diff --git a/Input_visualization_paper.ipynb b/Input_visualization_paper.ipynb index 3bf719b..264144b 100644 --- a/Input_visualization_paper.ipynb +++ b/Input_visualization_paper.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 44, "id": "b9258e15-f1fa-4237-91d9-48fc571605c9", "metadata": {}, "outputs": [], @@ -24,11 +24,10 @@ "import utils\n", "from scipy import stats\n", "import pyroomacoustics as pra\n", - "from network_lib import EndToEndLocModel\n", + "from network_lib import EndToEndLocModel, SampleCNNLoc\n", "from tqdm import tqdm\n", - "from params import fs, window_size, min_src, max_src,n_mic, mics, c, composite\n", + "from params import fs, window_size, min_src, max_src,n_mic, mics, c, composite_sample_cnn, composite_loc_cnn\n", "from utils import normalize, denormalize\n", - "from zennit.canonizers import SequentialMergeBatchNorm\n", "from zennit.attribution import Gradient\n", "os.environ[\"CUDA_VISIBLE_DEVICES\"] = '0'\n", "os.environ[\"TF_FORCE_GPU_ALLOW_GROWTH\"] = \"true\"\n", @@ -39,6 +38,17 @@ " 'font.size': 15})\n" ] }, + { + "cell_type": "code", + "execution_count": 256, + "id": "772dd15e-4552-4ab6-8512-3a0df0e865ea", + "metadata": {}, + "outputs": [], + "source": [ + "source_fixed=True\n", + "source_fixed_num = 29" + ] + }, { "cell_type": "markdown", "id": "8ccb7b59-4c0a-4a00-a63f-c477c27065f0", @@ -49,21 +59,31 @@ }, { "cell_type": "code", - "execution_count": 185, + "execution_count": 257, "id": "7aaf7b15-db62-4d87-a65c-bac9edb92784", "metadata": {}, "outputs": [], "source": [ - "SNR = 20\n", - "T60=0.3\n", + "SNR = 10\n", + "T60=0.6\n", "data_path = '/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/dataset2/val'\n", "data_path = '/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/dataset2/test/SNR_'+str(SNR)+'_T60_'+str(T60)\n", - "files = [os.path.join(data_path,path) for path in os.listdir(data_path)]" + "files = [os.path.join(data_path,path) for path in os.listdir(data_path)]\n", + "figsize=(3,1.5)" + ] + }, + { + "cell_type": "markdown", + "id": "0e7025ad-8810-4f64-b903-fb0dae0413b8", + "metadata": {}, + "source": [ + "# LOC-CNN model\n", + "Taken from: Vera-Diaz, Juan Manuel, Daniel Pizarro, and Javier Macias-Guarasa. \"Towards end-to-end acoustic localization using deep learning: From audio signals to source position coordinates.\" Sensors 18.10 (2018): 3418. https://www.mdpi.com/1424-8220/18/10/3418" ] }, { "cell_type": "code", - "execution_count": 186, + "execution_count": 258, "id": "10364e09-59f8-48ce-9cc8-62dba1d3a748", "metadata": {}, "outputs": [ @@ -91,22 +111,23 @@ ")" ] }, - "execution_count": 186, + "execution_count": 258, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load network model\n", - "saved_model_path='/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/models/model_SNR_'+str(SNR)+'_T60_'+str(T60)+'.pth'\n", - "model = EndToEndLocModel()\n", - "model.load_state_dict(torch.load(saved_model_path))\n", - "model.eval()" + "saved_model_path_loc_cnn='/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/models/model_SNR_'+str(SNR)+'_T60_'+str(T60)+'.pth'\n", + "\n", + "model_loc_cnn = EndToEndLocModel()\n", + "model_loc_cnn.load_state_dict(torch.load(saved_model_path_loc_cnn))\n", + "model_loc_cnn.eval()" ] }, { "cell_type": "code", - "execution_count": 316, + "execution_count": 259, "id": "b63a82aa-42ed-4eac-8eac-cd8be26640ad", "metadata": {}, "outputs": [ @@ -114,22 +135,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "Number of Network parameters: 2126355\n" + "Number of Network parameters for LOC-CNN: 2126355\n" ] } ], "source": [ "def count_parameters(model):\n", " return sum(p.numel() for p in model.parameters() if p.requires_grad)\n", - "print('Number of Network parameters: '+str(count_parameters(model)))" - ] - }, - { - "cell_type": "markdown", - "id": "44219be6-78a5-40b4-b6a8-3ac040159f57", - "metadata": {}, - "source": [ - "# Source Localization" + "print('Number of Network parameters for LOC-CNN: '+str(count_parameters(model_loc_cnn)))" ] }, { @@ -142,7 +155,7 @@ }, { "cell_type": "code", - "execution_count": 188, + "execution_count": 48, "id": "d6d77a46-6264-44a1-9a14-fd83db7b61f7", "metadata": {}, "outputs": [], @@ -153,23 +166,14 @@ "N_wins = win_sig.shape[-1]\n", "idx_slice = np.random.randint(0,N_wins)\n", "input_win_sig = win_sig[:,:,idx_slice]\n", - "src_loc_gt = data_structure['src_pos']" - ] - }, - { - "cell_type": "code", - "execution_count": 189, - "id": "fe39e528-afd5-4ee2-a2b6-1a230a6f7381", - "metadata": {}, - "outputs": [], - "source": [ + "src_loc_gt = data_structure['src_pos']\n", "with torch.no_grad():\n", - " est_pos = model(torch.Tensor(input_win_sig).unsqueeze(0))" + " est_pos = model_loc_cnn(torch.Tensor(input_win_sig).unsqueeze(0))" ] }, { "cell_type": "code", - "execution_count": 190, + "execution_count": 49, "id": "af280197-e3fa-40e6-a251-b0539405412e", "metadata": {}, "outputs": [ @@ -177,12 +181,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.11601216100380579\n" + "0.24895294233275747\n" ] }, { "data": { - "image/png": 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yOfX7/bFwEtUTsSxLrVaLAAMAACRdIMRUKhVtb2/HAUaSer1eonDheZ48z5vY1mw2ValU1O124+3FYlGbm5s6ODjQ5uamisViop4eAABwM6QKMe12W0EQqFwuj23vdDqJ9t/b29NgMJjosSkWi2q322PbbNtWrVZL0zwAAHCDpJrY22g0tLGxceHKLrMvAADASal6Yvb397W1tSXf99Xr9SRJ/X5fjuOMDS+d5rQem2nDUWEYqtlsxq+73a5c1z1z2Go4HGo4HMavj46Ozm0TAAAwU6oQE60oCsMwHuoJw1Dr6+t6+vRpoiDzU77vKwiCiYAzGAy0tbUVz4MJgkCFQkHdbvfUILOzs6PHjx+nbgMAADBPZjQajZIUDIJAuVxOtm2r3++Pvec4jnzfn9ieRC6XU7lcnpjwO02pVJJ0eo/OtJ6Yhw8f6vDwUKurq6nbBgAArt/R0ZHW1tbO/f5OPCcmm81K0tTellwuF/fQpFGpVFQsFhMFGEnx9WJOs7KyotXV1bEHAABYTolDzFnLm08O+SRVr9dl2/bYNWMijuOoXq+fum/asAQAAJZPqtVJ+Xx+aoCItiW9EF20nPpkD0w0UVg6Xoo9bWhqMBjIsiyuFwMAANKFGMdxtL+/P7H92bNnyufzicJFr9dTEAQT14A5OUxUrVan9tD4vq9qtZqmyQAAYEklntgbie5pFIWJXq+nR48eTaxOmjZhNwgCVSoVffzxx2OfeXBwoF6vF0/YDYJA7XZ7LOjU63U1Go1Uk4eTTgwCAACLI+n3d+rbDkTXazl5X6Ozlj2fVCqVFATB2NBR5ORVgG3bVrlcluu6ko6HqyzLutDqJwAAsJxS98SYhJ4YAADMM/Ml1gAAAIuEEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGun3RHV3X1b1793RwcCBJ2t7elmVZ5+4XhqF2dnZ07949SVK/35fneRP7Ji0HAABuptQhJggCOY4jz/OUz+clHQeaTz/9VK1W69z9Hz16pN3d3XjfIAhUKBTU7XbHAkrScgAA4GZKPZxUqVTkOE4cLiSp1+spm82eu2+z2ZSksX1t21Y+n9fOzk7qcgAA4OZKFWLa7baCIFC5XB7b3ul01Gg0zt2/1WppY2NjYvvm5qba7XbqcgAA4OZKFWIajcbUcJGU7/vK5XIT223bVhAECsMwVTkAAHBzpZoTs7+/r62tLfm+r16vJ+l4wu1Ph5emOSt4RHNcgiCQbduJyk2rbzgcajgcxq+Pjo7ObBMAADBXqhAThmHcE1Kr1eJt6+vrevr06ZlBZjAYSNKZk3IHg0H8/nnlptnZ2dHjx4/P/iEAAMBSSDycFARB/HxyToxlWdra2lKlUrlwI5IOD51Xbnt7W4eHh/HjxYsXF24TAABYbIlDTLT6aFpvSy6XO3euSrT/tDJRz0o2m01cbpqVlRWtrq6OPQAAwHJKHGLOGt45OVflIvtHbNtOXA4AANxsqVYn5fP5qT0k0bbzwkWxWFS/35+6/8kAk7QcAAC4uVKFGMdxtL+/P7H92bNnyufz54aLSqUi3/cntnc6nbF5NknLAQCAmytViKlWq7JtO76irnR8tV7f97W7uztWNpfLyXXdif0ljQWUIAgUBIE8z0tdDgAA3Fyp753U7Xbluq4cxxnblnSeSrR/r9eTZVnqdrvqdDoXLgcAAG6mzGg0Gs27EVfl6OhIa2trOjw8ZKUSAACGSPr9nfoGkAAAAIuAEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYKTUF7u7Cb777jv98MMP824GLuiNN97Qm2++Oe9mAACuGCHmhKOjI718+VLD4XDeTcElrays6P333+cihwCwxAgxf3V0dKQ//vGPevfdd/X+++/rzTffVCaTmXezkNJoNNJ3332nw8ND/fGPf5QkggwALClCzF+9fPlS7777rh48eEB4Mdzf/M3f6L333tN//dd/6eXLl4QYAFhSTOzV8RyY4XCotbU1AsySyGQyWltb03A41HfffTfv5gAArgAhRoon8TIZdLlEx5NJ2gCwnAgxJ9ALs1w4ngCw3AgxAADASIQYAABgJEIMAAAwEiEGV6JSqSiTySgMw3k3BQCwpAgxAADASISYOdn/al8/+/efaf+r/Xk35Urs7u6q3+/Lsqx5NwUAsKQIMXPymz/8Rr//4vf67R9+O++mXAnLsmTb9rybAQBYYoSYa/Rl+KW6X3XV+1NPT/7ziSTpd//5O/X+1FP3q66+DL+ccwuPua4bz2ep1+sqFArKZDIqlUrq9XqSpGazGW/P5XKq1+tjnxHtN21OjOu68b6FQkGu606U8X1fpVJJd+/ejcs1m80r+XkBAGbi3knX6KN//Sj+c0bHF2L7+n++VqFZiLePfjm67madqlKpKAgCFYtF2batdrutQqGgcrmsdrutcrmsjY0NNZtNua4ry7JUrVYlSf1+Pw48kTAMVSgUFASBbNtWuVxWr9dTvV6X7/vqdruSjgOS4ziSpGKxKOk41DiOo36/L8/zrvG3AABYVPTEXKPPfv6Zbt86zo0jjcaeb9+6rc9+/tnc2jbNYDBQv99Xo9FQq9VSrVaTJLXbbXW7XbVaLTUaDXU6HUlSq9U68/Nc11UQBPI8T/1+X61WS/1+X9VqNQ4zUTnLsvTq1St1Oh11Oh29evVKlmXRGwMAiBFirtEn//CJPv+Xz6e+9/m/fK5P/uGTa27R2ba3t8del0olSVK5XFY+n4+3R70lg8HgzM9rNpuybTsOQxHP85TP53VwcCBJ8RDUyUnBlmWp2+3q6dOnF/pZAADLh+GkObmlW/pRP8bPi+inE3Oz2awkaXNzM/VnRUNLUeA5KQookWi4KpfLqVwuq1QqaWNjg4nCAIAx9MRcsw/e+UD3372vwocF/eqffqXChwXdf/e+Pnjng3k3bcIsl0cHQSBJyuVy55ZttVrxvJd6vR5P8D05sRgAAHpirtmD1Qf64v98oTtv3FEmk1G1UNW3P3yrldsr827alYp6UaIho/PUajXVajWFYSjf99XpdOIVUf1+n14ZAAA9MfOwcntFmczx6qRMJrP0AUZ6HWJ835/6frSMOggCua6rdrst6bg3qFwuq9FoxL0z0XsAgJuNEINrEYWRk6uQItF1Yj7++GNls1nV63W5rjtxjZl+vy9pcq4OAOBmYjgJ12Z3d1e9Xk+u6+rJkyeybVtBEKjX642tWqpWq2o2m1pfX48nAvd6PQVBoHw+r3K5PM8fAwCwIOiJwbWxLCu+LkwYhmq32wrDULVaLe5lkRQPHWWzWbXbbbXbbVmWJc/zxlYxAQButsxoNFqcS8TO2NHRkdbW1nR4eKjV1dVTy33zzTd6/vy51tfX9dZbb11jC3GVOK4AYKak39/0xAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkVKFmEKhoGazqSAIJEm+76tUKsWvz9Jut6femXjW9QAAgJsh1V2sgyCQ4zjxa8uy1Gq1ZNt2on3r9brq9frU94vFojqdzqXrAQAAN0OqEFMsFrW5uamDgwNtbm6qWCzKsqxE+/b7fdVqNd27d2/ivSdPnqjRaMykHgAAcDOkCjG2batWq12oIsuy5HnexHbf92Xb9lgvy2XqAQAAN8O1Tew9OTwUCcNQnU5H5XL5upqBK9Lr9ZTJZE4dLgQAYNZS9cSEYahmsxm/7na7cl030VyVaWVc1x0bRrpsPcPhUMPhMH59dHR0brsAAICZUoWYwWCgra2teH5KEAQqFArqdrupJ902m02VSqWZ1rOzs6PHjx+nase87O9LtZpUr0sbG/NuDQAA5smMRqPRZT4gCiLRyqKkcrmc+v3+TOuZ1hPz8OFDHR4eanV19dT9vvnmGz1//lzr6+t66623ErfpMv73/5b+7d+On//1X6+lytTCMJTruvJ9X4PBQMViUdvb2wqCQE+ePNHu7q4sy1KpVJLv+2P7djodFYvFObX82DyOKwDg8o6OjrS2tnbu9/el58TYtj3xBXaedrutfD4/83pWVla0uro69lgkX34pdbtSryc9eXK87Xe/O37d7R6/vyjCMIyv1yMdrxjr9Xp69OiRnjx5ona7HZd1XVfVajUu12g0tEH3EgDgiiUeTnIcR7lc7tRVQ2EYJl4G3Wg0Tg0xs6xn0Xz00es/ZzLHz19/LRUKr7dfrl9sdlzXVRAE8jxv7Fg4jjM2X0k6Di7ZbDYeIowCDQAAVylxT8ze3t7U4Z/BYCDLslIFC9/3lcvlrryeRfPZZ9Ltv8bGKKxEz7dvH7+/CKKJ1fl8fiJMTlsmDwDAPCQOMdVqdepKIt/3U/3P+7xbB8yqnkX0ySfS559Pf+/zz4/fXwTRMZo2p8WyrNRDgQAAXIXEIcZxnIlrgNTrdWWz2Yn/nedyObmuO/Vzoi/IbDZ76XpMduvW+PMiiY7Rab1l3P4BALAIEs+JsW1b5XI5DifR3JQ0K4yk4/BiWdapX4SzqmdRffCBdP++9PCh9ItfSL/+tfTixfH2RREN2Z32O09yE08AAK5a6tsOJOkNOStw5PN5vXr1aib1mOjBA+mLL6Q7d44n91ar0rffSisr827Za9HKotNWg6VdjQYAwFVYwMGM5bey8np1UiazWAFGOu6JKZfL6vV6EyuRpt0+AgCAeSDEYKroQnaO46hQKKhSqSiXy2lvb+/Mi9g1Go14eTYAAFeJEIOpLMvS8+fPVa1WFYahfN9XPp/X8+fPx8pE8vm8qtWqBoOBms0m82YAAFcu1ZwY3By9Xk+WZU1d7h4EwdTr9TQajanlAQC4CvTEYKpKpaJCoTDRo+L7voIgMP6aPQAA89ETg6k8z1OlUtH6+rqq1aru3bunZ8+eqd1uy7IsbW9vz7uJAIAbjp4YTFUul9XpdLSxsaFmsxlP1q1Wq3r16pXRt38AACwHemJwqmKxeOZKJAAA5omeGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYADOxvy/97GfHzwBwHQgxAGbiN7+Rfv976be/nXdLANwU3HYAwIV9+aX08qWUyUhPnhxv+93vpH/+Z2k0kt5/X/q7v5tvGwEsL3picK16vZ4ymYzq9fq8m4IZ+OgjaWNDKhSkr78+3vb118evNzaO3weAq0KIAXBhn30m3f5rf+5oNP58+/bx+wBwVQgx88IsSCyBTz6RPv98+nuff378PgBcFULMvBgyC7LZbKpUKunu3bu6e/euKpWKer3e1LK+78dlM5mMCoWCms1m/H6pVFKhUJAkua6rTCYj3/ev5efA1bt1a/wZAK4aE3uvk2GzICuVitrttizLUrFYVBiGarfbarfbarVaKpfLcdlmsynHcSRJxWJR0nGocRxH/X5fnufJdV3Ztq1ms6lisahKpaKNjY25/GyYnQ8+kO7flx4+lH7xC+nXv5ZevDjeDgBXKTMaRSPYy+fo6Ehra2s6PDzU6urqqeW++eYbPX/+XOvr63rrrbeurkGZzPifR6PXz5EFORztdluVSkXValWNRiPe3uv19OjRI0nS8+fPZVmWJOnu3bsT28Iw1Pr6uiTp1atX8f6FQkGe56lWq13pz3BtxxUaDqU7d17/df72W2llZd6tAmCqpN/fdPxeJ4NmQbquK8uyxgKMJOXzeW1vbysMQ+3t7cXbwzCUpDjARH/udrt6+vTpdTQZc7Sy8jqjZzIEGADXg+Gk6/TJJ9Lf//3x+tOf+vxzKZ+//jadIgiCeOjnpw4ODiRJ/X4/3lYul9Vut5XL5VQul1UqlbSxsSHbtq+tzQCAm4UQMy+3bkk//vj6eYEEQRA/R/Ncpol6XySp1WqpXq+r0WioXq/H14EpFovyPE/5BQpoAIDlwHDSdYtmQRYK0q9+dfx8//5CzYKMek/K5bJGo9Gpj58ONdVqNfX7fb169UqtVkvValW+76tQKMTBCACAWSHEXLcHD6QvvjgePnKc4+cvvjjevkBs2z51+XO73ZbjOGM9Nq7rqt1uSzqeC1Mul9VoNOR5XrwPAACzRIiZBwNmQTqOozAMJ4aTgiBQpVJRs9mMe2yy2azq9bpc1x0bYpJez5thbgwAYNYIMZiqVqspn8+r2WzGF7krFArK5XKSjufARCzLUrVaVRAEWl9fV6VSUaVSUS6XU7PZVD6fH7umjCQ1Gg25rsswEwDgwggxOFW325XnebJtW+12W0EQqFgsqtvtTg0lnucpm83GF8SzLEue56nb7cbl8vm8qtWqBoOBms3mRM8NAABJcbE7cVG0ZcVxBQAzcbE7AObhxqgAUiDEAFgchtwYFcBi4GJ3AObLsBujAlgchBgA8/XRR6//HF164Ouvx2/PsbxT9wBcAsNJAObLoBujAlgs9MQAmC+DbowKYLHQE3PCEq82v5E4nga6dWv8GQDOwL8Ukm799R/MH374Yc4twSxFx/MWX4iLz4AbowJYPAwnSXrzzTf1xhtv6C9/+YvefffdeTcHM/KXv/xFb7zxht588815NwXniW6MeufO8eTealX69tuFvK8YgMWR6r+ohUJBzWYzvt+N7/sqlUqJ73+TdP8wDOW6rur1uur1enwzwquSyWT09ttv6/DwkN6YJfHDDz/o8PBQb7/9tjLRihcsNgNujApgsaS67cDdu3fHwoRlWWq1WioWizPdv1AoaHd3V/m/TugLgkClUkndbleWZSVtbuLLFkvSt99+qy+++EK3b99WNpvVysoKX34GGo1GGg6HGgwG+v777/XRRx/pzp07824WACCFpN/fqYaTisWiNjc3dXBwoM3NTRWLxVShIsn+zWZTkuIAI0m2bSufz2tnZ0ee56VpcmJ37tzRgwcP9PLlS/3pT3+6kjpwfd555x3dv3+fAAMASyxViLFtW7Va7cKVJdm/1WppY2NjYvvm5mZ8p+Sr8vbbb+tv//Zv9f333+v777+/snpwtW7fvq3bt5nuBQDLbuH+pfd9f2pQsW1bQRAoDMNUvT8XwZcgAACLL9U3dRiG8XCPJHW7XbmuK9u2Z7L/WZN3o+ASBMHYUNNJw+FQw+Ewfn10dJSoXQAAwDypQsxgMNDW1tZYoCgUCup2u4mCzHn7DwYDSTqzpyUqM83Ozo4eP36c+OcBAADmSrXEutVqjQUM27a1sbEhx3GufP8kS6y3t7d1eHgYP168eJGoXQAAwDyXvpSpbdvyfX8m+2ezWUnTA0vUAxOVmWZlZUWrq6tjDwAAsJwShxjHcVSv1099/7yekiT7J5mwm3T+DQAAWG6JQ8ze3p76/f7E9sFgIMuyzg0gSfcvFotTy4VhKNu2r3xlEgAAMEPiib3VanXq0mff91WtVme2f6VSmVqu0+moXC4nba6k13cxZpUSAADmiL63z72pwCihfr8/8jxvbJvneSPbtifK2rY9qtVql9q/0+mM7Tut3HlevHgxksSDBw8ePHjwMPDx4sWLM7/nE/fE2Latcrks13UlvZ7DMm3o57L7R9eP6fV6sixL3W5XnU4naVNjH374oV68eKH33ntv4j5IR0dHevjwoV68eMEE4AXBMVksHI/FwvFYLByPqzUajfTnP/9ZH3744ZnlUt0AcpmkuTkkrgfHZLFwPBYLx2OxcDwWw6WXWAMAAMwDIQYAABjpxoaYlZUV/fKXv9TKysq8m4K/4pgsFo7HYuF4LBaOx2K4sXNiAACA2W5sTwwAADAbIQYAABiJEAMAAIxEiAEAAEZauhAThqFc11W9Xle9XpfjOOfeYfukQqGgZrOpIAgkHd/bqVQqxa9xMb1eT4VCIfV+lz2emO6ix4PzY7aCIJDrunIcR6VSSZVKJdXvkvNjti57PDg/5iD1DYkWXD6fH3W73fh1dN+lV69eJdrfsqyx+zZYljV2Hyck9+rVq1G1Wh1Vq9VRPp8fXeSv22WPJ16bxfHg/Jidfr8/qlarY9tqtdpI0qjf7yf6DM6P2ZnF8eD8uH5LtcS62Wyq0Wio2+2Oba9UKrJte+rdsX+qUqloc3NTBwcH2tzcVLFYlGVZV9Tim6Ner8t13fPvSHrCLI4nprvI8ZA4P2bJcRx5njfx+7t7965s2574e/9TnB+zddnjIXF+zEPiG0CaoNVqaWNjY2L75uamGo1GopPatm3VarWraB5SmsXxxGxxfszO3t6eBoOBWq3W2PZisah2u33u/pwfs3XZ4yFxfszDUs2J8X1fuVxuYrtt2wqCgLFiw3A8scymBZA0OD9m67LHA/OxND0xZ52wUXdeEATK5/Pnfk6z2Yxfd7tdua4r27Zn0UwkNKvjidni/JidTqczdXuv1zv398n5MXuXOR4Rzo/rtzQhZjAYSNKZ449RmfM+Z2tra+wfgkKhoG63y1/EazSr44nZ4vy4Wr7vKwiCU79QI5wf1yPp8Yhwfly/pRpOOk2abtVWqzX2D4Nt29rY2JDjOLNvGC6EbvL54fy4Wo7jqFarqVgsXvgzOD9mJ+3x4Py4fksTYrLZrKTpJ3D0P5KoTFq2bcv3/Qu3Deld5fHEbHF+zEalUlGxWEw0IZfz4+qlOR5n4fy4WksTYpIsYzuvO89xHNXr9VPf538412cWxxOzxflxder1umzbVqPRSFSe8+NqpT0eEufHvCxNiJGOl8L1+/2J7WEYyrbtc0/8vb29qfsPBgNZlsV6/2t22eOJ2eL8uBrR8t2T/+Pv9Xrn7sf5cTUuejw4P+ZjqUJMpVKZ2m3X6XRULpfP3b9arU5N3r7vq1qtzqSNSO6yxxOzxfkxe71eT0EQTFxbJMnwA+fH7F3meHB+zMl8Lxg8e7Ztj13mOboM97RytVptbFu/3x95nje2zfO8qfsjnejy3aeZdjyi7UmOJ9K5yPHg/Jitfr8/yufzI8/zxh61Wm1ULBbHynJ+XL3LHg/Oj/lYmiXWkWhdfq/Xk2VZ6na7iZfH2batcrks13UlHXfLWpY1tYsQyUSz8vf29iRJpVJJtm3Hk+bOc5njiUmXOR6cH7MV3Rhw2lBF0p4Uzo/Zuezx4PyYj6W6dxIAALg5lmpODAAAuDkIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAY6f8DVvdE86UHyUMAAAAASUVORK5CYII=", 