnL0LJIFW4Q6crexiBawUdH5xtcU+PbGr3oyOcec1wjhytS7PDKoTKDLYaMzt1D9tB9xNNDuqyjjQ11vUJSxBQKYw1KBLNYkh3PoQv4CLHrSL4D+vvkSQniU69cCojq7yATIqnqgxLJDZJpiBExBjEajOovnDoHXcCEhOgMszVDXTiPXLxANBkxnlzYI2gNSiW06cttrNZYEQx9GZVGkWHRQdM1nrpytAacjkTVEVRHFEdKHnTofSV06psx+kPGNYlq3lAfV3TVCq0VOjNorTCiSFHwvg8wYuq7PUQUShvEZBhr0caitEF5kCBIVCile/O7DJKOJAtBxV4AVvpinUAkEPGAT4GOQKccXWjxxwl3I+FveNyuo9vr6A4cfhGhEVIrpA7w9K+HQovpy7WUwYrGiCHTGYUZUCSLlbzvD3ERUzt0FxDTX8T3GnIRrXsTweAUoQv4qIhBnZQpBbwyYDJSXpJnRd+MH3sjJtqazDnyEMi6DtU0qBDQSbAmQ2cFxmR80TjQiKARtDLIyYV5UqmXDZbYBw9KkWIgpn4eowTE9vvL3RLTHGL8EbpboCQhxqJiQ0lHQUsZK0yoIXUopdEn61xi7MuMlMIajdEnTf5iiCY/MXk0OGtJo0iYNci0Jh8aCh0wOmCUR0yLiiu0zfpgTBQqWVBCkkjjO7roSN4TnRAPj3C71/GrJSH6vntINDGdKAXHSJSIaPXiKh8OT5GVM9CCUh3SeWIdaI4XxCS9GWZyiHIc2RUb0zGD4QBle2Wv1arj4KhCUoYk4day4tnuFpVb4hrIZ5bJ/QNG2wWbdsRGWTBjQEfD0+Y210fCqtRs6sBONmCr3GZWnsYML9J0C5r2kNQtsb6mtCNmw1OcGZ4FBNl8I7L9cB94iIFsiujs9+r0fMeTUqJpGoqiWAdxa74q6/Wy5qVwRwQW/zY/+ZM/ya/+6q/ysz/7s2xsbABweHjI+973Pr75m7+ZH/zBH/waH+GX8lIn4PLHPsbTv/EbfPJ/eD/n3vpOzr31QexsSt11tFjme3PaVYvJBpSTGRvnzhEDLJ5+luuf/Aif4DJH40RRjBmYISM7YWhHlN6g9xfE/UOUGNJsRJqWpIHAIBGMpxNH3TXUbUO9nNMul4SmAdcyQHPabLDZZeStZrlYIk2LqSt819KdOHub0YTJPfdx6m1fz6m3vp7ZxdPMTm9TjkvmN3ZZ3LxFdXhMtXeIaz0xCsWpTXRhmY4nbG1vsX3uFKFeUu/t0R0fM9zcpJjNSOMxfliSTjwerFLk2pDp/qLv95KUEi4E9v2SG+6QipoudrjkWbY1bevpli2rquK4WdHFDlRf+y8nb6eUYv8g9D0H0jf/ptSHRGgBLS96bJy0nqN0H5QgJ8GYUsjJc/sSqb57oQ9gAKVR2vQNwrFX40qhv9B3Ak3nWB4v6bpAZnJ0ynCHkXq/ZbWqqKumb1huIqFNJA9oQEWiT1BH6OjVrJImoRFre3ndTqBO6CjkVjEqS6aDTbKtDZQMkGRIklCi+7vxQUGjUK0gKwU1JJfwPhFdgq5DS4WxDTp3SBmQzPf/xw5SA7QCnSAnD5z01WNJMFpjMktmLDFEQoi9EhcabRSSa+JAkyYaTIb2OVlU5DqR6HuBiBrdgvIdIbXo7oisPUY3c3SzRNcHDLorTJlTWMgLzUBDpgVrLJiMDiEqg5gcpTOCKAIGihLKkrIYUpiTAFOESB8oJGUh6+fdxIhKoc8wJU1KGjSYUd2bJDqFeNfvOxg8L1A3X0ClRC5gUoZWQ6LdIsbAatpgRpqBGpD5Bb45oK1vEfyK4CuWlSOsLF4C2iR2fA1Vh9In/Squ72lJCD5EmphoEgw3Zly4/x7KDYseBDrV0ZhIRUtHR0qBFDUZlpEq0dI3w0tKHLPgspnz/IZmOMwZ5GMKbaA9pmkXhBSRBKeGZ7hvei+TbIo5kTKWjTf0vSSDc1Ce/oqBSEoRFs+DzvpSrzuclBLee4wx6wvFNV+V9XpZ81K44wKL8+fP88gjj/CGN7zhS37+2c9+lve85z1cv379a3RkX56XMwGP/NiPcfahh3jqkX/F3hOXaQ5W0AbcvCKlhNnZYOONr2dy8RKNT9iy5P63v4F73vog6uAW+498gNXtW8x9w9y1HHcrqsLiL15AnT2DJ6GbSPr0M3B7STxuCMcNcd7gj5e0i4boe+fmFCPx5IFIf4c2AxkIMrAMz5/j/Fvfyv3f9i7ufcdbGUxGvx//zlc9KSWOFwsOD48IMVLXNb/2a7/GO7/hG4ATJSLvCTGilPR3tNUXsx6qv/iUROMcQQWCRJKKeCJHqzkHqyNc6Igq0kaPsx4yBblG5RoKQ1IQYiDEPuBB+ovaE+VdYjzJLCEElwgOYpfwTaJbBaq5wwf6rEwDoU6opDE2Q0WNb6CbB7rKkVLAZEKxoRmft9ipwgwNYtSL2RytToIoLSihH7cSjChMUpgksNBwZKEyJOdJXgiNIkUNA4FcSFkg6kS3EvztRLiViLd793Ox9HK2McIqwRJYJGQJ4gMq9OVsQXojQi29ghknH64qCtpqsmmJyfM++9MJNKCixQzH6MyQMkWyAaH3binCimF3xHD/NvnygCFzBqohUxGtBBcDVQyklNA2xyiNVQqVUt9MbwwhG4Lts3oaj+rqXk5ZK0QJyliMUpjQIdHjY8KL5rg8T2dyNv0n6VKGDwM8lrFqMAL1WNPlhoEboxkRpDdzLEIiqYQ68UdMEhHjkTIQZzeoJ4FWF6ycpllF1K0x84M9Di4/ip5fYaPQjEeR6eaQoizpYterwQloq9C5Rale9jqOh7TjMWpSMJGOoRZi6ljFBXOWBGsIO5cYeKFcLVCuwYRI38si7NrE7uaQ4ZmzzAY5O0qxaUd00fPs8TNEEU6f/kYE2L/xIaReoM0OO4MZo9kOcvZdSL4JykJ72H/desuJ+/yrn3Vpy5qXw3q9rHkp3HGBxXg85p/9s3/Gu9/97i/5+aOPPsr3fM/3sFgsvkZH9uV5ORNQHR3xSz/yI3z3j/842nzpB1s7n/PMv/glHv+n/5zdpy5TN5HBmXOMT12kOlri6o4E6DJDZScnhHRyV9wH3N4e8WgfITI4f47B6W2y2ZAmthwtD1AbAy48cDeGyPzadVLbkQ8GZEUBKWGKglMPPMDZhx7izOtf/+8d35r/MF4Jd4hCjHTBs6grjqsFR4s5XdewbGrmack8VMxDRaM8KU+Q930diV4quO8v6e9mxxPfjxh7R/GUEilBaDzdXotUCRsMA5ORZ3lf8oQlOMF1CdcluiYRO4i14GuhWyaqynN4tOR40VDXDtedqEL1cXBfiqb7IEXSF4vjIkn1wVFMfaCW5Zq8sExGJXlpMcYQnMMtHbYbYdspeZySM4agUBKJTuN8Rmg7pFoivkO07pvtxwkpHbZaobuAcaA7kCSIVshWiTo9QI80BgPHgbR0EEGSIp9OUajeILFySHSICohOKCOo6LGhRfmA6jyEljZEQvSo4FCxwboFxlfY5FAqpy3OEMpTjFbPkdFSje9lfPuDuHKDMN5i2B1RdpFQGurxPXiV4cVx4eBjbLRHuDAgBAH1RdlmSzVb4C4GTscHKH2G6iqkaYhtR0oJUl9GJUZTBGdRFAAAldJJREFUK8+N1RG78xc4am+AclhyRtmE6WDIICuIwwwpNDmakb9N4nn0/dvYyQApMwwG7SPxeAHLOSn0a8qnhIsKdeEU6syEQieGGkxS0EWSczSxplId3uZ0JlHFXWbRsp3Og4lEnRDfS1m7qUPlhlgOWU3O0hiNLJ/kQCwHJObRUyP4BDuxZVMiZ0+9nbsvfDt2dDex2Cam1PvsKE0VAytfs3RLCltglWVsx0yzKUrU7/t7+5Vwflnz6mG9Xta8FO64wOJP/+k/za/92q/xEz/xE7zzne8E4MMf/jA/9EM/xLve9S5+9md/9mt8hF/Ky5kAgGcfe4zP/sIvfMmbOobAuTe+kfv+0B9i4667SDFy9OSTfPr//U946pcfIW5MMfffixpPSF0EF7F5jnGOePkKYX8PdXYbf+Y0aVAQvac76NWdSmUZjSfkgwHb993Hqde8hp0HHmCwuYlSv/8fhH/QeDXXtPalXLxY0pUSGNVnVfpx9SViy6pitVqxqmrmizn782P2jw45nM/ZPz5k1dT4FAkx4E8yKf5k24WAD55Iwqg+a1PYnNlgjBLV93gkoW4Ty6plXrV03hMiBO9740M0KllaF4hRkGTwXhEDgKClLx9bhUMMlpySrvGklFBKE2Kiaz0Gw9iOyEXhTySPu5AofMFmvc0km1JmE6wMUFjEgV406KqBACkBtoAsBw0iDtUcYQcaOzAoE3uBgST9dbpW6HGOzSxiEmkQSbkQBwnoy8g0gsp171FSC7hIKlqi6UgFoBJmbshuTkhVDasWycaIygjqOr68jBl4iiIn7F/ArzxpcYiEDJs8KgVMB+NVQy4RqxLD1fPo6pAmGGrJkczSbnQ0ZzomLnH2UDP0JUoXWKNRur/gXrjbHLV7rOoDuq7ChY6ghKASFmGSDrmweY7tyQZJQSeeuXXcjAccHFW0c0ehpkyyKedKx8wE/OQ0frhDk2pSdsRo6hhmug+6WKHyAcVkCzUZsV/VNEf7eCx6NGGybci7JUUyJ9WFCSVATKRmgffHRNuiBhlRFEs0RylyTS+5bJd46xlLPOm1ETJgCOiTEq2WxJGyHIrQiMLpDC+GTBKbJIbKonWJV5om+RO5aDB2yMJssNITorYMszFv2nwNp4dn2Fc5q9igRJGpnAvDC5wuT3O73uVo+TwPDC+SiQZdgB2RVE7bti+eX1JK0NwmtUc8P3+Spw4/x5MHn6VzFUNluf/ie/jWB/5Ub7y55g8cr+bPozW/f9xxgUVVVfy1v/bX+Omf/mmccwAYY/izf/bP8nf+zt950Yn7lcLLDSy+HMF7rn/mMzz7m7/J4QsvUEynRO/JBgPufuc7GZYlN3/916l3d3uVopTwXUe2vcXmww9T3nUX5XjM6voNnvxX/4p2ueTM61//b4KI2ex3d9BrXjLr1PNLp+06mqZlvlpw6/CgDzhSPDFFhGFRMMwHFDZDKcXW5gZlUXzJPuqm4ebubW7eusXR8Zzj+ZyNjRmXLlwgNxtcub7gyeeucfnyLW7eOmL/aMmqaahcw0Fzm2rVIt4S8CdZEUA4cSsfUhZDyC2ZFVJyuC6RWoU4jekEp1qcbvCu7xXJq5zt7hQlA6zuZX6NyjHJkAXBtB0SIymzYBTaB1Tb+8t4E4k6grVgM0KmSVbAR3TnMKsaYiQNLOrMkPxSRpkJ2WHf7N6eb9F5okuG5CzDtqBcaRQBXERiRCkIm5E0jiCh90J5fky6XhEOriK+w2iFEYNqavALEiuUW6IlEsoMXwIxYIJF6RJLxiQes+GWlHqDXAl+qDkeC9eeeITF8W0GukApjVUZm4NNNgfbTAczXOo48MfsH97kcLnPUEdODQpGgxHjYhtjh0SlaMKKRXdISi15UpSieyUulROn53GTlipeZZQvCG6Ob2oyn9BkeNkgG24yHCXcao4LB5jzG2SZxYpGMoMa5KhMg0BIAUeHSy1trKlS23uoEBkYYZhnGGNRkkgqUnUdx3VNSL1/iiJhRCAmjkSxL4qQW8oyY6ssyTQctse0yWGMIipDFCGkSJs6XOqwGFyXaFKHEmGsDRs6wyrL4bIhjAzLWKEQjsRyLEIWcmZOc0YGjGMi8zVzdcR+mfDju9kYnMWWpzkwY6bT1/Ed9/wxMiIsniU1+6AzolguL3f52NGTXFUatOE7L30nr5m9Zn1h+ipk/Xm05qVwxwUWX2S1WvHMM8+QUuL+++9/xQUUX+R3I7D4t0kp0VUVJsuoj4957rHHuPzxj+PblnI6pZhOKcZjiskEnWUcXb3K4QsvEEPg7EMP8dpv/3Ymp0//LoxszZo/eLSu42B+zOZkSmYsnXO0bcuzL+zygQ9+nN/6xBe4dmufNni+2FgQUyK4hHf96dVqSz5QDMfColoQKot3/Q0EZQPDUgg60sVAt0rElaLoCkbtmKACK7ugjCO2u0uUaQMjGhMFExUCBCV4YwlZhoilCIaidpi2xeuIs5pkNGNvKD0k3xGjwxlFkxucVkQltKWlKhNT5TnXCgObUGNLeVaRpwy9tEirejPKmFCWXt460DermETYaki6QzVjdCoQCeh2CfF5xN9AzTtMnbDDyPi4ZjiHZGa022dYXBqjTY3yC1wZETMgGchdi233yOqWcu+Ixfwmx8sDlqujE1ljobS9GpWKQlUvWPgVDg8ETithw/RKaChLPryL8eQehsUZNBHvG+rumMPmGk7vkRhg6ysUg4zRtMTYCiUVCnfSv6PQ4yH+YE5yAaV0b4A5LLH3niVmGkffq6KVohDFSAxKKeLJxbekkz4nrYjSmzV6AnVKdKkvLxQSmZJepE6kf5z0ASmlUcoS6csaU4r44GhSQyMdOZCLJqF6ZTD6ErckCu0dvYCxwSgPUrOvK1bSUtlIV2haahZhgVMWZTbYSCVltyKPDiEwMhm58bRK8YSOPK2EPBtyZnieM9PXcPf2G7m48XqyYhuKbchmLwYeKSV+4/pvMMkmvGn7TX0fWYrMuznH7pgQA0YZjrojLi9foIuOU8UOD85ez1ax9fv6/l+zZs0dHFi8WvjdDiy+EvV8TjOf0y4WNPM5vm2Znj/PxsWLmGwt2fhKZO10+geProvcuNZw5fmGp55Ysnu8hw+OaumoV5GqdpRlzvnzU0YThU8Vq2bF7tE+wQniRiQsLtZkBQgdi/2W5BVEBUnhfUSbgDae493EauXp2pbYBAqvGUTLKMspdUZrFHVSxK5BtY46OZx3DMKAgcvRURO1JvZiZXhjiAbS2ONPRfzMk0ae2gf2DpbYQ83d+5bz3rI5PIWxBj9qkaKj1+WyKD8gDBRsJuIsIqpGOcGEEQpLGrfEcgGthcWAlASiA/pgTXIPp1uy0wtsozG3W0y1xE8C4dSAsDMkDRX6oMRcHSONIvNzJreeYPzhz1DP9zmqjqhdy2y4yXQwo2n2aFJLPpgxG55jM44oJOszwCmyqg9p2mOGdog2BclkSFb2wUU6gtkIPQPJElo6lL9FuvUUqD5DJNDLPdscs7GJGhS9tLQSBItoDVkgRSGsKsBhdiZIXvRqcBJJ0gEdJAMxI4kmyoxQd7jjfWgXqORQEtFWkeW9ZDLjIa2dolKLxBUahaB7ueQkfb/S8TFKKYwWrEqsbIYnQeyQlLA2w2pDkEiTPEn1cskJIEaUDye+LBUiczDCQiVcWuHSioW0LHWiHuaU5YSkDS4FrnWHKLtDjXAYFgQUXhS5GIwaISnRiMPJAG1nRLG4UPGs2+P09lv4/ge/n2k+ozAFMUbqrubpo6vcaJZ847kHsMby+tnr1+fXl8D682jNS+GOCCwuX77MXXfd9ZKff+3aNc6fP/97eEQvnd/PwGLNqw/nHI888gjvec971qnnNS/ifeJgv2Nvt390XUREyPPE55/4OH/oD70T7xU3rjY890xFlilOnckZTwxtG/G+Nwh0wXP2XMn58wN2Tuc4F7h8dc4TT+zz7DOH3N6rcF3AtQHXRaKPjEYZk3FO03qO5y27N+a4tqO0gkRBrTR+maHSAJtMf7Hs+wbmlAKBSKdTrzgWWmLoSMkTcLhM0WRC1C1n0w4DGTNyiVEsUECua6R0yFJQncWpQJcFVJyAyghK6IxQqRtMm6fYvPt1yPkpTDUq5RCE5BriqoFlJGUV/nxNGkWUH5MfX8Dcs4vauIUdbKDRuKdfYPm5p6h390jOQ+hAdSTliPOWOmgKGTDVA0os3WIf085RITBSBTM7YppPmdkJuTrxXfmiopjwbxQGUjwx0+yQOAccojQoTTCGvqDOI6JRdkLC0rlrNOkWwVdIDL3MtjKgckSPkQjJt4hYlJ2isjHKWII4OjpUalBxBc0RSVrIJ1Bsk6KQnINmhWpXkCAVWyhqdOaxZ8/C1gCZnCKzGkmO2GT4uoBhhbE3kcWcWDekTCGlgWmJzzJUu8T4FVESXYSOHE/WO9zjyaVFJw+KXu2OQB3nBNWhpVdFM6LoktAkaIi02iMqMpCITRGVFEoFMhtoJLKXOubRM0FjxbAUzZHNuF4OmeuO+ewuvu2hv8C9o7upXc04G/dzls9efM/FGDlqjnh+/hyv23yQQTZ46e/XGLneLnl6dczji31SCpzV+5zKMt515lteNRfp68+jNS+FOyKwOH36NN/93d/Nn/tzf463v/3tX/Y5x8fH/JN/8k/4e3/v7/Hn//yf5wd+4Ad+n4/yy7MOLNasWfN7TddFdm+0LBaeotQYI7RNpKoCx0eOg9uO27stXzzDKyXc/9ohD75xxM6pL3XA9i5y5XLDuQsFed4LOMyPW65fm7O7u8LHhDKKqnYc7NcQwUZ49lNHXH1qRewUwRlCyvDlmJQVvZmhC1A3UNXoqgLnEZ2IpWW5M6FzHdm8pmgbnILaKJxWdKrB+WNCd8gwJTZdydlwnolsstItrbuK73aJ7QJvC5w15GbKJDsPkiHRUQSo/DWkeJ6NS/eTT+9BdEQNc1KhYe5Rh0Dj8VNFmmjUTFCjFTG/TJwcoKcl0kTsCy3mcof+wgq/P8fX+3ThgM4tCXh8pgiZQquMSVBMppvobIPSzNiYnEL8gro7IsUGEyq069BdREJAJU0KES9172iuJ2SqJMRAIqFFY7QlCXhJRGNJWkG3QnkPMeBjJDMD8myE6p1yIMtIxpJ0IKqWJNL3+TQB2gDKYssZcTDDFR15extd7ePjPg1HNPUxIVgUAwYpYXWBTDYIZUHT3cK3e9gQGKQSpQq0CEofoDJPNIlkQOl+3fVNSYqYNBHBFAPKyQUYZjSjFRQdYhMK0AheaaJSJ3LQiqRAp4iVjkYiB9FSxkQRE5XOSNoyESH3gbpdsScL5uYmtVnxhbLgyugenjND5qHF+wPyLjJNLTOlGKmSDVWySg01ntH0Lbz1ru/jG+96PaeKksP2kM/ML7Pf1iQRlsHyeLXi8up5xsefpVg9y7heMvCWa2rE43rGcBr5P73jv2bXd3z04El+c/dzPHMUuXd8P2cGp3jvxfv4pq2zXCjHv89njTVr/sO4IwKLg4MDfvRHf5Sf/umfxlrLww8/zLlz5yiKgsPDQz73uc/x+OOP8/DDD/M3/sbf4L3vfe/X+pBfZB1YrPlKxBg5OjpiNputVbjWfFV+t9ZL10WefmLF5z+zZO92h/Sei4QAWsP5iwVXLzeMxoZv/rZNLlwqX9J+U0osDlsOblcsDltu3Fywu1thReEbT3XcIUBR5MRKceMLLcujlnD7mGAylo2j6SKkhEoRoxOmUOgiI+iCtLFBGA9pYmC+rGDeMvCaPGmsCDY4rO/6ngDdIqo3bJTkKdqMzbYkawVPIMQWQgWhQc0MdqNECoM/bmmWS274Oe1kQj48xcQMGNeHqO4FurML4oMGXjsl2px0I6Bf6EhXHMw78rYlX9XIckHyhi7N2bcLQmywXYVOqfcgyQeEfEjMtujKs0QZ4MMuWbUgjwavjlHNLbLgwQhpkCPjMVIWFG1HuZpjj68RlzWJEcgQSQqMxQ0bvHaYoiQzJZOYsVlH5PgQ51cgYG1GyCwp3+iVAruacerY1hajc2w+wuiM/eFDHBavw7T7iK9oiy1UsuRJ0CIUcc7E32TiboCC4DtijJhySpNrDtQubbyJCr2PjNGKTGmiHeDNacLxNoEbjJpdhqkmz3cxNhKJpEifxcGjlEZUgegCPdiiKDK68SncZEQaeFIGsa2IbUWlcqSEUxPHIAfvEivfcRxucKBvsacq5ig0iZEozjLh7mxGIQU6WkQ8Ih4nxxxIxaP5hP+pPMeteIrXtq/HR9iVFzjH43wHB7w2BM53I8b0fk5CZJA8IkfsqxX/2s54zE64ySb3tUfc7Z5n08JESjaSMJLIQZ5zNLuXCw/8Z1xqXsPUjtGlprwwQ1lNSomb9U0+ffApPrH/ab5u8+v4jvPfzioEnq6OOJMPOFd8dT+ppe+40VZohHsGky9VoFx/Hq15CdwRgcUXaZqGD3zgA/z6r/86zz//PHVds729zVve8ha+4zu+g4ceeuhrfYj/HuvAYs1XwjnHo48+yrvf/e516nnNV+X3ar188dT/75Zs3N5t+fV/fcDe7Y6z5/tSK+8T8yPPwYEjht4rZ+d0zhvfPOb+1w6/atlHSonVvGM17wC4/vycDz3yHA++YZvzr92kHGfEkHAucHit49rjK46utoTOM8g7NI7B9pBsOiKknL39yO71isPbK+om0iUNxpINEykLpARdm9PpwM3jPdoukamADR7jWnIf0cHR+lsQHaPBXVh9iq3KYptAa+DYJrwWTG4ZaBiR0KFFjCdtGfzpBmaKlAzxOJBWiUxKgq3I6468yUg1dF4Tiei6QTcVEhwpeZwCVIEiR0QhcUVJgWQzfHeAr67QuVs02hEkEQg4MyBMH8IO70GZErTCpxV1OMZXK5apxelEIKHry5jlM6ShQZ/ZRHRC15CvNhj70