From 12892d9293a0967c91dca87c565f991fbe3d6eff Mon Sep 17 00:00:00 2001 From: Fabi Date: Thu, 22 Aug 2024 23:37:35 +0200 Subject: [PATCH] Improved Error messages when fitting irasa --- examples/irasa_pitfalls.ipynb | 153 ++++++++++++++++++++++++---------- pyrasa/utils/irasa_utils.py | 17 ++-- 2 files changed, 120 insertions(+), 50 deletions(-) diff --git a/examples/irasa_pitfalls.ipynb b/examples/irasa_pitfalls.ipynb index 669159b..fc2cd1f 100644 --- a/examples/irasa_pitfalls.ipynb +++ b/examples/irasa_pitfalls.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -37,12 +37,12 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -89,20 +89,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 3, "metadata": {}, "outputs": [ { "ename": "AssertionError", - "evalue": "The evaluated frequency range goes up to 300.0Hz which is higher than Nyquist (fs / 2)", + "evalue": "The evaluated frequency range goes up to 300.0Hz which is higher than the Nyquist frequency for your data of 250.0Hz, \ntry to either lower the upper bound for the hset or decrease the upper band limit, when running IRASA.", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m irasa_out \u001b[38;5;241m=\u001b[39m \u001b[43mirasa\u001b[49m\u001b[43m(\u001b[49m\u001b[43msig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mband\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m150\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mpsd_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnperseg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnoverlap\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moverlap\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.05\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/git/pyrasa/pyrasa/irasa.py:123\u001b[0m, in \u001b[0;36mirasa\u001b[0;34m(data, fs, band, psd_kwargs, ch_names, win_func, win_func_kwargs, dpss_settings_time_bandwidth, dpss_settings_low_bias, dpss_eigenvalue_weighting, filter_settings, hset_info, hset_accuracy)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m data\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mData shape needs to be either of shape (Channels, Samples) or (Samples, ).\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;66;03m# noqa PLR2004\u001b[39;00m\n\u001b[1;32m 115\u001b[0m irasa_params \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 116\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m'\u001b[39m: data,\n\u001b[1;32m 117\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfs\u001b[39m\u001b[38;5;124m'\u001b[39m: fs,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m'\u001b[39m: hset_accuracy,\n\u001b[1;32m 121\u001b[0m }\n\u001b[0;32m--> 123\u001b[0m \u001b[43m_check_irasa_settings\u001b[49m\u001b[43m(\u001b[49m\u001b[43mirasa_params\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mirasa_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhset_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 125\u001b[0m hset \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mround(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m*\u001b[39mhset_info), hset_accuracy)\n\u001b[1;32m 127\u001b[0m win_kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwin_func\u001b[39m\u001b[38;5;124m'\u001b[39m: win_func, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwin_func_kwargs\u001b[39m\u001b[38;5;124m'\u001b[39m: win_func_kwargs}\n", - "File \u001b[0;32m~/git/pyrasa/pyrasa/utils/irasa_utils.py:159\u001b[0m, in \u001b[0;36m_check_irasa_settings\u001b[0;34m(irasa_params, hset_info)\u001b[0m\n\u001b[1;32m 157\u001b[0m band_evaluated: \u001b[38;5;28mtuple\u001b[39m[\u001b[38;5;28mfloat\u001b[39m, \u001b[38;5;28mfloat\u001b[39m] \u001b[38;5;241m=\u001b[39m (irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m/\u001b[39m hmax, irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m*\u001b[39m hmax)\n\u001b[1;32m 158\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m band_evaluated[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe evaluated frequency range is 0 or lower this makes no sense\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m--> 159\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m band_evaluated[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m<\u001b[39m nyquist, (\n\u001b[1;32m 160\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe evaluated frequency range goes up to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39m\u001b[38;5;241m2\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwhich is higher than Nyquist (fs / 2)\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 162\u001b[0m )\n\u001b[1;32m 164\u001b[0m filter_settings: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mfloat\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfilter_settings\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filter_settings[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "\u001b[0;31mAssertionError\u001b[0m: The evaluated frequency range goes up to 300.0Hz which is higher than Nyquist (fs / 2)" + "Cell \u001b[0;32mIn[3], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m irasa_out \u001b[38;5;241m=\u001b[39m \u001b[43mirasa\u001b[49m\u001b[43m(\u001b[49m\u001b[43msig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mband\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m150\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mpsd_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnperseg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnoverlap\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moverlap\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.05\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/irasa.py:123\u001b[0m, in \u001b[0;36mirasa\u001b[0;34m(data, fs, band, psd_kwargs, ch_names, win_func, win_func_kwargs, dpss_settings_time_bandwidth, dpss_settings_low_bias, dpss_eigenvalue_weighting, filter_settings, hset_info, hset_accuracy)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m data\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mData shape needs to be either of shape (Channels, Samples) or (Samples, ).\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;66;03m# noqa PLR2004\u001b[39;00m\n\u001b[1;32m 115\u001b[0m irasa_params \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 116\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m'\u001b[39m: data,\n\u001b[1;32m 117\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfs\u001b[39m\u001b[38;5;124m'\u001b[39m: fs,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m'\u001b[39m: hset_accuracy,\n\u001b[1;32m 121\u001b[0m }\n\u001b[0;32m--> 123\u001b[0m \u001b[43m_check_irasa_settings\u001b[49m\u001b[43m(\u001b[49m\u001b[43mirasa_params\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mirasa_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhset_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 125\u001b[0m hset \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mround(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m*\u001b[39mhset_info), hset_accuracy)\n\u001b[1;32m 126\u001b[0m hset \u001b[38;5;241m=\u001b[39m [h \u001b[38;5;28;01mfor\u001b[39;00m h \u001b[38;5;129;01min\u001b[39;00m hset \u001b[38;5;28;01mif\u001b[39;00m h \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m] \u001b[38;5;66;03m# filter integers\u001b[39;00m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/utils/irasa_utils.py:159\u001b[0m, in \u001b[0;36m_check_irasa_settings\u001b[0;34m(irasa_params, hset_info)\u001b[0m\n\u001b[1;32m 157\u001b[0m band_evaluated: \u001b[38;5;28mtuple\u001b[39m[\u001b[38;5;28mfloat\u001b[39m, \u001b[38;5;28mfloat\u001b[39m] \u001b[38;5;241m=\u001b[39m (irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m/\u001b[39m hmax, irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m*\u001b[39m hmax)\n\u001b[1;32m 158\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m band_evaluated[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe evaluated frequency range is 0 or lower this makes no sense\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m--> 159\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m band_evaluated[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m<\u001b[39m nyquist, (\n\u001b[1;32m 160\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe evaluated frequency range goes up to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39m\u001b[38;5;241m2\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwhich is higher than the Nyquist frequency for your data of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnyquist\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz, \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 162\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtry to either lower the upper bound for the hset or decrease the upper band limit, when running IRASA.