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syPM8+b4vSer3+3IcZ2R46SQn9dhMGo4Kw1CtVit+3ev15LruqcNWh4eHOjw8jF8fHByc2SYAAGCmVCEmWlEUhmE81BOGoVZXV/XkyZNEQebXPM9TEARjAWcwGGhjYyOeBxMEgQqFgnq93olBZmtrS48ePUrdBgAAYJ7McDgcJikYBIFyuZxs21a/3x95z3EceZ43djyJXC6ncrk8NuF3klKpJOnkHp1JPTH379/X/v6+lpeXU7cNAABcvYODA62srJz5/Z14Tkw2m5Wkib0tuVwu7qFJo1KpqFgsJgowkuL9Yk6ytLSk5eXlkR8AALCYEoeY05Y3Hx/ySarRaMi27ZE9YyKO46jRaJx4btqwBAAAFk+q1Un5fH5igIiOJd2ILlpOfbwHJpooLB0txZ40NDUYDGRZFvvFAACAdCHGcRzt7u6OHX/69Kny+XyicOH7voIgGNsD5vgwUbVandhD43meqtVqmiYDAIAFlXhibyR6plEUJnzf14MHD8ZWJ02asBsEgSqVih4+fDjymXt7e/J9P56wGwSBOp3OSNBpNBpqNpupJg8nnRgEAADmR9Lv79SPHYj2azn+XKPTlj0fVyqVFATByNBR5PguwLZtq1wuy3VdSUfDVZZlnWv1EwAAWEype2JMQk8MAADmmfoSawAAgHlCiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARrp53hNd19Xt27e1t7cnSdrc3JRlWWeeF4ahtra2dPv2bUlSv99XvV4fOzdpOQAAcD2lDjFBEMhxHNXrdeXzeUlHgeaTTz5Ru90+8/wHDx5oe3s7PjcIAhUKBfV6vZGAkrQcAAC4nlIPJ1UqFTmOE4cLSfJ9X9ls9sxzW62WJI2ca9u28vm8tra2UpcDAADXV6oQ0+l0FASByuXyyPFut6tms3nm+e12W2tra2PH19fX1el0UpcDAADXV6oQ02w2J4aLpDzPUy6XGztu27aCIFAYhqnKAQCA6yvVnJjd3V1tbGzI8zz5vi/paMLtr4eXJjkteERzXIIgkG3bicpNqu/w8FCHh4fx64ODg1PbBAAAzJUqxIRhGPeE1Gq1+Njq6qqePHlyapAZDAaSdOqk3MFgEL9/VrlJtra29OjRo9P/EgAAYCEkHk4KgiD+fXxOjGVZ2tjYUKVSOXcjkg4PnVVuc3NT+/v78c+LFy/O3SYAADDfEoeYaPXRpN6WXC535lyV6PxJZaKelWw2m7jcJEtLS1peXh75AQAAiylxiDlteOf4XJXznB+xbTtxOQAAcL2lWp2Uz+cn9pBEx84KF8ViUf1+f+L5xwNM0nIAAOD6ShViHMfR7u7u2PGnT58qn8+fGS4qlYo8zxs73u12R+bZJC0HAACur1QhplqtyrbteEdd6Wi3Xs/ztL29PVI2l8vJdd2x8yWNBJQgCBQEger1eupyAADg+kr97KReryfXdeU4zsixpPNUovN935dlWer1eup2u+cuBwAArqfMcDgczroRl+Xg4EArKyva399npRIAAIZI+v2d+gGQAAAA84AQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMlCrEFAoFtVotBUEgSfI8T6VSKX59mk6nI9d1FYbhpdYDAACuh8xwOBwmLXzr1q2REGJZltrttorF4pnnNhoNua574vvFYlHdbvfC9Rx3cHCglZUV7e/va3l5OdW5AABgNpJ+f99M86HFYlHr6+va29vT+vq6isWiLMtKdG6/31etVtPt27fH3nv8+LGazeZU6gEAANdDqhBj27Zqtdq5KrIsS/V6fey453mybVu2bU+lHgAAcD1c2cRex3HGjoVhqG63q3K5fFXNAAAACyJVT0wYhmq1WvHrXq8n13VHelFOMqmM67ojw0gXrefw8FCHh4fx64ODgzPbBQAAzJQqxAwGA21sbMTzU4IgUKFQUK/XSxRkjmu1WiqVSlOtZ2trS48ePUrVDgAAYKZUq5MmiYJItLIoqVwup36/P9V6JvXE3L9/n9VJAAAY5FJWJ01i2/bI0E8SnU5H+Xx+6vUsLS1paWkp1edO8sMPP+inn3668OdgNt544w29+eabs24GAOCSJQ4xjuMol8uduGooDMPEy6CbzeaJIWaa9aR1cHCgV69ejfTmwExLS0v64IMP6IEDgAWWOMTs7OxoY2Nj7PhgMJBlWamChed5qlQql15PGgcHB/rjH/+o9957Tx988IHefPNNZTKZS6kLl2c4HOqHH37Q/v6+/vjHP0oSQQYAFlTiEFOtVk/c56VarSau8KxHB0yrnrRevXql9957T/fu3SO8GO6v/uqv9P777+s///M/9erVK0IMACyoxPvEOI6jRqMxcqzRaCibzY6Fjlwud+IjBqIQk81mL1zPtPzwww86PDzUysoKAWZBZDIZrays6PDwUD/88MOsmwMAuASJe2Js21a5XI7DSTQ3Jc0KI+kovFiWdeJS6WnVk0Y0iZfJoIslup4//fQT1xYAFtCFl1jPs6RLtL777js9e/ZMq6urevvtt6+whbhMXFcAMFPS7+8re+wAAADANBFiAACAkQgxAADASIQYXIpKpaJMJqMwDGfdFADAgiLEAAAAIxFiZmT35a5+82+/0e7L3Vk35VJsb2+r3+9f2g7LAAAQYmbksz98pi+ff6nP//D5rJtyKU7bCwgAgGkgxFyhr8Ov1XvZk/9fvh7/x2NJ0u//4/fy/8tX72VPX4dfz7iFR1zXjeezNBoNFQoFZTIZlUol+b4vSWq1WvHxXC43cZflQqEwcU6M67rxuYVCYeLuzp7nqVQq6datW3G5tE9LBwAstsQ79uLiPvq/H8V/zujo8Qbf/OkbFVqF+Pjwd/Oz92ClUlEQBCoWi7JtW51OR4VCQeVyWZ1OR+VyWWtra2q1WnJdV5Zlxc+36vf7ceCJhGGoQqGgIAjinZl931ej0ZDneer1epKOApLjOJKkYrEo6SjUOI6jfr9/aY+fAACYhZ6YK/TFb7/QzRtHuXGo4cjvmzdu6ovffjGztk0yGAzU7/fVbDbVbrdVq9UkSZ1OR71eT+12W81mU91uV5LUbrdP/TzXdRUEger1uvr9vtrttvr9vqrVahxmonKWZen169fqdrvqdrt6/fq1LMuiNwYAECPEXKGP/+5jffW/v5r43lf/+yt9/HcfX3GLTre5uTnyulQqSZLK5bLy+Xx8POotGQwGp35eq9WSbdtxGIrU63Xl83nt7e1JUjwEdXxSsGVZ6vV6evLkybn+LgCAxcNw0ozc0A39rJ/j3/Po1xNzoyePr6+vp/6saGgpCjzHRQElEg1X5XI5lctllUolra2tMVEYADCCnpgrdufdO7r73l0VPizo03/4VIUPC7r73l3deffOrJs2ZprLo4MgkCTlcrkzy7bb7XjeS6PRiCf4Hp9YDAAAPTFX7N7yPT3/P8/11htvKZPJqFqo6vufvtfSzaVZN+1SRb0o0ZDRWWq1mmq1msIwlOd56na78Yqofr9PrwwAgJ6YWVi6uaRM5mh1UiaTWfgAI/0SYjzPm/h+tIw6CAK5rqtOpyPpqDeoXC6r2WzGvTPRewCA640QgysRhZHjq5Ai0T4xDx8+VDabVaPRkOu6Y3vM9Pt9SeNzdQAA1xPDSbgy29vb8n1fruvq8ePHsm1bQRDI9/2RVUvValWtVkurq6vxRGDf9xUEgfL5vMrl8iz/GgCAOUFPDK6MZVnxvjBhGKrT6SgMQ9VqtbiXRVI8dJTNZtXpdNTpdGRZlur1+sgqJgDA9ZYZDofzs0XslB0cHGhlZUX7+/taXl4+sdx3332nZ8+eaXV1VW+//fYVthCXiesKAGZK+v1NTwwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkVKFmEKhoFarpSAIJEme56lUKsWvp3V+GIZyXVeNRkONRkOO4ygMwzRNxRXzfV+ZTEaNRmPWTQEAXBM30xQOgkCO48SvLctSu92WbdtTPf/Bgwfa3t5WPp+PzysUCur1erIsK02TAQDAgkoVYorFotbX17W3t6f19XUVi8VUoSLJ+a1WS5LiACNJtm0rn89ra2tL9Xo9TZPn1u6uVKtJjYa0tjbr1gAAYJ5Uw0m2batWq6ler6tcLqfuFUlyfrvd1tqEb/X19XV1Op1U9c2zzz6TvvxS+vzzWbfkZGEYynEc5XI53bp1S5VKRb7vq9PpqFKpxEN8pVJJhUJBkuS6rjKZjDzPm2HLAQDXwdxN7PU8T7lcbuy4bdsKgsDouTFffy31epLvS48fHx37/e+PXvd6R+/PizAM4zlM0lEvmu/7evDggR4/fjwSKF3XVbVajcs1m82JQRQAgGlKNZwUhmH8pSZJvV5PrusmnhNz1vmnBZSo1yYIgpGhJpN89NEvf85kjn5/8430P50YkqTh8EqbdCLXdRUEger1umq1WnzccZyRaygdBZdsNqtWq6VSqRQHGgAALlOqEDMYDLSxsTESKKIJt0mCzFnnDwYDSTp1mCoqM8nh4aEODw/j1wcHB2f/pa7QF19I//RP0o8//hJWot83b0r/+q+zatmoKGzm8/mRACNJ9Xp9LMQAADALqYaT2u32SMCwbVtra2sjK44u6/wkw0hbW1taWVmJf+7fv5+oXVfl44+lr76a/N5XXx29Pw+iJe/FYnHsPcuyjO0JAwAslgvPibFt+0KTOI+fn81mJU0OLFEPTFRmks3NTe3v78c/L168OHe7LtuNG6O/50kUYibNTZKUePgQAIDLlPgr1HGcUzcyO6unJMn5SVY7nfYFurS0pOXl5ZGfeXPnjnT37tE8mE8/Pfp99+7R8XkRXYd+vz/xfZMnVwMAFkfiELOzszPxS20wGMiyrDMDSNLzi8XixHJhGMq2beM3u7t3T3r+/Gj4yHGOfj9/fnR8XkQri07qYWP5NABgHiQOMdVqVc1mc+y453mJVqMkPb9SqUz8kux2uyqXy0mbO9eWln5ZnZTJHL2eJ5ZlqVwuy/f9sUm8Sec/AQBw2S40nNRoNJTNZsd20c3lcnJd91znR4HmeJAJgiBe7oursb29Lcuy5DiOCoWCKpWKcrmcdnZ2Jk74jTSbzXh5NgAAlynxEmvbtlUul+NwEs1hOWnexEXOj/aP8X1flmWp1+up2+0mbSqmwLIsPXv2TK7ryvM8eZ6nYrGo7e1tVSqVuEwkn8+rWq1qZ2dHrVZLDx8+nFHLAQDXRWY4nJft1abv4OBAKysr2t/fP3WS73fffadnz55pdXVVb7/99hW2cH5FAXLSROpcLqfBYKDXr1/PoGXJcV0BwExJv7/ncIEv5kGlUlGhUBhbieR5noIgYFdeAMDMpdqxF9dHvV5XpVLR6uqqqtWqbt++radPn6rT6ciyLG1ubs66iQCAa46eGExULpfV7Xa1tramVqsVT9atVqt6/fq18UvdAQDmoycGJyoWi6euRAIAYJboiQEAAEYixAAAACMRYgAAgJEIMQAAwEiEGACLYXdX+s1vjn4DuBYIMQAWw2efSV9+KX3++axbAuCKsMQagLm+/lp69erocfCPHx8d+/3vpX/8R2k4lD74QPqbv5ltGwFcGkIMAHN99NEvf85kjn5/841UKPxyfHEfDwdcewwnATDXF19IN//n/8WisBL9vnnz6H0AC4ueGADm+vhj6W//drTnJfLVV1I+f/VtAnBl6IkBsBhu3Bj9DWDhcbfjSvm+r0wmo0ajMeumYFHcuSPdvXvUG/Ppp0e/7949Og5goTGcBMBs9+5Jz59Lb711NLm3WpW+/15aWpp1ywBcMnpiZoWNuYDpWVr6ZXVSJkOAAa4JQsysGLIxV6vVUqlU0q1bt3Tr1i1VKhX5vj+xrOd5cdlMJqNCoaBWqxW/XyqVVPifCZiu6yqTycjzvCv5ewAAFg/DSVfJsI25KpWKOp2OLMtSsVhUGIbqdDrqdDpqt9sql8tx2VarJcdxJEnFYlHSUahxHEf9fl/1el2u68q2bbVaLRWLRVUqFa2trc3k7wYAMF9mOFzcnaAODg60srKi/f19LS8vn1juu+++07Nnz7S6uqq333778hoUdXdHfx4Of/kdmZPL0el0VKlUVK1W1Ww24+O+7+vBgweSpGfPnsmyLEnSrVu3xo6FYajV1VVJ0uvXr+PzC4WC6vW6arXapf4druy6AgCmKun3N8NJV8mgjblc15VlWSMBRpLy+bw2NzcVhqF2dnbi42EYSlIcYKI/93o9PXny5CqaDAC4ZhhOukoGbcwVBEE89PNre3t7kqR+vx8fK5fL6nQ6yuVyKpfLKpVKWltbk23bV9ZmAMD1QoiZlRs3pJ9//uX3HAmCIP4dzXOZJOp9kaR2u61Go6Fms6lGoxHvA1MsFlWv15Wfo4AGAFgMDCddNQM25op6T8rlsobD4Yk/vx5qqtVq6vf7ev36tdrttqrVqjzPU6FQiIMRAADTQoi5atHGXF99JTnO0e/nz4+OzxHbtk9c/tzpdOQ4zkiPjeu66nQ6ko7mwpTLZTWbTdXr9fgcAACmiRAzCwZszOU4jsIwHBtOCoJAlUpFrVYr7rHJZrNqNBpyXXdkiEn6Zd4Mc2MAANNGiMFEtVpN+XxerVYr3uSuUCgol8tJOpoDE7EsS9VqVUEQaHV1VZVKRZVKRblcTq1WS/l8fmRPGUlqNptyXZdhJgDAuRFicKJer6d6vS7bttXpdBQEgYrFonq93sRQUq/Xlc1m4w3xLMtSvV5Xr9eLy+XzeVWrVQ0GA7VarbGeGwAAkmKzO7Ep2qLiugKAmdjsDsBC4FmpAE5CiAEw1wx5ViqAGWCzOwBzx7BnpQKYEUIMgLnz0Ue//DnajeCbb0af2LG4s/kAJJVqOKlQKKjVasXLYj3PU6lUSrxMNtoUzXEclUolVSqViedetB4AZjPoWakAZihVT8yvn6VjWZba7XaijcyCIFC9Xh/Zqt51XeVyOfX7/ZHPuEg9AMxn0LNSAcxQqhBTLBa1vr6uvb09ra+vq1gsyrKsROfW6/V4C/rjx1qtliqVysheIhep5yIWeLX5tcT1XAxz/KxUADOWKsTYtq1arXauinZ2djQYDEZ2epWOAsuvn6tzkXrO48aNo1G1n3766crqxOWLrmd0fWGW6Fmp9+9L//zP0r/8i/TixVw9KxXAjF3ZxN61tbWrqiq1N998U2+88Yb+8pe/6L333pt1czAlf/nLX/TGG2/ozTffnHVTcA7Rs1Lfeutocm+1Kn3//Vw+agzAjKQKMWEYqtVqxa97vZ5c1000V6Xb7U487vv+2Pnnrefw8FCHh4fx64ODgzPbJUmZTEbvvPOO9vf3lc1m9cYbbyQ6D/Prp59+0v7+vt555x1louUtMM7xwDKnz0oFMEOpQsxgMNDGxkY8PyUIAhUKBfV6vXNNuvU8T0EQjAWc89aztbWlR48epW6HJN25c0fPnz/X119/rWw2q6WlJb78DDQcDnV4eKjBYKCff/5Zdxh7AICFdeFnJ5VKJUkn97ScJpfLqVwuj034PW89k3pi7t+/f+azFyJ//vOf9erVK/3pT39K0HrMs3fffVcffPCB3nnnnVk3BQCQUtJnJ114Toxt2yNDP0lVKhUVi8VEASZpPUtLS1q6QH/zO++8o7/+67/Wjz/+qB9//PHcn4PZunnzpm7eZB9HAFh0if9L7ziOcrnciauGwjBMvAy60WjItu2JAWaa9ZwXX4IAAMy/xGtPd3Z21O/3x44PBgNZlpU4WETLqY8HGN/3p14PAABYbIlDTLVaHdltN+J5nqrVaqLP8H1fQRCM9bJ4njfVegAAwOJLPLE3CAJ1Op2RANJoNNRsNsd6TiZN2A2CQJVKRQ8fPhwpu7e3J9/34wm7aeo5S9KJQQAAYH5MfWKvbdsql8tyXVfSL3NTkgaL6AGOx4eOIuVyeWr1AACA6+HCS6znGT0xAACYJ+n3Nw+VAQAARlrodcRRJ1PSxw8AAIDZi763zxosWugQ8+2330qS7t+/P+OWAACAtL799lutrKyc+P5Cz4n5+eef9fLlS73//vtjz0GKHknw4sUL5svMCa7JfOF6zBeux3zhelyu4XCob7/9Vh9++KFu3Dh55stC98TcuHFD9+7dO7XM8vIy/wLOGa7JfOF6zBeux3zhelye03pgIkzsBQAARiLEAAAAI13bELO0tKTf/e53F3rqNaaLazJfuB7zhesxX7ge82GhJ/YCAIDFdW17YgAAgNkIMQAAwEiEGAAAYCRCDAAAMNLChZgwDOW6rhqNhhqNhhzHURiGic8vFApqtVoKgkCS5HmeSqVS/Brn4/u+CoVC6vMuej0x2XmvB/fHdAVBINd15TiOSqWSKpVKqn+W3B/TddHrwf0xA8MFk8/nh71eL37d7/eHtm0PX79+neh8y7KGkuIfy7KG3W73klq72F6/fj2sVqvDarU6zOfzw/P863bR64lfTON6cH9MT7/fH1ar1ZFjtVptKGnY7/cTfQb3x/RM43pwf1y9hVpi3Wq11Gw21ev1Ro5XKhXZtq16vX7mZ1QqFa2vr2tvb0/r6+sqFouyLOuSWnx9NBoNua575hNJj5vG9cRk57keEvfHNDmOo3q9PvbP79atW7Jte+zf+1/j/piui14PiftjFhbq2Untdltra2tjx9fX19VsNhPd1LZtq1arXUbzkNI0riemi/tjenZ2djQYDNRut0eOF4tFdTqdM8/n/piui14PiftjFhZqToznecrlcmPHbdtWEASMFRuG64lFNimApMH9MV0XvR6YjYXpiTntho2684IgUD6fP/NzWq1W/LrX68l1Xdm2PY1mIqFpXU9MF/fH9HS73YnHfd8/858n98f0XeR6RLg/rt7ChJjBYCBJp44/RmXO+pyNjY2R/xAUCgX1ej3+RbxC07qemC7uj8vleZ6CIDjxCzXC/XE1kl6PCPfH1Vuo4aSTpOlWbbfbI/9hsG1ba2trchxn+g3DudBNPjvcH5fLcRzVajUVi8Vzfwb3x/SkvR7cH1dvYUJMNpuVNPkGjv6PJCqTlm3b8jzv3G1Depd5PTFd3B/TUalUVCwWE03I5f64fGmux2m4Py7XwoSYJMvYzurOcxxHjUbjxPf5P5yrM43rieni/rg8jUZDtm2r2WwmKs/9cbnSXg+J+2NWFibESEdL4fr9/tjxMAxl2/aZN/7Ozs7E8weDgSzLYr3/Fbvo9cR0cX9cjmj57vH/4/d9/8zzuD8ux3mvB/fHbCxUiKlUKhO77brdrsrl8pnnV6vVicnb8zxVq9WptBHJXfR6Yrq4P6bP930FQTC2t0iS4Qfuj+m7yPXg/piR2W4YPH22bY9s8xxtwz2pXK1WGznW7/eH9Xp95Fi9Xp94PtKJtu8+yaTrER1Pcj2RznmuB/fHdPX7/WE+nx/W6/WRn1qtNiwWiyNluT8u30WvB/fHbCzMEutItC7f931ZlqVer5d4eZxt2yqXy3JdV9JRt6xlWRO7CJFMNCt/Z2dHklQqlWTbdjxp7iwXuZ4Yd5Hrwf0xXdGDAScNVSTtSeH+mJ6LXg/uj9lYqGcnAQCA62Oh5sQAAIDrgxADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJH+P2MD5JFt7NotAAAAAElFTkSuQmCC", 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" ] @@ -214,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": 191, + "execution_count": 50, "id": "b4e1b88f-e44e-425b-9529-10a081beffba", "metadata": {}, "outputs": [ @@ -222,7 +226,7 @@ "name": "stderr", "output_type": "stream", "text": [ - " ... (more hidden) ...\n" + "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 285/285 [00:29<00:00, 9.60it/s]\n" ] } ], @@ -240,7 +244,7 @@ " for n_w in range(N_wins):\n", " input_win_sig = win_sig[:,:,n_w]\n", " with torch.no_grad():\n", - " est_pos = model(torch.Tensor(input_win_sig).unsqueeze(0)).detach().numpy()[0]\n", + " est_pos = model_loc_cnn(torch.Tensor(input_win_sig).unsqueeze(0)).detach().numpy()[0]\n", " sources_est.append(est_pos)\n", " sources_gt.append(data_structure['src_pos'])\n", "sources_est = np.array(sources_est)\n", @@ -249,13 +253,13 @@ }, { "cell_type": "code", - "execution_count": 192, + "execution_count": 51, "id": "1b20c01f-a530-454c-b275-93b0191bf601", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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Z516udWj//v2amprKfh07dqzscgAAQOMrKwCNj49raGhIu3bt0qFDh+T1etXT06M//MM/1A9/+MOyK5MZ5VWolcflcq3YhydzfKHXZFp+Co0k6+joUGdnZ94XAABYu8oKQLt371YwGNT4+LjGx8d1//33a9OmTXr44Yfl8Xj0ute9Tp///Od19OjRks673K2r3D485RyfwVIcAACg4lFgu3fvVjgc1i9+8QslEgnt27dPZ86cUTAYlMvl0h133KFHHnmk6I7Fbre7YAtOZt9KAcbr9Wp8fLzg8U6nk4kQAQBAdYfBv/DCCzp79qzS6bRM05RpmhobG9O+ffu0adMmfeITn1jxHIFAQGNjY4v2HzlyRG63e8UAMzg4qHg8vmh/pt8SAABARQFoenpaX/va1/Tud79bra2tGhwcVCwWk9vtVjgc1vj4uM6ePauHH35YnZ2dCofDeuSRR5Y9p9/vl9PpzM7oLFmzQMfjcR04cCDvtS6XS6FQaNHxkvJCUCqVUiqVUjgcruTtAgCANaKsYfBf+tKXFIvFsiHDNE253W7dfffd8vl82r17d97r/X6/vF6vfuVXfkXf/va39eEPf3jZ8ycSCYVCIQUCgbx9xfbfyRyfTCZlGIYSiYRGR0dLfJcAAGCtcpimaZZ6UEuL1XCUCT1+v19dXV0rHtfd3a1PfOITuv/++0uvaQ1NT0+rq6tLU1NTjAgDAKBJlPL7u6wWoEgkoj179hQVenIVmoQQAACg1soKQPv27at2PQAAAGqm4RZDBQAAWG0EIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIAAAYDsEIABYztiYdOed1hbAmkEAAoDlPPaY9Oyz0uOP17smAKqord4VAICGMzEhnT4tORzSwYPWvqeekj74Qck0pc2bpZtvrm8dAVSEAAQAC+3aNf//Doe1PXVK8njm95tmTasEoLq4BQYACz3xhNR29e/DTNDJbNvarOcBNDVagABgob17pVtvzW/xyTh8WHK7a18nAFVFCxAALKelJX8LYE3gJxoACtmyRdq61WoFevhha7t1q7UfQNMjAAFY+8qZy2f7dunoUeuWVyBgbY8etfYDaHoEIABrX7lz+XR0zI8CczisxwDWBDpBA1ibmMsHwDIIQADWptWay2dsTAoGpeFhqbe3oioCqB9ugQFYm1ZrLh+WxgDWBFqAAKxN1ZzLh9tpwJpDAAKw9rW0SHNz89tSsTQGsOZwCwzA2pU7l8/+/dK110o9PYXn8lluqDxLYwBrDgEIwNqVO5fP+fPSuXPS3XcXnstnub49e/da5yjk8GHreQBNhVtgAJrbcqOyCvXdGRmRPvxhqwXn4kVp/frS+vZUejsNQEMgAAFobrktNwsDUDF9d1Z6PnOrK3M7bccOK0A98oh07BhLYwBNiltgAJrPxISUSEjJZH7LTTJp7Z+YsPb95/88f0yhvjt/8AfF9+1haQxgTaEFCEDzKXZU1qlTS58jMxT+vvuKHyqfuxQGS2MATY0WIADNZ6VRWZ/9bH7rkJS/plchLS35WwBrGj/pAJrPcqOyrlyR/tN/slp1cluAcoPS1q3zfXdyh8o//LC1zX0ewJpEAAJQkW0PbZPjQYe2PbQtu88YMuR40CFjyMju2/i5jXI86NDGz23M7tv1hV1yPOjQri/sWnbf6//89XI86NDr//z12X0f+/uPSZLmMg06V1tuPvlO6UrL1Z0LJydsa9P//Yduddz3su76zh9b+7Zv1y0fWyfHbx7RrteGsn17tj3Vt+h9FVu3X3/01+V40KFff/TXs/s6Ptshx4MOdXx2/raZJ+KR40GHPJH5W3CFyih0PgCVIQABqMjLF17O20rS1KWpvK0kXbhyIW8rSRNTE3nbpfb965l/zdtK0sjpf9DJjVJim7ItNyc3Sl9+s/TW+5aYlfnwYX38hh/pUpv0zZ99M7v75xdelBxXy7zat6fQ+yq2bv8w8Q95W0m6NHcpbytJyZeTedulyih0PgCVcZgm87cvND09ra6uLk1NTamzs7Pe1QEajvfLXv3k9E/kkEMnzp+oyjlb1SpJmtVsdl+bw+rnc8W8kt23sd1qQTp/+bzWXZEutUqbN2yWTFPT58/oUpv0lhNSMirNSmrV/LbP36KxG+fn7rmm7RpJ0mtXXsvua7n6d+Gc5pbdV6huhc5XrPaWdknS5bnL2X0drVZr0czsTHZf/65+mTL1lm1v0UPveqjkcoC1rJTf3wSgAghAwPIcDy7RkbhB3DQlHTkgOUxp6wXp5Wsl0yH17ZOOdy1/rOe4NDwqBQekxE21qW+5zAf45xvIVcrvb26BASiZQ40bgHampRsuSO+7W9laOmQ9vuGC9fxyfv9H0p1Hpd/7ceHnPcelpx+VPvBDa+s5Xp16l2rT+k31KRhYI5gHCEDJ5h6Y002fv6lqt7+qaeIL8/+fuWF1/QXp8CPz+x2fyT9mZ1ra/KpkSrr7OWvfPf8iffl/tcLT6Q3Si4a1PxOQul+T3vxLKyjVuqWof1e/4h+M17ZQYI0hAAFoSkvdqtr7funRr0vtc/NN3Jnt5RbpwX9rtdzkHrdUaEpGc8rzS1vPSXuvtgy96ZfW9gM/kr7tkl7emB+UADQ2boEBKItnW4HZk2toqVtVT94uvfW+wse89T5pywXruI99d/4W1t73W+FIKhyaJCkRlf72q1LPxfzney5Kf/uk9XxukFpN79j5jtoUBKxhBCAAJbt35F794uwvtGPDjkXPtS1oWF7ful7rW9fn7eto6Vi0b6FMX5vcPjY705L7hDXKK3Or6vd+JB2OSHt/aD3/gR9K3/lL67mFa7UfOiR98IfW///2v14NQt+TvrNz6dD0od+Wfv/9LdkglLGwF9TlFitIFcMhh67RNcW9eIFWteqh7z6kW/7bLWUdD8DCKLACGAUGLK8Wo8C++P9K//770lffYHVeDg5IYwfmn5+T9Recqfwwcq5dum5+JPmi55fav/f90le+Nj9kPnP+J98o7fXND61fitsv/eDG0t5jpRgFBuQr5fc3fYAAlGxd6zpdmr208gtLlNsZOdPX5q6fSutnrZaah94m/cd/soJJpkEmE2JMSS9vkLa9mn/OpaJa7nEOWeFHko4a0lffJIX+UWqZszpD/2Sz9MLVQVeZgJQ5bqmABaCx0QJUAC1AwMre8N/foJ+c/klVz2l+Juf/VduAkQk2C8tf6Ac3SM601Dontc9KHXPWaz/6Lum/1qhrzjVt1+jVT7668gsBm2EeIABNx3Nc+lm3lJlX2bFgu/AvtWr/5ZYJP5nzFgo/PzekjRel4xulwG9K6fXzr/0/D0vfj0i/9dP51xfqxwSgMRCAAJTME/Ho55M/r+o5/+iIdMvk0vflcwPJarYKLXfe16Wl101Jt52RvvL/SNfnNMLsmpL6Tkp/85T09hetfStNqliu1668lreAKoDS0QcIQMlyF++sxM609L8dlf79YemOk8Uf1yh9bpb6C/K7fyl96p3SR8asx0tNqliJan0PALsiAAGom9x5c9ZaZ+L/8uz8/y+cVLF3X+OvMwasddwCA1Ay8wFTRodR9vGZ+Xw++c7l+9ysFZl/aDPzElV6S8zoMBgCD1SIFiAANVerGZMbTSYIrcYtMQCloQUIQFneeP0byz42d+kJO8rcEit3+YxKPnsAFlqAquzy5cuanZ2tdzWwQEtLi9rb2+VwrOUbLbXzq4/8qn525mdar/W6qIsrvr5VrZrV/M/Fk7dLz29efmbltSx3nbEPva+0Y29af5POXDyje0fu1Vd9X6121QDbIABVyfT0tE6fPq2ZmZl6VwVLaG1t1YYNG7RlyxatW7eu3tVpat996bslvT43/Cx+Ln8CQjt5632lL59x/OJxHb94XM+ffp4ABFSAAFQF09PTOn78uDZu3KjNmzfT0tBgTNPU7OysXnvtNU1NTeno0aPavn27NmzYUO+q2dor10onN0rHOq2WkF99ae2NBFtKNULfulZCPFAJAlAVnD59Whs3btT27dsJPg1s48aN6u7u1sTEhE6fPq2dO3fWu0pNy3zA1PXD1+v0a6fLPkerKd11t9TzqvTYX1v77PDT88ibpTe9Iu2YtkJgOW7bfJue+6PnqlovwG4IQBW6fPmyZmZmtHnzZsJPE2htbVV3d7dOnjypK1euqK2NH4F6seNIsC+/SbrvfZJMad2sdInLD6gbG4/DqI5Mh+f29vY61wTF6ujokCRduXJlhVdiOW++4c0VHf+pd1Z/Pa9G98F/tuY/+q2fSd96ovw1wt62/W3VrRhgQwSgKqH1p3nwvarcvSP36vj549p5Xem3ETOTIL7hFXvc8looEZX+5qvFrRHWcvW/XJ6tHh1NH9X9375/9SoJ2AANsABK9tRzT5V13M60PW99LTS9Tuq8tPKEiHPZuaPnJV5OSJKeOfqMHnrXQ6tfWWCNIgABKNm61nW6NHup5OMIP5bOqx/dwjXCHJ8p/hyb1m+qap0Au+EWGICSzXxqRrdtvq3k4/a+fxUq08RyJ0Qs5bPp39WvydDkqtQJsAtagADUzJO3S7vOSp97duXX2kk5EyICqAwtQABKdu/IvXpp+qWyjj1qVLcuzajS0W/PHn1WO/6vHVWpC2BXtAABKFm5naAlqf+FKlakSWVGv81Jmu4ofULEOc3ppXPlBVAAFlqAmtDYmHTnndYWqIdSl2HIDH1/ywnpt36+OnVqRr37pBs+Lh3vqndNAPshADWhxx6Tnn1WevzxetdksXQ6LZfLpU2bNsnhcGhkZESpVEqBQECDg4PatGmTBgYGlE6nJUnDw8MaHByUx+ORy+XSyMhIfd8AilJqJ+iJL1jz3ySj1sgnyX6TIBby+jPSG1+xAmIp2lvaZT7AJwhUgltgTWJiQjp9WnI4pIMHrX1PPSV98IOSaUqbN0s331zfOkqSYRhKJBLq7+9XMpnUkSNHNDo6qkgkIskKPKFQSIODg3K73RoYGFAwGJQkbdq0SYODgxofH5fT6azn20CV7X2/9OjXpfa5+b+67DgJYi5T0pNfm3/cu09K3FS36gC2QwtQk9i1S+rtlTwe6dQpa9+pU9bj3l7r+UZhGIa6u7slSSMjIwqHw9nn3G63JCkej6unp0derzf7XCb0xOPxGtYW5SplOYbv7JQ+9NurWJkmlAmAs1e3K80Knevmzgb4awdocgSgJvHEE1Jm3U7TzN+2tVnPNyKn0ynDMLKPM8FIknw+X95rM89lbo+hcb33yffqmaPPaNvGbXn7Fy7bkDHxBekrV1d858ZNvmlraTrd8y9WHyn3ieVvid3QdoPa29p178i9NakfsFY1XADyeDyKRqNKpVKSrNaAgYGB7OPVPr5R7d0rHT5c+LnDh63nG9Fyt7K4zdW8vvnzb+po+qhOnj+Zt7/Q0g2SdQvs8tV/bex+62uhTTPWNjMrdCK6/IzZv7zySz1/+vmKRuIBaMA+QJkOsxmGYSgWixX9y7LS45tBS4s0Nze/bWS5rT9YO1odrZo1Z1d+4VVP3i49vzl/2Qfky50V+kPvW/n1pY7EA5Cv4QKQ1+tVX1+fzpw5o76+Pnm93pJ+iVZ6fCPbskXaulXasUP68IelRx6Rjh2z9gO1dOXTV+T8olMvpEuf1GdOi5ueTdEylFHMrNC3bb5Nz/3Rc7WpELBGNVwAcjqd2VFB9Ti+kW3fLh09Kq1bZ40G8/ulS5ekjo561wxYWWayv0z4yQ09hB8AtdZwfYCwvI4OK/xI1pbwg3q548Y7Snr9wsn+CD355iSli5wVupQReAAKa7gAlE6nFY1Gs1+BQKCkDsyVHo/KZCZCzAxlj0ajcrlckqRAIKD+/v7sa10uV7bDeu4xQ0ND2WPQmO7/9v069eopveWGtyx6rm1Bw7Lj6n+S1Rn6CsmnoBYVNyt0d1u3vvWLb8n7Ze/yLwSwrIa7BTY5Oak9e/Zk++2kUil5PB4lEomiOjKXc/zMzIxmZmayj6enpyt+H3ZlGIbGx8cLPheJRLITIi601DFoTJ//3ueXfO6KruQ9NnMGvrMa/NI++U7pUhH/Ik9emZTOa9EIPAClabgWoFgsltdp2el0qre3N29kV7WPHxoaUldXV/Zrxw5WWQaWs2n9prKPveN4FSuyRpztkL785tKOcXATEahIwwWgQpxOZ0WzA690/P79+zU1NZX9OnbsWNllAXYwGZpU/67+lV94Ve5iqL82sXr1ajaZtrFvu0pbEPXGjTdq7oEGnwMDaHANdQssEAjI5XItOYornU4vO6S93OM7OjrUQW9iYNXkTuxn5mzt3oYx65DaTGkgZYVDh6TTG6QXjXrXDFj7GqoF6NChQwX7gkxOTsowjBXn86n0eADF8X7Zq8PHl5iavID/8BvS5czoReVv7aztahrsvljcLNAZ6YtplsIAKtRQAcjv9xfsJBuPx+X3+1f9eADFefro0zp/+XzRr//i30ntLAK2osst1ki5lbx65VWWwgAq1FABKBAIaHh4OG/f8PCwuru781YUl6wh1KFQqOzjAZSv1A64DH8vzlvvs0bKFYOlMIDKNFQfIKfTKZ/Plw02mT47xQ6RrvR4AMWZe2BON33+Jp04f6Ko1z95u3RmvfR3T65yxZpUZnmQbeelHxTxepbCACrXUAFIskJMMa01S4WaYo8HUFuvbLS2hdYCs6NMJ3BT85/H3z4pOT5TtyoBtsK/QwDK4tnmKen1r1wrndwo/fgGaYpBl4s6g8+quP4/EkthANVAAAJQsvc++V7986l/1g3rblj0XMsS/6wc75J2fVT67Xukd39glSvYhM5fDYW/+a/WvEmS1ddq4ed588ab9b2XvscoMKBCDXcLDEDj++bPv7nkc3NaeoK+S23SxBfnHzMX0LyuGekrX5t/7PiMtYxI7lIikjRxfkI6Lz1/+nl91ffV2lYSWENoAQJQslZHa1XOQ/hZ7IqjuFthjAIDKkMAAlCyK5++ot3G7pKP25mWPvVOLdNGhDv2rTwU/rbNt2nmUzPLvwjAsrgFBqBmipnlGABqgRYgACV741+8US+mXyz5uNwlMTDPlHRF0ulrrNFyK5m8OKn7v33/alcLWNMIQABK9typ5zSr2ZKPY0mMwhyymuM3v1bcqvAvn39Zn//e51e7WsCaRgACUDMsibG0YtcBy9i0ftPqVQawAQJQExo7MaY7v3ynxk6M1bsqsCnzAVMb2zeWfNyTt0v/julrCiplHbD+Xf2aDE2uboWANY5O0E3osR89pmePPqvHf/S4em/srXd1Fkmn0wqFQpqcnMw+NgxD6XRao6Ojda4d6q06A+jXjlnxmQD1QAtQk5hITyhxIqHkyaQOPndQkvTUc08peTKpxImEJtITda7hvP7+fnk8HsViMcViMY2OjsrpdGYDEdaGW3tuLeu4v2VBVElWp+ejndJPN1tLhBTT+TnjHTvfsWr1AuyCFqAmseuLu7L/77g6fdypC6fkic6vx2Q+UP/epel0WslkctH+/fv3Kx6P16FGWA2f+4fPaaexUw6HQ98/+f2Sjt37funRv6YzdJukXdPSF++Qgu+yZskuRqta9dB3H9JT//KUfvbHP1vVOgJrGS1ATeKJu55QW4v1L2RmavzMtq2lTU/c9UTd6pbLMAxJUiAQ0MDAgIaHh5VMJmUYhhKJRH0rh6r51LOf0l/99K9KDj+S9J2dhB9J2QUu7nlOesMrkvvE/Bpgy5nVrF678pp+Pvnz1awesOYRgJrE3tv36vB9hws+d/i+w9p7+94a12hp4XBYkhSPxxUKheTxeORyuRa1DCWTSYVCoaqUWc1zYWU3XXdT2ccyGWK+6y9IyaiUiPLZALVEAGpCmdWhl1p1u96CwaASiYT8fr+cTqckKZVKqb+/X+l0Ovu6gwcPqqenpyplVvNcWNlL//El+W71lXVsKUO917LMbACZn+JShsFf03ZNQ9zyBppZY/4GRUFbrt2irRu3ynOjRw//1sPy3OjR1o1bteXaLfWuWlY6nVY0GpXb7VYkEtH4+LjOnj0rn8+ndDqtsbH5ofvxeFxer7cq5VbzXFhdT94uffKd9a5F4yllGDyAytEJuols79yuo//hqNa1rpPD4ZDf49el2UvqaOuod9WyUqmUAoGA/H5/dp9hGDpw4IBGRkbU3d2tZDKpeDye3U5OTmbDS2Z/ZtRY7nmSyaTGxsbkdDqVTqfl8/mWPRdW19t3vF0jz4+Udey3Xid97tkqV6jJzMn6C7ScYfC3bLql+hUCbIYA1GRyw47D4Wio8JNrcHBQsVgs+zgej8swDLnd7uw+r9erYDCYfTwyMqKDBw9mj1vYp2ffvn3ZjtQej0c+ny97voXnwuq6/9v36wcnf6C3b3+7vvfS90o+/pVrrXWvNr+2CpVrEi2S/luf9GsvSlsuSFOd69TuMHXZvJx9jUOO7GCH+eNaNDE9IU/Eo0SAgQVAuQhAqDq3262BgQENDAxkJ0A0DEMvvPBC9jXxeDwvDElWwHn66aeVTqcVj8flcrnyns90dA4EAnkjygqdC6ur0nWo3vyy9IrNA5Ak/fERa9vxKelS2yUtyDqLwo8kzWlO6Zm0ki8vnm4CQPEIQKgqt9udDSe5t68WOnLkiAKBQPZxZoRYKpXK3sbKDKnPiEQiCoVCGh4eViwWk8/nK3gurL5N6zfp7MWzZR//N1+tYmWa2KxD+v27ip8DCED10AkadRGPx9Xbay3jkUwmNTk5qd7eXvl8voLhJ5VKye/36+zZswoGgzp48OCS58LqmwxNqn9Xf0nH7Exbc9285YQ01Zh3bmuu1bRmgi5m/p9cRofBKDCgQvzdgbro7u6WYRiKx+NyOp0Fl8qIRqPas2ePJicn5fF4dPas1eJw9913580qvfBcaEy5c9zM1a0WjScRtbaOz9S1GoDtEIBQFz6fT/F4XN3d3dnQEggEFI1Gs6O89uzZI8MwZBiGwuFwNvSkUqm8Ds+FzoXV5f+mX8+98lxJx+x9v/To16X2OZqec11ukT70vtKOuTBzQe998r36xu9+Y1XqBNiBwzRN2lEXmJ6eVldXl6amptTZ2bnsay9evKgXXnhBu3fv1vr162tUQ1SC71nlHA86Vn5RAW85Yc16bEem5ic/zOX2Sz+4scxzchsMyFPK72/+EANQsg3tG+pdhaZVrcjS6ih19iAAuQhAAEp24RMX1Letr+TjXrlWOrlRGjesEVB24liwnZOU7rA+k1LtNnbryqevVKlmgD3RBwhAzRzvknZ9VLrUKr3lpH1vh0lS7z7puRsYAg/UCy1AAMryjp3vKOu4S23K6wxjl14ss1e32ffrKD/83HHjHVWoEWBvBCAAJfN+2atDzx3S9ddcX/Y5MrfDniv/FA0rE3Iyoef0NVLiRumZXVb2u9Be3q0vSXIZLo2fHZf/m0tPNApgZTS+AijZ00efrvgcmdthb/illDxQ3qKgjS7zfv6P90ovdUrfetJ6fL7dWv/rhgvS6Q3Si0bx5xxPj0tpaezkmKL/u43vIQIVIgABKFmhRTrLcalNemWj1RJ0rNOaE+dXX7LC0OVWaf3siqdoCAuHuGf+/3KLNe/RN65OXJ6ZAPL6V/P7P5UzCSIj8YDKcAsMQMnmHpjTjRuLm7zGc1x6+lFrW0irKd11t/SRfyf9ytXlxc5cI33u31SnrqslE/8uS0p1FX7NW++zJoC8fPVf2sw/uJnt5Rbr+VL1bevThU9cKP1AAFm0AAFYVb//I+nOo9Lv/VhK3LT4+UJLZGx+Tfrs/1eDylUg08rTLunwdsk1NX8bL/d23pO3S89vLjzi7a33lT8JIoDK0AIEoCyebZ4ln8td+PTuqytm3PMvkuekQ+4T+Yt/rtRC0sgyrUC/MW51dP7p9dL+O60Ozyc3Lu7oXOiOXntLe1Fl5b6u3BF4AObRAgSgLN/43W/omfFn9LZtb9OGDRv06quv6p9O/pMuzV7Sb/wv78m+LhMStrzq0Fhkvt/QX/3ziN5187t03XXX6cL//J9q/7VfW1TGsb+L6dVv/JXe+OdPrfbbKUumFaj7orXd/Jo09Ix08dVXtb6lRb8wTf341I915Xv/qLmR/6LWrVtlvviiHOfPy3Q49E+/+ddat327Zq67Ts9vfFUvTr2oO3fcqY0bN+r8+fN65tgz2tm1U7f23KqOjg7NzMzo+TPP6803vrlebxlYM1gLrADWAquOaDSqRCKhSCRS76rk4XtWA1/5ivShD0lXCsxW3NYmPfqotHfv/L5kUvJ4pJYWaW5ufptISFu2SLfeKp0/X6val6/Qe5MkhyP//01zfpvBP8VAxVgLDHUXjUaVTqc1MDCgUChU7+qg1vbulQ4fLvzc4cOLA8KWLdLWrVYIevhha7t1q7V/+3ZpdHT161wNhd6bJD3xhBWOpPmgk9m2tVnPA6gpboGh6uLxuLq7u+X3WxO1OZ1ORaPR7GPYzMJWnUK2b5eOHpXWrbNaRvx+6dIlqaNj/vmNGxu3FWi59yZZoejWW61gt9Dhw5LbvXp1A1AQLUDNaGxMuvNOa9uAvF6vfD5f9rHb7Sb82NFyrToLjY1J73mPdctLskJQJvxIVgC66eoQsmuukf7H/5Be//rVfw9LGRqS2tut1puhoeXf20ItLflbAHVBC1Azeuwx6dlnpccfl3p7612bRdLptEKhkCYnJ7OPDcNQOp3WaLPcykDlVmrVybXUNf2P/yi98IJ1/M9+Zu27eFG67jrpd39X+vSnq1ffzk5penrl1z3+uPSBD0gf/aj1eP16KRRa+r1lZALhjh3Shz8sPfKIdOxYcaEJQNURgJrFxIR0+rT1i+Dg1Wlln3pK+uAHrb4EmzdLN99c3zpe1d/fr0AgkNfqEwqFFI/H61gr1EVuIFjYqlPMNf1vCsyGaJpWAMno65Pe9CbpL/+ycB02bLCCx9Gjy9+mKib8fPzj82XndqBf+N4KKSUQAlh1tME2i127rL+MPR7p1Clr36lT1uPeXuv5BpBOp5VMJhft379/fx1qg4ZWzDX9B3+w/Dn8fqsPTc4t10WuvVY6dMhqZarUPfcU/9pCt6o7OuZHhBUTmgCsGgJQs2iSUSSGYUiSAoGABgYGNDw8rGQyKcMwlMj07wCk4q7pv/iLpa/tJ56QIhErSLzpTdINNxR+3enTVqDKtNws7IOz0s9OJrD09JR2uyr3th6AhkMAahalDiuuo3A4LMkaDRYKheTxeORyuRa1DCWTyaoNka/muVAj1bymt2+3bqk9/vh8qMrIhKrWVqmra3Gn7O5u6/lMIMoEnltvtTpb9/Za4erwYauc5UxMWB25k8n823rJpLV/YqL49wRgVdEHqBkVM6y4joLBoLxeryKRiOLxuFKplFKplPr7+/XCCy9kW4kOHjyonp6eqpRZzXOhRiYmpOefL/zc889bLS433yzdcot1ra9fL73vfdLXv251hL7llvxjOjqsVp7bbis83Pz735fe8IbFfXBOnZoPQleuWAHqzBnp7//e6rAcCBTfVyf3VnQmSGVu62Uw4SHQEGgBaialDCuuk3Q6rWg0KrfbrUgkovHxcZ09e1Y+n0/pdFpjOf0h4vG4vF5vVcqt5rlQI7t25XdmzvWBD8yHib4+6exZ6dw5a4bpc+esx319y5+/0HDzQn1wMp2T77zTGmnW32+Fsx078l9XjCa5VQ2AFqDm0gSjSFKp1KIRYIZh6MCBAxoZGVF3d7eSyaTi8Xh2Ozk5mQ0vmf1Op1OTk5N550kmkxobG5PT6VQ6nZbP51v2XGhwTzyx8nIZGblT2re05D9eqJTh5rkj0Q4dsvYdPGjVq5zRlUx4CDQNAlCzWW5YcQMZHBxULBbLPo7H4zIMQ+6cXwBer1fBYDD7eGRkRAcPHswet7BPz759+7IdqT0ej3w+X/Z8C8+FJrBaYaGUPxRW85ZVg9+qBuyOAISqc7vdGhgY0MDAQHYCRMMw9MILL2RfE4/H88KQZAWcp59+Wul0WvF4XC6XK+/5TEfnQCCQN6Ks0LnQZKodFor9QyG3FarQLavcVqhiMeEh0BQIQKgqt9udDSfLLX9x5MgRBQKB7OPMCLFUKpW9jZXpLJ0RiUQUCoU0PDysWCyWXW5j4bnQROodFlajFaoJblUDoBM06iQej6v36pIHyWRSk5OT6u3tlc/nKxh+UqmU/H6/zp49q2AwqIOZIcYFzoUmkgkLhw9bo60OH7YerzTcfDVUc40uJjwEGh4BCHXR3d0twzCyfYN6e3uza4dlRKNRpdNppVIpeXL+Qr/77rvVlzMCaOG50GTqHRaaYHQlgOrjFhjqwufzKR6Pq7u7W06nU5I1e3Q0Gs2O8tqzZ48Mw5BhGAqHw9m1xFKpVF6H50Lnwho1NiYFg9LwcPUWAl7pltVqlAmg7ghAqIvMbNG5lusztNxzhc6FNWqpVeMrtVyn6dUqE0BdEYAANLZiVo0vZa6eRi0TQE0RgAA0tnosL8GSFsCaRydoAI2tHstLsKQFsObRAgSgsdVjeQmWtADWPFqAqsSkObxp8L1qYtWcq6eRywSw6viJrlBra6sk6fLly3WuCYo1MzMjSWprowG0adRjrh7mBwLWNIfJn8OLTE9Pq6urS1NTU+pcbtXpq1KplNrb27V9+3Y5Mh0m0ZBmZ2c1MTGhtrY27dy5s97VQSlmZubn6jHN2iwvUY8yAZStlN/f/AlcBZs3b9bx48f10ksvqaurS+3t7QShBmKapmZnZ/Xaa69pampKc3Nz2rZtW72rhVIVu8Bps5cJoCYIQFWQSZmnT5/W8ePH61wbLKW1tVUbNmzQli1btG7dunpXBwBQRwSgKuns7FRnZ6cuX76s2dnZelcHC7S0tNAyBwDIIgBVWXt7u9rb2+tdDQAAsAxGgQEAANshAAEAANshAAEAANshAAEAANshAAEAANshAAEAANthGHwBmdVBpqen61wTAABQrMzv7WJW+SIAFXDu3DlJ0o4dO+pcEwAAUKpz586pq6tr2dewGGoBc3NzOnHihK677rq6zBw8PT2tHTt26NixY0Utxory8DnXBp9z7fBZ1wafc22U8zmbpqlz587pxhtvVEvL8r18aAEqoKWlRdu3b693NbLLa2B18TnXBp9z7fBZ1wafc22U+jmv1PKTQSdoAABgOwQgAABgOwSgBtTR0aEHHnhAHR0d9a7KmsbnXBt8zrXDZ10bfM61sdqfM52gAQCA7dACBAAAbIcABAAAbIcABAAAbIcABAAAbIeJEGsonU5raGhIPT09kqTx8XGFw2EZhlHU8R6PR4FAQF6vV06nU/F4XOFwWJFIRE6ncxVr3nySyaT27dunRCJR0nGVfo/sptzPmWu5eKlUSpFIROl0WqlUSoZhKBwOF/05cU0Xp9LPmWu6eJnPuqenR2fOnFEqldL+/fvldruLOr5q17SJmnG73WYikcg+Hh8fN51Op3n27NmijjcMw5SU/TIMwxwdHV2l2jafs2fPmn6/3/T7/abb7TbLubwr/R7ZQTU+Z67l4oyPj5t+vz9vXzAYNCWZ4+PjRZ2Da3pl1ficuaaLMz4+bgaDwbx9kUjElJR3nS6nWtc0AahGIpGI6Xa7F+33+XyLLoal+Hw+MxwOm8Fg0IzFYvwDtoxwOFzyL+ZqfI/sppzP2TS5lovl9/sLfjaGYRS8Vhfimi5OpZ+zaXJNFyscDpuGYeR9PmfPnjUlLQqhhVTzmuYWWI3EYjH19vYu2t/X16dIJKJwOLziOZxOp4LB4GpUD6rO9wjF4VouzqFDhzQ5OalYLJa33+v1amRkZMXjuaaLU+nnLHFNF8vtdi95S3BycnLF46t5TdMJukbi8bhcLtei/U6nU6lUSul0uvaVQh6+R2g0hf6hLwXXdHEq/ZxRPK/Xq0QikddfJx6PS5L279+/4vHVvKZpAaqB5b4hmYsglUqt2AEsnU4rGo1mHycSCYVCITrYVUG1vkcoDtdycUZHRwvuTyaTK35WXNPFq+RzzuCaLk88HtfQ0JBisVhRvwOXUs41TQCqgUyz3nI91Itp+pucnNSePXvyvtEej0eJRIIfsgpV63uE4nAtly8ejyuVSi35SzuDa7oyxX7OGVzTpUkmk4rH4zpy5Ii8Xq+8Xu+Kx1T7muYWWJ2V0lwXi8XyvvFOp1O9vb0KBALVrxiyuE1QfVzL5QsEAgoGg0X9wlgK1/TKSv2cuaZL43a7FQwGFYvF5HK5tHv3bqVSqbLPV841TQCqge7ubkmFv0GZtJp5Taky802gMqv5PUJxuJZXNjg4KK/XW1RHT67p8pXyOS+Ha7o4fr9fkvW5L6fa1zQBqAaKmZxppSbSQCCg4eHhJZ/nL7rKVON7hOJwLZdneHhYTqdTkUikqNdzTZen1M9Z4pquht7eXiWTyaL6+SynlGuaAFQjXq9X4+Pji/an02k5nc4Vv7GHDh0qePzk5KQMw2BW1yqo9HuE4nAtly4zFDu3RSKZTK54HNd0acr9nLmmi+dyuQq29OT2nVpONa9pAlCNDA4OFmwKHR0dlc/nW/F4v99f8C+SeDyebT5EZSr9HqE4XMulSSaTSqVSi+aYKebWCtd08Sr5nLmmi5dKpQrepsoEzZVGcFX1mi5p2kRUxOl05k2Nnpm+u9DrFs5oOT4+bobD4bx94XC44PGYn8Z+KYU+48z+Yr5HsJTzOXMtF298fNx0u91mOBzO+woGg6bX6817Ldd0+Sr9nLmmixcOhxcteTE6OmpKMiORSN7+1b6mGQZfQ5l5IZLJpAzDUCKRKHqIpdPplM/nUygUkmQ19xmGUbAp0M4yIy4OHTokSRoYGJDT6cx2alxJJd8jO6nkc+ZaLt7AwIBSqVTB2zDF/rXLNb2ySj9nruniBYNBjYyMKBKJyDCM7OKzo6OjRY+4q9Y17TBN0yz5KAAAgCZGHyAAAGA7BCAAAGA7BCAAAGA7BCAAAGA7BCAAAGA7BCAAAGA7BCAAAGA7BCAAAGA7BCAAa9rg4KAcDkf2a6XFFosVCoXyzptZSBNAc2ApDAC2EAwG1dPTU3AhxnIMDAyop6dHo6OjRS2YCaCxEIAA2EI4HK7q+bxer7xerwzDIAABTYhbYAAAwHYIQAAaViqVksPhkMvlWvRcIBCoqO9Npg9POp3W8PCwPB6PHA6HBgYGsquCR6PR7H6Xy6Xh4eGK3g+AxkEAAtCwnE6nwuGwUqlUXvhIJpOKRqPy+Xzy+XwVlTE4OKhIJKLe3l75fD7F43F5PB4NDg4qEAjI6XTK7/crlUopFAopGo1W+rYANAACEICGFgwG5Xa7FQqFsiO4BgcHZRiGDhw4UPH5JycnNT4+rkgkolgspmAwKEkaGRlRIpFQLBZTJBLR6OioJCkWi1VcJoD6IwABaHiZ0DE4OJgNQrFYTIZhVHzu/fv35z0eGBiQJPl8Prnd7ux+r9cryQpMAJofo8AANDyn06lIJKJAIKBkMim/358NJNU4d67MMPm+vr6qnB9AY6IFCEBT8Pv92f8PBAJVO281WpEANB8CEICmkBt69u3bV8eaAFgLCEAAGl48Hlc0GpXf71c4HFYymWRIOoCKEIAANLzMqK9IJFJwVBgAlIoABKChDQ4OKp1O5w0/zwx/HxwcrFe1ADQ5AhCAhjUyMqKRkRH5fL68UV9ut1vBYJBbYQDK5jBN06x3JQBgtQwODmpkZESr9U9dNBpVIBBQLBareFZqALVDCxAAALAdAhAAALAdAhAAW3A4HHI4HFUbOZZZTb6akzICqB2WwgCwpt199915y1pklrqo1MDAgHp6erKPc9cNA9D46AQNAABsh1tgAADAdghAAADAdghAAADAdghAAADAdghAAADAdghAAADAdghAAADAdghAAADAdghAAADAdv5/FDWsIq+eUX8AAAAASUVORK5CYII=", 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" ] @@ -277,15 +281,352 @@ }, { "cell_type": "code", - "execution_count": 193, + "execution_count": 260, "id": "18c54ab4-9d57-4af3-aa98-23762e4b0155", "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "unsupported operand type(s) for -: 'list' and 'list'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[260], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m MAE \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmean(np\u001b[38;5;241m.\u001b[39mmean(np\u001b[38;5;241m.\u001b[39mabs(\u001b[43msources_est\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43msources_gt\u001b[49m),\u001b[38;5;241m1\u001b[39m))\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMAE: \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;28mstr\u001b[39m(MAE)\u001b[38;5;241m+\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m[m]\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", + "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'list' and 'list'" + ] + } + ], + "source": [ + "MAE = np.mean(np.mean(np.abs(sources_est-sources_gt),1))\n", + "print('MAE: '+str(MAE)+ '[m]')" + ] + }, + { + "cell_type": "markdown", + "id": "c40a89e4-e4da-4186-9cd7-990f9c5342e3", + "metadata": {}, + "source": [ + "# SampleCNN model\n", + "Taken from: Sundar, Harshavardhan, et al. \"Raw waveform based end-to-end deep convolutional network for spatial localization of multiple acoustic sources.\" ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. https://ieeexplore.ieee.org/abstract/document/9054090 " + ] + }, + { + "cell_type": "code", + "execution_count": 261, + "id": "467f567e-8653-4cc4-82d2-2c97087b9038", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SampleCNNLoc(\n", + " (BasicBlock1): BasicBlock(\n", + " (conv): Conv1d(16, 64, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " (ReSE1): ReSE2Block(\n", + " (BasicBlock): BasicBlock(\n", + " (conv): Conv1d(64, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (dropout): Dropout1d(p=0.2, inplace=False)\n", + " (conv1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (SEBlock): SqueezeAndExcitationBlock(\n", + " (globalAvgPooling): AvgPool1d(kernel_size=(1706,), stride=(1706,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation1): ReLU()\n", + " (dense2): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation2): Sigmoid()\n", + " )\n", + " (activation): ReLU()\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (ReSE2): ReSE2Block(\n", + " (BasicBlock): BasicBlock(\n", + " (conv): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (dropout): Dropout1d(p=0.2, inplace=False)\n", + " (conv1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (SEBlock): SqueezeAndExcitationBlock(\n", + " (globalAvgPooling): AvgPool1d(kernel_size=(568,), stride=(568,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation1): ReLU()\n", + " (dense2): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation2): Sigmoid()\n", + " )\n", + " (activation): ReLU()\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (ReSE3): ReSE2Block(\n", + " (BasicBlock): BasicBlock(\n", + " (conv): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (dropout): Dropout1d(p=0.2, inplace=False)\n", + " (conv1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (SEBlock): SqueezeAndExcitationBlock(\n", + " (globalAvgPooling): AvgPool1d(kernel_size=(189,), stride=(189,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation1): ReLU()\n", + " (dense2): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation2): Sigmoid()\n", + " )\n", + " (activation): ReLU()\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (ReSE4): ReSE2Block(\n", + " (BasicBlock): BasicBlock(\n", + " (conv): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (dropout): Dropout1d(p=0.2, inplace=False)\n", + " (conv1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (SEBlock): SqueezeAndExcitationBlock(\n", + " (globalAvgPooling): AvgPool1d(kernel_size=(63,), stride=(63,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation1): ReLU()\n", + " (dense2): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation2): Sigmoid()\n", + " )\n", + " (activation): ReLU()\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (ReSE5): ReSE2Block(\n", + " (BasicBlock): BasicBlock(\n", + " (conv): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation): ReLU()\n", + " )\n", + " (dropout): Dropout1d(p=0.2, inplace=False)\n", + " (conv1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=same)\n", + " (bn1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (SEBlock): SqueezeAndExcitationBlock(\n", + " (globalAvgPooling): AvgPool1d(kernel_size=(21,), stride=(21,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation1): ReLU()\n", + " (dense2): Linear(in_features=128, out_features=128, bias=True)\n", + " (activation2): Sigmoid()\n", + " )\n", + " (activation): ReLU()\n", + " (pool1): MaxPool1d(kernel_size=3, stride=3, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (Avgpool1): AvgPool1d(kernel_size=(7,), stride=(7,), padding=(0,))\n", + " (dense1): Linear(in_features=128, out_features=256, bias=True)\n", + " (bn1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (activation1): ReLU()\n", + " (dr1): Dropout1d(p=0.5, inplace=False)\n", + " (output_dense): Linear(in_features=256, out_features=3, bias=True)\n", + ")" + ] + }, + "execution_count": 261, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load network model\n", + "saved_model_path_sample_cnn='/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/models/samplecnn/model_SNR_'+str(SNR)+'_T60_'+str(T60)+'.pth'\n", + "\n", + "model_sample_cnn = SampleCNNLoc()\n", + "model_sample_cnn.load_state_dict(torch.load(saved_model_path_sample_cnn))\n", + "model_sample_cnn.eval()" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "id": "3050cfe1-8e40-4922-97ca-41f35d54841e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of Network parameters for SampleCNN: 673475\n" + ] + } + ], + "source": [ + "def count_parameters(model):\n", + " return sum(p.numel() for p in model.parameters() if p.requires_grad)\n", + "print('Number of Network parameters for SampleCNN: '+str(count_parameters(model_sample_cnn)))" + ] + }, + { + "cell_type": "markdown", + "id": "51bc471c-b1c8-4967-a6b6-c3e2e6fbefaa", + "metadata": {}, + "source": [ + "### Localize one random source" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "66ac1814-216a-47a8-b437-2f1ad5cc6234", + "metadata": {}, + "outputs": [], + "source": [ + "idx_file = np.random.randint(0,len(files))\n", + "data_structure = np.load(str(files[idx_file]))\n", + "win_sig = data_structure['win_sig']\n", + "N_wins = win_sig.shape[-1]\n", + "idx_slice = np.random.randint(0,N_wins)\n", + "input_win_sig = win_sig[:,:,idx_slice]\n", + "src_loc_gt = data_structure['src_pos']\n", + "with torch.no_grad():\n", + " est_pos = model_sample_cnn(torch.Tensor(input_win_sig).unsqueeze(0))" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "79b643d6-bb61-4f85-be6b-60dfd4b602eb", + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MAE: 0.10374540494741245[m]\n" + "0.18061581756015432\n" + ] + }, + { + "data": { + "image/png": 