xRqSgwdmZQcHj6K81fxwbO19Z+gdMFq/7MMiksM9SmK+gre/DZdtiIay1DOkpsH8WpKe/X/i/h90MKorpiYARMzojA5Rmdo2zeMt2rCYvhmWjVC6ieJ3Qt0gzeBmnD26De4azjAatv70GhNUEIkkCSAq0jdAdIdIu4IRURQkPr/jVcaTUKUpS5GNEPN1qnI+MI2g60J6AZlhSgjijREK4UXYbWr6RqDJxF0ICoHZcl05JjZ27RylVup4gYrFDBOBZtpizwO0VlC1w3xVoWZXyC5GXUekVHF8OwRlH2zP8mRYgFpCIwRZfuSOxVJotFpheUaiQg4BEedNL/CBh/OC65miufVjCtpSqsLSkrGZsbQlAzUkPOTEX/i3gfYUAeMswlv3nwzIsLNasUjty7zseoWR7FFBJwLnMmGfNv2Rf7oqbvRotafR2teEndUYPFqZB1YrFmz5tVO2wQODhyLY4/NFOOxYbZpMaaXt9692fHJjx7z7FMrprP+giTLFdMNy2CgUbpvOVDSu6wbI+SF4vSZnM1ti2sDv/2b11ktOlwX0FqhjaCNQmtF13qWxx3PfXzB4WXPZJSxvWOR6GmXHW2VKGYFo5kmdJ5m0VIft1RHnnygmZ7JCEFYLiyyWXJ78TxHxy2Hy4CPGXY0ZTCbkucDtAv4pmXp93FhzsyNsIcWk0okWlKXIH7xo1J6A1EREglvI2GqYDtRbyfqSYMzEZUlRqdbSunQe5Z0K8NVhqbLSbcM01uevA1UNhK3E5MS9CSxekNLGhnsaky2GKG8gti73ic87fCQZnyAGN8rkFU52WGOWY2w7RgdBIkeMzLIRJM8pHmCZSKsWlK8TTS30UVHmoHaSGThXiSNUFEIso985tP4vQ0O8gvsmRpvT2NkQuE80R3gUoUOLVtuwXjjPrpsTG00SRzDsE8c7RPOOraqltleR5DXAOD8ZRZLSLnDhAW6EbzaQWcX8dfej/IHmHKKtSXanEWFFVI/RWz7MjolCVHgRQhodOiNDFsgHwyZjEbMCmEcHBtJUGFJW9+CfIG2CjFC3UV8t0nOgM6viCkQEZIZEs2IQhI5HUl59OaS2fkhCiFahTo1RGKF//weaVcT2zEJQ1vM8HqM9RoTW3RYEfwBQd1AJpo43aHTQ8Cgm4sUpceZXfJuQb2oMMMdivEm2egUR6Ul5U9ybmePJC0KIaWGmJbUqaFSiQNj+age8ivmHB/Xr2MpY7bGgdcPFcvDK9TtjONwkcxs4TaPMRb8csIobNJ4jZeG1+wY/ps3vZ23bO18LU4vXxEXI89Vx9w3nKK/BiaTa/591oHF15h1YLHmKxFjZG9vj+3t7XXqec1X5ZW+XmJM1FVARGjbwPGhp6pCn9kAUoQQE8En6jqwe6Pj8KDPXISQOHu+4DUPjhDpy1eci3RdZH7sWS0C971mwAOvG/LEJ2/xkV++iqsjg3GGyhJd5/+NCVyCyVbBztkhmcpZ3PQc3+5Y7bbMrxwzv1WTUIhSQCIGT3Ce4DpIAZGEshaxBSElvFRkG46NS54gkfleR324pF2usEYx2JwxzEbYVNAcetp9j+oKbJr23kJCr5ikO6TosGcSeqpRKNI44t/eEO/3pEyIc4V7IVA/rigeH5IvcrKk0AiQSCohRkEm1NEzbx1d5yBENosx1lgkj4Txiqg8XivSfkJuRZQukNKQpgo2IikHlMaPoCuE5hDme4HU9KVHZkdTfD3EcQ3eYRvQNw6wu9dQTtDq65C7heb+hjYfkqJCVi3pBlhXkbkOczhBVTOCzfBWWG7eIm226DGIZGgZktBELwRfE6Ni8/KDYHo1LbSn2TpAtxr1zAb7zT677gYhlKjBkMxGBtKwoUqm2SaZtWhasrrGXr5KfOpXiM1zCIpMEgOlScnjY0AEGI4RK0QzQvkF1tUU3YIyLIhi6KRA+w7tfV+eZTVaZxQokuREhlRFxvEK2lihuuuo1OIkIDGR61PY0YMobTHSMA3XafLzBDVD6YBtjsm6A8buGplKaG1BlSS/BOkDnS50RJOjBkJ274Dh3RnFzoRFMeL5rmXDCjtqyVD2UK5CVQ1KC2kyRWUZOvbrL7kcl0bs54FnS+GR4hTX9ffwuXoL0Uv+qzdc4Pt2zrGzs/Pi+SV6B9c/B9efgHYJvgGdQT4kqDFNPcJlF0Fn7KeWfy23GWwOeO3pUxglHIWW+4oZd+fTl3UucTHym4fX+dW9Kzww3OC5+pipyXlgOOOewYQz+ZCJyV41jfF3EuvA4mvMOrBY85Xw3vPBD36Qd73rXRizdrtd85W5k9dLSolrlxuefnKFUoKxgrUKY4Xp1FAONU88vuSpL6x6C4d04uvT9MZxJjNfsq9m5agXDa5pySwUpcG1jsVB1WdPUm90PhhpiqFlOLTYzNC6XhgqVxrVCK6OHO9Fjm9WzG/OMSpSDi0iQggQfSL43msihr6cTOcWpRIpdtRVh/OJpAMhLXG+JgBJJVAOQaFiiSQDSYBAjC2kDqxGWY2yBq0ygtfolBPFo1LEesEEfaKYBS4PlJOCwaBgxAAiLOfHuBSp2jlttSLzeX/x2e5jumOMJKw+hVVbdNogdoqojCRQa0+l+n6DrrvCKqtozw/J75qSbRWkZo+zn50wO9jCdzWxWBG3xrgLiS4MqENOGgOThFIRHRP20JHtBbLbObZe0BaPY1dHZDmQLmI4RYoevbyJLJ6jzRTz6TnmO2fwD4wYTU4za7Yx5TFGNSiXg1Kk4oC22qXarQkhstjYQu7bZna8SXb1mMFnfgGI1Jlm5e6hLi8SzuZMLg3Iww5+6DBNju9qFjcOme8e4UMiodFmxshMKVTBRCJWN+Q7t1HnhRA2IAjzWU2bLHJYEpYKtdqHW8dUvqZZfo4zbcVd2YSdyZiiusxBdwO8Z7EzpZruMD+6F3cYsc6jU0IWnyJbfhY72GAwfR3l0afQ8ZCJLHAmZ0+PqVxEBhH3rfcyqxpOP71LGzxduwIFk25FFjWLwddTzR5mcl6zM3ueyewWDDyDbI61xzTK8ly6yAthSKOPeSMLzuLZMQFLICpDQmhdBxF8EjoSXgneFGhn6eKYy9zDh/XX85T2pOIFrEnofMrhcJObgyFbZcHXDSY8pKe8MxuxsVzR7t6A5jZF1hB14snJOX7LlBw4z9nOc6o+wlX7FKMCV+bU5Yzjcos90VTeY6T377lUTnh4dpoHR5u/Z8HGC9WcDx3e4Ga7og4ngSmwk5VMTc6VZkEVPJu24C3THd4xO3NHBj7rwOJrzDqwWLNmzZqvHU0dWC4CbRtp20DXJro20raRpg5UK89q3tKsHL5zFIWQYuT2zZb92y0h9KVHrnW0tcPXAbpeStbmvcO2C6mPCf6tJJJEoBFIgtUK7RSxFeg8qXMkH9FaECW9R4iKvVcFgpgCrRSxc6TOoWJA4TFaEBIxBoLvEEkkSfgQTjJCmhQ0cqK+VAxhY1vIBpqQFD46FvMFMS8JZhOlJ0iKiHiKQUUMGa7Kke4IugVS1VgUmc0YbOfkRUZaCV0dcVFR+4wbwTNPjqGs2ABSFyEYwOC8ogmaRgtRKWJqGQTNKGQEERY6seUsB6bjMAt4CQSpcGFBKQU7ZpsCg0keHYVFd5XQ3WaryLD5GSScQ6kxCUVIjhQ6IJLpIVpZ2voJ1Ow54jseJlcXCbolZEsG0WJDJLoD5KkncNc+T9ut6JIiXrqXweseJMvPIN72GZ3pnObMbVK2QtUDvI/Mn+o4fmqCvbnPYLlL0BmFLijuuwd1b45MV8RJhdsS6mJA3tTkbQ0aglhc1IQkqLYhzB3p1AQ/HWNKT97sw8c2KJ/aJjZ7tIM9NvR9DDZvMCuFvOsYHz7OoL6MlwKzb6nLu9i/8CB1fg+cuoltbqKv7hCaMdP0ryjD58A5aArCfEoIR3hfE8KC0WTOzoUGPSqRPKeLAd84pB2S6RH5dIYqBlRtga+GMIzEgac0m5TKU4wibjBnMNxjGHZRKRGwJAmY5JHkTxTpBEnQ6zFDFGgkUkmkVoIWzWZMmARCIkjCqYRXERUFkzQqCSplvRyzWKJXhCjsS85yeJbbG+eYnXmAzdlduOEZtqzirHiy5Oli4Eo959G963x+eUhTt8y6jou+Y0cURTYhM2DDnKw7YtgeIb5B24JWGSrJaM2EKzLjBdlkmQtPdMc83hxSdR0qDJFQELLLnC5q/ovX/An+6uu+iVzp/+Dz1+/U//a1ZB1YfI1ZBxZrvhIxRm7cuMHZs2dfkaUta15ZrNfLK4eUEsdHnixTlAP1O37wexfYu1mxPGpZLhxd7fAu0tSOo4O+p6QcGIzugxWlhAS4LqGU4Dzs3XYcHTpiiHjn6WpBJYNKmkxrRmNLWSrysSLpXnp4cyZUBw2XP3dIu+gvFJUoMqMxoW9YDz72d+VFSGhEErqAfJiRDw2jjZKN0wNIiYNrS5YHFa7rEAnkGYymmuGmwRaJm9drdq+0kPp1GUKLKI9VkbyOKKdQUeFTTZOWpBkMzg3Y3tzA3t7ALRPHtxY0dSTqnCLPycSAlz5gSoKRApGTi7TkiekY565z4HY5piJmGSmzSKboyBnbN7OlTnNTnmSZzxlt3cNkI8eVCxI1/okF+nYENWKWZpiwIG93yUSjVI4aJBgaGjT4nCIaCFdJLbSyTZCcy2VGpYUNJxgUXfsCXh2TBiOM2kaFEZq8VwJDEUOiUjXEgA4dUYEeC2bRYKuGrpyxGG8RHkgMHlxQtpH8QOP3b6OqIU3K8KuG88FzRhtOt/tstdcxeGLbkWrH4eiNVOMR9c4N4mzJ7XbAKuTc3yx5YNnwzFtLfFNgVpAWFlkmytWK0/OPUlTP4mJL2y3onKL1iUXIWaUxSSwJ8HRY1dGqRFus6LoO02iKpuHeUc65s3cxOTfBnprhJpuISSQlVPqQyAIVIjoGkiicnkLcwqOpdM1Sz1EMmash0W4ykQNE9jkaCPORZiEDfNAM2o5Zu2JiFaeiZjA6xMZjpHPoGJDksNGBaGKyJDS9gLHqfVBESNJLH3uxuGQJwROSRqQAsbRi0EZR0GGlxdGicGRUZHTY6MliQAEqCYJAMr3hZEosVYM2Bq1yYjIoNWGQb2OyLdATsCOORMhO38Xg1D10xrBqK25Xcz67vM0Xdp9ndnwLL4bbpx7kobvewH+ycY7NfIgebyJfpuckpcR+c8zVw8tUe5fZNJatfMzmYIYSgY2LSP7V1cO+HC5G9ruaK0f7vP3spTsjsHDO8Z73vIef+qmf4jWvec3X+nBeEuvAYs1XwnvPY489xjd+4zfecaUta373Wa+XNS+FlBLXrjQcHrR84uOf4dv+8Fs4c7akqXqH92rRq3ItjhpuX21oF4HQJZRSKKvoOqhWnvm8Y37k8D4x3sgYDkt8pagOPe2iozqucPOa0LQvmgKKFpQSJCVwjlB3pBR6+woRtDEYo8kKzWBiGW5mjE7lWCJKIB8Z6mXF9au3OTg4xlqha1q6pmFQaow2pM6AWEyWM8jHbI82T1zSPW3TUi8boou42lEtG8ScJZghRgStBKeEViBKwKeGFBeQluTZBpnZJKZIjHMq7TiSQEciBCCBCx0qgcGRY9iWDTIpiemQTFYM8ozM9M3hzjkqvySkI5w5ZDk/ZuJeS2bvw2YWYzUjfUjbReqoCKMct1HRuQO0s8R4gb0EB2g2/JCzHeSLp2nZY2+UaFUBaURZN5h2SVcMiNOc7PSIKNDdPEQtlgxaTbSnWQx3ML7mve2HOM0+t+8uOH7dhObCABU0Ox/eQB9fpEgdW+4KJtyiS57WXTsxawx4HJPS0o42iE4jwSAJlJtDXbKX7mWx+0E2wxUujEuGRQaDKRQFupiAHfZLpWsQZWG0QbIJZwQxG4S64viFX0cfXUF8x3KwgTv3AGc2x5S3r6KXx6iYUDpHmQEpbRGcQcKCbHNEca9mdc6xKKDVhn0SN7RiHC33rgxjL2TGoKwBJdBOUFWJyleYyTVEJVITSHUk1pCaiKt3cO4hqmKTuogQDihWR6jUYekgG6DtBvhI6vbRGwvy6RQ9chwOCxbxkIyaIs0RWWJYYtISSQmdIgpoyRABQ4dOYFLqszbR9J47KhFR1BIhQYmhMAUhBWJ0uNjhUgQUJvWBTgACmiCalDIClqg0IiVPFWf59c2znLnnnfzJ+7+NzfxLJcVXqzkvPPdpbt18ivbwJjHUJL8ihRVLWfEnvv/9d0ZgAbCzs8Njjz3GAw888LU+lJfEOrBYs2bNmjV/EAghUi9dLyd8ovB1+uKY6jiBgGsdy0XD7o0Vl58+5upTK3wFsdEsjzq61kOMqBiREBEfkARa9Xf7EYVYgx3lZKUC74irFjdvSKkvKRMjpACEhMkV+dBiQuyNAFPA+47xRsF0e4BVBiUKLQptFFYSqemwhaGloK4Di+Ma8Y7QBY6rjlXj0bZvnje27z1IgFYZKWg672mDZ5UCQSD3GlrBqowNp9i1h1wtryNNhJCzkd3HIB2zIRVoh8kTWiXaSoh2CMUQawuyuuLZxTMghlk8zSZj8ghVqlhmQspLBkOFAurDOfVqlyCBODhDlVl8uMpWfYQyl9jdfJBxXDHRc6ZyxFa4TWZb9r8lY7VlaRYDssVF8tU2USri9Dah2EdiwB5r7O4F8s4w9NdRyyXXJjt0W9voS4FYduSfOUe87WiO5xgZocKS4ugjbN7+RXJ/AAlC6hXLRhaGRpOSI4Smz6ANLjIqLzDJRvjuBqm5RZ0bVhcuMNg4Q64z8kYo5waRjP3NROlH6ONr5Iur2FD3Aa4EJKxQfkE0ijCYEclQrYcORAyRjiQJiX02IyohSUYSQ1IWlTTSHRBYUYwvwuB+pK1Qbg+cI8XeYDKiCTGyUJZC1YRyB87dx1ZxSBmepbW7eFMRTQI9BLOBUlOUnvbHqiuUXxGrhrZL+Ntb0Fm88nRZx43ZIWE64EZZU5ULNsdDxtYwqjSzVjEwLQOdIOSoaMnbgAkBnwIdnpVtOR44KHNKExixi4ktwQ0JbkKtExiwqWPgO3IV0CYQtcMn8PQVoJ0uUWnEa/7Lf3XnBBY/+IM/iLWWH//xH/9aH8pLYh1YrPlKxBi5cuUKFy9eXJe2rPmqrNfLmpfDq3G99A35ga4NdK3vt5uT7TbQNv7F37s24NzJ1zawOvIsD1zv3K1Ba4PWhnqRWB075nsd1VFHe+xIte/vMJOwpTAcG+giceWRmPqsRK4pxxltB22IJBF0oRif0py5WDIqhSzTjHZKgo9orTClJsZE8on5rQqlhXxoufHCnHZDc1FmqINEcZfB4Tje63jhCzXzPcfGZMB0WCJiKEqFq2uqozleKva6xM25ZuESKg99QOQtkNEmj48rYvKIwGYqyciI1qBsJNMJIxobhM6BdodIXNKKpss2OTaB63KTocnZLHeYbFmKwhFcS2xHZEyxZkgSj6djtz5mf9EgdcuZtMG0WdGlXQ6HGdmlI079sYo0H6L3HSm7DXEIy/vRR/fThiVu+STq6Cb50RHl/iHF/m02rUIPTvPpnW9GhYYDW5MuakZvzsgmATmOpJuOqgkoRhTKkdmAHTYUfs7o888w+/xttvSASTHFFiPqbIJIjhWNi4G2O2a/XnKta1g1BwyamwxNAeUGCkv0njYakh2StrYJ2zlxlFPZDUrXcd/Nz7Mxv4YMNmhGm1zLDLcU3K5adtJ9aL1BUismYUq5epazxx9lVdxPtAMyo1DT+8jGM6ZqSakSpvKY5QqpD0ndMRIiSCJFT6tbvBVUvkWhNjEuIcmjhga7dZU4/QISIFuMWOltWpkRO0tslqRqH9euoK2w3qGJmODQ0aGMhSwjmSG6nGAuFqgzLTJVHJWKQVCY44B72tBez0hVS515wuYWo/GEkWowWcOp//Pfv3MCix/4gR/gH//jf8z999/Pww8/zHA4/JLf/+RP/uTX6Mi+POvAYs1XwnvPRz7yEd7+9revS1vWfFXW62XNy+EP8nr5ohHj0X4DgDbCbLukHHyp8Vtbez732D6fe2wPZRXjjQyvIsvac3zomB9Exjs5OxeGZLmmnjtuPbng9pMr5rsNxThx/p4cW2jqeUeoA9EJ1TKCzdjYGTLZKNAK6v0FxBaVHNvnhmgMxdRQzAwmF56/cshTTx6wNc0plCK0kePOEXcK7r1rk7uHI1ZPtDS356SZ50Z+iFcRm3JildMewep6pJ55BplGrkPtO3TSSCbEswIJ4pPgK00SgxsYrFaMUslRWuB9w5QJgUCWFHN/EyKYlJFJiUWDURgjKMl4wn2OZWrZ0GfYMKfYj4e0uWJ0l2FwT0OeH0F9RKYDRgkqbhOaS8Q4JBpNN10QZgvaQYcrHYNsH1t4WCaOPt3SfDhSVBuYwVmGxQ5eKXArMIGQaTQGrJBtZdiZRvDERSQ2keQCiNDpBiMWjSKJQhlDFEMMBh19H6gNFSoTFEIwDamryG4FUtPSlp5moyGOasLUEQaC1woVhGw1Znb9LprJcyxP7f//27vzOCmqc/H/n1NVvc1Mz8ZsDPsmiywuuKECbqhxI5qbGI1Ro8a4ReM1+k28N5rEgCYmmsSoiblXE6Mxyc8tcbuYIFtwAQEBQRYZYWBmGGbvvWs5vz96pnVEgYaRGfB5v179mu7q6qpzup45XU9VnVNoMw+9rZWCVSECTYX0i63Fcnbg86IUOHX4lEPKyMdTCs9z0G4H2o3j4mG4cZQbw/FbJD0Lw1GEfPmE3TiFliKUX0LCl0+5MQC/lUeq0EClHJx4I06sHiedJO3YJFyIaD8tWtFkuTQVmFDUD59ZySjSjElqCj2DPKUw3Da0GcTnq8LMK8NVms2RenwqQXGqlryC/ihCONHtpO0dJIImycIwJ7y66OBJLE466aRPfU8pxdy5c/djaXZPEgshhBDi4OO6Hm/8s5nFrzRSWORjzIRCCvv5qdueZktdglEj/dRuaKGupp1U0sFzNDqlcCIGTszEMA38PoXfD6YB2vPQQCLl4LgaK6goClqojjh2PA1aE8gzCfhMVOflXmgNSmEETcygSSrh4TgOGvBsD6UUeaV5lA8pZNihRVSNKGTAsSUoE1YtrGHBw++S3mSgbRPXU8QMTb3Xjp8EcUcTViWgNJ7W2JZGBRUFCR8hx0c66BHw+cjHIuDT5AV8WE6YRLuD4xmgM4MaeNrAxiONi0NmsABLmSjDwA340EETw29gmD60Y6I8F9P2wNXYlg/taZSdJGm3k/YipHUEU/lxtEHa8BE08kgbNjrkEfK5uP0gmJ8gTzWh0s1Y6SReqhVtJ3FNAy9ooTAhXYjjlkAyhNHhR7cbpJ12km4NycJ28iqrCPpLoC0BbgC/GSCfEkzPj3I9tNZ4nkO6cSWGUvhCY/B0HLM6iD18A6kJQXxmAcbGMPqDfvg6writm1ChUoy8MNoCJ68A1xfE9Xk4gxLYZSmS6SRuKI3f9JPXHsBsC+HuCJBs6sCq+zeV8XcoSGwk34mQ0CaYBbhGAVqF6CgdTFtROUYoH184jFeeR6I4SEqnCDtJdH0e3o5SJsQ3EIluJJVoI2DXUOTFKHFj2NiY/UuJpjQbtrkkDY+8iSPJO2wk1pAK/GkbFWnjG//964MnsTjQSGIhdsV1XWpqahg2bBimufdD0onPB4kXkQuJl/2n5v0476+PYac9qgYEOezIwt0OEaq1pqE+Rc2GOJs2xolFXbo2k+t6pGM2iWiSeCSFYUBevoGbsEm2pXFTGicFPr9BRXUQX1Bh2w6BsGLI6BL69c/DHzDxWQbJtjQ71kWoebOVjoY4ytD4QxaeNjEshZtysBM2GJBy4piWSSSeImhZaFvhDwQIFQRRgGFp8ot95Jf4cZMu6fY0bsLDTjh4lkHc0MRth3hbko6WCOlEEg8HDxfD1JiGQci0KLBM8n1+gvkFaCdIOmaBZ+EaGtcw8ApM/IU+woBCkfI0QZ+fVKuL3eHieG5mFCfPwdFJLG1hKT9pE1KGi2d4eFoTJIifIAFX4cuMIYCXOXGDY4KtHVw3jdaZMprKwmcEMZWFoR3QDo7hwzN8oExckigvieHZ+F2NYacxjAJc00faS3fO72GFivAMTdxIw4hG8sbWY5WnsLyBeOE4aSdOIprGn7CxGtowGtIktpQSNUZiBsqwzAC4MbzUZqzyKHkTAvhLizFbR6DTAWxfnIQvRqpfDC+QwsXE8wy8pMaXUOTH/fjTFj67hVBbAzpmk/BcEiX5mKWlKMbhsz0ML4rCQlnghVvRdOBtSWCXtMIAjZP2SK3bTnxNlFhLP5z8IVhGkD++fc3BlVgsXLiQ3/72t2zatIm//e1vDBgwgMcff5xhw4Zxwgkn7NEyZs+ezTPPPMN7771HKBRiypQp3HPPPYwePTo7j9aaH/7wh/zud7+jtbWVY445ht/85jcceuihe1xWSSzErjiOw/Llyzn88MM/d5cqiNxJvIhcSLwcPNJpj0i7Q3u7TUebA4DPZ9DclKb2gwTxuAuA1h6R5hjJaBrXcXFsD9dxsVMOqVgKrcE0FQHTxNMepqEorQpS1j9EXqGfptbtjDl0JPnhIJ5WeFpnhk91Ne1NCVrqE6Tb0qQiNjoNXjKz4981EphOO5kbRmqF43qd949xSMdTuHam/4rrODhpJzNamOVh+QwKCgL4DQvlmQT8BqZpoLXOdPI2wXMzdz5XKlP+YMhHuF8If8jK1HlHlEhLBDuRIhVzsNMa1/XQpgV+H75+Acwik0C+j8GDiigvzyOU58NNukQaY7iOS0G/zDDLTsqhrS5K0wetxNsSpGMeThJcV2MnTVzHwtUGKeWSNh0cfxrD8igfWEjF4BK8qEnsfRulIc9O0ZTwk/YXkQSSTgzDg4A2sXFIek2ogI+qwiB+pYgmUyTSdmfC4+DaDik7TdJME7cSnEg/tD/Olmo//YpGETYrUEYKT/vBDmLpfPAUXjqNjscwXR+GFcD1K1QwhZHXhF3QTCTisX2LTdIIYZDG8Bz8RpikUQBmkHJfGRHTI5aOozyFz01h2u1onUAbzTz22qUHT2Lx9NNPc8kll3DxxRfz+OOPs2bNGoYPH86DDz7ICy+8wEsvvbRHyznjjDO48MILOeqoo3Ach9tvv51Vq1axZs2abL+Ne+65h5/85Cc89thjHHLIIdx1110sWLCAdevWEQ6H92g9klgIIYQQoi/QWhOLuUTaUvgsRTLlsuX9OPV1SVKxNIlo5maRyXi6c7yrzGXmhgEFxQHCxUEMy0faNWhvc0inPDw303netR08x8Pygc+nCIZMQiETy2eAUriOJhF3iHakaduRINqSwkuCdhXK1GhTo/xkkwdlKPx5AULBANpWaFujjM4hg9Np0vE0eBrDAMuyCFgmIcuHzzQxOj+fTtvEo2nSMQc80GjwdObMhadRloHpy9x7wsAhXGpRPiAPK+Cno8nLXGZmKkJhi4qhfoL5mpb6BO1NKVJJj2TKw7NdtIaiUh9l1UEGjgiD7bL8/7aweWUbISwKQj48G+y4xjAV4X4hkh0OkZYUtt11/wwDrUAZmUvILMsiGAyA45GMxUnbaRLaJWVq8gJBAqaB7ZgozwAniWnqzL0qFJghi7yyfEKV+dh5UFfXQktbHBUsQBkhrGQT4USafA15SUXAS1KAhd9n4Ms3cf0GW5sMUsoH+WHwB8AyMLRCK5Pv/Wv8wZNYHH744XznO9/h61//OuFwmHfeeYfhw4ezYsUKzjjjDBoaGvZquTt27KCiooL58+czdepUtNZUV1dz0003cdtttwGQSqWorKzknnvu4eqrr96j5UpiIXbFdV02bNjAqFGj5FIFsVsSLyIXEi8iF30lXrTWpNMa7WmCoe7lcBxNOuWRTLqZHfukRyrpEY/atDQl2bQuQmtTKnOHetfDH/QTyPPjz7PIXAj1EV0vO+8GXlRgYkeStGyLk0zaeEFFIGgxfGSQoGWweXWc9gabcJmforIABcUBCor8WAETQ2lizUm2fxBj2/ooyZiDaRkUlvmoHJrPgFGFlFQFyS8yaW+OU7umhfa2FJFomlhEUxDKw58XANPEn2eQl69wkjbb1nSQTnqUj/JTXR4musKjvSZOtC1GKpkmWGwRrPDh+Sy0X2Vu6mi6uO0K2jVewiUdSZFOptEaQnn5FBQWoQMG8XSa1uY2ktEEVtLDME1QGkMrbNcmr7oKvwWGkwDDxkm4+PwGxdUBvvH09D3arz0gzpOuW7eOqVOn7jS9sLCQtra2vV5ue3s7AKWlpQDU1NTQ0NDAjBkzsvMEAgGmTZvG4sWL9zixEGJ3EolEbxdBHEAkXkQuJF5ELvpCvCilCAQ+uX+KZSksyyQv/1MSn7P679U6XVfT2JCivc3B8zSBgEG/cj+JuMtbi9v4oD5F+cQCRp/sx/MyN0z0PE3S0bhuJhFqTRi4ZQWUV4apqAowclQQw3bYsradTWubiC62Scc1/oBFJKJJJA1MXwGFZX4KBgQpKrUI+Q1ScY/WxjQ7Wgx8g/px2PgCnJYUm9+N4Po9gkf7KM8rxrAMdFphGiZl1flYPoPtNUmad6TxVYI5ENobE0RbTNIpP4PGhBk0KEB8R4RgoZ/CyjChkv64rkGoxGDHjij+QouC/CAV1YUoZRBp8dixOU2kwSYZdUjsSNO6qXWPv9cDIrHo378/GzduZOjQod2mL1q0iOHDh+/VMrXW3HzzzZxwwgmMHz8eIHvmo7Kystu8lZWVbN68+VOXlUqlSKVS2dcdHR1A5kjAR/+aptntueM4mbuSdj43DAPDMD71uW3bmKaZfW5ZFkqp7HPIXF/70ec+nw+tdfa553m4rpt97nkelmV96nPXddFaZ59/Uj2kTrnVyTAMxo8fj2EY3epxINfpYNxOfalOhx9+OI7j4HneQVOng3E79YU6KaWYMGECpmkeNHU6GLdTX6rT4Ycfjm3b2fueHAx12pPtZBhQVmHSf0CwW50Ki0zO+mJZTnVyHI8dDQ6rVrRT836CgrCPocdXY/kMEnHNmlXtnDatlIlHFAPuLuuUSmle+79GamMex10yiPIKA52ASJNDLJImvzRAytVsWNNB3fsJiqoCTJwWRmGSTLrEYzaOo4h1pHl/2Q7eeWUHfsMiEIjj93VQXGHRf1geRU0FkDKJ1Ni0GC6bvShaa7RWJBIOTY02rW02pqVIK5s9dUDcPefqq6/mxhtv5M0330QpRV1dHU888QS33HIL11577V4t8/rrr2flypX8+c9/3um9j4/qoLXe5UgPs2fPpqioKPsYNGgQAKtXrwZg7dq1rF27FoCVK1eyYcMGAJYvX05NTQ0Ab731FrW1tQAsXryY+vp6ABYsWEBTUxMAc+fOzZ6hmTNnDpFIBICXXnqJZDKJ4zi89NJLOI5DMpnM9j2JRCLMmTMHgLa2tuzwvE1NTSxYsACA+vp6Fi9eDEBtbS1vvfUWkDmLs3z5cgA2bNjAypUrpU77WKdUKsVLL71EKpU6aOp0MG6nvlKnTZs2sXr16oOqTgfjduorddq2bRv//Oc/cV33oKnTwbid+kqd2tvbWb169UFVp97YTmvWrGbgkBCDRjQxdUaMC77an+aWzbS01DFgUJCjTmymsLQZy1K7rVMoZGKGVnLmzHwiHQ4P/+YNnv17PYvf6eDpOSt4e3UbW+sTtKZXcuV3B/Efl5TR2PJvjj2xhCOO8aN9yzj3S1WcPrOAo85p4jf/dypX3TOMCTMdZlx7KKGRYZZtbOKt1c3841/v8ty/VvCvNzfwf2+s5ZU33+XNdVt4Y+066pIbGDQpiVW+hcDALeypA6KPBcDtt9/OfffdRzKZufFNIBDglltu4cc//nHOy7rhhht47rnnWLBgAcOGDctO37RpEyNGjGDZsmUcfvjh2ennnXcexcXF/OEPf/jE5X3SGYtBgwbR0tJCSUlJr2flB+ORhgO5Tq7rsmbNGsaNG5dd5oFep4NxO/WVOnmex/r16xk1alTnUbYDv04H43bqK3WybZu1a9dy6KGHZu4ncBDU6WDcTn2lTkop3nvvPUaOHEkgEDgo6nQwbqfPuk5KGcQiKZJxm2DITzDPxLSMbD06OjooLS09eDpvd4nH46xZswbP8xg3bhwFBQU5fV5rzQ033MCzzz7LvHnzGDVq1E7vV1dX853vfIdbb70VgHQ6TUVFhXTeFkIIIYQQnzu57NceEH0suuTl5TF58uS9/vx1113Hk08+yfPPP084HM72qSgqKiIUCqGU4qabbmLWrFmMGjWKUaNGMWvWLPLy8rjooov2eD1duVpXXwshPsp1XVavXs348eNl1BaxWxIvIhcSLyIXEi9iT3Ttz+7RuQh9ALjooov0b3/7W71u3bp9Wg6ZAcZ2ejz66KPZeTzP03fccYeuqqrSgUBAT506Va9atSqn9dTW1n7quuQhD3nIQx7ykIc85CGPA+1RW1u7233gA+JSqKuvvpr58+ezfv16qqqqmDZtGtOmTWP69OmMGTOmt4u3E8/zqKurIxwO77LTt/h86uqDU1tbK5fKid2SeBG5kHgRuZB4EXtCa00kEqG6ujo7etinOSASiy4NDQ3MmzePefPmZRONioqKbI96IQ4E0gdH5ELiReRC4kXkQuJF9LQDYrjZLuFwmJKSEkpKSiguLsayLKqqqnq7WEIIIYQQQnzuHRCJxW233caxxx5LWVkZ//Vf/0U6neZ73/se27dvz44jLIQQQgghhOg9B8SoUD/72c8oLy/njjvu4LzzzmPs2LG9XSQh9logEOCOO+7IjhkuxK5IvIhcSLyIXEi8iJ52QPSxeOedd5g/fz7z5s1j4cKFmKaZ7bw9ffp0STSEEEIIIYToZQdEYvFx77zzDvfffz9/+tOfsncWFEIIIYQQQvSeA+JSKIDly5dnR4RauHAhHR0dHHbYYZx00km9XTQhhBBCCCE+9w6IMxYlJSVEo1EmTZqUvfxp6tSpMjSaEEIIIYQQfcQBkVi88MILkkgIIYQQQgjRhx0Qw82effbZeJ7Hz3/+c6688kquuuoqfvGLX9De3t7bRRPiEy1YsIBzzjmH6upqlFI899xz3d7XWnPnnXdSXV1NKBRi+vTpvPvuu71TWNHrZs+ezVFHHUU4HKaiooKZM2eybt26bvNIzIguDz30EBMnTqSwsJDCwkKOO+44Xn755ez7EitiV2bPno1Siptuuik7TWJG9JQDIrFYunQpI0aM4L777qOlpYWmpibuu+8+RowYwbJly3q7eELsJBaLMWnSJB544IFPfP+nP/0pv/jFL3jggQdYsmQJVVVVnHbaaUQikf1cUtEXzJ8/n+uuu4433niDV199FcdxmDFjBrFYLDuPxIzoMnDgQO6++26WLl3K0qVLOfnkkznvvPOyO4ISK+LTLFmyhN/97ndMnDix23SJGdFj9AHghBNO0Jdddpm2bTs7zbZtfemll+oTTzyxF0smxO4B+tlnn82+9jxPV1VV6bvvvjs7LZlM6qKiIv3www/3QglFX9PY2KgBPX/+fK21xIzYvZKSEv373/9eYkV8qkgkokeNGqVfffVVPW3aNH3jjTdqraV9ET3rgDljcdttt2FZHw5iZVkWt956K0uXLu3FkgmRu5qaGhoaGpgxY0Z2WiAQYNq0aSxevLgXSyb6iq7LPEtLSwGJGfHpXNflqaeeIhaLcdxxx0msiE913XXXcdZZZ3Hqqad2my4xI3rSATHcbGFhIVu2bGHMmDHdptfW1hIOh3upVELsnYaGBgAqKyu7Ta+srGTz5s29USTRh2itufnmmznhhBMYP348IDEjdrZq1SqOO+44kskkBQUFPPvss4wbNy67IyixIj7qqaeeYtmyZSxZsmSn96R9ET3pgEgsvvKVr3DFFVdw7733MmXKFJRSLFq0iO9+97t89atf7e3iCbFXlFLdXmutd5omPn+uv/56Vq5cyaJFi3Z6T2JGdBk9ejQrVqygra2Np59+mksvvZT58+dn35dYEV1qa2u58cYbmTNnDsFg8FPnk5gRPeGASCzuvfdelFJ8/etfx3EcAHw+H9dccw133313L5dOiNxUVVUBmaNE/fv3z05vbGzc6YiR+Hy54YYb+Pvf/86CBQsYOHBgdrrEjPg4v9/PyJEjAZg8eTJLlizhl7/8JbfddhsgsSI+9Pbbb9PY2MiRRx6Znea6LgsWLOCBBx7IjkAnMSN6wgHRx8Lv9/PLX/6S1tZWVqxYwfLly2lpaeG+++4jEAj0dvGEyMmwYcOoqqri1VdfzU5Lp9PMnz+fKVOm9GLJRG/RWnP99dfzzDPPMHfuXIYNG9btfYkZsTtaa1KplMSK2Mkpp5zCqlWrWLFiRfYxefJkLr74YlasWMHw4cMlZkSP6dNnLOLxON/97nd57rnnsG2bU089lV/96leUlZX1dtGE2KVoNMrGjRuzr2tqalixYgWlpaUMHjyYm266iVmzZjFq1ChGjRrFrFmzyMvL46KLLurFUovect111/Hkk0/y/PPPEw6Hs9c8FxUVEQqFsmPOS8wIgO9///uceeaZDBo0iEgkwlNPPcW8efN45ZVXJFbETsLhcLa/Vpf8/Hz69euXnS4xI3pML45ItVu33HKLzsvL01dddZW+4YYbdFlZmf7Sl77U28USYrdee+01Dez0uPTSS7XWmeH97rjjDl1VVaUDgYCeOnWqXrVqVe8WWvSaT4oVQD/66KPZeSRmRJdvfOMbesiQIdrv9+vy8nJ9yimn6Dlz5mTfl1gRu/PR4Wa1lpgRPUdprXUv5TS7NWLECH7yk59w4YUXAvDWW29x/PHHk0wmMU2zl0snhBBCCCGE6NKnEwu/309NTQ0DBgzITguFQqxfv55Bgwb1YsmEEEIIIYQQH9WnO2+7rovf7+82zbKs7MhQQgghhBBCiL6hT3fe1lpz2WWXdRv5KZlM8q1vfYv8/PzstGeeeaY3iieEEEIIIYTo1KcTi0svvXSnaV/72td6oSRCCCGEEEKIXenTfSyEEEIIIYQQB4Y+3cdCCCGEEEIIcWCQxEIIIYQQQgixzySxEEIIIYQQQuwzSSyEEEIIIYQQ+0wSCyGEEEIIIcQ+k8RCCCGEEEIIsc8ksRBCCCGEEELsM0kshBBCCCGEEPtMEgshhBBCCCHEPpPEQgghhBBCCLHPJLEQQgghhBBC7DNJLIQQQgghhBD7TBILIYToYx577DGUUtmHZVkMHDiQyy+/nG3btvXouqZPn8706dN7dJlKKe68887s6676fPDBBz2y/LVr13LJJZcwfPhwgsEgZWVlHHHEEVx//fV0dHT0yDr2xZNPPsn999/f28UQQoj9zurtAgghhPhkjz76KGPGjCGRSLBgwQJmz57N/PnzWbVqFfn5+T2yjgcffLBHlrMrZ511Fq+//jr9+/ff52UtX76c448/nrFjx/KDH/yAoUOH0tTUxDvvvMNTTz3FLbfcQmFhYQ+Ueu89+eSTrF69mptuuqlXyyGEEPubJBZCCNFHjR8/nsmTJwNw0kkn4bouP/7xj3nuuee4+OKL92nZ8XicvLw8xo0b1xNF3aXy8nLKy8t7ZFn3338/hmEwb948wuFwdvqXvvQlfvzjH6O17pH17C+u6+I4DoFAoLeLIoQQ+0wuhRJCiAPEscceC8DmzZsB0Frz4IMPcthhhxEKhSgpKeFLX/oSmzZt6va56dOnM378eBYsWMCUKVPIy8vjG9/4Rva9j18K1dLSwrXXXsuAAQPw+/0MHz6c22+/nVQq1W2+jo4OrrrqKvr160dBQQFnnHEG69ev36ncn3Yp1CuvvMIpp5xCUVEReXl5jB07ltmzZ+/yO2hubqawsJCCgoJPfF8ptVO9Fy5cyLHHHksoFGLAgAH893//N67rdvtcOp3mrrvuYsyYMQQCAcrLy7n88svZsWPHTut48sknOe644ygoKKCgoIDDDjuM//mf/8mu88UXX2Tz5s3dLmcD+OCDD1BK8dOf/pS77rqLYcOGEQgEeO211z71O5o3bx5KKebNm7dTvV5//XWmTJlCKBRi6NChPProowC8+OKLHHHEEeTl5TFhwgReeeWVXX6nQgjRUySxEEKIA8TGjRsBskf/r776am666SZOPfVUnnvuOR588EHeffddpkyZwvbt27t9tr6+nq997WtcdNFFvPTSS1x77bWfuI5kMslJJ53EH//4R26++WZefPFFvva1r/HTn/6U888/Pzuf1pqZM2fy+OOP85//+Z88++yzHHvssZx55pl7VJf/+Z//4Qtf+AKe5/Hwww/zj3/8g29/+9ts3bp1l5877rjjqK+v5+KLL2b+/PkkEoldzt/Q0MCFF17IxRdfzPPPP8+XvvQl7rrrLm688cbsPJ7ncd5553H33Xdz0UUX8eKLL3L33Xfz6quvMn369G7r+MEPfsDFF19MdXU1jz32GM8++yyXXnppNtl78MEHOf7446mqquL111/PPj7qV7/6FXPnzuXee+/l5ZdfZsyYMXv0nX28XpdffjlXXnklzz//PBMmTOAb3/gGP/rRj/je977HrbfeytNPP01BQQEzZ86krq4u53UIIUTOtBBCiD7l0Ucf1YB+4403tG3bOhKJ6BdeeEGXl5frcDisGxoa9Ouvv64B/fOf/7zbZ2tra3UoFNK33nprdtq0adM0oP/1r3/ttK5p06bpadOmZV8//PDDGtB//etfu813zz33aEDPmTNHa631yy+/rAH9y1/+stt8P/nJTzSg77jjjp3qU1NTo7XWOhKJ6MLCQn3CCSdoz/Ny+m6SyaSeOXOmBjSgTdPUhx9+uL799tt1Y2PjTnUD9PPPP99t+lVXXaUNw9CbN2/WWmv95z//WQP66aef7jbfkiVLNKAffPBBrbXWmzZt0qZp6osvvniXZTzrrLP0kCFDdppeU1OjAT1ixAidTqe7vffx76jLa6+9pgH92muv7VSvpUuXZqc1Nzdr0zR1KBTS27Zty05fsWKFBvSvfvWrXZZZCCF6wj6dsbBtm9raWtatW0dLS8u+LEoIIcTHHHvssfh8PsLhMGeffTZVVVW8/PLLVFZW8sILL6CU4mtf+xqO42QfVVVVTJo0qdulMwAlJSWcfPLJu13n3Llzyc/P50tf+lK36ZdddhkA//rXvwB47bXXAHbq63HRRRftdh2LFy+mo6ODa6+9ttulS3siEAjw7LPPsmbNGu677z4uvPBCduzYwU9+8hPGjh3LunXrus0fDoc599xzdyqj53ksWLAAgBdeeIHi4mLOOeecbt/lYYcdRlVVVfa7fPXVV3Fdl+uuuy6nMn/cueeei8/n26dl9O/fnyOPPDL7urS0lIqKCg477DCqq6uz08eOHQt8ePmcEEJ8lnLuvB2NRnniiSf485//zFtvvdXtmtuBAwcyY8YMvvnNb3LUUUf1aEGFEOLz5o9//CNjx47FsiwqKyu7jaq0fft2tNZUVlZ+4meHDx/e7fWejsjU3NxMVVXVTjv8FRUVWJZFc3Nzdj7LsujXr1+3+aqqqna7jq5+CwMHDtyjMn2SsWPHZneatdbcf//93Hzzzfz3f/83f/3rX7PzfdL301XGrrps376dtrY2/H7/J66rqampx8oNe74tdqW0tHSnaX6/f6fpXXVKJpP7vE4hhNidnBKL++67j5/85CcMHTqUc889l//3//4fAwYMIBQK0dLSwurVq1m4cCGnnXYaxx57LL/+9a8ZNWrUZ1V2IYQ4qI0dOzY7KtTHlZWVoZRi4cKFnzii0Men7emZgX79+vHmm2+ite72mcbGRhzHoaysLDuf4zg0Nzd3Sy4aGhp2u46uPiK760+xp5RSfOc73+FHP/oRq1ev7vbex/uafLSMXeUuKyujX79+n9rJuWv0qY+We9CgQftU3o8LBoMAO3WQ70pqhBDiQJDTpVCLFy/mtddeY+nSpfzgBz/gjDPOYMKECYwcOZKjjz6ab3zjGzz66KM0NDRw7rnnMn/+/M+q3EII8bl29tlno7Vm27ZtTJ48eafHhAkT9mq5p5xyCtFolOeee67b9D/+8Y/Z9yEz/C3AE0880W2+J598crfrmDJlCkVFRTz88MM5Dw9bX1//idPr6uro6OjodhkQQCQS4e9///tOZTQMg6lTpwKZ77K5uRnXdT/xuxw9ejQAM2bMwDRNHnrooV2WMRAI7LZT+ccNHToUgJUrV3ab/vGyCyFEX5bTGYu//e1vezRfMBj81BFHhBBC7Lvjjz+eb37zm1x++eUsXbqUqVOnkp+fT319PYsWLWLChAlcc801OS/361//Or/5zW+49NJL+eCDD5gwYQKLFi1i1qxZfOELX+DUU08FMjvZU6dO5dZbbyUWizF58mT+/e9/8/jjj+92HQUFBfz85z/nyiuv5NRTT+Wqq66isrKSjRs38s477/DAAw986me/+c1v0tbWxgUXXMD48eMxTZP33nuP++67D8MwuO2227rN369fP6655hq2bNnCIYccwksvvcQjjzzCNddcw+DBgwG48MILeeKJJ/jCF77AjTfeyNFHH43P52Pr1q289tprnHfeeXzxi19k6NChfP/73+fHP/4xiUSCr371qxQVFbFmzRqampr44Q9/CMCECRN45plneOihhzjyyCMxDONTzzx1Oeqooxg9ejS33HILjuNQUlLCs88+y6JFi3b7fQohRF+x1zfIO/nkk5k2bRp33HFHt+mtra1ccMEFzJ07d58LJ4QQ4tP99re/5dhjj+W3v/0tDz74IJ7nUV1dzfHHH8/RRx+9V8sMBoO89tpr3H777fzsZz9jx44dDBgwgFtuuaVbe28YBn//+9+5+eab+elPf0o6neb444/npZde2qPhU6+44gqqq6u55557uPLKK9FaM3ToUC699NJdfu6GG27gL3/5C4888gjbtm0jFotRXl7Occcdxx//+MfsvT66VFVV8Zvf/IZbbrmFVatWUVpayve///1sEgBgmiZ///vf+eUvf8njjz/O7NmzsSyLgQMHMm3atG5nf370ox8xatQofv3rX3PxxRdjWRajRo3i29/+dnaeG2+8kXfffZfvf//7tLe3o7Xe7ZkZ0zT5xz/+wfXXX8+3vvUtAoEAF154IQ888ABnnXXWbr9PIYToC5TO9Tx0J8Mw6NevH8cffzxPPPEE+fn5QOZ61urq6p1uPiSEEELsT9OnT6epqWmnfhdCCCE+G/s03Ow///lPGhoaOPbYY3e6W6gQQgghhBDi82OfEov+/fszf/58Jk6cyFFHHbXTuOlCCCGEEEKIz4e97mPRNVxeIBDgiSee4K677uKMM87YqeOcEEII0RvkYJcQQuxf+9THoqGhgYqKiuy0p59+mksvvZREIiF9LIQQQgghhPgc2eszFjU1NdmbBXW54IILGDNmDEuXLt3nggkhhBBCCCEOHHt9xkIIIYQQQgghuuR8xqKjo2OP5issLMy5MAcLz/Ooq6sjHA5n+6IIIYQQQghxoNFaE4lEqK6uxjB2Pe5TzmcsDMPY5c6y1hql1Oe6j8XWrVsZNGhQbxdDCCGEEEKIHlFbW8vAgQN3OU/OZyxee+217HOtNV/4whf4/e9/z4ABA3Iv4UEqHA4DmQ3weT5zIz6Z4zi8+eabHHPMMVjWXndzEp8TEi8iFxIvIhcSL2JPdHR0MGjQoOz+7a7scx+LcDjMO++8w/Dhw/dlMQeVjo4OioqKaG9vl8RCCCHE50ba0fgtuQRYiINJLvu1+3SDvJ5y5513opTq9qiqqsq+r7XmzjvvpLq6mlAoxPTp03n33Xe7LSOVSnHDDTdQVlZGfn4+5557Llu3bu02T2trK5dccglFRUUUFRVxySWX0NbW1m2eLVu2cM4555Cfn09ZWRnf/va3SafTn1ndxeeP53ls3rwZz/N6uyjiACDxInLRm/Hiac2zayK0JT6/l0IfaKR9ET2tTyQWAIceeij19fXZx6pVq7Lv/fSnP+UXv/gFDzzwAEuWLKGqqorTTjuNSCSSneemm27i2Wef5amnnmLRokVEo1HOPvvsbn09LrroIlasWMErr7zCK6+8wooVK7jkkkuy77uuy1lnnUUsFmPRokU89dRTPP300/znf/7n/vkSxOeC53ls27ZNGnKxRyReRC56M15aEx6VBSZvbU3iyYCTBwRpX0RP65FLoVauXMmwYcP2ehl33nknzz33HCtWrNjpPa011dXV3HTTTdm7eqdSKSorK7nnnnu4+uqraW9vp7y8nMcff5yvfOUrANTV1TFo0CBeeuklTj/9dNauXcu4ceN44403OOaYYwB44403OO6443jvvfcYPXo0L7/8MmeffTa1tbVUV1cD8NRTT3HZZZfR2Ni4x5c1yaVQQgghPm9Wb0/xVrSBw/LL8GMxvirQ20USQvSAXPZrc+6p88UvfrHbqFDJZJJvfetb5Ofnd5vvmWeeyWm5GzZsoLq6mkAgwDHHHMOsWbMYPnw4NTU1NDQ0MGPGjOy8gUCAadOmsXjxYq6++mrefvttbNvuNk91dTXjx49n8eLFnH766bz++usUFRVlkwqAY489lqKiIhYvXszo0aN5/fXXGT9+fDapADj99NNJpVK8/fbbnHTSSTnVSYhP4rouNTU1DBs2DNM0e7s4oo+TeBG56M142dyeZHPUT3GojbxoEYdW+mXI9T5O2hfR03JOLIqLi7u9/trXvrbPhTjmmGP44x//yCGHHML27du56667mDJlCu+++y4NDQ0AVFZWdvtMZWUlmzdvBqChoQG/309JSclO83R9vqGhgYqKip3WXVFR0W2ej6+npKQEv9+fneeTpFIpUqlU9nXXvT66LsPq+muaZrfnjuOglMo+NwwDwzA+9blt25immX1uWRZKqexzyIzw8NHnPp8PrXX2ued5uK6bfe55HpZlfepz13XRWmeff1I9pE651cnzPJqbmxkyZEj2swd6nQ7G7dRX6uS6Lq2trQwcOBCl1EFRp4NxO/WVOrmuS3NzM0OHDt2vdUqn09QlbPxRH9uaNf2sOCknDxNHtlMfrhNk+p8OGDCAYDB4UNTpYNxOH69TUqe5uO1eIlYrZf58+ukQZUaAklSafhj4vUIKvDilehumdin3H8/AvJl7XadcbiGRcx+LqqoqvvWtb/Hoo4/u8pGLM888kwsuuIAJEyZw6qmn8uKLLwLwhz/8ITvPx496dN0vY1c+Ps8nzb8383zc7Nmzsx3Ci4qKsvewWL16NQBr165l7dq1AKxcuZINGzYAsHz5cmpqagB46623qK2tBWDx4sXU19cDsGDBApqamgCYO3dutrP5nDlzsn1MXnrpJZLJJI7j8NJLL+E4DslkkpdeegmASCTCnDlzAGhra2Pu3LkANDU1sWDBAgDq6+tZvHgxkBkm96233gKgpqaG5cuXA5mzSitXrpQ67WOdgGyierDU6WDcTn2lTrW1tRx11FEsW7bsoKnTwbid+kqdduzYQSqVwrKs/VqnV177NzviKYrsJLFNLbwfTdOWdGU79fE6JRIJjjrqKObMmXPQ1Olg3E4frVNDrIULttzLVreDSNsQNtUNxU0VsW1hjB+O+xn/75gH2Lo2SYeuRHdUUFVnY33wGmuWPojWeq/qtG7dOvZUzn0sLr/8cl588UVM0+Scc85h5syZnHLKKQQCPXst5WmnncbIkSP57ne/y4gRI1i2bBmHH3549v3zzjuP4uJi/vCHPzB37lxOOeUUWlpaup21mDRpEjNnzuSHP/wh//u//8vNN9+80yhQxcXF3HfffVx++eX84Ac/4Pnnn+edd97Jvt/a2kppaSlz58791EuhPumMxaBBg7Llkaxc6vTROrmuy7p16xg9enR2mQd6nQ7G7dRX6uR5Hps2bWLYsGH4fL6Dok4H43bqK3WybZsNGzYwevRolFL7rU7v1sd5al0rY4paSUcL2Wj4+fKIMOP6+WU79eE6KaXYuHEjQ4cOze7HHeh1Ohi3k2VZuNrlTx+8yF/iy1lvNFEcGgduEJbuYPsvn2DbGx8OegRw7ClTmHXtEA4ZVgkk8SXaCeeNx1d1MpRNzqlOHR0dlJaW7lEfi73qvK21ZtGiRfzjH//g73//O9u2beO0007j3HPP5eyzz6asrCzXRXaTSqUYMWIE3/zmN/nv//5vqqur+c53vsOtt94KQDqdpqKiYqfO23/605/48pe/DGSyzIEDB+7UefvNN9/k6KOPBuDNN9/k2GOP3anz9tatW+nfvz8Af/nLX7j00kul87boMa7rsnLlSiZOnIhpyjWtYtckXkQueiteXtnYzqptbRxSapG0E6xvDjFxaD7njSreb2UQuZP2pe/7wdv/zdMfPE3U148droMvNB435eOQcZNpeuxf1M7+M+VjDmHoEZM4ecYp6FaP1fPms2rJQrY3NvKL267nomNiBO0VaBRGageWGwdfAcbkuzCGf2W3Zchlv3afR4WCzGmSf/zjHzz//PMsXbqUY445hnPPPZevfvWre3RH7ltuuYVzzjmHwYMH09jYyF133cX8+fNZtWoVQ4YM4Z577mH27Nk8+uijjBo1ilmzZjFv3jzWrVuXvQvgNddcwwsvvMBjjz1GaWkpt9xyC83Nzbz99tvZf5YzzzyTuro6fvvb3wLwzW9+kyFDhvCPf/wDyPyDHXbYYVRWVvKzn/2MlpYWLrvsMmbOnMmvf/3rPf4+JLEQQgjxefL7lU140TZmHFKN34JX3ttKwl/CdUeU93bRhDig+f/Xh1YmvuLDQFdgmAMARUmNzdbv/J7RF36Tad/+Dv3LExzSWIDZks9o/xbsdII7fzGbOQvm8s9ZEzh6lB9lx7Ai69AKFIAysC5P7boA9MIN8saOHcutt97Kv//9b7Zu3cqll17KwoUL+fOf/7xHn9+6dStf/epXGT16NOeffz5+v5833niDIUOGAHDrrbdy0003ce211zJ58mS2bdvGnDlzut1a/L777mPmzJl8+ctf5vjjjycvL49//OMf3TLwJ554ggkTJjBjxgxmzJjBxIkTefzxx7Pvm6bJiy++SDAY5Pjjj+fLX/4yM2fO5N577+2Jr0kIIJPArl69OqfOUOLzS+JF5KI34sX1NI0RB7/lMLg0SHVxHoaCpqiz38og9o60LwcG7SnSdR5eNB+tFdpxqbvraQqnHsWEy39AJJGPjgZpXzeIUIvCUJqgz88jX72ICQP6c+vv38dsAd/WPFT74ahkZdeCe7ysOY8KtTvl5eVcccUVXHHFFXv8maeeemqX7yuluPPOO7nzzjs/dZ5gMMivf/3rXZ5ZKC0t5U9/+tMu1zV48GBeeOGFXc4jhBBCiIxo2sNJOxh+C8PIHK/0Gz6U6+J6GtOQIWeF2Ftuk4dnGyirFdcKYxWBO6cGr7mVsgm3gAaagwTWleOzNOFUJl/Ij7YTTqf53gnH8eUn/8b8pe2cMqoIAJUcAJF2tD/Z4+XN+YzFsmXL+N73vkdLSwsA//Vf/9XjhRLiYGaaJuPHj5frWcUekXgRueiNeGlJOBSaNhXhQrouri4JhQgZDpGU3NG5L5P2pe/TUQ3JOLq1CbemjsRbO0g+8k8AbF8VO95NEFpSiBlVWK6H3uKjY2l/7KYAaqvmkMAEAL78h43Q5kGrB7aGlB+jpefPVOWcWFx11VUUFBRw/vnndxueSwixZ1zXZfny5XLqWewRiReRi96Il7pomny/zZH9i5n7NETbYURZPiHToTGW3m/lELmT9qXv01pDqhQVHQHRBrzWTaA1GBahWgu92M/mTS38880W6hocdKOLu8zEmVPEjnXD6dc2DIBI0oUWDa0atnmodJLP4lxizpdC+f1+br/9dk4//XSuvPJKeqDvtxCfO6FQqLeLIA4gEi8iF/s7Xja3JTEMDVE/Zf3hnX/DkSfnEbRcaiJpDimT+O3LpH3p45Kg2gyUakGrMgI7RpNiGXgOoUgC03IIxlMMSAbxb4uxDggYmnB+jOq895lT/28ACv0muKCVi0q1oB0TSoweTy5yPmPR1WF68uTJnHnmmbz99ts9XCQhDm6maTJmzBg59Sz2iMSLyEVvxEtjh4unFds+0Hww/m36HxZn7VsmpoKaNnu/lUPkTtqXvs+qAyPehBGrIdBQjN8ZRv6kywCI1ryGV9dAoqWRkmSUUOfB/pRrohPNtG7zmLt5G0HD5E+HDye1RZGudfEijej2KF5dj4zh1E3OS/T5fNk7AF5xxRX89a9/7fFCCXEwcxyHJUuW4DgyYorYPYkXkYveiBfHcTDw0ei0U2Tms6F0HTE7jcKgKSKJRV8m7Uvfp5T68KyCykc5SYrMQsIDTmHzpl+TblrOiDaHfl0XIWlNVXQdhdFGlrV/wGONC7l+yFCml2Y6buP5cRKDM8/TPb/dc04sXnnlFRKJRPb1zJkze7I8Qhz0lFKUlJSglIyUInZP4kXkYn/Hi9YaE4eQ8hOv2sGKf1VQUX8I20asxdJ+lCuJRV8m7UvfZ6jOXXUNSm+joG4Jyn6L0nAlPnwsq/s+tW0v0NHyfmZ7dmyiIraWvzUv4vL3f8WkvAF8b2TxRy55UmjHz2fVkyHnPhbSp0KIfWOaJiNHjuztYogDhMSLyMX+jpeUq/GbLvnxItqqtrNt0nqWbj+MgjKLkLYIGDZpR+O3ZMe1L5L2pe8LB8O0xdsAKNzagfI8LNdPRUsepSVfoK79LV7puJeFkUeobhxJvhdjk72ZDp3gi8VHM6vagKSDtj7cf3dTbTgpyDvhuB4v715dXCWZrRB7z3EcFi9eLKeexR6ReBG52N/x0pZ08VsOlgM7Imlalg5km/U2WyMOPgV5lkN7SmK3r5L2pe/73rRbyduuyN8Glp2HAgo7ilBa4TNCHBW+gP8I3sxEhuNLNuFzkpxsjOF3xV/m9qBFgWETa/FIRVvw7Dac5LbMIwFc1/PdGfbqBnmHHHLIbpOLrvtcCCG6MwyDAQMGZG8kJcSuSLyIXOzveGmIplEKEv1a2dLsMbTNIbV2LFtGbKZaFeA3XbbF0pTn+/ZLeURupH3p+waUDcRMAJ7C8OIoL59g0oHOG092GBHG6FLGMZpS06HMzFzaNkC9h2OncByXdGojyoyRlw/Z3XfDxMgv6vHy7lVi8cMf/pCiop4vjBCfB4ZhMGTIkN4uhjhASLyIXOzveHm/NQkaWkJtROr8HLL6TfqVFPNyYCLbRzVTnCri/dYUh1Xk77cyiT0n7Uvfd/6pF/LMP//ColdfIhirwbOGobRCedvRRiVJI0XCe498/T6uLkGpUgBM0theG/VNTRQEYxCBQBAsC0ARuvE+VF5Bj5d3rxKLCy+8kIqKip4uixCfC12nnqdMmYJl7dW/oPgckXgRudjf8bK91cZQ0OLGsdpD9PdtZcKpR/NWTYRmz6ZIF7OtTW6S11dJ+9L3+SwfT/3sH/zohzfw1z/+Fi+9gaBTStBZRtg5FtNzMJw6othor4MqHQZVRjRdC9QBEElAVTE0bwfLBwP//BrByVM/k/LmfO5L+lcIsW8Mw2DEiBFy6lnsEYkXkYv9HS8p2yaNx/aopuS99eQVhlj99JNUNmylNW7hoUhKH4s+S9qXA4NSiosuugbLsjBNRdBpzozy5G2n2HkPjzpS7KCFDaTd98B9i66kAkADkZQCw8Q85DAChx//mZU1p0h65513ZFQoIfaRXNMqciHxInKxv+PFVA6u69HeFqJi4+tMmHk+Z9xxB/43XiYSCeAoG4W7X8oicifty4Fj1CGH8tfn3+TrV9yE5fcDkLBq8BPNJBmdx/3f99aT1Du6f9gwCIwaS79rbmXwk/9CfYY3RMwpko444ggaGhqoqKhg+PDhNDc3f1blEuKg5TgOc+fOlVE4xB6ReBG52J/x4nmZoWZtfxI34qPcF2P5rHupe+Ntxh05FjdhkiaNT0li0VdJ+3JgGT12Irfefi83/uphlDLwVOZsRJYChUvMq6PF+fAKI39ZOYc+9SLl3/0JZlHJZ1rGnC6oKy4upqamhoqKCj744AM8z/usyiXEQcswDMaPHy9HiMQekXgRudif8RJNe1imS8yKEWx1KQmXkMcQ3v/bHKwyg1A0RrvPo9zNx3E1limXUvc10r4cmGZ87TJmfO2y3i7GJ8opsbjggguYOnUq1dXVKKWYPHky5qecTtm0aVOPFFCIg41hGDL4gdhjEi8iF/szXrbHMp2y221FePMqdGMHhr2J6hNO5YMlz1NUsJqWQw6lv+HSlrQpy/fvl3KJPSfti+hpOSUWv/vd7zj//PPZuHEj3/72t7nqqqsIh8OfVdmEOCjZts3cuXM5+eST8flkbHexaxIvIhf7M1427EjgGg7RhI+h72/EjSZ5YWgdZ1SOxnTzKF/+BhunHAYFLh90pCWx6IOkfRE9Leexxc444wwA3n77bW688UZJLITIkWmaHHXUUZ96tk+Ij5J4EbnYn/FS15YirlySUT+VrdvZUG2w3ryGpmVrGT+wjfKldayKB0iHbTa2JJjcv+fHzBf7RtoX0dP2+qK6Rx99VJIKIfaCYRiUlpbKNa1ij0i8iFzsz3hJ2GmS2sFLaQLtrSzXg5k0JEShOZDXE8eA6aBSLhGVpqHD/szLI3In7YvoaTlF0pYtW3Ja+LZt23KaX4jPA9u2efHFF7Ft+aEVuyfxInKxP+PFwCXhi+Nrb6ep0iARmsDoQBUXHHsKQZ9i88BKgu3NdHgOji2jDvVF0r6InpZTYnHUUUdx1VVX8dZbb33qPO3t7TzyyCOMHz+eZ555Zp8LKMTBxrIsTjzxRLnLqdgjEi8iF/szXnymS9TVhGvWsix/IEMKiwgNW0e9tYaBVgWbfIMpfH8NUVdjyr0s+iRpX0RPyymS1q5dy6xZszjjjDPw+XxMnjyZ6upqgsEgra2trFmzhnfffZfJkyfzs5/9jDPPPPOzKrcQByylFIWFhb1dDHGAkHgRudhf8ZKyPZThEkublK1ZypbiY/jCpACLZ71O2SFlTDzxUNa9MYSxK//NB6cdh98niUVfJO2L6Gk5nbEoLS3l3nvvpa6ujoceeohDDjmEpqYmNmzYAMDFF1/M22+/zb///W9JKoT4FLZt8/zzz8upZ7FHJF5ELvZXvDTGUriGTSLmJ5lqJJwfomFlA6eOa+O4wnXEtrbhs3xor5Fk0odlpXE8vfsFi/1K2hfR0/bq3FcwGOT888/n/PPP7+nyCHHQsyyLGTNmyKlnsUckXkQu9le8rG9MEvdcnKRiR34VIwf42PHEQq599U78pf1Ye9WPGVIxjJrSkXhpjW2kaYynqS4IfKblErmR9kX0NBkGQIheII24yIXEi8jF/oiXLa0JIlYSIxonHhpFOBbgxNPKWHH/Ihr+9R5TLziK8YNKaPGNxIin6CDN6sb4Z14ukTtpX0RPksRCiP3McRxeeuklHEdGSRG7J/EicrG/4iVp20RwCNW+jwqWE122gYqhU5hbEOL/W7Od+pfbcJsSKCtMsGkz7Z7HxqbkZ1omkTtpX0RPkzRViP3Msiy+8IUvyFEisUckXkQu9le8KBxiaQNv6xqKw4dSENnCkn+GaNq2iVB1EesqBhKo2UFpSSleXQ1RdygJR67j72ukfRE9Tc5YCNEL5OiQyIXEi8jF/ogXw7JJJC0ScU15UDGgX38irTG+eOGXOfGKL7H1vY3kdZgM6Rck1pwgnjSxlMRxXyTti+hJe5VY2LbNSSedxPr163u6PEIc9BzHYc6cOdKYiz0i8SJysT/iRWtNWqWx4xZpVY7/gxStDRZHnnw0285poCHaxIRLp7BjaxsVOo+UXUw6YeG35IxFXyPti+hpe3Xuy+fzsXr1apRSPV0eIQ56Pp+P8847r7eLIQ4QEi8iF/sjXhoiaWLY6FgSM9AP/9LVjDn6TJZ+4T3UU8sIDyxgiPkF3p9USmhzK6YvjJdysM0EsbRDvl8uu+krpH0RPW2vL4X6+te/zv/8z//0ZFmE+FzQWtPR0YHWMqa72D2JF5GL/REvK7ZEaDXS0FpPYZ5ieHgE647YxsBVtVz+H9/kzLGnUVP3L0ZMGo67ahNFIQ8VaaKFNGubZWSovkTaF9HT9jqxSKfTPPTQQxx55JFcffXV3Hzzzd0eQohP5jgOCxculFPPYo9IvIhc7I942doeJ+pq3OYWwrZNvzEj8JfXcNwRZ/PUi210hA7ntKnHku9Ca1WQ/oUKZ3s9La7LqnpJLPoSaV9ET1N6L9PUk0466dMXqhRz587d60Id6Do6OigqKqK9vZ3CwsLeLo4QQgjRYx7590besJvo+MdqjlnnMuSYfMKH7WDhS4UUplqxEzaFys/I46AuWUW0yWNBqp3i845hkq+SG08Y3NtVEELkIJf92r2+0PG1117b248K8bnmeR5tbW0UFxdjGDIwm9g1iReRi886XrTWeGaaZJuFkTQ43F/J9lHvsvi1YkpSHUTOvYDKogBbX36RgVtaKasMktpSjyr0kUqY4Ev3eJnE3pP2RfS0fYqihQsX8rWvfY0pU6awbds2AB5//HEWLVrUI4UT4mDkui5LlizBdd3eLoo4AEi8iFx81vGytS1FB0nseJICy8Yd4hBNdFC0pZXEySdy5YbHOK9hDoMnjqZmU5o8mnH6KwqC4KZSOL7oZ1IusXekfRE9ba8Ti6effprTTz+dUCjEsmXLSKVSAEQiEWbNmtVjBRTiYOPz+Tj99NPx+Xy9XRRxAJB4Ebn4rONl6eY2mq04uq2D/mloH/cBtfMLaJ00kjNf/wsrPjict5eWcei8edSNKCWysp7+/csZENbo9kaadRrP8z6TsoncSfsietpeJxZ33XUXDz/8MI888ki3gJwyZQrLli3rkcIJcTDyPI/Gxkb5cRV7ROJF5OKzjpfGSJzWlIne1sFx7kAarDoKooozt2wgylg2tW3F72wnZY7mpPdrWef56Jdy6Z8KYTckaLM1a5ukA3dfIe2L6Gl7nVisW7eOqVOn7jS9sLCQtra2fSmTEAc1z/NYvXq1NORij0i8iFx0xUs6kqT5zS00v7mF9tUNuKmeGfXHNZNE2y3MHQmM4duofz3IkKIgK9tDPLZ9G0XHxHkr0MEz29+nQw0l4HTgbK4jWKAx6xNEkwbz3m/vkbKIfSfti+hpe915u3///mzcuJGhQ4d2m75o0SKGDx++r+US4qBlWRYnn3xybxdDHCAkXkQuLMtiyrijiCxfB9H1YIDb4aO1aTilUyZg+M29XrbnebSZMZxonFIdZ1NlLcPeyCcStFkfivMf486kNl3EkeNMCo5cxjNPrefw5nJq3FaGDxtMlX87O1IebijWgzUW+0LaF9HT9jqxuPrqq7nxxhv53//9X5RS1NXV8frrr3PLLbfwgx/8oCfLKMRBxfM86uvr6d+/v4zCIXZL4kXkItkSo+nNBbQ1dvB89H3aTZuByX6cU5VCex79TpyE4du75OKd2g4atY2zvZ3pwRDvvw1j8iye2RFn0qHTuCe9kHDKwI6nSelyzjtqKKuW1FDd4BLc3kr/Ah8NsQTtlQYpxyVg7X2SI3qGtC+ip+11YnHrrbfS3t7OSSedRDKZZOrUqQQCAW655Rauv/76niyjEHvNS3skVreTXNcBrodKtqPbmnCatuNzOzCCDnnDi7BKw6hJh8GQoSilPtsyeR7vv/8+lZWVn2lDbu+I4cYdfOUhjJDvM6+X+Gzsr3gRBz435bB94UJWb91Kk/89jk7ESCuPgK+RObGtnPi+h+k3KD3hsL1a/rLNzXQ4HsaWCNHhG5jwssWf2pKUDx/JgmQLx743grLBDoVNpTQ027xS3czRg0tJue1sq93K+KMOZenGHdT2D/HKhhbOG1ves1+AyJm0L6Kn7fUN8rrE43HWrFmD53mMGzeOgoKCnirbAUtukLd/acdGt26HbbWwoxGiUXQ8idOYwo15mOWFxNqTdKyuI74jTjppYHtFpI0iTF8xlutDe00MHNFE2bgw5hkzMMaN6+1q5UxrTWRRLfW/XUpicxNuKgWeA24CSyUJDCmk/Bun0O+cw3u7qEL0mKTrMLehgeaUTWUwyJSyMgr8fXeEG8f1eP39Nmp2tKOVi9ImAZ+P08aXU5oX2Ovlaq3Z/MoC1tStJNi8nqZkLY5qJ+E4FFopQtZodLiC/tZ4Rp8yg/CoATktvyWS4rFVa3lje4JhL8/l8EKbf75po4oH0VA0iMGD32HG+DxGeWlqUorF2zpIr5nI2n4mQ1rWMKzeZsrEofzeiBM/9RiOKgrznyeO3uv6CiH2n1z2a/c5sThYPfjgg/zsZz+jvr6eQw89lPvvv58TTzxxjz67PxMLnYxDIPS5OhqttYZoG7pmLby3GlraIZAP/UrRfo/kNpv0DkWgooP2tdto2RynsW0g8UglbioP5aZRThTtObhKYWCQ5w8TyitB6yRDR22kYqIf6ysXYAwa2OPl9zyP2tpaBg0a1CNHiOy2JFtmzaPt1TXYaQPDa8HnfYBFIwqHRLAIz6sGpwrldhBwVxGaXM7A228kNOHwz1XsHIh6Ol4OBhHH5uH31/HkxvW0dCSxEw64oAEsGFhaxKwjj+K0gdW9XdRu5r/fysaGJlpjBi2uDUYajUEQP/3zwTECfHFSOf3z83Je9roFr7OpdgmF27bQOnQk2wtG0tAQR3uKYCCAwRaG1b5Iv7wRFBQeyvgvfQV/4Z6v5w/zPmBVQQ3r33K5MPoW6//ezkYG0TxkCGcduYz/SOazZYdiYywPszBGaThJndfAorXjqSvsz8AdbzMVi+TRg3l5cDXDhhfy0+OPzbmeomdJ+yL2xH5JLC6++GKmTZvG9OnTOeSQQ/aqoH3VX/7yFy655BIefPBBjj/+eH7729/y+9//njVr1jB48ODdfv6zTix0Ikbq/7sP580nMVUToECBkd8PY9wMzK/cjeEP9vh69zftOpBK4KViNLc20tDcgN5RT1FjM0UJh2BRMf7+JSjVSmpbCy3teTQnHdr9O4h25OHVjyQvXophe6S9NC2GpsUXoMGXR5MVoAmTDu2RSKXwpV36JW2CnoHPKqTMtKguaqGiWNH/iIFUjimnbHARpWFjn3fEHcfhrbfe4uijj8ay9u5qRK01LS+vpvbH/0eqDQzdgt9dTnPAZnN5NS2GTVKnSJcFcCqD6JCHtmOEGpMMWOoQ7ohR4kQoLE5RNuMIKi69lvzJx33qD4tr29jRKHY0SrKxkVRrK1YohFlQQKC4mEBxMf7CQklSPgM9ES8HA601b7Y0cde7y1m5vYF4S4pASx556RBBM4RSJtpzSSZjRNIx0hUuAwcW8cLZZzA4nN+rZX+vJcIr7+4gTgcNVpxEyiDZbuHZHspUmAEIFKfJC3j0C0A6Vczo8jKmlhUTtkws0yDteaS1R9rzcLRH0LAIGgZBw2DlyreIbl9L9cZGVvWr5qXlO0jsSFBVEMTIV8Q9m/YOi+HjBnOiuYJC16O4cBxjL/wqVtC/2/K7rst9b73NkgYH30uvM762hWWNhQSHj+ErJW2Y2w2W5oVIFNkYeWkKo4Uo208bEUr7reftD0qI5VcwqHk1F1eP4KFyF2/6OP5z4jgOqyraD1tAfBppX8Se2C+JxdVXX838+fNZv349VVVVTJs2LZtojBkzZq8K3lccc8wxHHHEETz00EPZaWPHjmXmzJnMnj17t5/v6OigpKSI1taeTyxSy+cTufty8gZEMAZWoAtKUJhoz8ONtGJ2NKBiNuaxN2B+6Ud9/giEdhx0RzvEWmB7DTraAp5LXTrFkvY46yMaK6oYGE1SnojSjsF6Xz61VoiAMilRJtVYFDsK0/GRtH0kbZO47dLh2qRclw7HJJWyIRnFSMUgncaxNXmGRcAfIhAsRPvz6Qj0o9nMR9sGRY4i6g8w1N/BYNVMB3nUqiJa/EG8PJOCYj9V/fMZNTiP4dUBKov9FOYbFAQVpvnZ7VwntzRR+72naFu6nZRRSrNvO435dcQq4qTG5mMcWoE7oAhfXoigNghojakMUKDR2Aa0BiBuO6hNCYILtlA6dwXFW7dh+lKQb4I/gKcs0q5LxE4TTaWJOjY2GkdnhiQ0lEIpUDozZrVCYaCwlIEv4McfCOIPhwmW9CM8YCDlY8YyZNo0Bh59DIFQ6DP7fsTBw/E0dckk83c08Hz9RpY2bMNtDJEfLSLfK8TSfpxkDBI78CcbMXQShQmBAZh5g/B8Fq2Jerb7tjNycBnzLvoCgf10EzDP89iRSjNn83ZW1daSDEJL3CLV4eHVtaBq2zFjrZhuDK0NXKsQL1yCqgyhKkswi4MEw2n8VgQvncSzHZThYZgaw9BgKQzLRPktfAGLIC5mIkVryiWVVhhmZ7uvwPRsjHgM1kdwG1K0Rfx85RCDwaoJr2Aoky+54sP5P0E8meavr7/PW76tbF0Q59D5K2ipDzOsegwDB65iadCkKZhE2e2UpFP4kx5Bv8KxAiSTQ6hqr6YhEGdbMo5HmFGxNUw6dBjPnHAoE6sV35k0iYLggX8grDdoT2cergedfz3HQ6c9PNtFp108x0WnvcxvbdoF20XbnX8dD217aFeD56I1oAClwFSZOPMbqICBCvkx8wKYpQX4CwKYIR9qF3EjDi779VKohoYG5s2bx7x587KJRkVFBfX19fuy2F6TTqfJy8vjb3/7G1/84hez02+88UZWrFjB/Pnzd7uMjo4Ojr9jHIvufJeiou5HY7x0ms0vvszmN/+F11yPYbj4iqBydBUDjz8H36CjMPPLdlqm57q03nk5zvrnMYaabNteQuuGMG12BSm3hJRRQNhKETZi9A+vpnJYLb6EiZ70LcIX/SdW5b5dEqC1xsXG1TYaMJWFiYWhchvVw0vGYeUbsGoZuqEO7do4KGzHotULEvOCmNqP1hYdpkW76afRKqTeKmGbKiaiCoiqII5n4enM0RXtaXBsvFQCnY6iU+146TZwE2jl4SnwlIGLBq3xXA+0h/Ic0B6gUVpnLqNQJlqZKNMHRhBl5uGZYSzXo7+OMkRHGOBFsewU290w9aqIRh2iSfmIKB+u6UcphaEUpmliGRY+w4epfFgq830ZnsLyNBZgoDEByzDxKYuQ8pOn/ASVQUh7BJIJzGQcXyJOXqAFSj7AqWwgPjhFclA+XmEQrQwsV2OlPHTMI92miTR5RNrS2O1J3NYkOpXG8nmEQh7FIY9gCTC0kET/fJJhPynt4rbG0O83oOpbMJva8bkuBQGD/JIAvsIQRqEfVRDCDvlxAgG0qdCGglQKFU/gtrTjNkUw2jowYgkC0Qi+ljZ0W5JEm008BkkbXA3KBF8ACgoVoSILK+xD5flwLB+OsnBt8JKgUgonpYimLWK2Qdwz0NrEsiwsnw9fSTHB0mKsghBGfoCoF6fDi6NNhUdn06ZAaQVa4/cFyA/lM2zIGA4feyyFeYUkYlE8L4VlJrBUHL+K48VbSDVtJR1rRqXbsNwEAU9jKQ/T1ai0BwkPN5EmHUtgx5IYjs78eDsOnu3iumlcz4GgRoXB8iv8lkEAEx9+gqF8fIXF+IrLMIsHYBYPxCgajFU+ClU+EsMXAs/BdVJs3byJgdVVmEpDsBiVV5n58e+DXMfBdRyUYWCYJoax81k+V2vijkvUcahpbmPZ6nW8Wx/hg+YE25MujmNiGCF8vgIsXz6mYaGUS8CLUqQbKNI1lPs6CAUUlqHxuy6W7WKmXfxph1DcJhU3WBk8hm0Fh6I9lwJ3K/38dQwr9Th99BCGjpyIr6gCMz8PlMJJJnFSKVKxGPH2dpKxKNGmZto219JSV8e2xu00JCN04JDKC+IW5qGLCtD5Bej8fHR+GO3Pw/OF8IwCXArQ2kLbHrR0UPDBNip1I/2awNpaQiqqcB2N39CELEVBvkNHYQf1pZomlUeLLscrDqMtA2UqtAPa9dAuKA8MpTGVxkyl8VIubY7C9FmZpB9AZy7z1CEFJX7MCh+BMo/8cAcquoOKre1cqG2aK/pz2MTplI4Z2X0buS5vLqlnlbuJ98w23t9QTuiXLzPICxOd2opJA17Ko0AnCSkH07SJmA7thkuHYdJGCC8axt9eSkFiEENSA2gKadrSDv1T60gcWU30hMMZUxTjR1NP2n8Buh9prUknUsQjMdqbI0SBmKsJGiaWZ+I3TJSnUGmF06GJ77BJtNk4CRftOKBdDM/FUDYmLiYpDC8FpPB0BE8n8EiiSKF1GrSDxgbtovAwcAGdea41SoFWuvNAUyaHyFJ8OEUp1Eff7dxN9ABba1Kei601nqdwPbA1pJWHYxnErACp/HyC/SooLu1HYXkJhf1KCeUVEA4WkGcFCVl+dsRamfveGyze8CYNzdvwpRMUuR6ljqIkrQhpiCtFi09T71O0Bv0Mrx7DjSd/nfEVn/0gK6K7/ZpYxGIxFi1alE0uli1bxrhx41i+fPm+LLbX1NXVMWDAAP79738zZcqU7PRZs2bxhz/8gXXr1u30mVQqRSqVyr7u6Ohg6t8vJdE0EF/NBGjxM9B1OdIf57Aqj2hZEe3FHk5xFNOXaZT7xWxUyuODpEtgQ5po6zCaohD3NeOvsvGNGYA7eBhOqB+2FwJDdTYMOrNz7Gq0DTqt0baLTjropI2KJzDbduCLNGDF6zGi21CRWoxEC44NjrJQRUX4yvoRqKoiWF2Ov18hVnkBZn4Q029imAplGhiWQpmqc38m0+wordCdJfFcg1gqn1gySNIOYNs+NJ3XPTselu1haI+0YZA2TVwj8xnPM/Dcjxz50BqlNIZlY5ouyvQwjDSGsjF0FNNtxXDjGG4y02AaJpbfwufzYQb9mMEAVtCH8plgKJShMKzMUTzV+aOrOxslTeaoO2SSNydl4yZT2LEkdixBuiOO3RbDadWkOwKk43kko37sZBDT8GMpCGqPglSUkJemK81yPU3CU8S1SQKDJAYJbaCDFka+HyMcwCgIYuYFMfICWCETM2BhBQwMy8C0QJkKw/BQSmNaHkq7KMdG2w5uWxq32caNuJA2MFyFqcHnN/D5FcpngRXEM314ZgBlmCjDQJmdf1UmIfOlU4QTUQJGCrfIItbPh50PbshDq84tq3XmrIStwFPgWmhPgc58h55SuIaBZ4BnKjyj68eJ7C04tVaZXyUPcMHzVOeRNgdcN5Po4WV+wFQmngwyP25G54+cQoFh0PXjp1TnUTrvw4RRdd7kSZFZnlIa5elMHHR+TmvwtJdJMFGozrN6Wms8z8DRPjQGZud3r7SHcl0M2wHHRWuVSaoshWcaeBigjc4jfR8JqM7/E935wlAOCgfDyPzQ0/nTrzs/r5XKLEdr8NRHvjPd+fDA9Tq/w851GCqTYBjqI+tX6M66ep0xrnXXvoHO/HU7l6tUtwQlc0Lqw/JnkvauddG5Lj5cn9E5o1JgglKd9VEmGgNtmJ2pc2cKrRTaMDrX++GqFQqlXEwzjWmm8VlpfL4YQTNCgA4sN43huSitM//DhoFG4SiFUgpXZ3aftDbwDAPHNMBSKO1hOC52OkgkNoB4ogzPtTDwMI00KA+lMtsZA7TpwzMttGFldlw+LGBms3qZLao8F+V64Lgox0M5GiPtYjkupuMScpMUxiMUeRGMtmba65pJJ5IEfC4hn0uepcmzNIbSpD1IewYp1yDlKOKOge1ZFBTlUV5VQGGhH5/fxPEMXEyU9rATDqo5ihV1qYkUsr5jEnaymrAXxEymIL0dlarDSDeClcQLmbiFRcSqqogPrcAZGsAoswjmpwmaUfxOGhyN52k800AFTLBMHNdHNFaA3tjEscteYXDJdvA5JHWauJEm4kvR4UsR0WBjUaANirRJiacJYxLw/LgYRJSm0TFIREpJR6tIJIuJxxJ4hxQTO30a4cJW/F4C03M745dMnOgP2+qu/2o6/088xYf/Nx/5P1Neph1QWmefm51tg6k9DNfF9DJtjaEdwENrD2V0tj1m5n/YM7vaNwOUgacy69edMZ4Jh0wsK0NlD0ppZeEpE08beJ6Z+X3zMs8z/+td1VGZWFIa1dXWKN0Zjx953TlPZ4Rn/qrOf2iVqYfWOvNddf71PK/zH99DZf7ZcTvblExb0NlGdJWl8/+n++uuRqCrAcn8NTyNSSaptcg8zK4DZZ4Gz8DwOv8XO9s3DxOtFC4mWhmdrbOJqww8ZeDgw1Vmpu1VRtdPC10tqEJjKA9L2x95OJg6jcL+sHwf/ixlq9KZZXc9ofu7H9n9/Vieoj/yTHV7tvMuc7cpXbOojyyys6lFq2x51EdWqj+28g9f7zz9w7J8ZD798c99tDDqI+X7yHLVh/Prri+t+9s71fB/vn7eHiUWe31B3W233cb8+fN55513GD9+PFOnTuV73/seU6dOpbi4eG8X22d8PBvWnT9on2T27Nn88Ic/7Dbt1NsXorTCV62xBoCZp2kogn+Wasywi2sYpJMBXNsCV6HCHlapjd9KY4x38FA4dgDtmdgeWHacgpYW/A3v0P7+B2x5r45YzMX1NFZQUTykgNJDSigZWkhRWQn+igJMlUfUyCeihpNwDyXtWXQFmuFzsCwb07LRaNKOJuEoPFvhpA3cDoVuUqDND3dCvMyOXFfjBnykAVAo5ZHZjU5j6CSGTqNcMD2Ncl2SOHieg/JsDC+N5TmYXYffPECbKG2gANNNYnopfF4cv47j85n4QwGsvBD+cBDlt3AsPynTJWk5RI0kbXlJsDI7z35/AH/AwkBRlF+A1grHcSgsKMJLpsHxKC0sIhlJgAuF4UJi0TiYPsziYlKpZOYyH+3iKBdHQdrzSKUdHJXZgc7syGhcx8ROZXZY3OzeHeR7EMbFwMXq/Gvg4nNcLMfBSrVhJlOYsTQ67uDFXLxmjZPU2K4i7SocI4BnhLC9ACkjn6RZSJxCEmmLVMojlVbYKXBthecqtDbBM9Guyu50K7erVetqyj7cfobpw/KXYAUMCoNQbILfBN9HdzYVeN12cj3wvK6cIbt7nNmF8DI/I8rD0pnXSnng88DvoYMa5dcYlkb5wLPM7M5t5se6a70erlKdZ5sUDh+egVBoMgfdFJ5SKKUzcdj5UU+Bhw9XK1ytPrJj3dniaw9XZ36QPa0zlxFqD9fTaDeJdts7f8z9KMNCmSbaMjCCQYwCI3PkT4PpaMw0WLiYeJmzIii0l3l4OltatKdwtQ9b+zM/8BhoOpMWHLTnoLSD8txMMmlpTBOU6XYm9Ab4M38ziTKdO/5e5rvoTDS07tzl6fxrGCqzn0RXPpA5MOCaCm0And/lhw1f5o8BGGQSFm1lEtHMTjVk9r86f+K8rjp0xod2MDp3jgzlobp2PJSLhYeBwme4mNnDIgYuCkcrlOo8s6ENlKMwbFBeIYYuwkRh6iDa8WG6RibpdDM7Gx4uGhttung+N5PgGpniqK79Ic/FUUkS4QbSPgvHVbiugecoPJfM2YCURyDaTl5HmmBrnEBHCiuazvzvKgcfLoZyMQ0XZbgYls5uK6U7k2PtgXZJOwnSRpoUMdJGkrxSTQqNqy0cK0RT2kIFy/EFCkhFWikMmlg6jZlso8xME8TGj43q0KRafaS8EAY+LHwoDEJaE/cHaCg9imnnn88R0Sh1dbVMmjSKtrYWduxIMWniiTQ3NdLY2MTwYYewZdM22pqjlJVWs2nNZppeeI+2pmaiowtwR2rMIj+BgInhalR7DLOlDX97M/kdW2krVrxaVUC9VUKhz8/4qnEMKx/F9m0NDB4wkEGFeax9bw1lg6rxh/wsXfMOpZUlNMXa2fjBBsqIUm40U1pcT1lpLWHPT74TwHB8ND39LrUlY4gMHIAd9H/4O+Ppzh3VzkzYzSQKhudheA6G46BcB8Nz0a6H4XgoBV7Ahxew8AJ+HL+F9lvYPgvXZ+EZJtqy0GZmBxed2eFVGrRjZBqPzp1vpTNnsvE0Rmd7YeBlpyvtZQ5aaA8cjU6nIWnjRlM4rSmcSBIn5WA7HtqN43pRHDONVi6eSoFnZ3fglGdlkhLPwsPK/O4qE0MbmIaB4bMwDBPDn/mrfBbKsjAsH1gmWFbmYFLnQUBtGZlLmQwLLAuUD4zO3+7ODDnznOzfrgMh2RSt66BB59EyZapMcmAYuEbnWTTDyBxkyB5oUJn/B6PzwI/KnClBpfnwDErn2RNclHbx4RLAwVBpLDJnZjKJfDZVxPMUnmfgGn5cgnjKh6P8pJUPdNfljZ+WGXT+qmR3VtTOs388V/hI8qe7Jnwk28nu3iv9kWThI82oJnvAteuz3ROdj63042XNzrPz3dCzS1KZ397uC3U/toqPbGM6v1P14TbOHGX6eJKlM7+VH/1Ocjz/sNdnLAzDoLy8nO985zucd955jB07dm8W0+fszaVQn3TG4qmO/8NVCscycU0T1ephNDeRDreyfdNG7MaFrK+oorrIT4e28OorGLd2EiXOIVT6LfIMm6AZI69gB4c4yzBCbRQfeQh5x9xCsGAIjuNgWZmjarZtZztddU0HsNMpdMtmIquXk9q4iXRblBYXIspPiyqk3s1nm1uOZ+eT5wSpdNsZQCNlqo0iFcOXb1MfjvO2Wc9iexv1rqY8EmBMh6IyaZF0Ckg5QQxbUeg0U2TvoMxspdSXoNDy8Fm+TJLh2RjawvBAuZmjGgGfJhD0oYI+jEA+Rn4xOi8MRf0gaOAZKbRVgg4eipN/KKpgcOboZ8hPsKwQf78g2q/w+Xx4nofrutnnnudhWdanPnddF6119jmAaZqf+txxHFTnpU2O42AYBoZhfOJzhYcTqUOlmyHSTrq5HTraMaINeJFmlOkHpWiNt1FWXolRUIEbKMDKK4a8EtyyofiKK9DQZ+pkGAa2bWN2XtbSFW+7ij3HcfD5fGits893uZ1cF9M08VwnUw9/YK/qBKANRdpOo1UmGYnbSWyd6R/iOE7mDJxhkLLTFPiChAMh/J5ByB/YbZ0sy8rWye/375fY8zyPTZs2MWzYMHw+X+9up4Mx9g6yOtm2zYYNGxg9ejRKqT5bJ9u2MS0zW6eubeB6Lj6rs07awzIz0xVqp7r2tTodiLGnlGLjxo0MHTqUQCBwUNTpYNxOvV2njo4OSktLP9tLod555x3mz5/PvHnzWLhwIaZpZjtvT58+/YBONI455hiOPPJIHnzwwey0cePGcd555+1x5+3nV19FsW1huRHW+31sryxkmy+fI7ZuRJtB3g5VkdfcxLCKqZw75GzGhoeB65FasYXky//GiM8jUPgeKqRQk6diHHoxZsm+3VtBe17mPg/NzdDehm5rgUgbJOOQjEBxIYwaByMPxQiXfMoyXEin8FrqcN9+FmpeRce34Frl6IKhGNUTsQZPQhUHMOxGdONKaN0I6Sg4NvjDEOqHKugHoUK0FyVz0bCBsvKgaDSq3+EQHnbQXkPpui4rV65k4sSJmKbceVbsmsSLyIXEi8iFxIvYE71yH4t33nmH+++/nz/96U/ZLOlA1TXc7MMPP8xxxx3H7373Ox555BHeffddhgwZstvPd22A1vZWAvZG2mr+P960U7we2YydP4iwGeAIK49TJnyHgkDRfqhR36C1hnQ7pFoyEwwTQv0zR/GFEEIIIUSfk0tisU+DFi9fvjzbaXvhwoV0dHRw2GGHcdJJJ+3LYnvdV77yFZqbm/nRj35EfX0948eP56WXXtqjpOKjDAxC/SZjtbzHWVpzzoiv4jUuwSibhFF5/EF7RP7TKKUgUJx5fI65rsvatWsZO3asHCESuyXxInIh8SJyIfEietpeJxYlJSVEo1EmTZrE9OnTueqqq5g6depnfqfp/eXaa6/l2muv7ZFl+UZ9DZ1qxWtdizXyK6jgzsPJCiGEEEIIcSDb60uhXnjhhYMqkehJn/Wdt4UQQgghhNgf9sulUGeffTZtbW38/Oc/Z+3atSilGDt2LFdcccVON4X7vOnK1To6Onq5JKIvcl2X1atXM378eDn1LHZL4kXkQuJF5ELiReyJrv3ZPTkXsddnLJYuXcrpp59OKBTi6KOPRmvN0qVLSSQSzJkzhyOOOGJvFntQ2Lp1K4MGDertYgghhBBCCNEjamtrGThw4C7n2evE4sQTT2TkyJE88sgj3cbRvfLKK9m0aRMLFizYm8UeFDzPo66ujnA4/LnroC12r6Ojg0GDBlFbWyuXyondkngRuZB4EbmQeBF7QmtNJBKhuroawzB2Oe9eJxahUIjly5czZsyYbtPXrFnD5MmTicfje7NYIQ560gdH5ELiReRC4kXkQuJF9LRdpx27UFhYyJYtW3aaXltbSzgc3qdCCSGEEEIIIQ4se51YfOUrX+GKK67gL3/5C7W1tWzdupWnnnqKK6+8kq9+9as9WUYhhBBCCCFEH7fXo0Lde++9KKX4+te/juM4APh8Pq655hruvvvuHiugEAebQCDAHXfcQSAQ6O2iiAOAxIvIhcSLyIXEi+hpe93Hoks8Huf9999Ha83IkSPJy8vrqbIJIYQQQgghDhA5XwoVj8e57rrrGDBgABUVFVx55ZX079+fiRMnSlIhhBBCCCHE51TOicUdd9zBY489xllnncWFF17Iq6++yjXXXPNZlE0IIYQQQghxgMj5UqgRI0bwk5/8hAsvvBCAt956i+OPP55kMil3bRRCCCGEEOJzKufEwu/3U1NTw4ABA7LTQqEQ69evl7tNCyGEEEII8TmV86VQruvi9/u7TbMsKzsylBACFixYwDnnnEN1dTVKKZ577rlu72utufPOO6muriYUCjF9+nTefffd3ims6HWzZ8/mqKOOIhwOU1FRwcyZM1m3bl23eSRmRJeHHnqIiRMnUlhYSGFhIccddxwvv/xy9n2JFbErs2fPRinFTTfdlJ0mMSN6Ss6Jhdaayy67jPPPPz/7SCaTfOtb3+o2TYjPs1gsxqRJk3jggQc+8f2f/vSn/OIXv+CBBx5gyZIlVFVVcdpppxGJRPZzSUVfMH/+fK677jreeOMNXn31VRzHYcaMGcRisew8EjOiy8CBA7n77rtZunQpS5cu5eSTT+a8887L7ghKrIhPs2TJEn73u98xceLEbtMlZkRPyflSqMsvv3yP5nv00Uf3qkBCHGyUUjz77LPMnDkTyCTn1dXV3HTTTdx2220ApFIpKisrueeee7j66qt7sbSiL9ixYwcVFRXMnz+fqVOnSsyI3SotLeVnP/sZ3/jGNyRWxCeKRqMcccQRPPjgg9x1110cdthh3H///dK+iB6V8w3yJGEQYt/U1NTQ0NDAjBkzstMCgQDTpk1j8eLF0ogL2tvbgczOIkjMiE/nui5/+9vfiMViHHfccRIr4lNdd911nHXWWZx66qncdddd2ekSM6In7fWdt4UQe6ehoQGAysrKbtMrKyvZvHlzbxRJ9CFaa26++WZOOOEExo8fD0jMiJ2tWrWK4447jmQySUFBAc8++yzjxo1j8eLFgMSK6O6pp55i2bJlLFmyZKf3pH0RPUkSCyF6iVKq22ut9U7TxOfP9ddfz8qVK1m0aNFO70nMiC6jR49mxYoVtLW18fTTT3PppZcyf/787PsSK6JLbW0tN954I3PmzCEYDH7qfBIzoifk3HlbCLFvqqqqgA+PEnVpbGzc6YiR+Hy54YYb+Pvf/85rr73GwIEDs9MlZsTH+f1+Ro4cyeTJk5k9ezaTJk3il7/8pcSK2Mnbb79NY2MjRx55JJZlYVkW8+fP51e/+hWWZWXjQmJG9ARJLITYz4YNG0ZVVRWvvvpqdlo6nWb+/PlMmTKlF0smeovWmuuvv55nnnmGuXPnMmzYsG7vS8yI3dFak0qlJFbETk455RRWrVrFihUrso/Jkydz8cUXs2LFCoYPHy4xI3qMXAolxGcgGo2ycePG7OuamhpWrFhBaWkpgwcP5qabbmLWrFmMGjWKUaNGMWvWLPLy8rjooot6sdSit1x33XU8+eSTPP/884TD4eyRw6KiIkKhUHbMeYkZAfD973+fM888k0GDBhGJRHjqqaeYN28er7zyisSK2Ek4HM721+qSn59Pv379stMlZkRPkcRCiM/A0qVLOemkk7Kvb775ZgAuvfRSHnvsMW699VYSiQTXXnstra2tHHPMMcyZM4dwONxbRRa96KGHHgJg+vTp3aY/+uijXHbZZQASMyJr+/btXHLJJdTX11NUVMTEiRN55ZVXOO200wCJFZE7iRnRU3K+j4UQQgghhBBCfJz0sRBCCCGEEELsM0kshBBCCCGEEPtMEgshhBBCCCHEPpPEQgghhBBCCLHPJLEQQgghhBBC7DNJLIQQQgghhBD7TBILIYQQQgghxD6TxEIIIYQQQgixzySxEEIIIYQQQuwzSSyEEEIIIYQQ+0wSCyGEEEIIIcQ+k8RCCCGEEEIIsc/+f2HFLdbM3E9AAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 800x400 with 6 Axes>"
       ]
@@ -268,8 +266,8 @@
     "\n",
     "nperseg = int(raw.info['sfreq']*2)\n",
     "raw.compute_psd(method='welch', n_per_seg=nperseg, n_overlap=nperseg//2, fmin=0.25, fmax=50).plot(axes=axes[0])\n",
-    "aperiodic_mne.plot(axes=axes[1])\n",
-    "periodic_mne.plot(axes=axes[2])\n",
+    "irasa_results.aperiodic.plot(axes=axes[1])\n",
+    "irasa_results.periodic.plot(axes=axes[2])\n",
     "\n",
     "axes[0].set_title('PSD')\n",
     "axes[1].set_title('Aperiodic Spectrum')\n",
@@ -296,60 +294,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
        "Text(0.5, 0, 'R2')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 800x400 with 2 Axes>"
       ]
@@ -359,15 +319,49 @@
     }
    ],
    "source": [
-    "df_ap_f, df_gof_f = aperiodic_mne.get_slopes(fit_func='fixed')\n",
-    "df_ap_k, df_gof_k = aperiodic_mne.get_slopes(fit_func='knee', scale=True);\n",
+    "fixed_model = irasa_results.aperiodic.get_slopes(fit_func='fixed', scale=True, fit_bounds=[.5, 45])\n",
+    "knee_model = irasa_results.aperiodic.get_slopes(fit_func='knee', scale=True, fit_bounds=[.5, 45]);\n",
     "\n",
     "\n",
     "f, ax = plt.subplots(ncols=2, figsize=(8,4))\n",
-    "ax[0].hist(df_gof_k['r_squared']);#\n",
+    "ax[0].hist(fixed_model.gof['r_squared']);\n",
     "ax[0].set_xlabel('R2')\n",
-    "ax[1].hist(df_gof_f['r_squared']);\n",
-    "ax[1].set_xlabel('R2')"
+    "ax[1].hist(knee_model.gof['r_squared']);#\n",
+    "ax[1].set_xlabel('R2')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 6.,  8., 11., 17., 17., 16.,  9., 12.,  4.,  2.]),\n",
+       " array([ 8.14227952,  9.53481945, 10.92735938, 12.31989931, 13.71243924,\n",
+       "        15.10497917, 16.4975191 , 17.89005903, 19.28259896, 20.67513888,\n",
+       "        22.06767881]),\n",
+       " <BarContainer object of 10 artists>)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(knee_model.aperiodic_params['Knee Frequency (Hz)'])"
    ]
   },
   {
@@ -387,7 +381,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -429,33 +423,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 248, using nperseg = 248\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n",
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 241, using nperseg = 241\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n",
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 234, using nperseg = 234\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n",
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 228, using nperseg = 228\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n",
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 222, using nperseg = 222\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n",
-      "/Users/fabian.schmidt/miniforge3/envs/pyrasa/lib/python3.12/site-packages/scipy/signal/_spectral_py.py:600: UserWarning: nperseg = 256 is greater than input length  = 216, using nperseg = 216\n",
-      "  freqs, _, Pxy = _spectral_helper(x, y, fs, window, nperseg, noverlap,\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "aperiodic, periodic = irasa_epochs(epochs, \n",
+    "irasa_epoched = irasa_epochs(epochs, \n",
     "                                   band=(.5, 50), \n",
-    "                                   hset_info=(1.,2.,.05), \n",
-    "                                   as_array=False)"
+    "                                   hset_info=(1.,2.,.05))"
    ]
   },
   {
@@ -467,303 +441,5243 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in multiply\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:114: RuntimeWarning: overflow encountered in scalar power\n",
-      "  'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n",
-      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/aperiodic_utils.py:27: RuntimeWarning: overflow encountered in power\n",
-      "  y_hat = b0 - np.log10(x**b1 * (k + x**b2))\n"
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in power\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n",
+      "/Users/fabian.schmidt/git/pyrasa/pyrasa/utils/fit_funcs.py:137: RuntimeWarning: overflow encountered in multiply\n",
+      "  y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))\n"
      ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Offset</th>\n",
-       "      <th>Knee</th>\n",
-       "      <th>Exponent_1</th>\n",
-       "      <th>Exponent_2</th>\n",
-       "      <th>Knee Frequency (Hz)</th>\n",
-       "      <th>fit_type</th>\n",
-       "      <th>ch_name</th>\n",
-       "      <th>event_id</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1.384293e-27</td>\n",
-       "      <td>1.327888e+13</td>\n",
-       "      <td>4.514556e-01</td>\n",
-       "      <td>7.825370</td>\n",
-       "      <td>31.880262</td>\n",
-       "      <td>knee</td>\n",
-       "      <td>MEG 0111</td>\n",
-       "      <td>Auditory/Left</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>3.031858e-28</td>\n",
-       "      <td>4.417963e+01</td>\n",
-       "      <td>2.857408e-13</td>\n",
-       "      <td>1.981088</td>\n",
-       "      <td>6.768057</td>\n",
-       "      <td>knee</td>\n",
-       "      <td>MEG 0121</td>\n",
-       "      <td>Auditory/Left</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>4.071002e-28</td>\n",
-       "      <td>3.109493e+03</td>\n",
-       "      <td>1.255273e-14</td>\n",
-       "      <td>2.467438</td>\n",
-       "      <td>26.032316</td>\n",
-       "      <td>knee</td>\n",
-       "      <td>MEG 0131</td>\n",
-       "      <td>Auditory/Left</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1.790656e-28</td>\n",
-       "      <td>1.480185e+01</td>\n",
-       "      <td>4.554958e-10</td>\n",
-       "      <td>1.122679</td>\n",
-       "      <td>11.026333</td>\n",
-       "      <td>knee</td>\n",
-       "      <td>MEG 0141</td>\n",
-       "      <td>Auditory/Left</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>3.958079e-28</td>\n",
-       "      <td>6.873358e+02</td>\n",
-       "      <td>2.709892e-13</td>\n",
-       "      <td>2.654790</td>\n",
-       "      <td>11.713811</td>\n",
-       "      <td>knee</td>\n",
-       "      <td>MEG 0211</td>\n",
-       "      <td>Auditory/Left</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         Offset          Knee    Exponent_1  Exponent_2  Knee Frequency (Hz)  \\\n",
-       "0  1.384293e-27  1.327888e+13  4.514556e-01    7.825370            31.880262   \n",
-       "0  3.031858e-28  4.417963e+01  2.857408e-13    1.981088             6.768057   \n",
-       "0  4.071002e-28  3.109493e+03  1.255273e-14    2.467438            26.032316   \n",
-       "0  1.790656e-28  1.480185e+01  4.554958e-10    1.122679            11.026333   \n",
-       "0  3.958079e-28  6.873358e+02  2.709892e-13    2.654790            11.713811   \n",
-       "\n",
-       "  fit_type   ch_name       event_id  \n",
-       "0     knee  MEG 0111  Auditory/Left  \n",
-       "0     knee  MEG 0121  Auditory/Left  \n",
-       "0     knee  MEG 0131  Auditory/Left  \n",
-       "0     knee  MEG 0141  Auditory/Left  \n",
-       "0     knee  MEG 0211  Auditory/Left  "
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
     }
    ],
    "source": [
-    "ap_slope, ap_gof = aperiodic.get_slopes(fit_func='knee', scale=True)\n",
-    "ap_slope.head()"
+    "knee_epoched = irasa_epoched.aperiodic.get_slopes(fit_func='knee', scale=True, fit_bounds=[1, 45])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -772,13 +5686,13 @@
        "<Axes: xlabel='event_id', ylabel='Knee Frequency (Hz)'>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -788,7 +5702,7 @@
     }
    ],
    "source": [
-    "ap_data = ap_slope.groupby(['event_id', 'ch_name'])['Knee Frequency (Hz)'].mean().reset_index()\n",
+    "ap_data = knee_epoched.aperiodic_params.groupby(['event_id', 'ch_name'])['Knee Frequency (Hz)'].mean().reset_index()\n",
     "ap_data\n",
     "sns.pointplot(ap_data, x='event_id', y='Knee Frequency (Hz)')"
    ]
@@ -875,7 +5789,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
diff --git a/pyrasa/irasa_mne/mne_objs.py b/pyrasa/irasa_mne/mne_objs.py
index b5ce0ed..7ce3380 100644
--- a/pyrasa/irasa_mne/mne_objs.py
+++ b/pyrasa/irasa_mne/mne_objs.py
@@ -1,4 +1,5 @@
 # %% inherit from spectrum array
+
 import matplotlib
 import mne
 import numpy as np
@@ -10,6 +11,8 @@
 from pyrasa.utils.peak_utils import get_peak_params
 from pyrasa.utils.types import SlopeFit
 