\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 163\u001b[0m )\n\u001b[1;32m 165\u001b[0m filter_settings: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mfloat\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(irasa_params[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfilter_settings\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filter_settings[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "\u001b[0;31mAssertionError\u001b[0m: The evaluated frequency range goes up to 300.0Hz which is higher than the Nyquist frequency for your data of 250.0Hz, \ntry to either lower the upper bound for the hset or decrease the upper band limit, when running IRASA." ] } ], @@ -125,22 +125,22 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 30, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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/3WtwVQDQ/BBegDo4vmL1I+O7S5LeWbxHFTa7wVUBQPNCeAHq4ZbzOyiiha8y88v005ZMo8sBgGaF8ALUg5/VouuT4iRVLfgIAGg6hBegnm4YFCezSVq6O0e7sgqMLgcAmg3CC1BP0WEBurBHlCTpo+WpBlcDAM0H4QVogEmD20uSvlhzQMXllQZXAwDNA+EFaIBhXSLUoVWgCsoqNXtdurLyS7Vm/xFtOphndGkA4LVYVRpooBmL9+iv322tsX3WnYM1qFMrAyoCAM/DqtJAE7o6MUbhQb6SJLNJCvazSpJmMIEdADQKq9EFAJ4uLNBXCx4YqbySCrUN89f+nCKN+ccizd+aqbTcYsWGBxpdIgB4FVpeABcIDfRRXKtA+VjM6hIZrOFdI2R3MAcMADQGwgvQCG4Z2kGS9OnKVEYhAYCLEV6ARjCqW6TatwpUfmmlvlp30OhyAMCrEF6ARmA2m3TzkA6SpA+W7pOXDeoDAEMRXoBGcs2AGAX6WrQjs1CLd2YbXQ4AeA3CC9BIQvx9dO2AWEnS099uUXml3eCKAMA7EF6ARnT/mPPUKshXu7IK9c7iPUaXAwBewe3CS1pamkaOHKn4+Hj16dNHn3/+udElAfUWGuijx3/TQ5L0yvydSs0pNrgiAPB8bhderFarXn75ZW3ZskU//fST7r//fhUVFRldFlBvE/pF6/wurVRWadefv95E510AaCC3Cy9t27ZVv379JEmRkZEKDw9Xbm6usUUBDWAymfTMFb3kazFr4Y7D+mHTIaNLAgCPVufwsmjRIl122WVq166dTCaTZs+eXWOf119/XR07dpS/v78SExO1ePHiehW3evVq2e12xcbG1ut4wF10at1CU0Z0kiS9OHe7Km103gWA+qpzeCkqKlLfvn312muvnfbzWbNmadq0aXrssce0bt06DR8+XOPHj1dqaqpzn8TERPXq1avGT3p6unOfnJwc3XzzzXr77bfPWk9ZWZny8/Or/QDu6M4RnRUe5Ks92UX6Yu0Bo8sBAI9lcjTgAbzJZNJXX32lCRMmOLcNGjRICQkJeuONN5zbevTooQkTJui5556r1XnLysp00UUX6Y477tCkSZPOuu+TTz6pp556qsb22iypDTS1GYv36K/fbVXbUH8t+ONI+ftYjC4JANxCfn6+QkNDa3X/dmmfl/Lycq1Zs0Zjx46ttn3s2LFaunRprc7hcDh0yy23aPTo0ecMLpL0yCOPKC8vz/mTlpZWr9qBpvDbwe3VLtRfGXml+ohFGwGgXlwaXrKzs2Wz2RQVFVVte1RUlA4dql0nxSVLlmjWrFmaPXu2+vXrp379+mnjxo1n3N/Pz08hISHVfgB35e9j0X1jukqSXv9ltwrL6rZo4+b0PKUfLWmM0gDAY1gb46Qmk6nae4fDUWPbmQwbNkx2O50Z4b0mJsTorYV7tCe7SE9/s1n/N7FPra6PNfuP6Jo3l8pqMetPF3fXrUM7yGw+cdz/1qerotKuiYkxjVk+ABjOpS0vERERslgsNVpZsrKyarTGAM2V1WLWMxN6yWySPlt9QP9ZkXrugyS9+vNO2R1SeaVdz3y7RTfOWK4DR6omvfto+X7d+8k6PfD5eu3KKmjM8gHAcC4NL76+vkpMTNS8efOqbZ83b56GDh3qyq8CPNr5XSL00MXdJUlPfbNZa/affS6jTQfz9Mv2wzKbqpYcCPCxaPmeXF388mI9/c0W/fnrTc59v9vAPDIAvFudw0thYaFSUlKUkpIiSdq7d69SUlKcQ6GnT5+uGTNm6N1339XWrVt1//33KzU1VVOmTHFp4adKTk5WfHy8kpKSGvV7AFf5/QWddGnvtqqwOXTHh2v0xNeb9NW6A8oqKK2xb/KCXZKky/q2031juur7+4YrIS5MhWWVenfJXjkcUtfIFpKkORszmvT3AICmVueh0r/88otGjRpVY/vkyZP1/vvvS6qapO6FF15QRkaGevXqpX/+85+64IILXFLwudRlqBVgtKKySk18Y6m2HTrxqCfQ16JXru+vMfFVj1p3Zhboon8ukiTNnXaBurUJliTZ7A69tWi3Xpm/U+N6ttETl/XUoL/9pAqbQz9NH6Eux8IMAHiCuty/GzTPizsivMDTFJdXat6WTK1Py9OSXdnanlkgk0l6ZHx3tfDz0TuL92hvdpHGxkfp7ZsH1Di+0maX1VLViHrreyu1YPthTb/oPN17Ydem/lUAoN4IL4QXeKgKm11/+XqzPllZvRNvaICPPvv9EGery5l8vjpND/53g7q3CdYP05qmtRMAXMGwSeoANIyPxay/XdlLj1/aQxazSbHhAXr80h5a/KdR5wwukjQ2vo18LCZtO1Sg57/fpl+2Z8lm96p/nwAALS+Au8ovrVCQr1UWc+3mSDrujg9Xa96WTOf7e0d30fSx3VxdHgC4FC0vgBcI8fepc3CRpL9f3VfPXtlLY3pUdfj9en26vOzfKACauUaZYReAcUIDfXTToPaa0C9a/Z+Zp/05xdqZVajOrVvo9QW7dKS4Qm1C/TS+V1vFhgcaXS4A1JnXhJfk5GQlJyfLZrMZXQrgFoL8rBreJULzt2Vp7qZDahsWoJfm7XB+/urPuzR/+ghFhvgbWCUA1J3XPDaaOnWqtmzZolWrVhldCuA2xvasenT0/aZDeu3nnZKk0d0j1SkiSAWllXru+21GlgcA9eI14QVATRf2iJLZJG3JyNe+nGK1DPTRqzf018vX95PJJH217qCW78kxukwAqBPCC+DFIlr4aUD7cOf724d3UpCfVX1iwnTjwDhJ0qR/r9CYfyzUWwt3G1UmANQJ4QXwcscfHYUG+OjmIe2d2x8c103d2wSrwubQrqxCvTB3u/KKK4wqEwBqjfACeLnrkmJ1VUK0Xrqmr4L9fZzbwwJ9Nefe4fr1T6PUuXWQbHaHFu48bGClAFA7hBfAywX7++gf1/ZzLvR4MrPZpJiWgc45YRZsy2rq8gCgzggvADSqe6QkaeGOwywnAMDteU14SU5OVnx8vJKSkowuBfA4ie1bKtjfqtyicq0/cNTocgDgrLwmvDDPC1B/PhazLjivtSQeHQFwf14TXgA0zKhuVY+O5mzMUKXNrs3pebr2rWX6eVvVIo/fbkjXc3O2qrzSbmSZAOA9ywMAaJgxPSIVGuCj3YeL9Mr8nfrf+nTtyynWjswCvXpDf037NEWVdoc6RATphmNzxACAEWh5ASCpauj045f2kCS98vMu7cspliQdLa7Q5HdXqvJYR953Fu+RnU69AAxEeAHgdHVijIZ3jZAkmUzS45f2kNkk2R1SWKCPgv2t2nO4SPPpFwPAQIQXAE4mk0nPT+yjgR3D9fil8bp9eCfdd+F5sppNeu7K3rppUNUMvW8t3C2Hg9YXAMYwObzsb6D8/HyFhoYqLy9PISEhRpcDeIUKm10+FrMy80s1/IUFKq+061/X99MV/aKNLg2Al6jL/ZuWFwDn5GOp+qsiKsRffxjVRZL0zLdbWQsJgCEILwDq5M4RndS5dZCyC8v0z592GF0OgGbIa8ILM+wCTcPPatETl/WUJH2+Ok2FZZUGVwSgufGa8MIMu0DTGd41Qp1bB6mo3Kav1h1UVn6psgpKjS4LQDPhNeEFQNMxmUzOkUevzt+p4S8s0PnP/6wn/7dZeSX0gwHQuAgvAOplYkKM/H3MyiooU1mlXRU2h95fuk93fLCalakBNCrCC4B6CQ300Z3DO8nPataD47pp5m0D1cLPqpX7cjX53ZXq+9SPevJ/m40uE4AXYp4XAPXmcDhksztkPTaUeva6g5o2K8X5udVs0vJHL1RECz+DKgTgKZjnBUCTMJlMzuAiSRP6R+vukZ3VLzZMHVoFqtLu0Ox1Bw2sEIA3IrwAcKmHLu6u2VPP1+3DO0mSPludJofDoaW7s/Xsd1tUWmEzuEIAno7wAqBRXNa3nfysZu3ILNTjszfpxndW6J3Fe/XlWlpiADQM4QVAowgN8NENA+MkSf9ZkercvnxPjlElAfAShBcAjeYvv4nXi1f3UftWgYoKqeq0u3JvLitSA2gQrwkvLA8AuB+z2aRrBsRq4YOj9MsfR8nHYtKh/FKl5hYbXRoAD+Y14YXlAQD3FuBrUd+YMEnSij25xhYDwKN5TXgB4P4GdgyXJC3ZnW1wJQA8GeEFQJMZ3rW1JOnrlHS9s2iPwdUA8FSEFwBNZnCncE0Z0VmS9OycrZqzMcPgigB4IsILgCZjMpn08PjuuvOCqgnsHv1qozLzSw2uCoCnIbwAaHJ/HNtNvaJDdLS4Qv/4cYd+2JShy179VTszC4wuDYAHILwAaHK+VrMevriHJOnn7Vl6Zf4ubTyYp9d/2W1wZQA8AeEFgCGSOraUv49ZhwvKtCUjX5L0/aYMFZRWaPW+XE39eK0O5fFICUBNhBcAhvCzWjSwY6tq20or7PpuQ4Ze+GG7vtuQoeQFu2oct/twoUrKz7y449cpB7UlPd/l9QJwH4QXAIYZ3iXC+ToyuGr5gPeX7tOa1COSpG82pKu80u7cZ9nuHF340kI9/e3m055v8c7Duu/TFF3yyuJGrBqA0QgvAAwz/LwT4eXZK3vLajZp26EC2exVax8dLa7QL9uznPssOPb6TDP0Lt19YtHHCpv9tPsA8HyEFwCG6RYVrMv6ttP4Xm00unukLu7VxvmZn7Xqr6c/fbFBby3cLbvdoZS0o5Kk1Nzi04aT7IIy5+v0oyWNWzwAwxBeABjGZDLp1Rv6643fJspiNmnS4PbOz56+oqc6RgTpSHGFnvt+mya/t1Kr91W1uFTaHUo7zeKO2w6dGGq9P4fFHwFv5TXhhVWlAc83sGO4Lu7ZRgPat9QV/aI17/4L9PxVveXvY9bindk69jRJkjQ7JV2Ldx52vq+02bU98+TwUtSUpQNoQiaHw+E4926eIz8/X6GhocrLy1NISIjR5QBwgW83pOuej9fV2G42ST9NH6FOrVtoR2aBxv5zkfOz24d11I2D4nSkuEKJ7Vs2ZbkA6qEu92+vaXkB4L0u7d3WORrJ13riry27Q5q/taoT7/pj/WGO25dTrBveWa6Jbyw97ZBrAJ6L8ALA7ZlMJn37h2F6cFw3PX5pj2qf/XfNAf24+ZAW7cyWJPWODpUkLdp5WJn5VR14X5y7vcbSAz9tydQ9H69VQWlFE/wGAFyJ8ALAI0SG+GvqqC7qExNWbfv2zALdOXONvlmfLkn67eA4Sao2P4wkrdp3RA6HQ8eflN/+4Wp9uyFDL/24o/GLB+BShBcAHqVPdKhuHBSnP13cXd2igmt8PqF/tKLDAmpsf/Srjer5xFwN+OtP1Trzbj/EYpCApyG8APAoZrNJf7uyt+4a2VkvXdtXj1/aQ0G+FklV88b4WS0a1/PEfDFjekQ5XxeX25RTVK6Zy/Y7t+WV8NgI8DSEFwAeq1d0qG4f3knf3jtcF/dso+cn9pakapPdHX+MdLLvNmY4X+/KKqzxiAmAeyO8APB4HSOC9OakRPWPqxoSndi+pYZ1idDQzq00vGtr536x4VWPkzJOWq263GbXjszTPzqatyVTe7OZLwZwN1ajCwAAV7OYTfro9kHO98k3JmjZnmxN6Betq99cVmP/Zbtz1OvYKKXj5m/N1B0frpaPxaSdz17S6DUDqD3CCwCvd2mftrq0T1uVlNuqbR/TI1I/bc3S95sydMcFnSRJT/5vswpKK+XnU9UwXWFzqNJml9VCQzXgLrgaATQbAcc69h73zIRekqS1qUe153ChcgrL9P7Sffpi7QGt2HNihep9rJMEuBXCC4BmZcqIzmrhZ9WXdw9V29AADeoYLkm69q3lWnZSYNl9+ERfl11ZDKcG3AnhBUCz8vD47lr3l4uUcKxz78vX91OHVoHKLizTyz/tPO0xOzMLm7JEAOdAeAHQ7Pic1H+lbWiArkuqGk69K+v0IWV7ZoHyiitks1f1fwFgLMILgGZvVPfWp90+rmfVBHffbshQ36d/VOdH52jAsz8pt6i8KcsDcArCC4Bmr1tUsHMOmON6tA3Rc1f1kdlUfd+jxRU1VrAG0LQYKg2g2TOZTHp3cpK+TklXZIiffjuovWwOh3wsZgX4WFR0yhDrxTuz1Ss6VK2D/QyqGGjevKblJTk5WfHx8UpKSjK6FAAeqGtUsP44rptuHtJBZrPJ2S/m5FWsj6+h9O6SvRr38qIa5zhSVK4fNx+Sze5okpqB5sprwsvUqVO1ZcsWrVq1yuhSAHiRF67uo9HdI/XV3UM1ZURn5/bconJV2Ox64utNGvfPRSoordDd/1mrO2eu0XtL9hpYMeD9vCa8AEBjiA0P1Lu3JKl/XEu1CfWv9llqbrE+WLZf2zMLNH9rlnOemH//SngBGhPhBQBqqV1Y9U69n6xIdb4uLKt0vj4+GumRLzfq/Od/VkZeSdMUCDQThBcAqKVTW15mnNTCsu+k1afLKu0qLKvUJytTdfBoiV6ed/rJ7wDUD+EFAGqp7Snh5WRrUo9Ue//VuoPO1z9tzZTDQSdewFUILwBQS4G+Vj1zRc9qc79EHhsuvS71aLV9v1mf7nydU1Su/NJKAXANwgsA1MGkIR10TWKs8/2bkxJPu9+6U1piVu3N1dpTtp3JrzuzNWdjRv2LBLwck9QBQB1dPzBWs1anaXjXCHVsFXTafSps1R8T3f7haknSxIQY7c8p0hu/TTztJHcOh0O//fcKSdKyR0arbWhAjX2A5o6WFwCoo/5xLTX/gRF6a1KiWgb5qmPE6QOMJEW08K32/ou1B7R6/xH9sOn0LSv5JTVHLQGojvACAPXQuXULBfpWNV73jwtzbj+/S6tq+/WLbXna4//89WZtPJBXY3tOUZnzdWkFK1gDp0N4AYAGSuoQ7nydEHcirPhZzerRNviMx900Y7kKSis0d/MhVdqqgsrJrS35pRWNUC3g+ejzAgANdO2AWGUcLdHAjq20PbPAub1tqH+NuWFOll9aqZtmrNCGA3m6YWCsnruqT7XwUsAIJeC0aHkBgAaymE2aPrabhnWNUGiAj3N729AAXdg9Sv3jwhQbHqCEuDA9fUVPXdyzjXOfDcceHX2yMk02u+OU8ELLC3A6tLwAgAuFnRRe+sSEqk2ov766+/xq+9w8pIOy8kt1wYsLqvVrWZd6RDmntLwUlFboaHGFYsMDG794wEPQ8gIALhQWeCK8DOwYfsb9IkP8Fd82pNq2q99cpvlbM53v80sqNPndlRr+wgLtPlzo+mIBD0V4AQAXCvI70aA9oP2Zw4skRQbX7A+z9qSZeg/llTrff8+kdYATj40AwIW6RQXr4p5t1D4iUKEntcKcTgv/s/8V/PP2LOfrskqGTQPH0fICAC5kNpv05qREPTK+xzn3vfOCTpKkS3q30Ss39K/x+dHiEx129+cUV/vsSFE5iz2i2SK8AIBBzosK1srHLtS/ru+vNiFnHlItSftzipyvl+zKVv9n5unvP25v7BIBt0R4AQADRQb7y8dirhZeTKaa+6XmFstud+iHTYd004yqtY+SF+xuqjIBt0J4AQA3EBlyYpHGMT2iqs0XI0lHiit036wUTfloTbXtxeWV+mFThsoqbU1SJ+AOCC8A4Ab8fSzqGtlCknTfhV2VcGy9JJNJ8vep+qv6m/XpNY5799e9mvLRWt30zoomqxUwmsnhZT2+8vPzFRoaqry8PIWEhJz7AABwE5n5pSoorVSXyBbal12kH7cc0pgeUbpz5hrtyjr3PC+rHx+jD5fuU3y7UI3rGSXT6Z4/AW6qLvdvhkoDgJuICvFX1LG/sztEBOnOCzpLkvbUcoK6l3/aoY+Wp0qSgv2tevWG/jq/S4Tmb83UwI6tFB7k2yh1A02Nx0YA4OauHxhXY1tEi5pB5HhwkaqWFrjlvVV6a+FuTflorW55b2Wj1gg0Ja8JL8nJyYqPj1dSUpLRpQCASz04tpv+b2JvLXl4tAJ9LRrYIVy3DetUq2PfW7JP0okFIAFvQJ8XAPAgeSUVCvCxyMdi0k0zVmjp7pxaH7vv+UsbsTKgYepy//aalhcAaA5CA3zkazXLZDLpuqRY5/aR3Vrrzd8mGlgZ0HTosAsAHios8ES/l6cu76n2rYIU4m9VfmnlGY8pr7TL18q/W+HZ+D8YADxUi5NWsA72r5rUzmw+8/DoTQfzFP+XH9Tjzz9UG8G0ZFe2xv5zoVbty5Uk2exVvQme+36r3lm0pzFKBxqE8AIAHsrvpBaU4GMrVOeXnFjM0XJKkPnNq7+q0u5QSYVNo19aqJV7c1VcXqmbZqzQjsxCTfs0RU9/s0X9nv5Rczcf0lsL9+jZOVtZABJuh8dGAOChurcJVt/YMEUG+8nHUhVk7CfljB/uG64lu7L15DdbTnv8tW8tU/9jM/lKUmmFTe8u2StJuufjtc7t5Ta7/KwW1/8CQD0RXgDAQ1ktZs2+e+gZZ9LtGhWsrlHBZwwvkrQu9ajzdU5RufN1he1ECiqtILzAvfDYCAA82KnBxXrsUdGwLhHObTNvG9ig7yitYNFHuBfCCwB4kc+mDNGEfu30j2v7OrcN79paix8apcGdwut1zpJywgvcC+EFALxIQlxLvXx9f0WG+FfbHhseqE/vHKI7L+ik7m2CtfihUc7POkUEnfWcD3y+ntYXuBXCCwA0I49e0kM/TLtA0WEBzm39YsPOesya/Uf071/3NnJlQO0RXgCgGTKbTbqiXzt1iwquNlPvmbw4d7uyC8uaoDLg3BhtBADN1L+u7y+Hw6E92UXObf+5fZAOHinRQ19sqLH/M99u0VUJMRpxXuumLBOogZYXAGjGTCaTc4I7SeoTE6qIYN/T7vt1Sromv7tSK/bUfjFIoDHQ8gIAzVxksL8eGd9dYYE+Cvb3UesW/mfd/7PVB7Qm9YjGxrdRl8gWTVQlcALhBQCg34/o7Hx9ppaX475Ye0CS9M36DH1/3/BGrQs4HR4bAQCqaRXkV6v9tmbkq8eff9Ckf69QWaVNecUVWrP/CGshodERXgAA1fhazfrTxd11dWKMhnZupav6R59x35IKmxbvzNaqvUf06OyNmvjGUv1z3g5V2uyatSpVabnFTVg5mgseGwEAarhr5InHSJn5pfpy3cGz7l9WadN3GzIkSa/8vEv+vha98MN2RYcFaMnDo1VcXimzySR/H9ZIQsPR8gIAOKvIYD9dnRij688yH8zx4HLcm7/sliQdPFqi0gqbEp/5SSNeXMAjJbgELS8AgLMymUz6+zVVayUt3HFYGXmlNfY5tWUmv7TS+XpfTpFKKmwqqbBp3pZMje3ZpnELhtej5QUAUGs/TR+hNY+Pcb73tZ77NpKWW+J8fefMNcoqqBl+gLogvAAAai3Iz6pWLU6MRhrY4dwrVd/x4epq7zen57u8LjQvPDYCANTZF3cN1d7sIvWKDtHFLy+u07EHGIGEBqLlBQBQZ4ntW+rqxBh1bxOi24d1rNOxBWWVWrM/V9e8uVQbD+Q1UoXwZoQXAECDlNvsddq/qKxSN7y9Qqv2HdGkd1c0UlXwZoQXAECDtG8V5Hx9Se/qI4nG9YyqsX9Rmc0ZeI4WV0iSCkor9N2GDJWU2xqxUngL+rwAABrkpkFxOnikRGN6RGpolwjZ7A794ZO1at3CT93ahGju5sxq+7+/dF+195U2u+77NEU/b8vSdQNi9X9X92nC6uGJaHkBADSIv49Ff7ksXkO7REiSLGaTXr8pUU9d0UttQs+9TtKvu7L187YsSdKs1WmSJIfDoa0Z+aqs4yMpNA+EFwBAo4kK8T/nPre8t6rGtg+X7df4fy3WU99saYyy4OEILwCARtOzXagevaR7nY4pLq/UE//bLEmauXx/Y5QFD0d4AQA0qjsv6KxrB8TUev/4v8xtxGrgDeiwCwBodI9e0kN2h3R1Yoz6xITqwf9uqLGY45lsP1SgmJYBCvLjloUqJoeXLfGZn5+v0NBQ5eXlKSQkxOhyAABn0OuJuSosqzz3jpK6RQXrh2nD9cuOw+rZLkSRwefuSwPPUpf7N4+NAACG+NPF3Wq97/bMAs1OOahb31ul295ffe4D4NUILwAAQ/x2cHstenCUgmv5OOj+WeslSRsP5qmgtKIxS4ObI7wAAAxhMpkU1ypQH90+SMO6ROiNmxJqfeyIF3+RJC3dla3covJGqhDuyu3CS0FBgZKSktSvXz/17t1b77zzjtElAQAaUd/YMH10+yCN6h7p3NbmHPPD5BaVa9W+XN04Y4UG/HWevKz7Js7B7bpuBwYGauHChQoMDFRxcbF69eqlq666Sq1atTK6NABAI/Kznvj3dFigjw7ll551/0U7DkuS7A5pT3aROrduIalqdl6TydR4hcJwbhdeLBaLAgMDJUmlpaWy2WwkagBoBk4OHC1q0Q/m1Z93OV9f+spi3Xp+R+3PKdLWjAJ9f99w+ftYGqVOGK/Oj40WLVqkyy67TO3atZPJZNLs2bNr7PP666+rY8eO8vf3V2JiohYvXlyn7zh69Kj69u2rmJgYPfTQQ4qIiKhrmQAAD3TXyM6SpGljztOD42o/Gqm0wq43ftmtORsPaW92kTYcyGusEuEG6hxeioqK1LdvX7322mun/XzWrFmaNm2aHnvsMa1bt07Dhw/X+PHjlZqa6twnMTFRvXr1qvGTnp4uSQoLC9P69eu1d+9effzxx8rMzDztd0lSWVmZ8vPzq/0AADzTg2O7adVjYzSsa4SmjupS7/OYeWrk1Ro0SZ3JZNJXX32lCRMmOLcNGjRICQkJeuONN5zbevTooQkTJui5556r83fcddddGj16tK655prTfv7kk0/qqaeeqrGdSeoAwPNtTs/T67/srvVsvMe9f2uSRnaLPPeOcBuGTVJXXl6uNWvWaOzYsdW2jx07VkuXLq3VOTIzM52tJ/n5+Vq0aJG6dTtz0+EjjzyivLw8509aWlr9fwEAgFvp2S5UyTfWfgj1cZ+tTtPBoyXVth0tLtflr/2q5AW7znAUPIVLO+xmZ2fLZrMpKiqq2vaoqCgdOnSoVuc4cOCAbrvtNjkcDjkcDt1zzz3q06fPGff38/OTn59fg+oGAHiXORsPKbeoXB/+bpDmbMxQkJ9VS3dna8OBPG04kKe7RnSWmWdLHqtRRhudOkStLsPWEhMTlZKS0ghVAQA8VVx4oFJzi+VrNau80l6rY5bvydV5j3/vfH9yVnnxx+36w+guyi+pVJtQ1knyNC59bBQRESGLxVKjlSUrK6tGawwAALU1Y/IAjTivtT69c7AS27es1znsJ/XwfOOX3frNK79q8HPzlZZb7KIq0VRcGl58fX2VmJioefPmVds+b948DR061JVfBQBoRs6LCtYHvxuohLiWev2mBD0yvrsevaR7g865J7tIkvT9prp1Bobx6vzYqLCwULt2nejstHfvXqWkpCg8PFxxcXGaPn26Jk2apAEDBmjIkCF6++23lZqaqilTpri0cABA8xQV4q/fj6iaD2Z8r7Ya+fdfZLPXfzLT2evSdfBIiR65pAcT23mIOoeX1atXa9SoUc7306dPlyRNnjxZ77//vq677jrl5OTo6aefVkZGhnr16qU5c+aoffv2rqv6NJKTk5WcnCybzdao3wMAcB+x4YH67t5huvjluk2GerItGfnakpGvdmEBzlAE99ageV7cUV3GiQMAvEOHh79zyXn+b2JvfbwiVc9P7KMebbmHNCXD5nkBAMCT/emLjVp/IE9/+GSd0aXgLAgvAACv9cBF51V736l1UK2OyzrHitYwFuEFAODxOkXUDCWrHhujP1zYVV/efWK068SEmFqdL7+0UvmlFS6rD65FeAEAeLwPfjdQtwztoL9d2du5rWWgj6Sq0UnHRQbXfkb2Pk/+WGOJAbgHwgsAwOPFhgfqyct7qlubYOc2q6XqFhdw0vDnVi1863Te85//WRsOHHVJjXAdrwkvycnJio+PV1JSktGlAAAMkhAXphsHxVWbwC7Q90R4aRlYt/AiSZe/tkTHB+bmFVdo+Z4c2RswrwwajqHSAACv5nA41PGROZKkpQ+Plr+PRX/9bou+XHuw1ueIDQ/QsC6ttWJPjvZkF+lf1/fTFf2iG6vkZqku9+9GWZgRAAB3YTKZ9O4tA1RQWql2YQGSpJeu6aux8W005aM1kqRbz++g95bsO+M50nJL9MnKVOf77zceUqCvVb2iQ9Q2NKBR60dNhBcAgNcb3b364sAmk0ljekQ639f1GcTcLYf0w+ZDahnoo3V/GeuKElEHXtPnBQCAurBazOp4bIj1yG6t63Ts8bBzpLhqOPXOzAJ9tjpNDodDczZmKCXtqCtLxSloeQEANFv/u+d8rU/L0/ldWjm3dYwI0t5jK07XxrrUI7ry9aWSpD2Hi/Tmwt2SpEUPjlJkiJ9MJsnPyoKPrkR4AQA0W8H+PhrWNaLathZ+dbs1Hg8ukvTl2gPO1xe8uEABPha18LdqxSMXymw2NaxYOPHYCACAkwT5WfT+rfWbdsN0Sj4pqbDpcEGZSittLqgMx3lNeGGeFwBAQ8S0rBo1dHnfaI3sFnmOveumuJzw4kpe89ho6tSpmjp1qnOcOAAAdTF76vnacOCoRp5X/+BiPrXp5ZgSwotLeU3LCwAADRHRwk+ju0fV6JsSHVb7eVwy8k6/GnVJBeHFlQgvAACcxhd3DdVdIztr/gMj9MO04Q06V3ZBmbxsQntDEV4AADiNxPYt9aeLu8vfx6LubRq23MyNM1boD5+sc1FlILwAAFALL1/Xr0HHf7shwzWFgPACAEBtTOgfrSv7N2wxxrxjM/KejMdJdUd4AQCgHloH+9X5mAv/sVBSVWAprbBp5rJ9Gvi3+dp2KN/V5Xk1rxkqDQBAYwsL9HG+nnPvcC3bk6PUnCIltG+pG99Zcc7jswvL1P3P36u0wq4AH4tzFNJT/9uiT+4c3Gh1exvCCwAAtXTfhV21K6tQExNi1DrYT5f3bef87F/X99N9n6ac8xylFXZJ1YdPL9uTo89Wp+naAbEur9kbec1jI2bYBQA0trBAX828bZAmnKbvyxX9ovWbPm3rfe6H/rtBZSwjUCteE16mTp2qLVu2aNWqVUaXAgBopl64uk+Dji+rtJ92O516q/Oa8AIAgNECfa36afoFeuHqPtr17Pg6H19UVqnBf5uvDg9/p/05RZKkn7dlqu9TP+rHzYdcXa7HIrwAAOBCXSKDde2AWFktdb/F/uXrzTqUX7XEwIgXf9Gy3Tn63furlV9aqTtnrtGhk5YfOFxQJru9ebbImBxe1hZ1fGHGvLw8hYQ0bEZEAAAa4qPl+/X47E0uPefgTuEKDfDR3M2Z+k2ftnrtxgSXnt8odbl/0/ICAEAjuWlQnMvPuXxPruZuzpTUfGftJbwAANBITCaTXr8pQc9M6KVhXSKc2/92ZW+Xfs/BoyW69b2V+nVntkvP666Y5wUAgEZ0Se+q4dOTBreXJJWU2xTga9GjX2102Xc88uVGLdpxWAu2H9a+5y912XndFS0vAAA0oQBfi8vPmX60xOXndGeEFwAAPFhphU27sgqNLqNJEV4AADDAo5d0d76OCvFTh1aB9TrPhOQlrirJY9DnBQAAA9x5QWeN79VWby7crduHd1KAj0WDn5tf5/NsO1RQY9u+7CKt3JeriQkxsphNkqpm6TWZTA2u2x14TXhJTk5WcnKybDbWhQAAeIbY8EA9e2zkUfkZlgaoj5F//0WSVGlz6MZBcUpesEsfLN2nL+4aqtjw+rXwuBOveWzE2kYAAE/ma3XNLfnhLzY4X6/Zf0SS9OLc7coqKNMLc7e75DuM5jXhBQAASJ+uSnO+/nHLIVXYTrToVNpc17pjJMILAABuYu60C3TdgFj1jQl1yfkKSiv195NaWw4eG1K9+3BhtVDjaVjbCAAANzT8hZ+VllsVNgZ2DNfIbq31wg8Ne+zTLtRf/eLCNGfjIY3pEaUZkwe4olSXYG0jAAA83Me3D3a+vnVoB1lOGim09s8X1euc6XmlmrPxkCTpp62ZDSvQQIQXAADcUGx4oN64KUG3D+uocT3byHxSeAkP8nXJd5z88KWgtEL//nWvMvLcf7ZerxkqDQCAtxnfu63GH1sbyWx2/RwtHR+Zo8cu6aHY8AD94ZN1qrA59P7SvVr80GiXf5crEV4AAPAAllOyi8Vsks3e8G6rz87ZWu398X427ozHRgAAeIBTW17G9Ih0vo5pGdDU5RiK8AIAgAc4v0uEJMnXUnXrfnh8D13VP1o/PzBCv/5ptDPMnBxqvBVDpQEA8BC7sgoV0cJXYYE1O+w6HA5V2BzytZr1z3k79K/5O+v/Pc+Ol9XStO0bdbl/E14AAPBCn69O04P/3XDuHc8gooWf3r81Sb2iXTNh3rk0y3lekpOTFR8fr6SkJKNLAQDAcNcMiNXFPdvU+/jswjL95tVfXViR63hNeGFhRgAAqgvya/ig4u2HClxQiWt5TXgBAADVnTSvnT6fMqRe5xj38iJtOpinL9cekLv0NCG8AADgpU5eUiCpQ7j+dmXvep3nN6/+qumfrdfS3TmuKq1BCC8AAHipYV0jqr0ffsr7utqVVdig412F8AIAgJca17ONnrq8p+Y/MEKS5O9jcX4287aBdT6fTxMPnz4TlgcAAMBL+VrNmjy0g/O9v8+J8FGfILLx4FFJcQ0vrIHcI0IBAIBGd3LLi70enW8/WZmmA0eKXVlSvRBeAABoJk5ubenZNlTTLzqvzufYnJ7vypLqhfACAEAzsvTh0Zr/wAiFBvro7pGdq30WHXbuBR5/P3NNY5VWa/R5AQCgGWl3UkCxWsxK+ctFcjiq+sf4Wc2a9O+VWrbHPYZEnwktLwAANGNhgb5qGeSrID+rrBazPrlzsNElnRPhBQAAVNMr+uwLI2bklTRRJadHeAEAANV8cOtAPTiu2xk/v+fjdU1YTU2EFwAAUE2rFn6aOqrLGT9fl3qkCaupifACAABOa9GDozTj5gE1ttsNXp+R0UYAAOC04loFKq5VoNFl1EDLCwAAOKsnL4uv9v7K/tEGVVKF8AIAAM7qlvM7av0TY3XbsI6SpDah/obW4zXhJTk5WfHx8UpKSjK6FAAAvE5ogI+sZpMkyWZwpxevCS9Tp07Vli1btGrVKqNLAQDAKwX5WRUe5Ct/q7HxweRw1GNZSTeWn5+v0NBQ5eXlKSTk7JPsAAAA91CX+7fXtLwAAIDmgfACAAA8CuEFAAB4FMILAADwKIQXAADgUQgvAADAoxBeAACARyG8AAAAj0J4AQAAHoXwAgAAPArhBQAAeBTCCwAA8CiEFwAA4FEILwAAwKNYjS7A1RwOh6SqpbUBAIBnOH7fPn4fPxuvCy8FBQWSpNjYWIMrAQAAdVVQUKDQ0NCz7mNy1CbieBC73a709HQFBwfLZDIpKSlJq1atOudxtdkvPz9fsbGxSktLU0hIiKtK9gi1/XNsKk1Vj6u/xxXnq+856noc145ruNu1IzXf68fdrp3a7Nucrh2Hw6GCggK1a9dOZvPZe7V4XcuL2WxWTEyM873FYqnVf/Da7idJISEhXv8/0anq8ufTFJqqHld/jyvOV99z1PU4rh3XcLdrR2q+14+7XTt12be5XDvnanE5zus77E6dOtWl+zVX7vbn01T1uPp7XHG++p6jrsdx7biGO/75NNfrx92unfqcG1W87rFRY8rPz1doaKjy8vKaRQIGXIVrB6gfrp3T8/qWF1fy8/PTE088IT8/P6NLATwK1w5QP1w7p0fLCwAA8Ci0vAAAAI9CeAEAAB6F8AIAADwK4QUAAHgUwgsAAPAohBcX+fbbb9WtWzd17dpVM2bMMLocwGNceeWVatmypa6++mqjSwE8SlpamkaOHKn4+Hj16dNHn3/+udElNRmGSrtAZWWl4uPjtWDBAoWEhCghIUErVqxQeHi40aUBbm/BggUqLCzUBx98oP/+979GlwN4jIyMDGVmZqpfv37KyspSQkKCtm/frqCgIKNLa3S0vLjAypUr1bNnT0VHRys4OFiXXHKJ5s6da3RZgEcYNWqUgoODjS4D8Dht27ZVv379JEmRkZEKDw9Xbm6usUU1EcKLpEWLFumyyy5Tu3btZDKZNHv27Br7vP766+rYsaP8/f2VmJioxYsXOz9LT09XdHS0831MTIwOHjzYFKUDhmrotQM0Z668flavXi273a7Y2NhGrto9EF4kFRUVqW/fvnrttddO+/msWbM0bdo0PfbYY1q3bp2GDx+u8ePHKzU1VVLVMt6nMplMjVoz4A4aeu0AzZmrrp+cnBzdfPPNevvtt5uibPfgQDWSHF999VW1bQMHDnRMmTKl2rbu3bs7Hn74YYfD4XAsWbLEMWHCBOdn9957r+M///lPo9cKuJP6XDvHLViwwDFx4sTGLhFwW/W9fkpLSx3Dhw93fPjhh01Rptug5eUcysvLtWbNGo0dO7ba9rFjx2rp0qWSpIEDB2rTpk06ePCgCgoKNGfOHI0bN86IcgG3UZtrB8Dp1eb6cTgcuuWWWzR69GhNmjTJiDINYzW6AHeXnZ0tm82mqKioatujoqJ06NAhSZLVatVLL72kUaNGyW6366GHHlKrVq2MKBdwG7W5diRp3LhxWrt2rYqKihQTE6OvvvpKSUlJTV0u4FZqc/0sWbJEs2bNUp8+fZz9ZWbOnKnevXs3dblNjvBSS6f2YXE4HNW2XX755br88subuizA7Z3r2mFkHnBmZ7t+hg0bJrvdbkRZhuOx0TlERETIYrFU+5eiJGVlZdVIxABO4NoB6o/r5+wIL+fg6+urxMREzZs3r9r2efPmaejQoQZVBbg/rh2g/rh+zo7HRpIKCwu1a9cu5/u9e/cqJSVF4eHhiouL0/Tp0zVp0iQNGDBAQ4YM0dtvv63U1FRNmTLFwKoB43HtAPXH9dMAxg52cg8LFixwSKrxM3nyZOc+ycnJjvbt2zt8fX0dCQkJjoULFxpXMOAmuHaA+uP6qT/WNgIAAB6FPi8AAMCjEF4AAIBHIbwAAACPQngBAAAehfACAAA8CuEFAAB4FMILAADwKIQXAADgUQgvAADAoxBeAACARyG8AAAAj0J4AQAAHuX/AXiPByn6FzyxAAAAAElFTkSuQmCC", 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", 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" ] @@ -165,22 +165,22 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 31, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -216,7 +216,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -249,8 +249,8 @@ " \n", " \n", " 0\n", - " -3.49265\n", - " -0.295551\n", + " -3.43411\n", + " -0.28364\n", " fixed\n", " 0\n", " \n", @@ -260,16 +260,16 @@ ], "text/plain": [ " Offset Exponent fit_type ch_name\n", - "0 -3.49265 -0.295551 fixed 0" + "0 -3.43411 -0.28364 fixed 0" ] }, - "execution_count": 49, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -306,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -339,8 +339,8 @@ " \n", " \n", " 0\n", - " -1.330078\n", - " 0.980967\n", + " -1.254911\n", + " 1.002556\n", " fixed\n", " 0\n", " \n", @@ -350,16 +350,16 @@ ], "text/plain": [ " Offset Exponent fit_type ch_name\n", - "0 -1.330078 0.980967 fixed 0" + "0 -1.254911 1.002556 fixed 0" ] }, - "execution_count": 50, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -391,7 +391,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -424,8 +424,8 @@ " \n", " \n", " 0\n", - " 1.741269\n", - " 4.196593\n", + " 1.77126\n", + " 4.200501\n", " fixed\n", " 0\n", " \n", @@ -434,17 +434,17 @@ "" ], "text/plain": [ - " Offset Exponent fit_type ch_name\n", - "0 1.741269 4.196593 fixed 0" + " Offset Exponent fit_type ch_name\n", + "0 1.77126 4.200501 fixed 0" ] }, - "execution_count": 51, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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Hx2jSiGilj4xVWDC3ZwOBgvBCeAH8nt3uUHnDOb1ZXKHXd7mujC1dmCxvzo3DdOfEBE1OjtXYYVGEGcCPEV4IL0BAaeu06a8HavXJybM6WNWk/ZWNqmt2DTPmIJNS4yI1PCZcw2O/eMSEa3xitGaMjZPJxEzAgC/z6/BSUVGhJUuWqLa2VsHBwfrRj36kBx54oNfvJ7wAgc9ud2h/pVXvH6jR9iN1OlTTpKbWnsfTpI2I0T9l3aDZ4+I1ODK0HysF0Ft+HV6qqqpUU1OjqVOnqra2VtOmTdOhQ4cUFRXVq/cTXoCBx+FwqNraqvL6c6q2tqqqsVXVja2qajyvbZ/X6Vy7zbnv0KhQzbxhqJbMGKWbx9AjA/gKd36/g/uppl4bMWKERowYIUlKSEhQXFycGhoaeh1eAAw8JpNJI2IjNCI2osu2My3t+vWHx/XmnpM6dfa86lva9c6nVXrn0yqlxkXqS6mDNSV5sKYkx+qmpBhFhvrcn0UAV3D7vsOioiItWLBASUlJMplM2rBhQ5d9CgoKNGbMGIWHh8tisWjbtm3XVdyePXtkt9uVkpJyXe8HgCFRoVp+13htf+JO7V8xT3/49iz9n5tTFBFiVnnDOb1dUqkfv1OqB37xoSY//Z6+9vKHKthyRKWVVvlYxzSAL7j9T4yWlhZlZGTooYce0qJFi7psX7dunZYvX66CggLdeuutevnll5WTk6PS0lKlpqZKkiwWi9ra2rq897333lNSUpIkqb6+Xt/4xjf0yiuvXLWetrY2l8+yWq3ufiUAA0RUWLAso4bIMmqInpw/SR+fOKN9Jxv16alGfXryrGqsbdpV1qBdZQ16/i+HFBsRInOQScMGhemnD0zRlOTBRn8FAOrjmBeTyaT169dr4cKFzrZbbrlF06ZN0+rVq51tkyZN0sKFC7Vy5cpefW5bW5vuvvtuffOb39SSJUuuuu/TTz+tFStWdGlnzAsAd5XXn9PWw7Xacui0dhyt1/mOS2NlhkWH6eUlFr1VfFIOh/TD+RMVHc7Ck4Cn9NuA3SvDS3t7uyIjI/Xmm2/q/vvvd+733e9+VyUlJdq6des1P9PhcOjrX/+6JkyYoKeffvqa+3fX85KSkkJ4AdAnrR02ldW1yOGQ8t4oca7VdNHYYVEq+LtpmjicvzOAJ7gTXjw613ZdXZ1sNpsSExNd2hMTE1VdXd2rz9i+fbvWrVunDRs2aOrUqZo6dar27dvX4/5hYWGKiYnRa6+9phkzZmju3Ll9+g4AIEnhIWZNGhGjtKQY/fLBTMUPCpMkfSl1sIbHhOvY6Rbl/HybvvWbPao8e97gaoGBxSvD6q+89dDhcPT6dsTZs2fLbrdfe8cr5ObmKjc315ncAMBTRg6O0Dvfma1jdc2aOXao6prb9aMNn+kv+6v1XmmN6prb9NayWQoK4rZroD94NLzEx8fLbDZ36WWpra3t0hvjafn5+crPz5fNZrv2zgDgpouz9koXxr/8YolFB6utWlSwQx+Xn9XqrUd19ly7YiNC9I1ZozUoNFifnmrUrrJ6zbtpuEYNZboHwFO8MmDXYrGooKDA2ZaWlqYvf/nLvR6w2xdMUgegP72y7Zh+8u4Bl7bIULNsdodzYcmbkmL0zndmMyEecBVeHfPS3NyskpISlZSUSJLKyspUUlKi8vJySVJeXp5eeeUVvfrqqzpw4IAee+wxlZeXa9myZe5/EwDwcQ/OGq30kRf+0E5LHaxxCYN0rt2mtk67okLNCg0O0v5Kqz44Uud8T3unXcdON6vT5v4lcgDX0fOyZcsWZWVldWlfunSp1q5dK+nCJHXPP/+8qqqqlJ6erhdffFG33XabRwruyeWXjQ4fPkzPC4B+Y23t0Im6c0ofGSO7QzpQZVVsRIiGx4br2XcPaO2O48pIjtWMsUP1WWWj9paf1bl2m0YNjdTj2RO0IOPC/Fa/++iEqhtblTUxQdNShxj8rYD+5ddrG/UVl40A+JKTZ87p9p9ukc3u+qc2yCRdbPqHW8fovqlJWpi/3bn9AUuybh4TpxljhyolLrI/SwYMQXghvADwIf+v6JjeK63WhOHRSk+K1ZTkwUodGqnVW44of/NRSVL8oFDVNbdLkkwm6eJf5uEx4dr43TmKi2I1bAS2ARleuGwEwB+9vqtcT/zPpbms1v/TLJ3vsOnVD45r36kLSxbcMiZOX5k2UpsPntZHZfUyB5k0LXWI5t00XLeNH6Zh0WEGfgPAMwZkeLmInhcA/sThcOi7r5foj59UKiM5Vm//82znttJKqxYWbFd7Z88DeyNCzPqX7PFaOmu0Tp05r/cP1KisrkVPzp+kQWGskA3/QXghvADwIy1tnfrNhyeUfVOibhg2yGXbZ6catabomMobzmn2uHjNnZQgSSosrdH/HqztsmzBRblZN+h78yZ6vXbAUwgvhBcAA4DD4dDLRcf0H38+2GVbRIhZG787R8NjwhURalZ7p12v7Twhk6SHbh3NnDPwOe78fgdMnyIz7AIYaEwmk5bdfoPiIkN1oqFFy26/QVGhwfrqLy7M+pv1sy2SpCGRITIHmZwDgieOiNasG+INrBzoG3peACDA1Fpb9Q+/3q3PTlm73Z4+MkZLZoxSa4ddHx6t1zdvGyPLqLh+rhJwxWUjwguAAc7hcKiqsVWDwoNVUn5WZ893aGx8lO5b9YHs3fzVHz00Uj/6mzQNjgzVD/7wqb4790bn5HlAfyC8EF4AoFvvflqlf//jfjW0tHUbYi73/Fen6P4vjVSI2e2VZAC3DcjwwjwvANA7drtDQUEmNbV2qPF8h97Yc1K7yxr04bH6LvsOjQrVHRMSNG3UYI0cHKE7JiQYUDEGggEZXi6i5wUA3Ndps+u5jQd19ly7bp8wTNuP1Ol/D9Y6B/le9G9/k6a5kxK0+/gZzbphqJIGRxhUMQIN4YXwAgB91t5p1+7jDfrJuwd0oKrr4N85N8brpcVTFRsRomAuLaGPCC+EFwDwmE6bXb/+8IR+/E5pl23mIJNsdoduGz9MP/vqFCXEhKvDZmecDNxGeCG8AIBH2e0O/fajExo3bJDio8P09f+3s8slpUFhwbprUoLe/qRSL35tquZPHiFzkEnmICbEw7URXggvAOBV3319r94uqZQk5aQP19bDp3Wu3XWS0EFhwYoMNeuVpdM1eWQss/riqgZkeOFuIwDoP7VNrdr0WbVm3zhMY+Kj1NLWqek/eV/nO7qf5fzvZ6QqMTpc89KHK2lwBItGoosBGV4uoucFAIzxvwdr9PCv9yjUHKSJw6P1ycnGbvcLMkn/uWiKHpie0s8VwpcRXggvAGCIwzVNGhoVqqGDwvRx+Rn97cs71W6zd7tvdlqivjY9RXelJfZzlfBFhBfCCwD4BIfDocbzHVq/95RW/Knr3UqSNCExWuMSBin/76b1c3XwJQNyVWkAgO8xmUwaHBmqh24do8zRcXp+0yEVHT7tss+hmiYdqmmS5YMyRYaatTgzhcG9uCp6XgAA/eq1D4/rR2/vv+o+v1w6XXMnJarG2qrmtk7dMGxQP1UHo3DZiPACAD6r02bX7uNnFBVm1sL87T0uEDlqaKRO1J+TJO144k6WIghwXDYCAPisYHOQZt4wVJL0ft7tqmtu1+7jDdpbflZTU2L1s/cOS5IzuEjSaztP6Af3TDSkXviegAkvl8/zAgDwD2OHDdLYYdLNY+KcbUMHhWn93lPaVdbgbFu95aj2HG/QyMER+vHCdP1w/We6a1KCvjx1pBFlw2BcNgIA+ByHw6Gvvfyhdh8/c9X9Jo+M1ZvLZio8xNxPlcFb3Pn9ZuUsAIDPMZlM+v03Z6joe1n6u1tSe9xv36lGbdxXpU9PnlWA/VscVxEwl40AAIEl2Byk1KGR+vYdN+h8u033Txupj441aNXmIy775b3xifP5z/92KpeSBgAuGwEA/EpFw4WBvP/yxifadbyh230++uFcJcaE92dZ6CMuGwEAAlZKXKRS4iL1xrKZ+uAHWRqX0HUOmId+tVt1zW1cSgpQhBcAgN9KHhKpV74xvUt7aZVV03/yvv7jzwcNqAreRngBAPi10fFR+qc7btCQyJAu214uOqaWtk7Ze5oJD37J58a8NDU16c4771RHR4dsNpseffRRffOb3+z1+xnzAgADl93u0PRn31dDS7uzzWSSxsRH6fbxw/SDeyZyW7WP8usZdiMjI7V161ZFRkbq3LlzSk9P11e+8hUNHTrU6NIAAD4uKMikuyYl6I09J51tDod07HSLjp1ukdlk0r/+TZqBFcITfO6ykdlsVmRkpCSptbVVNpuNAVcAgF77zp036tt33NDttt0nrj7pHfyD2+GlqKhICxYsUFJSkkwmkzZs2NBln4KCAo0ZM0bh4eGyWCzatm2bW8c4e/asMjIylJycrO9///uKj493t0wAwACVEhepH9wzsdvJ7cpON+t8O8vI+Du3w0tLS4syMjK0atWqbrevW7dOy5cv11NPPaW9e/dqzpw5ysnJUXl5uXMfi8Wi9PT0Lo/KykpJ0uDBg/XJJ5+orKxM//3f/62ampoe62lra5PVanV5AACw4r6butyJZG3t1LQfF6qwtOffFfi+Pg3YNZlMWr9+vRYuXOhsu+WWWzRt2jStXr3a2TZp0iQtXLhQK1eudPsY3/72t3XnnXfqgQce6Hb7008/rRUrVnRpZ8AuAECSJv7oz2rtsLu0DY4MUfG/3i1zkMmgqnAlwyapa29vV3FxsbKzs13as7OztWPHjl59Rk1NjbP3xGq1qqioSBMmTOhx/yeffFKNjY3OR0VFxfV/AQBAwPn+vImKCDFraFSos+3suQ798H/2qbap1cDKcL08Gl7q6upks9mUmJjo0p6YmKjq6upefcbJkyd12223KSMjQ7Nnz9Y///M/a8qUKT3uHxYWppiYGL322muaMWOG5s6d26fvAAAILP8we4z2PZ2tp++7yaV93Z4K3fzsX3WuvdOgynC9vHKrtMnk2g3ncDi6tPXEYrGopKTE7WPm5uYqNzfX2e0EAMBFweYg3Tt5hELMJi377ccu277xy11669uzDKoM18OjPS/x8fEym81dellqa2u79MYAANCfgoJMuid9RJf2PSfOuExqB9/n0fASGhoqi8WiwsJCl/bCwkLNmuXdVJufn6+0tDRlZmZ69TgAgMARFnzhZ/ChtbvV0sblI3/hdnhpbm5WSUmJ89JOWVmZSkpKnLdC5+Xl6ZVXXtGrr76qAwcO6LHHHlN5ebmWLVvm0cKvlJubq9LSUu3evdurxwEA+LeCv5um6PBg/erBTN08Jk6S9EnFWf3k3VKDK0NvuT3mZc+ePcrKynK+zsvLkyQtXbpUa9eu1eLFi1VfX69nnnlGVVVVSk9P18aNGzVq1CjPVd2N/Px85efny2Zj8iEAQM/mTx6hnPThMplM+tMnlc72zQdPG1gV3OFzCzP2FQszAgB668Ff7dKWQxdCS1xUqFb/3TR9KXWIQoN9bvWcgGfYPC8AAPiT+ZMvDeBtaGnX4jU79cP1+wysCL3hc6tKXy8uGwEA3PWVL41UTHiIlv222Nn2VvFJ2ewOTRoRrW/d1v0CjzAWl40AAAPelkO1evBXXW/4KH1mniJDA+bf+T6Ny0YAALjhjgkJ2vb9rC7t9c3M/+KLCC8AAEhKiYvUi4szXNrqmtsMqgZXEzDhhUnqAAB9dcf4BJfXT/9xvzbsPWVQNegJY14AALjM6Cfe7dL2wtcy9JVpyQZUM3Aw5gUAgOuUNWFYl7a8Nz4xoBL0hPACAMBlnvvKZM0cO7RL+4o/7VeAXazwWwETXhjzAgDwhBGxEfr9t2ao8LHbXNp/tf24Dtc0G1QVLhcw4YWFGQEAnnRjYrR+8fcWl7ZPTp41phi4CJjwAgCAp92TPtzl9emmNu2vbNTLW4+qw2Y3qCowbSAAAL10uqlN9/7fDyRJkaFmLZk52tiCBih6XgAA6KWjpy+NeWH8i3EILwAA9NK2z+ucz6PCuHhhlIAJL9xtBADwhmmpg7ttHxRm7t9C4MQMuwAAXMWZlnYVfX5aHx6t1+u7K5zteXeP16NzbzSwssDizu83fV4AAFzFkKhQfXnqSFU3trq0n2u3GVQRAuayEQAA3hQa7PqT+YutR/V5TZNB1QxshBcAAK7To6+XGF3CgER4AQCgF7obIVp59nz/FwLCCwAAvWHvJr00nu9QbVNrN3vDmwgvAAD0Qk/35j61/rP+LQSBE16Y5wUA4E0OdZ9eig6f7udKEDDhhVWlAQDeFGQyddvebrOrrZPbpvtTwIQXAAC86WuZKUqNi9TQqFBnW3hIkBwOqbz+nIGVDTyEFwAAeiEmPERbv3eH3s+7XREhZmWOHqLWDrsk6du/+9jg6gYWwgsAAL1kMpk0JCpUu//1Lr3+rZnO9iO1rDDdnwgvAAC4aVBYsMxBJr3wtQxnW3un3cCKBhbCCwAA12nuxETn86+9/KGBlQwshBcAAK5TWMiln9GSirPGFTLA+Gx4OXfunEaNGqXHH3/c6FIAAOhW2BWLNTa3dRpUycDis+Hl2Wef1S233GJ0GQAA9Mh0xdwvWw7VGlTJwOKT4eXzzz/XwYMHNX/+fKNLAQCg12qtbUaXMCC4HV6Kioq0YMECJSUlyWQyacOGDV32KSgo0JgxYxQeHi6LxaJt27a5dYzHH39cK1eudLc0AAAMVd9CeOkPboeXlpYWZWRkaNWqVd1uX7dunZYvX66nnnpKe/fu1Zw5c5STk6Py8nLnPhaLRenp6V0elZWVevvttzV+/HiNHz/++r8VAAAGaGhpN7qEASHY3Tfk5OQoJyenx+0vvPCCHn74YT3yyCOSpJdeekmbNm3S6tWrnb0pxcXFPb5/586dev311/Xmm2+qublZHR0diomJ0b/92791u39bW5va2i4lXavV6u5XAgDAI8obzumPn1QqOy1R4SFmo8sJWB4d89Le3q7i4mJlZ2e7tGdnZ2vHjh29+oyVK1eqoqJCx48f189+9jN985vf7DG4XNw/NjbW+UhJSenTdwAAwB0/uGei8/n2I/V69Pd7tXrLUQMrCnweDS91dXWy2WxKTEx0aU9MTFR1dbUnD+X05JNPqrGx0fmoqKjwynEAAOjOstvH6tn7013aNu33zm8eLnD7slFvXHnrmMPh6NLWGw8++OA19wkLC1NYWJjy8/OVn58vm41lyQEA/cdkMmnYoDCXthGx4QZVMzB4tOclPj5eZrO5Sy9LbW1tl94YT8vNzVVpaal2797t1eMAAHCljJTBLq+HE168yqPhJTQ0VBaLRYWFhS7thYWFmjVrlicP1UV+fr7S0tKUmZnp1eMAAHClxBjXsGJnjUavcvuyUXNzs44cOeJ8XVZWppKSEsXFxSk1NVV5eXlasmSJpk+frpkzZ2rNmjUqLy/XsmXLPFr4lXJzc5Wbmyur1arY2FivHgsAgCslD4nQyTPnJUnnOxjC4E1uh5c9e/YoKyvL+TovL0+StHTpUq1du1aLFy9WfX29nnnmGVVVVSk9PV0bN27UqFGjPFc1AAA+Zs2S6Zr/fy9MynrmHPO9eJPJ4XA4jC7CEy4fsHv48GE1NjYqJibG6LIAAAPIts9Pa8kvdyk8JEif/vs8hQb75Co8PunilZPe/H4HzH9VBuwCAIw2e1y8hkSGqLXDrs8qG40uJ2AFTHgBAMBoJpNJllFxkqSPT5wxuJrAFTDhhbuNAAC+IDUuUpL0k3cP6IPP6wyuJjAFTHjhshEAwBeca+90Pn9jD7O+e0PAhBcAAHxBW+elSV5iI0IMrCRwBUx44bIRAMAXXH4T77l25nvxhoAJL1w2AgD4gu/eNd75/HxH51X2xPUKmPACAIAvGBMfpecXTZEknag/Z3A1gYnwAgCAh0WHX5jAfn+lVTZ7QMwF61MILwAAeNiMsUOdz8+yVIDHBUx4YcAuAMBXDIkK1aCwC70v7+6rMriawBMwaxtd5M7aCAAAeMvoJ951Pv+vBzK0yJJsYDW+b0CubQQAgC8JMl16/oM/fGpcIQGI8AIAgBf88sFLwxiYrM6zCC8AAHjBsEFhzuf1LQza9aSACS8M2AUA+JLIULPL6y2Hag2qJPAETHhhhl0AgC8JC3ENL6/vYpFGTwmY8AIAgC8ZEuk6zsXa2mFQJYGH8AIAgBdEhgbrwVmjna9ZpNFzCC8AAHjJhOHRzudN9Lx4DOEFAAAvMZsuTfZy9HSLAmxeWMMQXgAA8BLbFWGFVaY9g/ACAICXpAyJdHld1dhqUCWBJWDCC/O8AAB8zewb4/XawzfL/MVaAdxx5BkBE16Y5wUA4Ivm3DhMt46LlyQ1tXYaXE1gCJjwAgCAr4oOD5bEHUeeQngBAMDLIr+Ybfd8B3O9eALhBQAALwsNvvBz295pN7iSwEB4AQDAywgvnkV4AQDAy0LNF35uO2yEF08gvAAA4GX0vHgW4QUAAC+72PPSTs+LR/hkeAkODtbUqVM1depUPfLII0aXAwBAn4R80fPy+10VBlcSGIKNLqA7gwcPVklJidFlAADgERd7XiTp05NnNSV5sHHFBACf7HkBACCQtF021mXT/moDKwkMboeXoqIiLViwQElJSTKZTNqwYUOXfQoKCjRmzBiFh4fLYrFo27Ztbh3DarXKYrFo9uzZ2rp1q7slAgDgUzJHD3E+z998VMUnGgysxv+5fdmopaVFGRkZeuihh7Ro0aIu29etW6fly5eroKBAt956q15++WXl5OSotLRUqampkiSLxaK2trYu733vvfeUlJSk48ePKykpSZ999pnuvfde7du3TzExMd3W09bW5vJZVqvV3a8EAIBXTR8dp9nj4vXBkTpJ0s5jDbKMijO4Kv/ldnjJyclRTk5Oj9tfeOEFPfzww86Bti+99JI2bdqk1atXa+XKlZKk4uLiqx4jKSlJkpSenq60tDQdPnxY06dP73bflStXasWKFe5+DQAA+tXw2HDn84urTOP6eHTMS3t7u4qLi5Wdne3Snp2drR07dvTqM86cOePsSTl58qRKS0s1duzYHvd/8skn1djY6HxUVDCSGwDg2xwOoyvwbx6926iurk42m02JiYku7YmJiaqu7t0ApQMHDugf//EfFRQUJJPJpJ///OeKi+u5ay0sLExhYWHKz89Xfn6+bDYWvQIA+J7LA0srCzT2iVdulTaZXLvDHA5Hl7aezJo1S/v27XP7mLm5ucrNzZXValVsbKzb7wcAwJvGJQxyPie89I1HLxvFx8fLbDZ36WWpra3t0hvjafn5+UpLS1NmZqZXjwMAwPV4ePYY5/PzhJc+8Wh4CQ0NlcViUWFhoUt7YWGhZs2a5clDdZGbm6vS0lLt3r3bq8cBAOB6hAYH6Qf3TJQknWsnvPSF25eNmpubdeTIEefrsrIylZSUKC4uTqmpqcrLy9OSJUs0ffp0zZw5U2vWrFF5ebmWLVvm0cIBAPA3ESEX+gzoeekbt8PLnj17lJWV5Xydl5cnSVq6dKnWrl2rxYsXq76+Xs8884yqqqqUnp6ujRs3atSoUZ6ruhsM2AUA+LqIULMkqZWelz4xORyBdcPWxQG7jY2NPU5sBwCAEd4uOaXvvl6imWOH6vffmmF0OT7Fnd9v1jYCAKCfRIZeuODBZaO+CZjwwt1GAABfFxHyxWUjwkufBEx44W4jAICviwi98LPL3UZ9EzDhBQAAXxcRwmUjTwiY8MJlIwCAr+NuI88ImPDCZSMAgK+7OOaFnpe+CZjwAgCAr7vY89Jpd6i9025wNf6L8AIAQD+52PMi0fvSF4QXAAD6SYjZJHOQSRK3S/dFwIQXBuwCAHydyWRSeDC3S/dVwIQXBuwCAPxByxehZU3RUYMr8V8BE14AAPAnv99VYXQJfovwAgAA/ArhBQCAfjQsOkySdO/kEQZX4r8CJrwwYBcA4A++NWesJKnTbteR2maDq/FPARNeGLALAPAHweYLt0pv2l+ju17YquITZwyuyP8ETHgBAMAf7LkirLy3v9qgSvwX4QUAgH704KzRLq9fLjqmo6e5fOQOwgsAAP0oc3Rcl7a5/7VVX3v5Q7V1MnFdbxBeAADwAbvKGrRxX5XRZfgFwgsAAP2s8LHbum3/6V8O9XMl/onwAgBAP7sxMbrb9srG1n6uxD8FTHhhnhcAgL+7Y8Iwo0vwCwETXpjnBQDgT55ekNaljZWmeydgwgsAAP7kwVvH6IMfZGnk4Ahnm/V8h4EV+Q/CCwAABkkeEqmf/+1U5+vapjbjivEjhBcAAAw0fXSc3vnObElSQ0u7ig6fNrgi30d4AQDAYDclxSgs+MJP8jde3aXffXTC4Ip8G+EFAACDmUwmJcaEO18/tf4zbWLNox4RXgAA8AGzb4x3ef2PrxUbVInvI7wAAOAD7stIMroEv+GT4aWsrExZWVlKS0vT5MmT1dLSYnRJAAB41eWXjXB1wUYX0J0HH3xQP/nJTzRnzhw1NDQoLCzM6JIAAPCqxBh+63rL53pe9u/fr5CQEM2ZM0eSFBcXp+Bgn8xYAAB4TGRosL5121ijy/ALboeXoqIiLViwQElJSTKZTNqwYUOXfQoKCjRmzBiFh4fLYrFo27Ztvf78zz//XIMGDdJ9992nadOm6bnnnnO3RAAA/NIP509yef2nTypVefa8QdX4Lre7NFpaWpSRkaGHHnpIixYt6rJ93bp1Wr58uQoKCnTrrbfq5ZdfVk5OjkpLS5WamipJslgsamvrOovge++9p46ODm3btk0lJSVKSEjQPffco8zMTN19993d1tPW1ubyWVar1d2vBACAz4gOD1ZTa6ck6Tu/3ytJOvrcfJmDTEaW5VNMDofDcd1vNpm0fv16LVy40Nl2yy23aNq0aVq9erWzbdKkSVq4cKFWrlx5zc/88MMPtWLFCv3lL3+RJP30pz+VJH3ve9/rdv+nn35aK1as6NLe2NiomJgYd74OAACGa+2waeKP/uLS9tz9k/X1W1INqqh/WK1WxcbG9ur326NjXtrb21VcXKzs7GyX9uzsbO3YsaNXn5GZmamamhqdOXNGdrtdRUVFmjRpUo/7P/nkk2psbHQ+Kioq+vQdAAAwUniIWV+bnuzSxpIBrjw6Eraurk42m02JiYku7YmJiaqu7t1MgcHBwXruued02223yeFwKDs7W3/zN3/T4/5hYWEKCwtTfn6+8vPzZbOxnDgAwL+NSxjk8trEFSMXXrmNx3TFf2WHw9Gl7WpycnKUk5Pj1jFzc3OVm5vr7HYCAMBfDY4IdXlNeHHl0ctG8fHxMpvNXXpZamtru/TGeFp+fr7S0tKUmZnp1eMAAOBtsZEhLq837qvWwvzt6rDZDarIt3g0vISGhspisaiwsNClvbCwULNmzfLkobrIzc1VaWmpdu/e7dXjAADgbbERIV3aSirO6rNTjQZU43vcvmzU3NysI0eOOF+XlZWppKREcXFxSk1NVV5enpYsWaLp06dr5syZWrNmjcrLy7Vs2TKPFg4AQKAaHNk1vEjS/QU7uG1a1xFe9uzZo6ysLOfrvLw8SdLSpUu1du1aLV68WPX19XrmmWdUVVWl9PR0bdy4UaNGjfJc1d1gwC4AIFBcOeblcvsrGzUleXD/FeOD+jTPiy9y5z5xAAB8UXdzvVz024dv0ewb4/u5Iu8zbJ4XAADQd+Eh5h63ne/gCkPAhBfuNgIABJLuBu1KUktbZz9X4nu4bAQAgA9qaGnXf/75oNbt6X7m+NV/N005k0f0c1Xew2UjAAD8XFxUqP5j0eQet3/7dx/3YzW+hfACAICPMplMmjsxwegyfE7AhBfGvAAAAtGPF6Yrc/QQrfr6l7pss9sDauRHrzHmBQAAPzH6iXddXpc+M0+RoV5ZprDfMeYFAIAB4NOTjSo6fNroMvod4QUAAD/1t2t26huv7tIbPdyRFKgCo69JLA8AAAh8ESHmbiepe+ZPpXI4HCqpOKtnvpyuEHNg900w5gUAAD/x6cmzevBXu9XQ0t7jPmuWWJR90/B+rMozGPMCAEAAmpI8WB//6O6r7vPnz6r7qRrjEF4AAAgg6/ee0tN/3G90GV5FeAEAIMCs3XHc6BK8ivACAICfGR4TLkkaOThCNyV1Pz4kwIa0ugiY8MIMuwCAgeKP37lVv/j7adr6vTu08ivdr3/024/K+7mq/sPdRgAA+DG73aGxP9zY7baDP75H4SHmfq7o+nC3EQAAA0RQkKnHbWfO9XxLtT8jvAAA4Od+/Q8365+zxungj+9xaW9u7TSoIu8ivAAA4OduHz9Mj8+boPAQsxZPT3G2N7cRXgAAgI979v50hQVf+HknvAAAAJ8XbA5S+shYSVIL4QUAAPiDqLAL6y5bGfPi25jnBQCAC4ZEhkiSznK3kW/Lzc1VaWmpdu/ebXQpAAAYKn5QmCSpvpnwAgAA/EBM+IWel89rm/V+aU3ALRVAeAEAIMBEhV2YVfd/D9bqkd/s0bv7qgyuyLMILwAABJjI0GCX1+s/PmVQJd5BeAEAIMBc7Hm56K8Ha7V2e5n+5Y1PVHyiwaCqPCf42rsAAAB/cmXPiyQ9/adSSdIfPj6p4/9xb3+X5FH0vAAAEGCiQv1jJenr5XPh5dChQ5o6darzERERoQ0bNhhdFgAAfuPiJHWByue+3YQJE1RSUiJJam5u1ujRo3X33XcbWxQAAH4kJS7S+XxKcqw+PdloYDWe53Ph5XJ//OMfNXfuXEVFRRldCgAAfiMuKlT/uWiyTDLpnW5uk376j/vV2mGTyWTSc/eny2QyGVDl9XP7slFRUZEWLFigpKQkmUymbi/pFBQUaMyYMQoPD5fFYtG2bduuq7g33nhDixcvvq73AgAwkC3OTNXXMlNks9u7bFu747he312h3+8qV2VjqwHV9Y3b4aWlpUUZGRlatWpVt9vXrVun5cuX66mnntLevXs1Z84c5eTkqLy83LmPxWJRenp6l0dlZaVzH6vVqu3bt2v+/PlXraetrU1Wq9XlAQAALuiwXX123SO1zf1Uiee4fdkoJydHOTk5PW5/4YUX9PDDD+uRRx6RJL300kvatGmTVq9erZUrV0qSiouLr3mct99+W/PmzVN4ePhV91u5cqVWrFjhxjcAAGDg6LB17Xm5XOP5jn6qxHM8erdRe3u7iouLlZ2d7dKenZ2tHTt2uPVZvb1k9OSTT6qxsdH5qKiocOs4AAAEsmsta/To7/fqo2P1/VOMh3g0vNTV1clmsykxMdGlPTExUdXV1b3+nMbGRu3atUvz5s275r5hYWGKiYnRa6+9phkzZmju3Llu1w0AQKAa1Ivbphev2dkPlXiOV+Z5uXLUssPhcGskc2xsrGpqahQaGtrr9+Tm5qq0tFS7d+/u9XsAAAh0T9+X1qv9/vRJpc61d3q5Gs/waHiJj4+X2Wzu0stSW1vbpTcGAAB437iEaB388T3X3O87v9+rp9Z/1g8V9Z1Hw0toaKgsFosKCwtd2gsLCzVr1ixPHqqL/Px8paWlKTMz06vHAQDA34SHmPWPt4+95n7r9/rH6tNuh5fm5maVlJQ4Z8EtKytTSUmJ81bovLw8vfLKK3r11Vd14MABPfbYYyovL9eyZcs8WviVuGwEAEDP5t003OgSPMbtW6X37NmjrKws5+u8vDxJ0tKlS7V27VotXrxY9fX1euaZZ1RVVaX09HRt3LhRo0aN8lzV3cjPz1d+fr5sNptXjwMAgD8aMzRwZqs3ORzXuonKv1itVsXGxqqxsVExMTFGlwMAgM84Ud+isGCzZqz8qyRpTHyUyupaXPY5/h/3GlGaW7/fPreqNAAA8I5RQ6M0PDZc/5w1TnNujNem5bdpSnKsyz6PrSvpEmh8jU8vzOgOLhsBANA7j8+b4Hx+X0aSy6rT6/ee0p4TDdr2/TuNKK1XAqbnhQG7AAC4z9rN8gAVDeeV/eJWnTp73oCKri1gwgsAAHBfVQ+rSh+uadZzGw/0czW9Q3gBAGAAe+zu8Qo1dx8Hdpc19HM1vRMw4YVJ6gAAcF/S4Ah9tqL7tQRrm9r0xp4KtXdefWXq/sat0gAAQKOfeLfHbd+bN0G5WeO8enxulQYAAG6ZkBjd47YPPq/rx0qujfACAABkMvW8Ldh8lY0GCJjwwpgXAACuX1xUaI/bzEGEF69gnhcAAK7fTx/I6HFbh823BuwGTHgBAADXb+TgCG1+/I5ut20/Ut+/xVwD4QUAAEi6sFCjPyC8AACAq0oeEmF0CS4ILwAAwGneTYld2lLjIg2opGcBE1642wgAgL67KSm2S9v5DpsBlfQsYMILdxsBANB33c27v7f8rNo6fSfABEx4AQAAfWfvYdWgN/ac7OdKekZ4AQAAToMjQ5zP3/nObOfzxnPtRpTTLcILAABw+j83p2reTYn6z0WTFR5yKSb87L3DsrZ2GFjZJYQXAADgFB5i1stLpmtxZqpMVyx4NPO5v6rVBwbvEl4AAEC3osODXV63tNu0aX+1QdVcQngBAADdSogO79J2pLbZgEpcBUx4YZ4XAAA8b9v3s1xeB5mMX2E6YMIL87wAAOB5Vy4NEBxEeAEAAD7MZDLp+/dMcL4OIrwAAABfl37ZkgFmwgsAAPB1lw9zMT66EF4AAMA1DIkMdT7vtHe/fEB/IrwAAICrSh956bJRe6fdwEouILwAAIBreujW0ZKkn//1c+072WhoLT4ZXl588UXddNNNSktL06OPPipHDytcAgCA/hFivhQZFqz6wMBKfDC8nD59WqtWrVJxcbH27dun4uJi7dy50+iyAAAY0Hxgbjqn4Gvv0v86OzvV2toqSero6FBCQoLBFQEAMLD9z8enjC7Bye2el6KiIi1YsEBJSUkymUzasGFDl30KCgo0ZswYhYeHy2KxaNu2bb3+/GHDhunxxx9XamqqkpKSdNddd+mGG25wt0wAAOBBp5vajC7Bye3w0tLSooyMDK1atarb7evWrdPy5cv11FNPae/evZozZ45ycnJUXl7u3MdisSg9Pb3Lo7KyUmfOnNE777yj48eP69SpU9qxY4eKioqu/xsCAICA4vZlo5ycHOXk5PS4/YUXXtDDDz+sRx55RJL00ksvadOmTVq9erVWrlwpSSouLu7x/W+++abGjRunuLg4SdK9996rnTt36rbbbut2/7a2NrW1XUqDVqvV3a8EAAD8iEcH7La3t6u4uFjZ2dku7dnZ2dqxY0evPiMlJUU7duxQa2urbDabtmzZogkTJvS4/8qVKxUbG+t8pKSk9Ok7AACArv7pjktDOIxeIcCj4aWurk42m02JiYku7YmJiaquru7VZ8yYMUPz58/Xl770JU2ZMkU33HCD7rvvvh73f/LJJ9XY2Oh8VFRU9Ok7AACArhZZkp3PJ42IMbASL91tZLrifiqHw9Gl7WqeffZZPfvss73aNywsTGFhYcrPz1d+fr5sNptbtQIAgGsLC77U3/Gv96YZWImHe17i4+NlNpu79LLU1tZ26Y3xtNzcXJWWlmr37t1ePQ4AAANR6GXhJX5Q6FX29D6PhpfQ0FBZLBYVFha6tBcWFmrWrFmePFQX+fn5SktLU2ZmplePAwDAQBRmNjufR4YZO02c20dvbm7WkSNHnK/LyspUUlKiuLg4paamKi8vT0uWLNH06dM1c+ZMrVmzRuXl5Vq2bJlHC79Sbm6ucnNzZbVaFRsbe+03AACAXouJCNb8ycMVYg5SUmy4obWYHG4uHLRlyxZlZWV1aV+6dKnWrl0r6cIkdc8//7yqqqqUnp6uF198scdbnT3tYnhpbGxUTIyxA4oAAEDvuPP77XZ48VWXD9g9fPgw4QUAAD8yIMPLRfS8AADgf9z5/fa5VaUBAACuJmDCC3cbAQAwMHDZCAAAGI7LRgAAIGAFTHjhshEAAAMDl40AAIDhuGwEAAACFuEFAAD4FcILAADwKwETXhiwCwDAwMCAXQAAYDgG7AIAgIAVbHQBnnaxI8lqtRpcCQAA6K2Lv9u9uSAUcOGlqalJkpSSkmJwJQAAwF1NTU2KjY296j4BN+bFbrersrJS0dHRMplMRpcjScrMzNTu3bv99nh9/bzreb877+nNvn3Zx2q1KiUlRRUVFX49jqq/z0NvHLO/z0VPn4e92Y/z0PePORD+Jl5tu7fORYfDoaamJiUlJSko6OqjWgKu5yUoKEjJyclGl+HCbDb36x8bTx+vr593Pe935z292dcT+8TExPj1j0Z/n4feOGZ/n4uePg97sx/noe8fcyD8TezNZ3jjXLxWj8tFDNjtB7m5uX59vL5+3vW835339GZfT+3jz4z4fv5+Lnr6POzNfpyHvn/MgfA30dfPw4C7bAR4GrffwxdwHsJX+MK5SM8LcA1hYWH693//d4WFhRldCgYwzkP4Cl84F+l5AQAAfoWeFwAA4FcILwAAwK8QXgAAgF8hvAAAAL9CeAEAAH6F8AL0wTvvvKMJEyboxhtv1CuvvGJ0ORjA7r//fg0ZMkRf/epXjS4FA1RFRYXuuOMOpaWlacqUKXrzzTe9dixulQauU2dnp9LS0rR582bFxMRo2rRp+uijjxQXF2d0aRiANm/erObmZv3617/WW2+9ZXQ5GICqqqpUU1OjqVOnqra2VtOmTdOhQ4cUFRXl8WPR8wJcp127dummm27SyJEjFR0drfnz52vTpk1Gl4UBKisrS9HR0UaXgQFsxIgRmjp1qiQpISFBcXFxamho8MqxCC8YsIqKirRgwQIlJSXJZDJpw4YNXfYpKCjQmDFjFB4eLovFom3btjm3VVZWauTIkc7XycnJOnXqVH+UjgDT13MR8ARPnod79uyR3W5XSkqKV2olvGDAamlpUUZGhlatWtXt9nXr1mn58uV66qmntHfvXs2ZM0c5OTkqLy+XdGH59iuZTCav1ozA1NdzEfAET52H9fX1+sY3vqE1a9Z4r1gHAIckx/r1613abr75ZseyZctc2iZOnOh44oknHA6Hw7F9+3bHwoULndseffRRx+9+9zuv14rAdj3n4kWbN292LFq0yNslYgC43vOwtbXVMWfOHMdvfvMbr9ZHzwvQjfb2dhUXFys7O9ulPTs7Wzt27JAk3Xzzzfrss8906tQpNTU1aePGjZo3b54R5SKA9eZcBLytN+ehw+HQgw8+qDvvvFNLlizxaj3BXv10wE/V1dXJZrMpMTHRpT0xMVHV1dWSpODgYP3Xf/2XsrKyZLfb9f3vf19Dhw41olwEsN6ci5I0b948ffzxx2ppaVFycrLWr1+vzMzM/i4XAao35+H27du1bt06TZkyxTle5rXXXtPkyZM9Xg/hBbiKK8ewOBwOl7b77rtP9913X3+XhQHoWucid7qhP1ztPJw9e7bsdnu/1MFlI6Ab8fHxMpvNLv+ylaTa2tou//IAvIlzEb7A185DwgvQjdDQUFksFhUWFrq0FxYWatasWQZVhYGIcxG+wNfOQy4bYcBqbm7WkSNHnK/LyspUUlKiuLg4paamKi8vT0uWLNH06dM1c+ZMrVmzRuXl5Vq2bJmBVSMQcS7CF/jVeejVe5kAH7Z582aHpC6PpUuXOvfJz893jBo1yhEaGuqYNm2aY+vWrcYVjIDFuQhf4E/nIWsbAQAAv8KYFwAA4FcILwAAwK8QXgAAgF8hvAAAAL9CeAEAAH6F8AIAAPwK4QUAAPgVwgsAAPArhBcAAOBXCC8AAMCvEF4AAIBfIbwAAAC/8v8Bjd9CfY8yXpUAAAAASUVORK5CYII=", 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" ] @@ -471,7 +471,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -504,8 +504,8 @@ " \n", " \n", " 0\n", - " -1.284622\n", - " 1.033202\n", + " -1.231065\n", + " 1.03467\n", " fixed\n", " 0\n", " \n", @@ -515,16 +515,16 @@ ], "text/plain": [ " Offset Exponent fit_type ch_name\n", - "0 -1.284622 1.033202 fixed 0" + "0 -1.231065 1.03467 fixed 0" ] }, - "execution_count": 54, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -546,6 +546,75 @@ "irasa_out.fit_aperiodic_model().aperiodic_params" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A good way of accidently misspecifying your model is to pass the filter bounds to `pyrasa.irasa`.\n", + "Model misspecifications will result in informative error messages. \n", + "That will tell you how to improve your irasa fit." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "ename": "AssertionError", + "evalue": "You run IRASA in a frequency range from 0.05 -200.0Hz. \nYour settings specified in \"filter_settings\" indicate that you have a pass band from 0.05 - 50Hz. \nThis means that your evaluated range likely contains filter artifacts. \nEither change your filter settings, adjust hset or the parameter \"band\" accordingly. \nYou want to make sure that the lower band limit divided by the upper bound of the hset > 0.05 \nand that upper band limit times the upper bound of the hset < 50", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m irasa_out \u001b[38;5;241m=\u001b[39m \u001b[43mirasa\u001b[49m\u001b[43m(\u001b[49m\u001b[43msig_lp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mband\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m.1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mpsd_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnperseg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnoverlap\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moverlap\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilter_settings\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m50\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.05\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/irasa.py:123\u001b[0m, in \u001b[0;36mirasa\u001b[0;34m(data, fs, band, psd_kwargs, ch_names, win_func, win_func_kwargs, dpss_settings_time_bandwidth, dpss_settings_low_bias, dpss_eigenvalue_weighting, filter_settings, hset_info, hset_accuracy)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m data\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mData shape needs to be either of shape (Channels, Samples) or (Samples, ).\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;66;03m# noqa PLR2004\u001b[39;00m\n\u001b[1;32m 115\u001b[0m irasa_params \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 116\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m'\u001b[39m: data,\n\u001b[1;32m 117\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfs\u001b[39m\u001b[38;5;124m'\u001b[39m: fs,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m'\u001b[39m: hset_accuracy,\n\u001b[1;32m 121\u001b[0m }\n\u001b[0;32m--> 123\u001b[0m \u001b[43m_check_irasa_settings\u001b[49m\u001b[43m(\u001b[49m\u001b[43mirasa_params\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mirasa_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhset_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 125\u001b[0m hset \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mround(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m*\u001b[39mhset_info), hset_accuracy)\n\u001b[1;32m 126\u001b[0m hset \u001b[38;5;241m=\u001b[39m [h \u001b[38;5;28;01mfor\u001b[39;00m h \u001b[38;5;129;01min\u001b[39;00m hset \u001b[38;5;28;01mif\u001b[39;00m h \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m] \u001b[38;5;66;03m# filter integers\u001b[39;00m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/utils/irasa_utils.py:171\u001b[0m, in \u001b[0;36m_check_irasa_settings\u001b[0;34m(irasa_params, hset_info)\u001b[0m\n\u001b[1;32m 168\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filter_settings[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 169\u001b[0m filter_settings[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m=\u001b[39m band_evaluated[\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m--> 171\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m np\u001b[38;5;241m.\u001b[39mlogical_and(band_evaluated[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m filter_settings[\u001b[38;5;241m0\u001b[39m], band_evaluated[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m filter_settings[\u001b[38;5;241m1\u001b[39m]), (\n\u001b[1;32m 172\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYou run IRASA in a frequency range from \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 173\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m -\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 174\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYour settings specified in \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfilter_settings\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m indicate that you have \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 176\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124ma pass band from \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 177\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m - \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 178\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 179\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThis means that your evaluated range likely contains filter artifacts. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 180\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEither change your filter settings, adjust hset or the parameter \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m accordingly. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 181\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYou want to make sure that the lower band limit divided by the upper bound of the hset \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 182\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m> \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 183\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mand that upper band limit times the upper bound of the hset < \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39m\n\u001b[1;32m 184\u001b[0m \u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 185\u001b[0m )\n", + "\u001b[0;31mAssertionError\u001b[0m: You run IRASA in a frequency range from 0.05 -200.0Hz. \nYour settings specified in \"filter_settings\" indicate that you have a pass band from 0.05 - 50Hz. \nThis means that your evaluated range likely contains filter artifacts. \nEither change your filter settings, adjust hset or the parameter \"band\" accordingly. \nYou want to make sure that the lower band limit divided by the upper bound of the hset > 0.05 \nand that upper band limit times the upper bound of the hset < 50" + ] + } + ], + "source": [ + "irasa_out = irasa(sig_lp, \n", + " fs=fs, \n", + " band=(.1, 100), \n", + " psd_kwargs={'nperseg': duration*fs, \n", + " 'noverlap': duration*fs*overlap\n", + " },\n", + " filter_settings=(None, 50),\n", + " hset_info=(1, 2, 0.05))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "ename": "AssertionError", + "evalue": "You run IRASA in a frequency range from0.05 -200.0Hz. \nYour settings specified in \"filter_settings\" indicate that you have a bandpass filter from 4 - 200.0Hz. \nThis means that your evaluated range likely contains filter artifacts. \nEither change your filter settings, adjust hset or the parameter \"band\" accordingly. \nYou want to make sure that the lower band limit divided by the upper bound of the hset > 4 and that upper band limit times the upper bound of the hset < 200.0", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m irasa_out \u001b[38;5;241m=\u001b[39m \u001b[43mirasa\u001b[49m\u001b[43m(\u001b[49m\u001b[43msig_hp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mband\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m.1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mpsd_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnperseg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnoverlap\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moverlap\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilter_settings\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.05\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/irasa.py:123\u001b[0m, in \u001b[0;36mirasa\u001b[0;34m(data, fs, band, psd_kwargs, ch_names, win_func, win_func_kwargs, dpss_settings_time_bandwidth, dpss_settings_low_bias, dpss_eigenvalue_weighting, filter_settings, hset_info, hset_accuracy)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m data\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mData shape needs to be either of shape (Channels, Samples) or (Samples, ).