diff --git a/examples/01_basic_usage.ipynb b/examples/01_basic_usage.ipynb index e0152b5..fc705cb 100644 --- a/examples/01_basic_usage.ipynb +++ b/examples/01_basic_usage.ipynb @@ -223,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 1, "id": "c8e9cc78", "metadata": {}, "outputs": [], @@ -244,13 +244,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "bb7e5786", "metadata": {}, "outputs": [], "source": [ "try:\n", - " from supports.linf_utils import plot_3D_histogram, load_histograms\n", + " from supports.linf_utils import heatmap, annotate_heatmap, get_heatmap_array, load_heatmap\n", "except ModuleNotFoundError as e:\n", " raise ModuleNotFoundError(\"\"\"\n", "\tFirst, ensure you have installed the addition to the repository with the command:\n", @@ -277,30 +277,20 @@ "id": "138c0a5f", "metadata": {}, "source": [ - "Internally, $l_\\infty$ compares two normalised histograms:" + "Internally, $l_\\infty$ compares two normalised histograms, represented here as heatmaps:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 3, "id": "6b176f6b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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YVBtZkwkWknTMhSQZG4EHjS9qQKCFSP4za9asoerVqxtiLKZ8bSXJ4JxRSMfuVWt6zN9rigacn9IXRt2JBeUCpVqy0UXxQM7XTniyqeYzTUqbamWkIxLJ6CUdZAnwfmOQWRq4+YckGZtnXwKxRVYCr4GCO4DuMeTQjYSSEJCXRyMBHjY96TFfryki1Oem7sTyJNGvrE/4Uks2+1xFAP52XAMc3KaaD4Zym2p8DyJttNaLnI70RDr4O7jNtnQN9Q9JMg62RebGYrwzioslGglek+HpMeze6tWrF9TO3e6dt5ES/Z7UknG99NQngoETGhSw2OJ64OBqBNgY4V8rbaqNAt5fTiiAdA31DUkyDvR94cZiSEPUqlWLdZDNnTvXlF0tzhEijPh9IBcIXBrxmiLuwI1SS1bXJ5SDo1z+xqgFxwkkowYWXZAIrgNIxwqbaiPBn18OXq/hkK6hhSFJxgJwoT/kqPHAGGUsBv8YpGmAQEQy/QHpMRAMXtebSnO4k4yW+oQ6VWSkhpgTSQZQ1mTUg7RYnDlJwycJ7ea4nsrBUDvVG3Du/ubApGvoJUiSsWj2BS2yKMx37NjRcGMxM0gG5ILfhYcZaSGjCIYjVElGS6qI79q5hphy144jFOVv9MzJeLKA4G3lXL1Br021mZGMP0SEuWto6N/NNoI7AfKdT6C7Tvw8VIcxNOjJWMzI6ACvgTQcfhdak7ELNxr83EXuMDILuA/UGmJ81473GPUdPQuokyMZreftz6Yaz5iVjRf+IplgXUMjQox0JMmYAD5NzLvHeGjMdzB6HgBuLIYb0FfKyohIBjc4fhf+5b8L3VO8xdooIKoDYL/MVZPxr8gdRmZBvWtXTtYjylFO1uMaqeVvnEwygRKBXptqNF4YSTp6IxlfUGqu+SKdl19+me644w7q2rUrOQ2SZCyShlFO5Wu9QZXGYs2aNfOZRgmWZJCKA8Fgh920aVP37zKyfoLXQYoI3UQAGgkwQMql+rFw8MVUtGKvVVDLuagn6wH1vIkTScYoWRktNtVKsztcu2C7/cyMwCO8kM66devopptuIidCkoyBUEYv6tZkftNoIQK9xmLBkAzOFWkadEF5SsUZRTLYkWNnjlpP48aN2UODtAZPG/EOIzRH4Hy4CjAnnVBRTQ52sp7L3+A64jrxawI9MScZt5lFjmrJIH7N+L2FRgJeJ/OmRqDlObeqBhRRcF4gTi3+TyJCkoxFsy/KSMZoY7FAyYB3qiHdgE41T3M2vrTLtIKrQSMywd+knKTmUHcY8W48LKhoaeWqyTy9Zubsiajgs1A4uHEbdurYjPBo0CnzJlYJZCqvGe/240StVCPQ47AabE1GL3hEG+jws92QJGOwLbI/S1lfC3agxmL89+ohAyzgSI/hoYKQprdUXDD2y/xvggwLHvCaNWuy1+MDa/6Kvcq0EU+B4LyVsydc/sWoeo6TiAvXAJsQ/O1IpzrJuM2uNJ9Spw5qBHptqgOpqxoBGcmEIbTYIquB7/FURA/WWEwPyeC8kTLAUbt2bZZS8HXegabLlA6ZjRo1KvQ38d+n9XU9qSZjYQDhKHfwSuvlcKnnKAv/vozbMJ+D6FAU4zYrpf59Qa9NNa4fzt1qrbrMglkhJ0KSjMW+L2oiMMJYzNtrq4FFB+kx3LDXXHONe5DTFwIhGaTf8DfhfPA34SFVvyYQaBpOOXuirudwActwqef46i7TY9yG62RlClLU9nUtNtUA/m9Vg0pOwTyNJJkwQTDSMNj98IVVaSymTCUFCn9kgIcECz8eCvUgp7/X1UMGKEgjDefLAsDohUzWc4w1buOkY6T8jRpO6YpTi6NiU5iSkuJumEGtxGxF7oyMDPavTJeFOAKxRfYWbeA1uLHY1Vdf7b6Bg4G3SIbrnOGBgM4ZCE3PeWutySi71EAu6IbyBr3pMr1Q13OwEHDSUddznNSR5QmBzsl4SkHygjha51EQxwKrJJ1g5G88nbeIkYw/8OceNVNvitzKlGSJEiWCJh0ePUmSCWEEmh5TAz+HXQkIBjUEo4zFvJEMQmzM2eB3ak2PBZIu42k4LOZ6NM6skJZRtgEr6znKQq+ynmP04KnZMGoY01NBnNcm0L2mNG4zIk0karpM73l7UiMw0qaakwyuvVONASXJmGiL7KnNGYua0cZintJa3AYAOyk96TF/r6sG8tVIw+FBgseMlt9jdiSjR0tMXc/BA42/gbe1Wq2LFQjMSDvhb+ade7hflbUJdZqI1730XCcnKxX4+jt92VQfOHAgIBsI3lnmxOsFSJLROPsSDMHgAUUxGqE0yAUPrdHgaS0cyK9DSJDbAARzc3pLl+FzmEBH11KNGjXY7lfP7xHlgVHXc7AJwMKA94rLuthVHBdpsfZm3AZyVuuHcfkbbzt2u9qArZaU8TRMm1FgAwHC5jbVStLxRCY8knEqJMlomH0xylgMN5NZ+X8+f4JJeqSDkB7j3VfBwFO6DAsvSBN/W/Pmzd3tn8G+riikgwca7d3qeg7IW7R6jl3XUI9xG66VcvHk5ywSWWtFMIOYET5sqlGfRYSobKnm9xe+x6hIZuTIkfTZZ5/R0aNHmfLG8OHD2VrhCe3ataNFixYV+XyXLl1oxowZmn+nJJkgZ1/0GIutXbvWcM8XDpwz5mzwQCM9ZtSkt5oMUBxGegyLDH5PoMVgUUnGXz0Hf79I8zkipJ30GrcpPZCcBiPFMSMVNtWA2nsI60Xfvn1Z6g2bHWQOQE6BYtq0adSvXz8aPXo0U/j44osvqFOnTuw+5gKtSvz8888sQuUAEYKY7r33Xl2/V5KMyliMt1YGayyGgjvCXLONxXDemO7GooebFeKWZtV6UMhE0wJSY0iRBfN7nEAyvorjakdHPp+DXSonHavqOXaTjB7jNuygkWIFkNLldR9R5W+slJSJVNUL0aU5dOhQGjVqFItykGrHs9e+fXt6++232cZHD4YMGUI9e/akxx9/nH0MskFEMn78eHr99deLfD/eFyWmTp3KNhKSZAIAj15WrFjB3kS0vgYKtbFYnqJbydvEf6DgtR50AXERTaMXHE6MIBcsEEa1XIsMreTnaT6H1ymUMv18ITWjniNCJKN38cSuHM8aoj7szpXGbbxzTRT5GzMjGX9AqgzS/rhGuCbff/89LV68mBYsWKA7TYuIBKaJ/fv3d38Of0eHDh2Y5YYWjBs3jh544AHdrdRivpM2zb4ohyWNMBZL+fZbmtKnD2Xn5FByrVp0eYsWdO0jjxAZUPgHsSBthTccZIY8OPdpMRK4OeFxgt+H7jGjCpBOjGT01im81XOUw47BwonXkC/SPBpWGrepnS9xnYyYNTEKVotjAsiIYIOC63DLLbewQy8wJI21Ti1ZhY+59YYvYAAVG1oQjV6ELcl4mn3BzRNIpKE2FsMN8c0999C6guIYbsm0LVvYsW3iRBpfogRVataMWnfrRtd166Yrj6/s6kKXGnaGWsQ3AwFUahHB4LXxdxm5gxN9921mPYenjLhiMk+vBVLPcUIko4a63unNuA3Xiis2+DJuC9VIhkMEBWaQC3QVvTUJ+EJYkoy32ZdASEZtLHZ6zx4a1L49nTlxwuP3s9+UlkYHFyyg6QsW0NSnnqLEK66g2v/7H3V46imq0by519+Fc8ZDhwcQv0uZMw1WLVkJvA52lKj1IH2IKMnoB8sMUgzHeo5TScbXOXszbgPpKI3b+LXS6wfjtEgmo6C7LBggpYvzRkOBEviYD5L6iqRQj3nvvfcC+t3R4Tr7wmUtlDennsI8vg+7UQxYcWOxxaNG0Q8vv6yLqKLQcHDwIG389lt25MbGUtl69ajp7bdTx169qESBUB/SVYiWkGK59tprixRKjWoqUFsw4zXxNxoJRHwgTJAzr1cYlT5yCnzVczB3guujtZ7jNJLRIynjzbgN10ntB8NJx0wbbzsimczMTPd9EiiwXmBjOm/ePGbjDODZxse9e/f2+bPTp09n9+fDDz8c0O8OG5LhmmG+pGG0RjLYWWEh5irDcbGxNLJzZ9q8YEHQ5xkFefb162ne+vU0Z+BAikpOpvKQym/Vijo88ghLkXlaVIwgGS6iiQeVWzCjK8jIvD/IErM8AHb0OGfspnj6iC+q4Wa/7Kmew0nHVz3HiTWZYMQxlSZkSj8YXCcIzqK+YEQa0te5W92UkFlQkwkWaF/u3r07m21D2gstzHht3m326KOPshb0QYMGFUmVgZi4MrVeRIfT7IsnW2QltHR/KY3FMLB3bMsWGnbTTZSemmr4uWO/5ELP/KJF7Fj32WdUrGpVqtexI3V65hmqVLeuIYV0rhLAZ3qUIppGprUQEWERQMEXqTjsTnHjYrFQ2y9juI+nj3jx14lzFYFAvXtX1nM4IYOUcF0QFYraiWWFOKYnPxh1GpIbt3H5m2CuF9YHq9utswyqydx///0s+hswYIC7U3TWrFnuZgCkItXvC2ZolixZQn///XfAv9dZd6cJtsjqG1Y5fKS+ubBAgmS4sdjcwYPp1wEDLKstROXlUfaePbRmzBhaPWYMuRIS6LKGDanF3XdTgy5dAjoPZRt0ixYtiqgEGNEFhmuHNlXc4IiQQCwgHF/2yyj+YlHlO1T8bUonTDNl6J1Uz8H7hvcQO9JAdcSshpmSMt6M23AfqVWSA9m82NVdlmSQAjNSY97SYwsXLizyOa58EQxClmQC8X3x1sLMjcXwddRDoiMjaWi7drRjxQqyC/hrIrKz6URKCs1MSaE/X3sN1VBa0a4dtX38cWpy001+/2bsjpG6QuHUm0pAsA0F2IXh2uFclKrT/sgL34dokQsNcvkNEBWaEvhO3oyUiOhQLqS8BRjXwFM9hyv/ikTIVnrJeDNuU25elNfK3yyTHTWZjIwMxxqWhSTJBOP7oq7JeDIWO7B6NY249VbKTEsjkcBu+zNnaMevv7IjNyqKSlavTg07d6ZOzz1H5VVyFFy+HTtjb3UeJRkE0sUEQsBgKrqEMDukfDj1imnyCXLI8+A9UjthKlNrwThhirQYawHeF5COr3oONyMTpcHCTi8Zb8Zt/F7ig6NKbTrlPWFHJJOVleVYL5mQI5lgfV+UxXNPxmIzBw6kGR9/7Ihia1RuLmVs305/b99OK1eupBEFoTCuDcgFuf0mTZr47VpRihpqvZb43t27d7OjXr16rJjo6XUDvY54yJUWudwJk89V4G/kCwUOK1tcrYb6fdFTz7ErChTFFdObcZvyWiESUjYRWB3JuAqI0O45mWAQMiSDGwT512CELXkkg24VpHi4sVhEbi592qoV7V2/npwCLN/HC46a5855TF1p2dHyB0orIYDkEb0gxIduGxf/83iOBpG12gkTD6VS2RaLKF8knKSTZURU4KmegzoOj3J4FGhlPUdUmX/1teLGbbhWqCGirohnB0VzHvFYQdCZBtZk7EB0qKTHePdYMMKW+FksxNj58zTSrsWL6as77qBzWVnkFKDNAZMt+c7gRBcvXGA7M8ylIKpAMU/PnIJWQuA1Hi514+sBNGsnq9ydIsWpXCi4Tha+pkytiVwk1wI91xKpNWUUiI0Zl75R1nPMnK53ygCp0rgNwLXB2oBzVxq3mS2ImpmZKWsyTrdFBvA62Nkh9YIuK9w4v7zyCs0dPpxFBU4B3MAxE53fT5eP7KwsFl00aNBAt/gnv57+Ote4QrO/Go/yda1IO6oXCr6oKovkytSaE1KhRi7YiOrUvjD8+vDpemW6yAjtOlEjGX/ApgnXGnVBEApP0yoJGpG7suEiMsi/E/crok+ZLrMByuglGFMxpbEY0i5IkcVHRNBHTZrQwa1byUk4iTkeLzcqxC0DuVH9pcuwYPDWbj0KzXYJZKoXVS5iyQu//Hvw92CxCNQvxyoYeQ2VvjDKeg73N1HWc/hsSiCpRzsL/8FCWZNRp2k5QeN6gaDxuWSFAVkgxmNIOwOSZASeffH3WlhYEPpiQBA72tljx9Kbt99O5wvqGE4A4riDkETz8vWYqKiAb1Jf6TLMsqDGg8VIr0KzCCrMnkQsQZhYWHn3Hb6mVCEQLbVmZupJWaPg0/W8qw/DtIhcA0k9ilL4DwTeusvUBK00bjtVUBvk8jdK10t/wGvw13Yqop1sixzMbkhpLAaJBTwg3/XqRcsmTSInIbsgPeZ5hDQfwXjYeCMZPDiI/hC5oINMtMU3EOB+QiSLvxmGUVyCXjnIp0ytmeEPI3J9Q93VF2g9x6npMq4eouXcvRm3nVa4qiISUqYiPUWFvOjvxOvlKJLhtRfczDzPGcyDpTYWyz59mga2bk3Hdu8mJ+E0aiEFnWS+oDROCwRKaRmlBA33zQnkvRAhkvEHpQS9ul6h1BPjpGOmMKOI8FbP4ekiQLmI8pkTp6bL+DMQyIYqUmHcBii7/HhUyKNmXCtu3AaSMaoFf+TIkfTZZ5+x7jjYKA8fPtyndD+i1jfffJPZMOM8UYuC3lmXLl1Ci2Q4weANWbVqFXNyC/SCezIW2/Drr/R/3btTjhc5GRGRV0AuWtXScgtSi4GCT/3jwUD0h/eCR3+Bwgkk469ewXemaHrAzhSLqDK1ZoWmmCidWp6uD1dpUNZzsIAiAnKiQoMRGRRfXX48FQlFC9QKIVTJVR0QRQeziZk2bRoTyITlMkYLQBadOnVi9y338VEC59OxY0f2tR9//JF1pYIM1bJTjicZpTQM3pRg0j6ejMW+fewxWjFtGjkJ5wvSY3oqRkZEMthRoT2Zzw4FO2viNJLxtTOF9zruU+UigftNKdVvlrSLKCTj6fqo1ZK53hpcGnG9QELKnbvoKVdlF6vRiI2NLWTchrrg7bffzhZ4ZF5wna677jq68cYbmVqy3i7RIUOGUM+ePd2KyyCbGTNm0Pjx4+n1118v8v34PO7lZcuWuTcEeB8DQbRTpGH4rjAQWQe1sVjG0aP0TpMmdPIgyuXOwdmCAr9eGcxgBTzxfiC9iHAZ0jpGLGoiLozBAA8i6lO8u85XK7CR0i6ikoyveg5frEEsuD5otsDmDx+L4H7pDXp0EINF8eLF6fnnn2eaa2PHjmWLPrxfcNx22226SAbXds2aNdS/f3/35/B3ICu0fPlyjz/z+++/s2ae5557jn777Td2Xz/44IP02muv6V5/o50y+8L/MHxe6x/pyVgs5bvv6Lunn3Z3pzkB2O8fLWhRDgSBRjL8+uGawwIAO3aj4PRIxh9AIkgx4MDfyVNrSutlpbRLMKk10RZjLfcVUmdcuFJPPcfu87ZDHDMpKYk11+AA8egFIkc8w1wklAMfg+A9AZJQ8+fPp4ceeohmzpzJarDPPvssW5vfeecd55KMN1tkgL+5IActqRq1sRhyxd/ccw+t/fNPchJyCtJjwegNeItkDm3rRdu2LqVS5TtTzXpPU4nkGkUcMrEL4vpNRgILC17bKTvxYIC/z5NUv9I7hw/x8V281sXMiUStLvx7av/1pLfmrxPLbNgl81/MhhkZ/K3I/IwZM4b9zcgAQSwYjQOOJBn17IunkJRHM1rqMmpjsdN79tBHN95IqSp/a9GRXiAPE1xFpSjJ5F48S7vWXE9nU7dTiQSivPQRtHXFCMrMSqKo+KupZLnb6FRaHSpT9jLm/7J06VJDFzOQC5oHoNKMnb3SgjmUdMW8wZd3DuZz9HjnOJGk/c3JeHK/5PUc9XyOlfUcPVkUkUimbNmy7LxB2ErgY3QGegLScUgBK/9etPXjeeUbT8eQjHr2xddwpb/iv9JYDBIquIBLvv6apvXrF1TTgJ3iloa8noJkss4upR1rb6UL5zFhcwmREUTFkyBKs5RyTi+l+Byik7sq0urT7ej8+ZbkcjUw5FyQNkIDAZfn4D4oXFfMKMl+J0HtncN38agl+vPOcSLJ6G1h9jSfw+eXeD3HiiYLO9JlWQbI/IMQEImgngMbZf634GNvBmbwzZo8eXKhvxkRJchH70YwWgRbZK3Kyb4iGaWxGNJjeDC/uuUW2jRvHjkJanFLI0nm5P5BtG/be5SX5z8qiY3BcZjowmRKjphMGxe9TK6oelTuijuoZv1eFJ+g3++b65uhtoOFVDlnopbshzqwekfv5KlnrfC2i1d65yj1sZw4PR/sYq00IuP1HE46ynoOv3eMquc42bCsX79+1L17d2revDkbP0ALM6Ik3m2GjjXUD9E2DTzzzDM0YsQI6tOnD6sDYbPz0Ucf0QsvvKD7d0c7SdjSE8l4MhY7tnUrDevYkdJOY1zR2eKWRoDJ56zvSCePLg74NYolojq0gc6d3EDr5w+kjHOlKb5Ya6pSoztVvqqrz/cPiwr68fE+cX0z1HvUKTi1FhQeMLRvKnf02M0aUSx3Cnx55+B68ucIqWaneOcYSYzKeg5vslBHgiAlZSQYaErWrprM5TrblT3h/vvvZ+npAQMGsJQXnsNZs2a5mwFAzkoChczS7NmzqW/fvtSoUSN2bUE46C7TiwiXTZVD7v2i52ZbsWIFS7Hwi44HCykWdE80bNiQLV7Lx46l7/v0CbptVxRxSyOAS/z5Lya9ONp1z0VRjqsaJZfvTDXqP0MlSl1V6H1GhIl/YZLGQ3+0RCPtg6hGyz2gLJbj4MVyTjpGpUjQVYOFHPln0YFHFwPKWGD5wDL3zrGzQO4Pa9euZalBb/UAI6Gs5+C+wcYFNQ4e5eip56Behk0PpuWtwiOPPMJaiQNZ3EWBbVvBQLzjcTPw5gC1sRifhl07aRIl5eWxaAAH9t9OFrc0AmZvIxLicymBdlJu+nDaumw4ZWQnUXR8EypV/nY6lVabkkuXYw0EyshDLyGoi+XqORSlxTCIJ1D1ZNGjAPW54jnC5go7UqV3Di+QKw3JsKCKUOOysrbhq57D9ei01nPsimSSHGxYBjgq34CFBiSDBwhFKE/eJTEJCczvPrbgcBUs5Jxw8hwmbuk0YO0owRoIltCFU0so7gLRqTNX0Joz7eiquk9RuQrXGDIno5xD4ZL02GWi7oNisOjqyUZBWfj35Z2DiB/PjlLgMxDpeaPP2WoEU8+xoyaT6XDrZceRDN5shKx4WNAtwR8mJeJUb0hEwR+JI76AZESIcrSKWzodyNbExh4iOv897V3/PW3KiiWKqkeumDZUuuI9hkvSc4kXLrEOwlEbk9m1uJoFb3+LWsASCxZfUJEWxKZNmVqzyjtHFBVmX/Uc1C+U9RxcH9xHTmxhDluS0fuQI6+KNx4PAtrrvOWaY/28IXZHOXrFLY0C+iVE2MwXS0Tctp5yLq6nJbO+o7p10Utnrnqy0pgMi6uyboHDm1gjdq7zR42iZnfdRaUrViQRoTUaVNpSc+8ctX99oLUKvRC1I85TZ5/Suhv1HNwrIEgrImRXwb0r02UmQ2kshjcfOVNfxUx1JOMLvqKciyZEGYGIWxqFnPNEUYJ0AKdnEC1eSZSRdelKnDk6ivZs+YjSs8pRyXKdWGqteInABPl8GZN5q1vwBgK+aKcdPUpDr7+eDfD++cYbFFGiBFVs2pRa3X8/tb7vPmFUhANNPfH2cRxIOatnT7g3jBneOU6R+lenH3GvgCBxD6nrOUbZLZvVwmwnhCYZpbFYixYtWCSD6WhfiCtRIuDf5y3KwZFrk7ilUbhwniheAJI5coxo6WqinBwsdC624Bzd0Z2OH/yVXf+SiWeJMnfSzpSRrIEgMrYJVahyL11Z62GKiooxfOFQtgTjXkMqNm37dhr/5ptu+we2tKal0eGFC+nnhQtp+rPPUsIVV1Ctdu3of08+SdWbNiW7YFR9Q12rwA6akw73zlFGf8Gk1kRJlwUCLPiIcrzVc5RpWSPmczJluixw+Lv4amMx7Bzxhvqb3I8PwuPEW5RDQUY5FxITaX9WMOpjweO8AG7SW7YTbdhy6eOYmFzau64ZpZ/d5bOBIOPIElq7/0XKvnA5JZZsR1fWfpLKXtbckHNSz+b88t57tHjIEJ9pqCjorh08SJu++44dubGxVKZuXbq6a1e6sUcPKl7QyWQVjE49KaM/tXcOn0nD15RaYnrSRqKmy/xB2V3mr54DQUmelk0uuE5628l5HU2SjMFQGotBdwwpDmX3jD+SSQgikjEjysHsy0mbCYany2z73ReJVq4lOoBiVAHKlCa66YY8jwTjCbExrnwFgouT6dDmyfTfqlhyRdalMhVvp6vq9KC4+OAFPKc98wytmDxZ989FwXBqwwZauGEDzf/gA4pKTqYq11xDbR56iK65/XZTF1Qrxtw8eefwHTy6PPW0AfNzdmIk46u7zFc950CANS9kbbAeSpIxEGpjMXUuUgvJxAfg3GZGlINjp031F2/pMjuQnkm0ZCXRGcUgUN0aRE0aBje/k99AsIEunN5Amxa/R5nZpSmuWCuqdFV3qlj1Zl0Le8758zS8fXva/++/FCywBLkg5Dh7Nju+i4ykpCpVqG6HDnRjr15UqU4dcno7sLKxAlCm1njaSNm1pvbOCYVIxh88tZOfKRgmVtZzlP45agJDFANIkgkQ6ptMbSzmSTJEC8kkemhrNhvqKAfL3yoSC3ZEMqi/LFtNdEHRK962NVHFy4wdEI2OIipZDE3hM+nk7pl0YEsUXcirRiXL3UxX1e3ls4Hg9N69NLRtW0pPNaffLyovj87t3UvrvvmG1n7zDbkSEqh8gwbU7M476X+PP07xQXYOiSCQqUwb8ZklLKYQquW21ModfChGMnqdL7MV/jmIdHBNlOlHXE8U/fH7jDC4GzlyJJPph6QMFAuGDx/ONMw8YcKECW5NM2Va2V89XNhIxpOxmDeISjKeohwKc5LZuoNow+ZLtStsAG+7iSjeglEMrkBAmSNoZ8oIrw0E/82dS9/cfz9L/1h1b0RkZ9PJVato9qpV9Ncbb1B0uXJ0VZs2dP2jj1KjDh10E4YIJONtZol75/Aoh3vnAJh3g1KBGR1ZZsHIif8ElakdiBnXiddz3n77bXYNQU7YgAejXzZt2jQmkAnL5ZYtWzJxzE6dOrENACc9NZD2w9c5grnHbF0P1cZi/vrBlbIy3pBgM8kA4jzyl2DROkp4e1auI9p/6NLnSpci6tSObEGRBoJ9L1J2TkXa93c5Wjtxva3DsFha87Co/PYbO3KjoqhE9epUv1Mn6tCzJ5XX6KkuEsmogYyE0pYau/OUlBT3sw+od/CiwqyJ/whFPQfajFjjXnnlFSa1j/+j+QIbcNglQx0ZIsB6MGTIEOrZs6c7OgHZzJgxg1k6v/76617PyShtOdtIBjnJZcuWuY3FtOwQ/PnJAEkF2lZ2QsRH3oqaTEZm/vyLsv5SqzpR80bm66dpRUyMi5Z/foh2r1SwoCCIys2lzO3bKWX7dlo5fDhRUhJdfvXVdM1999H1Dz5IMR7ahp3mjMlbn7FoYsH25IDpzTvHblilXRYdHU233XYbq8UgmoAw8MKFC2nOnDnuOo1WoBa0Zs0a6t+/v/tzuO4grOXLl3v9OWwGQHj4m6E7CJl/vGcB/T1kEyBoiZwg2FsrNHWXWVD4dyJyTBZIO3qcaOmqwvWX61sSVbpcHIK5mE0042Wi0+Lxi+eNSmYmHV26lH5fupQm9etHX2IgWRWpi5Yu8we1OaGyI0uptI0BbD4oy0kH32dnas1q7bLMAnFMiMLec8897NALKNTjvLmkPwc+xtCtJ2DTjygHEv/okBs8eDDLNOH9QFTlqHQZco56dmIgGdykvh4sJz1woUIynuovXTsg70zC4OxBopmvEp2zv5tcN+CQeszH5sqpJONPaVs9KKs0seOpNSv/dqtVmDNtUmCGtQAODhAMrC++/vprev/993W/nog1aq/gbzCY2ZdhVQRsBBzmJ2M2Ll4wp/6Sso5onyIyKFWCqHN7Egr7lxEtHEyU67BbQq1zl33uHBVXbbCcFsnwzjIt5+zJxM7TsKMV3jl8c2tlJJNR4H0TDEDYWDeRjlQCH2utueA6wwsK1zwQOJJkEFaLTDIiPvIXc0yov6QQnYFeTgGqX0nUsok46TFg/XdE634kxwFxy74Ct1SOTZs3U+yuXYXkXZxWkwl0RgY/g9QZDtQKlGZkSg06fl2QJTGSEHgE5rRIJjY2lo2EzJs3j+644w7334KPe/furek1cK0RSXbp0sV5JKPXUwQ3DQ5vdRm8FlR2XQLs7KJNsFEWJV3mqf7SpjlR1UriEAzOY967RAfyG5gchfMFBKPu1bihXTu28GA3jxZgyLsAGIBEjh0Lq+i+OUZFA55sqXmrNAgHG1GlL0yw9g6cZKyMZLKysgwZxET7cvfu3al58+asDo4WZtxHvNvs0UcfZa3UgwYNYh+/9957bBi+Ro0ajMgxXwMif/LJJ0M/kvFV/EcXBbTOcPGiY2Ism31wCskYlS7btpNo/aZL9ZfICKJbOxIlCdR5eiGd6M9+RGdPkOOQWUAwuV7SFmp5l8WLF7ttyPnCynfzVtcstMCsaX+k1tTeOUp7B6V3TiA6YlhzuBOplemyJANqMvfffz9LMQ4YMIANY1599dU0a9YsdzMANinKvwtkjZZnfC/uJ0RC6ASuV69e+JIMLgp67rGTQ5FqYWws5disFybafhL6YUHXX9YT7YOUdAFKFCfq0h4RKQmD0zuJ/nrTPhmdYHCmQKlbazDI23sxN4FFli+sEJfF4COvWWC3L0o7sBUKzErvnCpVqrh1xPh0PdcRU6bW/EWAdrliJicHr8kHIDXmLT2G9mglhg4dyg6jYHu6TC+UA5lKr5latWqxGwqvGW1iAdCp7J0bRGCXkZWvP5aqqL9Uq0zUurk46TFg1zyiJSOI8gQ6J10dZDp/hqeaeTuwemH11g4M0rFr0t4OSRmljpjaOwcpRy3eOXbYE2RlZTGBYKdDtLVQcySDGwXFKISU8JpBCsH9PRbZyDopkgm08H/0REH9RZFua92UqFoVsQhm1RiiTTPJcUCm/1BBFKMXPu0IPNQseJQDuX6lVhb3PrECIohjevLO4ak1b945WHPssF5OFFgBIaRJBlPCGCTCcBb3mlHC02S01QgFklHXX7A23NKBqHiS8a6hgSIvl2jOm0SHPc+VCQ3E49As1jfD7TmS0dsOzCftkXfHpD1Ihi+q2LD56t4MBqKJY6qdU7ktNSIdpXcOrg/O3UqyyQwBLxnHkQzeZEQwKORhKhWtjB6HugSYAhSNZHJ11GSQjVy1nmivov4CYulyY74WmCjISiWa0Y8owxwBZVOBktHeAsXuYKE3MvA0ac/TRzt27GBquzx9hEjISOtl0V0xlbbUSu+cw4cPs7Xnn3/+0eWdEwwkyRgAXZ4fOTksPQYVV+w48HB4Q4wkmSLwoyvqRmZWvv6Ysv6C1uRrW4iVHju+hejvd6wT/rSqg8wXzhwdRVs2TKBiyR3pqjq9KD4xX7E82EVOLWKpTB+hdVWZPgLpBDP0KEK6LBDvHJw3yBgdVupro0w7Qi5LtBZmu+GISAYFzPXr17NdA/Ko/rpkYgTIY0Y6MJI5VlB/Oa/YXl9zNVGNamIRzH8ziJZ/I9Y5mdVB5kYE0b4tr1FSDJErYyvtSPmS0rOKU3b2lbR3+1NUrXY3t4WBUf4w3HqZOzzy2RxlZxZSa3oiE9HSZVqB6wAyVl8bT945RqQdXSFivSw8yeBCY7eAEB6DQYhecJP7E8mMtUHvR/QL649k/ttFtA71F8Xqd8uN+W3KIi3my4YR/beAHIljBV1kRgDrdMli6VSy2L+UebQ3rdn/PJ3LuYKSkv9H1er0otJlGxuePlJ2ZqGBIJDZHKdFMr5amH155/C0Y4kSJQql1vQQrCQZA+DrZkN6bNOmTWwXhUlV3i+uxVMmToA3JtIxJBNBy9e4aO+BS59BIAiBS5E2nBgmnfUa0Yk9FFYdZBz+luW4WBfFxR4kuvAtHdj4LW3NiiNXVH0qW/EOqlbncYqLK0lmdGZ5ms1BSs2bVL9TIxktBX912pG7X54+fZrN5wB6OvokyZgIEAvSY+jqQPeYMgeMNxLtmL4QV7w42Q3RHiNXXn53mDIqwccr18XR3gOXbFUhzX9DK7Gil4xjRDNeIsrKIMfhYkH9xerR4GKJeEbW0vlTa2nTogGUea4sxRVvTZWrd6fLK3c0JJoIZDZH9MK/NwRy3p7cL08rvHNQv1Gm1pSEzAnciIl/PdbLSkydOpW6detGt99+O/3666+hQTK4sJA4wBuA0BwhqPph0OIpE6fDoyZcCv8RBQSCegusuiFwOWM+BC4vEUyzRkS1q4tFMIfXEc37UHvjQqh2kAWjuoqyQMliJ4lcf9CJnX/Qvk1RlOOqQcnlbqar6j5FScX1e4Romc1Buojv5FHPAbBhxEYRXzOySC66zH+ED+8cbkvNCRkFf95qjs8Fg0CslwHMC7388st0/fXXU8iky3DRkR5DThNaObjYnqCFZOIFIBkR02W43PFx+cfpM4UVlG9uR5RcSiyC2fQj0ervxJnJsaKDzBuMrGIkxuOs/qO8jP9o+8phlJFdnKLimtLlVe+nKjXuN6yBACQC51scfCcPuXgsonBlVBbJkUYSWdzT6PmYaJV3jpKQoRsG4gG+//57uvXWW1lNOpDoMxDrZfytDz30EA0cOJBp44EMHb8WpqWlMQE21GGQHvNGMFprMgkljck/O/7CKqDmZfXz0qAOUfmyRMWLEcXYHN+C6BZ9TLTKoQSDsZ09BhIMg0m1cmSASiSlU1L0Iko79CytmVOW/vmjHq1Z0ptOnzROwlq5k8cOGjtkZCtAPshcYP5k3bp1rNEHZCSahYHZhmXxBYTcoEEDWrJkCUtxIT33559/ss8hqwNyCMR6GVbLeqyXocKM96hHjx5kBKJFSI8hdMPgEw5/bI0dgF8LZoNE5UKZZNTpZWWUQyXz01PZ5/NTa+fOWxvhnNxMdHQFESpx2E7khWkHmR241EAwiQ5snFSogeCqOk9QbFxwWQLeXeZrNgepGqXeWCCqyUbDSoHMqKgoqlOnDqt1zZ07l6XSEFFAn9Fs62UQ3Lhx41hN3CjYSjIo4OOGatq0qTuP6w9a0mWSZDREMqoTVJMI8vjFowskZFx4r/JJJ/ucBfWRCCIkbHjSBqd+UXGICBAhqg6KDKShsKvrV9lA8G9BA0FS2UepWZt3A95YeooIvM3mqFWTsU4YbUgmovVyhsIVE9cFdRSzgQjykUceobFjx7rTeI4nGeRkETbryTU6hWREmwSAxpcSep5RFuXE5x/JPMopiHDMiHLU5xZVcCDIcqkIJy+MO8isBjYeZ86cpBXrpgdMMlrmZDzN5vAoBx1reP7RjcVJB+uI2bM3Vkv9ZxrQWabXehl1IGz6u3btWsSsDZEnMk54PxzXXYY3Tk/+VQvJJBnIwqESyfgjGT1EwaKcYvkHfo6Rzbn8SMeIKCfCx4YRS4kyysEjkGNjlGNoB5kPiDC/iIHdtf8SJZcJ/O4OZE4GqTJPhmRIB2FhxNeVDQRm+OZYHclkZWUF7eap13oZKTpIdynx1ltvsQhn2LBhAdsO2E4yesEL/7jZvL0BSQV5XjshwJpQCLl5xpGMEngLEuLzD8SPPMrBgXbpQF43QsddGVkQ4dgR5WQUqCgbWuAXEHgPN2wm2roz/+PIyMCXjWDnZLTM5iin7PF/I6IcqyOZDINcMfVYL6P5AE0GSnALFfXnQ5pkuBaQr53F6fR0shsiDmP6JBmDfo+nKIel1lDL0bgaB3ouVkY5qQVT/Fb1Q9gVyWBzkrK2sCJ3sCRjZGrL12wOn7JXNhAEOptjdSSTadAgpl7rZTNgO8nghtObLvPWt44bAXlD+EDYjYgQTpcFEuVwC+hzPMpBLcfDz4CUUgzqnFVHObkK0gk0ysHrIMN9gkL/hoLC9ZKUfOM6JaIiA19szZaVUc/mYDzCk4AlSAm7dK3EYUckU8wgSRk91stqTJgwwfkkoxf8jVbXZdDmh7Y73FiYtZmPWk9B0coOCEcy6khGdYJWtChj/iamIMrJ4x1ryignIpZmL7xAWen5xGAkIgpu9uggohyzO8hEup/wvixaXtjygSMyiGFNKwUy8XuUApaYw0NqDTprIBx0tyobCHzVQOyqyYQCHEcyuAnUxX+Egxs3bmQhYN26ddnXIyTJ+CSRIpGMxZcqUhXlXMghGjUphxGOFRdPb5RjdweZlemy9AyiBcvyvYU8ITLKvppMMEBDAJ/NwWZUKWDpbzbHju6yYiEgjikEyQSyq+EkgxsFMhW4QWAmhAIWR2R0NOXZKHglHMmoVk71ZUdkYSdiYxDRFJyExeoinqKciwWkcz4iknJceayDzFZ/NItuqFOp+RGM0lNIjajIwCMZUVSYse74m83hWmLoWLNjTqasAF2yIUEygQBvNnYhkKPAv61atSoiJAeSkfBOInaky/wBaw8LPm1maCyBsQVHvCuPNtpNMBZFMoePEi1ZVXRwV41gtM1E9ZPxNZsDwgEwJY+Fn8v0m/l3ZGVlBS2OKQocuRLjzUWrIt5s1F88uc9FmdArrwfCPUYqEolQbSZtzCwWUiFg52H/RtcNYSQbTb6hdu8jSlmvbbMRFe38SEbPbA4IB3IrqN8gNQ9Dsri4OHctB8QUqAOmL5JBlBUKsJ1k9OwGuNYZ3gB0jzRs2NDrz0fZrHUkGtSLR4SAkQxIhkUM4q9BlsPMzf+m/4j+3ar9+zMysthziAXWnxOmUyIZX+Ddr1WrVmUy/Xw2hxu1IZti9GxOhoHdZRTuJKMVSisA/ob6eiOjJcnoIhm7azKFJv2dtQZZAjMuCd7zNRuJdup0G42PT2LP4e7du1kxXbmj9zdt70TTMl705+uNFbM5mbLwby0ga4D2ZLxZSI8hVeZP7j/aQYZIIixaYqTLcFYugXJU4kCd3gwWaBlfvobo4GH9P1u8eAnmsIjFF8Vy7OiV0/bcfhk1BfVG0CnpMiX8dZb5m81JTEws5ICppYFAtjBbiMOHD7ObF2EqN+7Rol8W48c/22zg0SpYMoVEkUhGAJJxP8ewiZYBTSEYmWG6cIHon5VEJ04F9vORUflZAmXLL9/Rg3CwwMIXBgszj3J4S7AT02V6oi9PszmpqansmoBwUN/B1/g18TSbw/XZZOHfIHi74UAi6ObgUgjcdwJwAsnwi2t3V5I6ZcYvt4jpMrX9gMQlGLUuY/Zl4XKitCCUl6KjY73u6LmnPRZm7OhBOsqWYDy3XDLFKRFNMK6YMTExzAAMB5/N4USM6M/bbI5R6TKYn3322WdsHUX0OXz4cKZh5gk///wzffTRR2wsBORYs2ZNeumll5j8v6NJxluoiPQYCAjpMbQL6jUuixGgMyNKMJI5l02UkOiFZARQeXTImmMPDCCZM2lEC5flT/MHg6iCSMYXQCBIDeFQtgSDbDB6gAM1HB7pBKopZgWMmpGJUMzmQNFYOZuDRgpcm7/++ouVAvB5dLAFg2nTpjGBTFgut2zZkoljwpcGERVITw28F2+++SZTYwbZwZUTQpr43mD8bIQjmePHjzO56csvv5z9sZ52O3jDIQnhC3ECFM1Eu7hKkvGn0mwHJMmYF8kcP5mfIoMeWbCIidG/+GHRgiIHFtIWLVqwnTIWV+ywQTi8bsFNyawcfPQHs5oVIj3M5sDr5ZdffmH/h9dW+/bt2QIPjxeoTuvBkCFDqGfPnm7FZZANLJzHjx9Pr7/+epHvb9euXaGP+/TpQxMnTmTt244mGZ4uQyiJ/nPkcuvXr8+KaP7k/n0hVoCimTiPST4unHNITUbCUJLZfyi/yG/UexwVFRdUKzCeX2Qn0CSAWiuvWyCNtHXrVvaxMsqxwpTMF6ySlImNjaVu3brRLbfcwlQIEEmkpKQw0sE1e/rppzW/FkhqzZo11L9/f/fn8Dd06NCBli9frum9mj9/Pot6PvnkEwoGtpMMgKhkw4YN7N/WrVv7zUVqqcnECVA0E+LiqiIZb5AkIzYCXWO3785vUzYS0TGBjQdwl0U1YajrFkpTMtQHkDbihXIzBh9FlPkHkOJCdPHqq6+SXuDaYY3kkv4c+Bi1bm9Amg41NazF+Ju/+uor6tixIzl6HUQhbNmyZewGatq0qaYbSAvJxJcsSXZD5EhGxHRZVJTI/XjOI5kNW4i2bDf+XKKjg4tkfEUFnkzJeHcWCAcdbMruLHxfqFkvZ2Vlsagm2JpMIEBzBurhGAaFgyZqOldddVWRVJqjSAahMNJj6B7TerNoKfzHlShBdsNJJCNCJBMRIQnGiDkZvJeQiNkD204TEBUgyfBIRs+CjQ0l9MK4WKSyO0upnMxJxwzr5WC6ywIBFni9Sgpq4HrhnFHjUQIfQyrHG/DeYFQEQFcv0pdwzXQ0yeBCeup0CDaSSSiwDbUTopGMsldCxJqMbGH2DrWgqTfAGG5pCtGR4+adS6CRjLd0md5NKeoVSuVkkA5quUrrZZCOUdbLVqsUZBhgvYxIqFmzZiwaueOOO9x/Bz72ZmDmCfgZf01WwpNMoO6Y/gr/IpCMaGvmeVUkg8wkv4xarZEtmfiXKAoNayVcRSHTf/qMuacSExNYu7HR0/7K7iwAiyEiHJDOwYP5ftHKKCfQ9JMdNZliBqQBkerq3r07NW/enM3GoIUZr827zR599FFWf0GkAuBffC863XAtZ86cSd9++y2NGjXK+SSjF/4iGdzMZ4Nk31CMZC6cL+pUyUlGjDkZBcFIvtGVLkvPzJ+BycivGQtJMmZP+4NEMPqAg8u7gHBgx460DxZuZZu0VsLDWmNGGs5sBeb777+fqUYPGDDAPdQ+a9YsdzMAZnOU1wAE9OyzzzKCRsSIEZLvvvuOvU4wCDmSQYSDOZvUbB+tVOFKMueKkgy/SiJEMg5TGxEmXabFaMxIRAsSyWiVd0Hhms/lgHSQVsP6oW6T9gY7DMuKGTTnh9SYt/TYwoULC338wQcfsMNoODJdhsI/3nj8jHJnhDdn3bp1bHq4Vbt2tILshWjpMmhWKaG0BRGju8zuM3BeJHPkGNGSFGs3CYGSjN3Wy9jB48C6gbUCpIPhb8zngWS4tAvIR0kqdlgvJwkw5xdSJKMX/AbAm89bnhEOIoKB5wM0dy5k2eXGLi7J5KjSZdGKRV2MdJndZyAuPF0bdI+tXGe9F1BMtJjpMq3AOaBVFwfWC2Q/eJs01AeUIpY4rO4uywwhmf+QIBnsMLATgQhfo0aN3PnGOAF2AlGCRzJIl5FA6TJZhPGO2BiisuWiaN++XLqQkx/BYA7GDohS+DcK2KhihAKHWsQSnjn4HAgS0ZAWz5xgkSkjGeOhd3fDDYRQIAPBYOcBpQDR3hjhIxnFu+/P190KFFp/ZOG/ECKjiBJjc6luzfyPl62271yiYwJTOHeCYZlaxBIb2VWrVrGNrVbPnGCRKUlGDOBmRf3Fl1JARGQkuWwcABHtcVKLI4pGMnJOxjuK2GXbWEPbvPk/ysyO12XCJVK6TA/wt+Gc0eqLAUctnjlGkMxlKjkYJ8NxJIPQFakx7DAwkIU2O283bkRUlK0kE+GAFmYOP2NHlkCSjPbCv9V1GCWq16hFF3Ly/Z64mCWvX/jq0hI1XeYPyu4yLZ45ymHQyAD+XlmTMQFadzcgFoSreFPxZvuToomMiqI8I7TNA4Roj9NFdSQTJVZNptBCKhpD2wz1WmWnyVyFCpUpMSm5kJgl5jGUXVpYZNVRjhMjGV/dZd48c7A+oQkJ1ye5gIBxTbR65oSS9bIwJKP1wiM9hrQY6i9r1671Ky0TFR1Ndm7QRXucctQtzIIV/h24ybXt2tgZycTEJnoUs+RdWlhk1VEOFlkn1GSCmZNBqgy6YDhAMOnp6Yx0jhw5wiTztXrmGDknIwIcQTLoZd+4cSMLUWvXrs1uVC3SMpEWTul6/P0keCQjGsmIxsoCQaRIxpv9srpLCxtDEA6PcvB1PLf4nJ5ajt0IZE4GBIx0WYkAPHNw3ZB2s9J6eezYsTRp0iTatGkT+xi6Z7Bi9vb9jiMZbyE0blTIe0NttUGDBkwuQo9IZrQNUtlKiLZmqjOHymc896KA3WUS3msyNhb+taS88D1I+eDgUQ5mUM6cOeMxyjFCRsUMYA3CESwhxmjwzIGcC9Y0iH4Gez30Wi9j+h+GabC7R1oPRmU33XQTK09gc+94kvEE5DcRvYDVW7VqVYTZtcj9RxnQ6REMIgSPZJTPDdR77YYDMylhmS4LBHheQThYYOvVq1ckysHCxpsHRIpy+BpjZJovwotnDhwrv/nmG6a19u677zJCADFg/k9vLUuv9fL3339f6GOcx08//cRUmyGkGQyEfKzB5LjgeGNRf/EUOmqJZGI0FtrClWSiRYtkIgS+eDbD6SSjLPzzKAcLbJMmTZiXPTxMQEBYWBcvXsycctGxBTKy+5wBM0kvqsAz56WXXmIdaiBZRBFLly6la6+9lkUkesCtl2G1HIj1MoDrjmgTUWawEC6SQciInCW6NapVq+aVwTWly3y0U1oB0dZJdQlL+dwIUZMRcssjBiKiBKnJBNEd5q3w762Ww1NJdkY5fI2xsivu/PnzTKIfER