+# FutureWarning:
+
 
 class PeriodicSpectrumArray(SpectrumArray):
     """Subclass of SpectrumArray"""
@@ -170,7 +173,10 @@ def __init__(
         )
 
     def get_slopes(
-        self: SpectrumArray, fit_func: str = 'fixed', scale: bool = False, fit_bounds: tuple[float, float] | None = None
+        self: SpectrumArray,
+        fit_func: str = 'fixed',
+        scale: bool = False,
+        fit_bounds: tuple[float, float] | None = None,
     ) -> SlopeFit:
         """
         This method can be used to extract aperiodic parameters from the aperiodic spectrum extracted from IRASA.
@@ -393,7 +399,10 @@ def __init__(
         )
 
     def get_slopes(
-        self: SpectrumArray, fit_func: str = 'fixed', scale: bool = False, fit_bounds: tuple[float, float] | None = None
+        self: SpectrumArray,
+        fit_func: str = 'fixed',
+        scale: bool = False,
+        fit_bounds: tuple[float, float] | None = None,
     ) -> SlopeFit:
         """
         This method can be used to extract aperiodic parameters from the aperiodic spectrum extracted from IRASA.
diff --git a/pyrasa/utils/aperiodic_utils.py b/pyrasa/utils/aperiodic_utils.py
index 030adf4..1e43f08 100644
--- a/pyrasa/utils/aperiodic_utils.py
+++ b/pyrasa/utils/aperiodic_utils.py
@@ -5,129 +5,29 @@
 
 import numpy as np
 import pandas as pd
-from scipy.optimize import curve_fit
 
+from pyrasa.utils.fit_funcs import AbstractFitFun, FixedFitFun, KneeFitFun
 from pyrasa.utils.types import SlopeFit
 
 
-def fixed_model(x: np.ndarray, b0: float, b: float) -> np.ndarray:
-    """
-    Specparams fixed fitting function.
-    Use this to model aperiodic activity without a spectral knee
-    """
-
-    y_hat = b0 - np.log10(x**b)
-
-    return y_hat
-
-
-def knee_model(x: np.ndarray, b0: float, k: float, b1: float, b2: float) -> np.ndarray:
-    """
-    Model aperiodic activity with a spectral knee and a pre-knee slope.
-    Use this to model aperiodic activity with a spectral knee
-    """
-
-    y_hat = b0 - np.log10(x**b1 * (k + x**b2))
-
-    return y_hat
-
-
-def _get_gof(psd: np.ndarray, psd_pred: np.ndarray, fit_func: str) -> pd.DataFrame:
-    """
-    get goodness of fit (i.e. mean squared error and R2)
-    BIC and AIC currently assume OLS
-    https://machinelearningmastery.com/probabilistic-model-selection-measures/
-    """
-
-    residuals = np.log10(psd) - psd_pred
-    ss_res = np.sum(residuals**2)
-    ss_tot = np.sum((np.log10(psd) - np.mean(np.log10(psd))) ** 2)
-    mse = np.mean(residuals**2)
-
-    if fit_func == 'knee':
-        k = 3  # k -> number of params
-    elif fit_func == 'fixed':
-        k = 1  # k -> number of params
-
-    n = len(psd)
-    bic = n * np.log(mse) + k * np.log(n)
-    aic = n * np.log(mse) + 2 * k
-
-    gof = pd.DataFrame({'mse': mse, 'r_squared': 1 - (ss_res / ss_tot), 'BIC': bic, 'AIC': aic}, index=[0])
-    return gof
-
-
 def _compute_slope(
     aperiodic_spectrum: np.ndarray,
     freq: np.ndarray,
-    fit_func: str,
-    fit_bounds: tuple | None = None,
+    fit_func: str | type[AbstractFitFun],
     scale_factor: float | int = 1,
 ) -> tuple[pd.DataFrame, pd.DataFrame]:
     """get the slope of the aperiodic spectrum"""
 