\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;66;03m# noqa PLR2004\u001b[39;00m\n\u001b[1;32m 115\u001b[0m irasa_params \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 116\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m'\u001b[39m: data,\n\u001b[1;32m 117\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfs\u001b[39m\u001b[38;5;124m'\u001b[39m: fs,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m'\u001b[39m: hset_accuracy,\n\u001b[1;32m 121\u001b[0m }\n\u001b[0;32m--> 123\u001b[0m \u001b[43m_check_irasa_settings\u001b[49m\u001b[43m(\u001b[49m\u001b[43mirasa_params\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mirasa_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhset_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhset_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 125\u001b[0m hset \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mround(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m*\u001b[39mhset_info), hset_accuracy)\n\u001b[1;32m 126\u001b[0m hset \u001b[38;5;241m=\u001b[39m [h \u001b[38;5;28;01mfor\u001b[39;00m h \u001b[38;5;129;01min\u001b[39;00m hset \u001b[38;5;28;01mif\u001b[39;00m h \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m] \u001b[38;5;66;03m# filter integers\u001b[39;00m\n", + "File \u001b[0;32m~/git/pyrasa/pyrasa/utils/irasa_utils.py:171\u001b[0m, in \u001b[0;36m_check_irasa_settings\u001b[0;34m(irasa_params, hset_info)\u001b[0m\n\u001b[1;32m 168\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m filter_settings[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 169\u001b[0m filter_settings[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m=\u001b[39m band_evaluated[\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m--> 171\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m np\u001b[38;5;241m.\u001b[39mlogical_and(band_evaluated[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m filter_settings[\u001b[38;5;241m0\u001b[39m], band_evaluated[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m filter_settings[\u001b[38;5;241m1\u001b[39m]), (\n\u001b[1;32m 172\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYou run IRASA in a frequency range from\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 173\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m -\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 174\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(band_evaluated[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYour settings specified in \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfilter_settings\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m indicate that you have \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 176\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124ma bandpass filter from \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 177\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m - \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 178\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124mHz. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 179\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThis means that your evaluated range likely contains filter artifacts. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 180\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEither change your filter settings, adjust hset or the parameter \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mband\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m accordingly. \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 181\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYou want to make sure that the lower band limit divided by the upper bound of the hset \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 182\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m> \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m0\u001b[39m],\u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 183\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mand that upper band limit times the upper bound of the hset < \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(filter_settings[\u001b[38;5;241m1\u001b[39m],\u001b[38;5;250m \u001b[39m\n\u001b[1;32m 184\u001b[0m \u001b[38;5;250m \u001b[39mirasa_params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhset_accuracy\u001b[39m\u001b[38;5;124m\"\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 185\u001b[0m )\n", + "\u001b[0;31mAssertionError\u001b[0m: You run IRASA in a frequency range from0.05 -200.0Hz. \nYour settings specified in \"filter_settings\" indicate that you have a bandpass filter from 4 - 200.0Hz. \nThis means that your evaluated range likely contains filter artifacts. \nEither change your filter settings, adjust hset or the parameter \"band\" accordingly. \nYou want to make sure that the lower band limit divided by the upper bound of the hset > 4 and that upper band limit times the upper bound of the hset < 200.0" + ] + } + ], + "source": [ + "irasa_out = irasa(sig_hp, \n", + " fs=fs, \n", + " band=(.1, 100), \n", + " psd_kwargs={'nperseg': duration*fs, \n", + " 'noverlap': duration*fs*overlap\n", + " },\n", + " filter_settings=(4, None),\n", + " hset_info=(1, 2, 0.05))" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/pyrasa/utils/irasa_utils.py b/pyrasa/utils/irasa_utils.py index 0fdb9ae..f656cdd 100644 --- a/pyrasa/utils/irasa_utils.py +++ b/pyrasa/utils/irasa_utils.py @@ -158,7 +158,8 @@ def _check_irasa_settings(irasa_params: dict, hset_info: tuple) -> None: assert band_evaluated[0] > 0, 'The evaluated frequency range is 0 or lower this makes no sense' assert band_evaluated[1] < nyquist, ( f'The evaluated frequency range goes up to {np.round(band_evaluated[1], 2)}Hz ' - 'which is higher than Nyquist (fs / 2)' + f'which is higher than the Nyquist frequency for your data of {nyquist}Hz, \n' + 'try to either lower the upper bound for the hset or decrease the upper band limit, when running IRASA.' ) filter_settings: list[float] = list(irasa_params['filter_settings']) @@ -168,18 +169,18 @@ def _check_irasa_settings(irasa_params: dict, hset_info: tuple) -> None: filter_settings[1] = band_evaluated[1] assert np.logical_and(band_evaluated[0] >= filter_settings[0], band_evaluated[1] <= filter_settings[1]), ( - f'You run IRASA in a frequency range from' - f'{np.round(band_evaluated[0], irasa_params["hset_accuracy"])} -' + f'You run IRASA in a frequency range from ' + f'{np.round(band_evaluated[0], irasa_params["hset_accuracy"])} - ' f'{np.round(band_evaluated[1], irasa_params["hset_accuracy"])}Hz. \n' - 'Your settings specified in "filter_settings" indicate that you have ' - 'a bandpass filter from ' + 'Your settings specified in "filter_settings" indicate that you have a pass band from ' f'{np.round(filter_settings[0], irasa_params["hset_accuracy"])} - ' f'{np.round(filter_settings[1], irasa_params["hset_accuracy"])}Hz. \n' 'This means that your evaluated range likely contains filter artifacts. \n' 'Either change your filter settings, adjust hset or the parameter "band" accordingly. \n' - f'You want to make sure that band[0] / hset.max() ' - f'> {np.round(filter_settings[0], irasa_params["hset_accuracy"])} ' - f'and that band[1] * hset.max() < {np.round(filter_settings[1], irasa_params["hset_accuracy"])}' + f'You want to make sure that the lower band limit divided by the upper bound of the hset ' + f'> {np.round(filter_settings[0], irasa_params["hset_accuracy"])} \n' + f'and that upper band limit times the upper bound of the hset < {np.round(filter_settings[1], + irasa_params["hset_accuracy"])}' )