8IA23SVlgvK/Haa69RxYoVCxGVo0kGbyBuQLA4nNuwu+FOeN6gKZKxOc8rGsnk+ohkREiXObC7NewimYgg7motczKeajlcVwxRDhZdEA0nHbNrObyzzCqSyc3NZbI2vIUZHWv+1kKj8fHHH9PUqVNZnUZr27XwJIMp2pUrV7L/o/Dka6CLA2+8P8e2WEGLiSJGMkKQjCz8i08yQUYyen/e7ijHagXmjIwM9m8w3WWBWi8DgwcPZiQzd+5cVgsyAkKQDL+R4Pug9Q3VUviPtXmgSbR1Un25lBP2IpCMbGH2DuVjYatVtj/3NB8ItkvLU5SDbjWQjllRjtWzPZmZ+a5zwczJBGq9/Omnn9KHH35Is2fPZg6ZRkEIkkF7Hwp/eqAlXRYXQgNNRiDXV03GPmEEN2Th3zuU65ydRf9g0mVGT/xjo4ldOw5fUY4njxitsFrmPysri7Uze9JiNNN6GS3LcNCcPHkym+vBbA3Au+AcTzKBGJdpIhkDBprChWREiGSC2CSHhQqzCIOYEUG8SWZGBeooh7cFg3S4R4wyylEOP/o7Z6tdMZOSkoImY73Wy6NGjWLX6J577in0Ou+88w5rpw4JktELfySDOs/J9HRLz0l0+EqXAeB4O4vvchhTG8nYGskEmS6zKvXE24KVUQ7XFePDj5xwfEU5dtRkkgxK8+uxXsbAu1lwNMl4k5XBDgY6Z0kG9HgHA6yTuD0FcDb26H4pWsuw7C5zQLosiJvGLoFMZZTDPWK0RjlW12SysrJYesqJQqJhEclwGwAUAaFxlli7Nm0g+y+wSpdSnEhGjKFqN2RNRmMkY+OuJdIhkUygUc6uXbtY4ZwTDjayVlsvJ4ZYV6xjazLq7jL8H3M2KPqh2IUQ+ExyMtkNkdZx0SMZUdNlIgzXK1ObttZklGynEyJK/fuLcjAmgcYkbF65xpqZf0NGiCkwC0UygUYyICbUX5Ae4zI0fIAoweZ0mWgXWN36WmT2wua1Xfns2n0uokGUmgx+N99t611snSD1r45yQDSQ7PcU5QTasRZO1suirYG6gDcXNwHefOgcYciobt26hW5iu2sywkUyeX6cKG1e2QutWZJhvM/J2BpaRTDP+0AWW1HSZVoBEsXfhcFIpN95lIPUGkQ9EeXAF0Y5lxNslJMVYoZlQpGM3jeH36wwLwO5INRVI8liOQbHRzI254VkTcY7CmWpbHyfYmPjmKClunCuxYJZxHSZnhZmZZQD8LkcHLt37zYkysmQ6TIxwOsvAMx41EJwHAllypDdEDmSEW1TKedkvEO5XtkbyUSyiAT1ib0xxannjiyqeCGXbonMoTY5x9wWzEqpF74hdFokw9cab4ORiFxwKGs5PMpBCl+tPhChgWBlukwAKG2YccP6ekNibVZhFo1kXIJHMjJdJn53WU7ORSYjvz2+NL1w4Dzl5kbSgagStDKVKOLYeaqSF0ltS7ro9phMppWFxRe7euz+rZ45MQJahzGNinKysrKY+nEoQZh3XAvLo3MMfgh4k1q0aKFJv8zu4QuhSSZCLJKR6TLxu8sSk4rRtuRK1Hv/uaIjBLFxtC++FE06n0h373fR/QdcNDg1kpanXaDDhw+z3T2k5lFAh+YY92oRGYESI49wrr76apZeRE0HaxyinH/++YdtlDF1j8hF2VVrVCQD62XIw6AJCs6YKSkpXr8X7pd33303+36cIyRowi6SwZuwZ88ednPCY4HbgfoayFQOj7n8EVE4sLgHEili6Uv2wmHp+rAcxtxRojF9sO00ufyFU5GRlJ5YghYR0aJTRJHns6lidg7dVC6G7oxNZ6TD0258h4/dvmgwQlYmKirK/Tcqoxyk1niUg1oMPgfyDbYmo9d6GecDceJ7772X+vbtS0ZDeJIBiWzatIldfAi9oZtDj34ZdiF+o51wiWRcgkcygs7JiIDIaPvfp4PJzejPKr39E4wH5MUl0MG4BBqfQzR+fy6VOueia5Ii6faYC1Q76wAzKixRooR7MUZHlwhNAmak+BJVtRysbb/99ht99tlnjHxx4POdO3dmTU1mWy8jK4QD8PT1kNloe7qQCB1XrFjBulfgM6MkGK0kExGkmmlYRTI2Zy8K3QH2ry/iFv5teJ92l72eZjT+hPIiY4J/scgoOpNYkv52FafnjkfRzXty6Y1T0fTb2Vw6knqGpZJgPYzmnuPHjzMbYLtgtkBmVEGU88QTTzCiBalgMw1Zfsj1P/zww5ZbL4dNJAMFUcy/VKpUiWrVquXVttUfyURFR5OdAsORDopk7O1akt1lmgv/Fv/u/yp0ogV1X6c8ZThlIC7GJxJ6RbdkEA07e5HKXYigVsUi6M6Y81Q5fQ+rGSjnUYxQKdYKq5sVcnNzWX2ka9euzCET66DV1sshTzLI0yJPiaN+/fo+Oy20RDJRMQbsvEIkXaZGbl4cHMWFSZfJ7jKNNRkLI5l/K91Fi2v1sW4HEBVNJxJK0h+5RH8cJYrNvkj1Y6KoE+VSB0pltVnIvCg7tYL1XhFF6t/lcrHsDXfFRCs4bAucDmFIBjsT1F82btzIZBxQsEKO1hc0kYzNxUSRN+dZWYXtqyXJiIuoaOsjztVXPkop1XuSnbiQUIzWEdG6NKKPT12gihcj6doSEXRn7DlKTd3JOtaUg6BGi0taHclkBtldFoz1csiTDDockDNEyx30x7R0mmjpLouOw27dPohGMkrPGPWzY3dHqSQZbS3MVmwGltV4ltZX7UZCISaWDsfE0vQcoumHXJRwLpcaxUVTl6iLdH3uiUJumHwQNNgoxGrTsqwCqX+rrZfDgmRwcdBtUbVqVc35Vi2RTLTNA5mikcz580QF+qHCDWPKORmN3WUmbgZcFEEL67xCW6/oSkIjIoKyE4rTSiJaufY/WnRnG7q+cSO33A3qD2gYULZIc+FcPekrKyOZnJwcpocWbAuzXutlNAtwBRX8/9ChQ7R+/Xp2HjVq1AgdkkFeFcNAen8Gb4ovxOi8sUKeZLK9k4zthX9JMrbKyuRGRNHc+m/TrstuJMdg11ai/9ZT9B2t2Icgk3LlyrnrGyAc2A9DYw2pNE44aCTwRx58SNKqSCYjI4P9y2syVlkvo2W6SZMm7o8HDx7MjrZt2xZx0HQ0yQTSLaIlksmz2ZlLtLXy/LlL/5fpMmfWZMyIOC9GxtKshh/Q/rKtyTHYsYlox7/5/92ymc6fPM7qMziwUKNwzrMjiBK4MRnm7pSDoPgXdsxq8LXFqkgmKyuL/WvExL8e62Vs7vV4eTmWZAIxLvNFMshDImS+YHMOSMRIxpvUvySZ8Jz4vxCVyGZgjiRfTY7BfxuIduWneICb2rWltDNn2A4eBmPIcoBsQCD4Fx1piHCwm8cawz1ikBrCfApIiUc5aDjCWsRlb6wimczMTEaMVtaArIBQJKMX3gr/SKEhp4ivlb/iCjq9di3ZhQiBSabInIxAJOMS7cKFaCSTHVOK/rx6MJ0oUZscg63riPYUnvkoWbw4OxC5gBxAIJgZ2bt3L9tsIj3GSQeRAuoNOKpVq8bqEFzM8uDBg4xg8H08bWUVyWRkZFg6A2QVHE8y6kjm7NmzbGIYnSUofB1WqQRYDdFuF2UJSz36YDvJeP1AwoyaTEZcOfq9yRA6k6SvFmobwK5b1hDt2+Hz20AKiFpw8AgBEQ4nHaTGOOFgnUDUgwjn8ssvZwSVlpbmjnIATNDzKAfEZBYJZIagzL/j02XqiX8UsDAdXL16dbZDwevFBVlECxYRDkqX5dotihuJByxTzAsnEMkY0V12NuEK+r3JUEpPuJwcAawLm1YRHdhV5Ev+bhUs3DhQe0B2g0c5aHlGrQZEw0kH6Sqky/A5zJxgbg/zJfiZffv2uWVg8DWjB0EzC0hGRjICRjLcixu5WHRS8B0MECcjmUK4IHAkc/p0AcFImBrJnEq6iv5oMoSy4uw39dMEsOrGFKJDezx/2eWiu+76gh5//Aa69dYmPhdpHrUoazMgHBxQeUcHGq/j4OtYYxDhoOUXUQ7ELEE4+F7IvgRiTOYNMpIRuCaDcBZvOIY41W9Sgh/VgHAmGdFqMoUulmgdEyFSkzlaoh7NuPozOh9j73OhGbgpN6wgOrLP+/e4iGbP3sWOqKhxVLt2Gbrjjqb09NMdqEwZ7zMnIARELTggdY+oBmSD1BrqOFhbsMYgbQbSwZwNSAUkVLNmTY/GZIhwAh0EzQhB62XHkwwK/LgxcLO0atWKdZCoES8jGe8kI1i6LMSyBMKRDKT6Zzb6iC5GGyu9YhryconWLyM6etD39ymuB5w6t2xJpS1b5tFHH82lsmXjqG3bGvT00+2pTRvfzQ1YPxC1ID2GtDtanuG/glkTmI2hEUDZIo3aDiIcpf0yCAe+LWgmUMrdJGgYCgdpyUjGZOgJNaHFg3wpgEEibx0gCaVLG3Z+oYALijkZXpfh5GJ3JCMn/jXWZFyBSfXPafAO5UbZK7OkGai1rltCdPyw/+/1ej0i6OTJC/TTT1vYERvrooYNL6P77ruGevRoRwkJRa8FUmSYfkcDEabluUoANrS8eQCRDdYbZfMAohj8H5EMXoNHOcePH2cEBZJRyt14Wq9CNV3muKQE3kAU7EAw8F4AfNm4JiYnk50Qba28cKHwx8q6pd0kI+dkzBHIhFT/3w3fcxDBXCRa8482ggE0Xo8LFyJozZrj9Nprf1LZsv2oVq1X6dln/482bz5YiGBQd4H+l1KGBlELbEdQ823Xrh01bNiQfR3T8ytXrmQjE+hcQzSDNBu+hu9v2rQps19GOg6fx+svXryY/v33X9aopFQsAckYkS7TY70MTJ8+nerUqcO+H3/XzJkzKWQjGX/Am4Q3By2GSI+B9TG9i1DVW5dHooxkCiFHpcKj7DC7aJ+BKIMkGeO7yyyX6g8WF3OI1iwmOlVYRdgnAtocRdKhQ9k0ceJamjhxDSUmRlKdOsl0441X0iuv3OdT5wxRCI9Kateu7fZ9wQHSQdpNGeXExMSwCAepNxAZai+IiEAySK3h4wULFrCPQUZWWi8vW7aMunXrxnTMbr31Vpo8eTIT1ly7di01aNCAwipdhvATfzjCUqVKM37Gl7RMYtmyppyrU6GOZJRmWEiB24lCb79D1kSRazIiSPXrAhwwVy8kSj2p7+eCnhuKoKwsF61de5odn3++mqpVK0m33NKInnuuI1Wq5LsLj/u+4MBapGwGOH/+fKEWaXSg8ZZqPgi6evVqRk4gGjQLoBbUpUsXuvnmmxmRmWm9PGzYMPZ7XnnlFfbx+++/T3PmzKERI0awnw05kvEGsD5cMmFghp2DMp/pT78sSdHObAdE25DnqNNlUWJGMnLiP7gWZiGl+v3dmCkLic6e0v+zBqd58/IiadeudPryy6X05ZdLqGTJaGrTphr16NGWbr65sc/NMNYjRAw8asnKynJHOTBcQ4TECQcqBMjAICvz448/0iOPPMKaDjCCAbJAFLJq1Srd1sv9+/fXbL2MzyPyUQKRz6+//kpGQWiSwZuEPCdqMPXq1WOdHHo9ZaJtdsYEQIl2dwd7Ixllukyo7jJJMoUQFaMtknGMVL+65TFlAVFaamA/b6p8eASdPZtLf/21kx3R0XlUu3ZZuvNOtEjfSMnJvlukk1SDoHwmB3N92BwjykEjAVqiEf1A+bhv374sooAhm9nWy+ic8/T9+HxIkoxyh4CLhTZCXPgWLVqwNyNQJWa2etkolImLrFrbxSEZZUFZoEhGkoz+7jJHSvVDFhwEk34m8NewcHN08WIkbd58mjZvnksfffQ3LVnyCjVurE2WJzo6mkUqOLCBRm0ZxPDBBx/Q33//7bYnQC0Fh17/G1EhZOYbhTR0bCDURP3FG8F4kpbxhAgL7VNFZ3LUVUUt/MsWZu/w1wUIqf6/Gg1yFsGcyyJaMS84ggFsicDz6Isv7tFMMJ421EiXQQLr008/ZSky1EbQ5dW1a1eWboObpdnWy/i82VbNwpEMWgCRJ8QUrrJP3Ru0RDKRNktniyTcrY5klPzrLyA0G7LwH1jhH1L9f1z9ubO8YLIz8wkmMy3417L8vs2jYcPuph49/hf0K+3du5d1dcFoDAV6dHdhtubPP/+kxo0bB2y97D7TAutlbNY9AZ9XkxkK/96+3+mbbNafjk4LFPcxRatlONNfTYaTjJ3rp0gXOUd1qZT8azfJFIpeZCSjmWTW1HuaXInFKf5iGp2LdoBcTFYG0cr5+URjBCy9b/NoyJA76ckn2wf9SgcOHGBdZDhQ5OcNTVjTAl3k9Vov9+nTh9WBPv/8c7rlllto6tSpbA0eM2YMheL6x9JiyEUiitEKTZEMiv/ZCvnhMI5kiqTLlN1lvrnadMh0WWDdZWmlqtPRqv+jiLxcKn1mO8WnH6UMVxKlxRmX8jAMmen5BINUmVGwzDc8jwYPvpOeeqpD0K905MgRtqjfeOONbHjSKM8avdbLbdq0YdHTW2+9RW+88QZrQEBnmVEzMsKRDBes0wNNJGOgHLfTSSZXRTKRAtVkZOFfY3eZqgbhisi/w1yRUXS6dF0iHGjfzzxMJc7sopwcF52KqUiuyPzZMtuQkZZPMEq/CSNgyX2bR598chs980zwBHP06FEWvWCBR8RgtBOmHutl4N5772WHWRCOZPTCX+EfIandWSCRIxlR52RkTaYwlPsk9b7d5WWaPzOpIjuAmJxMSj69hSKz0+lMVHnr02oo7q9cUFQ8zwiYHoG76KOPulLv3p2CfqUTJ06wwj70FjEgGWpWy8KTTCDwFsmg4IXecISlCcWK0YXTp8kuiHQbqVNiInWXSRVmjSSjimTyCiIZX8iJSaLjl7Vg/+dptbj0o5TlSqSzcSYbl51NJUqZX7TrxCjkmpkuc9EHH3ShPn1uDvqVTp06xQgGNedvv/3WUMMzkSHcX6nXHRMkoxSZ45OvEKzDvyigbUy0V9o8SjDtQW+yMuqvWQ0ZyWi7NuoSBE+XaYW3tNrFC/lptbwoA9NqZ07lz8GoQ2gjYdrmyEXvvdeZ+vbtYkhT0+23305Vq1ZlxXVPtiShCuFIJthIBmJz0DiDmikUULFbiLGZZERaL3N9RDLqzjOrIWpNxr4xXs9Q78G0RDK+oE6rlT29lSKz0+hMZDk6FxOEH9PpE/laZGZ3lFw04x1y0TvvdKKXXrol6FdKS0ujO++8k82+QPGY6y6GC0KKZNBfDgsACNWhS4LXeGI0GAaZeo4kDtTPe6E5GYFIRmqXeUewkYz/tFrzghfOo9Kp2yk+4whl5ulMq0FFefU/1txUhv8KF731Vkd69dXgpXkyMjLo7rvvZpveX375JWSm+MMqXYZIBXMyUDyF7zZa7+Bup4SMZC5BXb4q1MIsUk1GpIsmGIp0l5mlaBERSadL1yHCAUXzrGOUFZOc336MTjFvOHEkX67fKp0iQ0nGRW+80YH697896FeCYsm9997L1qjffvtNkztmKEI4kgmElDBstG/fPjZ8BKkGNeJs9s0WOl2mIBmZLnMG4uLxpuWaEsn4QlZigZBiTCxRsZJEZ9KIUo/kdyXgc8DxQ0Rrl1jrgGdYusxFr7/ent588w5DpLEeeOABZg+PORUjzMicCkeTDFRKodCMdNm1117rNRSNK16c7EQ8IqksA4fPgoD62VcOQNpOMqIys2DIU4WjwdZkAt4RJJfMP5B5SD1BdHgf0Zol+lzVjIAh962LXn31f/T223cF/UpoRHr44YdZLebvv//WPfsXahDuUdY6KwMPbmicIQRFOOor12k3yaQJQjCAOoOhjGSuqGzclG8gkJGMNhQdxrT5McYbV7o8QizrCQYIunHNRX36XEvvvHN30KeCjlZIt2DgEhFMKR/ivuEC4UhGC2BTCt9qeDTUqlWLzcT4QrzNO4kIB8zJtGh1Jz329FyyE7Im4xnqfZeZhf+gYGWKTImcYNJlLurWrSa1b1+ObVp37NjB2o311IXdp5GTQz169GCilxCZhDGZhMPSZXjjcRNAfweaPJDHRnHNn6xMvIc6jZUQab10UUnadOARKpP0DxWP30rR0bnUuevL1P7mdyjPZkMZGclog7gkY9P9E3BNxkUvvHAdDRqUXzvBsCT8XTBjx6XzccAC2d9cC5qPnn76adq6dSuzUcbPSTiMZPAmwoIZRX7YlfJCGlqYQT6IZryJzMXbHLKKRDI5F3KoftOXqVy5T9jH5escosRi+Y6jkZFRbCbErvVdRjLaEMjEvyWwy1o1oHSZi3r3vpYRDAASURqKIR3PLZM3bdrE0l7Y1II84HSpBDa50AqD9TG0wdROk+GOaCfUZBCtYMAyLi6OTfArdxVc+wdvtDeSSUhOJjsRKdj1xcPCwQmGIyPvQbqYMZtKJJ0qVK+x5tyUH1j7u4WG6lqoMzlhH8noJhkXPfNMa/rkk25enxGQCg7M26FTDBEOSAeZFNSBsRZBsgoqyq+99hotXbqURTAVK+YPtUqIuf55BEJY5EoRssKQRx22cpLx5SmTKEnGDX+55moNxlLNVvupVI0dlEHP0um0ynTBREUQJWQk4xlqvi1CMjY7v9pOMrok0VzUq1dLGjz4Ic0/AVKBvxUURNq1a8eIB3N5zz77LJvJg0wM/m/mHMygQYOYDX3x4sWZcsAdd9xB//33n8+fGTt2LF1//fWUnJzMjg4dOrBattUQ5O70DNReEMGguF+3bl2PkQp2Hfi8r7pMYpkyZCdE2pRfWauWpu+LS6hIV9b7jGq12kbl6x+nczHv0qn0upR9zrxbRkYyXuCn8J8XzoV/MK7mX+uiJ5+8hoYOfSTgX4dOVizy99xzDz344IMs2nnyySdp2rRpjHDgEWMGFi1aRM899xytWLGCNRWghnTTTTex8oE3IHXXrVs3FmFhow6ixM8cOnSIKNzTZaivoIAGr2lEL/66NPzJ/dtNMqIweeOWLWnInDnuj9PTs+nFF7+l++5rSZ06ebd6jY5Ooko1XyGiV1hzwPGDkynt2ASKpbVULMk4ZV0ZyXhGhJ+1XJh0me3Wqr7goscfb07Dhj0a/Cu5XDRw4ED68ccfacmSJUxVGUD6zF90ESjQDq3EhAkTGNmhDnTDDTd4/Jnvv/++0MfffPMN/fTTT8xuGW3WYUsyGGSC/SeYGvUXLSGoP+MySTJEnR94gF4bN8798e7dx+naaz+itLRcmjr1X4qJcdHVV19Ojz12HT3yyHVefS7QHFChyiPsAE4fm0unDn1FkTnLqHix9MLuljohtcsCrcmEebrML1zUvXszGjHiseBfyeViqauJEyeyCIETDIBIRi1pZRbQmADoaZNGbRvrqtWt1YLcnZeAIhuKarBh1prj9Ecy0TbLakfavD71fOutQgSzdOl/1KzZe4xgOHJyImjVqqP03HM/UqlSL1CzZgPo00//oMxM3yZTpS/rQDWb/kzVWx6lpEoplHbxQUpNKxeQDlqhtVSSjBsRDin8l0i0QZvLb/eyix55pAl99dXjwf8ql4s+//xzGjVqFEtZ1a9fn+xAXl4evfjii0zlRI9NMhoU0JiA2oyVEC6SQYGqcWPvqZtALZjZkxrAgJURsGu9jIqMpLfHjaN2993n/tyUKUupV6/JlJfnnfrwtW3bUmngwL9p4MBZVLlyMeratRHz1ahY0XsTRVLJ+nRVo7Hs/+ezj9LRPcPoXNpvVDx+P8XGuvQtpmKsm0JCnS7LEySSScsu7OtkP1z00ENX0+jRPYJ/JZeLvvzyS/riiy+YVIzeNcpIoDaDtmqk6rTi448/Zg0KqNNYrQQtxt0ZJEAy3rrLcHNgAtdO20U7LjKiwRHz5hUimA8++IWefNI3wRRFJB04kEVffbWCatZ8m6pU6UdPPDGGNm064Pv3J1SgqvUGUe1WW6h8gxN0PvYDOpXegLLPeWcPZV9HVLQMZbxGMqqvuyKiwzdd5nXv4qIHHmhEY8Y8GfyvcLlo9OjR9Mknn9DMmTOpefMCKwQb0Lt3b/rzzz9Zqq5SpUqafmbw4MGMZECOjRo1IqsRMiTjzYJ58+bNrN0w0karU6uXS3S8TFq/nupec437c489NpoGDZoX5FseQadO5dC0af9Sy5af0GWX9aE77xxKc+f+6/OnoqMT6Ioafal2y5VUqclZyiv+DZ3ObEPpmXEevz8uLpbuenBYEOcZ4iQjC/9+SMZF997bgMaN6xX8y7tcNH78eFbox+KOQXA74HJheLQ386SZP38+VatWTdPPffrpp/T++++zxgG7yFGQLZB+gUx/3WXcgpk3ECyMjqa8CyZ5jAvE5JWrVaMxK1dSQsFUMq5L+/Yf0+rVRw2muwjKyMijv//eTX//PYalw5o0qUiPP34dPfjgtV4bB/D+lq/cjR3AmROL6MSBERSRs4RKJKVRiRLFqPfLyyl910kDzzXEWpgFTZfZIo7pgWTuvrs+TZjwdPAv7XLRt99+S2+88Qb98ccfdN1115GdKbLJkyczXxrMykCAE4C1Ca9do2PsiiuuYI0JACKvAQMGsJ+DziP/GailWGk9IMjdabwFM/rJQT7wmEHqKBwimYbXXEPj1q51E0xaWjbVr/9GAcGYiwsXImjlyiP09NPTWeNA8+YD6LPP/vTbOFCqXFuq2XQ61Wh5hIpVWUsvvb2VkstcRVE2vl/CtzAXGcYUJZKx3iuiRPEEevbZ1lS1ahJFROTRHXfUoUmTnjGEYDD78vLLL9PPP//MhjDtxKhRo1hHGc6Dd7HhwDkq5wrRRq38GWy2MdOj/Bmkz6yEkE+yXndMZU2GC9zBgrlGjRosZQYCirLRV9sKJm93111083PP0T///MOaJ86di6J77vk/SkuzfneJms/Wran07ruz6d13/6LKlYvTbbc1on79OlOFCt4bBxJLXGoHjbRa08bR3WWRYVuTiY2Jos8+e5Ad7Dk36L4Bsbzwwgv0ww8/UMeOHcluuDSshyjqK8Fq0QJASJLRC9xYYGy4Y27fvp3q1avHWvVAMFw4M9pGkgGwDJix3GP9eeaDD+i+vn3dLeAzZ6bQE0/8QBcvirD4oHEgk0aOXE4jRy6jsmXjqGPHOvTiizdTgwaVvf+UjGQ0p8vEqclYv6GJUZCKUQTz+++/M0VlpJm6dOliyGuGM0LiSQaJnD59mo4fP86KWyh8Y1fDCQaRUVSc5yKzVcDtb/QjiIdq4Lff0nW3X/Ij//XXtdSz5w/kcolAMGpE0MmTF2jKlI00ZcoGKlEiimbP7keNGlUt8p2RNs82OSmSyQvjwr+SZIwAusfgCYNhy9sVz5VE4BBxJdJV/EdhH3lIKAWg8wOFMDXBADEW94abfaET4uNp9KJFhQiGtyiLSTBF8dhjrQsRzI4dR+n775ew1MDxk7Lwr4VkXAhzhEmXWV+Tub7+pRRrsJg7dy499thjTH4FdQwJY+DoSAbicNDuwY4ePtoYMuINAEqCAaJNVEjVAiOXgdJlytDYlBQqU6FCoRbl6dM3ibpvUCGPPvnkNurdu5P7M8uW/UddugxnygNPPz2Fal5+kWSiwr8zpjBRjA3psg5NGtGYR4O3TOYClA899BCNHDmSHngg32NGIsxJBhYAKPBjIAnteOis4AQDclFHQ7GJiWQnjFr6q9WqRaOXLaO4AtI0r0XZHERG5tHEid3prrsuzfD88ssqevTRCe4hUfx74JD1u2LHkEyegPUYiyOZpldWoo/bN2eNPtDi8uYlpQXwgrn//vtpyJAhrA04kDEKCYeRjL83GYQCtVPI/6MvPDU1ldLS0lhUA1c6qJOqpRNiVW52VsOIpaDVjTfSoN9+c18ftChfc827bCLfCYAI54wZL9C1115KcYwaNZdefvmXIjSc54iITIB0mSipMgtrMu0a1aeJD97KTMS2bNnCOkvhN8WdK2N1NPmsXLmSpcY++ugjJtkvCSZMSMYbUGcBuRw+fJhZAKBVFzt5RDIYlMJNh+I/OswwsMQJJzEx0XaSCXYpuKdXL+o9dKhKRflDW1qUA0FiYgQtWdKfate+5Bz49ts/0JAh/3i8OnkOiMpESJcJMyNjUQvzDQ3r0YwX8tWUQSh16tSh9PR09uxj8wnSQV1WaZXsjTiwKb3rrrvo3XffZcOOkmDCnGRQ4N+wYQOdO3fObQGgLPAjcoEpDw60M3PC2blzJ7vRztskjhksyeDGf/7jj+mu3r0LqSjfeutwNgDpBJQpE0OrVr1Dl11W0v25Hj3G0NSpG72m+PKkQqYmWRlhpv0tiGSubVCX/urzeJHnA/VYHNWrV2frA7dK3rVrFxvEBuHgQNcpT6thLUH32Ouvv84UjSXBmAeB7tBLUL/h8EHABD+ACX4QCkJkdCGpC/wAwmWk0Zo0aUJt27ZlkgokwJyMXkCx4OPp0wsRDFSUO3X60jEEc+WVxei//wa5CQbvWZcunzEPG181pFwZybih5pHC6bLwiGRa16tNs1UE4wlYG1CnxbOP6Xi46mKt+Pfff2nYsGEscnnvvfeYg2Xfvn3p1VdfNZVgBgVgmwxMnz6dRWn4exo2bMhaq50KIUlGCcy/wDoUoS88tpUSMp4K/GrExMQwKYXqTZv6t54Q6EIjxTd26VJq2bmz+3Pvv/+zo1qUmzW7jDZu/IASEuLc0ShqSIsW7ff7sy7xb00x0mUikUwgJkIa0LJuLZrTt4duMsBagYUdvi9wj8SGE6l1yKpAogUdZcOHD6c9e/aQWVgUgG3ysmXLmG0y5nXWrVvHiAkH5P2diAiXHv0WiwASwe7j4MGDzIYZjI7dCU+P4WYLpJvk2I4dNHvwYNoxaxblnjxp6TK2C/asGr+3bPny9E1KCpUqV85Di7ITdvguat26LL3xxg2sIIsHPSYmkdq0+ZAOHcrW/Cov0ngh/to1UFKw8feXLkc0RrGRHTeF6OTp/P9nJFxGk+5OISEwaShRjrEitM1r16SFL/c0JNrYsWMHde7cmR5++GF66qmnaMaMGUz4Eul1kIEVOHHiBHse8Pu82Saj0w0kBNVnDswAXn01vHFGk9MgbE1m27ZtdOjQIRa9oEXR04ClXlxWsyY9+vXX7P8n9++nOUOG0LY//6ScI0dMJxytZ1yzXj36atkyFoE5sUUZBNOrV0saMuRhJlSKulhKyr/Us+fvlJnphPN3QLpM1BZmg2syzWrVMIxgEK3ceuutdO+99zJvFawj0CbD4dfw0GLb5OXLl1O/fv0Kfa5Tp07066+/khMhZE4C3WNgfLC3UQSjRtkqVajbF1/QwJ07qf/evdTkhRcopnJlMut207IUXN+5M41JSXETzNmzWZapKBuDPBo48GYaOvQR9j4hD52ZGU1PPAEbZ0kwgSLSKekyA2syTWpWp0Wv9DLkeUfXGTTIQDJDhw4tkgUxSvPMKNvko0ePss5YJfAxl+p3GoSMZCBuifZkXn8xmmDUKF6uHN09aBA7ss6epXnDh9OGH36gzN27KcqgbKK/M+/2/PP01McfO7ZFGTLrY8c+SN26Xev+3Pz5m+jOO0fTxYuSYIyMZAqTjCD7RLVqZxBoVL0aLX71KUOed2xYUeSHkjKm+YMZ2rTDNjkUIMgdWhS4GUAw3jrIzEJiyZLU9a236K2NG+ndEyfo+vffp6S6dSk3yJvT214pMiKCXh42rBDBoEW5WbP3HEMw0dEu+v33ZwoRzNSpy+i220aFBMHoGe6zvIVZlDkZg0im4VVX0rLXnzHkecfOHwSDyOHrr7+2lWB667BNrlChAh07dqzQ5/AxPu9ECEkyb7/9Nj377LPMkxoNAHb1sEO6pVO/ftR/9Wp67/Rp6jBkCJVo3JguBhBee7rQMdHR9Nlvv9GtTz7p2BZlCCssXfoatW9/Kfz//PMZ1KPH947pgvOHHJscVbVFMlEh44pZv1pVWt7/WUOed6Tbu3btymq6sE+2KiVmhG1y69atad48WKVfAjrT8HknQshVADcHBiiff/559qb06tWL7QIwaGUXUCdp99RT9OqyZTTo7Fm6ZcwYSm7RgnI1StKrLzRaKcenpFCzG290bItyqVLR9O+/7xXyhXn55e9pwIC/RL21QqImI6SsTJCRTL0rq9LKN4yZuoeuIdYQdKVOmjSJzZvZmSL77rvvmDcNt03GAd8nDuil9e/f3/1xnz59aNasWfT555+zBigoEqxevZqRlRMhyB1aGGBs5E9RsEOLIWZkMDQFwoEUN7osMKBpF/AgtH7oIXpp4UL6KDWV7po8mcpdfz3l+vCsUT46l11+OU3Zto0q176k4dW9+yj6+OP5or4lRVCpUgJt2/YRVax4yemyW7cRNGrUcod0wTkHRSIZxXqecHkdcnrRv3aVyrTCoAjmzJkzbJIfA9hTpkxxN9E4yTa5TZs2jJTGjBlDjRs3ph9//JGteb6aBUSGkHMynoDi/6pVq9gFR+iJ3QCKeRhSuvnmm9kuQQRsnjuXFg4fToeWLaNIBRHCHWUbEV1Vpw4N/vtvSi5dmj1UhVuUnYGGDcvS0qVvuVMQuIXatx9EKSlaJ4GcNSezFqoTNv7+SlcRfXFpTaIvxhKdv0BUpWpdKtX9H3p6twACqZkZRFNH6v6xWpUr0eq3nqeoqOA3VxDJve2221hHKhZltUiuhD1wDMmoCQcy/z/99BPz4oaXdYcOHdgOBq2KEMizW4sI+knzpk2jw7Nm0clVqyg1PZ1K3XwzPfDOO+xrKCYnJJSgbt2+pUOH7EsD6kWHDtXo11/7uq/v+fM51KLFu7RrV5rhv6sPjRcirhONZIaOIbqiSiN6pu8ymnj8HD232/v0uGXIOEs0Td+gYI1KlWjt28YQDGaysOGEpiFS6/hXQgw4kmSUwOlv3ryZRTggHOgC/e9//2M3HDpLsKuxmnCgVAAl6Hr16rk7Qs4cO0alCnrfEb2sX7+dOnf+inyoSwgGF3Xv3oy++uqSftSpUxnUvPk7dPy4OYXxPvR/FGmrGJAYJFO9QQP66McX6ezRcRRDa2nhqsb02DPz2X39zdFs6rNHgJvobCrRj2M0f3v1K65gBBMdHXxBHtPxd999N7semOJHvVNCHIiwUQwKuLGQq0RxDMqqGzduZHINY8eOpauuuoqFz7BTRQug2XyK14d0BZSfIdCnbDnkBAMgzbR48V5KTERrrP2LqH/k0RtvdChEMJjjqVfvTdMIRuISIqKi6LLK3ahWi7lUrcVpevzZBe6NU46y1cwh3WXVKlakNW/3NoRgUECHkyU2bqjfSoIRD46PZLwBf9bu3bvdKTV4R6ChACk1EA8GPo2McHCTI6JCXhgEg+44LTh8OJW1/P7++wY6fDhLON7HkOWIEffRY4+1dX9u9epd1LHjUNPbrGUkk49aTZrQGC8DfEezL9A7/x6kv9Mu0vH4EkRRNnVSnT5B9Mt4v992ZcXLaf2AF1j7frA4f/48E5KEiC7GHSDlLyEeQpZklMCfeODAAUY4aBqANlDz5s0Z4eCoUqVKUIQDgT1EUfg9ELELdHgP6acvvphJP/20lvbtS7edcKKi8mjatJ7UufPV7s/NnLmOHnjgG8rNNf/cXqD/oyhJMlSnWTMa/Q/M3XzjWNZ5+nL7Ufr11DnaF1OMXDHeux0Nx8mjRL9N9PktVS6vQBvf6WMIweCZe+SRR5i+4dy5c31qgUnYi7AgGSXw50JqAmSDCGfx4sWsTRA1HBAOUmx6CAet1JDjRpiOtJ1RQ1/p6dk0fPhs+uGHVbRz5xnLZ2fQjT1vXj9q0uTS8Ni4cQuoT58fLTuXF2gCRZH9qgd2k8x9vXvTs598outnsi9epLE7j9PkI+m0hRIoNz6RTMXxw0R/fOv1y+WTS9EfT9xFlStWZAZjwWzqIJf/+OOPs7Q0Bhwx4iAhLsKOZJTAn47JYLQ7IsqB5EPdunXdhFO7dm2fDwN68tHlhr53mCOZ1WCADq7Ro+fRd98tp23bTlJenrmLfIkSkbR8+Vt05ZWXrAY++OAXGjRorqXRlSQZos4PPECvjRvn/jg7+zx98MGv9MQTbal69Qqa7/Pp+07SuP2ptDonhs4lmtDuf/QA0YzJHr90RfnyNPe5ByktNZU9b5B34W6ViED0bMygANKzZ09mQobnVS0kKSEewppklMBlSE1Npd9++40RDkJw2LmCbEA66BRTah9heApeNzVq1GDpNquA2s+ECf/Q//3fEtq48ajhaasKFeJo9ep3KTn5UgH1mWfG06RJWGqt7dJ7niZQdBiTzG3du1O/r74qFN02bvw2HTt2njWMlCwZTe3a1aAXXuhErVrV1Py6S4+doS93naTFWURnE0pAKDD4kz28j+ivqUU+XbF8Odr47ouUUJBCxvgBNmewgADhICrhnkOISHwNT+Leh9zUypUrmR8LNncS4kOSjBdgShfdKiCc2bNnM1E73jSAPnzc5FOnTmUPh13AWzdt2goaO3YhrV17KOhCfJ06pWjFigHuBx2vf8cdQ2nuXPOcA30hnEnmnl69qPfQoe6PYfsAgjlxwnM3H8ZCrrmmCvXq1Y5uv7255qh6x9ks+mL7UZp19iIdDaZx4OAeotk/FPrU5eXK0r8D+7oJRg3cX9xzCISD/6N4j2cKUY5y1gXkBO+Xf/75h0UwlStfkjKSEBuSZDQgPT2deWxjFgeRDnZUiG6grYYGAjvVXTnwNs6YsY6++moerVy5n/TKvN1wQ2WaOfMV9+KEv/G66z6gjRuhVWAPnqeJFG2aw4+4JPPgiy9Srw8/LNQQcvXVb9Pp0xc1q2I3aFCeHnmkDfXo0VaztMqpcxdo6NZD9MPhNDpcrCy5YnU0DuzfSTTnJ/eHl5UtQ/8O7EdJcbG62pFBNjiQVUADze+//842dqifooNs4cKFTDLGTIDIPvvsM9aRiowF6rd43n3h+++/p08//ZSNMGAYHA6ceI0yZcpQuMP+1dEBgGQNDI/Q0YIU2ogRI9guCzceajivvPIKLV261FKHPTVADrfe2pQRxalTw2nGjGeoU6fqlJQE0vC1j3DR/fc3pL/+etVNMJmZ56hBgzdtJZj8Mws/PPb664UI5tixs9Sw4VuaCQaAvcL69SfopZd+o+TkF6lx4zeZ+GpqaobPnysRFUG3nj9G0ysRnWhdngaXvkCNz52i6HMahj0Vgmrly+gnGADPFFLPzZo1o7Zt2zJPKQw1Q+wSSsrXX389W8TxHJoJDHeiGQj6iVqAZx8ilz169GBjDNOnT6eUlBRWO5KQkYxmfPDBB6xOg10Nbn4AqtCQ4MYuCxFOXFwceyDuvPNO5mFhp/qrEphrGTJkFi1YsIPS0rBY8VSKi+69txq9/votLEWBv+vYsTPUvPl7lJqqfVEzC71pIsWEUSTTa8AAevC11wrNUDVt+i6lpxuVMsyjihUTqXPnhtSvX+dCjR1YuNeuXcsW+oYNGxaKzrFE/HLgFH2z9zSl5ERTdmKJoi+9eyvRgt+pfJnStHFgPyoeH3z7NFJkGLKGijGeP5wfnjOk1bCY+/NlMQLYePmLZAYPHsyEMHft2uX+3PDhw+mTTz5h6h/hDkkyGoGHEJcKROLt68gVo4aDbjV8L6If3JzYldltfMWxefNBGjJkJs2b9x+9+monuu++piwnjmP//lTq23cenTsngiwl0XM0iWLpYsiTDK72cx99RPf06eP+3P79JxnZZ2aa9Xi6qFSpGPrf/2rSs8+2p8jIMx4JxhNWHD9Lw3edoIWZRGd448COzVRu0zL69z1jCAbPz0cffcTUOtCmXL9+/UK6hRh4tkIuSgvJIJKBlBWee6TJ8Czdd999rDt1zBjtUjuhCkkyJgBtlpi/QdiMGw+5ZhAOcss33nijkOqwS5Zso1tuGU4XL4qTQQ0HksEy+eKQIXT7U08Vkuxp2fIDysqy7tGMj3dRq1ZX0tNPt6dbb9W+gO9Oy2aNA1sPHaEfOzalkonB39tYkhAdIBqAeRdSV3ZBC8kAeNafeOIJlt3A84+MBjacMTZbDYgASTImA3WaZcuWuT0h0L4JawLctLAqSEw0eUhOI44ehbzNX/TTT6sLWmTtJ5tn6VuKo5yQJRks47e/8AJ1fPhhlq7EzMjOnceoTZtBuhs3jERMjIsaNryMHn30WnrssestXSixHH355ZesaI5UNOozdkILyWzZsoWpwPft25c6derEmgVQp23RogWNU8w4hSskyVgIhPooCHLCgSfOTTfdxG5g3Jx2euLg3DD3Ax2oK6+sRePGIRJbQ3v3ptlGOKFMMpEREfTG2LHU7Oab3enKHTuOUb9+Cygnx36CV2rX1aiRTPfe25x6976JSpY0b1OEpQi1DdRfMDbQsmVLshtaSAbyNohgEM1wLFmyhDUqHD58OOzneSTJ2LioQ46GC3ju27eP7YZwM8MTJ1jpDb3RFiaoIZEDT3RlOg+dZiNHzqEpU1Jox47TlsrbPEPfUTxdCDmSAcG8O2kS3XDXXe7PrV+/l9q1G0w5OWLUwzwjj664IoluuaUh9e3bmapUMU7OBcsQdv1vv/02k+u/7rrrSARoIRnYDKDJR+l2CX1EOFweOnSIifGGMyTJCAC8BZs2bXJ74qBts3379mz4E7UcdH2ZRTiYuEYhFeeAYqqv1Ai+9+uv5zN5m82bT5gubxOKJBMVGUkfTJtGrbt0KdT916HDUMEJpjBKl46h3bs/MSSVhnvv22+/ZSkmDEDDqthOoHsNumgAnokhQ4awwj7SmWix7t+/PyOPSZMmse+ZMGECa1dGmo+ny1588UXWQLFy5UoKd0iSEQx4O2C8hggHB8gH/jggHBQTMQltFOEgxEc0hcilUaNGujSkEP18++0SGj/+H9qw4RibzTAaT9P3lECoD4UGyYBgPv3lF2rWoYP7c8uW/UedO38pVMOFP5QsGUUbNrxH5cp5aGUO4H6fMmUKW5SRQkY0bzcw8AlSUaN79+6MUB577DHmxovv40CTwujRo2nPnj1MtQCbRLQwX3HFFRTukCQjMPDWoPeep9QwJ4AQnMvbINcbKOFg4Ayvh90ZBkqDUS3Aef7440oaM2YhrV590DCfmafoe0oMEZKJjoqiITNmUKPrr3d/buHCLXTbbSMtsU0wCiVKRNHGjcYQDIDoHXpkP/zwA0sTS4QeJMk4BHib9u/f7/bEWbFiBete4Z440HLSSjjQZUMEg10WBD6NTsX99dd6GjlyLq1YsY+yswN/nadoMiWSjW1WBpEM/FO+nDOH6l5zjftzc+ZspLvu+tr0lKPR6tzr179Hl11W0pDXw2Dlk08+ySIZbJokQhOSZBzsiYPoBgc6WWCWxi0KqlWr5pU4Tp06xQzWII9TtWpV08918eJtNGzYbFq8eDdlZGB6XxuhRUbm0UvFfqOLaankZJLBEO5XCxdSDcWsx59/rqVu3cY5imCKFwfBvEsVKuSrXQQLFPeRdpo4cSLdc889hrymhJiQJONw4O1D+yv3xEGeGLYE3KJA6XOD9BiEB/F1O9oq163bw2Zx5s/fTmfPKuVtCiM6Oo9+//05Wv74rZRx7Bg5lWTi4+Jo9OLFdGXBtDrw888p9OijEy03oQsGxYpF0rp171LFisYQDOZfHnroIRo7diyzT5YIbUiSCSHgrcSci9ITp2bNmiwVASJC3htpNrNVbLVg69ZDTN5m9uytdOrUBTfhREfn0mef/Y/atKlLf3TtSpnHjzuSZBLi42nsihVUqeYln5dp05ZTjx7fOYpgILC6du07VKmSMWrC2ARBcuWrr75i8yVWtelL2AdJMiEKvK2ovUAq/f3332ctmRAUfOCBB5iAJ7rJRLAo4DpdgwfPoCVLdtLUqc9S+fIJjBSndehA50+dchzJJCUm0jcrV9LlV13l/tykSf/QM89gjkKMa24HwSCti5mSoUOHMsViSTDhATFkgiUMBx7gYsWKsZ0jxDvhjYH5G0Q46OVHKzQiHBAOpDvsJBwM9X35ZfdCn0MbaGLp0kKQjB4UK16c/m/1aiqnUAj+5pv51KfPT44imMTECFq9eoBhBIMI+t5776WPP/5YEkyYQUYyIQxoKuGBRpuosl8f7cuzZs1iTQMowEJdAISDGg6kPPTMy5iJrLNnae6wYbRh+nTK2rOHomy6VbVGMiVKlqSJ69ZRssJ3fsSI2fTaa787imDi4vJo1KjO1LDhVWwzAuOtYDYh2OBgxguy/X369JEEE2aQJBPiwNvr66GGQjT3xEFqDYOZWBBAOCJ54pzPzqYFI0fS2ilTKP2//ywlnDW4Tn6+J7l0aZq4fj2VUDghDh06k956a4ajCAaKQikpb1JycixzqETaEkoPZcuWZSKe+FfPPYFOxltuuYVef/11NtEvCSb8IElGoognDhfwxIKABQIpNagOiOKJg0VvyTffUMrEiZS6ZQtFm+xI6o9kypQrRxM3bKBiJS/Njwwa9Bt98MEczS3bIhFM9eoV3J/D8gD7cZANSAdRMAZ4QTiIcrz5KwFQq8CAJab533zzTUkwYQpJMhIeAU8MeJ1zT5zz588zwkGEA8kMX4uLlcDtu+y772jhyJGUtmULxZhAOL5IpnyFCjRx40ZKSEpyf27gwJ/o008XOI5gVqx4k2rWvEQwngCS4RFOWloa87MH2YB0lLYVUPQGwfTq1Yvee+89STBhDEkyEpp0yuD+xyMcLC7cEwdaU3Z64uD2he87RAmhIL19zhxa/PXXdGzVKoo6f95Ukrm8UiWasH49xSUkuD/35pvT6IsvFjuKYLBfWL68P9WurU8tGBsPHuGgdR6pMQwJt2rVil577TWm9TVo0CBLmkqwIYIHDeo/uBe0GI3h/EGAsHeG7QZmxwYMGMDMxySMgyQZCd0WBVCW5YSDRUbpiYOONquAWxc7ZqgYoENOTXab5syhRcOH08HlyykqK8tQkql85ZU0bu1ailVEdC+99B2NHr3CcQSzdOnrVLfuFUGnMNFEAqFI3B/wRsJifddddzG9PbObSf766y+2EcJ9gN+phWQwsHzs2DHmXwN5JZAT7m/UIiWMgyQZiYCBBxIqAlzA88CBAyyywcNrticOfje65zALhIXFn6X1jmXLaP4XX9D+f/4hSk/XRQNqkrmyZk0au2pVIZn73r0n0P/932pHEUxsrIuWLHmd6te/1G4dDOCJhAgXmw1YVGAoGM0kUJhYtGgRieQBg+5KzIzt3r2b1ZgkzENYkwxCeSyO27Zto4SEBLbjgjx37dq17T41x3rioIaDa4oU1o033shao432xAHBKE3W9NaH9m/YQHOHDKHdc+eS68wZv7SgJJma9erR6BUrCu3Mn3pqHH333TrHEczixa9RgwaVDXk9+KuAXPCef/311+4UGWp7+JoVOnl6SAbKz5gba968OfOySUpKYvcqBpexFkgYh7AmGey6sJuBmjEehjfeeIMtlNgh46aTCAy4pUDc3IRt8+bNrDsNDz3ao9EGGyjhoD6E3D/SMyCYYE2zju3YQX9//jltnzWLck+c8NhszEmm7tVX01dLlhQ698ceG03Tp29yHMEsWvQKNWpkzMKPegaepdatW9P48eNtn7PSQjI4XwwqI/JGHebkyZOMeOAj83//93+Wnm+oI6xJRg0UMNElg9Aei6KEcZ44nHBgMYCIEQsAdo4VKlTQTDjYCODnuWOh0TM8pw8eZISz9Y8/KOfIETfhgGTK165NfcePp8suu4yRJMitW7cR9Pvv/5GTEBMDgnmZGjc2Rr8ONTmkRhs3bswiAhHmqrSQDOqIixcvZgSJDjkA9ycUodFBJ6MZ4+CcKTELgPw+IHO0xj7wKKpiGA8FYaTRQC6o49SpU4c97CNGjGD1HF/7HS6Ng10yIhgzFrPS0HYbOpQG7txJ/ffupaYvvkixVapQq44dacSiRayYDUdEbEI6dBjoSIJZsOAlwwgGDRd4L2F6BytiEQhGK9BJBhUMTjAA/g7cgwcPHrT13EINMpJR5PnxwJw5c4YJ+UmYC9x2yNVzTxx0BiE64Z44UIrmEQ4WM+TP0T3WsGFD24U9O3f+hP75x1kLUXS0i+bP70fNml0S7QwGsIxA6hOiq4hSRRnU1RrJjBkzhg2JIhLjHZFoVEBnWkZGhoxkDISMZArw3HPPsXrM1KlT7T6VsAAWAixQL7zwAlMZQCSDllf8H2Rz3XXX0aeffsokb5DrRx1GBIIBOXbq1Ijq1UtmxmpOIZh58/oaRjCI+KECgdQhGj1EIBgQw/r169kB7Nmzh/0fbrJA//796dFHH3V//4MPPsg02R5//HFWg8WcDWRvcA8+88wz7P7EgbQoTABfffVVOnfOfpdWJ0JGMqz9tDfbxeBGww0lYb8nDmZwkILBe4KUBoqy2GUipSHK9DiaEMaPX0QTJiyhf/89Rrm5kUISzJw5L9I119Qw5PUgMQOCQVT5xx9/CLPjRxEfRXs1MBA6YcIE5sKJVCe+jwPNKc8//zyLokE48LnBzAxIBvMzaABAgwnStHidp59+mnWfSuhDWJMM/nTcZAitcfPB4EtCDCCq7NixIyvEos0UKbW///6bqlSpwtJpWOhEiGyU99LUqctozJhFtG7dYcrJsZ8Io6Ly6O+/X6RWrYy5r1EQhx8MSH7mzJkh24EJQkLaHBsdDvzdiI4wF4b0LTam2AAhbQgrc3SmKl0+kX4fPHgwS8shSkfU99RTTzENNwCfe+mll9g9jXv4+uuvp2HDhglhKGg0xHhCbUyRQVJi8uTJrKiLThMcUCaWsHfBfvLJJ9mO8ssvv2S7SESa2F1CLh4DdCAgGK/hoV29ejV7qO0EFt5u3a6lBQveoNTU4TRlymN0ww2V2US9XQTz118vGEYweCbuv/9+dp3//PPPkCUYbxueZcuWudOCSJthABgKB/ga9Nng8pmSkuL+GaTn4J3z9ttvs3Qc1hgQDYDoCDNFWHPQ4YZICnUhtFWjwSXUENaRjLe0C8Jk7GYk7APSMngIfe2qISXCPXFgcobGDUQ5InniAPPnb6Ivv5xDS5fuoawslyUEM2PG83T99XUMeT0sqtilY3ePnbeyIysUgWcfm0+oSKBtHhpniDZgX46IxhMwcIxuSUQvuHchGoquySeffLLI9+K1kZaDJBJfg0AuuIcRPaHjMpTgnJ5DExDG/Co8fBEMgJ00Umk4uCcO2qKRV8fiwE3YMJNjd2tt+/YN2AGkpOykoUNn0cKFOygtDYrRxqbV0Izwxx/PGUYwWPxQMMcM2dy5c0OeYDhQ3xk1ahTbzMAuGvcQJxjU4j766CNGOuiQxDUCEXHtPJAHPob6gSegiQV26Op7HGSOmbJQQ1iTjERoAMVnkAoOPPDz5s1jhIMUBnaK2GVyT5xgFQKCBQrwU6b0Zv/ftOkAff75TJozZxulpuYETTicYNq2rWfIuSKtg+4rdGjNnz8/rObHsInBfBcAFQMMm44bN445zULtGfWTL774gtUF8b1oh+apLn/NEBkZGSzd9v333xf5GiKgUENYp8skQhtYJLknDmo6WAS4Jw52qiJ44kB/Dd1LFy7E0E8/baG//tpMx4+f1004IJjffnvGHTEFC6SJkOpBzQFNMVDCCBd4KvxPmTKF+vXrx+qBiJZxPUA6AOpUSJVBCBQ/g4gEhIx64pMe0mVjx45lVgjodoOIbKgjrAv/EqENRC1IWYwePZpNcaN+g3QPfObRqo5dKdpw7Wr04ASDBat9+5b01VdP0J49n9OOHe/TM8+0oiuuwI44TxPB/PzzU4YRDNJBaBlHWgdRYTgRjDfce++9rM43cuRI1oWK9CyaAZAaQ9cYmlI4kK4FiWC2ZtKkSSwFtmLFCjcpPfTQQ0yaCPVDFP7RtQYix8xYKKoNSJKRCAtggWjbti3zO4EkPVpwIS2CLiC0jaLuABJCKsMqgkFXHBbwWrVqFWpCqVgxmQYPfoi2b/+U9u//hF566Qa68spiHgknIiKPRo9GKtAY5XDsyrHYYVFEDQbXSALzRtGsbRkDwmg9hrQROsTatWvH9PfU6gLoKsP3DRgwgM12oTMP6gIAajeIsNGOz2e/sOFBBBSKkY1MlzkQKEjiQLgN1K9fn93MnTt3tvvUHAcsqogmuCcOdpJoj+aeOCjOGj38yQkGLa1qgvGFzMxz9OWXs2natBTaufMM+9yIEbdR/fql2RQ+ojSQFo5AhiRxLfjsBpQXQnFmQ8J6SJJxIJDiwc4cYTvevokTJ7JiJBSKQTgSwfnUcMVopDmUnjhoMQ2WcDjBYPeL9y/Q1zt/Pof27z9FNWtWKGSFjAMDgpi7AImBcLTMtOBvR1SHmgJSNxgwlJAwApJkQgQoNIJoEHZLGGftzAkHA3VItyEtAsIJxBMH7bCImoIlGC0ND2g5Rp0AEj2IajjhgHzUvxcE884777DiNiIYadonYSQkyTgcKNKiewpT8Yhk0OEiYSzwiGCugRMOhBfhA889cbCA+yMMqwjGU5cYDLkQ4eBfTK3jfBHdcC+fDz/8kBWlQTBW3T+oSWBThGty5MgRv6rJSmBCHoTfoEEDtyCmhLiQJONQIK0DdWIUC7E7hWwFaggS5gKPC2phqOFgYYRHTqtWrVgNBwc8StQEwgkGRXTMXtgl8IkNCXS3QDggFnRH4Xx5dxPUr60C1BpAFpgXQfFbK8mgtRg/g+uISE2SjPiQJONQYOYDQ3Io+GKH/c033zAzLRnJ2OOJA9LBoo2uI+6JA197bAaQhoKEvJ0EowbatqHdh8UdUQ26p3De6ILyNqlup/8LB+zSEQmiJon6kSQZ8SFbmB0KpD2waGFXN2jQIDaRjClkCXs8cRAJgPQxyIfZErwfLVq0oPbt2zMiQiFdFIIBOWKKfdasWSxthcgGEimY7wAhigpoCmIYEvUjCedAysqECFC8RYeRhD0AgSAdBuVo+I4gjQZVXdQ/fv/9d6ahxvXU7PTEAcEg6oVAI2aFICYKYN4Dh6iAbTcsvDG8aLcWnYQ+yEjGgUCrKXagqA0gHYOPsZPGJLGE/YBVNLTSMLyHNmjUDjB/snHjRuYbguhz4MCB7GMrLQpAMJhAf+utt5jMDpoXnADUkuBkiWuGuSIJZ0HWZBwItCkjJYOuHAzgwVcFMhYYIpSwHyAW1BhALOqIJS0tjfmxoIaDdBU6vFC/QYSDeo5ZJmx4zNEc0rdvX0YwVtddgqnJoNifnJxcyL4B5Iy/CZ/D8CjSkhJiQpKMhIRNgISN0hMHCylPqV1zzTWGeuKgzR16ZGgSEU0Zwh/JgFAwp6TEV199xZSh8fdAhy6cTNScBpnclJCwCWg9h/AiDnR7YUeOCAcfc/sCRDnBeuKgCwsEg6K+KAQDgsXsEQfaqNEphqFiaHohBYyGCaT3EN1hJkYJDJaiUUH9eQnxIGsyEhICAKQCQsGiijQo5ODRpv7www+zlt3nn3+e7dwxza8HSM317NmTvS5ISxRAWgdzOXw2BzL6+D80+ABcA3TrSTgfMl0mISEwQCqYf0JaCBEJPoasDVJL6Abz5Ykze/ZsZtyGbjLMl0hI2AFJMhISDgEkYpYsWeImHKScoPIAwkEhX6m8DIkYDFaidsEdQiUk7IAkGQnb8PHHH7PcO0zEYGUroa+tF54vXN4GumSYy0HKDfYESLPhmkJpQBKMhJ2QJCNhC1atWsVsbGHSBCtkSTKBA91XqHGAcBDlYCoeBA5nRkkwEnZDkoyE5UCaBzMhSOVg8vzqq6+WJGMg4aAWg6hGEoyECJDdZRKWA8KMt9xyC3Xo0MHuUwk5oN0XbcqSYCREgZyTkbAUU6dOpbVr17J0mYSEROhDkoyEZThw4AAr8s+ZM4cN0klISIQ+ZE1GwjKg7RbCkUq5FHRJIbWDNA9UpI2UUpGQkLAfkmQkLEN6ejrt27ev0Ocef/xxqlOnDhP4lBIhEhKhB5kuk7AMmN9QEwmEDcuUKSMJRkIiRCG7yyQkJCQkTIMkGYdg+fLlrF6B1t9QAszW5IyM2IBBXteuXalixYqsfobami/AugDeRuXKlWPDtq1bt2azOxLhCUkyDsG4ceOYEi8e+MOHD9t9OhJhhMzMTGrcuDGNHDlS0/fjHgXJwN55zZo1TNEBJLVu3TrTz1VCQKDwLyE20tPTXcWKFXNt27bNdf/997s+/PDDQl//7bffXDVq1HDFxcW52rVr55owYQKaOVypqanu71m8eLHruuuuc8XHx7sqVarkev75510ZGRk2/DUSTgbuq19++UX3z9WrV881cOBAU85JQmzISMYB+OGHH1gHVu3atZnw4fjx45n1LDd7uueee5gS74YNG+ipp56iN998s4gdMGRG7r77buYrP23aNKbmCw96CQkrpG7QWQhDMokwhN0sJ+Efbdq0cX3xxRfs/zk5Oa6yZcu6FixYwD5+7bXXXA0aNCj0/W+++WahSKZHjx6uXr16FfoeRDaRkZGu7Oxsy/4OifCMZD755BNXcnKy69ixY6adl4S4kJGM4Pjvv/8oJSWFunXrxj6GDS98QlCj4V9v0aJFoZ+BP7wSiHAmTJjA7H750alTJ7bDRCQkIWEWJk+eTAMHDmTROCyTJcIPck5GcIBMYFaFzh4ObCjhiDhixAjNqsdIo73wwgtFvgY/dQltePfdd9mCqQRSmNu2bbPtnETXqXvyySdp+vTpUgw1jCFJRmCAXODN/vnnn9NNN91U6GuowUyZMoUtcujiUUItPglZ/S1btlCNGjUsOe9QRv369Wnu3LnujxFZShQF7k0YpoFoQq3tXkIf5BMiMP78809KTU2lHj16UMmSJQt9DUV8RDlIQwwZMoTJsuD71q9fz1JjAJd7x9datWrFCv3YWWLKHqQDoUqt0ZDEJVKpUKEChRMQCe/cudP9MVKsuM9QyEckDHfTQ4cOsQ0RT5F1796dhg0bRi1btqSjR4+yz8MeWn0fS4QB7C4KSXjHrbfe6urSpYvHr61cuZIVYTds2FCkhXnUqFHsa8qifkpKiqtjx46sFTopKcnVqFGjIq3QEr7xzjvvuBITE12XX365q1q1aq4HH3zQtW/fPleoA00muJ/UR/fu3dnX8W/btm3d34//+/p+ifCCFMgMQXz44Yc0evRoJq0vYRz++usvtqtHivLIkSOsPoMd/KZNm5gum4SERFFIkgkBwMYYHWYQmly6dClTBkBqDNbGEubhzJkzVLVqVZauRKpSQkKiKGRNJgSwY8cORiinT59mOfKXXnqJ5cklzEWpUqWoVq1aheoVEhIShSEjGQmJAIHUGUgdrc2e2sMlJCSkQKaEhGa8/PLLtGjRItq7dy8tW7bM7fLJB2UlJCSKQqbLJCQ04uDBg4xQTp06xWTsr7vuOlqxYgX7v4SEhGfIdJmEhISEhGmQ6TIJCQkJCdMgSUZCQkJCwjRIkpGQkJCQMA2SZCQkJCQkTIMkGQkJCQkJ0yBJRkJCQkLCNEiSkZCQkJAwDZJkJCQkJCRMgyQZCQkJCQnTIElGQkJCQsI0SJKRkJCQkDANkmQkJCQkJMgs/D+XC4eCf/f/MAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -308,10 +298,11 @@ } ], "source": [ - "load_histograms(csv_path=dataset_path,\n", + "load_heatmap(csv_path=dataset_path,\n", " target_col=target,\n", " protected_list=protected_list,\n", - " method_kwargs={'feature_involved': 'Gender', 'subgroup_to_check': 'F'})" + " feature_involved='Gender',\n", + " subgroup_to_check='F')" ] }, { @@ -326,22 +317,15 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 21, "id": "7249e1c6", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[INFO] The most impacted subgroup bias > 0.125\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "Is the most impactful subgroup biased? False\n" + "Is the most impactful subgroup biased? True\n" ] } ], @@ -362,7 +346,7 @@ ], "metadata": { "kernelspec": { - "display_name": ".venv (3.13.3)", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -376,7 +360,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.11.2" } }, "nbformat": 4, diff --git a/examples/supports/linf_utils.py b/examples/supports/linf_utils.py index 4d32f4a..0f4fcc5 100644 --- a/examples/supports/linf_utils.py +++ b/examples/supports/linf_utils.py @@ -4,87 +4,181 @@ import pandas as pd import matplotlib.pyplot as plt +import matplotlib +import matplotlib as mpl + import warnings warnings.filterwarnings("ignore") -def plot_3D_histogram(xdata,ydata,xlabel=None,ylabel=None,zlabel=None): - - x = xdata # turn x,y data into numpy arrays - y = ydata - - fig = plt.figure(frameon='False')#create a canvas, tell matplotlib it's 3d - ax = fig.add_subplot(111, projection='3d') - - #make histogram stuff - set bins - hist, xedges, yedges = np.histogram2d(x, y, bins=(5,3), density=True) - xpos, ypos = np.meshgrid(xedges[:-1]+xedges[1:], yedges[:-1]+yedges[1:]) - - - xpos = xpos.flatten()/2. - ypos = ypos.flatten()/2. - zpos = np.zeros_like (xpos) - - dx = .9*(xedges [1] - xedges [0]) - dy = .9*(yedges [1] - yedges [0]) - dz = hist.flatten() - - cmap = plt.cm.get_cmap('jet') # Get desired colormap - you can change this! - max_height = np.max(dz) # get range of colorbars so we can normalize - min_height = np.min(dz) - # scale each z to [0,1], and get their rgb values - rgba = [cmap((k-min_height)/max_height) for k in dz] - - ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color=rgba, zsort='average', ) - plt.title(zlabel) - plt.xlabel(xlabel) - plt.ylabel(ylabel) - - -def load_histograms( - csv_path, - target_col, - protected_list, - method_kwargs +# https://matplotlib.org/stable/gallery/images_contours_and_fields/image_annotated_heatmap.html +def heatmap(data, row_labels, col_labels, ax=None, + cbar_kw=None, cbarlabel="", **kwargs): + """ + Create a heatmap from a numpy array and two lists of labels. + + Parameters + ---------- + data + A 2D numpy array of shape (M, N). + row_labels + A list or array of length M with the labels for the rows. + col_labels + A list or array of length N with the labels for the columns. + ax + A `matplotlib.axes.Axes` instance to which the heatmap is plotted. If + not provided, use current Axes or create a new one. Optional. + cbar_kw + A dictionary with arguments to `matplotlib.Figure.colorbar`. Optional. + cbarlabel + The label for the colorbar. Optional. + **kwargs + All other arguments are forwarded to `imshow`. + """ + + if ax is None: + ax = plt.gca() + + if cbar_kw is None: + cbar_kw = {} + + # Plot the heatmap + im = ax.imshow(data, **kwargs) + + # Create colorbar + cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw) + cbar.ax.set_ylabel(cbarlabel, rotation=-90, va="bottom") + + # Show all ticks and label them with the respective list entries. + ax.set_xticks(range(data.shape[1]), labels=col_labels, + rotation=-30, ha="right", rotation_mode="anchor") + ax.set_yticks(range(data.shape[0]), labels=row_labels) + + # Let the horizontal axes labeling appear on top. + ax.tick_params(top=True, bottom=False, + labeltop=True, labelbottom=False) + + # Turn spines off and create white grid. + ax.spines[:].set_visible(False) + + ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True) + ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True) + ax.grid(which="minor", color="w", linestyle='-', linewidth=3) + ax.tick_params(which="minor", bottom=False, left=False) + + return im, cbar + + +def annotate_heatmap(im, data=None, valfmt="{x:.2f}", + textcolors=("black", "white"), + threshold=None, **textkw): + """ + A function to annotate a heatmap. + + Parameters + ---------- + im + The AxesImage to be labeled. + data + Data used to annotate. If None, the image's data is used. Optional. + valfmt + The format of the annotations inside the heatmap. This should either + use the string format method, e.g. "$ {x:.2f}", or be a + `matplotlib.ticker.Formatter`. Optional. + textcolors + A pair of colors. The first is used for values below a threshold, + the second for those above. Optional. + threshold + Value in data units according to which the colors from textcolors are + applied. If None (the default) uses the middle of the colormap as + separation. Optional. + **kwargs + All other arguments are forwarded to each call to `text` used to create + the text labels. + """ + + if not isinstance(data, (list, np.ndarray)): + data = im.get_array() + + # Normalize the threshold to the images color range. + if threshold is not None: + threshold = im.norm(threshold) + else: + threshold = im.norm(data.max())/2. + + # Set default alignment to center, but allow it to be + # overwritten by textkw. + kw = dict(horizontalalignment="center", + verticalalignment="center") + kw.update(textkw) + + # Get the formatter in case a string is supplied + if isinstance(valfmt, str): + valfmt = matplotlib.ticker.StrMethodFormatter(valfmt) + + # Loop over the data and create a `Text` for each "pixel". + # Change the text's color depending on the data. + texts = [] + for i in range(data.shape[0]): + for j in range(data.shape[1]): + kw.update(color=textcolors[int(im.norm(data[i, j]) > threshold)]) + text = im.axes.text(j, i, valfmt(data[i, j], None), **kw) + texts.append(text) + + return texts + + +def get_heatmap_array( + df: pd.DataFrame, + race_values: list = ['Green','Blue','Purple'], + age_values: list = ['0-18','18-30','30-45','45-60','60+'], + protected_list: list = ["Race", "Age"], + ) -> np.ndarray: + '''Retrieve a matrix with the subgroups' relative frequencies + ''' + tot_counts = sum(df.value_counts().values) + dummy_lst1 = [] + for i in race_values: + dummy_lst2 = [] + for j in age_values: + dummy_v = df[(df[protected_list[0]] == i) & + (df[protected_list[1]] == j)] + dummy_lst2.append(sum(dummy_v.value_counts().values)) + dummy_lst1.append(dummy_lst2) + + return np.asarray(dummy_lst1) / tot_counts + + +def load_heatmap( + csv_path: str, + target_col: str, + protected_list: list = ["Race", "Age"], + feature_involved: str = 'Gender', + subgroup_to_check: str = 'F', ): - + '''Plot example heatmaps + ''' csv_path = Path(csv_path) df = pd.read_csv(csv_path) - ############# Manual encoding ############# - df["Race_cod"] = df["Race"] - df["Age_cod"] = df["Age"] - - for index, row in df.iterrows(): - if df["Race"][index] == 'Green': - df["Race_cod"][index] = 1 - elif df["Race"][index] == 'Blue': - df["Race_cod"][index] = 2 - elif df["Race"][index] == 'Purple': - df["Race_cod"][index] = 3 - - if df["Age"][index] == '0-18': - df["Age_cod"][index] = 1 - elif df["Age"][index] == '18-30': - df["Age_cod"][index] = 2 - elif df["Age"][index] == '30-45': - df["Age_cod"][index] = 3 - if df["Age"][index] == '45-60': - df["Age_cod"][index] = 4 - elif df["Age"][index] == '60+': - df["Age_cod"][index] = 5 - ############# Manual encoding ############# - # Filter by positive target df = df[df[target_col] == 1] + # (possibly) discriminated group + discr = df[df[feature_involved] == subgroup_to_check] + + fig, (ax, ax2) = plt.subplots(1,2, figsize=(20,5)) - discr = df[df['Gender'] == 'F'] - priv = df[df['Gender'] == 'M'] + im, cbar = heatmap(get_heatmap_array(df), df[protected_list[0]].unique(), + df[protected_list[1]].unique(), ax=ax, + cmap="YlGn", cbarlabel="rel. freq general population") + texts = annotate_heatmap(im, valfmt="{x:.2f}") + im, cbar = heatmap(get_heatmap_array(discr), df[protected_list[0]].unique(), + df[protected_list[1]].unique(), ax=ax2, + cmap="YlGn", cbarlabel="rel. freq. Female instances") + texts = annotate_heatmap(im, valfmt="{x:.2f}") - plot_3D_histogram(discr.loc[:, ('Age_cod')], discr.loc[:, ('Race_cod')], - xlabel="Age", ylabel="Race", zlabel="F") - plot_3D_histogram(priv.loc[:, ('Age_cod')], priv.loc[:, ('Race_cod')], - xlabel="Age", ylabel="Race", zlabel="M") + fig.tight_layout() + plt.show()