-    curv_kwargs = {
-        'maxfev': 10_000,
-        'ftol': 1e-5,
-        'xtol': 1e-5,
-        'gtol': 1e-5,
-    }
-
-    off_guess = [aperiodic_spectrum[0]] if fit_bounds is None else fit_bounds[0]
-    exp_guess = (
-        [np.abs(np.log10(aperiodic_spectrum[0] / aperiodic_spectrum[-1]) / np.log10(freq[-1] / freq[0]))]
-        if fit_bounds is None
-        else fit_bounds[1]
-    )
-
-    valid_slope_functions = ['fixed', 'knee']
-    assert fit_func in valid_slope_functions, f'The slope fitting function has to be in {valid_slope_functions}'
-
-    if fit_func == 'fixed':
-        fit_f = fixed_model
-
-        p, _ = curve_fit(fit_f, freq, np.log10(aperiodic_spectrum))
-
-        params = pd.DataFrame(
-            {
-                'Offset': p[0],
-                'Exponent': p[1],
-                'fit_type': 'fixed',
-            },
-            index=[0],
-        )
-        psd_pred = fit_f(freq, *p)
-
-    elif fit_func == 'knee':
-        fit_f = knee_model  # type: ignore
-        # curve_fit_specs
-        cumsum_psd = np.cumsum(aperiodic_spectrum)
-        half_pw_freq = freq[np.abs(cumsum_psd - (0.5 * cumsum_psd[-1])).argmin()]
-        # make the knee guess the point where we have half the power in the spectrum seems plausible to me
-        knee_guess = [half_pw_freq ** (exp_guess[0] + exp_guess[0])]
-        # convert knee freq to knee val which should be 2*exp_1 but this seems good enough
-        curv_kwargs['p0'] = np.array(off_guess + knee_guess + exp_guess + exp_guess)  # type: ignore
-        # print(curv_kwargs['p0'])
-        # make this optional
-        curv_kwargs['bounds'] = ((0, 0, 0, 0), (np.inf, np.inf, np.inf, np.inf))  # type: ignore
-        # knee value should always be positive at least intuitively
-        p, _ = curve_fit(fit_f, freq, np.log10(aperiodic_spectrum), **curv_kwargs)
-
-        params = pd.DataFrame(
-            {
-                'Offset': p[0] / scale_factor,
-                'Knee': p[1],
-                'Exponent_1': p[2],
-                'Exponent_2': p[3],
-                'Knee Frequency (Hz)': p[1] ** (1.0 / (2 * p[2] + p[3])),
-                'fit_type': 'knee',
-            },
-            index=[0],
-        )
-        psd_pred = fit_f(freq, *p)
+    if isinstance(fit_func, str):
+        if fit_func == 'fixed':
+            fit_func = FixedFitFun
+        elif fit_func == 'knee':
+            fit_func = KneeFitFun
+        else:
+            raise ValueError('fit_func should be either "fixed" or "knee"')
 
-    gof = _get_gof(aperiodic_spectrum, psd_pred, fit_func)
-    gof['fit_type'] = fit_func
+    fit_f = fit_func(freq, aperiodic_spectrum, scale_factor=scale_factor)
+    params, gof = fit_f.fit_func()
 
     return params, gof
 
@@ -135,7 +35,7 @@ def _compute_slope(
 def compute_slope(
     aperiodic_spectrum: np.ndarray,
     freqs: np.ndarray,
-    fit_func: str,
+    fit_func: str | type[AbstractFitFun] = 'fixed',
     ch_names: Iterable | None = None,
     scale: bool = False,
     fit_bounds: tuple[float, float] | None = None,
@@ -186,6 +86,8 @@ def compute_slope(
         fmin, fmax = freqs.min(), freqs.max()
         assert fit_bounds[0] > fmin, f'The selected lower bound is lower than the lowest frequency of {fmin}Hz'
         assert fit_bounds[1] < fmax, f'The selected upper bound is higher than the highest frequency of {fmax}Hz'
+        freq_logical = np.logical_and(freqs >= fit_bounds[0], freqs <= fit_bounds[1])
+        aperiodic_spectrum, freqs = aperiodic_spectrum[:, freq_logical], freqs[freq_logical]
 
     if freqs[0] == 0:
         warnings.warn(
@@ -216,7 +118,6 @@ def num_zeros(decimal: int) -> float:
             freq=freqs,
             fit_func=fit_func,
             scale_factor=scale_factor,
-            fit_bounds=fit_bounds,
         )
 
         params['ch_name'] = ch_name
diff --git a/pyrasa/utils/fit_funcs.py b/pyrasa/utils/fit_funcs.py
new file mode 100644
index 0000000..f58020e
--- /dev/null
+++ b/pyrasa/utils/fit_funcs.py
@@ -0,0 +1,171 @@
+import abc
+import inspect
+from collections.abc import Callable
+from typing import Any, ClassVar, no_type_check
+
+import numpy as np
+import pandas as pd
+from attrs import define
+from scipy.optimize import curve_fit
+
+
+def _get_args(f: Callable) -> list:
+    return inspect.getfullargspec(f)[0][2:]
+
+
+def _get_gof(psd: np.ndarray, psd_pred: np.ndarray, k: int, fit_type: str) -> pd.DataFrame:
+    """
+    get goodness of fit (i.e. mean squared error and R2)
+    BIC and AIC currently assume OLS
+    https://machinelearningmastery.com/probabilistic-model-selection-measures/
+    """
+    # k number of parameters in curve fitting function
+
+    # add np.log10 to psd
+    residuals = psd - psd_pred
+    ss_res = np.sum(residuals**2)
+    ss_tot = np.sum((psd - np.mean(psd)) ** 2)
+
+    mse = np.mean(residuals**2)
+
+    n = len(psd)
+    bic = n * np.log(mse) + k * np.log(n)
+    aic = n * np.log(mse) + 2 * k
+
+    gof = pd.DataFrame({'mse': mse, 'r_squared': 1 - (ss_res / ss_tot), 'BIC': bic, 'AIC': aic}, index=[0])
+    gof['fit_type'] = fit_type
+    return gof
+
+
+@define
+class AbstractFitFun(abc.ABC):
+    freq: np.ndarray
+    aperiodic_spectrum: np.ndarray
+    scale_factor: int | float
+    label: ClassVar[str] = 'custom'
+    log10_aperiodic: ClassVar[bool] = False
+    log10_freq: ClassVar[bool] = False
+
+    def __attrs_post_init__(self) -> None:
+        if self.log10_aperiodic:
+            self.aperiodic_spectrum = np.log10(self.aperiodic_spectrum)
+        if self.log10_freq:
+            self.freq = np.log10(self.freq)
+
+    @abc.abstractmethod
+    @no_type_check
+    def func(self, x: np.ndarray, *args: float) -> np.ndarray:
+        pass
+
+    @property
+    def curve_kwargs(self) -> dict[str, Any]:
+        return {
+            'maxfev': 10_000,
+            'ftol': 1e-5,
+            'xtol': 1e-5,
+            'gtol': 1e-5,
+        }
+
+    def add_infos_to_df(self, df_params: pd.DataFrame) -> pd.DataFrame:
+        return df_params
+
+    def handle_scaling(self, df_params: pd.DataFrame, scale_factor: float) -> pd.DataFrame:
+        if 'Offset' in df_params.columns:
+            df_params['Offset'] /= scale_factor
+        elif scale_factor != 1.0:
+            raise ValueError('Scale Factor not handled. You need to overwrite the handle_scaling method.')
+        return df_params
+
+    def fit_func(self) -> tuple[pd.DataFrame, pd.DataFrame]:
+        curve_kwargs = self.curve_kwargs
+        p, _ = curve_fit(self.func, self.freq, self.aperiodic_spectrum, **curve_kwargs)
+
+        my_args = _get_args(self.func)
+        df_params = pd.DataFrame(dict(zip(my_args, p)), index=[0])
+        df_params['fit_type'] = self.label
+
+        pred = self.func(self.freq, *p)
+        df_gof = _get_gof(self.aperiodic_spectrum, pred, len(p), self.label)
+
+        df_params = self.add_infos_to_df(df_params)
+        df_params = self.handle_scaling(df_params, scale_factor=self.scale_factor)
+
+        return df_params, df_gof
+
+
+class FixedFitFun(AbstractFitFun):
+    label = 'fixed'
+    log10_aperiodic = True
+
+    def func(self, x: np.ndarray, Offset: float, Exponent: float) -> np.ndarray:  # noqa N803
+        """
+        Specparams fixed fitting function.
+        Use this to model aperiodic activity without a spectral knee
+        """
+        y_hat = Offset - np.log10(x**Exponent)
+
+        return y_hat
+
+    @property
+    def curve_kwargs(self) -> dict[str, Any]:
+        aperiodic_nolog = 10**self.aperiodic_spectrum
+        off_guess = [aperiodic_nolog[0]]
+        exp_guess = [
+            np.abs(np.log10(aperiodic_nolog[0] / aperiodic_nolog[-1]) / np.log10(self.freq[-1] / self.freq[0]))
+        ]
+        return {
+            'maxfev': 10_000,
+            'ftol': 1e-5,
+            'xtol': 1e-5,
+            'gtol': 1e-5,
+            'p0': np.array(off_guess + exp_guess),
+            'bounds': ((-np.inf, -np.inf), (np.inf, np.inf)),
+        }
+
+
+class KneeFitFun(AbstractFitFun):
+    label = 'knee'
+    log10_aperiodic = True
+
+    def func(
+        self,
+        x: np.ndarray,
+        Offset: float,  # noqa N803
+        Knee: float,  # noqa N803
+        Exponent_1: float,  # noqa N803
+        Exponent_2: float,  # noqa N803
+    ) -> np.ndarray:
+        """
+        Model aperiodic activity with a spectral knee and a pre-knee slope.
+        Use this to model aperiodic activity with a spectral knee
+        """
+        y_hat = Offset - np.log10(x**Exponent_1 * (Knee + x**Exponent_2))
+
+        return y_hat
+
+    def add_infos_to_df(self, df_params: pd.DataFrame) -> pd.DataFrame:
+        df_params['Knee Frequency (Hz)'] = df_params['Knee'] ** (
+            1.0 / (2 * df_params['Exponent_1'] + df_params['Exponent_2'])
+        )
+        return df_params
+
+    @property
+    def curve_kwargs(self) -> dict[str, Any]:
+        aperiodic_nolog = 10**self.aperiodic_spectrum
+        off_guess = [aperiodic_nolog[0]]
+        exp_guess = [
+            np.abs(np.log10(aperiodic_nolog[0] / aperiodic_nolog[-1]) / np.log10(self.freq[-1] / self.freq[0]))
+        ]
+        cumsum_psd = np.cumsum(aperiodic_nolog)
+        half_pw_freq = self.freq[np.abs(cumsum_psd - (0.5 * cumsum_psd[-1])).argmin()]
+        # make the knee guess the point where we have half the power in the spectrum seems plausible to me
+        knee_guess = [half_pw_freq ** (exp_guess[0] + exp_guess[0])]
+
+        return {
+            'maxfev': 10_000,
+            'ftol': 1e-5,
+            'xtol': 1e-5,
+            'gtol': 1e-5,
+            'p0': np.array(off_guess + knee_guess + exp_guess + exp_guess),
+            'bounds': ((0, 0, 0, 0), (np.inf, np.inf, np.inf, np.inf)),
+        }
diff --git a/simulations/notebooks/sim_peak_tests.py b/simulations/notebooks/sim_peak_tests.py
new file mode 100644
index 0000000..8f98150
--- /dev/null
+++ b/simulations/notebooks/sim_peak_tests.py
@@ -0,0 +1,30 @@
+#%%
+from neurodsp.sim import sim_oscillation
+import matplotlib.pyplot as plt
+from pyrasa.utils.peak_utils import get_peak_params
+import scipy.signal as dsp
+import numpy as np
+# %%
+f_range = [1, 250]
+n_secs = 5*60
+fs = 200
+osc_freq = 98
+f_range4plot = [80, 110]
+
+ts = sim_oscillation(n_seconds=n_secs, fs=fs, freq=osc_freq)
+plt.plot(ts[:100])
+
+#%%
+freqs, psd = dsp.welch(ts, fs, nperseg=int(4 * fs))
+plt.plot(freqs, psd)
+
+freq_logical = np.logical_and(freqs >= f_range[0], freqs <= f_range[1])
+freqs, psd = freqs[freq_logical], psd[freq_logical]
+# %%
+pe_params = get_peak_params(psd[np.newaxis, :], freqs, min_peak_height=0.1)
+pe_params
+# %%
+
+freq_logical = np.logical_and(freqs >= f_range4plot[0], freqs <= f_range4plot[1])
+plt.plot(freqs[freq_logical], psd[freq_logical])
+# %%
diff --git a/tests/settings.py b/tests/settings.py
index e6d9e30..2554378 100644
--- a/tests/settings.py
+++ b/tests/settings.py
@@ -4,14 +4,18 @@
 
 N_SECONDS = 60
 FS = [500, 750, 1000]
+
 OSC_FREQ = [5, 10, 20]
 MANY_OSC_FREQ = np.arange(2, 30, 1)
+# through a bug in neurodsp #223 there is a systematic error in generating spectra with high frequency peaks
+# where the actual simulated center frequency is biased.
+# This bias increases as the simulated center frequency gets closer to the sampling rate used in the simulation.
+# If you want to play around with this check: simulations/notebooks/sim_peak_tests.py
 EXPONENT = [-1, -1.5, -2.0]
 KNEE_FREQ = 15
 # There seems to be a higher error in knee fits for knee and exponent estimates when
 # the difference in pre and post knee exponent is low. This kinda makes sense
 # TODO: Test this systematically -> see whether this is an issue with irasa or slope fitting in general
-
 EXP_KNEE_COMBO = [
     (1.0, 10.0),
     (1.0, 15.0),
@@ -24,6 +28,7 @@
     (2.0, 625.0),
 ]  # we test exp + knee combined as both relate to each other
 TOLERANCE = 0.3  # 0.15
+HIGH_TOLERANCE = 0.5
 KNEE_TOLERANCE = 5
 MIN_R2 = 0.8  # seems like a sensible minimum
 MIN_R2_SPRINT = 0.7
diff --git a/tests/test_compute_slope.py b/tests/test_compute_slope.py
index c678f18..a71f5c8 100644
--- a/tests/test_compute_slope.py
+++ b/tests/test_compute_slope.py
@@ -3,8 +3,9 @@
 import scipy.signal as dsp
 
 from pyrasa.utils.aperiodic_utils import compute_slope
+from pyrasa.utils.fit_funcs import AbstractFitFun
 
-from .settings import EXPONENT, FS, MIN_R2, TOLERANCE
+from .settings import EXPONENT, FS, HIGH_TOLERANCE, MIN_R2, TOLERANCE
 
 
 # Test slope fitting functionality
@@ -64,3 +65,48 @@ def test_slope_fitting_settings(
     # test for warning
     with pytest.warns(UserWarning, match=match_txt):
         compute_slope(psd[freq_logical], freqs[freq_logical], fit_func='fixed')
+
+
+# test custom slope fitting functions
+@pytest.mark.parametrize('exponent, fs', [(-1, 500)], scope='session')
+def test_custom_slope_fitting(
+    fixed_aperiodic_signal,
+    exponent,
+    fs,
+):
+    f_range = [1.5, 300]
+    # test whether recombining periodic and aperiodic spectrum is equivalent to the original spectrum
+    freqs, psd = dsp.welch(fixed_aperiodic_signal, fs, nperseg=int(4 * fs))
+    freq_logical = np.logical_and(freqs >= f_range[0], freqs <= f_range[1])
+    psd, freqs = psd[freq_logical], freqs[freq_logical]
+
+    class CustomFitFun(AbstractFitFun):
+        def func(self, x: np.ndarray, a: float, b: float) -> np.ndarray:
+            """
+            Specparams fixed fitting function.
+            Use this to model aperiodic activity without a spectral knee
+            """
+            y_hat = a + b * x
+
+            return y_hat
+
+        @property
+        def curve_kwargs(self) -> dict[str, any]:
+            aperiodic_nolog = self.aperiodic_spectrum
+            off_guess = [aperiodic_nolog[0]]
+            exp_guess = [
+                np.abs(np.log10(aperiodic_nolog[0] / aperiodic_nolog[-1]) / np.log10(self.freq[-1] / self.freq[0]))
+            ]
+            return {
+                'maxfev': 10_000,
+                'ftol': 1e-5,
+                'xtol': 1e-5,
+                'gtol': 1e-5,
+                'p0': np.array(off_guess + exp_guess),
+                'bounds': ((-np.inf, -np.inf), (np.inf, np.inf)),
+            }
+
+    slope_fit = compute_slope(np.log10(psd), np.log10(freqs), fit_func=CustomFitFun)
+
+    # add a high tolerance
+    assert pytest.approx(np.abs(slope_fit.aperiodic_params['b'][0]), abs=HIGH_TOLERANCE) == np.abs(exponent)
diff --git a/tests/test_mne.py b/tests/test_mne.py
index 46bd47c..6b8ae9d 100644
--- a/tests/test_mne.py
+++ b/tests/test_mne.py
@@ -1,5 +1,6 @@
 import pytest
 from neurodsp.utils.sim import set_random_seed
+from scipy.optimize import OptimizeWarning
 
 from pyrasa.irasa_mne import irasa_epochs, irasa_raw
 
@@ -13,8 +14,9 @@ def test_mne(gen_mne_data_raw):
 
     # test raw
     irasa_raw_result = irasa_raw(mne_data, band=(0.25, 50), duration=2, hset_info=(1.0, 2.0, 0.05))
-    irasa_raw_result.aperiodic.get_slopes(fit_func='fixed')
-    irasa_raw_result.periodic.get_peaks(smoothing_window=2)
+    with pytest.warns(OptimizeWarning):
+        irasa_raw_result.aperiodic.get_slopes(fit_func='fixed')
+        irasa_raw_result.periodic.get_peaks(smoothing_window=2)
 
     # test epochs
     irasa_epoched_result = irasa_epochs(epochs, band=(0.5, 50), hset_info=(1.0, 2.0, 0.05))
diff --git a/tests/test_peak_detect.py b/tests/test_peak_detect.py
index c8ac781..78adc33 100644
--- a/tests/test_peak_detect.py
+++ b/tests/test_peak_detect.py
@@ -37,7 +37,7 @@ def test_no_peak_detection(fixed_aperiodic_signal, fs):
 
 
 @pytest.mark.parametrize('osc_freq, fs', [(10, 500)], scope='session')
-def test_peak_detection_setings(oscillation, fs, osc_freq):
+def test_peak_detection_settings(oscillation, fs, osc_freq):
     f_range = [1, 250]
     # test whether recombining periodic and aperiodic spectrum is equivalent to the original spectrum
     freqs, psd = dsp.welch(oscillation, fs, nperseg=int(4 * fs))