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19AAAgOshUYhpt9sKgkClUmlse6fTibX/7u6u+v3+RI9NoVBQu90e22bbtqrVapLmAQCAayTRxN5Go6GNjY1zV3aRfQEAAI5L1BOzt7enzc1NeZ6nbrcrSer1enIcZ2x46SQn9dhMG44Kw1DNZnP02vd9ua576rDVYDDQYDAYvT48PDyzTQAAwEyJQky0oigMw9FQTxiGWl9f1+PHj2MFmZ/yPE9BEEwEnH6/r83NzdE8mCAIlMvl5Pv+iUFme3tbDx8+TNwGAABgntRwOBzGKRgEgTKZjGzbVq/XG3vPcRx5njexPY5MJqNSqTQx4XeaYrEo6eQenWk9Mffv39fBwYFWV1cTtw0AAFy9w8NDra2tnfn9HXtOTDqdlqSpvS2ZTGbUQ5NEuVxWoVCIFWAkja4Xc5KVlRWtrq6OPQAAwHKKHWJOW958fMgnrnq9Ltu2x64ZE3EcR/V6/cR9k4YlAACwfBKtTspms1MDRLQt7oXoouXUx3tgoonC0tFS7GlDU/1+X5Zlcb0YAACQLMQ4jqO9vb2J7U+fPlU2m40VLrrdroIgmLgGzPFhokqlMrWHxvM8VSqVJE0GAABLKvbE3kh0T6MoTHS7XT148GBiddK0CbtBEKhcLuuDDz4Y+8z9/X11u93RhN0gCNRut8eCTr1eV6PRSDR5OO7EIAAAsDjifn8nvu1AdL2W4/c1Om3Z83HFYlFBEIwNHUWOXwXYtm2VSiW5rivpaLjKsqxzrX4CAADLKXFPjEnoiQEAwDwzX2INAACwSAgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIx087w7uq6r27dva39/X5K0tbUly7LO3C8MQ21vb+v27duSpF6vp1qtNrFv3HIAAOB6ShxigiCQ4ziq1WrKZrOSjgLNRx99pFardeb+Dx480M7OzmjfIAiUy+Xk+/5YQIlbDgAAXE+Jh5PK5bIcxxmFC0nqdrtKp9Nn7ttsNiVpbF/btpXNZrW9vZ24HAAAuL4ShZh2u60gCFQqlca2dzodNRqNM/dvtVra2NiY2J7P59VutxOXAwAA11eiENNoNKaGi7g8z1Mmk5nYbtu2giBQGIaJygEAgOsr0ZyYvb09bW5uyvM8dbtdSUcTbn86vDTNacEjmuMSBIFs245Vblp9g8FAg8Fg9Prw8PDUNgEAAHMlCjFhGI56QqrV6mjb+vq6Hj9+fGqQ6ff7knTqpNx+vz96/6xy02xvb+vhw4en/xAAAGApxB5OCoJg9Hx8ToxlWdrc3FS5XD53I+IOD51VbmtrSwcHB6PH8+fPz90mAACw2GKHmGj10bTelkwmc+ZclWj/aWWinpV0Oh273DQrKytaXV0dewAAgOUUO8ScNrxzfK7KefaP2LYduxwAALjeEq1OymazU3tIom1nhYtCoaBerzd1/+MBJm45AABwfSUKMY7jaG9vb2L706dPlc1mzwwX5XJZnudNbO90OmPzbOKWAwAA11eiEFOpVGTb9uiKutLR1Xo9z9POzs5Y2UwmI9d1J/aXNBZQgiBQEASq1WqJywEAgOsr8b2TfN+X67pyHGdsW9x5KtH+3W5XlmXJ9311Op1zlwMAANdTajgcDufdiMtyeHiotbU1HRwcsFIJAABDxP3+TnwDSAAAgEVAiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIx0c94NWETffPONvvvuu3k3A+f02muv6fXXX593MwAAl4wQc8zh4aFevnypwWAw76bgglZWVvTuu+9qdXV13k0BAFwSQswPDg8P9ac//Ulvv/223n33Xb3++utKpVLzbhYSGg6H+uabb3RwcKA//elPkkSQAYAlRYj5wcuXL/X222/r3r17hBfD/fznP9c777yj//iP/9DLly8JMQCwpJjYq6M5MIPBQGtrawSYJZFKpbS2tqbBYKBvvvlm3s0BAFwCQow0msTLZNDlEh1PJmkDwHIixBxDL8xy4XgCwHIjxAAAACMRYgAAgJEIMQAAwEiEGFyKcrmsVCqlMAzn3RQAwJIixAAAACMRYuZk78We3v+X97X3Ym/eTbkUOzs76vV6sixr3k0BACypRCEml8up2WwqCAJJkud5KhaLo9enabfbcl031vDCReoxxcd//Fifff6ZPvnjJ/NuyqWwLEu2bc+7GQCAJZYoxARBIMdxlMlklEqlVC6X5bpurC+rIAhUr9d169YtpVKpiUexWJxJPYvsi/AL+S98df/c1aN/eyRJ+sO//UHdP3flv/D1RfjFnFt4xHXd0XyWer2uXC43OkbdbleS1Gw2R9szmYzq9frYZ0T7TQutruuO9s3lcnJdd6JMFFyj35co2AIAEEl076RCoaB8Pq/9/X3l83kVCoXYwwW9Xk/ValW3b9+eeO/Ro0dqNBozqWeR/fJ//XL03ykdXYjty//6UrlmbrR9+NvhVTfrROVyWUEQqFAoyLZttdtt5XI5lUoltdttlUolbWxsqNlsynVdWZalSqUi6eh4R4EnEoahcrmcgiCQbdsqlUrqdruq1+vyPE++70s6CkiO40g6+l2QjkKN4zjq9Xqq1WpX+K8AAFhUiUKMbduqVqvnqsiyrKlfPp7nybbtsV6Wi9SzyD79+0/1j//nH/Xt999qqKOwEj3fvHFT//w//3mOrZvU7/fV6/VGr13XVb1eV7vdlu/7ymazko7CTrFYVKvVGoWYaVzXVRAEqtVqY8fXcRw1m03V63VVq9VRIHr27NkovIZhqPX1dTWbTUIMAEDSFU7sjf6yPi4MQ3U6HZVKpatqxlx9+Lcf6slvnkx978lvnujDv/3wilt0uq2trbHX0ZBfqVQaBRjpx96Sfr9/6uc1m82pAbVWqymbzWp/f1+SRkNQx3vfLMuS7/t6/PjxuX4WAMDySdQTE4bh2LwE3/djz1WZVsZ13bFhpIvWMxgMNBgMRq8PDw/PbNe83NANfa/vR8+L6Kf/3ul0WpKUz+cTf1Y0tBQFnuOigBKJhqsymYxKpZKKxaI2NjaMnxMFAJitRCGm3+9rc3Nz9BdyEATK5XLyfT/xF0yz2RybzDuLera3t/Xw4cNE7bhqd966o7tv39X91fv69X//tX7/f3+v54fPdeetO/Nu2oRZzkOKVpZlMpkzy7ZaLdXrdTUaDdXr9dGk4UKhMOq1AQAg0XBSq9Ua+2KzbVsbGxtTh4rOUqvVThxGOm89W1tbOjg4GD2eP3+euF2X7d7qPX3+T5/ryW+eyNlw9OQ3T/T5P32ue6v35t20SxWFz2jI6CzValW9Xk+vXr0azbXxPG80MRgAgAvPibFtW57nJdqn3W4n/ms6Tj0rKytaXV0deyyilZsrSqWOVielUimt3FyZc4suXxRiTjqG0TLqIAjkuq7a7bako96gUqmkRqMxmtAbvQcAuN5ihxjHcSauBXJcknvkNBqNE4eFZlkPFkcURqIl1cdF14n54IMPlE6nVa/Xp14YMVopxdwYAICUYE7M7u6uNjc3J7b3+31ZlpVo/oTneSqXy5deDxbLzs6Out2uXNfVo0ePZNu2giBQt9sdW7VUqVTUbDa1vr4+mgjc7XYVBIGy2ey1Wc0GADhd7J6YSqUydSWR53mnXhvkp86azzCrerB4LMtSr9dTpVJRGIZqt9sKw3A0/yUSDR2l02m122212+3RdYaOr2ICAFxvqeFwGOsSsUEQqN1uj13jI1pBcvwLSNJoaexJF7eLLow27S/qJPWc5fDwUGtrazo4ODh1fsxf/vIXPXv2TOvr6/rZz36WqA4sLo4rAJgp7vd37OGk6DLx0fyFMAxHf1knkU6nT7054KzqAQAAyy12T4yJ6Im53jiuAGCmuN/fV3bbAQAAgFkixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYzES321UqlVK9Xp93UwAA1wQhBgAAGIkQMyd7e9L77x89AwCA5Agxc/Lxx9Jnn0mffDLvlpwsDEM5jqNMJqNbt26pXC6r2+2q3W6rXC4rDENJUrFYVC6XkyS5rqtUKiXP8+bYcgDAdUCIuUJffCH5vtTtSo8eHW37wx+OXvv+0fuLIgxD5XI5NZtNSVKhUFC329WDBw/06NEjtdvtUVnXdVWpVEblGo2GNjY25tJuAMD1cXPeDbhOfvnLH/87lTp6/vJL6YdODEnScHilTTqR67oKgkC1Wk3VanW03XGcUbCJFAoFpdNpNZtNFYvFUaABAOAy0RNzhT79VLr5Q2yMwkr0fPPm0fuLIAxDNZtNZbPZsQAjSbVabU6tAgBgHCHmCn34ofTkyfT3njw5en8RBEEg6aiH5acsy1I2m73qJgEAMIEQMyc3bow/L5IoxGQymanv27Z9lc0BAGCqBfwKXW537kh37x7Ng/nd746e79492r4oLMuSJPV6vanvR6uSAACYJyb2XrF796TPP5feeONocm+lIv31r9LKyrxb9qNoZdFJy6RZPg0AWAT0xMzBysqPq5NSqcUKMNJRT0ypVFK3251YieQ4zpxaBQDAOEIMptrZ2ZFlWXIcR7lcTuVyWZlMRru7u1Mn/EYajcZoeTYAAJeJEIOpLMvSs2fPVKlUFIahPM9TNpvVs2fPxspEstmsKpWK+v2+ms0m82YAAJeOOTGYqtvtyrIsNRqNifeCIBgLMJFGozG1PAAAl4GeGExVLpeVy+UmelQ8z1MQBFyVF0uLm7MC5qAnBlPVajWVy2Wtr6+rUqno9u3bevr0qdrttizL0tbW1rybCFyK4zdn5RZgwGKjJwZTlUoldTodbWxsqNlsjibrVioVvXr1aupwEmAqk27OCuBH9MTgRIVC4dSVSMCyMOnmrAB+RE8MgGvPlJuzAhhHTwyAa+/DD6Vf/Wq85yXy5InEPU+BxURPDAAcs8g3ZwUwjtMUAGTGzVkBjGM4CQBkxs1ZAYwjxADAD44HlkW8OSuAcQwnAQAAIyUKMblcTs1mc3SHYs/zVCwWY9+xOO7+YRjKdV3V63XV63U5jsMNBQEAwJhEw0lBEMhxnNFry7LUarVk2/ZM93/w4IF2dnaU/WFdYxAEyuVy8n2fK8UCAABJCUNMoVBQPp/X/v6+8vm8CoVColARZ/9msylJowAjSbZtK5vNant7W7VaLUmTAQDAkkoUYmzbVrVaPXdlcfZvtVramHLXtXw+r0ajQYgBAACSFnBir+d5ymQyE9tt21YQBMyNMVy321UqlVK9Xp93UwAAhkvUExOG4Wi4R5J835frurHnxJy1/2kBJRp2CoJgbKjpuMFgoMFgMHp9eHgYq10AAMA8iUJMv9/X5ubmWKCIJtzGCTJn7d/v9yXp1Hk2UZlptre39fDhw9g/z1zt7UnVqlSvS1OGzwAAwOkSDSe1Wq2xgGHbtjY2NsZWHF3W/nGGkba2tnRwcDB6PH/+PFa75uLjj6XPPpM++WTeLTlVs9lUsVjUrVu3dOvWLZXLZXW73alloyXzt27dUiqVGi2pjxSLReV+uMOe67pKpVLyPO9Kfg4AwPK58BV7bdse+6K6yP7pdFrS9MAS9cBEZaZZWVnRyiJfYvOLL6SXL48uBfro0dG2P/xB+od/kIZD6d13pV/8Yr5tPKZcLqvdbsuyLBUKBYVhqHa7rXa7rVarpVKpNCrbbDZHYbRQKEg6CjWO46jX66lWq42GDpvNpgqFgsrl8tRJ3AAAxBG7J8ZxnFMnY57VUxJn/zjLtePOv1lIv/zl0dBRLid9+eXRti+/PHq9sXH0/oKIwkqlUtGrV6/UarXU6XRG1+r56KOPxo6567qyLEuvXr1Sp9NRp9PRq1evZFnWKKQWCoVR0CkWi6pUKlz3BwBwbrFDzO7urnq93sT2fr8vy7LO/DKKu3+hUJhaLgxD2bZt9pfep59KN3/o/BoOx59v3jx6f0FEoaTRaIxtz2az2traUhiG2t3dHW2PAs3x42NZlnzf1+PHj6+iyQCAayb2cFKlUpl6jRbP81SpVGa2f7lcnlqu0+mMDV8Y6cMPpV/96qjn5aeePJFOWHU1D0EQnDhUuL+/L0ljYbNUKqndbiuTyahUKqlYLGpjY8PsnjMAwGIbxtTr9Ya1Wm1sW61WG9q2PVHWtu1htVq90P6dTmds32nlznJwcDCUNDw4ODi13Ndffz3893//9+HXX3+duI7EfH84lIbDGzfGn33/8uuOqdfrDSWd+ahUKmP7RcfzeJlCoTD0j/1svu8PJU38LlyGKz2uAICZifv9HbsnxrZtlUolua4r6cc5LNOGfi66f3T9mG63OxqS6HQ6cZu62O7cke7ele7fl379a+n3v5eePz/aviCi3pNSqaRWqxV7v2q1qmq1qjAM5XmeOp2Oms2mcrmcer0evTIAgJlKDYfRpIzlc3h4qLW1NR0cHGh1dfXEcn/5y1/07Nkzra+v62c/+9nlN2wwkN5442iV0nAo/fWv0oKtqspkMur3+3r16tXEe+12W51OZ7TaKAgCNRoN5fP5iSG/er0u13VVq9VUrVbV7XaVy+VGry/TlR9XAMBMxP3+XrjbDlwLKytHAUY6el6wACMdrSYLw3DiGj5BEKhcLqvZbI56VtLp9Cis/HSVWtTTRi8MAGDWCDGYqlqtKpvNqtlsji5yl8vlRve1Oj7MZFmWKpWKgiDQ+vq6yuWyyuWyMpmMms2mstnsRA9No9GQ67oKguBKfy4AwPIgxOBEvu+rVqvJtm21220FQaBCoSDf96eGklqtpnQ6PbrGjGVZqtVq8n1/VC6bzapSqajf76vZbHJDTwDAuTEnRsydWFYcVwAwE3NiAGBvT3r//aNnAEuHEANgeRlyo1UA53PhG0ACwEIx7EarAM6PEANguRy/kWp0KYPoRquR5Z0KCFwrDCcBWC4G3WgVwMXQEwNguRh0o1UAF0NPzDFLvNr8WuJ4QjdujD8DWCqc2ZJu/PA/uO+++27OLcEsRcfzBl9g1090o9VcTvrd746e795dqButArg4hpMkvf7663rttdf09ddf6+233553czAjX3/9tV577TW9/vrr824Krtq9e9Lnn/94o9VKZSFvtArgYvgTVVIqldKbb76pg4MDemOWxHfffaeDgwO9+eabSkUrVHC9GHCjVQAXQ0/MD+7cuaPPP/9cX3zxhdLptFZWVvjyM9BwONRgMFC/39f333+vOwwfAMDSIsT84I033tC9e/f08uVL/fnPf553c3BBb731lu7evas33nhj3k0BAFwSQswxb775pv7mb/5G3377rb799tt5NwfndPPmTd28ya82ACw7/k8/BV+CAAAsPib2AgAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYaanXEUd3MT48PJxzSwAAQFzR93b0PX6SpQ4xX331lSTp/v37c24JAABI6quvvtLa2tqJ76eGZ8Ucg33//fd68eKF3nnnnYn7IB0eHur+/ft6/vy5VldX59RCHMcxWSwcj8XC8VgsHI/LNRwO9dVXX+m9997TjRsnz3xZ6p6YGzdu6N69e6eWWV1d5RdwwXBMFgvHY7FwPBYLx+PynNYDE2FiLwAAMBIhBgAAGOnahpiVlRX99re/1crKyrybgh9wTBYLx2OxcDwWC8djMSz1xF4AALC8rm1PDAAAMBshBgAAGIkQAwAAjESIAQAARlq6EBOGoVzXVb1eV71el+M4CsMw9v65XE7NZlNBEEiSPM9TsVgcvcb5dLtd5XK5xPtd9HhiuvMeD86P2QqCQK7rynEcFYtFlcvlRP+WnB+zddHjwfkxB8Mlk81mh77vj173er2hbdvDV69exdrfsqyhpNHDsqxhp9O5pNYut1evXg0rlcqwUqkMs9ns8Dy/bhc9nvjRLI4H58fs9Hq9YaVSGdtWrVaHkoa9Xi/WZ3B+zM4sjgfnx9VbqiXWzWZTjUZDvu+PbS+Xy7JtW7Va7czPKJfLyufz2t/fVz6fV6FQkGVZl9Ti66Ner8t13TPvSHrcLI4npjvP8ZA4P2bJcRzVarWJf79bt27Jtu2J3/uf4vyYrYseD4nzYx6W6t5JrVZLGxsbE9vz+bwajUask9q2bVWr1ctoHhKaxfHEbHF+zM7u7q76/b5ardbY9kKhoHa7feb+nB+zddHjIXF+zMNSzYnxPE+ZTGZiu23bCoKAsWLDcDyxzKYFkCQ4P2broscD87E0PTGnnbBRd14QBMpms2d+TrPZHL32fV+u68q27Vk0EzHN6nhitjg/ZqfT6Uzd3u12z/z35PyYvYscjwjnx9VbmhDT7/cl6dTxx6jMWZ+zubk59j+CXC4n3/f5RbxCszqemC3Oj8vleZ6CIDjxCzXC+XE14h6PCOfH1Vuq4aSTJOlWbbVaY/9jsG1bGxsbchxn9g3DudBNPj+cH5fLcRxVq1UVCoVzfwbnx+wkPR6cH1dvaUJMOp2WNP0Ejv4iicokZdu2PM87d9uQ3GUeT8wW58dslMtlFQqFWBNyOT8uX5LjcRrOj8u1NCEmzjK2s7rzHMdRvV4/8X3+wrk6sziemC3Oj8tTr9dl27YajUas8pwflyvp8ZA4P+ZlaUKMdLQUrtfrTWwPw1C2bZ954u/u7k7dv9/vy7Is1vtfsYseT8wW58fliJbvHv+Lv9vtnrkf58flOO/x4PyYj6UKMeVyeWq3XafTUalUOnP/SqUyNXl7nqdKpTKTNiK+ix5PzBbnx+x1u10FQTBxbZE4ww+cH7N3kePB+TEn871g8OzZtj12mefoMtzTylWr1bFtvV5vWKvVxrbVarWp+yOZ6PLdJ5l2PKLtcY4nkjnP8eD8mK1erzfMZrPDWq029qhWq8NCoTBWlvPj8l30eHB+zMfSLLGOROvyu92uLMuS7/uxl8fZtq1SqSTXdSUddctaljW1ixDxRLPyd3d3JUnFYlG2bY8mzZ3lIscTky5yPDg/Ziu6MeC0oYq4PSmcH7Nz0ePB+TEfS3XvJAAAcH0s1ZwYAABwfRBiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADDS/werd492evkv3gAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "est_pos = est_pos.detach().numpy()[0]\n", + "\n", + "plt.figure()\n", + "plt.plot(mics[0,:],mics[1,:],'g*')\n", + "plt.plot(src_loc_gt[0],src_loc_gt[1],'b*')\n", + "plt.plot(est_pos[0],est_pos[1],'r*')\n", + "plt.legend(['mics','gt','est'])\n", + "\n", + "print(str(np.linalg.norm(est_pos-src_loc_gt)))" + ] + }, + { + "cell_type": "markdown", + "id": "db70ec94-2898-4f13-abd8-13b19be477d8", + "metadata": {}, + "source": [ + "### Localize all sources per each window" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "f1a012ee-7ec0-4f53-baa4-2c95a10d2a9b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 12%|███████████████████████▊ | 34/285 [00:47<05:54, 1.41s/it]\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[57], line 14\u001b[0m\n\u001b[1;32m 12\u001b[0m input_win_sig \u001b[38;5;241m=\u001b[39m win_sig[:,:,n_w]\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[0;32m---> 14\u001b[0m est_pos \u001b[38;5;241m=\u001b[39m \u001b[43mmodel_sample_cnn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_win_sig\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munsqueeze\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mdetach()\u001b[38;5;241m.\u001b[39mnumpy()[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 15\u001b[0m sources_est\u001b[38;5;241m.\u001b[39mappend(est_pos)\n\u001b[1;32m 16\u001b[0m sources_gt\u001b[38;5;241m.\u001b[39mappend(data_structure[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msrc_pos\u001b[39m\u001b[38;5;124m'\u001b[39m])\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/network_lib.py:165\u001b[0m, in \u001b[0;36mSampleCNNLoc.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 163\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mReSE1(x)\n\u001b[1;32m 164\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mReSE2(x)\n\u001b[0;32m--> 165\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mReSE3\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 166\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mReSE4(x)\n\u001b[1;32m 167\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mReSE5(x)\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/network_lib.py:128\u001b[0m, in \u001b[0;36mReSE2Block.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 127\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[0;32m--> 128\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mBasicBlock\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 129\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdropout(x)\n\u001b[1;32m 130\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconv1(x)\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/network_lib.py:91\u001b[0m, in \u001b[0;36mBasicBlock.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[1;32m 90\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconv(x)\n\u001b[0;32m---> 91\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 92\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mactivation(x)\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m x\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1516\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1517\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1518\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1525\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1526\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1527\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1530\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py:171\u001b[0m, in \u001b[0;36m_BatchNorm.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 164\u001b[0m bn_training \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrunning_mean \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;129;01mand\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrunning_var \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 166\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;124;03mBuffers are only updated if they are to be tracked and we are in training mode. Thus they only need to be\u001b[39;00m\n\u001b[1;32m 168\u001b[0m \u001b[38;5;124;03mpassed when the update should occur (i.e. in training mode when they are tracked), or when buffer stats are\u001b[39;00m\n\u001b[1;32m 169\u001b[0m \u001b[38;5;124;03mused for normalization (i.e. in eval mode when buffers are not None).\u001b[39;00m\n\u001b[1;32m 170\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 171\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbatch_norm\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 172\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 173\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# If buffers are not to be tracked, ensure that they won't be updated\u001b[39;49;00m\n\u001b[1;32m 174\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrunning_mean\u001b[49m\n\u001b[1;32m 175\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtraining\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrack_running_stats\u001b[49m\n\u001b[1;32m 176\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 177\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrunning_var\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtraining\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrack_running_stats\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 178\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 179\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 180\u001b[0m \u001b[43m \u001b[49m\u001b[43mbn_training\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 181\u001b[0m \u001b[43m \u001b[49m\u001b[43mexponential_average_factor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 182\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43meps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 183\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/nas/home/lcomanducci/miniconda3/envs/xai2/lib/python3.9/site-packages/torch/nn/functional.py:2478\u001b[0m, in \u001b[0;36mbatch_norm\u001b[0;34m(input, running_mean, running_var, weight, bias, training, momentum, eps)\u001b[0m\n\u001b[1;32m 2475\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m training:\n\u001b[1;32m 2476\u001b[0m _verify_batch_size(\u001b[38;5;28minput\u001b[39m\u001b[38;5;241m.\u001b[39msize())\n\u001b[0;32m-> 2478\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbatch_norm\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2479\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrunning_mean\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrunning_var\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtraining\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmomentum\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43meps\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbackends\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcudnn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43menabled\u001b[49m\n\u001b[1;32m 2480\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "sources_est = []\n", + "sources_gt = []\n", + "N_sources = len(files)\n", + "for n_s in tqdm(range(len(files))):\n", + " data_structure = np.load(str(files[n_s]))\n", + " win_sig = data_structure['win_sig']\n", + "\n", + " N_wins = win_sig.shape[-1]\n", + " sources_win = []\n", + "\n", + " for n_w in range(N_wins):\n", + " input_win_sig = win_sig[:,:,n_w]\n", + " with torch.no_grad():\n", + " est_pos = model_sample_cnn(torch.Tensor(input_win_sig).unsqueeze(0)).detach().numpy()[0]\n", + " sources_est.append(est_pos)\n", + " sources_gt.append(data_structure['src_pos'])\n", + "sources_est = np.array(sources_est)\n", + "sources_gt = np.array(sources_gt)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce58bdc7-03f4-40fc-b6d3-9d370baaa188", + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure()\n", + "plt.plot(mics[0,:],mics[1,:],'b*')\n", + "plt.plot(sources_gt[:,0],sources_gt[:,1],'g*')\n", + "plt.plot(sources_est[:,0],sources_est[:,1],'r*')\n", + "plt.xlabel('x [m]'),plt.ylabel('y [m]')\n", + "plt.legend(['$\\mathbf{m}$','$\\mathbf{s}_{test}$','$\\hat{\\mathbf{s}}_{test}$'], fontsize=15)\n", + "plt.axis('equal')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "df5f2e8b-4f7e-4d97-b70a-fd9b8438dbe8", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "unsupported operand type(s) for -: 'list' and 'list'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[58], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m MAE \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmean(np\u001b[38;5;241m.\u001b[39mmean(np\u001b[38;5;241m.\u001b[39mabs(\u001b[43msources_est\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43msources_gt\u001b[49m),\u001b[38;5;241m1\u001b[39m))\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMAE: \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;28mstr\u001b[39m(MAE)\u001b[38;5;241m+\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m[m]\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", + "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'list' and 'list'" ] } ], @@ -304,14 +645,15 @@ }, { "cell_type": "code", - "execution_count": 288, + "execution_count": 289, "id": "07f0b669-a0f3-4226-a28e-8a3e15dcaafa", "metadata": {}, "outputs": [], "source": [ "# Extract one random source\n", "n_s = np.random.randint(len(files))\n", - "#n_s = 29 # N.B. Fixed if you want to reproduce paper exact same results!!!!!!\n", + "if source_fixed == True:\n", + " n_s = source_fixed_num # N.B. Fixed if you want to reproduce paper exact same results!!!!!!\n", "data_structure = np.load(str(files[n_s]))\n", "win_sig = data_structure['win_sig']\n", "sources_gt[n_s] = data_structure['src_pos']\n", @@ -320,17 +662,38 @@ }, { "cell_type": "code", - "execution_count": 310, + "execution_count": 290, + "id": "8bc75a4b-3a03-41c2-a97c-d20b21f06343", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "50" + ] + }, + "execution_count": 290, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_s" + ] + }, + { + "cell_type": "code", + "execution_count": 291, "id": "8e9f4520-2f08-46a3-b14a-3261246bc5bd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([1.48125 , 5.375 , 1.33693965])" + "array([1.48125 , 5.4375 , 1.23807996])" ] }, - "execution_count": 310, + "execution_count": 291, "metadata": {}, "output_type": "execute_result" } @@ -341,7 +704,7 @@ }, { "cell_type": "code", - "execution_count": 289, + "execution_count": 292, "id": "2abecab9-f47e-46bd-a3a3-f1d19ffe44b1", "metadata": {}, "outputs": [], @@ -351,32 +714,40 @@ "output_gt = output_gt.repeat(N_wins,1)" ] }, + { + "cell_type": "markdown", + "id": "a1587e58-ec6c-40b1-bce1-4eb5adf5985f", + "metadata": {}, + "source": [ + "### Loc-CNN" + ] + }, { "cell_type": "code", - "execution_count": 290, + "execution_count": 293, "id": "15c8c505-539d-49b4-8037-8262acbac8dc", "metadata": {}, "outputs": [], "source": [ "# Apply LRP\n", - "with Gradient(model=model, composite=composite) as attributor:\n", - " out, relevance = attributor(data, output_gt)\n", + "with Gradient(model=model_loc_cnn, composite=composite_loc_cnn) as attributor:\n", + " out, relevance_loc_cnn = attributor(data, output_gt)\n", "\n", "data = data.detach().numpy()\n", - "relevance = relevance.detach().numpy()" + "relevance_loc_cnn = relevance_loc_cnn.detach().numpy()" ] }, { "cell_type": "code", - "execution_count": 291, + "execution_count": 294, "id": "47523f30-b484-4470-adcb-8ee5257ed992", "metadata": {}, "outputs": [ { "data": { - "image/png": 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hdfiZheq2bqkfC5zpnvQ6yzacBe7ll1/WlgsXy9a2bVvtvuEscG6WWJOQNcHvj5qYDLF9+3a89tprtTLxQji5EAF3AqFb0DxS1q1bh2HDhrnGlNRl+vfvj8suuwwPPfSQ77LvvPMOAOCJJ57wVc6rgOO52/ggTgWNHwHnZ6H0aLhQ/Vj1TO5PU7lGjRrZ/nazRJkEHM0lB7gH9puWiOL7utWlKxepC9XNehbOAudWXzjhF6kFjuLHhep2f4azwLldB9OkEwAoLS3F8OHDrWWzFHQWren44fAzaWLQoEEYMmQIrr766ojqEgSviIA7QQgEAkhOTsby5ct9l83Pz0e/fv2wadMm67vLLrsMS5YsQa9evaLZzBMCtS7oggULIj6G3wc5HTBMAo6LMtOAxd2NfJCIlguVCrNIXagmIWZaSisaws8k4Dh5eXna44cTYrSO1q1bu5bz6kKtqKiw9bVX92qkFrhIBVy4RL5e2gyY88KZZvh6FcThLHAzZsxAfn4+zj33XNv3pqXI/ODH2q/Szrz44osR1SUIXhEBdwJAH3AXXXSR9Xn//v0oKCjAkCFD8Ne//tW1/PDhw/HRRx9h9OjR1ncq0L6mzfjfffcdzjvvPLz++uvVXlekgcyAvwcyAPzhD39wrZcO1NwCxwcMam3hYs8kmvwIOFPMGN3GLWC8nMmlSklMTHTdz4/rlfajScCZRMbatWu1+/F2cMsPreO3v/2tazmThcwkOPjfyhLMy5mEF1D9Ao6Xa9q0qbacHwHn5tYGzCtbmGbZ8vqWLVsGHdGywEXTOyII0SIu/C6VbNy4EeXl5VGtnMbAnMy4PVSuuuoqvPrqq9bfEydOtCUxBYCPP/7Y+vzTTz9Zn2sr/mLUqFFYtWoVLrnkkmrP1VSVGWVVWcKHXy+6oLrJhQpUivJTTjkFgN5aR4PmvbpQw1ngjh8/bqXiMIka3d+qjXxbKBSyrG3dunWzZlKGQiEcP37c6gc/Fjg3l6fJPZeUlOR6fD8xW277+lnhwI+AKy4u9lSf10kM4YRfpC5Ut+TH0RJwJgvcoUOHrJcMkyUScLcsRyrg+PEOHTrkmAnrRnJysmNSiSBUB54F3LBhw5CRkRG1QXnevHmOgO+TFfrQuvDCC63PVLwBwHvvvecQcP/3f/9nfY7k2jz22GN47733sGjRIivb/65duzB37lyMHDnSkX8sHDzXmRufffYZ7rjjDixZssS20DYAfPjhhzj11FPRpUsXRzlTMthw0Mz1bgJu48aNaNeunXEFAT5Y9e7d2/ocTsDRBzt3N5oGT5OQCBcD57avF8udEn46kajEJi939OhRTwLOJDq8WuAOHTpkE5MXXXQR3n77bcd+vC6TBc6PgHMTUdFyTVaHC9Xk0vQq4Ewu6YqKClu5H3/80bU+fh3oSyjdFukkhkgFHN9v8+bNaNGihaeyjRs3tn7n9N4UhGjjWcCFQiFMnz49ahX7nQVYn/niiy+sz/369XPdL1wC2R9++MH63Lx5c0eqBM7OnTsxefJkAJWpE+644w4AQFZWFv75z3/i8ccftz18KZs3b8bSpUuxd+9eTJgwwRJhPOmqjqeeegoTJkwAUGm9oXW8+uqruOyyywDoBSl1MfshFArZZsbpBtSHH34Yt956K2bPnm3L8B8uDoq+iPCHtc4Cp9AJH0q0XKhuwiKcBS6cZUgJOL5t//79lmUsGhY4/r3OOqJWjqBtVrGS/HtVxq3uaFjg/EwOqA4LXLQmMURigePi57777sPw4cO15ahI27dvn+33YRJwJqvszp07LdcvF3C63/3WrVuxd+9e28sxvz+eeuopzJkzx1FWB30GrFmzBmlpaZ7KCYJfPMfAjRgxIqoVR/t4dZn09HTrs+lB3759e8/H/NWvfmV91rm+N23ahGbNmll/33nnndbngoICAM4s9JS0tDTcdNNNuP32223t9yLglHjjdbz22muWeHPjo48+0n6/f/9+DB061DVwuKKiwjgbDgBuvfVWAMBtt91m+z7c4EEJ58ryM1hH04Wqq4MH2pti5/yIu4ULF2q3cXenOoaydroJODqY6n4fbtvpS2I4AUdDEUznFq0YuA4dOmjL1fYkhmgIOP77oM8Hkwu1pKTEdVs41ysVfvSFirdFZ4Fr2bIlunTpYlsRg1sGTS/WHLpusZ+wo7KyMjRp0gR///vfPZcRTm48Czg+qIVj9+7deOmll6J2vJMFk6uFPzTLyspsf7dp08YakOlbIHe7AsArr7ziWg8tO2XKFO0+9GFXXFyM+fPnY9SoUcb8ZDpSUlKsz//4xz9s2/zE8Q0fPhwvvfQSrrrqKqxfv944oxMwWzbCJRetioDzmjeMH4vvSxMG8/ZG6m71M4nCdB50JrVp/VHVruTkZADeYuB0vw/TeqRu35uC0msiBo6+6ERqgfOapoRv92qBq6iosP0GTUKaHpP/Pk499VTXdtLrwMMPTBY4/qzw2i9cwN11113W5y+//NL6zAWi14TUvCy3AJpo164d9u7di3vuuQe7du3yXE44eam2WagpKSno0aMHHnzwQVuQt2CHJi8FvLtaAGcQf9euXXHuuefij3/8o02E6WINTQ8kWjY3N9fTzMLrrrsOCxYswDfffGN916dPH9c6FFRocdHlJxD4jTfesD536dLFthYjEF5YzZw50/XYfuJvwg3cfsSBSUBRqJgGzJY0P1a+SF24ffv2dT0GvcaqLeEEnMkS42W7ro2mcITqEHCmxMGRukKjMYnBz/1pEsomAWd6OTKJNHpf821vvvmm7e/TTz/d+kz7mv9W+d/333+/9dntntP97UYoFLJZ3UxL0JmQFSMEL0RFwL3zzjto2rQpYmNj0bt3bzz00EPYuHEjOnbsiNtuu03i3QzQoF3glweVTvTyhxi1XgGVKRSKiorwyiuvOAZjPrnATRzRmYeKp59+2vY3Fwxu0Jl2bpiEicmFGw7qEtbVw/uHvolzwg2Opm1VscCZxBWFx+b4scBxi4vbNi8TDn79618DsL8weHE5KgE3ceJEbTk3saOgqUPodjc3JeAckKnbK1IBZxLKPMGsmzWrttOImI7pNeGwScDxRelNbaFWNt6WcePG2f7msXRuxzS9fNF7gN8fXtOIHDhwwFZHpAJOZrEKXoiKgMvNzcW8efOwePFipKenY86cOejUqRN69+6NWbNmYfXq1dGopl7C11pUD6rzzjvPsW84Vx51y/AHDp+AooK+FS1btsSf/vQntGnTxvHQef75521/+3m40OTCgNPKRt+W+bY//vGPtr8jXWEAcPYdddf8+9//NpaNdEah7u9IZzj+8MMPaNWqFZYuXYpvvvkGDRs2dG2Dn2W3Io1z021r3rw5APvLghcxqV5Wdu/ebd0D4Sxw9PpRi7HXmC36+wiFQtU+iYHj5hYOl/Mu0kkMbitUeJ1VC9h/q5Fa4D744APbNpN7/IILLnDdxmeEUtFGP4ezwJ1//vnacvz56dUCx70dkQo4ry/JwslNVATcwIEDMXToUAwdOhQzZszA+vXrsWrVKgwYMADLly/HsGHDolFNvUQ34P/www+2lBdu+/KHERWD3GXz6aef2v7u2LGj4/gvvPACtmzZ4pi9anoTDwedCQiYH4TcAvTtt9/a/jalEOnZs6exHfwclJWxoKAAl156qa+y6jrwSQB0m5e//Qg4oPKhnpmZibPOOsvRF15FR6QTJbxY0ho3bgzAPvh5KUctH6psOAEXFxdnveS4LQHmNQ9cpMKV/63rZ7dQBTcLXLj4y0gtcG5uxUgtcF4tfPzvQYMG2baZZq+q+0nXTv4coeKLnmu4Zyb9mx4jnAXu4MGDOPvsszFy5Ejb99zT4VXA8fpMidsFQeE5jYhf0tLSZPq0B3QPFOWK4pge5oD9YcVFFv+bP9hMLjr6lgr4y0rOhYYpqDdcHjuTgOMB0Bw+EKv9f//73xvLAfpBrqKiwjpGy5YtrTfmqsxCDXd9TRw5cgRxcXGoqKhwhCyYYsS8zrj0MolBWQXpoGwqpz6npqZa66Du27cPycnJYV2o8fHx2uTEXoP1//e//+HgwYNo0KCBUfxUNQauUaNG1iBOExy7tU1dq6SkJBw6dMhozTKJLdNkAVO/mKy10YiBU8+ZU089FVu3bjWKSa9LcB05csS23Y8Fjp4Tfb6EE3Bz5szBV199ha+++grz58+3ZlhzAbd37154gce8ebX4KSTf3MlJVCxwGRkZxhmngjv8gcJjRCjh0lmYgnC5COPbTQKOpiQB/Fng+BuoTsCFQiEcPHiwSgIu3IxVPuCYMviHK3vkyBGbldIUbG0S2dEWcEBl3inOb37zG9f2vf/++9ZnPzFwOpGjYtlMAk53TLoUl7o/wlng4uPj8d133wEAPv/8c+3xdUKFWqlvuOEGz+emrIR+04ioPqHtMa2Tqj6rmZt8NqJXF6pJuJiEEc1J6XXdV77Ni+hUKyx4FWmmbfyZEqmAM1ng+N8q5RBgv0ZcsHm1wHGvx8UXX+ypHADcfPPNiImJQadOnTyXUYRCoWpfMUeoPqIi4Hr06IGFCxfi9ttv9/zGIVTCHyh+UlTwsqYYMb6qAX+jNAkg08yxcIQTcMnJyRg1ahRatGjhmjRYEU0BFy5GiaKzwLlZ/LzEwB04cACPP/542BnIfgScum/c+kgNQLw9NLyB3z8XXXSRtRqIn8kIXixwNEUF7UvVfm4JUn9TF6qywM2bN8/RFkAvduj6r//617+0bdRN7FAi068Fjgo49Z0XN6xKjG1aSUBXt2onvwZuEyx4W+gLgBcBp+rzaoFTn70ION025ZL2KuDCvfS6CTg/zzwa7sKF3u7dux37b9myBS+99JLtmvD9/GRuUJM9+PMkHKNHj0ZMTAxiYmJqbelFoWpERcANHz4cpaWleOqpp5CamoouXbpgwoQJePnllyMO4jxZ4IO0KTg9nHXHJEr4g4tb0Uw/YP5QqooFjguMhg0b4vnnn8e+ffuwYcMG47F04mTbtm1YuXKlYxBWAfWKcNYuSo8ePYz7Hj161FUshxNwOTk5yM7OxqRJkxxJh6NhgXNrlxpkTBMw+D2wadMmK7GyaTUKkwvVTfC4CS1dDBzwyz1IXajXXHMNANgsD1x8qePoBJxbG3UWOL8Cjotaep5eBJyK/zp+/Lgnt7D6rLsGJre56X4wWa+41bU6LHC6+0j1i0nAUSMCPwf+LKP7mlyoJpcmncHOz133Utq7d28MHToUTz75pLZuAHjrrbdc66NUZWnBZ5991vrsdQnEqlBeXo4LLrgATz31VLXXdbIQtUkMRUVF2LlzJ9atW4exY8eipKQEQ4cOxa9+9auIlz86GeBvWjwbOSXc26Qp+WM4AWcyo/O3Tz8CjmciVw9b5cryYwnjD2r1svC73/0O//nPf2zb+IoQukHTre5w6T1MAi5cLNKPP/6I2bNnhy3L15N0Q7mC1UDldh2VkPYj4Cj8fKlL3k8MnDonem50fzcBp86PulDVOsDULeomoLkAMJ2bScDt2bPHdXF2nTBKTEy0rEbqO1196rrphKZbrjRd3eoaUFeoScD5eenT1adms+usbLq/1TFUO93Oh9evtnkRcDrXqxKaPBWK2+xVk9Dj0Jn2qtwpp5wCwGlZO3bsmCXq6Aucl2dqVlaWIwE+n+zGc4N6xY9XhTJ//nxcddVVnl42H3roIXzwwQe2lXiEqhEVARcMBjFr1ixs3LgRwWAQt912G5YvX46KigqsWrUKY8eOjUY19RI/Vhb+I4/ExabwM02+Ki5ULkjVQ1K5iExuXx6npt42lXWtoqJC66Kg+yp0wdpub6/h3K1VscCZ+P77763PXq5tIBBwiCa3AVm1w9Qe07Xwsk3nQnXrDzeLjZuAU/tQF6q6P7wE13OBQzGJbh4DB/yS9Pn48eM20as7b91kC901UvVQMayC0unvPpwLlYpZJdpNcZim+8FkSeMWRtMsVF2/6MpFS8DpZraq5w39zfPnqc6FqoQ7t6S1a9fO+vzb3/7W+qzapZYp5M8Yms7pk08+sT6r/ej1o+3bs2cPHnzwQcyaNcua8EPPTxFp7kyej9Qr1113HV588UXbyjBuiDcu+kRFwKWnp+Nvf/sbSkpKHBcpLS0NQ4cOjUY19RI/YsgUDxMONwucyppvir2riguVz65S56CSEJuEAT8/9ZBTD2M/7h+d1YMunUMJJ8KOHDlSLQKOvpl6ubaJiYkOS6bbdXRz3+n20WEqx8WRKfhcJ2J0+QvDCbj4+HjL+uNliSfqeuV4mWFLJ1ooqznvL51lLj4+3hJ/pmvALZPx8fFagermQlX10e2bN2/WtlNXbsiQIY7tJuEXqQVOfa5OAacTuToBx8vRbcqleNZZZwFwWrqohVTnem3atKljGwDcfffd1udWrVo52kLTrIwZM8b6TF+Ei4qKtHUD+klMOviLry7v6IIFC9CzZ0/897//dWw7evQosrKyrL+95K177bXXrM+jR4+OKF7+iSeewD333CMTL/5/PAs4L0GV6enpaNKkSdSOVxXKy8uRnZ2NmTNnYubMmRg3bpyvhYVrCvVwPu2008Lua3rTDIebBU7nUuJUxQLH61UPHCXgTKKBz9bjZU3t4PXyvvvxxx/xu9/9TlvWiwUunKXL7W+veBFwsbGx1gQAJTTc7gkvFjhTnZFa4HiSZNVvqh2BQMA2gz2cC1UncEyCUbVFHY8nzr7//vt9C7hnn30WFRUVjrrcBBy3wOn6kgu4uLg4qz9Vn4RCIYeI4q5XmndODZAmAac+d+/e3fpO9ZmXWDZVxzvvvOMobyrnxYWqu65KONFtXAiYLHD0Gpli59RnJbL4SytdMlAn4JQFbs+ePbZnWLdu3azPl1xyifVZCcaWLVta31Gr1rXXXmt9Hj58uOs53HzzzfACFZJujBo1CsXFxQ4P2po1a5CQkIAHH3zQ+i4nJyfs8egki2effRbp6eme2gpUrmTSoUMHTJw4EX//+99tS6CFQy3h5+atCcdnn33mSEB9ouBZwEU7GW91J/dNT0/HiBEjkJWVhaysLGRnZ6Nnz54nnIjzI6SqYoHjGcLVA8mL4K5KDBxvI7fAhRM4dLDjFjgTPIZMuQjUoF/VBenp2qt+ynrFy31K84qFE3A8hsy0j1td4bYpwbFx40asW7dOK7C5BS4uLg79+/e3BrNIXKhlZWXWvRFu0gQXcHfddZdx8ohOwAGV7m6TpYnWF4kFLi4uzrJuqT7RhTnwSRo0/YQSIaaXCi6MAKeAM7lJeYohuk03Q7WmXaiqnGonFVvcekUHeJMrlD//TAIOAJ577jnrM03ps3DhQscx6POYZg6gYofWp3OZfvPNN9bzfsGCBQgEAnj55Zdt+/CVLABYaXk4y5cvt/0dSX5Xmq5IwZeXc2Pv3r0499xzbZZALwL0s88+QyAQQFxcHGJiYpCamup7VaiKigqcd955uOCCC/Duu+9i3759J5T1z7OAC4VC2LhxY1T+bdiwoVo7Ye7cuQDsN1owGERaWppjSanapiqWMPUg8WK9+3//7/9FXK+bC7VXr15hy7pZwvg6rm7QgVwNSMo94aesEnDt27cPW86LBc6t/XQQ+uSTT1wfiiaOHz/uSPvith8XcPRa0dmZJgucKhupgFP9QwfzM844Q1sXb4eyTnGx4ibg1EN/zZo1tuXgsrOzEQqFXK1pbgJOV5fOAseFyuHDh7XCSD3XdBY4PpOWxnhyARcbG+voE52o103SUL9LkwWOW+6SkpKse0m1k6f80KUKoVYkhamcTsCp2cI8VUiks1B1LludgDOlH1F1U1eo6jMu/MIJuNGjR2vroBY/msB5/PjxAIABAwZY2+m6sJR77rnH8d1ZZ52FU045BaFQCKNGjQIAXHHFFbZ9aEyn4owzzrAmwkU6GcKN/v37a7/38oL70EMPab83JYUH9G5hL2OWOvYLL7xgmymcnp6Oxo0b4/rrr/d0jJrA80oMI0aMwIwZM6JWsdeOjIT8/Hzt8Xv37o28vDzk5uZWW91+UQ9nXXoDt32BSnP0fffdB8CeqsArSoRVxYXau3dvWzyGDjcB58WKBtgHV1VW99av49ixY5YVQD2YWrRoYZssoCOcG/Sdd95B586djWXXrVvnSJ7sxhlnnIFvv/3WEoVeg33pahCqn5Rr57zzzrOlBjAJuMOHDyM5Odl3DJzK/s7XQlXt0dWlszQB4QWcaht9k6cCaP78+bZBLhAI2FyObgJuyJAhWoHOz43Hzh08eFDbX8eOHUN8fLxNwKnP559/vi0nW1xcHGJjY219ZbLAqXs4OTnZ+v0ePXrUtppEfHy8w82o2pmQkGBLJhwbG2uzaCYmJuLAgQMOC1yjRo3w888/ayee0OdHRUUFYmJibNt27NhhjIE7cuQI+vTpg6NHj1quQbV6RTgL3HPPPYeEhATj6hXchUpjybgQo6KQC7GKigocPnwYSUlJtskH/DiqHH+uhkIhVFRUWHkVOfQcVBJnmqCac+zYMcTFxSEtLQ3r169Ho0aNHIKGhyl999136Nq1KwD38JMbb7wRL7zwgi/3ZjgKCgpct+Xm5uLOO+80ll+0aJH2+8aNG6OiokK7AgVN7cKhL75uTJ48Gc8884x22zPPPIN7770Xbdu2NR6jJvAs4Pj05ROZwsJCrUgLBoMoLS1FeXm5ZwFR3fixhFHTPb25vFizuOBQ9fp1oW7dutVaqslL2XAu1HDQwdWv+NOlqjDl2dOVA/Q5kvLy8rRl1UBD0ziEo1evXvj222+tAdtrbGNMTIxDwD388MMAKte+DQaD1r4rVqzAkCFDtKLq4MGDRgF36NAhW4yT4ujRo0hISHAMrnQ7Jz09HTt37nRMKvBqgRs8eDDeffdd9O3b1ybgGjdubKuvQYMGOHDggFYYFRcXW9b5M844wzbTlLo54+PjrW38gb9v3z6b+KGB//Hx8bbzUwHeytJE2xIXF2f7joo7NcmmqKgIAwcOtFmg1bNAJ4h5bCAVTdSVHhsb64gpPHDggFWOCjh6HPqZvngePXoUiYmJnixw6ne4detWKw2HSgvTuHHjsAJuy5YtVlyYWje0efPmKCsrs004UHVTa+3evXvRuHFj63miBDEVcNwCp44xa9YshwdAJ+BofWofmm6E9gEtl5SUZMV3rVmzBps2bbLFxSk2bdqEYDBoPYNvvvlm64VewS1XmZmZ1trU6v7p0KGDTeipeFTeVoVuje5w0OUKGzRoYBtPZs+ebQm4UCiEAwcO2Ppl27ZtRi+GinOnrFixwhgjd9999+Hee+8FUCnoJ0+ejGAwiMmTJ1teCzfxpmjXrt0J4UqNyizUEwlT7JAa+P1mrK5O1BuZl7gynidMQWczuUEfohs3bsTbb78NwL8LtWXLltZbrBcRRh/C69evxz//+U8A3sQfoF9SyWtZnYDzYq3kAs6PyVyX5ywcasBVg5TXdRB1Ao4yceJE6/PDDz+MsrIy7cPw4MGDtvxUlEaNGrlaDY4cOWJzJarcV3S7juzsbJv4AbwLOFXu9NNPtw2SfGKJus46gUPjkJKSkqy6+PFoO2JjY20zNcvLy63zowMOj3PjFr+rrrrKIeDc2qlQK02oNunaScspq7NOwCn4ZJL4+HjHKg5ciNG0KToLnNrfi4DTvax4WaVB1UfFunqeq9Qe1IKt9lOWJwD48ssvcezYMUt4qfuWCgvVd9wz8re//c36rCzOVMCpYyQlJWHEiBHW99OnT3f8rnXCLzExEX/4wx+s79u3b48ffvgBHJX0XNWne6nlE4i+/vpr67PynPzxj3+07aP6XM2+VRQXFwOArW3du3e3PTOUZ2PFihWYNWsWQqFQ2JUpqCC8/vrr0ahRI9xxxx34v//7P3z99dcYN26cbX+afBiAbSIFUCnsL7zwQpiYOnUqFi9ejJ07d6Jz5854/fXX8fjjj6Nz586oqKjQxuvpMIWV1BQ1KuAinQXiB2UtMVlp3LJOHz58GHv27LH9qynUlH8dasChDy26aoHJpfj0008DsD8M//SnP1mfTQJOvfm5mdv9WuC6dOmijZfiqOz/wC8DzbJly6ylj7yuYxotC5wfTLm+3ODJeL3O8g0EApbw1wX1Tp482fi34uDBg/jLX/6i3ZaQkOC6SPbRo0dtvxE3CxwfBL/++muHBY6nzOCuS10iX3of8EkrSiDoBE5sbCwmTZpkbecpMWg5KuBoP1ABp1ttgQtUxeLFi23HNAk4FQayYcMGvP3229pz5/n/qAVOPW+51cutPm6504k0nq6EXltltfFjgaMoi5hupqmblRf45dmpnvl8oXug8mVT1dmvXz9kZGRY9SkBp3Oh8skrdJtuggMtp1YKAYBp06Zpf6NKSFELnIpbU3XoXqAyMjIA/PJ7adCggW1SBABb/QolmJRFfcOGDY5x+ciRIzaxBwA9e/bEqlWrLCEHVM48pdbBq666Ch988AEuvPBC3HbbbcjLy3NYAePj4x1xk6pNyuo1bdo0fPzxx+jWrZtt8sXIkSNtM3AV6ve0a9cuT8YMoDIkTKXQosTGxrrG63GWLVvmab/qpNoFHDXPpqSkYOnSpXj33Xeru1ot4Wb2TZ8+HSkpKda/mvRx635sCjXwqofYvn37bD9Wbq6n6IJ+P/74Y8d2HWr2lJug8GuBo3BrDeWee+6xBkv147z88sut7bqHquKRRx5xDIqzZ8+2glFNsYavv/46gF/6+eDBg67ixY2jR49iy5Ytvt7OuNjwKuBiYmKsmVkrV64EAOvhP3PmTFtKCQCuS5WpeCIdx44dc7VaHjlyxBYXy8UKn6igoPFUqgyfseiWmoQek55fKBTyLOAAu2hWdVFBqBNwlPLycmufhIQEKyic16fLO+fVAkcHkosvvtgotug29ZxTebp0bkTdZBJ1Dfr27Yvp06c7XKj0WNSira5Dt27dcPHFFzuEnymRL0W5iE0WON3vV71EqJdCnYBLSEjAr3/9a+v7999/3yHgDh48aLnFVN26l0Uu4OjMRDoDd/DgwbZy6vlCUe5fWh+dfLdjxw7ccccdjnIKKuBGjBhhm9n5wAMPOPa/6667bMaCn376yfEiTlOkUHgY1dChQ22/i+LiYlxwwQXW3xMmTNCe8+LFi23rF7ds2TJsHBxQuXZxUlKSw40bFxeHQCDgOrlt+/btCIVCDuGos2yaoMIagBWrWJtUq4CbMmUKMjMz0bRpU3Tp0gU5OTno1KlTtabyUBdRV4eyvLld6JycHOzevdv6V1ZWVm3tVKg3GJNliOdM4kkTTSJDmfnd3HImS6X6YbuV9WKBO3bsmHaJJv4gpg/0hIQEa2DTCSE+KNK+u/LKKx1lb7rpJtux3VDHVXmDlJtZQV1vHLW+39dff41WrVpZFh4vRCrgdNfdJBx034Wrjwf8qgEHqHwDVTF3OtwE3O7dux2CirvvuFtTLTtERROlc+fO1rbY2FhH7jV1D6tyNLUH7TN1rlxIcgvce++9Z+1jStarm/VKt6l26mah8nPUiS2dgPvss8+sMnPmzLHalJSUZJ0Dd6FSUQgAt99+u1bAqf3VNipeAeDtt9+2nptKwJkmMVBMAk6dp+55pQScLj8kFXB0ZigAhwuVTnoxWeCU1btNmzZWO1XbVZtNL5mUM88801ZfUlISWrRoYUvia+LNN98E8Mu59+rVy/hCP2/ePLRu3dr6W7mE6UxZN28Qdy3q7m0OnfDx3nvvAaj8TfOwFJ3Y5Kj7rEWLFg73sBvvvvuudd25APPK+vXrUVFRgWeffdbKiTdw4EDPk9Sqk2oVcGqW4s6dO7F8+XI0bdoUWVlZ1bpwrpcAdxrcTUlMTESTJk1s/6qTAwcOWGLM5Bbk8Tx82ZJLL73Utay6eQ8fPqwNuuRWNPo3fSDqyvKHcNeuXbVTt3WxUFzA0YcrHUh1rkg+sFGzeVJSknGdVTcRA1TGVSmOHz/ueMMyTeTh4s5PlnF17VWMERXMN954o2s5bmGjA5DqA/r27lXAvfvuu9YAcvz4cdv1O+ecc6zPPD4FgBV436xZM1cBt23bNsc2NwGn7rGXXnoJmzZtcpS74YYbAFTeTzphpPZXg7W676hrloo0t6S7XMC9+eabVsxPo0aNXF294QSc2q6zFHKXmFcLHPUc3HDDDTYR4yYY6exVBRVb6tx5nFtiYqLj96gsJJG6UHWWO3WP6kIvlICjLlRdOhfu+eEWOFoPtYjx1WSUW69Zs2ZWfyo3JBdwV199taO9wC8vvzoXKgDbC6Dal7sHaS5Kes15nJgJlY+Vjj+6lRc4OvdjOOiSY37hqznp0tfooMYaGprjhWHDhiEUCqFTp07W/Z+Xl4dQKITly5f79s5UBzUWA9exY0drjdTqzqOSkZGhXRS+vLwcwWDwhJmBGi6PjYInvZwzZ461bfLkyUZTLn3g6ZaA4m9rVJQpAafLOq8r2759e3zyySfYs2eP7eGSn5/vEIAmAXf8+HFrYFuxYoWjXi4IaFnd8lIUKtIoy5Yts/XVsWPHHOdMYwc5XmMvdHDXHU3T8sgjj7iW4wKurKzMYflRq010797d5jqncAHXs2dPK7/UsWPHbAOw24CkUIPv/v37bYMnX7bMqwWOigPqelX3gBq833//fZsYUdvV4KsEnLq/qcWMzvz0KuAAWNnZmzdv7mqBMy3dpYuBo23hL0imVSioYORhEerc6QxR7kKNi4tziCpqheIC1c0CR+ujAo4LKp0FjsfA6QScLuRDl+CbC82EhATHs2/btm0AKgd5dW150uSkpCQ0a9YMa9eutcqpZLBr1661xBVfd1bdz7p0Q/3797f2V0tfKaupKkf7R1n8brjhBtuzjrpo6fP03HPPtdVHrWtu0MkAdEm/Rx99VLs/FYkmrwaFhyF4iUf2Wwdl/PjxthfrhIQEXzNH+QSJE5FqFXAZGRmYNWtWjS9iO2zYMCvVBaWgoACZmZk12hYTNG+WMsfr4C7U3r17W9vuu+8+Y04bKkoOHz5siz0AKn/4bokSadmDBw86BA1/CKsfWePGjXHRRRdZ348aNQqLFy921OtWF10iavTo0fjoo4+09Shat26Nf/zjH3jiiSfQoEEDa1B8/PHHHe7bhIQE22xCxaWXXmqzlhw9etRhOQwEAq65EL0kCHaDxybRuBYu0nh7KLt27XLNr6ZyiOngLvKEhATb7FbVD+np6Y57TeWLUpMgaAC6Om58fDzOPvtsWzkucNQ15QKOnmNMTIxDwNEYGxV4TVNwKMHJB1Yas0bdlspyqtw9tJzbGzd1oXpJHExFkykGjv8ude5O3SQG7r5TLjHqUVCJWul14CEDqi+olY1PYtBZ4KhlUsFdtjoBp2KSlBCjAk6JGJN7kAo4XQ48HtawYMECAJXPV/WMVWKQu1DpEliKlStXWoKSu1BVn/BlqIDKl+6pU6daf1NRoX6n1Euk+i4lJcUWDkKh15x7jlauXOlI5K6Op9DFFjZo0ACTJk1yzFTl7Yt0WUw+UQKonMCgGwtpbJ3CFKMeCoUwZ84c7W+WTsTo1asXDh8+jP3796Nnz562/Uxj8olCtQq47OxsLFy4EB06dECXLl0wYsQI/POf/6z2dVDVj4aKuNLSUpSWlp5QSXwDgQA2bNiANWvW2OISONwCp6ZJn3feeWjcuLFjUKXLpNAH5aFDh6yZnABwyy23oGvXrrY1Qak4pIPWoUOHHOlXkpOTbT9u+iCPiYmxDV7cHdSwYUOcccYZtu/uvvtujB8/Hl26dLGdE10EGah821XpSFS9kydPttxpqt7Zs2c7hOO6deuslToUyrRP26uzwAHuFqhAIOApGbMOaoE7cuSILRWBScDxbfv373ed3Wma5cyX46ECjqYC0L0Fq+OrHF70rVrVqdqissEPGDDA8yQG+gAOBAIOAUfdMiqUIC4uzjF5hru21ID7/PPPaycqqGcIFQ58MDDFwNHz48sYKZFgEnCxsbGOAURNVNFZ4KiA4/eFWoWEWq90S5NxlEUsISHBcX1of/L7wm3yQygUMsbAKdSz8NixY9a1Ub8JU7nGjRs7LGn0Gj366KOOF1ig8p5VfaOMDaZJDBRlEVP3Or/PdJb5hg0b2tJG0ZyRpvCilJQUh8hQUGMAdzOXlZVpX/Ife+wx17qAXwQ1TZCdkZGBhQsX2o7XqlUr69kL6FeHuPLKKx3ftW/f3pE+a9KkSdi4cSN69OiB1q1b4+WXX8Yzzzyj9drRVRIo4Zbo6tGjBzp27AigMk4/ISEBycnJKCoqwjvvvIO2bdvi9ddfD5vs90SgWgVcz549rRi4oqIiDB8+HEVFRcjOzq7OagFUmrnz8/Mxc+ZMzJ07F7m5ucaM0LVFhw4dcM455zhuFvrwUw8D9ZBWDwklgEwpKwKBgC3gmU4ZV2/4tO7WrVtj48aN2LFjBwKBgC29w6xZs2zHbtKkie1HxB/k9K3w008/dZwfdelVVFRg6tSp1lsTHVB4xvQDBw7Y3AfcTUXLqiBfRefOnW3t7NKlizUdnAs4XewefVAClQ8DNYiaXAKm9QNpP+3du9dmgTPFWfBt1JrEZ1tyMUoD3Wm+OMApvtVDVheYzQUAHfBGjhwJ4Jfrox7ix44dcwhN6kJ1E41HjhxxCLi///3vjjbx+4EKB3U8atVVE550IoZeC55qRU2soC5b3SSGyy+/3BYuoT7TmDv+205MTHSERixdutQ6pknA0fVQAdgmFagYVb6Gqs7VS12vXKBSS5PbCzm18PDwDdNvhZZT9wO9Dm4kJSU50tHwSS86IZCcnOxwheomMdAJPEDlAvPKRXfFFVcgLy9PO4mBrwrUsGFDmzinzwbq8uMhGykpKTbPBsX08nj//ffjsssuw9ChQ23hN6YgfNrGdu3a4cCBAygtLUVBQYEtv53iiSeewP79+7Fz504rSS5FZwEEnNezYcOGiI2NRVFREX788Udcfvnl+POf/6wVU4MHD8aCBQuwcuVKjBgxAjExMXjnnXc8rfL0/fff49tvv3UsMTZgwABs2rTJlu/uRKbGYuBSUlIwdOhQPPXUU65LY0ST1NRU5OXlISsrC2PHjkVeXp7r5IUTAX6D0rdoHpejZjwqNxGPYaKB5oB9cNQNUrTuuLg4tG/f3gr+VA/EF1980TagjBgxAi1btrS9EfP4AvoQ4w/sRo0a2VwePD6FtonOKO7cuTNGjBhhnOXlJv4GDx6Ma665xiYKRo4cab2xxsTEWP3uZoGjS/cAlQ9c1Ra3LOU9evTAVVdd5dpeeq4dOnRwzebOiYmJsVlMdQLOrZ94nIypTUrA6SxwXADoBKcqR604bha4b7/91hYzRdtPkwar+nTpaPg9Xl5e7hhYb731Vmu7ErC6QYLO4Bw0aJA2yadpFqpqJ/2dqMB13SQGHnv1yiuvWOXUhCddsl5a36RJk/Cvf/3LuhZKwCUnJzsSJpsscMqleuzYMZuLmwpi0++wYcOGtskP9PdksmxRF6C65ioUwvRSk5iY6HCFcuEOOIVYw4YNrTq5K5S2k/7WAODee+9Fjx49rL/Hjx9vLSJPrWBUNAGVz0ndBCDALva4tTElJQXx8fG2e9cLt9xyC5KSkrBkyRKMHz8eGzZswOeff+6IzzOl92rQoIFltXIjOTnZOm8esmHyJKiZqnQyXkxMTNhJAoFAAFdffTX69euHhQsXYt++fbb1Y03Ex8eja9euJ8REhKpQrQJu+PDhyMnJ8TUj72SFm73pDa9+yPv370f79u2tWUIqmJYP9GlpaXjjjTesZVPUQyg9Pd1yv9I3bi7gKOrYt99+uyVQ4uPjsXDhQgQCAW12dwV9aHJTOW8zL0vbpB4Gv/rVr/DDDz+gRYsWtgcrF3/0HKjYeu211xzpGfigTePn3FYSoIOWaf1QRZ8+fYwPCt4GL9YGoPIeoQ9datlS56GzrPCBSIfOAmcScKaUAro4N15O3Vtbt261PYRpnToBp7M88Lb079/fMZBT15ZyW8XFxSEnJ8f6ni7npMrRcAN6fjxGTJXTCVuVekXnQuXXns6c6969u3VMkwUuISEB1157rRV3qKxKSUlJ1nH55AfdfaIshd9//70j7YoS2AkJCRg4cKCjrDoHWo7+VkxB6fSaLl++3Bb20aBBAyxfvlxbLikpySqrBJw6d3p+fKY8zTiwZ88em+uWPmf4pLNmzZo5Yl9VfXT2o1qeSXH66acjPj7eej5TaDt52hNlmZw1a1ZYKxON9+PPlw4dOmifARdeeKFVP4879gt9OQ83weu8887D3r17bS8rkRDueVkfqfYYuNWrV6N9+/bo0qULJkyYgJdeeqnGJzXUBU499VRbygf6wKexK7o16rp37+7IGzRo0CBrORT1cC8rK7NmPdG3OCoW+Y+d/ihU3BmNe6ODJZ8wQIUOtYTRadlu0GOpc969e7dVziTg6DmogapLly7Wd/Qhyd8M1flMnz4dt99+u7GNgF3AuU1kUIkm3eB9vmTJEgDhVy5RcXfKmqazwOmElS6OSC01pOJGaZtUwLWyHKnVPVq2bGm04Ci4m1TnCqXxlcq1TpcKU9/zcjpXXFxcHPLz862/v/zyS4cFTtfeuLg42xJCN910kydLk84Cp15aTamIqCVN7c/TSQC/JLGmM1RNAo6eN/BLLFNiYqLDAkctd2+88YY21+HgwYNt50fjCxMTE10tM0lJSa7lTAKO9vWVV15ps1YlJiYiIyMDd955JwYNGuSoTwm4AQMG2FJN0PuIz2Rt1qyZ9ZtYsWKF4/wUPP61UaNGrteXilD+cq7CMPhyVYD9ecStdNS1PHv2bG29vCzvo3Ao67d6WagKf/7znwHA9lt0o1GjRnXeGlYbVHsM3JIlS6w8cGlpaVi4cKHnJIUnG1RUUXekW+CuWlYkEAgYE6pSgaMsHfQBymf6UXSuDrc3Hd2MT4US7X379sW3337rKMsHSOpuUQMRPT5tMxdw9G+VhoS22ev50nxIbgsqUwFBF22m+BVwyrKqFpZ2Q7WdWnG8CDg1EEyZMgVApRuYB5fryqk+UBYMKhhN+fV0FjhlzVDX/brrrnOUa9Cgge2a33vvvQ4Bp2tnfHy8Y7Y5t8Dp3OM0jQhQuZYkt8C5nR+PgVP3u2mlk9jYWJx22mkAfvld6qyv6v6gs3pNs1Dd0Ak4KsAHDRqE//znP45yTZs2NVrS3J5PVMAdPnzY1peBQMA1I4CbWFZrnQKVs+95PszExERLOB04cMA2Q5kKLd0MeJUYdt68ebaVCGhb+HkGAgFtWoqYmBjHc1OJST+r+/AXQlqWikI6yUBx5plnYsuWLa7rGNcETz/9NLZv325NcBKiT7UKuDFjxqCgoAAbN25Ex44dMWbMGCxevLhGYuDqInTwUG9Obdq0cR38abAyfXBzUUIHQTUjjQ5IVPBwd7eubq8CTvcgPuWUU7SDPY/H8LOWKG8zHWB0C5VTeF/pBurMzEzbMjxA5cOpZ8+etgzibiImPj5euxqFItLZTqrtNEZSnbtJwKnJKypWsmnTpg6BY4pZ0a1i4MeFeuTIESvuTE0g4f0LVFpt+aopSvjRvubL8Ojaws/PzXLHX2y8WuBU3kklBNQ9aRJwNGebOi+dBU4Nwir1h1cLHEcX5O9FgNNcb9SSpiYbcVcfrU+VW7FihZUIW/XlggULtMld3fratAILUCma3YL5qfWKP9O4hUxZtGmePoVysd9///0A9FY0nTXp5ZdfxmeffeYrAwM/hts1uvbaa7Xfn3rqqZ5WS6guAoGA670hRIdqn8QwdOhQdOjQobqrqRfQH2j79u2xefNmrFu3znV/OvCb3IIU5cqkAxV9CHHLBI9dA9zFEH8b1QkTXvbRRx9FixYtHIG5OgHH044oeEyMbv1Vr6tqeFn5Aai0GBUVFdlmk7k9YGNjY12Xb1PbTXz11VeYOXOm43tugXv//fctC4qbgBsxYoQllqkI4ELFZDGkVqxIXKhu6+PquOuuu2x/q3g12tf8vvAi4HQJVrkFLjY21rMF7scffwRQmZYE0Ke94KtqxMbGWoKDCzjduqW0PtNSWgq+vjK1wPGF7mk5Gm7A6zt8+LAtNUcgEMDEiRPRvXt3x0xrKuBuvPFG68VdHSspKQkffPCBbUa02q6bbcmvAf+9paWlaQUcT9HEBaLbms4678O0adMQCoWscJcWLVo4ksa7xWWee+65xmeziSeeeMK1baaXBKF+ExUBt2bNGkyYMKHa87vVd/jA07JlS+NsLTerm1tcF8XtLZcPFlWxwPG8cYDTDTFp0iRs3brVMQjrhBRPj+CGzj3m9pDjb/FeBZwOt/0SExPxpz/9CaNHj9aKUDcBpyxlZ511ljaPkiqnBjKa0sVtEgO9dtSdpput5wZ1F0biQtVdHwAOd8/555+PtLQ02wCrZvnR+kxpZBS6NVT5jDVugYuJifHUL7pz100O4EveNW7c2JEIluYAdKO8vNyTBY4LMSrgZs2ahSuvvFJ7/Xiyam6B432ZmpqKL774wpFjkwo43g4KfyYkJiZqn0+mewyo7E+deOJ92bt3b+t3WFBQgJiYGG2aH6/Wo2AwaHN3+skHSdfn1D0b1q9fj3nz5jnCjtq1a4dp06Zhzpw5dSJfmVA9REXALVq0CKtWrbL9gDds2ICcnBwRdT6gP0QvLkT6sOYJT932U7gNSNw6ohNwboMLF3C62cdeZwrpXI5u9fL4KV1Z/lCdN28ehgwZ4ijL4+kA7wLObYC5+uqrER8fj/nz59uWqVFwwa3iougArHtIcxcqxc0CR/tQZ4EznavKe6b2qaiosO4XkwVOtZ2KAGWVpykW+Mw4NXuNusRVShl6zrzNNIZJQa1GCp7VnlvgYmJitHm9eKJSL3nndO08evSoqwXOJODeffdd41JaCv5bprNQgcrntq4cf6nhkzTcZq7ycl4FHC9HEwfz78OhE0/8WIFAAN988w1CoRAyMjIA6JfJ8+P+o4ls1aQRL9DJCDqrY6dOnXD99ddrf+M5OTkYP36857qE+kdUBFynTp1QVFRkexh37NgR06dPR0FBgS3TtOANNysFxeublx8Bp1s+iuPVhapzTZgyqYeDD2rr1q3D9OnTHUG8OgHH673++uvx6quvRtUCp3vITpo0yeau0+3D+025rcO5xbkLVdcWvo0OZjSlhBcBp1IX6NLDeIm1oZY75VKmgek8Foln/wf0IQC8zbo1hnXnxxe39mqB40syxcfH29yVjz32mFbk8HYuW7bMEhzcAkd/Yzzh6qmnnmoTcKFQSGuB4wmwExMTHb8hde/RdvLfN7XAHTp0SOvGBvQCTifEvFjgdALWtBycwouA06GzcCtrrxcifa5Rz4DXtbEFQREVARcMBm1LG1HGjBljpR8QvOMlTsht0OSCwI+A4w8tnXDw6kLV4dUCp5vdxR/qnTt3xpQpUxzuUS8Czg2eFBnwLuB0bebxN14EnGqDW64+/p3umGowdctzB/zSn3v37rUEgGmwU4OjLk0LbQNfoofmDAPsy4XR+4HXrf5Ws60p9Jp7GaB1LlSdpdotBo7WweuLi4uzAvSByvVZdRY/3X2k+vSll17CgAEDtBY4vhRX27Ztre1PP/00LrroIq0ljea0U+12+/3p7gsFtcDdcMMN6Nevn/Z8dAJOTbzg7TCVa9CggbadPNZMh+5Z52XRdN0+upRNbkS6jB5FF28sCCaiIuDS09NRVFSEZs2aYcKECdZC0AqaSV/whpcEsV4FnG7w1y0IDzgXDfYj4HQCxmtZL8fyMlADejdoVSx/XgWcrl6TgFLwc1WDuGlmMf1Od0y1aoZpJpsaqOn6i6aAaDXI6RIl0++4a5ILOOAXa4PpflDXW7cgOB0wvVwfrzF+PMmzF1dofHy8lTQXqIyr0glGXu6HH36wncd7771nCWnaL3RtY6Byxi69ZwoKCqy0JfQ68GXfuAuVn4PCZIFzKwPoBZwu5yf/HfP6GjVqFHYNUjfeeuutsO3U4WUfE/Q66tyxJtRvlcdICkI4oiLglB9+zJgxKCkpQXp6OmJjY3HRRRehd+/evkzRJztqwOU5xXQPNC4OLr/8cqSkpNgCYwFvkxg+//xzzJ0718oNxttD4Q9cNYOUptQA9CLMq5DyYoFzQ2eB8/IWDujX7PMq4HT18r43xbJxwlngTDFwuiWmeHt4f7oN1Ap17WhbvMTA6QScmgXJ2zB//nzrs7pH+/fv70gwS4/F72Vdri2dRQwAbr75ZuvzV1995SkGjp+r10kM/LfUuXNn19m+pnv97rvvtrmegV/ci6b6IrXA6Ras53UB+tg5Hfx68Xs7NjZW206V0JiyYsUKBINBvPHGGwAqJ35xdFZ1ToMGDRyTWvwklqXnTlch8EJxcTGWLVumtTQLgomoCLiePXviqaeewowZM7B8+XLs2rULixYtQigUQs+ePTF9+vRoVHNS8N133+GFF15w/JhXrFjheGjzgWTp0qUoKytzpEigC78r+AP5tNNOw5gxYxwCSxeXwR+us2bNwv79+z0t0VSV5U68CriqCMerrroKP//8sy09iFfx58UCpxNibgNFVWLgdPvxY/Jy4dIRqLbr2mKyYOjirJRlht8PdBA1uS1NAk6XvNTNAqdWoAAqz4tuLykp0ZYLBAK2WYvqvKgYVIKKltPN8KZLvVFM9/opp5ziao02xTzGx8d7ssDpJhWYJsoodIludXz44Yfa74Ff7gddO/nsWKDSY1BSUmLlzdRZv7yE8AQCARQWFqKiogI9e/YEAO1SV27Q5bl0ItJE69atcemll8pKBIJvoiLguIs0JSUFmZmZWL58ObKzs13j4wQnp59+OkaOHOn4Mffp0wf//e9/bQlPuRiIiYnRDsLTpk3DY489ZluTzqtVSSf+dA9XrwKpKhY4ry7UqsTAAZWuJ9qPXsvq6uXXSDc5xc0CRwdIPzFwNB4LsP8+TcfkcTyffvqpdjmxQCDgyTXM0YkAfi/Rfej15ver6f5VKR3UihZxcXFalyZgn2gTExPjsFxu3rzZ0RbAvjyQ+q3q+oqejy4Xoe6eSUhICJsvzG2SE78OdIWWBg0aYNu2bY4ygUDAVh9fuzIxMRFr1651lONhHrp7lC8/pdrhhts6wCUlJdpkz5xhw4Y5vuvWrVvYckBlPwQCARQVFSEUCuHMM8/0VA6onIBz66234qyzznJMchGE6iIqAm7s2LGYMmWKI2XInj175K0iylAx4TXLdnJyMm666SZbWgqvAm7GjBl48sknbTPhvFrCdNaFmrDA6SxmfmPgaF1e2+zFAqdbiNttsKaiQbePOja/D/jalFSM0n15Od5vffr0wQMPPIBNmzY5XtJ4WS8u1EAg4OhLk4AzTQCg2/jMYdVvKq7z2LFjri5UGicWCASQmppqi2dzq1+legFgJfHV9QG9jzp37uyYUUrXFVbo7jeeuiQ9Pd2xD+A8vxtuuAEzZ87EtGnTcOaZZzpmpurKBAIBLFiwwPo7MTFRK8TcrIcU3exOtzWDKbQPgsEggsFg2DJAZVv379/vup5pdTJr1ix89dVXnpOGC0JViYqAS0lJwYwZMxwpQ6ZNm4ZOnTpZb8JC1aFCxG+g76effmp99vpQa9KkCSZMmGCLK/IqaHQuj5qIgXvttdfQvn1720Dh1Q2qoAO21zZ7EXC6dugWEAfs5+snBs5r8udwLjBF27ZtHSlheHtMLlRqZeLxSLo4PAUVrSYL3DnnnGPL2aXOg7bJzYWqW2JJt1Yzv27096PcsLprxPtt5cqVmDZtmjXRKzk52TG7Unf9br75ZvTt2xePPPIIAPc4K50F/rbbbkNOTg4CgYBjdQZAf+1oP8XHx2PIkCGOfZRwpXAXppc+0UH7Vy235pXk5GRb+91+X4JQ14nqUlpjxoyx1lcEKgfwxYsXawdyITKoePIr4Pgi1JHW61XA3XzzzVi7dq217Iyfsn4S+XL69euHjRs32twpfi1wpkWs3dDNIjMJuJ9//hnbtm1DSkqKY+Y2YD9fPzFwpn4yTYzwI3L9WOB0wlahS1mha5/JAhcTE4Pt27dj7dq1thm14YQJYF9GTr006ILedffAypUrMWnSJAwdOhSAt3Q9MTExyMnJQf/+/a3vgsGgzVKl+42kpKTg448/xl//+lfHNkq4OEaddSjcJCe30AwdfMk4euzMzEw0atQITz31lGt53W/Iq/WN8+yzz2LgwIHaZegEoT5QI2uhennjErxBB5KquAb8Cjg6uPtxg3br1s328PdalgYFK/yebyQirCpl09PT8fTTT9u+4yKJ5oVr3ry5FXPVv39/xznTwdaPBc7UT5FY4HTw9phEo5uAi4mJcbTdq4DT3b/dunWzJQPWnY/JWqmEm841qBM+/fr1w6OPPuqac89Pf9Jr5vVFhc/6dluCiqI7tk7A8RQkXvOcjRw5EsAvSZJpn0ydOhW7du3SWsQqKipQXFxs5byj1zfSlCKjRo3C8uXLHQmiBaG+UO0CToguVXGh0rVE/QqaSAUcEJkYWrRoESZNmoTMzEzrO7/nWxUBF4kLFQB+97vf2f7mg/rEiRPx5z//2ZGcFXAG8NM+18WSuk1i8LpuZ7gYOBN+yroJOJ3YoP1FP/N9veTt8pPAGoA2wN8PvD5dQL0btF1ef1980oSX66e7j3TirG/fvrj55putRdRjY2PxyCOPIDs72yjm+vbtiw0bNmDp0qVWOUWDBg1cLbWBQAA9evSwXkpoH0S6ALwg1Hfkl1HH0K1l6ZXf/va31ueqWKT8CrhIBqd27drh0UcftS3wXBUB5zcGLlLxx4WFzlL1zDPPaHNa0bIVFRVhJwCpBK98UDSJFDrBgQ+MkVrgeHobAHj88cetz34EHD1nNwtcTEyM52XkuCVJJ/xUouC77roLAHDjjTd6OjaH96cfi3EkFjiO1+s3ffp09OjRw/pb99sIBAJ4+OGHbWt8/vWvf8WMGTOwbNkyBAIB3H333drjd+jQwbo+dHUBP88NlcpDEAR3RMDVMejA5fdBTwdSvyKsKvXS/asiHP3WG6kVjdfrp6/CCTgT9PqY1sI9/fTTkZ6ebi1Z5cUC99Zbb+Ghhx6y5Vnj6UAitcDprsvEiROtz3SW6KxZs4zlKG4Czo/7n1vVdKL4ySefxDfffIMJEyYAqFzEPFysmRf83K+07yMVcF7v0ylTpmDlypXW335XIRgwYAB2796Ne++9N+y+NCbaz3JTnTt3xkcffeRrYXhBONkQAVfHoG/5fh/0dCD1K+CqUi93o/jBlLA1HN9995312a+Ao2LKT1k/wf0cL4t1A8AVV1yBwsJCK57OiwXuoosuwi233KJd/1MRqQXO7X5Qa3HSIHI/MZzUWvjNN99Yn6u67BEnNjYWZ5xxhq1vIk1/dO2111qfvSyHp6D55/z8Rp577jnrc6QWv6+//tpzOUXjxo099VHLli3x7rvv4u233/a9Xuj5559vS30kCIId76OLcEJAB06/AxkVcH6EBa/Xb0xKbVn+3n77beuzXxfq4sWLrc/RdKGaoDMoTfD+9xMDx4lUXOvWVOVMmzYNd999t227aXUFxfLly7FmzRoruz4AbNmyxfrsdwJOJEQq4Kg72UueNAVNg+Ln96UmC/itj/7+eR69aHPhhRdW6/EF4WRFLHB1jKpYCaryoK5KAl6aEiRS91AkZadNm2Z9rsqgX1MCbvv27Z72M1nRAH/nSst6TRUBAOvXr/dUnynPm5uAGzhwILKysmxChrbTz4sLXYnAD5EKOHq9/fze6AvGhg0bPJej/UmviSAI9R+xwNUxqiLCqlL297//PQDY1gj1CrXA+R0Y6cDm14U6cuRING/eHF27dvVdb6tWraxllKriQvUj4LxaUKJpgaPt9evicqvfRKTpIfgED69Eek70fuG5zUzQNVLpagDhoL8RP5n8o2GNjLZLWhCEmkEscHUMP3E1nKoIuLPOOgtFRUXaNRHDQXOf+YXOIvQjhhQZGRkRic7CwkJkZmb6Pt+qWOC8Ek0LHG1fpPkaIxVwfgR5pALujTfe8LwvJVJLN43bM01E4QwcONDzvpSqpNh4++230alTJ+3yboIgnPiIgKtjVEUQVDXWpWfPnq5L+JgYPHgwpk6disLCQt9lMzIy0KlTJ4waNcp32apw5plnIj8/3/NC2Ap+ffxcr8GDBxu3d+/eHQAwfPhw2/fRssBFuoZjTQg4aqHy6moG9GtxeiFSAUfvlz59+nguRycxRMoFF1zga//f//73WL9+vW1VCEEQ6g4i4OoY99xzDzp06BDR8jCnn356NbQoPDExMbj77rtdF+A20aRJE6xbtw7PPvtsNbSsesjOzrY++5ksEu4cP/74Y2zYsMG2/JOujpoQcPRaRirg/Ews4UlrvdK3b1/rs0oT4heeSy4cRUVFmDp1Km655ZaI6tOtA+yF0aNHR1ROEIS6icTA1THatWvnK8iZMmHCBGzbts22IkNdINKA8tri6quvRm5uLgB/VqZmzZqhQYMG2rU4gcpYvA4dOji+Ny1HFY5IXailpaUR1Rdpbr7hw4djxIgRnvdX0Pg1mlw4HFRE0RnJXujZs2eVEtFGKuDOPffciOsUBKHuIRa4k4iEhATcf//96NevX203pV7Dl8TyQySzdLmAijQhr59ZqHQdzpoQcBRqVQtHo0aN8O2336KkpMSXO3vs2LFITk7GmDFjfLvRq4pfAbdu3TqsXLkSZ555ZjW1SBCEExGxwAlClIl01YBIiZYL1U+qGLrEWU24UCl+RXHXrl1919G5c2ds3769SmlvIsXvPdO5c2d07ty5mlojCMKJiljgBCHKtGnTBmeddRZOP/10BINBX2Wff/55xMTEWMtkeaEqaSCoe9qPcKDWs0gFnN/YMoVfARcpDRo0qFH3/ZNPPolWrVphzpw5NVanIAh1F7HACUKUiY+PxxdffAHA/4oXf/jDH7B3794q5Z7zA03J4UfAUWudHwFHBVGks15rSsDVNBMmTMD48ePrXMynIAi1gwg4QagGqiKq/MaGUQH14Ycf+iobqYCjbfQjOKqS1FkRqeu1LiDiTRAEr4gLVRDqODRhrJ+JCIBdUEUq4PwkrD377LOtz36XZ5s6dSqaN29um0AhCIJwsiICThDqOD///LP1ma4E4AVqgfOT1Z8G9/sRcNTC5NfSePfdd2Pr1q2+z1EQBKE+IgJOEOo4Xbp0sT5XxQLnByrEIl3h4/zzz69SvYIgCCczEgMnCHWctLQ05OfnR2SZilTAUfxY4ADgp59+wo4dO8SSJgiCUAVEwAlCPSAzMzOicn4WhnfDr4Br1aoVWrVqVeV6BUEQTmbqtQu1uLi4SkvaCEJ9pzYEnCAIglB16p0Frry83FpMvKioCMXFxbXcIkE4cakNF6ogCIJQdeqdgEtNTUVeXh4AYObMmSLgBMFApBMQon0MQRAEwR/12oUqCIKZgwcPVvkYYoETBEGoeUTACcJJzJEjRyIuO3z4cADAbbfdFq3mCIIgCB4RAUc4fPgw9uzZY/snCPUZlUMuJSXFd9kXX3wRZWVlGDx4cLSbJQiCIIRBBBxh+vTpSElJsf61bdu2tpskCNXKXXfdhUAggIcffth32ZiYGLRp06YaWiUIgiCEQwQcIScnB7t377b+lZWV1XaTBKFaueaaa3Dw4EFcd911td0UQRAEwQcn3CzU8vJypKeno7y83HOZ/Px8pKWlVbnuxMREJCYmVvk4glCXkHteEASh7nHCCbjU1FSsXr26tpshCIIgCIJwwnLCCbgTiVAoBAAymUEQBEEQhBpBaQ6lQdwQAWdg7969ACCTGQRBEARBqFH27t1rzBBQrwXcjh07qlS+devWKCsrQ+PGjREIBKLUKjt79uxB27ZtUVZWhiZNmlRLHYI70v+1j1yD2kX6v3aR/q99TrRrEAqFsHfvXrRu3dq4X70UcOPGjQMALF68GAAwcOBABINBDBs2DBkZGZ6PU5NpEpo0aXJC3DgnK9L/tY9cg9pF+r92kf6vfU6ka+AlN2e9FHBqLVT1vyAIgiAIQn1C8sAJgiAIgiDUMUTA1TKJiYm45557JBdXLSH9X/vINahdpP9rF+n/2qeuXoNAKNw8VUEQBEEQBOGEQixwgiAIgiAIdQwRcIIgCIIgCHUMEXCCIAiCIAh1DBFwgiAIgiAIdYx6mQeuLlBeXo7p06ejWbNmAICSkhLk5uYiNTW1dhtWxyguLsaYMWOwevVq7Xav/Rzt/eo7paWlyMvLQ3l5OUpLS5Gamorc3FwEg0HbftL/1Yu6Ds2aNcOOHTtQWlqKnJwcpKWl2faT61AzLFmyBKWlpcjKyrJ9L/0ffXr27Ilx48YhIyMDwWAQhYWFyM3NRV5enu05VK/7PiTUCmlpaaHVq1dbf5eUlISCwWBo165dtdeoOsKuXbtCY8eODY0dOzaUlpYWMt3GXvs52vvVZ0pKSkJjx461fZeVlRUCECopKbF9L/1ffZSUlISysrJs3+Xl5YUA2PooFJLrUBPs2rUrlJqaGsrNzXVsk/6PPqmpqSEA1r/U1NRQQUGBY7/63PfiQq0F5s6dCwC2t+RgMIi0tDRMnz69tppVZ0hNTUVeXh7y8vIwYsQI1/289nO096vv5ObmIjc31/Fdamoqhg0bZn0n/V+9LFmyBHPnzkV5ebn13fDhwwHYV6GR61AzqH5x+176P7pkZGQgNzcXWVlZyM/Px4YNGxxLZdb3vhcBVwvk5+ejV69eju979+6NJUuW1EKL6ide+zna+9V3Fi9ejDFjxji+z8jIQHFxsfW39H/1kpaW5nBZK3bu3Gl9lutQ/RQWFrqusy39Xz0Eg0FkZWUhNzcXmZmZWhdmfe97EXC1QGFhITp16uT4PhgMorS01PZGLUSO136O9n71Hd0DTIf0f/WSkZGB1atX2wauwsJCAEBOTo7tO7kO1UtxcbEj7lAh/V971Pe+FwFXw5gusHoQl5aW1kxj6jFe+zna+50MFBQUID8/3/F9cXGxZRGS/q95CgsLMX36dOTn51tiQq5D9TNz5kzHpAWF9H/1UV5ejrlz51r/xo0bZzv3k6HvZRZqDaNcG6YZK9T9IUSG135W26O138lKYWEhSktLUVBQAED6vyYpLi5GYWEhVq1ahYyMDJsrT65D9WKyvAHS/9XJzp07MXz4cJt46tmzJ1avXo1gMHhS9L1Y4E4gxPRdM3jt52jvV58ZN24csrKyXOOAKNL/0SUtLc0K5O7UqRM6duzoyRIg16HqLFq0yNM9r0P6v2rk5+fbxFQwGESvXr0wbty4sGXrS9+LgKthmjZtCkB/wZV6V/sIkeO1n6O938nIsGHDrBlhCun/2mHs2LEAYM0GlutQfcydO9cWa6hD+r9mUfnggJOj70XA1TBekv25zSwTvOO1n6O938nGzJkzEQwGbWkrAOn/2qRXr14oLi5GeXm5XIdqorS0FE2bNg3bH9L/1cO4ceMwc+ZM1+0ny70vMXC1QEZGBkpKShzfl5eXe75RhPB47edo73eyoKbNU8sbjQmS/q9eOnXqhLS0NMeEEhoTlJaWJtehGlDxnirmU1FeXo5FixahpKQEAwcORGZmpvR/NbB48WIr5yFFxapVV5+eaH0vFrhaYNiwYZaZl1JQUIDMzMxaaFH9xGs/R3u/k4Hi4mLtkkG0f6T/qxdlBeKoXHxKSMt1iD4ZGRlWMnH6DwBGjBiBvLw8qy+k/6PP2LFjHVZ/oPL5o8IIgJOg72t87QchFAqFQsFg0Lbsh1qOQ/CHWsLJDa/9HO396jMlJSWhtLS0UG5uru1fVlZWKCMjw7av9H/1kZub61gyq6CgIAQglJeXZ/terkPNAMCxvFkoJP0fbUpKShxLluXm5tZIn55IfS8u1Fpi9erVyM7ORnFxMVJTU7F69WqHOV5wR800Wrx4MQBg4MCBCAaDVkC9wms/R3u/+szAgQNRWlpqW3VBwd9Cpf+rj6ysLCxZsgR5eXlITU1FeXm55drjMyPlOlQvNAeZWt6MPouk/6NLMBhEZmYmsrOzAfwS86Zzb9bnvg+EQqFQrdQsCIIgCIIgRITEwAmCIAiCINQxRMAJgiAIgiDUMUTACYIgCIIg1DFEwAmCIAiCINQxRMAJgiAIgiDUMUTACYIgCIIg1DFEwAmCIAiCINQxRMAJgiAIgiDUMUTACYIgCIIg1DFEwAmCIAiCINQxRMAJgiAIgiDUMUTACYIgCIIg1DFEwAmCIAiCINQxRMAJgiAIgiDUMUTACYIgCIIg1DHiarsBgiAI9YHCwkKUlpaioKAA+fn5KC4uRmFhIQCgoKAA2dnZyMjIqOVWCoJQXwiEQqFQbTdCEAShrjNz5kxkZWWhZ8+eCAaDGDFiBDIzMwEAS5YswZgxY7Br165abqUgCPUFcaEKgiBUkcLCQkuslZaWIhgMWn8rysvLa6FlgiDUV8SFKgiCUEV69eqF1NRUlJaWory8HDk5Obbtq1atQlpaWi21ThCE+ohY4ARBEKpIamoqgEpXaTAYtP5WLFmyBCNGjKj5hgmCUG8RAScIghAlCgoKHBMViouLUVpaarlUxZUqCEI0EAEnCIIQJQoLCzFw4EDbd4sWLUJaWhqCwSBKS0utmamCIAhVQQScIAhCFCguLgYArQVOuU+XLFnimNwgCIIQCSLgBEEQokBpaSkyMjIc8W/Z2dkoKSnB3LlzRbwJghA1JA+cIAiCIAhCHUMscIIgCIIgCHUMEXCCIAiCIAh1DBFwgiAIgiAIdQwRcIIgCIIgCHUMEXCCIAiCIAh1DBFwgiAIgiAIdQwRcIIgCIIgCHUMEXCCIAiCIAh1DBFwgiAIgiAIdQwRcIIgCIIgCHUMEXCCIAiCIAh1DBFwgiAIgiAIdQwRcIIgCIIgCHWM/w/JhPzoAR/gUgAAAABJRU5ErkJggg==", + "image/png": 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", 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" + "
" ] }, "metadata": {}, @@ -385,25 +756,25 @@ ], "source": [ "# Plot single window \n", - "plt.figure(figsize=(7,1.5))\n", + "plt.figure(figsize=figsize)\n", "plt.plot(utils.normalize(data[1,0]),'k')\n", "plt.xlabel('$n$')\n", "plt.ylabel('$x_m[n]$')\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_input.pdf',bbox_inches='tight')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_input_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 292, + "execution_count": 295, "id": "8b7b9b8e-ab0f-45d5-8e37-6e0d8c0e7760", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -412,67 +783,49 @@ ], "source": [ "# Plot relevance map for the window\n", - "plt.figure(figsize=(7,1.5))\n", - "plt.plot(utils.normalize(relevance[1,0]),'k')\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(relevance_loc_cnn[1,0]),'k')\n", "plt.xlabel('$n$')\n", "plt.ylabel('$R_0[n]$')\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_relevance.pdf',bbox_inches='tight')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_relevance_loc_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", - "id": "e5e96495-3e94-4263-ad97-f7d409819483", + "id": "1196c243-1a1c-465a-891d-a084e0f0c4c3", "metadata": {}, "source": [ - "### GCC-PHAT visualization" + "### Sample-CNN" ] }, { "cell_type": "code", - "execution_count": 293, - "id": "fde9e5c8-ce1b-4227-9c39-1f654aca32a0", + "execution_count": 296, + "id": "2b1923f7-4978-497d-b0fe-c19b2f8e2c9d", "metadata": {}, "outputs": [], "source": [ - "idx_m1, idx_m2 = 6,9 # Microphone indices\n", - "audio_signal = data_structure['signal'][0] # In\n", - "\n", - "# Reshape signal arriving at mic 1\n", - "win_sig_mic = data_structure['win_sig'][idx_m1]\n", - "win_sig_mic = np.transpose(win_sig_mic)\n", - "win_signal1 = np.reshape(win_sig_mic,window_size*N_wins)\n", - "\n", - "# Reshape signal arriving at mic 2\n", - "win_sig_mic = data_structure['win_sig'][idx_m2]\n", - "win_sig_mic = np.transpose(win_sig_mic)\n", - "win_signal2 = np.reshape(win_sig_mic,window_size*N_wins) \n", - "\n", - "# Reshape relevance relative to signal at mic 1\n", - "relevance_mic = relevance[:,idx_m1]\n", - "lrp_signal1 = np.reshape(relevance_mic,window_size*N_wins)\n", - "\n", - "# Reshape relevance relative to signal at mic 2\n", - "relevance_mic = relevance[:,idx_m2]\n", - "lrp_signal2 = np.reshape(relevance_mic,window_size*N_wins)\n", + "# Apply LRP\n", + "with Gradient(model=model_sample_cnn, composite=composite_sample_cnn) as attributor:\n", + " out, relevance_sample_cnn = attributor(torch.Tensor(data), output_gt)\n", "\n", - "# Compute STFT of signal\n", - "WIN_STFT = librosa.stft((win_signal1))\n", - "LRP_STFT = librosa.stft((lrp_signal1))\n" + "data = torch.Tensor(data).detach().numpy()\n", + "relevance_sample_cnn = relevance_sample_cnn.detach().numpy()" ] }, { "cell_type": "code", - "execution_count": 294, - "id": "036a513d-2986-40b8-857c-9d3f123f7ffe", + "execution_count": 297, + "id": "d20257ac-e1bd-4622-9c17-bef25887bd89", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -480,34 +833,137 @@ } ], "source": [ - "# Audio at microphones (reshaped to stack together different windows)\n", - "plt.figure(figsize=(7,1.5))\n", - "plt.plot(utils.normalize(win_signal1),'k')\n", + "# Plot single window \n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(data[1,0]),'k')\n", "plt.xlabel('$n$')\n", "plt.ylabel('$x_m[n]$')\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_input_full.pdf',bbox_inches='tight')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_input_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 295, - "id": "6ab235c2-92d1-4dbc-a76d-0e3576c5312e", + "execution_count": 298, + "id": "f44523d6-3340-44c6-9126-12add7597c99", "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_2625186/1412976144.py:3: UserWarning: power_to_db was called on complex input so phase information will be discarded. To suppress this warning, call power_to_db(np.abs(D)**2) instead.\n", - " librosa.display.specshow(librosa.power_to_db(WIN_STFT+1e-9), x_axis='time', y_axis='log', sr=fs,cmap='viridis')\n" - ] - }, + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot relevance map for the window\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(relevance_sample_cnn[1,0]),'k')\n", + "plt.xlabel('$n$')\n", + "plt.ylabel('$R_0[n]$')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_relevance_sample_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e5e96495-3e94-4263-ad97-f7d409819483", + "metadata": {}, + "source": [ + "### GCC-PHAT visualization" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "id": "fde9e5c8-ce1b-4227-9c39-1f654aca32a0", + "metadata": {}, + "outputs": [], + "source": [ + "idx_m1, idx_m2 = 5,10 # Microphone indices\n", + "audio_signal = data_structure['signal'][0] # In\n", + "\n", + "# Reshape signal arriving at mic 1\n", + "win_sig_mic = data_structure['win_sig'][idx_m1]\n", + "win_sig_mic = np.transpose(win_sig_mic)\n", + "win_signal1 = np.reshape(win_sig_mic,window_size*N_wins)\n", + "\n", + "# Reshape signal arriving at mic 2\n", + "win_sig_mic = data_structure['win_sig'][idx_m2]\n", + "win_sig_mic = np.transpose(win_sig_mic)\n", + "win_signal2 = np.reshape(win_sig_mic,window_size*N_wins) \n", + "\n", + "# LOC-CNN\n", + "# Reshape relevance relative to signal at mic 1\n", + "relevance_mic_loc_cnn = relevance_loc_cnn[:,idx_m1]\n", + "lrp_signal1_loc_cnn = np.reshape(relevance_mic_loc_cnn,window_size*N_wins)\n", + "\n", + "# Reshape relevance relative to signal at mic 2\n", + "relevance_mic_loc_cnn = relevance_loc_cnn[:,idx_m2]\n", + "lrp_signal2_loc_cnn = np.reshape(relevance_mic_loc_cnn,window_size*N_wins)\n", + "\n", + "# SAMPLE-CNN\n", + "# Reshape relevance relative to signal at mic 1\n", + "relevance_mic_sample_cnn = relevance_sample_cnn[:,idx_m1]\n", + "lrp_signal1_sample_cnn = np.reshape(relevance_mic_sample_cnn,window_size*N_wins)\n", + "\n", + "# Reshape relevance relative to signal at mic 2\n", + "relevance_mic_sample_cnn = relevance_sample_cnn[:,idx_m2]\n", + "lrp_signal2_sample_cnn = np.reshape(relevance_mic_sample_cnn,window_size*N_wins)\n", + "\n", + "\n", + "# Compute STFT of signal\n", + "n_fft = 512\n", + "win_length=512\n", + "hop_length = win_length//4\n", + "WIN_STFT = librosa.stft(utils.normalize_z(win_signal1),n_fft=n_fft,win_length=win_length,hop_length=hop_length)\n", + "LRP_STFT_loc_cnn = librosa.stft(utils.normalize_z(lrp_signal1_loc_cnn),n_fft=n_fft,win_length=win_length,hop_length=hop_length)\n", + "LRP_STFT_sample_cnn = librosa.stft(utils.normalize_z(lrp_signal1_sample_cnn),n_fft=n_fft,win_length=win_length,hop_length=hop_length)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 300, + "id": "036a513d-2986-40b8-857c-9d3f123f7ffe", + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Audio at microphones (reshaped to stack together different windows)\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(win_signal1),'k')\n", + "plt.xlabel('$n$')\n", + "plt.ylabel('$x_m[n]$')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_input_full_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "id": "6ab235c2-92d1-4dbc-a76d-0e3576c5312e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -516,16 +972,16 @@ ], "source": [ "# STFT of audio at microphones\n", - "plt.figure(figsize=(7,1.5))\n", - "librosa.display.specshow(librosa.power_to_db(WIN_STFT+1e-9), x_axis='time', y_axis='log', sr=fs,cmap='viridis')\n", + "plt.figure(figsize=figsize)\n", + "librosa.display.specshow(librosa.amplitude_to_db(np.abs(WIN_STFT),ref=np.max),hop_length=hop_length, x_axis='time', y_axis='log', sr=fs,cmap='viridis',win_length=win_length)\n", "plt.xlabel('$Time [\\mathrm{s}]$')\n", "plt.ylabel('$f_k~[\\mathrm{Hz}]$')\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_stft_input.pdf',bbox_inches='tight')\n" + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_stft_input_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n" ] }, { "cell_type": "code", - "execution_count": 296, + "execution_count": 302, "id": "05f4bf12-0f21-44d6-bff3-74e3328d848a", "metadata": {}, "outputs": [ @@ -534,7 +990,7 @@ "text/html": [ "\n", " \n", " " @@ -543,7 +999,7 @@ "" ] }, - "execution_count": 296, + "execution_count": 302, "metadata": {}, "output_type": "execute_result" } @@ -555,15 +1011,31 @@ }, { "cell_type": "code", - "execution_count": 297, + "execution_count": null, + "id": "e7a9394f-514b-414c-8d18-3aaf054f3c43", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "1e2ad291-eb27-4d1b-badc-77a7d7a2f34e", + "metadata": {}, + "source": [ + "### Relevance LOC-CNN" + ] + }, + { + "cell_type": "code", + "execution_count": 303, "id": "c63a6a32-f3a3-4106-bb31-90178c7eae2f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] }, "metadata": {}, @@ -572,35 +1044,110 @@ ], "source": [ "# Relevance at microphone (reshaped to stack together different windows)\n", - "plt.figure(figsize=(7,1.5))\n", - "plt.plot(utils.normalize(lrp_signal1),'k')\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(lrp_signal1_loc_cnn),'k')\n", "plt.xlabel('$n$')\n", - "plt.ylabel('$x_m[n]$')\n", + "plt.ylabel('$R_0[n]$')\n", "plt.ticklabel_format(axis='y', style='sci', scilimits=(4,0))\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_relevance_full.pdf',bbox_inches='tight')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_relevance_full_loc_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 298, + "execution_count": 304, "id": "1b2e33ae-53a2-422b-815f-ea1effb8c158", "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_2625186/3523326894.py:4: UserWarning: power_to_db was called on complex input so phase information will be discarded. To suppress this warning, call power_to_db(np.abs(D)**2) instead.\n", - " librosa.display.specshow(librosa.power_to_db(LRP_STFT), y_axis='log',x_axis='time', sr=fs,cmap='viridis')\n" - ] + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 304, + "metadata": {}, + "output_type": "execute_result" }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# STFT of Relevance at microphone \n", + "\n", + "plt.figure(figsize=figsize)\n", + "librosa.display.specshow(librosa.amplitude_to_db(np.abs(LRP_STFT_loc_cnn),ref=np.max),hop_length=hop_length, y_axis='log',x_axis='time', sr=fs,cmap='viridis',win_length=win_length)\n", + "plt.xlabel('Samples')\n", + "plt.ylabel('$f_k~[\\mathrm{Hz}]$')\n", + "plt.xlabel('$Time [\\mathrm{s}]$')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_stft_relevance_input_loc_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", + "ipd.Audio(utils.normalize(lrp_signal1_loc_cnn) , rate=fs) # load a NumPy array\n" + ] + }, + { + "cell_type": "markdown", + "id": "0aafdbe9-2269-48b4-b3da-9abdc6b660d5", + "metadata": {}, + "source": [ + "### Relevance SampleCNN" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "id": "0f15326e-8dc6-4ac4-b81f-e1b59b87c2b3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Relevance at microphone (reshaped to stack together different windows)\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(lrp_signal1_sample_cnn),'k')\n", + "plt.xlabel('$n$')\n", + "plt.ylabel('$R_0[n]$')\n", + "plt.ticklabel_format(axis='y', style='sci', scilimits=(4,0))\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_relevance_full_sample_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 306, + "id": "ff6b088f-d6dd-446d-82b8-2d83b140645f", + "metadata": {}, + "outputs": [ { "data": { "text/html": [ "\n", " \n", " " @@ -609,15 +1156,15 @@ "" ] }, - "execution_count": 298, + "execution_count": 306, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -627,28 +1174,44 @@ "source": [ "# STFT of Relevance at microphone \n", "\n", - "plt.figure(figsize=(7,1.5))\n", - "librosa.display.specshow(librosa.power_to_db(LRP_STFT), y_axis='log',x_axis='time', sr=fs,cmap='viridis')\n", + "plt.figure(figsize=figsize)\n", + "#librosa.display.specshow(librosa.amplitude_to_db(LRP_STFT_sample_cnn,ref=np.max), hop_length=128, y_axis='log',x_axis='time', sr=fs,cmap='viridis')\n", + "librosa.display.specshow(librosa.amplitude_to_db(np.abs(LRP_STFT_sample_cnn),ref=np.max), hop_length=hop_length, y_axis='log',x_axis='time', sr=fs,cmap='viridis',win_length=win_length)\n", + "\n", + "#librosa.display.specshow(20*np.log10(np.abs(LRP_STFT_sample_cnn)), hop_length=hop_length, y_axis='log',x_axis='time', sr=fs,cmap='viridis',win_length=win_length)\n", + "\n", + "#plt.imshow(20*np.log10(np.abs(LRP_STFT_sample_cnn)))\n", "plt.xlabel('Samples')\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_stft_relevance_input.pdf',bbox_inches='tight')\n", - "ipd.Audio(utils.normalize(lrp_signal1) , rate=fs) # load a NumPy array\n" + "plt.ylabel('$f_k~[\\mathrm{Hz}]$')\n", + "plt.xlabel('$Time [\\mathrm{s}]$')\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_stft_relevance_input_sample_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n", + "ipd.Audio(utils.normalize(lrp_signal1_sample_cnn) , rate=fs) # load a NumPy array\n" + ] + }, + { + "cell_type": "markdown", + "id": "cd3e23cb-c889-4b8b-bb63-35bbfef795a5", + "metadata": {}, + "source": [ + "### Plot GCC-PHAT" ] }, { "cell_type": "code", - "execution_count": 299, + "execution_count": 307, "id": "7f4d26ea-dcfe-4b07-a148-b8083dcb9eeb", "metadata": {}, "outputs": [], "source": [ "# Compute GCC-PHAT\n", "_, gcc_sig = utils.gcc_phat(win_signal1, win_signal2, fs=fs)\n", - "_, gcc_lrp = utils.gcc_phat(lrp_signal1, lrp_signal2, fs=fs)\n" + "_, gcc_lrp_loc_cnn = utils.gcc_phat(lrp_signal1_loc_cnn, lrp_signal2_loc_cnn, fs=fs)\n", + "_, gcc_lrp_sample_cnn = utils.gcc_phat(lrp_signal1_sample_cnn, lrp_signal2_sample_cnn, fs=fs)\n" ] }, { "cell_type": "code", - "execution_count": 300, + "execution_count": 308, "id": "a604a5f7-6515-46fc-9e71-97a79fef2855", "metadata": {}, "outputs": [], @@ -666,7 +1229,7 @@ }, { "cell_type": "code", - "execution_count": 301, + "execution_count": 309, "id": "7ce64e5a-c1d1-42de-a7b7-c4653f5cf86c", "metadata": {}, "outputs": [], @@ -675,15 +1238,18 @@ "dist_mic_samples = (np.linalg.norm(mics[:,idx_m1]-mics[:,idx_m2])/c)*fs *2\n", "\n", "gcc_sig_plot = gcc_sig[int(len(gcc_sig)/2 - dist_mic_samples):int(len(gcc_sig)/2+dist_mic_samples)]\n", - "gcc_lrp_plot = gcc_lrp[int(len(gcc_lrp)/2 - dist_mic_samples):int(len(gcc_lrp)/2+dist_mic_samples)]\n", "gcc_gt_plot = gcc_gt[int(len(gcc_gt)/2 - dist_mic_samples):int(len(gcc_gt)/2+dist_mic_samples)]\n", + "gcc_lrp_plot_loc_cnn = gcc_lrp_loc_cnn[int(len(gcc_lrp_loc_cnn)/2 - dist_mic_samples):int(len(gcc_lrp_loc_cnn)/2+dist_mic_samples)]\n", + "gcc_lrp_plot_sample_cnn = gcc_lrp_sample_cnn[int(len(gcc_lrp_sample_cnn)/2 - dist_mic_samples):int(len(gcc_lrp_sample_cnn)/2+dist_mic_samples)]\n", + "\n", + "\n", "\n", "ticks = ['$'+str(int(tick))+'$' for tick in np.arange(-dist_mic_samples,dist_mic_samples,dist_mic_samples*2/len(gcc_sig_plot))]" ] }, { "cell_type": "code", - "execution_count": 302, + "execution_count": 310, "id": "cc365369-8000-4807-960f-928a10c425b8", "metadata": {}, "outputs": [ @@ -693,15 +1259,15 @@ "Text(0, 0.5, '$GCC-PHAT(\\\\ell)$')" ] }, - "execution_count": 302, + "execution_count": 310, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -710,7 +1276,7 @@ ], "source": [ "# Ground-truth GCC-PHAT\n", - "plt.figure(figsize=(7,1.5))\n", + "plt.figure(figsize=figsize)\n", "plt.plot(utils.normalize(gcc_gt_plot),'k')\n", "plt.xticks(np.arange(len(gcc_gt_plot))[0:-1:20],ticks[0:-1:20])\n", "plt.xlabel('$\\ell$')\n", @@ -719,15 +1285,42 @@ }, { "cell_type": "code", - "execution_count": 303, + "execution_count": 311, + "id": "571016fe-7d21-4b3f-b715-f27152eb69f0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Signal at microphones GCC-PHAT\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(gcc_sig_plot),'k')\n", + "plt.xticks(np.arange(len(gcc_sig_plot))[0:-1:20],ticks[0:-1:20])\n", + "plt.xlabel('$\\ell$')\n", + "plt.ylabel('$GCC-PHAT(\\ell)$',fontsize=10)\n", + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_gcc_input_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 312, "id": "564efcd1-6d0e-494a-a3b4-167244b8907f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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7ObS7k4jIG7kqpHGGJxE1B0MaEbVpIoLvvvsOgOtC2o8//sirnRBRk1od0jZv3uyIOoiI3OKXX36B2WxG+/btMXToUKfuq3fv3rj66qshIti1a5dT90VE3q/VIY2D9InIm1m7OocNG4YOHTo4fX/WpTjY5UlETWl1SOPFgonIm7lqPJqVtcuTl4cioqa0OqQ5a7o6EZGjlJWVYcqUKbj33nuxYcMG1NTUKI+5K6Rt376dX3KJqFGcOEBEPq26uhr33XcfPvvsM3z44Ye48847ERYWhrS0NPz6668uD2nh4eEICAjAiRMncPToUZfsk4i8E0MaEfm0efPmoaCgAJ06dUJCQgKCg4NRUlICnU6HAQMGKNf/dVVI69SpE66//noAwDvvvIPt27fjxx9/xPHjx3H27Fm2rhGRgiGNiHzW6tWrsWTJEgDA22+/jbfeegvHjh3DqlWrMGbMGOUamgMGDECPHj1cVpe1y/OFF17AzTffjGHDhqF///7o0qULVCoV8vPzXVYLEXmuVl9xgN/6iMgT7dq1C3PmzAEAzJ8/H7GxsQCAoKAgzJ49G7Nnz0ZhYSFycnIQFRXl0tr++te/ori4GCdPnoTZbIbZbEZFRQUsFgsqKyuRmZmJiRMnurQmIvI8ftLKlJWVlaWcCL1RRUUFVCoVzGYzunXr5u5yiMgBTp48iYiICBw7dgx33XUXPvzwQ/j7e3bHgYjg66+/xh/+8Ad07doVp0+fdsmSIETkevZmj1aftbw5oBGR77l48SJiYmJw7NgxDB06FO+9957HBzTg8kz5cePGoWfPnqisrMS2bdtatB0RwcaNG/HWW2/BYrE4uEoiciXPP3MRkc9x5jCJp556Ctu2bYNKpcJHH33kVS3k/v7+mDx5MgBgw4YNzXqtiODzzz/H2LFjMXnyZDz55JN4//33nVEmEbkIQxoRucyBAwdw66234qqrrlKul+lI77//PrKysuDv748PPvgA11xzjcP34WxTpkwBYH9IExHk5+dj3LhxuOOOO2yuZMAJCETeze6QlpeXh5KSEieWQkS+ymKxYOnSpRg1ahS+/vprHD16FJMmTYLRaHTYPkpKSpCQkADg8qxJa4uUt5k4cSL8/f2xb98+HD58uNHnWkPvpEmT8O2336Jjx4545pln8N577wG4fG1lT53cVV1djWeeeQbLli1zdylEnkvsZDAYxM/PTyIiIiQrK8vel3k8s9ksAMRsNru7FCKfVFJSIuPHjxcAAkAmTZokN9xwgwAQjUYjJ06caPU+qqur5dZbbxUAMnbsWKmqqnJA5e4zbtw4ASAZGRmNPi8yMlIASMeOHSUxMVH5XZ47d04CAwMFgBw4cMAVJTdbdna28p749NNP3V0O+TCTySSffvqpnD9/3t2lKOzNHnaHtNzcXDEYDHXuNxgMsm7duuZX6CEY0oicw2KxyL/+9S/p2rWrAJBOnTrJ8uXLxWKxyPHjx0Wj0QgAueGGG6S8vLxV+3rllVcEgHTt2lWKiooc8w9wI+u/5+67727wOdu3bxcA0qFDBykuLq7zuDUYv/XWW06stGUuXLggV111lRLS+vTpI7/99ptDtl1ZWSn//ve/5c4775QuXbrIHXfcIfv373fItul3FotFduzYIUlJSZKYmCipqamyatUq2bBhgxQWFsrx48ft3taFCxdk9erVcvToUYfX+euvv8rw4cMFgAwYMEAyMzPl0qVLDt9Pczk8pDXWemYymWTRokX2V+dBGNLI2+zbt0+mTZsmr732mly4cMHd5dTr4MGDcscddygfwuPGjZODBw/aPOfQoUPSu3dvASC33nqrnD17tkX72r59u7Rr104AyLvvvuuI8t2usLBQAEjnzp0bPMZ/+tOfBIA89NBD9T7+8ssvCwCJiYlp9v4tFovs379f3nrrLUlOTpa5c+fKM888I4mJifLXv/5V/vKXv8irr77a4kC8bNkyASD9+vWT6667TgDIjBkzxGKxtGh7Fy9elI8//ljuv/9+6dSpk/K+s94CAgLk6aeflrKysga3cebMGdm6dats27ZN9u7dK4cOHZITJ05IRUWFVFdXt6guq3PnzsnXX38tOTk5sn///lZvr7UqKiokNjZWYmNjm93SeuzYMUlPT5dhw4bV+T1feZs9e7Zdx9T6Xu7Vq5d8++23Lf1n1XH69Gml1b72TaPRyLvvvuvW4+DwkDZv3rxGHzeZTF7ZoubtIe3EiRPywQcfyBdffCE1NTUu2++FCxdkw4YN8t5770lWVpYsXbpU0tLSZMGCBfLSSy+J0Wh02r5beiL3BT///LMSbKwnm5ycHI/5nZw9e1bmz58vHTp0UFp50tPTGzwZ7tmzR1QqlQCQqVOnNvsbbmVlpYSFhQkAmTVrlsf8HlqrpqZG+vTpIwCkoKCgzuO//fab0p35zTff1LuNbdu2CQDp3r17k+cGi8UiP/30k2RkZMh9992n7Nue27hx4+Stt96S06dP2/VvO3v2rLL95cuXS2FhoRKyV69ebdc2rH755RdJSUmRkJAQm5rCwsLkhRdekM2bN8u0adOU+0NCQmT58uVSVVUlFotF9uzZI+np6TJhwgTlPVvfzd/fX8LCwmTatGmi0+lk9erVUlhYKGazWSorK6W8vFx+++03OXHihBw5ckT27Nkj2dnZEhcXJyNHjpSAgACb7XXq1EnGjRsnf/nLX+Rf//qX/PDDDy57754/f95m+EG7du0kMTGx0QBbWVkp77//vkyePFn8/f2V1wYFBckDDzwgycnJ8vDDD8ukSZNk5MiR0rdvX/Hz8xMA8uabbzZazwcffGDzu+nYsaNDskR5ebmEh4crLbV79+6VpUuX2pw/hw4dKqtXr5aioiKXBzaHh7T4+Pgmn5Obm2vv5jyGu0LamTNnZOXKlZKcnCzPPvus8g31ySeflMcff1x0Op2sXLlSvvzySzl+/LjyB3zp0iX58ssvRafTyahRo2ze3FdddZU899xz8uOPPzqt7kuXLklWVpYMHDiw0RN3p06d5LXXXnPoG//EiRNy7733SkBAgHTs2FGCg4Olf//+EhYWJtdff73cfPPNMnHiRJkxY4Y8+uijkpiYKAsWLJBVq1ZJZWWlw+pwl5KSEuX3fu2119p8kI4bN67BD2tXsFgskpuba9OFNWnSJPnpp5+afO1XX30lHTt2FADypz/9qVn7/fOf/ywAZODAgY1+yHijRx55RADI//zP/9R5LD09XQBIeHh4gx/uVVVVSldzfUNVarvvvvvq/A137NhRJkyYIImJiZKUlCQpKSmi0+lk/vz58vzzz0t0dLTNB3a7du3k7rvvlvz8/Eb3Za09NDRULl68KCK/d+9269ZNfvnll0Zfb7FY5Msvv5SYmBib/fft21cSExNlx44ddX4n+fn5Ni0/11xzTb1BtF+/fhIaGiq9evWSzp07K0HDEbfevXtLREREvS19AOS6666TV155xand9ZcuXZK77rpLAEiXLl1k0qRJ9QZYkcufje+9957cc889yt+n9XbrrbdKdnZ2o5+bS5cuFQDSvn172bFjR73PKSkpUb6kPfvss3LnnXcKAPHz85MlS5Y0+t5uLFiZzWYZM2aMAJCePXvKvn37lMfOnDkjaWlpEhwcbPNvCgwMlOHDh8v06dNFp9PJqlWr5PDhw/b+apvNKWPSmpow4I0TClwd0kpKSiQpKanOG6SpW6dOneT666+Xbt261XnsxhtvVN7o1ltkZKQsW7ZMvv32W9m3b58cPnxYysvLWxyaqqur5d1331XGEVm/nWi1Wrnrrrtk1qxZMnv2bHniiSeUAdwAZMyYMfLdd9+1+veWm5tb59tyc24qlUoSExPrdLnZy2KxSE1NjVRVVcnFixfl/PnzcvbsWamoqJCzZ88q38yd5ejRo8rv/tprr5VTp05JZWWl/O1vf7M56c+cOVNWrFghH374oWzbtk0OHTokFRUVTq3t559/lujoaKWGq6++WtavX9+sff73v/9VWhv27Nlj12tyc3OVE/oXX3zR0vI91tq1a5Vv+7VVV1fLoEGDBICsXLmy0W1YP/QaG45y8OBB5ff4xz/+Uf72t7/JF198Ydcg62PHjsmSJUtsvjD6+fk12O1sNpule/fuAkDefvtt5f6qqiq5+eabBYCMHz++3pa/yspKWblypYwcOdLmbzsqKko++uijJs9tVVVVsmzZMptzb6dOnWTKlCmydOlSOXDgQJ33rMVikXPnzsnRo0dl06ZNsmzZMnn88cfltttuq/d8FBAQIIGBgRIcHCzjx4+XlJQUyc3NlcOHDyvbrq6ulv3798u///1vefbZZ+X2229XWkWtt7Fjx8qyZcvk5MmTTR4De1VXV8v999+vBHDr38zGjRttAuz1118vd911V52WxbCwMHn++eftPodaLBa59957BYAMGjSozrjT2pN9brrpJrl06ZJUVVXJE088oezziSeeUELj2bNnZf369TJ79mzld9+rVy+Ji4uTzz//XAn8lZWVcssttwhwuRV579699dZnMpnkxRdflOHDhzfYirpmzZoW/rab5vCQJiISGxsreXl5DT7eVJeoJ3JFSLN+85s+fbrNNz+NRiNPP/20JCUlybx58+S5556TF154QRYsWCBPPPGETJw4UTQajc1rrN94HnjgAXn33Xfl1KlTInK5CXvt2rUyderUOk3rV96CgoKkb9++MmzYMLnllltk6tSp8uCDD8pTTz0l8+fPl9TUVPnHP/4h77zzjqxbt05WrVolQ4cOVV7fq1cvef311+XcuXP1/ntrampkxYoVSqBs166dLFiwoM7YmpqaGiktLbVpKbxSeXm5PPjgg8q+R44cKTt27JCSkhLZv3+/FBYWytatWyU/P1/Wr18v7777rvzjH/+QV199VebNmycJCQkyZMgQmw+QKVOmyOeff25X9/B3330nycnJTbYcWrfdsWNH6datm/To0UMmTJgg77zzjpw5c6bRfZw8eVJycnJk+/bt9dZ06tQp5fev0WjqDK49evSoPProo41+61epVLJ48WKHhjWLxSIZGRlKSAwMDJQFCxa0eGzZlClTBIC8/vrrTT73/Pnzyolap9O1aH+erry8XPlbrj184JNPPhEAEhwc3OTv+rXXXhMAcscddzT4HJ1OJwBk8uTJrar3hx9+UP5W/f39Ze3atXWe8+KLLyrB88pQdfDgQeW9ZH0PWCwW2bJlizzyyCPSuXNnm3NYXFycfP/9982u8/Tp07Jy5UrR6/WtHtN55swZOXfunFy6dKlVw01MJpOsWrVKtFptnfP94MGD5YEHHpA33nhDvvnmmxbNULRYLBIXF6ecj6+cTWsNsNYAbb0NHTpUXnjhBdm7d2+Lzh3l5eUSGhoqAOTee++12cbf//53AS636B06dMim1iVLlijnM61WK9OmTZOgoKA659vaP6vVannooYeU4KdWq6WwsNCuOqurq8VoNMpnn30mb7zxhiQkJEhUVJRNC5yjOSWkmUwmGT16tEycOFHy8vKUjZvNZlm0aJEsXLiw5RW7ibND2pEjR+TGG2+0eTNptVr5+OOP7W7Vunjxovz000+yYcMG2b59e5OvO3XqlCxdulTGjRsnV199tXTv3l3at2/f4lYo6y04OFjS0tKaDB1WR48etRkPotFo5KabbpKwsDDp3r27zR9Zjx49ZPLkyfL888/LRx99JMeOHZOCggIZMGCActKfP3++8m2pOWpqamTDhg02A9kBSP/+/eWuu+6S+fPny9q1a+XAgQNSXV0tx44dk0WLFtU5bi29denSRWbPnq2MG6yurpZt27bJCy+8IKNHj7Z5bp8+fWTOnDny3//+V86dOyelpaVKHQMGDKh3Fp/Vnj175PHHH5epU6fKmDFjZNCgQXW6Vh588MEGw7XI5ffaq6++KpGRkZKent5gF+Kvv/4qd999t7LdqKgomxNtSyxcuFCAxmc0Wun1egEud3G15D3hLW677TYBIP/85z+V+6zv42effbbJ1+/Zs0eAyxMQ6vs9VVVVSd++fQWA5OTktLrempoapZu2Xbt28sknnyiPnT59Wvni1lALxfLly5XAr9PplPGG1ltYWJikp6dLaWlpq2v1VMePH5fXX39dIiIi6j2ftG/fXm6//Xa7B9hbLBZJSkpSgs0HH3zQ4HNLS0vllVdekZdfftlhAWXnzp3K58/SpUtF5PJ4SesXkIZaXdetW1cnmA0aNEgSExOVlt78/Hx5/PHHbcaZAZe7zRvqYvUUTglpVunp6eLn5yf+/v7KzRtb0UScH9Kqq6slNDRUgoKCJD4+Xn744Qen7MceFy5ckN9++02MRqMYDAbZtGmT5ObmSnZ2tixatEiee+45eeqpp2T27NkSExMjEydOlHHjxsno0aPlxRdfFJPJ1Ox9WiwWWbt2rfTq1avRFqjGQk5YWJhs27bNIb+Dn3/+WZ5++ul6u42t39Br19O+fXu59957Zd26dXLq1CkpLS0Vk8kkFRUVyrfoM2fOSGlpqZw4cUJ++eUXOXjwoOzevVtefvllGTx4sM32raH5yv2OGDFCGT9kvXXq1EkZ49W7d2+7xnfV58yZM/Lmm28qJ8XIyMh6p7p//fXXylR1661z587y1FNP2QSwzz77TBnP06FDB1myZIlDJq3s2LFD+Qbc1BeRlJQUASAPP/xwq/fryVJTUwWA3HnnnSJyeUas9f1pT7dTTU2N9OjRQwDI1q1b6zxubZXr0aOHw8JudXW1MsYtMDBQmfhgPWY33nhjg+8Xi8VS58tUly5d5NFHH5WvvvrKZyaG2KusrEw2btwof//732Xq1KnSs2dPm9/N7NmzG+0S/e2335SABkCys7NdWP3v3nzzTeV8qtfrlda1+++/v9Fjun37drnnnnvkpZdekj179jT43OrqatmyZYskJibK+PHj3To+115ODWlWBoNB9Hp9iz68PYUrujt37tzp09/87FFaWir/+c9/ZP369bJlyxb54Ycf5MSJE3LhwgU5f/687NixQ/75z3/KI488IiNGjFCa/BMSEuxuuWuOM2fOyJYtW2TZsmUyZ84cGTNmjM23tltuuUUyMjJafdwsFots3bpVHnvsMZsQplKpZObMmbJq1SplAdILFy7Ixo0b5cknn7TpXg0JCWlRt86VNm3apATEvn37Kt/ETSaTJCQkKB/+PXr0kAULFsiIESNsgvQ999wj8fHxyn3Dhg2ze/yYPaqqqpTw3FQ3hbUFsrmzAb3N3r17lS8P58+fl2effVaA5nVNxsbGCgB56aWX6jxmbemub3JCa1y6dEnuuece5ctGTk6O8vdVu3WtPsePH5cxY8bI7bffLm+//bZPTPpxFIvFIgcPHpTZs2fbtBotWbJEmRl94cIFycvLk2nTpimzZgHIa6+95ta6p0+fbvOl/Oqrr/bq7NBaDg9p69ata7SrxVt5+xIcvqqystJhi1vaq7q6Wn7++Wc5cuSIU7Z/9uxZ+fjjj2XLli1NrohvsVjEYDDIkiVLHDpbt6ioSGkt69Chg8ybN0/p7gIgjzzyiLKUgsVikYKCgjotGwDkqaeearTbtKWsA92XLFnS4HNOnz6tnOibs2CmN7JYLNK/f38BIHl5ecqg96aCTm0ZGRkCQG677Tab+0+cOKG0rjqjhf/ChQsyefJkm/fNTTfd1OZaw5zlm2++sekSve666yQ+Pr5OS/3o0aM9Yv3A2uPT/P39623ZbUscHtJ4WSgi31BRUWEzVhCADBkyRDZt2tTga/bv3y9xcXESEREhGzZscFptixcvFuDymmkNsc56HDFihNPq8CSPPfaYAFBaVwcNGtSsWdrW2Zvt27e3mWhgXQrj5ptvdkbZInJ5Edfaa3Lp9Xqn7astqqmpkezs7DrdoP369ZPk5GS3Dq+pj8FgkOHDh8sbb7zh7lLcjpeFshNDGrVFNTU1smDBAundu7fMnz/fY65pt2vXLqULp6EgMmfOHAEgiYmJLq7OPfLy8mw+gNPT05v1eovFogS8jRs3Kvddc801AsDpX7orKyvlgQcekGeeeYataE5SXl4u8+fPl8cee0w+//xzt1/RgJpmb/bwExGBHbKzs/HYY4/V+5jZbEZWVhbmzp1rz6Y8SkVFBVQqFcxmM7p16+bucojatJqaGoSEhMBsNmPnzp2IiIio8xyNRoPi4mJ8+umnmDJlihuqdK2Kigr06NEDVVVVCAwMxNGjR9GjR49mbeORRx7B22+/jZSUFKSlpeGrr77Cbbfdhs6dO+PEiRPo2rWrk6onovrYmz387d1gUVFRg4+pVCrMmTMHeXl5zauSiKiWgIAA3HbbbQCAL774os7jRUVFKC4uRvv27ZXn+bpu3brh1ltvBQDMmjWr2QENACZMmAAA2LRpEwBg5cqVyvYY0Ig8l90hrby8vNHHVSoV7GyUIyJq0O233w4A+L//+786jxUUFAAAxo4diy5duriyLLdKTU3Ffffdh1deeaVFr7eGNIPBgMOHDyMnJwcA8Oc//9lhNRKR49kd0qKjo5Gdnd3oc5oKckRETRk/fjwA4KuvvkJ1dbXNY3q9HsDl81FbctNNN+E///kPBg4c2KLX9+/fH9deey0sFgsef/xxnDt3DkOHDsXYsWMdXCkROZLdIS0mJgb5+flYv359g89prEuUiMgeN9xwA9RqNSorK2EwGJT7a2pqsHnzZgCAVqt1V3leKyoqCgDw2WefAbjciubn5+fOkoioCXaHNADIysrC//7v/2LSpElYv349KioqAFweALd48WJ0797dKUUSUdsREBCAP/7xjwBsx6UZDAaUl5dDpVLVO6GAGmcNaQDQrl07PPzww26shojs0ayQplKpsGvXLkRFRSEmJgbBwcEICAhAcHAwSktLkZSU5Kw6iagNqW9cmnU82vjx49GuXTt3lOXVbr/9dqXl7O6770avXr3cXBERNaVZIc0qOTkZFosFu3btQn5+PsrKypCamuro2oiojbKOS9u6dSuqqqoAtN3xaI7SvXt3ZZZoQkKCm6shInvYvU5aXl4ewsPDMWjQICeX5FpcJ43I81gsFvTs2RNlZWX45ptvcMMNNyA4OBiXLl3CTz/9hGuuucbdJXqlkydPori4mBMGiNzM4eukhYaGQqPRIDIy0maWZ1MzPomImsvf399mXNqWLVtw6dIlXHXVVRgyZIibq/Neffr0YUAj8iJ2h7Ti4mIUFhZi586dNlceSE5OxqxZs5CdnY2SkhJn1Ngog8GA0aNHu3y/RORctcelWbs6tVotZyQSUZth9+jbsrIyTJ8+vc79Wq0WERERSEtLc9mMK5PJhJSUFADArl27bKbpE5FvsIa0rVu34ujRowA4Ho2I2ha7W9JMJlO998+aNQtJSUk4dOgQdu3a5ai6GqVWq5GZmYnMzEzMmjXLJfskItcaMWIEQkJCcO7cOezfvx/A7yvnExG1BXaHtNOnT9d7f0xMjPL/wcHBra+IiAi249IAYOTIkVw2gojaFLtD2pUTBurDy0IRkSNZl+IAeJUBImp77B6TFhMTg5kzZ8LPz6/Bi/J6w2WhLl68iIsXLyo/W6+aQESexzouDeB4NCJqe5p9Wajly5cjMjKyzmWhdDodQkJCnFKkI6WmpkKlUim3ll6wmIicb/jw4Rg7diyGDh2KP/zhD+4uh4jIpVp0WajY2Ng6l4UymUyYO3eus+p0GJ1OB7PZrNyOHDni7pKIqAF+fn7Ytm0bfvzxRwQFBbm7HCIil2rRBfCSk5ORnJyM3bt3o6ysDBEREVCpVHa/3mQyISoqqsEZo/XJyclBeHh4C6q1FRgYiMDAwFZvh4iIiMiZWnWV4lGjRrXodWq1GoWFha3ZNREREZFPa1VI8wXWS5dyAgERERG5gjVzNHX59DYf0iorKwGAEwiIiIjIpSorKxsdLub1Ia20tLRVr+/Xrx+OHDmCrl27Ou2agBUVFRg4cCCOHDnS6NXuyfvw2PouHlvfxWPrm7zpuIoIKisr0a9fv0af57UhLT4+HgCwdu1aAJfXUNJoNIiNjW3Wopf+/v4YMGCAU2q8Urdu3Tz+jUMtw2Pru3hsfRePrW/yluNqz4RLrw1pmZmZNv8lIiIi8iXNWieNiIiIiFyDIc0FAgMD8be//Y3rs/kgHlvfxWPru3hsfZMvHlc/aWr+JxERERG5HFvSiIiIiDwQQxoRERGRB2JIIyIiIvJADGlEREREHoghzQ1yc3OxcOHCBh83GAwYPXq0CyuiljIajUhJSUF8fDyio6MRGxsLo9HY4PN5bH0Dj6Pna+wY5ebmIiUlBSaTybVFUatZz7kLFy5ESkoKYmNjYTAYbJ7jU8dXyKXKy8tFrVZLenp6nfvj4uIkLi5OwsPDhYfG8xUVFUlcXJzNfcnJyQJAioqKlPt4bH0Dj6Pns/cYpaenC4AGb1qt1sWVkz2KiookOTnZ5r7MzEwBIIWFhcp9vnR8uQSHiy1cuBCpqanQ6XRITk5u8DkpKSngofFs8fHxSE9Ph1qttrk/ODgYGo0GhYWFdV7DY+sbeBw9X2PHKD4+Hmq1GiEhIXUeW7NmDXJycqDRaFxRJjWD9fOzuLhYOe+aTCYEBwcjLi5OuQKRLx1fr70slDfS6/XQarVITU11dynkAGvXrkVZWRlycnJs7tdqtcjNzXVTVUTUFLVajfT09Dr36/V6aDQar/kAb2vCw8MbPDZlZWXK//vS8eWYNBcyGAwIDw93dxnkIBEREe4ugYhaID4+vs59JpMJBQUFmDFjhhsqIntotVoUFhba9F7o9XoAgE6nU+7zpePLljQXWbhwYYPdm+SdCgoK6r3fYDB41Tc1oramvr/PlJQUpbuMvINer0dqaipycnJsGkB86fgypLkAW9DaDr1eD6PR2GCAIyLPs2LFCkRHR7u7DLKTwWCAXq/Hzp07odVqodVqG32+Nx9fhjQXWLNmTb394+R74uPjkZyc3ORJg4g8R3p6OoqKitxdBtkpPDxcafhYsWIFQkNDUVhY2GAPhjcfX4a0JphMJkRFRTVrvZXaTa8rVqyw6Ssnz9HaY3ul2NhYaLVaBnIP5ejjTb4hNzeXx9iLxcXFKeul1Tej3tuPL0NaE9Rqdb0H3h5GoxHdu3evs0QDeYbWHNsrLVy4EBqNhgHNgznyeJPvyMzM9OoPcbo8iUuv18NkMtX5vPX248uQ5kTWsUlXjk8ymUxYs2YNioqKEB0d7XWzTciWdbmN2gGN4xCJvINer0dsbKy7yyA7DB48GOHh4XWWPbIGM6PRWOe86+3HlyHNiRoa0LhixQrMmjWLsz19gMFggNForHMs9Xo9QxqRh2vsEm7keYxGY72fqdbLQl15zvWF48uQ5ialpaUteow8h9FoxJw5czBr1iyba7GWlpbCYDDUG8J5bH0Dj6Pns+cYWT/Eu3fv7uxyyAHS09PrhDTrjPr6ltfwhePLkOZC8fHxyptmxYoVMJlMymBz6+PA5ZXsASA6OhoajcbmOeQ5oqOjYTQa61zcF0CdLmweW9/A4+j5mnOMrGOGua6hd0hOTkZubi4yMzOhVqthMpmUYUX1/f35wvHltTuJiIiIPBAvC0VERETkgRjSiIiIiDwQQxoRERGRB2JIIyIiIvJADGlEREREHoghjYiIiMgDMaQREREReSCGNCIiIiIPxJBGRERE5IEY0oiIiIg8EK/dSUTUCnq9HgUFBQgJCUFycrK7yyEiH8KWNCKiFjIajUhPT0d6ejo0Gg1MJpO7SyIiH8KWNCKiFoqNjUVWVhYAoKysDGq12r0FEZFPYUsaEVEL5ObmAgDCw8MBgK1oRORwDGlERC2QkpKC+Ph4AJe7Pa1hjYjIURjSiIiayWAwwGg0YubMmQAut6pptVo3V0VEvoYhjYiomdasWYPw8HCo1Wrk5uZixowZ7i6JiHwQQxoRUTPp9XpotVoYDAao1WpoNBp3l0REPoghjYiomQwGA4DLY9HYzUlEzsKQRkTUAoMHD2Y3JxE5lZ+IiLuLICLyFnq9HtHR0eCpk4icjS1pRER20uv1MJlMXLSWiFyCIY2IyE4RERGYMWMGtFotjEajcv/ChQu5mC0RORy7O4mImslkMiE1NRWDBw+GyWRCXFwcW9eIyOEY0oiIiIg8ELs7iYiIiDwQQxoRERGRB2JIIyIiIvJADGlEREREHoghjYiIiMgDMaQREREReSCGNCIiIiIPxJBGRERE5IEY0oiIiIg8EEMaERERkQdiSCMiIiLyQAxpRERERB6IIY2IiIjIA/0/uQQunbOT9NIAAAAASUVORK5CYII=", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -735,26 +1328,26 @@ } ], "source": [ - "# LRP GCC-PHAT\n", - "plt.figure(figsize=(7,1.5))\n", - "plt.plot(utils.normalize(gcc_lrp_plot),'k')\n", - "plt.xticks(np.arange(len(gcc_lrp_plot))[0:-1:20],ticks[0:-1:20])\n", + "# LRP GCC-PHAT - LOC-CNN\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(gcc_lrp_plot_loc_cnn),'k')\n", + "plt.xticks(np.arange(len(gcc_lrp_plot_loc_cnn))[0:-1:20],ticks[0:-1:20])\n", "plt.xlabel('$\\ell$')\n", "plt.ylabel('$GCC-PHAT(\\ell)$',fontsize=10)\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_gcc_relevance.pdf',bbox_inches='tight')\n" + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_gcc_relevance_loc_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n" ] }, { "cell_type": "code", - "execution_count": 304, - "id": "571016fe-7d21-4b3f-b715-f27152eb69f0", + "execution_count": 313, + "id": "7b900093-f291-4776-890b-6ef6d372cf72", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -762,18 +1355,18 @@ } ], "source": [ - "# Signal at microphones GCC-PHAT\n", - "plt.figure(figsize=(7,1.5))\n", - "plt.plot(utils.normalize(gcc_sig_plot),'k')\n", - "plt.xticks(np.arange(len(gcc_sig_plot))[0:-1:20],ticks[0:-1:20])\n", + "# LRP GCC-PHAT - SAMPLE-CNN\n", + "plt.figure(figsize=figsize)\n", + "plt.plot(utils.normalize(gcc_lrp_plot_sample_cnn),'k')\n", + "plt.xticks(np.arange(len(gcc_lrp_plot_sample_cnn))[0:-1:20],ticks[0:-1:20])\n", "plt.xlabel('$\\ell$')\n", "plt.ylabel('$GCC-PHAT(\\ell)$',fontsize=10)\n", - "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_icassp/ex_gcc_input.pdf',bbox_inches='tight')\n" + "plt.savefig('/nas/home/lcomanducci/xai_src_loc/endtoend_src_loc2/plots_spl/ex_gcc_relevance_sample_cnn_SNR_{}_T60_{}_n_source{}.pdf'.format(SNR,T60,n_s),bbox_inches='tight')\n" ] }, { "cell_type": "code", - "execution_count": 306, + "execution_count": 314, "id": "e90fc344-880d-44c4-9b64-672360b83b73", "metadata": {}, "outputs": [ @@ -782,9 +1375,10 @@ "output_type": "stream", "text": [ "Estimated time-delay\n", - "(GT): 1.5 samples\n", - "(Microphone signals): -3.5 samples\n", - "(Relevance signals): -0.5 samples\n" + "(GT): 3.5 samples\n", + "(Microphone signals): -4.5 samples\n", + "(Relevance signals LOC-CNN): -0.5 samples\n", + "(Relevance signals SAMPLE-CNN): 0.5 samples\n" ] } ], @@ -793,8 +1387,117 @@ "print('Estimated time-delay')\n", "print('(GT): ' +str(np.argmax(gcc_gt)-(len(gcc_gt)/2))+' samples')\n", "print('(Microphone signals): ' +str(np.argmax(gcc_sig)-(len(gcc_sig)/2))+' samples')\n", - "print('(Relevance signals): ' +str(np.argmax(gcc_lrp)-(len(gcc_lrp)/2))+' samples')" + "print('(Relevance signals LOC-CNN): ' +str(np.argmax(gcc_lrp_loc_cnn)-(len(gcc_lrp_loc_cnn)/2))+' samples')\n", + "print('(Relevance signals SAMPLE-CNN): ' +str(np.argmax(gcc_lrp_sample_cnn)-(len(gcc_lrp_sample_cnn)/2))+' samples')" ] + }, + { + "cell_type": "code", + "execution_count": 315, + "id": "b1be3b95-19a6-4762-9b1b-aeaa7a80cb45", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.6" + ] + }, + "execution_count": 315, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "T60" + ] + }, + { + "cell_type": "code", + "execution_count": 317, + "id": "69302c4d-3aef-4d90-9bc7-9bfda3affd7e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.48125 , 5.375 , 1.33693965])" + ] + }, + "execution_count": 317, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sources_gt[29]" + ] + }, + { + "cell_type": "code", + "execution_count": 318, + "id": "dc05cbb3-5954-4079-8ef2-538ff8342638", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.48125 , 5.4375 , 1.23807996])" + ] + }, + "execution_count": 318, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sources_gt[50]" + ] + }, + { + "cell_type": "code", + "execution_count": 319, + "id": "d019893f-19e2-4d9b-ad79-02a0234a9000", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.8640625 , 5.28125 , 1.41723473])" + ] + }, + "execution_count": 319, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sources_gt[70]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9368eed9-64e7-4353-a9a4-db00bc78f710", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ae0e730-3fa8-49d7-a4a3-c26e4147e679", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc051b10-068e-4327-9d52-50984081caf3", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {