diff --git a/examples/bayes.ipynb b/examples/bayes.ipynb index 454c29e..0be164c 100644 --- a/examples/bayes.ipynb +++ b/examples/bayes.ipynb @@ -14,42 +14,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "0fd9178b", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from pyem import EMModel\n", - "from pyem.models.bayes import simulate, fit\n", + "from pyem.models.bayes import bayes_sim, bayes_fit\n", "from pyem.utils.math import norm2alpha" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "99a20e07", "metadata": {}, "outputs": [], "source": [ "# simulate computer agents completing the fish task\n", - "nsubjects, nblocks, ntrials = 30, 6, 15\n", - "true_lambda = np.random.uniform(0.2, 0.8, size=(nsubjects, 1))\n", - "sim = simulate(true_lambda, nblocks=nblocks, ntrials=ntrials)\n", - "all_data = [[sim[\"choices\"][i], sim[\"observations\"][i]] for i in range(nsubjects)]" + "nsubjects, nblocks, ntrials = 50, 6, 15\n", + "true_lambda = np.random.uniform(0.2, 0.8, size=(nsubjects, 1))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "787bc9c3", "metadata": {}, "outputs": [ { "data": { - "image/png": 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AoVCILVu2YNKkSTh8+DD69u1bb3yENEWVzYaixN8ILi4u+O2338BxHNq0aYOAgABT8sjLywMARERE1HiscRTJmjVrMH/+fCxcuBDDhg2Dp6cnTp8+jeeff97slwAA+Pj4mL3mOA6HDh3Ca6+9hueffx6lpaWIiIhAQkIC7r//figUCjDG4OfnZ3acQCCAt7c3CgoKzLZXXeRBJBKZPQuoTdW4auPm5oY+ffrUu1/VrpjKPD09AQCFhYXV3lMoFKb3ayIUCvHVV19h6tSp6NWrFwCgZ8+emDt3LtauXQsvLy8AwKpVq1BYWIizZ89CIpEAqCicFRkZiaVLl+K7776r9x6Ic7M06TPGoFAaoNEyiIQc5G68OhsvtkKJvxF4PB769etX43vGJLJv374a+7yNrdo9e/Zg/PjxZktNXrp0qcZz1vQfIjQ0FHv27IFWq8XJkyfx6quvYty4cbh9+zbkcjk4jsPdu3fNjtHpdMjPzzfF2FiW/kc9evQohg0bVu9+mzdvrrUvXSqVomPHjtX68m/cuAGVSlWt77+qPn36IC0tDVevXgVjDF26dMGcOXMQGRlp+vR26dIldOvWzZT0gYp77N27Nw3nJPVSqVT1Jn2NluGvDDVOXypDVo4WOj0g4AMd/YTo390F4Z3EEAnt9wuAEr+dREdHQyqV4tatW2Zlp6sqKyuDSCQy27Zjxw6rrycUCjFkyBAsWrQI48ePx507d9C1a1f06dMHX331FebNm2fad+/evdDpdBg8eLDV12kMW3X1jBkzBvv378e7775r+rf78ssvIZFIMGLEiHrPz3EcunTpAgC4d+8edu/ebTaCKTAwEPv37zc97AUAg8GAc+fOISgoqN7zE+cmFovh7++PO3fu1Jj0S1QG7Pq5CBczNQAHyN14kEo46PQMaTc0SL2uRniIGI/GeMBdap+Bl5T47cTDwwMrVqzAwoULcevWLQwbNgw8Hg+ZmZn49ttvsXfvXkilUjzwwAP44IMP8OGHH6Jr167YsWMHrl69atE1Lly4gP/973+YOnUqOnXqhKKiIsTHxyMoKAidOnUCUDHDeOLEiXjssccwY8YM06ieESNGmPXvNwV3d/daPyFZY8GCBdixYwemTJmCF154Aenp6Vi5cqWpYqvRiBEjcOPGDbN/zzfffBOdO3eGr68v0tPTTaMsKn/CeOaZZ/DZZ59h3LhxePHFFyEUCrFp0yZcuHCBKsGSevH5fCxevBi5ubnVFofSaBl2/VyEC1fUaNdWALHIPLHLXPlQawy4cEUNoAgzxsrt0vKnxG9H//vf/9C+fXusXr0a69atg1AoRKdOnfDQQw+ZWqpLlizBvXv3TLNOH374Yaxduxbjxo2r9/x+fn7w8/NDfHw8bt++DQ8PDwwePBjbt2839ZOPHz8ee/fuxYoVKzBhwgTI5XI8+eSTLTqBhYSEIDExES+//DLGjh0Lb29vLFiwAK+//rrZfnq93uzBOlDxbGD+/PmmH8pp06bhtddeMz2bAYC+ffsiMTERy5cvx9NPPw2dToewsDDs37+/3qGtxDkplUp89913eOyxx8BxHPh8fo0rAqZkqHExU1Nj0jcSi3jwbytASqYaKRlqRHST1LhfY1BZZkIIaYTKD3KnTJmC//73vzXuxxjDJ98okHZDg46+whr3qSwrR4uwIBGemSS3+QNfmrlLCCENVHX0zqhRo2rdV6E0ICtHC7mbZWlX7s7DjRwtFMr6iw9aixI/IYQ0gLXj9DVa9vfoHcta7wI+B72h4jhbo8RPCCFWasjkLJGQg4AP6PSWJXKdnoHPg10e7lLiJ4QQKzDGEBcXVy3pM8ZQWKLH3QIdCkv01Qr6yd146OgntLjrRlFiQKCf0OKuIWvQqB5CCLECx3F49NFHkZCQgFWrVqFDQDDOppXXOxmL4zj07+6C1OtqqDWGWkf1AEC5xgAGhvu6u9hlJi+N6iGEkAZQq9XQ6IXVJmMJ+BWTsRRKAxhjZpOxNFqGrT8qcOGKGv5tBZDUkPzLNQZk39OhVxcxjeMnhBBHUSqVePfddxEbG2san8/xRNj1k8LqyViPxngAKEJKphocOMjdK/2yKKlo6ffqUvHLwl5lGyjxE0JIHSo/yM3JycHHH38MjuMaPBnLXcrDjLFypGSocerv7qEydcWD3G5BIqrVQwghjlR19M4rr7wCjuPAGMOpS2UAhzr76gFAIuKBA4fTl8rQN1QMjuMgEnKI6CZB31AxVeckhJDmoq4hm42ZjOXp/k/ZcY7jzF43FRrOSQghVdQ3Tr85TcZqCEr8hBBSxYcffljn5KzmNBmrIairhxDSJBy12lRDxMbGIjc3F3PmzKlxRq5xMlbaDQ1krvV31ShKDAgLEtllMlZDUOInhNiVo1ebspRerzeVM5fL5Vi9enWt+zanyVgN0Tx+/RBCWqUSlQFbf1TgiwNFSLuhgUjIQebKg0jIIe2GBlsPKLD1RwVKVLavQGkNpVKJOXPm4IcffrD4mPBOYoSHiHHnng7lmprjN07GCg8RI7yT2FbhNhq1+AkhdtFcVpuqj1KpxPz585Geno6cnBwMHToUbm5u9R7XXCZjNQQlfkKIXTSX1abqUjnpy2QyvP/++xYlfaPmMBmrISjxE0JsrrETnJpC1aRvSWnlmjh6MlZDUOInhNicrSY42Yutkn5ljpqM1RD0cJcQYnPNfYLTr7/+atOk39JQi58QYnPNfYLTuHHjUFJSgqioKKdL+gC1+AkhdtCcVpsyUiqVUKvVACq6ZZ544gmnTPpAM0j869evR3BwMCQSCSIjI3Hs2LFa9505cyY4jqv21aNHjyaMmBBSH+MEJ8YY1LWMcTdqiglOxto7r776qin5OzOHJv7du3dj7ty5WLx4MZKTkzF48GCMHj0aWVlZNe7/wQcfIDs72/R18+ZNeHl54ZFHHmniyAkh9WkuE5wqF1y7evUqcnNz7XKdlsShSy8OGDAAERER2LBhg2lbWFgYJk6ciPj4+HqP379/PyZPnoxr164hMDDQomvS0ouENJ0SlQG7fq57glPlpQltrb4qm87KYQ93NRoNzp49i0WLFpltj4mJwcmTJy06x+eff46RI0danPQJIU3LUROcGGO4fbcEy5a/iYwrt+FOSd+MwxJ/Xl4e9Ho9fH19zbb7+voiJyen3uOzs7Px008/YefOnXXup1arzfr0iouLGxYwIaRBmnKCk7Eg3InzRUg8mgJl6WAIAoZg0P3dodD4ma7t7Bw+nLPqN54xZtF/hi1btkAul2PixIl17hcfH4/ly5c3JkRCiA3Ye4KTsVvpYqYG5eVlKC8rgZCnR+/ekchWuGDrAYVdu5VaEocl/jZt2oDP51dr3efm5lb7FFAVYwybNm3CtGnTIBKJ6tw3Li4O8+bNM70uLi5GQEBAwwMnhDQ71QvCyeAr7wWOxzM9y2sOBeGaC4f92hOJRIiMjERiYqLZ9sTERERHR9d57NGjR3H16lXMmjWr3uuIxWLIZDKzL0JI65KSocaFK2VwE5eZagN5yOVmP+9VC8I5M4d+3pk3bx4+++wzbNq0CampqXj55ZeRlZWF2NhYABWt9enTp1c77vPPP8eAAQMQHh7e1CETQpoZxhiOny9CZmYGzpw+icLCwlr3rVwQzoEDGh3OoX38U6dORX5+PlasWIHs7GyEh4fjwIEDplE62dnZ1cb0FxUVYe/evfjggw8cETIhxEr2XHKRMYbUzCIcOpoGVUkhhHzOtIpWbZq6IFxz5NBx/I5A4/gJaRr2XHKx8uidn4+moVTvDQ56tPeTI8DPBZ4yPvi8ms+tKjegRGXAvMe94Ovl8PEtDuGcd00IsavKI2zAVdTukUoqJm6l3dAg9bq6wSNsjOe+cKUMmZkZUJUUgpN6Qi6Xo0zDx+UsDTzd+egUIIJIUD35N3VBuOaIEj8hxKbsueSi8dzJ6WW4fT0ZKkUehCIh/Pw8oNLw4SblQa9nKCjWAzc16BooqtbyV5QYEBYksmtBuObOee+cEGIXDVly0epztxFALOQgEgkRHRWNDn4uAAC9HuDzOUglHApL9Cgs1psd3xQF4VoCavETQmzGVksu1vRAGIDp3FIXAe677z6Ul5XB1c0NegODp4yPgiI9pBIe+HwOAENuoR7eHnxwHGcqCNeri/0KwrUUlPgJITbT2CUX63ogHOxnQFLybQQF+AMA+Hw+XP9eGJ3P49C5gwhXoTG18jkOKFLqkV+kh6qcgYGhV5eK5wrO3L8PUOInhNiQcclFqcTyJRfL1AwaLavzgfDFzDJ8m3gD5VohYLiBXj2qF1sTCjh07ShCYbEeuYV6FJXoodUDag2za0G4logSPyHEZhq65CKAWh8Ia7Va3Mo4jfJiDTi3cKghhd7AahyuyedxaCMXwNujotunXMvwwhRPBPoJnbpPvyp6uEsIsZmGLrl46662xgfCWq0WSUlJUCgUEAq08G8rRUkZr9pD26o4jkNpOUPXABEl/RpQ4ieE2ExDllzsFybB6dTyag+EKyd94+idwHYu4ADcydPVWXKBRu/UjRI/IcSmrF1yMcBXWO2BMGMMf/zxT9KPioqGTCaDp4wPTxkPBUV6lJQ6bjnHlo76+AkhNiUScng0xgNA3UsuGkfYqMoN1R4IcxyHwMAgqEovYWBUlKm8Cp/HIbidCFduapBbqIdCaajz3PQgt2aU+AkhNmfNkos6PavxgXBAQAD8/f0hEJinKY4DOvoKMHqQG1KvaZpsOcfWhBI/IcQuLF1y0fhA+GJmGTIuX0D3sDCIJRIAqJb0gX9KLtzfR4r7+0jtvpxja0SJnxBiV/UtuchxHHoGA98nZkJVdBdlZSpERUXXmMBremjrrKWVG4MSPyHEbiypxa9UKrH1k9egKugOvnsPdA0NqjXpU8kF26DETwixOUtr8SuVSsyfPx9X0tPh7pGPwYPH4laBBKocLT20tSNK/IQQm7K0Fv+4aD6WLVmI9PR0yGQyJKx+Cx0CAi16IEwah1bgIsSJ2XpZRI2WYeuPilpr8QOAWmPAnXs6FN89g6xzayFzd0FCQgJCQv6pv2PP5RoJtfgJcUr2WhbRmlr8en1vBIQOx7IFU8ySPlD/A2HSOJT4CXEy9loW0ZJa/IwxcBwHiYgHkUiE6AeeRXCw3EZ31jDO+OmCEj8hTsSeyyLWV4tfq9Xijz/+QEhICNq1awe5Ow9ZlWrxNzV7Lgbf3FHiJ8SJNGRZxIhuEovOXVct/soF11JSUuDr4wMBn2eqxd/U7LkYfEtAiZ8QJ2GrZRFrU1st/qpVNgcOHAi+QACdWg8+D03eqrbnp56WovX9KiOE1KgxyyJatH8NtfirJn1jlU3gn1r8lsZjK/ZcDL6loMRPiJMwdsUI+DW3Xo019MvKDVBrDODzAL0BFnfFVK3FX1fSd1S9/IZ+6mlto96pq4cQJ1FbV4zewFBQrMe9Qj2UKgMYq6iAKRQCMiv7t421+C9cUUNTervWpO+o0guNXQy+taDET4iTMHbFpN3QQOZakcQ0OoaMmxoUllQsZSgScuDxAIMBKCw2QK1h+PZoCR4bZdlDTvNa/O3Rtj0P7fw8oWNS5Cl0KC0zABwcVnqhMYvBtybU1UOIk6jaFaM3VCT9gmI9XMQc3KS8vz8VcODzOEhEHDr6CfHXVTV2/VxkUfJTqVRwERnwWIwHosKl8Grjh6xcAVIyNUi7roFGyxDdU4rHHDRapqGLwbe2h7vU4ifEiVTuihGLOBSW6CGVcOBX6vfX6wFVuQFeHnz4egmg1TGLhnYqlUosWLAAnt7tERjxX6Re10Ei4hAWJALHAYwBpeUGnPxLheJSvUOGStb0qacuxtr/Tf0A2t4o8RPiRIxdMYwp8MtpFco1FbNVGQMM7J8uDS8PPjp3EIHP48AXcfUO7TQm/bT0DIjaRyLfpRRB7aXVHqB6Aw4dKmn81JN6XQ21xlDnA97WvGB7gxL/6dOnsWfPHmRlZUGj0Zi9t2/fPpsERgixD3cpDxOHyPDnFQ1KVBWlCvSMgeMAuTsfPp58eMr44PMqrZJVx0NOU9JPS4O0bT8EhI1EYLvqSd+ooRPEbKXypx7/tgJIaoiztdf+tzrx79q1C9OnT0dMTAwSExMRExODK1euICcnB5MmTbJHjIQQG2MAXF148PPmQ8DnYDAAvL/7smtq3db2kLNy0neXyRD94PPIKXKxywQxW7F2MfjW1r8PNODh7ltvvYWEhAT88MMPEIlE+OCDD5CamoopU6agY8eO9oiREGJjxoecekNFC9xFwoNYVHtxspoeclZO+jKZDCveSEBxudRuE8RsybgY/IwxcnQLEkGjZaZPP92CRJgxRo4ZY+WtslwD0IAWf0ZGBsaOHQsAEIvFKC0tBcdxePnllzF8+HAsX77c5kESQmzLFg85s7KycO3atYpFVBIS4CrvCJ2+oMUMlbR0MfjWyOrE7+XlhZKSEgBA+/btkZKSgp49e0KhUEClUtk8QEKI7dniIWf37t3x9ttvQyaTISQkBIUl+hY5VNIZa/9b/Tlm8ODBSExMBABMmTIFL730Ev7zn//gsccew4gRI2weICHEPowPOe/c06FcU3N3i/EhZ3hIxUNOpVKJrKws0/t9+vQxLaJSU62eujiqVg9pQIv/ww8/RHl5OQAgLi4OQqEQx48fx+TJk/H666/bPEBCiH1Y+5BToy7FggULkJOTg9WrVyM4ONjsfDRUsuWgNXcJcXIaLTNb4FxvAPg88wVJjEnf+CC36hq5lc9lXHPXkqGSrbHkcUtgUeIvLi62+ITWJtP169fj3XffRXZ2Nnr06IE1a9Zg8ODBte6vVquxYsUKbN++HTk5OejQoQMWL16Mp59+2qLrUeInpGa1LUFYdfRObUnfyLjISV2fIlrzIictgUVdPXK53OKPY3q93uKL7969G3PnzsX69esxaNAgfPLJJxg9ejQuXbpU69DQKVOm4O7du/j888/RuXNn5ObmQqfTWXxNQkjNanrIaW3SB/4ZKln5U0SZuuJBbrcgUatf1rAlsKjFf/ToUdPfr1+/jkWLFmHmzJmIiooCAPz+++/YunUr4uPjMWPGDIsvPmDAAERERGDDhg2mbWFhYZg4cSLi4+Or7X/w4EE8+uijyMzMhJeXl8XXqYxa/IRYpiFJvypnXMi8JbCoxT9kyBDT31esWIHVq1fjscceM20bP348evbsiY0bN1qc+DUaDc6ePYtFixaZbY+JicHJkydrPOa7775Dv379sGrVKnzxxRdwdXXF+PHjsXLlSri4uNR4jFqthlr9zwo61nRbEeLMeDwe+Hx+g5M+4JxDJVsCq0f1/P777/j444+rbe/Xrx9mz55t8Xny8vKg1+vh6+trtt3X1xc5OTk1HpOZmYnjx49DIpHgm2++QV5eHp577jkUFBRg06ZNNR4THx9Pk8oIaQCpVIpVq1bh3r17CAwMdHQ4xIasfrISEBBQY+L/5JNPEBAQYHUAVT/2McZq/ShoMBjAcRx27NiB/v37Y8yYMVi9ejW2bNmCsrKyGo+Ji4tDUVGR6evmzZtWx0iIs1AqlTh06JDptVQqpaTfClnd4k9ISMC///1vHDp0CAMHDgQAJCUlISMjA3v37rX4PG3atAGfz6/Wus/Nza32KcDI398f7du3h4eHh2lbWFgYGGO4desWunTpUu0YsVgMsbj1VdcjxNaUSiXmz5+P9PR0KJVK/Pvf/3Z0SMROrG7xjxkzBleuXMH48eNRUFCA/Px8TJgwAZcvX8aYMWMsPo9IJEJkZKRpFrBRYmIioqOjazxm0KBBuHPnDpRKpWnb5cuXwePx0KFDB2tvhRDyt8pJXyaToW/fvo4OidiRQydw7d69G9OmTcPHH3+MqKgobNy4EZ9++ikuXryIwMBAxMXF4fbt29i2bRuAiv+cYWFhGDhwIJYvX468vDzMnj0bQ4YMwaeffmrRNWlUDyHmqib9hj7IJS1HgxZiKSwsxOeff47U1FRwHIewsDA89dRTVg+xnDp1KvLz87FixQpkZ2cjPDwcBw4cMPUpZmdnm9UFcXNzQ2JiIl544QX069cP3t7emDJlCt54442G3AYhTo+SvnOyusV/9OhRTJgwATKZDP369QMAnD17FgqFAt99953Z0M/miFr8hFTQ6XR44YUXGjVOn7RMVif+8PBwREdHY8OGDeDzK8bn6vV6PPfcczhx4gRSUlLsEqitUOInzq7ypKqDP32PfXu2ImH1akr6TsTqxO/i4oLz588jNDTUbHt6ejr69OlT67DK5oISP3FWGi3DXxlqnP67jIJODwj4gJ+nAf/qK6cyCk7E6lE9ERERSE1NrbY9NTUVffr0sUVMhBAbK1EZsPVHBbZ8X4BfjmeAx+khc+VBJOSQmcNh6wEFtv6oQImq6ZdBJE3Pooe7Fy5cMP39xRdfxEsvvYSrV6+ajeP/6KOP8Pbbb9snSkJIg2m0DLt+LkJyugq3r59HsSIPV/T3MGDAAACAzJUPtcaAC1fUAIqoVLITsKirh8erKKxU364cx1lVndMRqKuHOJtzaeXY/H0BsjKTUazIg0gkRFRUdLX//+UaA+4W6DBjjBwR3SQOipY0BYta/NeuXbN3HIQQO2CM4fj5ImRmZkBVR9IHAImIBw4cTl8qQ99QMVXRbMUsSvxUq4OQlun23RIkHk2BqriwzqRvJHfn4UaOFgqlgapqtmINmsB1+/ZtnDhxArm5uTAYzB8GvfjiizYJjBDSeGs++AjK0p4QCjlEDaw76QOAgM+hTM2g0TrViqxOx+rEv3nzZsTGxkIkEsHb29vs4yDHcZT4CWlGnprxBFIT0tE9LNyiZ1o6fcVKWfRwt3WzOvEvWbIES5YsQVxcHHg8Wi+TkOamcmnz7qEBeCjGHelZGouOVZQYEBYkgtyNfrZbM6u/uyqVCo8++iglfUIchDGGwhI97hboUFiiNxttp1QqMXfuXJw5cwZAxafwAT1cwBiDWlP3GP1yTcVC6Pd1d6EHu62c1TN3Fy5cCC8vr2pLJrYUNJyTtFS1zbzt6CdE/+4uCPLVYvGrC5GWlgYfHx9s374dQqEQGi3D1h8VuHBFDf+2AkhE1Rtt5RoDsu/p0KuLmMbxOwGrE79er8dDDz2EsrIy9OzZE0Kh0Oz91atX2zRAW6PET1qiEpUBu34uwsVMDcABcjceBHwOOn1F3R2dTo/szN9QcPkLyNwE1QquGY9PyVSDAwe5e6XjSypa+uEhYjwa4wF3KX2ab+2s7uN/6623cOjQIVOtnqoPdwkhtmWceXvhihrt2gogrtJidxEZcDIpGcVlbSBqNwmrXh9ereCau5SHGWPlSMlQ49TfnxjK1BUPcrsFidC/uwvV6nEiVif+1atXY9OmTZg5c6YdwiGEVJWSocbFTE2NSV+r1SIpKQnFCgWEYimCuo1EqcGvxvOIhBwiuknQN1Rsqs4pEnKQu/Go0eZkrP5MJxaLMWjQIHvEQgipgjGGU5fKAA7Vkj4AZGZmQqFQQCQSInrgfXBxccHpS2V1llfhOA6e7nz4egng6c6npO+ErE78L730EtatW2ePWAghVSiUBmTlaGsdXtm1axcEBgaaZuRWnnlLSG2s7uo5deoUfv31V/zwww/o0aNHtYe7+/bts1lwhDg7jZZBpwekkn9a5TqdDnx+RUud43jo1auX6T1bzrytvGALdQm1LlYnfrlcjsmTJ9sjFkJIFSIhBwG/YkYt8E+fvru7O3r37l0tEdti5m19w0bpIXDL16CSDYSQpiF346GjnxBpNzRwERmQlJQEhUIBlaoUZWVdIZVKzfZv7MzbmoaNSiUVwz7TbmiQel1Nwz5bgQYVaSOENA2O49C/uwtSMsoqhmz+/SA3Kiq6WtJv7Mzb+oaN0oItrUeDEv/XX3+Nr776CllZWdBozGuAnDt3ziaBEUIqBPlqkZ35G4rL2kAoliJq4H01LqJinHkb3kncoOvUNWzUSCziwb+tACmZaqRkqGnBlhbK6s9qa9euxVNPPQUfHx8kJyejf//+8Pb2RmZmJkaPHm2PGAlxWkqlEotfXYiCy19ApL+O4C73QaFyQXGpHqpyA4pL9cjK0eJuQUXSfzTGo0Gt8PqGjVZWecEWKyf+k2bC6hb/+vXrsXHjRjz22GPYunUrFi5ciJCQECxZsgQFBQX2iJEQp3X58mVcuXIFMjdXrHp9OEoNfnaZeVvfsNGqaMGWls3qxJ+VlYXo6GgAgIuLC0pKSgAA06ZNw8CBA/Hhhx/aNkJCnFhERARWrFgBPz8/UxkGe8y8rWnYaF1owZaWzequHj8/P+Tn5wOoWJIxKSkJQMW6vPSxj5DGUyqVuHv3rul1dHS0We2dxs68ramsc9Vho/WhBVtaNqtb/MOHD8f333+PiIgIzJo1Cy+//DK+/vprnDlzhsb3E9JISqUS8+fPR2FhIdasWQN/f3+bnbuu8fn3hUnQvq0AV25pIXOtv+uGFmxp2axO/Bs3bjStsxsbGwsvLy8cP34c48aNQ2xsrM0DJMRZGJN+eno6ZDIZysrKbHZuS8bnt/HgQ6czQK0x1PmAlxZsafmsrsff0lE9ftIcVU36VevpN0blhVhqG6qp1hhwK1cHgAEMaO8rpAVbWjGLWvwXLlyw+ISV64YQQupnz6QPWD4+v72PAHfu6eDrzcfdAl2tC7Y0ZtgoaR4sSvx9+vQBx3H1PrzlOA56vd4mgRHiDOyd9K0dny/gc/D2EGBMtBtOp5bTgi2tlEWJ/9q1a/aOgxCnpNPpoNVq7ZL0gYaNz7+Vq8Vjo2SI6Cah6pytlEWJPzAw0N5xEOKU5HI53n//fRQWFiI4ONjm52/M+HzjsFHS+tBYLEKamFKpxG+//WZ6LZfL7ZL0geplnetD4/OdAyV+QpqQUqnEggULsHTpUhw8eLDOfWuaaGUtY1lnS1fkUpQYEOgnpPH5rRyVZSakiRiTflpaGmQyGbp27VrjfrZcCMVY1jn1uprG5xMTSvyENIGqSb+2B7n2WAglvJMY4SFiXLiihn9bQb3j8xta1pm0HA7/PLd+/XoEBwdDIpEgMjISx44dq3XfI0eO/L3OqPlXWlpaE0ZMiHUsTfqVF0Lx9eKjo68QMlc+pBIeZK4Vr/28BLhwRY1dPxdZXCBNJOTwaIwHenUR426BDlk5WpuXdSYti0Utfk9PT4s/+llTmnn37t2YO3cu1q9fj0GDBuGTTz7B6NGjcenSJXTs2LHW44xjno3atm1r8TUJsQVLFyJXq9UWJX3AvguhuEt5mDFWjpQMtV3KOpOWxaLEv2bNGtPf8/Pz8cYbb2DUqFGIiooCAPz+++84dOgQXn/9dasuvnr1asyaNQuzZ882XefQoUPYsGED4uPjaz3Ox8cHcrncqmsRYgvW9r+LRCLcd999uHPnTp1Jv6ELofQNFVvcKBMJOUR0k9ilrDNpWayu1fPvf/8bw4YNw5w5c8y2f/jhh/jll1+wf/9+i86j0WgglUqxZ88eTJo0ybT9pZdewvnz53H06NFqxxw5cgTDhg1DUFAQysvL0b17d7z22msYNmyYxfFTrR7SUDX1v5vKGSgNYIzV2P/OGENhYSG8vLxqPXdhiR7vfpEPkZCzqDpmcakeGi3DgmneNNaeWM3qPv5Dhw7hwQcfrLZ91KhR+OWXXyw+T15eHvR6PXx9fc22+/r6Iicnp8Zj/P39sXHjRuzduxf79u1DaGgoRowYYTYmuiq1Wo3i4mKzL0KsZU3/+7Yf8rB23Qao1WoAFSNr6kr6xvNXfHqwfKKV3gBaCIU0iNWjery9vfHNN99gwYIFZtv3798Pb29vqwOo+hGTMVbrx87Q0FCEhoaaXkdFReHmzZt47733cP/999d4THx8PJYvX251XIRUZmn/e1s5cODwZaiyUlBY8DaWLl1q0flpohVpSlYn/uXLl2PWrFk4cuSIqY8/KSkJBw8exGeffWbxedq0aQM+n1+tdZ+bm1vtU0BdBg4ciO3bt9f6flxcHObNm2d6XVxcjICAAIvPT4il/e9arRbJ5/6ASuUCkVcknnxyqMXXME60SruhoYVQiN1Z/b9m5syZOHnyJORyOfbt24e9e/fCw8MDJ06cwMyZMy0+j0gkQmRkJBITE822JyYmmtb0tURycnKdqxSJxWLIZDKzL0KsYUmhM61Wi6SkJCgUCgg5FcJ6D4eXj+U1rowTrRhjUGvqnmVLE61IYzVoAteAAQOwY8eORl983rx5mDZtGvr164eoqChs3LgRWVlZppW84uLicPv2bWzbtg1AxaifoKAg9OjRAxqNBtu3b8fevXuxd+/eRsdCSG3qK3RWOemLREL0jegDxpNa3f9OE61IU2lQ4s/IyMDmzZuRmZmJNWvWwMfHBwcPHkRAQAB69Ohh8XmmTp2K/Px8rFixAtnZ2QgPD8eBAwdM1UCzs7ORlZVl2l+j0WD+/Pm4ffs2XFxc0KNHD/z4448YM2ZMQ26DEIvU1/9+9uxZU9KPiooG+K6moZLWXufRGA8ARUjJVNNCKMRurB7OefToUYwePRqDBg3Cb7/9htTUVISEhGDVqlU4deoUvv76a3vFahM0nJNYizGGT75RIO2GBh19hdXeL1IocPbcOfTr1w8ymQxZOVqEBYnwzCR5g7piNFpmNtFKbwD4vIbV6iGkJlYn/qioKDzyyCOYN28e3N3d8eeffyIkJASnT5/GxIkTcfv2bXvFahOU+ElDnEsrx9YDCvh5VYzqqTr6jDEDOI6Hco0Bdwt0mDFGbvGs2tpYOjuYEGtZ/XD3r7/+MptwZdS2bVvk5+fbJChCmhtj//udezooSzVISkpCYWGh6X1j0s++p0N4iG36340Lofh6CeDpzqekT2zG6sQvl8uRnZ1dbXtycjLat29vk6AIaW6M/e/dAnn449xV5BULcSY5FaUqHRU6Iy2O1Q93H3/8cbzyyivYs2cPOI6DwWDAiRMnMH/+fEyfPt0eMRLSLHAGFf78dTlUNwGRVyRCuw2Hshzg8xgVOiMtitV9/FqtFjNnzsSuXbvAGINAIIBer8fjjz+OLVu2gM9v3nVDqI+fWKpyH7tWo8LKZQtx+e/KsKtXJ8DLJ5D630mLZHXiN8rMzMS5c+dgMBjQt29fdOnSxdax2QUlflKfqhU41RodLqenQpl/GVJkYvUb/0Vo15qrbBLSEljdx79ixQqoVCqEhITg4YcfxpQpU9ClSxeUlZVhxYoV9oiRkCZTojJg648KfHGgCGk3NBAJOeTdvQ5lcSEEbl3Qoffz+O2SJ0pUlq1hS0hzZHWLn8/nIzs7Gz4+Pmbb8/Pz4ePjA71eb9MAbY1a/KQ2ao0BG78pREqmBu3aCOAmrei+0ev1+PPPP9G5c2eIJW648/fM2Rlj5dSfT1okqx/u1lY9888//6y39CwhzZGxa+eHYyU4l66GSAAoSvRwd+XBx1MATxkfERERpv0bsgIWIc2JxYnfuPwix3Ho2rWrWfLX6/VQKpWmGjuEtBSVF1fJztOB4xiEQiAvrwDFShcoiqXwlPHRKUAEkaDi/3xDV8AipLmwOPGvWbMGjDE8/fTTWL58OTw8PEzviUQiBAUFmco0E9ISVF5cxVvOR04+4CLmUJCXC61GDYOuHCKZBAXFAG5q0DVQBD6vIsnL3Xm4kaOFQmmgFbBIi2Nx4p8xYwYAIDg4GNHR0RAKq9csIaQlqby4isEA6A0GFCvyodGowefx4OPrB5FIAD6fobBEj8JiPdrIK35kBHwOZWpGK2CRFsnqPv4hQ4aY/l5WVgatVmv2Pj0wJS1B1cVVSlUaFCkU0Gp0lZJ+ReOGz+cAMOQW6uHtUVE6gVbAIi2Z1cM5VSoV5syZAx8fH7i5ucHT09Psi5CWoPLiKlqtFmfP/gFteRF4fJFZ0jcSCTkoVQZTC19RYkCgn5BWwCItktX/axcsWIBff/0V69evh1gsxmeffYbly5ejXbt2pgVTCGnuKi9unp+fj2KFAgIUw13mAT6/ejcmjwcwBhgMtAIWafms7ur5/vvvsW3bNgwdOhRPP/00Bg8ejM6dOyMwMBA7duzAE088YY84CbGpyour+Pn5oU/fvnBzkyFbIUJBkR5SCQ+Vq48YDADHAVo9Q36+nlbAIi2a1S3+goICBAcHA6jozy8oKAAA/Otf/8Jvv/1m2+gIsRMBVPCR66FQVszA7dChA+RyGTp3EMHLg48ytcHUtaPTAWVqAxhjKCimCpyk5bM68YeEhOD69esAgO7du+Orr74CUPFJQC6X2zI2QuxCqVRi4cKFSPrlU2g1WrPFzYUCDl07itC1owhydz4MhooZvQYD0D1EjJljPTFjrBzuUurbJy2X1V09Tz31FP78808MGTIEcXFxGDt2LNatWwedTofVq1fbI0bi5Gy5EpVSqcSCBQuQlpYGd1kuIn11yLqnM1vcnM/j0EYugLcHHyWlBuTk69CjkxjPTJRDXMMC6IS0NA2uzmmUlZWFM2fOoFOnTujdu7et4rIbqtXTclStklnxMLbha89WTvoymQwJCQlo6xeEXT/Xvbh5eEhF1w618klr0ejE39JQ4m8ZKpdSAAfI3SolZGVFf7s1CbmmpB8SUlFamRY3J86mQYn/1KlTOHLkCHJzc2EwmJenbe7dPZT4mz+NlmHrjwpcuKJGu7aCGrtX1BqDxVUy60r6ldHi5sRZWN3H/9Zbb+G1115DaGgofH19zX4w6IeE2ELlUgq19amLRTyLq2SWlZWZftHXlvSBfxY3J6S1s7rF7+vri3feeQczZ860U0j2RS3+5o0xhk++USDthgYdfeuvB5WVo0VYkAjPTJLX2fDIzc2FUqmsNekT4kysflrF4/EwaNAge8RCiFkpBUtUrpJZmVKpxOnTp02vfXx8KOkT8jerE//LL7+Mjz76yB6xEGJWSsESAj4HvQFmVTKNffqLFi3CsWPH7BUqIS2W1X388+fPx9ixY9GpUyd07969Wnnmffv22Sw44nwql1KwRNUqmVUf5LZv396e4RLSIlmd+F944QUcPnwYw4YNg7e3Nz3QJTYld+Oho58QaTc0kLnW/6BVUWJAWJAIcjeexaN3CHF2Vif+bdu2Ye/evRg7dqw94iFOjuM49O/ugtTraqg1hjpnylaukllaWkpJnxALWd3H7+XlhU6dOtkjFkIAAOGdxAgPEePOPR3KNYYa9ynXGJB9T4fwEDE6tTNQ0ifEClYn/mXLlmHp0qVQqVT2iIcQiIQcHo3xQK8uYtwt0CErR4viUj1U5QYUl+qRlaPF3YJ/qmTK3F0QGhpKSZ8QC1k9jr9v377IyMgAYwxBQUHVHu6eO3fOpgHaGo3jbzmsKaXAGMO9e/fg4+Pj4KgJaf6s7uOfOHGiHcIgpDqRkENENwn6hoqrlVIoLS3Ftq3bMXPmTAgEAnAcR0mfEAtRkTbS4iiVSsyfPx/p6ekYM2YMFixY4OiQCGlRqM4saVEqJ32ZTIZ///vfjg6JkBbHoq4eLy8vXL58GW3atIGnp2edY/eNSzESYmtVkz49yCWkYSxK/AkJCXB3dzf9nSZtkaZGSZ8Q26E+ftLsMcbw8ssv488//6SkT4gNWN3Hz+fzkZubW217fn4++Hzra5mvX78ewcHBkEgkiIyMtLio1okTJyAQCNCnTx+rr0laFo7jMHPmTPj4+FDSJ8QGrE78tX1AUKvVEIlEVp1r9+7dmDt3LhYvXozk5GQMHjwYo0ePRlZWVp3HFRUVYfr06RgxYoRV1yPNF2MMhSV63C3QobBEX+3/WZ8+fbBjxw5K+oTYgMVdPWvXrgVQUZZ55cqVcHNzM72n1+vx22+/4fr160hOTrb44gMGDEBERAQ2bNhg2hYWFoaJEyciPj6+1uMeffRRdOnSBXw+H/v378f58+ctviZ19TQvtS2o7u/FkHp2D+Y+MxZduwQ7OkxCWhWLJ3AlJCQAqGiZffzxx2bdOiKRCEFBQfj4448tvrBGo8HZs2exaNEis+0xMTE4efJkrcdt3rwZGRkZ2L59O9544416r6NWq6FWq02vi4uLLY6R2FdNC6pLJRzK1VocPHoVKlVXLFh1AtsSAuDhZvVcQ0JILSz+abp27RoAYNiwYdi3bx88PT0bdeG8vDzo9Xr4+vqabff19UVOTk6Nx1y5csW0uIZAYFno8fHxWL58eaNiJbZjXNBcqTJg/9ESpN/QoH2ltXW1Wi3OXjgFlUIBoUgKn8DB+OqXknoXVCeEWM7qZtThw4fNXuv1evz1118IDAxs0C+DqkNDGWM1DhfV6/V4/PHHsXz5cnTt2tXi88fFxWHevHmm18XFxQgICLA6TtI4Vbt0Cor1yM7TwVPGR4nKAIGAg0GvQ1JSEhQKBUQiIaKi7oNI4mrRguqEEMtZnfjnzp2Lnj17YtasWdDr9bj//vvx+++/QyqV4ocffsDQoUMtOk+bNm3A5/Orte5zc3OrfQoAgJKSEpw5cwbJycmYM2cOAMBgMIAxBoFAgJ9//hnDhw+vdpxYLIZYLLb2NokNVe3S8XDlUKZm4PEApcqAy1kaeLhyyL+TjCJT0o82PYPhwOH0pTL0DRXTHBJCbMDqUT179uxB7969AQDff/89rl+/jrS0NNPoHEuJRCJERkYiMTHRbHtiYiKio6Or7S+TyfDXX3/h/Pnzpq/Y2FiEhobi/PnzGDBggLW3QpqARsuw6+ciXLiihq8XHx19hZCIeFBrGFzEPLhJeXAR83A7V4micg8IRWKzpA/UvqA6IaRhrG7x5+fnw8/PDwBw4MABPPLII+jatStmzZplGvljqXnz5mHatGno168foqKisHHjRmRlZSE2NhZARTfN7du3sW3bNvB4PISHh5sd7+PjA4lEUm07aT5SMtS4mKlBu0r9+HoDg17PAHDQ6ytKLbfxdMU9QxuEBQdUG20l4Fd8Qqi8oDohpOGsTvy+vr64dOkS/P39cfDgQaxfvx4AoFKprJ7ANXXqVOTn52PFihXIzs5GeHg4Dhw4gMDAQABAdnZ2vWP6SfPFGMOpS2UAB4hFPOgNDAXFeuTk6VCiqmi983gchAIOLmIObm7uUKr51Z7zVF1QnRDSOFaXbFi2bBnWrFkDf39/qFQqXL58GWKxGJs2bcKnn36K33//3V6x2gSN4286hSV6vPtFPkRCDhIxDxk3NabJWWoNQ1m5FgI+wONXLOYj4HNwkXDo21VittZuVo4WYUEiPDNJTn38hNiA1S3+ZcuWITw8HDdv3sQjjzxienDK5/Orjcknzk2jZdDpAbEIyLipQUGxHlIJB44DSooVMBgk0Bp0kIqEADhodAyGMkCrqzgGMF9QnZI+IbbRoFkxDz/8cLVtM2bMaHQwpHURCTkI+EBBsR6FJcakz5B7NxdajRqcgA+hyBUAwOMq+vp1eoZilR5uUp5pQfVeXcQI70QjswixFYtH9YwZMwZFRUWm12+++SYUCoXpdX5+Prp3727T4EjLJnfjIcBXgOw8HQCYkr5aowafx4OPtyskYh50ekCrY9AbKn4B5BbokZWjMVtQnfr3CbEdixP/oUOHzEofvPPOO2aLruh0OqSnp9s2OtKicRyH7sESqDUMPF6VpO/rB4lECLk7D3I3HoSCisQuFHJQqgwIbifCjDFyzBgrh7uUFoojxJYs7uqp+gzYycr4kwbq1F4IVxceFCVqqDU6U9IXiSoe6HJcxageAV8Pb7kA/t58lGuAqQ+4w89b6ODoCWmdqPIVsStXKQ8dfIQQCDgUwAtCoRDgBNDpAAP7Z2y+t1yAzh1EKFMbADCzUT2EENuyOPFzHFdtVAWNsiB1USqVEIAhpL0Qao0BHdrKkFuoh1JlgJ4xcBwgd+fDx5MPTxkffB6H7DwDwoJEkLtR4ifEXqzq6pk5c6Zp+GZ5eTliY2Ph6loxKqNy/z8hSqUSCxYsAAA8+cxbSL0OuEt58PbgQ6NlMBgA3t+TsowNCBq6SUjTsDjxVx2u+eSTT1bbZ/r06Y2PiLR4xqSflpYGmUwGX1kxwkNkuHBFDf+2Akhq6MahoZuENB2LE//mzZvtGQdpJaom/Yo1cgPh628AUISUTDU4cJC78yDgc9DpGRQlFS19GrpJSNOwumRDS0clG+yn5qT/zxq5Gi1DSoYap/6uya83VEza6ugnRP/uLgjvJKakT0gToMRPbKK+pF+ZcRUujZZBJOQgd+NRnz4hTYiGcxKbUCgUyM3NrTfpAxWjwTzdravkSgixHWrxE5u5efMmtFptnUmfEOJ41OInDaZUKnHt2jX07NkTAGgtY0JaCJolQxpEqVRi/vz5mD9/Ps6ePevocAghVqDET6xmTPrp6emQSCTw9PR0dEiEECtQ4idWqZz0LXmQSwhpfijxE4tR0iekdaDETyyiUqko6RPSSlDiJxYRi8Vo164dJX1CWgEax08sptfrkZubC39/f0eHQghpBGrxk1oplUrs2LHDtNoan8+npE9IK0ATuEiNKtfeKSoqwnPPPefokAghNkItflJN1YJrDz74oKNDIoTYECV+YsaaKpuEkJaJEj8xoaRPiHOgPv5WzJq694wxxMXFUdInxAlQ4m+FNFqGvzLUOP33Slc6PSDg173SFcdxePTRR5GQkIBVq1ZR0iekFaNx/K1MicqAXT8X4WKmBuAAuVultW2VBjDGEB5Ssbatu7R6T59arYZYTIudE9KaUR9/K6LRMuz6uQgXrqjh68VHR18hZK58SCU8yFwrXvt5CXDhihq7fi5CQWEJli5diuzsbNM5KOkT0vpRV08rkpKhxsVMDdq1FUAsqvl3uljEg39bAf68UoZjh7bhZtpvyMnJwccff0zr3hLiJCjxtxKMMZy6VAZwqDXpG/E5Pa5lZkCV7wF3mQyvvPIKJX1CnAgl/lZCoTQgK0cLuVvdSV+r1SIpKQmqYi0Erh2x4nUavUOIs6E+/lZCo2V/j96pveVuTPoKhQJCIYduYT3g375jE0ZJCGkOqMXfSoiEHAR8QKevfZDWxYsXoVAoIBIJ0atPJIQiabVhnYSQ1o9a/K2E3I2Hjn5CKJSGWvfp3r072rRpg6ioaGgNLgj0E9bbNUQIaX0c/lO/fv16BAcHQyKRIDIyEseOHat13+PHj2PQoEHw9vaGi4sLunXrhoSEhCaMtvniOA79u7uAMQa15p/kz9g/fxeJRIiKioJI4gYGhvu6u9BDXUKckEMT/+7duzF37lwsXrwYycnJGDx4MEaPHo2srKwa93d1dcWcOXPw22+/ITU1Fa+99hpee+01bNy4sYkjb57CO4kRHiLGnXs6lGsM0Gq1OHHiBG7cuGHap1xjQPY9HcJDxAjvRGP2CXFGDp25O2DAAERERGDDhg2mbWFhYZg4cSLi4+MtOsfkyZPh6uqKL774wqL9nWXm7p9XyiqGbBbfhUjIw30DoqAs44Gh7pm7hJDWz2E/+RqNBmfPnkVMTIzZ9piYGJw8edKicyQnJ+PkyZMYMmSIPUJskdylPPx7iADFmdugyr8IgcgFXbtHwMD46BYkwowxcswYK6ekT4gTc9ionry8POj1evj6+ppt9/X1RU5OTp3HdujQAffu3YNOp8OyZcswe/bsWvdVq9VQq9Wm18XFxY0LvJlTKpVY/OpC3ExLg7tMhhWvJ8C/fYd6q3MSQpyHw4dzVk1EjLF6k9OxY8egVCqRlJSERYsWoXPnznjsscdq3Dc+Ph7Lly+3WbzNGdXTJ4RYwmGJv02bNuDz+dVa97m5udU+BVQVHBwMAOjZsyfu3r2LZcuW1Zr44+LiMG/ePNPr4uJiBAQENDL65unw4cOU9Akh9XJY4heJRIiMjERiYiImTZpk2p6YmIgJEyZYfB7GmFlXTlVisdhpKk4+9NBDKC4uRlRUFCV9QkitHNrVM2/ePEybNg39+vVDVFQUNm7ciKysLMTGxgKoaK3fvn0b27ZtAwB89NFH6NixI7p16wagYlz/e++9hxdeeMFh9+BoSqUSQqEQYrEYHMfhiSeecHRIhJBmzqGJf+rUqcjPz8eKFSuQnZ2N8PBwHDhwAIGBgQCA7OxsszH9BoMBcXFxuHbtGgQCATp16oS3334bzz77rKNuwaGUSiXmz58PqVSK+Ph4p/lkQwhpHFqBq4UyJv309HTIZDKsW7cOHTtSwTVCSP1oMHcLVDXpJyQkUNInhFiMEn8LU1PSpwe5hBBrOHwcv7NhrGLRc42WWT2pipI+IcQWKPE3EY2W4a8MNU5fKkNWjvbvRVOAjn5C9O/ugvBO4npr4+fm5uL27duU9AkhjUIPd5uAsXDaxUwNwFXUzhfwOej0Fa1/xiwvnHb58mUIBAJK+oSQBqMWv51ptAy7fi7ChStqtGsrqLYQusyVD7XGgAtX1ACKMGOs3Kzlr1QqkZ2djS5dugAAunbt2pThE0JaIXq4a2cpGWpczNTUmPSNxCIe/NsKkJKpRkrGP7OQjbV35s6di0uXLjVVyISQVo4Svx0xxnDqUhnAodakbyQR8cCBw+lLZWCMVTzIXbAAaVdugyduC41eAifrlSOE2Al19diRQmlAVo7W4nVt5e483MjR4trtYix782PczO8NQcA4BIV1x1fHpEi6orD4QTAhhNSGEr8dabQMOj0glViWpAV8DopiDf735gkoVH0hcOOhT6/O8JC5QadnSLuhQep1Na2gRQhpFEr8diQSchDwAZ3esi4aVZkGl67eg7bME0LcQ3T/+8xGHtX3IJgQQixBTUY7krvx0NFPCIXSYNH+dwsYOE4IAbuH6Kj7ahxuWtuDYEIIsRQlfjviOA79u7tUrBmgqTv5l6n1KClj6NBOjvsHDahzjkHVB8GEEGINSvx2Ft5JjPAQMe7c06G8huSv1Wpx+ep13Lyrg0jAoX1bEQQiKcrKDVBrDLUmduODYEs/TRBCiBH18duZSMjh0RgPAEVIyVSDAwe5e8XM3XK1FskXrkKlKkPXoHJIJcG4kaOFWsNgYACPA9ykPPh48uEp44PP+6c/X8DnUKZm0GipxU8IsQ4lfjtjjEGnZxgd5YauHcW4dK0cN+/qoCzVIj09Far8y3DhbqNdu9k4d0UPjmOQSngQcBwMjEFRooeiRA9PGR+dO4ggFFQkf52egc8DPdwlhFiNEr+d1FWUbUgfPnZ/sQbKKylwcxXi/knv40auGF4yhhKVoVIy5yASctDrgYIiPa5Cg64dReDzOChKDAgLElk8R4AQQowo8dtBTUXZpJKKomwXM8vwfWImVPnt4e6WiWdfikdisgva+/BRojKgJEsDvZ6Bz/+nJc/nA1IJD4XFehQW6+Em5YGB4b7uLhaXdCaEECNK/DZWV1E2xhguJJ+BqkgJvnsP/OtfY3E9TwZwWohFPAgEHDzd+Sgo1kMqQbXkDwB38nRwc+GhdxcxwjvRGruEEOtRP4GN1VWUjeM4BAUFQizk0L9PEG7kSXDpmtrUXcPncegUIIKXjI8yNYNSZfh79m/FQ1y9gaGwWI/QQBEejfGg/n1CSINQi9+GLCnK1qFDAPz8/CEQCFB0S4OCYgP8vP95XyTg0DVQhMJiPXIL9VCqDNDrAY6rmLkrFXOYOMSdyjUQQhqMEr8N1VSUTavVIiUlBd3DwiCWSAAAAkHFP7vcjYfsPB3K1AyuLv+ch8/j0EYugLcHHxotg8EA8HhAucYAra5iiCchhDQUZRAbMhZlE/zdN6/VapGUlIRbt27h7Lmz1SZjScQcJCKu1klYHMdBLOLBRcKDWMRDkZIh0E9II3kIIY1CGcSGKhdlMyZ9hUIBkUiI8PCe1Ubg6A2Ap4wPDvWXdCjXGGgkDyHEJijx25CxKFt+kXnSj4qKrrH2jqLEgB4hYvTuUntJB6Ai6Wff0yE8hEbyEEIaj/r4bYjjOPQMRsU4/aLSOpO+sQU/MNwFXTqKwHHVSzro9AyKkor9enUR00geQohNUOK3sZ+/Ww9Vvhx89x6I7BNUa9LPvqdDr7/H4ouEHGaMlSMlQ41Tf8/0LVNXlGToFiSiVbcIITbFMSer61tcXAwPDw8UFRXVWfq4oXJzc/H6snh07v8SbhVIam3B17aKFmMMCmXF+H2RkIPcjUd9+oQQm6LEbwOMMbPkzBiDVgezFrzeAPB5FbV6qAVPCHEkSvyNpFQqsWjRIjz88MMYOnRotfepBU8IaW6oj78RlEol5s+fj/T0dGRnZ2PgwIGQ/D1Jy4jjKurvEEJIc0GJ30rGFrxCocSbby5HRno6ZDIZ3n333WpJnxBCmiNK/BaqXF8/81Y5LqWmobR0CEQdwvHM08PQISDI0SESQohFKPFboHJ9fb1BjxsZf6G0uBBCoQTBXYfj52QJ7hQpahylQwghzQ1lqXpUrq/v68WHoew2ShQ5EAkMiB7YB12DZPDzEuDCFTV2/VxEa+ASQpo9avHXo2p9/ZCQEGg0GrRv3940Kkgs4sG/rQApmWqkZKgR0Y36+gkhzRe1+OtgrK9vMOgh/PtXJMdxCAsLqzYUVCLigQOH05fKqlXhJISQ5oQSfx0USgMyb5XjesZfOHfuLAyGuitoyt15uJGjrbXMMiGENAcOT/zr169HcHAwJBIJIiMjcezYsVr33bdvHx544AG0bdsWMpkMUVFROHTokN1iUyiUuJSahpLiQuTn56OsrKzO/QV8DnoDqJ+fENKsOTTx7969G3PnzsXixYuRnJyMwYMHY/To0cjKyqpx/99++w0PPPAADhw4gLNnz2LYsGEYN24ckpOTbR6bUqnEW2+tQKmyGEKhBFFR0XB1da3zGJ2+orAalWIghDRnDi3ZMGDAAERERGDDhg2mbWFhYZg4cSLi4+MtOkePHj0wdepULFmyxKL9LSnZoFQqsWDBAqSlpUHUYRqCw4aja1D95R2ycrQICxLhmUlyKstACGm2HNbi12g0OHv2LGJiYsy2x8TE4OTJkxadw2AwoKSkBF5eXrXuo1arUVxcbPZVl8pJXyaT4cWnh0EskdAKWYSQVsNhiT8vLw96vR6+vr5m2319fZGTk2PROd5//32UlpZiypQpte4THx8PDw8P01dAQECd58zKysK1a9cgk8mQkJCAB/4VhPAQWiGLENJ6OHwcf9XWcdUSx7X58ssvsWzZMnz77bfw8fGpdb+4uDjMmzfP9Lq4uLjO5N+9e3e8/fbbkMlkCAkJAQA8GuMBgFbIIoS0Dg5L/G3atAGfz6/Wus/Nza32KaCq3bt3Y9asWdizZw9GjhxZ575isRhicd2tcKVSiYKCAnTs2BEA0KdPH7P33aU8WiGLENJqOCzxi0QiREZGIjExEZMmTTJtT0xMxIQJE2o97ssvv8TTTz+NL7/8EmPHjm10HMY+/ZycHKxevRrBwcE1xyvkENFNgr6hYqqvTwhp0Rza1TNv3jxMmzYN/fr1Q1RUFDZu3IisrCzExsYCqOimuX37NrZt2wagIulPnz4dH3zwAQYOHGj6tODi4gIPDw+rr1/1Qa4lA5yovj4hpKVzaOKfOnUq8vPzsWLFCmRnZyM8PBwHDhxAYGAgACA7O9tsTP8nn3wCnU6H559/Hs8//7xp+4wZM7Blyxarrq1UKrFy5UpT0k9ISDD16RNCSGvmtEsvPv3008jMzKSkTwhxOg4v2eAoly9fpqRPCHFKDh/O2dSMH3AkEglWrFiBNm3a1DupixBCmit3d3erB5g4XVfPrVu36p3ERQghLUVd5Wdq43SJ32Aw4M6dO3X+ljRO8rp586bV/6DNRUu/h5YeP9Dy76Glxw+0/HuwJP6GtPidrquHx+OhQ4cOFu0rk8la5H+Wylr6PbT0+IGWfw8tPX6g5d+DreN32oe7hBDirCjxE0KIk6HEXwOxWIylS5fWW+OnOWvp99DS4wda/j209PiBln8P9orf6R7uEkKIs6MWPyGEOBlK/IQQ4mQo8RNCiJNx2sS/fv16BAcHQyKRIDIyEseOHat133379uGBBx5A27ZtIZPJEBUVhUOHDjVhtNVZE//x48cxaNAgeHt7w8XFBd26dUNCQkITRlsza+6hshMnTkAgEFRbMKepWRP/kSNHwHFcta+0tLQmjLg6a78HarUaixcvRmBgIMRiMTp16oRNmzY1UbTVWRP/zJkza/we9OjRowkjrs7a78GOHTvQu3dvSKVS+Pv746mnnkJ+fr51F2VOaNeuXUwoFLJPP/2UXbp0ib300kvM1dWV3bhxo8b9X3rpJfbOO++wU6dOscuXL7O4uDgmFArZuXPnmjjyCtbGf+7cObZz506WkpLCrl27xr744gsmlUrZJ5980sSR/8PaezBSKBQsJCSExcTEsN69ezdNsDWwNv7Dhw8zACw9PZ1lZ2ebvnQ6XRNH/o+GfA/Gjx/PBgwYwBITE9m1a9fYH3/8wU6cONGEUf/D2vgVCoXZv/3NmzeZl5cXW7p0adMGXom193Ds2DHG4/HYBx98wDIzM9mxY8dYjx492MSJE626rlMm/v79+7PY2Fizbd26dWOLFi2y+Bzdu3dny5cvt3VoFrFF/JMmTWJPPvmkrUOzWEPvYerUqey1115jS5cudWjitzZ+Y+IvLCxsgugsY+09/PTTT8zDw4Pl5+c3RXj1auzPwTfffMM4jmPXr1+3R3gWsfYe3n33XRYSEmK2be3ataxDhw5WXdfpuno0Gg3Onj2LmJgYs+0xMTE4efKkRecwGAwoKSmBl5eXPUKsky3iT05OxsmTJzFkyBB7hFivht7D5s2bkZGRgaVLl9o7xDo15nvQt29f+Pv7Y8SIETh8+LA9w6xTQ+7hu+++Q79+/bBq1Sq0b98eXbt2xfz581FWVtYUIZuxxc/B559/jpEjR5oWfmpqDbmH6Oho3Lp1CwcOHABjDHfv3sXXX39t9TK0TlerJy8vD3q9vtqC7r6+vtUWfq/N+++/j9LSUkyZMsUeIdapMfF36NAB9+7dg06nw7JlyzB79mx7hlqrhtzDlStXsGjRIhw7dgwCgWP/2zYkfn9/f2zcuBGRkZFQq9X44osvMGLECBw5cgT3339/U4RtpiH3kJmZiePHj0MikeCbb75BXl4ennvuORQUFDR5P39jf46zs7Px008/YefOnfYKsV4NuYfo6Gjs2LEDU6dORXl5OXQ6HcaPH49169ZZdW2nS/xGVavZMcYsqnD35ZdfYtmyZfj222/h4+Njr/Dq1ZD4jx07BqVSiaSkJCxatAidO3fGY489Zs8w62TpPej1ejz++ONYvnw5unbt2lTh1cua70FoaChCQ0NNr6OionDz5k289957Dkn8Rtbcg8FgAMdx2LFjh2mN69WrV+Phhx/GRx99BBcXF7vHW1VDf463bNkCuVyOiRMn2ikyy1lzD5cuXcKLL76IJUuWYNSoUcjOzsaCBQsQGxuLzz//3OJrOl3ib9OmDfh8frXfqLm5udV+81a1e/duzJo1C3v27MHIkSPtGWatGhN/cHAwAKBnz564e/culi1b5pDEb+09lJSU4MyZM0hOTsacOXMAVCQhxhgEAgF+/vlnDB8+vEliBxr3Pahs4MCB2L59u63Ds0hD7sHf3x/t27c3JX0ACAsLA2MMt27dQpcuXewac2WN+R4wxrBp0yZMmzYNIpHInmHWqSH3EB8fj0GDBmHBggUAgF69esHV1RWDBw/GG2+8AX9/f4uu7XR9/CKRCJGRkUhMTDTbnpiYiOjo6FqP+/LLLzFz5kzs3LnT6v40W2po/FUxxqBWq20dnkWsvQeZTIa//voL58+fN33FxsYiNDQU58+fx4ABA5oqdAC2+x4kJydb/INqaw25h0GDBuHOnTtQKpWmbZcvX7aq1LmtNOZ7cPToUVy9ehWzZs2yZ4j1asg9qFQq8HjmaZvP5wP4Z3VBi1j1KLiVMA6h+vzzz9mlS5fY3Llzmaurq+np/qJFi9i0adNM++/cuZMJBAL20UcfmQ0HUygULSL+Dz/8kH333Xfs8uXL7PLly2zTpk1MJpOxxYsXOyR+xqy/h6ocParH2vgTEhLYN998wy5fvsxSUlLYokWLGAC2d+9eR92C1fdQUlLCOnTowB5++GF28eJFdvToUdalSxc2e/bsFhG/0ZNPPskGDBjQ1OHWyNp72Lx5MxMIBGz9+vUsIyODHT9+nPXr14/179/fqus6ZeJnjLGPPvqIBQYGMpFIxCIiItjRo0dN782YMYMNGTLE9HrIkCEMQLWvGTNmNH3gf7Mm/rVr17IePXowqVTKZDIZ69u3L1u/fj3T6/UOiPwf1txDVY5O/IxZF/8777zDOnXqxCQSCfP09GT/+te/2I8//uiAqM1Z+z1ITU1lI0eOZC4uLqxDhw5s3rx5TKVSNXHU/7A2foVCwVxcXNjGjRubONLaWXsPa9euZd27d2cuLi7M39+fPfHEE+zWrVtWXZOqcxJCiJNxuj5+QghxdpT4CSHEyVDiJ4QQJ0OJnxBCnAwlfkIIcTKU+AkhxMlQ4ieEECdDiZ8QQpwMJX5CGmDo0KGYO3dus71OUFAQ1qxZY/N4SOtAiZ+0GDWtl1r5a+bMmY4OkZAWwenKMpOWKzs72/T33bt3Y8mSJUhPTzdtq1oPXqvVQigUNll8hLQU1OInLYafn5/py8PDAxzHmV6Xl5dDLpfjq6++wtChQyGRSLB9+3YsW7YMffr0MTvPmjVrEBQUZLZt8+bNCAsLg0QiQbdu3bB+/XqrYtu+fTv69esHd3d3+Pn54fHHH0dubq7p/SNHjoDjOBw6dAh9+/aFi4sLhg8fjtzcXPz0008ICwuDTCbDY489BpVKZXZunU6HOXPmQC6Xw9vbG6+99ppZCd7c3FyMGzcOLi4uCA4Oxo4dO6rFt3r1avTs2ROurq4ICAjAc889Z1ZemTgXSvykVXnllVfw4osvIjU1FaNGjbLomE8//RSLFy/Gm2++idTUVLz11lt4/fXXsXXrVouvq9FosHLlSvz555/Yv38/rl27VmPX07Jly/Dhhx/i5MmTuHnzJqZMmYI1a9Zg586d+PHHH5GYmFhtGb2tW7dCIBDgjz/+wNq1a5GQkIDPPvvM9P7MmTNx/fp1/Prrr/j666+xfv16s186AMDj8bB27VqkpKRg69at+PXXX7Fw4UKL74+0Mo2uKUqIA2zevJl5eHiYXl+7do0BYGvWrDHbr6byzQkJCSwwMND0OiAggO3cudNsn5UrV7KoqKharz9kyBD20ksv1fr+qVOnGABWUlLCGGPs8OHDDAD75ZdfTPvEx8czACwjI8O07dlnn2WjRo0yu05YWBgzGAymba+88goLCwtjjDGWnp7OALCkpCTT+6mpqQwAS0hIqDW+r776inl7e9f6PmndqMVPWpV+/fpZtf+9e/dw8+ZNzJo1C25ubqavN954AxkZGRafJzk5GRMmTEBgYCDc3d0xdOhQAEBWVpbZfr169TL93dfXF1KpFCEhIWbbqrbWBw4caLYGa1RUFK5cuQK9Xo/U1FQIBAKz++7WrRvkcrnZOQ4fPowHHngA7du3h7u7O6ZPn478/HyUlpZafI+k9aCHu6RVcXV1NXvN4/GqLUmn1WpNfzcYDAAqunuqLuFoXNKuPqWlpYiJiUFMTAy2b9+Otm3bIisrC6NGjYJGozHbt/LDZo7jqj185jjOFJMljPdW1wLjN27cwJgxYxAbG4uVK1fCy8sLx48fx6xZs8z+LYjzoMRPWrW2bdsiJycHjDFTcjx//rzpfV9fX7Rv3x6ZmZl44oknGnSNtLQ05OXl4e2330ZAQAAA4MyZM42O3SgpKana6y5duoDP5yMsLAw6nQ5nzpxB//79AQDp6elQKBSm/c+cOQOdTof333/ftF7rV199ZbP4SMtDiZ+0akOHDsW9e/ewatUqPPzwwzh48CB++uknyGQy0z7Lli3Diy++CJlMhtGjR0OtVuPMmTMoLCzEvHnz6r1Gx44dIRKJsG7dOsTGxiIlJQUrV6602T3cvHkT8+bNw7PPPotz585h3bp1eP/99wEAoaGhePDBB/Gf//wHGzduhEAgwNy5c82Gtnbq1Ak6nQ7r1q3DuHHjcOLECXz88cc2i4+0PNTHT1q1sLAwrF+/Hh999BF69+6NU6dOYf78+Wb7zJ49G5999hm2bNmCnj17YsiQIdiyZQuCg4Mtukbbtm2xZcsW7NmzB927d8fbb7+N9957z2b3MH36dJSVlaF///54/vnn8cILL+CZZ54xvb9582YEBARgyJAhmDx5Mp555hn4+PiY3u/Tpw9Wr16Nd955B+Hh4dixYwfi4+NtFh9peWjNXUIIcTLU4ieEECdDiZ8QQpwMJX5CCHEylPgJIcTJUOInhBAnQ4mfEEKcDCV+QghxMpT4CSHEyVDiJ4QQJ0OJnxBCnAwlfkIIcTKU+AkhxMn8P1VaMs+VXp11AAAAAElFTkSuQmCC", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -58,11 +56,11 @@ ], "source": [ "# fit and recover\n", - "model = EMModel(all_data=all_data, \n", - " fit_func=fit, \n", + "model = EMModel(all_data=None, \n", + " fit_func=bayes_fit, \n", " param_names=[\"lambda\"], \n", " param_xform=[norm2alpha], \n", - " simulate_func=simulate\n", + " simulate_func=bayes_sim\n", " )\n", "\n", "recovery = model.recover(true_lambda, \n", diff --git a/examples/glm.ipynb b/examples/glm.ipynb index cc07d12..12d7e32 100644 --- a/examples/glm.ipynb +++ b/examples/glm.ipynb @@ -49,7 +49,7 @@ "data": { "image/png": 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", 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", 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PPsvrr7/e38PZKxLkhRCiHbtn0Xzuc5/r5xHtHQnyQgixm8GWJtkZCfJCCNHKUArwIEFeCCGytm7dyt133w0MjQAPkkIphBA53nzzTdauXctpp53W30PpEYNmJr948WIOPfRQCgoKKC8v55RTTuGTTz7p72EJIYaA1o3aDzvssCET4GEQBfkXX3yR888/n9dff51nnnkG27aZP38+zc3N/T00IcQgdu+99/Ltb3+bzZs39/dQesWgKWvw1FNP5fx+5513Ul5ezjvvvMMXvvCFfhqVEGIwu/fee7njjjsAb5lm7Nix/TyinjdogvzuIpEIAKWlpR1ek0wmSSaT2d8bGxt7fVxCiMGhdYA/55xz+MpXvtLPI+odg2a5pjWtNRdddBFHHHEEM2fO7PC6xYsXU1RUlP2prKzsw1EKIQaq3QP8UMii6cigzK45//zz+cc//sG///3vTr9etTeTr6yslOwaIYax4RTgYRAu11x44YU88cQTvPTSS3tcPwsEAgQCgT4amRBioEulUrz88svA8AjwMIhm8lprLrzwQh577DFeeOEFJk+e3O3nkDx5IUQ0GuXf//43J5xwQn8PpU8MmiB/3nnncd999/HXv/6VqVOnZm8vKioiFAp16TkkyAsxPH3yySc5cWM4GTQbr7fddhuRSISjjjqK/fbbL/vz4IMP9vfQhBAD2JIlSzj33HN59NFH+3so/WLQrMkPki8cQogBpHWxsXg83s+j6R+DZiYvhBDdMdSqSe4tCfJCiCFHAvwuEuSFEEOKBPhcEuSFEEOSBHjPoEmh7AmSQinE8LBs2TJmzJjR38MYEGQmL4QY9J5++mlisVj2dwnwu0iQF0IMakuWLGHx4sVcdtll2LaN1pr6qMP2Opv6qDPs068HTZ68EGL40FrT0OSSSmssv6I430Ap1ea61puscw79LB+stnnr4ygbt6WxHfCZUDXKz2HTQ8ysDmD52z7HUCdr8kKIASOZcnltaZx3lifYVuug1K5Avf8Ei4mjLfLDBsX5Bvfdd182wH9r0bk4RfNZtjYFCorzDXymwna8DwutNTMnBjhtfhEF4eG1gCEzeSFEv0ulNW8si3P/PyN8usNGa7D8inBQ4fcpVm9K8/9ebSIvaDC2wkeycQ0fvvoqKD+Lvr2IVMF8PlyVZPRIHwErN4gX5pkkUy4frkoCERaeVDysZvQS5IUQ/Soac1ny/xp4/p0YzQlNXkjhNw1sV7OzwWlZdlHkhxWxpMuq9Q007GyCsi9z0JQ8qg+YxV+ei7Yb4DMClsF+I30sXZtk6Zoks6cF+/hd9p/h9b1FCDGgpNKaB56O8MayBGkHSgoMQgED04REQuNq8PsUrtak0pAfMtBGEJ9hM2lcCbZVzT1PNpBIuUDnNa6CloFC8dbH8WG1GSszeSFEv1m6xptZAxgKTNNbRkmmNMm0i89UGAqUUiRTLkHLxGeajBl/ACPKLLbU2GytdQgFFA1Rl/ywQXmJSUmhiWm0XZIpLjDYsC1NQ5NLSYHZp++1v0iQF0L0C601b34cx3EhntS71sm19zt4gR/ATqfQyiSeNAgHFTsjmsbmFKBAgeNqlNI0RB0aog4lBSbVlRaWLzfQ+0xFPKlJpYfPTF6Wa4QQ/aKhyWXjtjT5YYXWYLREI8eFtK0xWiJ8KpUimUqRTiZJpV2iMYdUWhOwDPJCBqbyHuOt2xuEAoq6Roc1m1I4bm4wtx2NaTCsNl4lyAsh+kUqrbEdsHwGSoHrLauTWS5XaleAB/BbfrSGVNpLq/SZYBota/YuZMK5aXpZOfVRh/pGJ+c1G6Iu40b5Kc4fPqFv+LxTIcSAYvkVPhOU0uSHjewSSubMU+sAH7AsfD5/Npj7fcqb+SsIWCrnQwJ2re3X1O868ZpIuWg0h04PtXuwaqiSIC+E6BfF+QZVo/xEmjXlJd4mqNOynOK6KdJpL2oHLAvLsnAcjcZbpw8FVDZQaw3hoCKRdHFaTdwtv6Ip5p2aTaRctu6wmTkxwMzqQF+/1X4lQV4I0S+UUhw2PYTWmnBQUVJgEktomppiJGMRAKyWAO/qXcs4lk8RsLwA7zgapWByZYARxT7iSTcb2N2Wtf1N222219kcONk78Tqc1uNBsmuEEP1oZnWAmRMDfLgqydgKLxzVNQaxAmm0YYDyk7Y1tgs+w/vJC3mzeMfRxBKa0kKTkSXeT32jQ029Q1PMJW1rtIYp4/x84eC8YVu7RoK8EKLfWH7FafOLgAhL1yYJBRRjK3w0hAqJxjXNcZe0AwEfTBjjp7HZpbHZxXa8pZzSQi9VMpMTX1bsY0SRSSqt2VxjM6XK4sKvFWMYw3fRQoK8EKJfFYQN/I1Pkp+AsVNPZNP2NAG/olxDeYnJyBIfTTGXLTttHEcRaXIpCBvsV+Zr99CTUgqNxueDzx8cHtYBHiTICyH62b333svdd94BwP9+cQqnzZ/dpsRwpvRwc8zlsRca+WRDivyw0e6p1swm64GTh98ma3skyAsh+s29997LHXd4Af6cc87hsMMObfc6pbyN2ZICk0Unl/DA097yjkJRXNCqrHDUS5Mcrpus7ZF68kKIfrF7gO9O0+1UWrN0TZI3P46zcVsax/UORg33BiHtkSAvhOhz+xLgW+tqB6nhTJZrhBA9oisBV2vN0uUb+fP//RXMAs5e9PW9DvCwaxlHdEyCvBBin6TSmo/WJHmrZemkvd6qQKtrQkycew3pVIKm8HjeXZGQ5ZVeJMs1Qoi9Fo25PPB0pNPeqlMqLQBWrE9g+kzpv9rHZCYvhNgrma5OnfVWjSUcXng3RjwWx236mM/NPYRQKJRzzXDuv9oX5GNTCLFXlq5JsmxtqtPeqrGEprk5QXMsTjyl2L59e5trdu+/KnqWBHkhRLdlujp5pX7bDyNaaz5Zu5N4vBnQjKiYxLhx49q9drj2X+0LEuSFEN2W6erUWfONFSvXUteQAJ2iID+IL1DUadu91v1XRc+RIC+E6LZMVyef2f76+apVq1i9ag0oRWFBAYUFBWid29hjdz5T4bgMq/6rfUE2XoUQ3Zbp6mQ7bQOyY9ts3rwZcMnPyyMvPw9Xe3XfO6sVNhz7r/YFmckLIbot09WpvaUV0+fj8MMP54CZ+1MxsoBUWpNKey3+Ogvgw7H/al+Qv00hRLe17uqUTHmBPtrYmL0/GAwyfvw4yktMXA2u67X466jkwHDtv9oXJMgLIfZKpqvTlh02y1es4cUXX2xZptklFFSYhtdYOxzsOMAP1/6rfUHW5IUQeyXT1WnZstdYvaEZrP1oiKYpTbg5ZX+Pmh0GYOWmFApXSgP3MQnyQoi99sRj9/PBs3dDaDIHHH4G+aWVRGMupgHTxls5tWtalwaOJ3WbayTA9w4J8kKIvbJkyRJuv/12AM45fS6nn354p1UoZ08LMmtqQEoD9zEJ8kKIHF0pGZwT4FvVg99T2V8pDdz3JMgLIYBdJYPfXBZj7adpUjZYPpg4xs9nZoSZMdEilvSyabbXxoF9a/gh+oaUGhZCEI25LPl/Dby1PEk05uScTDVaDjGFQ4qiPB9+n3cQKqDqOHneeFlPH+AkyAsxzKXSmj89Xs8L78ZwXC+oW36FUhBPaqLNLo4LoLF8ivJSk9JCE60BhdSCH+DkfxUhhrn3Pknw0nsxbFuTF1Tkh70Ux6aYS7TZxdUALlq7pGyXhqjD5hqbWFIzotDHh6uSPPB0RGrODFAS5IUYxrTWPPV6E7GEV3bANBVaQ2OzSzyp8SbrDtp1QHtrOI4LQUtRF3HYVJOmYoQpteAHMAnyQgxj9VGHlRtS+HzeqVSAZGpXqQLtujjeWg2maaCUQSoNoAkHDeobHWIJLbXgBzAJ8kIMYzsbHGJJjeVrCQWa7AzecVxc1wG8AG8YJgagNTgazJZMyJp6h+J8qQU/UEkKpRCDWFdy2rv4TIBXzz1ta1zHzmbYZAJ85qrWf7D83tq9q7XUgh+gJMgLMQhlctrfaikT4DXwgKpR/m6VCSgrNgkHFc1xl1DQm6UDmIaBjYsydgV48GK7oXbN4g2lcLQmbSO14AcoCfJCDDLRmMsDT0dYtjYFyqvtHg56Bb9WbEixfH2SGRMCnDA3H8uvOp3hlxSYTKm0eGt5AseBzCWGaeLzGy2ZNbksP5iGd2GmGUg05nJAdUBqwQ9AEuSFGERSac0DT0f4cFWS0SN9bZpo54UMttfZPPNmMy++F2O/ET4sv+pwhq+U4vjD8/l4XZLa+hiFeT78Ph+ptIvPVKTsXVHecb0PgfzQrg+MTDMQ00RqwQ9Q3frYvfXWW/niF7/I1772NZ577rmc+3bu3MnEiRN7dHC7e+mllzj55JMZPXo0Sikef/zxXn09IQaapWuSLFubajfAp23Nyo0p1m9J4zia5rjG1d4SyooNKe5+soG7/9FANJa7OTprapCRoY3E403U1DWhdSY3XmMoL7g7DiggHIBgwAvkjuM1A1EgteAHsC4H+d/+9rdccsklTJs2jUAgwIknnsjixYuz9zuOw4YNG3plkBnNzc0cdNBB3Hzzzb36OkIMRFpr3vw4Doo2Ad5xNas3p6iLOIQCBoX5Jj7Ty3cvCBtUVfgZVdr+waWHHlzCsheug8bXKSkwCFgmpgFp25u5GwqUAX4fhIMGjguJpKa+0cHvU3xmZkhqwQ9gXV6u+cMf/sCf/vQnTj/9dADOO+88TjnlFOLxONdcc02vDbC1E044gRNOOKFPXkuIgaahyWXjtnS76971jQ71jQ7hoJHdFM1kvqTSmoClCFgG+430ZQ8uzZ4W5N577+WOO+4AYNF/FHLAoRN5Y1mcVRtTfLrDq/se8ENhvkna1sQSmljSRQFVo3ycfnwRh00PSYAfwLoc5NetW8fcuXOzvx9++OE899xzHHPMMaTTab7//e/3xvj2STKZJJncdQqvsVUPSiEGm1RaYzu0aaOntaamPpPPvut2w8gsqey6LWgZ2YNLy976C3/+sxfgvWqS3gQuU/O9Oeay5tM0H69LsGm7je1otIZRZT4OmRbiszODbb5RiIGny0G+rKyMTZs2MX78+OxtM2bM4LnnnuPoo4/m008/7Y3x7ZPFixdz9dVX9/cwhOgRlt+r/mg7uSkvqbSmKea2mU27LRulxm5xuLjA4J2lW1j10kNA23LBmZrvJQUmYyv8fGFWSBp9DGJd/hg+4ogjeOSRR9rcPn36dJ599lmeeuqpHh1YT7j88suJRCLZn02bNvX3kITYa8X5BlWj/G1OlbouuNrLWW8tk/mye/D3mYrCohHMOGBWl+rBZ4J+RamPkgJTAvwg0+WZ/GWXXcY777zT7n0zZszg+eef5y9/+UuPDawnBAIBAgHZ8RdDg1KKw6aHWL4+STLlZpdKDMPbHHUztX8Bp2W2X17SNijbjsbyG/zoih8zskT++xjquhzkDzzwQA488MAO758xYwYzZszI/n7eeedxzTXXUFZWtm8jFEJkzawOMHNigA9XJdlvpI+g5c3U80OKuqiLoRSu1iRSmhGFJiWFuxbpV61aheO4WPnjmTjWwjRNtNYyMx/ieu0w1L333svFF1/co0G+qamJ1atXZ39ft24d77//PqWlpVRVVfXY6wgxUFl+xWnzi4AIS9cmMyVniMZcmlp+lPI2Z0sKd63GfrJyFSvXbAd/GXmFSWxX8at767pdBkEMPr3WGaqgoIAPPvigRw9IvfDCC8ybN6/N7QsXLuSuu+7a4+OlM5QYKlJpL2f+vqcifLrDQWuN7Whc18tlV0pn19LdxGbWbk6ArxgrGKaiLMSkMX5c7aVlaq2lu9MQNqjKGhx11FFSr1qIFsvXJTEUzJ4awGcqHA0bt6VoiLqAwjRh07ZmkskwWAWEAiZjRoWZNNbC7/Nm7YV5JsmUy4erkkCEhScVy4x+iBlUQV4I4cmUNxhT7s/JVZ86LkB9o0NNvcP2HVGSyRQYYfKDaQ6YUkRJoZktLpbR3iEpMXTIdzMhBpmOyhtorVv6tBqMLEjQVPM22FH8PqgYWciIorYBPqP1ISn5tjy0yExeiEEi0yBkR73Nms0pivJa0iVdTV2jw456h6aYi9aglMWIMXOIJQ3ywlZOeYOOFBfs6u5UUmB2eJ0YXHotyH/zm9+UzU0hesDuDUJiCc2GbWkK8wzKS6EuYhNpOSDl94HPp3BdcFQYW2viSZdQ0Mgpb9Aen6mIJ7V0dxpi9irI19fXc8cdd7B8+XKUUkybNo2zzjqL0tLS7DW33XZbjw1SiKFqT+372msQ4jO9LkyRJocd9TZaQ2mhQSwWJdoQo6KiAp/fwDQMkimHlA0k9xy4bUdLd6chqNtB/sUXX+TLX/4yhYWFHHLIIQD87ne/49prr+WJJ57gyCOP7PFBCjHUdKV9H9BugxCtNcUFJjvqHVzXa7pd25AgGWsEFE3NMQoL8jEM8PuU17PV1TTFvRl9RxqiLvuPt6S70xDT7Tz5mTNnMnfuXG677TbMlpJ3juNw3nnn8corr7B06dJeGWhPkDx5MRC0Pzv32ve1zlvff0KAvzwbpaLUzAnwqbRmR73D8vVJr26Na2M7gHbw+018Pj9+nyIUUDiOJtLsErAUFaU+9h9vtXvCNZFy2V5ns/DEYsmuGWK6HeRDoRDvv/8+U6dOzbn9k08+4eCDDyYej/foAHuSBHnR31Jpzd3/aOiwfR9AMuXyaU0aV3sz8XH7WW02VzMfCK6r0a6XF28YmmDABFR2hg8QslS2Q9TsqW3LAydSLlt32Bw4OSB58kNQt7+XzZ49m+XLl7e5ffny5Rx88ME9MSYhhqzO2vdlBCyDshIfn+6wUQpStmblhhSrNqZoiDoYhrdJ6rrerB9loAwFareMGO2VGi4qMCguMEimNJtrbBqbHWIJl8Zmh43b0myv8wK8dHcamrq0Jv/hhx9m//xf//Vf/Pd//zerV6/ms5/9LACvv/46t9xyC7/4xS96Z5RCDAGdte/bnc/0ygfvaLBpbHZpaHLJCyhQCq0haTugNWiNMgzAQGuvSYhhgOU3CAW8+vNNMc3oMpP8kMHkSouaept40ttknTbekto1Q1yXlmsMw9vx39OlSikcx+mxwfU0Wa4R/ak+6nD9/9Vi+RWFee3noWeWZbbttNmy08ZxvTLCpgkKhcZrnJ22vQbb4OIzvfRIDRTlG+QFDUyDTNVhmmIupqGYd0iY755SRKRZSwOQYaRLM/l169b19jiEGPI6at+Xkba9Ztz1jV7BMVNB2gUXvI3VllV206DlwBNo7TXWVspbe3UcF8PwZvwZpgmJpMv+EywMw6CkoNffqhhAuhTkx40b19vjEGLI8/u8JZumuJPNR8/Moh3XC/B1EaeliiQ0x+3sYxWg8ZZnHFcBCqUygd77sXzeDN91d/V6dRxNMqXJCxlMHG31/ZsW/U7KGgjRyzI58W8ui7Nlp0005hIOGOSHDcpLvMYe9Y0O9Y1egDcMiDS53iGmFho3u1yqWtZhMrP5DMdLsiHtaByX7MnVwjyDUSN85EsZ4WFJgrwQvWj3nPiRxSaxhFdfoCHq0BB1KC4wWtbXM0srmniidQ0Cjda7Zu/ZxXa8QG8arYK9BscGTCguMCkvMWmKuVSPkUNOw5UEeSF6WKZUQVPM5fEXo3yyIcWYlpRJx9U0J3R2WQY0tQ0OKVtTmGegXU005pDO5i/oXTN45QX61hRegM+cbC0vNZlSaWGaCsuvSKY1zQmXQ6eHZIN1mJIgL0QP2b1UQV2jw9adNiWFJtGYi8+nMA3FpLEWq/E2WMErKNYU1zTFNCnbJZ1dptFo7a3BKNVqmabl3syk3tVkPwhGFvsIh7wF+daHnDJlEsTwI0FeiB6w+7JMUZ5X0dEwvBTGlRtTlBSa2a5MU6qsbHOPhqiDqyGW8HLXIbOh6jVwzczgdcvtSrPrz4qW9Xew/BAKQGOzQ0PURaPlkJPoWpAvKSnp8le9urq6fRqQEINNKq3bFBJLplySKU0oYGD5FY4DdRGH1aSYUmVhGoqyYh8lBSbL1ydpjLloFywLnKSXG68xcDOdultkjqp42Tbe/zENL3OnKN8gZStcreWQk8jqUpC/8cYbs3+ura3lZz/7GccddxyHH344AK+99hr//Oc/+Z//+Z9eGaQQA1l7pQpc1wvIRsvM3DS9BtuZLJqyYh9aa7bXe7PuvKDylmtSLqZh4GYyZ7TKpkm2llme1xpKCgwqSg0WHFPMtPGWHHISObpdoOyrX/0q8+bN44ILLsi5/eabb+Zf//oXjz/+eE+Or0fJiVfR07TW/OGxBlZsSFFV4c/enky5fLAq2VJiYFewbYq5FOV7WS876h221dmkbI0BpG2vdLBhaJThx1Deh4WryQn0Xo69d7ttw6gRJl+YFZbiYqJd3c6p+uc//8nxxx/f5vbjjjuOf/3rXz0yKCEGi4Yml43b0m3SEy2/Ij9stOmy5PcpttfZfLIhRV3UwXE0PgNsx8Z10nhr797GqeuSc+Bp13OA1go77QX8OfsHZd1ddKjbQX7EiBE89thjbW5//PHHGTFiRI8MSojBIlOqwGfultqoFOUlmX4LXoTWGprjXheooKUIB7wlFdu2cWwHnCYsn4OhjGzuu9tq9m603GY73glZy1IcOiPI975SQoEcdBId6HZ2zdVXX83ZZ5/NCy+8kF2Tf/3113nqqae4/fbbe3yAQgxklt+r9Gg7bVc9SwpNSgpM6hodwkGv5EAyrb32fS0fCul0GttxQacoKgwRDAVpiHoHoQrzDdDeB4njai/gaxhZ4qO0yES7mlOPLNxjRUsxvHX7X8eiRYt49dVXKS4u5tFHH+WRRx6hqKiIV155hUWLFvXCEIUYuIrzDapG+Wloatsl2zQU1ZUWpYUm8YTXocl1vdsdV1PX0Ixt26AdivINiou9JRfT9D4QIlGXWNLFcb1vCpZPMarMx7TxflxHc8AkyX8Xe9btjdfBTDZeRW94d0WCu59sYFRp+41AHFezvdbm43VJbAfyQgYBv8IgwbYtGwkWjGVESR5KQWOzSyLpeideNfh85GzA5ocVY0b6Oagl/12WacSe7NVhqDVr1nDnnXeydu1abrzxRsrLy3nqqaeorKxkxowZPT1GIQa0mdUBZk4M8OGqJPuN9BHcLdCbhsoWHqsoMplcZeE3FZY/SNM4i807fdQ2ONiuV+fdOxmrsV0vi8ZxvJx4yw+mgopSk2/ML5KCY6JLuv2v5MUXX+SAAw7gjTfe4JFHHqGpqQnwukddeeWVPT5AIQY6y684bX4RB04OsL3OZuO2dJsWe7WNDkX5Jn69E+XECVjepmtBfh6TxlqEg4pEctcGbeZEq8+AoKUYXebjsJlhZk0LsjPisHJjqn/ftBg0uh3kL7vsMn72s5/xzDPPYFm76lPPmzeP1157rUcHJ8RAprWmPuqwvc7GdjRnnljEwhO9A0mptCYa8zJppo23OOs/iijxb2Ddhm28+tprpFO7grTPhIClCAUMAn6vjZ/teBk1pUU+po0PMKM6QEHIIBQwUSje+ji+x05tQsBeLNd89NFH3HfffW1uHzlyJLW1tT0yKCEGst0LkXkplFA1ys9h00N8+z+KiCVzW+zdd999LHv9VSj7MmMrJ+JvNUFKpTXNcU1eyNtcTdmaeFJTPcbPfmW+NidXiwsMNmxL09DkUlLQfhtBITK6HeSLi4vZunUrEyZMyLn9vffeY8yYMT02MCEGot0LkRXnG4SDCtvRrNiQYvn6JDMnepuimQC8ZMkSL71Y+TloSh6OVUki5WbX7jObqj7lZd0kU5qyIpOKEW0DPHiZNvGWDxEh9qTbQf7000/nRz/6EQ8//DBKKVzX5ZVXXuHiiy/mzDPP7I0xCjEgtFeIrLXCPJNkyuXDVUkgwsKTinn4ofuy50fOOXshXzr1cB54OsLStUkUiuICA9fVuK5X9900FKWFJtWVXhGz9tiOzrYPFGJPup1CmU6nWbRoEQ888ABaa3w+H47jcPrpp3PXXXdhmgP366OkUIp98e6KBPc8GaGi1Oz0AFIi5bK9zmb/spU8eKeXjHDOOedwxhlnAN6HxdI1Sd5stdzz6Y40aVszaaxFSaHZYYAH2Lgtzf7jLb57arEUIRN71O2ZvN/vZ8mSJVx77bW8++67uK7LrFmzmDx5cm+MT4gBQWvNmx/HQbHHE6ZBy0ChSFtTmTJ1Kl/4/OezAR68GfjsaUFmTQ3Q0ORtzq5Yn+KR5yMUhI1OA3wi5dWJl05Poqu6HeSvueYaLr74YiZOnMjEiROzt8fjca6//nquuOKKHh2gEANBR4XIOlJcYLC1TvOzn9/IyNJgu9copbLr9iUFJis3JjvMtQfp9CT2TreXa0zTZOvWrZSXl+fcXltbS3l5OY7jdPDI/ifLNWJvba+z+dW9tS1pjipbQnj32fSqVavw+XxU7DeOaMzlotNLqSjt2lwqs6nber3eZ3qbuplOT5lNXTnpKrqq2zN5rXW7XxM/+OADSktLe2RQQgwUWmtq6h1eXxpjU00a2/ZOsCoF+WGD8hIzu4a+atUqVqxYAYAVKiEQzO/W5mhB2GDhScU56/XxpLfJKp2exN7qcpDPtABUSjFlypScQO84Dk1NTZx77rm9Mkgh+loy5fLa0jivfxTng1XJbIlg8IKxz69oiHr9WUsKTFRqE6tWegF+2rRpOOQxbpS/y8s7Ge2t10unJ7Evuhzkb7zxRrTWnHXWWVx99dUUFRVl77Msi/Hjx2dLDwsxWKXSmteXxrj3/0XYstMmlfbKDAQs71RqPKGJxl2CtkFhvoHWmk9rmok3JgGDadOmUDmumu119j5tjrZerxdiX3Q5yC9cuBCACRMmMHfuXPx+/x4eIcTgUhtx+N1Dtbz5cYJUalfTDkN5pX9tNIbhBf1EyoUmwI0Sb2oEXxGVE2ZSOa5SNkfFgNLtNfkjjzwy++d4PE46nc65XzY0xWBUG3G44g81rP00jeN4LfYcF2gpFua4LZ2Z8H4AmhMOdjIFKIKhMEmCbKtNc+BkaccnBo5uB/lYLMall17KQw891G6tmoGcXSNEe1Jpza1/qWP91jSZs3ym6RUJM1p6rIJXfiAT6MNBg0RKY1CA3xciGAzi8ym+Oq+Iww8ISYAXA0a387AuueQSnnvuOW699VYCgQC33347V199NaNHj+aee+7pjTEK0as+Wp3gozVJ/OauQE47icWZ5h2ZmX1xgUFRYYA500uYPsFizEg/08ZbEuDFgNLtmfzf/vY37rnnHo466ijOOussPv/5zzNp0iTGjRvHkiVLck72CTHQaa15+f04yZQmaBmkbNdbjukgTmvXJe26mIYPtIkCLJ8i7YDP1BLgxYDT7Zl8XV1dtgJlYWEhdXV1ABxxxBG89NJLPTs6IXpZQ5PLpu1pTFNhtJQT0Hgx3lDeJmuG6zq4roN2wXYcXO0t5RgGNETdvUqZFKK3dftf5MSJE1m/fj0A06dP56GHHgK8GX5xcXFPjk2IbmndxKM+6nSpqUYqrdF4bfVA4/cpXNdLYTRNoCXQu66D43jNug3DwDRNUrYmP2zgai31ZMSA1e3lmm9/+9t88MEHHHnkkVx++eWcdNJJ/O53v8O2bX7zm9/0xhiF6NSemnjMmGi1aeKRCcaWXxG0FKGgQSzhEgookmmNq72TpoYC23HR7q4Ar5SBz1AYLfXkt+10JGVSDFjdrl2zu40bN/L2229TXV3NQQcd1FPj6hVSu2boaa+JR6beS32jQ1NcE/DT0vRa5QT/mdUB/D74w2MNvL08QUPUIWgpojGXZFqjgFTawdXeB4L3weD9ORSA/JBJRanJAZOknowYuLo9k99dVVUVVVVVPTEWIbqlsyYeaVvzadKmvtEmZUNpoUH1WAutadPB6bDpIT5em8RxDRqbXMIBRSKlSdugtQLtoAyD1qubhqE4bEaQeXPypJ6MGND2Ksi/+eabvPDCC9TU1OC2fI3NkCUb0VeWrkmybG0qG+C19pZk0o5m3ZY0kahDXsgkD01z3KUp5lKcb1JRYqK1znZw+sb8Ig6YFODdT5LoPE1NnYPjgM8HrqtwXRMw0HiHpMaN8mE7Gr8PZkyUlEkxsHU7yP/85z/npz/9KVOnTqWioiJno0k2nURfad3Ew+dT7Giw2VHv0NSy1BJLuAT8ilTaARSxpGb5+hThoMJQivywQXG+wYerE8yZFuK0+UVAhNc+iqM1BK2WE6+GV5TPNCAUUBTkGTQ2a2xH8+xbMeqjLicfUSCzeTFgdTvI33TTTfz5z39m0aJFvTAcIbom08QjL6hYuSFFfdQ7aW35FbbtbTOl0ppYAlAaU4F2NaZhoBTZCpKmAa98EGPW1ABnnljEa++sJRkzKC4pxjS9+kzhgIHtahJJTXPc27wNmgaO6/Dx2iS1EZsDqoOyLi8GpG4HecMw+NznPtcbYxGiy1Jpb2lmZ8Qh2uwSDipMU+E43gzcNMBxWg6uatDKu800FD6f92HgOJrGZpfXl8X5Wn0hTzz+COvWB8FNM3LMeKqqxgOwfmuKpkZNOGjQuoVxKGDgujCi0JfTvFtm9GIg6fa04wc/+AG33HJLb4ylS2699VYmTJhAMBhkzpw5vPzyy/02FtF/LL8innRpiO4K8LDr8JLW4LRUkDQNrxyBl/++6zlMUxEOGkSbXX5/97Pcd/9DoEyqq8czdcpEQkGD5oRLfdRtE+CBbEVKn6nYb6SPpWuTLF2T7KO/ASG6ptsz+YsvvpiTTjqJ6upqpk+f3qbk8KOPPtpjg9vdgw8+yPe//31uvfVWPve5z/GHP/yBE044gY8//lgyfIaZojyF44Ltakxz11xFKW+93nYADarlrkyesLHbtEYpSKVSvPDGZtBpqirHMLZyrPeYlq5QQJsAD7s+NAzDa+6tULz1cZxZUwOyPyUGjG7P5C+88EKef/55pkyZwogRIygqKsr56U2/+c1vOPvssznnnHPYf//9ufHGG6msrOS2227r1dcVA0+kWXtLLy3LMhmm4W3Eap07a8/8cbdkMCKNMZLNO8BfxlcWLOLAGVXsbHCymTpNMbfD5ZdU2jvxmrm/uMBgw7Y0DU1uu9cL0R+6PZO/5557eOSRRzjppJN6YzwdSqVSvPPOO1x22WU5t8+fP59XX3213cckk0mSyV1fnxsbG3t1jKLvpNLeGnlxgdmyJm9kyxAELUUsoXcFdu3NtjPLKxm2o0nbNugUBWXTWB8vprk+zdadaZrjLqWFJo6r8Zlt50KO4z1ReYmZnbX7TEW85WStEANFt2fypaWlVFdX98ZYOrVz504cx6GioiLn9oqKCrZt29buYxYvXpzzLaOysrIvhir6gOVX+H0wttxPaZFJPOnlwafSGtP01uId1wvwpgF+n3daNTO7tx1vlh4O5RMqHIsywwQsxegyk6ICkx31Dms+TRNLuNhO7szccTSxhKakwGvinWE7XikE2XgVA0m3g/xVV13FlVdeSSwW643x7NHua51a6w7XPy+//HIikUj2Z9OmTX0xRNEHivMNqkb5aYq7TKmymFJlUVxgehusLZ2dvGwab9nGcXRLIxCXHXVJaiMOsYQmltTYrq9llq8JBQ1mTAiw30gfhvJOvTZEXdK2m12+iSc1pYUm1ZUWprHr355UohQDUbeXa37729+yZs0aKioqGD9+fJuN13fffbfHBtdaWVkZpmm2mbXX1NS0md1nBAIBAgEpGjVYaa1paHLbLSymlOKw6SGWr09i25qyYh8jikxSaY3rQn3UYd2WNKYBiZQmmfbW8OsaUqTSNj6fi2H6vVTLlsybVZvSlERcJo31PjTqi03WfppiZ8SlOaYJBhTFBSblJd4MvnWAT6RcqUQpBqRuB/lTTjmlF4axZ5ZlMWfOHJ555hlOPfXU7O3PPPMMX/7yl/tlTKJ37KmqZOZ06YyJFpPGWixbk2TUCB8FeUa2fo1lKSJNLjsbbAwDRpf5aIhESCUdcJsxA2WAt5wTtBTFBQauq6iLOKwmxZQqi7JiHyUFJm9+HMdxNVPH+SnMM9sE8UTKlebdYsDa5yqUfenBBx/kW9/6Fr///e85/PDD+eMf/8if/vQnli1bxrhx4/b4eKlCOfB1VlWyoclFa83+4wPMmBhg2dokaz9NsXm7TXPCJWgZ7FdmUlpo4mrY2eBQU2+jgHQySn2jDW6S/IICUk4ou0lblG9kG4Y4DsSTbjbIA9Q1OqzfkqIo38DvMyguaDWmqDeDzxQ7kxOvYqDZ5yqUfenrX/86tbW1XHPNNWzdupWZM2fy5JNPdinAi4Gvs6qSAIV5Jk0xl2ffaub5t5upGOGjtNBk6niLukaHrTtt1m1JU1PvMLbcz8zqALOmFPHc88/x9DthsMrJKygkGArjxl3CIYNwUOXMzDP58DX1DiOKvFl70FLsV+bn+MPzWLUpxcZtaeJJb5N12ngr59uFEANNl2bypaWlrFy5krKyMkpKSjpdc8y0AxyIZCY/sL27IsE9T0aoKDXbBHgAx9Ws3JhiZ72NMhTTxu2abYO3ht8Uc9my02bmRIvvnlrCI395gD/9+QHY72yqqiqZUl2F7Wg+XpfENFW7gTmzrn/Q5AABy6Cx2SGV1lzyrREU5xsd7hMIMRB1aSZ/ww03UFBQkP2z/KMWPa11Vcn2AjxAfaNDfaNDfthLmWw92wZvM7Ygz2ScX7H607RXhnj0aJQZYEzlOCZXjyUU9EoSF+SZNESddoO8oRSO1tmDUw1Rl/3HW9mAXlLQzvFXIQaoLgX5hQsXZv8s1SdFb8hUlewo/XD3EgOWX2Xz4gNWbqAOtiox8N1Tj+S3FRO57/kgdssBJqUU5SVekPdSK3Mf72qdLVcgWTNisOv2LpFpmtTU1LS5vba2FrO9Ah9CdEEqrVuyaDouIdC6xEDm9KrjapIpl3jCJZnyNmbXr19PyEpnSwzMmFZJ1Sh/TrmBkkKTkgKTWEJnT6+2fq1Mg+6tO2xmTpSsGTF4dXvjtaMl/GQyiWVZ+zwgMTxZfq//qu20/+/LbTm96muZTTuu1+JvzWZvE9RtqThpJyPUbt9MwNrOlP0PYke9TXG+lc2pT6ZcApaBaSiqKy3YlKlF762xa71rDDX1XoPu0+YXyaaqGLS6HOR/+9vfAt5X3dtvv538/PzsfY7j8NJLLzFt2rSeH6EYFjInWFdsSFGY1/YboWF4QdzVGtdVRFpSF1WzJmAZ+JQi0hilKaYhPA3X72Pjdpc/PR6heqyfWVOC7D/OYtnaFPuN9BG0DCyfYso4i/pGh5p6h8Zmh0RSU5hnMGtqkMNnStaMGPy6HORvuOEGwJvJ//73v89ZmrEsi/Hjx/P73/++50cohoXWJ1gzs+3WLL/Xsq8h6rX4s21NUYFBXsi7rqEhQlPMBeXH5/OhtQ+0JhRQ2cbdUyotpo23WLkphUJl890tvyIvqAj4TSZXWnz16ELGlvtkDV4MCV0O8uvWrQNg3rx5PProo5SUlPTaoMTwNLM6wMyJAT5clczOtjMym6Xb62wSSS94h4NeEG5oiBBpcsEI4DcVfsuX7QplO5qqCj/JlMuK9SlmVAc4fX4R761M5OS77z8hIPnuYkjq9pr8888/n/O74zh89NFHjBs3TgK/2CeWX2Ubai9dm8yZbduOpinu4rpe5ktB2DvEFG1sIhK1wcxDGQauMkikwG96QX57nc2IIi/vfr+RPpavT3LY9BD/eWqx5LuLYaHb2TXf//73ueOOOwAvwH/hC19g9uzZVFZW8sILL/T0+MQw4nV00hx/eD5fmVfA1HEWqbQm2pIqWT3GorLCT0WpQTINjc0OcTuI8uWjDANDGdBSWhgFyZRme51Dc9zbSG2dWglQUmBSUerVp5EAL4aqbs/kH374Yb75zW8C8Le//Y3169ezYsUK7rnnHn7yk5/wyiuv9PggxdDWUUGyseUmRxwUZvRIH8UFBgE/3HC/zX5lPuIJl082pkjbYBje/pBpeo26TdPrBOW43nOv25Ji+sQApqFyujfJoSYxHHQ7yNfW1jJq1CgAnnzySRYsWMCUKVM4++yzsxk4QnRVewXJAhbURRxeeDdFMhUjL2QwttzPmJE+muMONdu34PcHMY0iSgsVjc0uygCf0XY2bpoQaXapb3QoK/ZJ9yYx7HR7uaaiooKPP/4Yx3F46qmn+OIXvwhALBaTw1CiW1oXJKsoNamq8BMMGGzebvPpDhvXhVDAIJZw2VZns/bTFBu2RNmwTbFmQwTH9soSKLWrh2trrquxfAaG8nLeM8tB0r1JDCfdnsl/+9vf5mtf+xr77bcfSimOPfZYAN544w3JkxfdsnRN0qsv01Jx0nE1azalqGt0CAdVttyA32cSi7uQ3E5z3VYITcQXLCYY8jo6+X3Ka/vXasritkzUQwGFYZAtgdC6Do0Qw0G3g/xVV13FzJkz2bRpEwsWLMh2XjJNs02TbSFaa93pye+DN5bFcgqS1Tc61EdzAzx4Sy7xeJzaxiZI11I0YiJNKR+plEvAbxIKKJJpjas1hlK4LadWg5ZBwFI4DjhaE09qqUMjhp1B1TRkX0mp4f7R3saq1rBlZ5qyYpOx5X4MBcvXp2iIOuSFFK7rpUCiNY3RKNHGOCjFpNE2leMm8OoHXo/h/LCB3wdNMU3K1ii8nq4By6Awz8AwvNdP25oRRSZzpgVZeFKxLNeIYaPL31lPPPFEIpFI9vfrrruOhoaG7O+1tbVMnz69RwcnBr9ozOXufzTwf09GWLEhheVXFOYZ+EyINrts3GazckOK5rhLtNlBa6+0784Ghx31DttqHaJxC3yFmIFi0uYY4gmXsiID01QUhA209hp7+Eyv/IHlV4SCCld7G6yNzS5KweypQalDI4adLs/kTdNk69atlJeXA1BYWMj777/PxIkTAdi+fTujR4/GcZzeG+0+kpl830qlNXf/o6HdTk/JlMsHq5JoNLYNeSHFzgYnW8Pdcb3Zvga09m40lEFBnsI0vIDeHHeZNTVEKJCZ+Wua45odDV7pA+/x3j/vr84r5NSjCiTAi2Gny2vyu38WDKNVHrGXdt9Yba11LZpQQLGj3iHteCdV3ZYAr5RXlAwML/gr7768oCIa8wL/tro04/ezCAW95w8HoazYJJXWxJMuO+odZk0NSIAXw9ag6vEqBo89dXpq3bgjldY4bkupYAcc1wU0PqNVSq4Cv29X3XkvDdJg7Eg/2+vsNiUQMg22Z0+TJRoxvHU5yCul2mQkSIaC6MieOj1BpnGHweYaG9jVBMT7kugF68y/MZ/pNRSxbU0s4eL3K4ryTcqKfZz0uXzeWp6QBttCtKNbyzWLFi3KpkwmEgnOPfdc8vLyAK9piBAZmRl3plJke0xDUVlhsWWnN5vXuGRWAb3g7jXxyD6D9m5PpDRlxSajy3xsrknzjeMKmT0tKAXHhGhHl4N86z6vQLZ+TWtnnnnmvo9IDAl76vSUsSsMO2hXAwpleBXGFKCMljo0DiRcnT38VDXKj8/08uNTaS0NtoXoQJeD/J133tmb4xBDzJ46PemW9MYdEYdE0sZ1HXBT+Kwgft+uFn+ZbJvMp0HQUgQDBgG/F+ClRIEQnZONV9ErOur05LiaukYvB74p5tLYkhuPMgkG/PgtH2nbm637zF3lCQAcR5O2YWSJgeVXbK9zpESBEHsgQV70mpnVAWZMCPDuJwnKS3z4TNi4PU1D1Jue+0yvBIEyDNAarQLe7F2TLVHQurCkq7wPieICg2RaShQI0RUS5MU+aV2PpvWGZ6aUQSLlNf34tCZOyvZWXfJCCr8JqbS3HBMOGqiWJh92y1k6bzbvBXrwAr/jeh8MAb/B1h02B04OMLM60H9vXohBQIK82CsdNfqoGuVnZnWApasTrNiQBgXVY/xsrTXYtC2NqyHSZOPaKSrKAoDPK0ngUzQ2uSRSbkswB9vedWJVAT7Dy49vaHI4eHJA8t+F6AIJ8qLb2mv0EQ56ee3L1yV5/u1mXA0HVAfID5tordmy0yE/bGCnmohEmsAIkE65lBQVE2lysCxFUYFBMKWINLsYaPx+RbolV97vUziuZkyZj7P+o4gDJgUlwAvRBRLkRbe0bvQxeqQPy69oirskUy4+nyIcNEjb3oGmTdttpowzsG3t1XNPNhFtrAegqCAfzHyCliKClyJpmhAMKAzDwHY0+48LELAAFImUS23E4ayTi5mzf6g//wqEGFQkyItuydSjGVniY1ONzdadNvGEi5fh7v0fn6EoyjeojzrUNzrkBQ2amptpjjYCUFxcTFFRIU0xb3mmpMBsaRRiYLZUklSOwvJ76ZKJlEt9o8vBU4IcMCnYn29fiEFHgrzoskw9mpSteX9lgqa4F9xNw6s7o11vMzWNxna8oF1T70ByA81NJihFcVExRUVFgJff3hzXTJ9ggfKahoBXmAygOeGyo8FBozlQ1uCF2CsS5EWXNTS5rP00zafb08SSGtNsqTfTkhGTmc0rBSkb3LiLzwd2pBbcfMIFFRQV5WWfz1AKR3sHmqZUWdQ3OtTUO+yot8kLGWitpQaNEPtIgrzoEq01O+ptNtekaU545QUy6Y6KXeUJXMjWm7EdiCc0h86axaZPa6mPh3AcnW3t52rtlRM2vDo2ZcU+8kKKgKX4ylEFzJ4WlBo0QuwjCfKiU6m05sPVCf79QYy1m9Nsr/NOqLqOF5wzh5W0htYtBnTLvD6e8grDT6muYOWGTJNuME0vl764wMzO0BMpl207vfTIzx8clpm7ED1AgrzoUG3E4da/1PHRmiTJFCh0TiB3XW/m3pZGt8zSXVexemOK6dUhqist2JSiPurgao3raoryDKIxN1v/XdbehehZEuRFu2ojDlf8oYYNW20CliIv5NVy3zPd0jVsV5BuiLqs2ZRiyjiLKeMsttfabNiaJhwyMAxvRi9r70L0Dgnyoo1UWnPrX+rYsM2mMN/IBl1XG0BnPXx3NfxQmXxKvA3ZnQ0O4VAa5X0f4NjPhDlhrteST+q/C9F7JMiLNj5aneCjNUksX24ZX1+nxR51q4Yf0Homn0xDynapqbP5wqwwn5kRlhm7EH1EgrzIobXm5ffjJFOavJABLYXBMhurhtGqxvuuR3UY4A0DSgoN4gmNwsuaqRjh76N3I4SQIC9yNDS5bNqexjQgbWua45p0y1q81rkbr7vbPcCDd0DK8mmMkEFTwmXp2pQEeSH6kHRbEDlSaU3a0STSmsZml1TaxVtVb4nu7QZ51W6Az1yeTHkfAArF0jWJlo1ZIURfkJm8yKGAuoiD43jLMo7O7c60S24GTXsBPnNLPKmxXJeifINttTYNTa70YxWij0iQH8baa/ixaXuaRFJ7Qb7DCbduOdWqdxWawQvqmYcYyrtL45189fugrNiHq72USSFE35AgPwx11PCjssLHlh020bi7xwAPtDd5zwZ37yCU9//bDhTmmeSHFLYjjbeF6EsS5IeZzhp+LFubYtWmFGm7o0e3n0Wj2DWhbx3gdctEP2ApJoy1qI9I420h+poE+WFk94YfASs32Cql+Xhd699b16PpOE3S7/NSJR23pdRBS4D3+SDgh5ElJj5DGm8L0R8kyA8jmYYf7QV4gB31uadZlfKWXxxXZzNivACdG6QzAd40dt1j+RUFIUXShpICk207HWm8LUQ/kO/Nw0Sm4QeKdgO81pqG6G4lC1qWW0xDoXAwlcZnKny7JcYELAOfqXBcUAbkhb0loKaEVys+mXal8JgQ/URm8sNEQ5PLxm3pDtfDU2lNIpV7W+vlGZ8v9wCToXZl34woMigtNEkkNfVRh8Zml3QaCvIMPjMjxBEHSRkDIfqLBPlhIpXW2A6Eg+0HWtf1ll18ZqYZiFcR3tVeHmTO+aVWa/UVpYo504Js2m4TCirywwYVpT5mVntLM+UlpqzBC9GPJMgPE5ZftQTw9nMjvQYgipCliMadljx4lVOnJpsH3+opjpqdx3dPLWmTby+BXYiBQdbkh4nifIOqUX4amtpv82H5vVl42k6gnTSgMv8vp72f0dKuD8jWt0m3bK5WlPooKZCZuxADyaAJ8tdddx1z584lHA5TXFzc38MZdJRSHDY9hNaaZKptoFdKkWreRjwWBzeRmwdv7PrR2lvaMQ2YNt5i1eY0S9ck+/bNCCG6bNAE+VQqxYIFC/je977X30MZtGZWB5g5McCWHTaJ3QL9qlWr2LRuKThNGH6vmUdRvoHfx676ZNpbsw8FoKrCR9UoPwrFWx/HpeiYEAPUoFmTv/rqqwG46667+ncgg5jlV5w2vwiIsHRtEoWiuMCgob6WFSs3gVVB2YhCEo7Xls80oLTIxHE1rgO2qzGVoqTQpLrSwjS8x2/YlpaiY0IMUIMmyO+NZDJJMrlrKaGxsbEfRzMwFIQNFp5UzNI1Sd5sqV1jhUoYOWoM+5VqvjR/Av/4dxSUorHZpSnmglaYJhQVmJSXmJQUmpiGt5TjMxXxpJaiY0IMUEM6yC9evDj7DUDsYvkVs6cFOXiKRaTZC9B+3whKCkwamlyefasZy68YM9JHKq2z6ZWWX7XZVLUd78CT5MALMTD165r8VVddhVKq05+33357r5//8ssvJxKJZH82bdrUg6Mf3JYsWcLPf/5zCsNQUeqjtNCHUionC0cpRcAyCAUNAlb7aZENUZdxo/xSdEyIAapfZ/IXXHABp512WqfXjB8/fq+fPxAIEAhIrZTdLVmyhNtvvx2AefPm8bnPfS57XyYLZ/n6JMmU224JhIxEypWiY0IMcP0a5MvKyigrK+vPIQw7rQP8OeeckxPgMzJZOB+uSrLfSB/BdgJ9IuWydYctRceEGOAGzZr8xo0bqaurY+PGjTiOw/vvvw/ApEmTyM/P79/BDRK7B/gzzjij3es6ysLxmV7d+YaoN4OXomNCDHxKD5IE50WLFnH33Xe3uf3555/nqKOO6tJzNDY2UlRURCQSobCwsIdHOLB1NcC3lkrrnCycTDnhqlF+DpsekqJjQgwCgybI94ShEOTb68uaWQ/v6L6tW7eycOFC0ul0lwN8V19TCDGwSZAfJDrqy1o1ys+sKUE08P7KRJv7MjPuDz94h9WrV+9xo1sIMbRIkB8E2uvLmlkfr4041NR5TVlHlvooKzJb3ZfCMExmTvTWzgvCkuYoxHAj/9UPcK37slaUmlRV+CnMMwkHDfJCBomUd5gpldYkk5q8kEE4aLB9y1pWL/s3hYEUH65K8sDTETmVKsQwJEF+gOusL2t9o0N9o0N+2CQ/bFAf9X5ftWoVK1asIJFI0NCwg/1G+li6NinVIoUYhiTID2Cd9WXVWlPT0njbNME0vY3QT9buZMWKFQBMnTqN0WPGoV1wbHhzWUyqRQoxzAyaPPnhqLO+rKm0pinm5qQwppJNRKMJUAEqx0/F9o/ig1VJtAbH1dQ3Oew/McDhM8OS+ijEMCEz+QEs05fVZ+5KkUymXOIJl0RK42qN0ZLKGIlEiDY2gjIoHnUQMXckDVEHwwC/H0xDEY25PPh0lLv/0UA01n6HKCHE0CIz+QEs05c1ldY0J2x21Ds0xVzclhWXWELjWi5hQ3kdnZSBP1AIpp9QQGWXcABcVxMOGJSXmny4KglEWHhSsczohRjiJMgPYMX5BqNG+HjlwzhOSwNuy6/wKYWrvRLAjc0utm1QNrKc2kgKlI+8UG6AB++DorjApCBsYPlVdiN29rRgf7w1IUQfkeWaASxtQ6TJobll7T2/JUD7fF6wD1kOhvKKhUWaXVA+LJ/C58v9n9Xx9mcpL/GabActQ9r2CTFMSJAfwJauSbKj3qG81CSZ0tnZPHhr8HW12zBIozXEk4CGcDB3Bu84EEu4lBR6HZ0yWrftE0IMXbJcM0Bl0icNUzFlXIA1m1LURx1Ae1k0jVFQJigX0wDXBscF1wXbBlfvaslXWmQyaayVbdkH0rZPiOFCgvwA1Tp90vIppoyzqG90+GTtTi9N0vCTn5dHxch8RhSZRJts1m21STsa0CgFxe30ZM2Qtn1CDA8S5AeoTPpkZvnFNBT1O9ZR9+kKUH6qJ02memJptu9qfkhR36QpzDOoqvB32JM1oyHqsv94S9r2CTHESZAfoDLpk3bLOnymVAHAtKnVTJ5cnXO940JpoQFKYRhtT8i2Jm37hBg+ZBo3QBXlKcpLTWrqHZIpl0wSzLRp05g8eXKb6xuiLjMmBDhoUoAtO2wSqfY3VDNt+2ZOlLZ9QgwHMpMfYFrXjV+1Mc3mmjQ7G2wK86qYeVAZVWOL2zwmMzP/7AFhJldZKCVt+4QQHgnyA8judeOdxE6K84tpbNLUOQ6GCpBwUlRXWlg+L0Dv3lDb8isWnlSc07YvnvQ2WaeNt6RtnxDDjDQN6Se7t9QLBxT3POnVjR890sfGDWtYsWIFxSVljBgzi4aoi+tqHBdKCk2qKnw0Nms0usOmINK2TwghM/k+1lEbv4Cl2LjNZsLoXQEeYFRFGRPHBahvdKipd4g0OdRFHPKCigMmBTudmSulKCkw29wuhBg+JMj3ofba+IWDCtvWfLw2RSzh0tBQT92W1UDuJmtZsY8RRSaptGZzjc2UKovvnlKEYcjeuRCiYxLk+0jrNn67d3lKplyUAu3GqIvaEKhiyjirTRaNUoqApRhZYrK9zibSrCkp6Ot3IoQYTCTI95HO2vi5LjTHYjRHI4AmXDiKEeVFHT6XlCQQQnSVfNfvA5218QNaDi9ZGIaP4uJCQqEQNfVOhxUipSSBEKKrZCbfBzpr4wdesC4utNB6JAX5Zra1XyqtCVhtA7mUJBBCdJVEiT6wexu/jNWrV1NbW4tSyqv1bigcx5vZa+0t4+xOShIIIbpDgnwf2L0ODXi1aJYvX84bb7xBPB7P1nuPJVxsG5Tygn1rUpJACNFdslzTB4rzDSor/Cxbl8RvKjZsWMeqlV4e/OTJkwmFQgBMGmuxmhRbd9rkBRWJlIvjIiUJhBB7TYJ8L8scfqqpt9m0Lc26TY3Emk0ITqRqdD4Tq6uy1/p9inGjfLguVI3ykUxpEilXShIIIfaaBPle1Prwk6s1ym0mFre9Nn2Fo2h2QqzcmGLSWAu/z5u5b691+OzMIGeeWESsJU1SShIIIfaWBPlesvvhp7ra7US2vQ+BKsKFowiFQvhMxY56m2RaU5JvgCK7HBOwDAJWf78LIcRgJ0G+l+x++KmiooL9RpVRUGgxoryImnqHppiLz1REog7VY/ycfESBLMcIIXqUBPle0PrwUyZgG4bBnDmHZJdcMnVoXBe27rSpKDGZNTUgSzJCiB4lKZS9IHP4qbFuM0uXLs2eXG0dwL06NAahoEFZicnG7TYNTe13cxJCiL0lM/lekEprNm3ewuYNq8BNUlFRQXl5eYfXSy0aIURvkSC/B3vTeONvf32UzZsCgI9p0yZ0GuBBatEIIXqPBPkOdNTco2qUv9N89SVLlrDkntth5NfZb+JcJk8eu8fXklo0QojeIkG+HR0293A0KzakWL4+2W7LvSVLlnD77bcDcOKRlWxOlpNMue1WnsyQWjRCiN4kU8fdtM5vryg1qarwU5hnEg4aFOZ5v48q9fHhqiQPPB3JrqNv3LiRP//5zwCcc845/Pd3T2TmxABbdtgkUu1vqEotGiFEb5OZ/G46a+6REbAM9hvpY+naJEvXJJk9LUhVVRX/8z//w5YtWzj99NMBOG1+ERBh6dokCkVxgYHPVFKLRgjRZyTIt7Kn5h6tBS0DheLVDxuz+e1HHXVUzjUFYYOFJxWzdE2SN1vW9uNJLbVohBB9RoJ8K3tq7rG7xvrN/GP5To475GAmT6xo9xrLr5g9LcisqYFuZ+kIIcS+kjX5Vjpq7tGeVatWsW7tKhLJNK+/+c4er1dKUVJgUlHqo6TAlAAvhOgTMpNvpb3mHu1ZtWoVK1asACOPqsox/MdJB/bRCIUQontkJt9Kcb5B1Sh/p+UFsgEe2K9yCnPnjJf8diHEgCXRqRWlFIdND6G1JtlO2mPrAD9p8nRGlpdLfrsQYkCTIL+bmdWBdvPbHdtm8+bNgBfggwWVkt8uhBjwZE1+N5ZfdZDfbnDAwZ9l05YGwsUjsideJf1RCDGQKZ2pgzsMNDY2UlRURCQSobCwsNNrU2nN0jVJnnltG5F4GMcF09hz7RohhBhIZCbfAcuvWP7OI/zz/+7gwh/8hLmfO1Ly24UQg44E+Q60LjYWa9xGRan8VQkhBh/ZeG1H6wB/zjnncMYZZ/TziIQQYu9IkN+NBHghxFAyKIL8+vXrOfvss5kwYQKhUIjq6mquvPJKUqlUj76OBHghxFAzKBaaV6xYgeu6/OEPf2DSpEksXbqU73znOzQ3N/OrX/2qR15Da00kEgEkwAshho5Bm0J5/fXXc9ttt7F27douP2ZPKZRaa9577z1mz57dk0MVQoh+MyiWa9oTiUQoLS3t9JpkMkljY2POz+6ef/757LKPUkoCvBBiSBmUQX7NmjX87ne/49xzz+30usWLF1NUVJT9qayszLl/yZIlXHPNNVxxxRW4bsdFyYQQYrDq1yB/1VVXoZTq9Oftt9/OecyWLVs4/vjjWbBgAeecc06nz3/55ZcTiUSyP5s2bcre13qT9YADDsAwBuXnnRBCdKpf1+R37tzJzp07O71m/PjxBINBwAvw8+bN4zOf+Qx33XVXtwNzZk3+j3/8I/fddx8gm6xCiKFt0Gy8fvrpp8ybN485c+Zw7733Yppmt58jE+SPOOIIfD6fBHghxJA3KFIot2zZwlFHHUVVVRW/+tWv2LFjR/a+UaNG7dVzSoAXQgwHgyLIP/3006xevZrVq1czduzYnPu680Ukc+2CBQs4+eST2822EUKIwaSgoKDToomDZrmmJ2zevLlNho0QQgxmeyqdPqyCvOu6bNmypc0nX2NjI5WVlWzatGmPdeaHmuH83mF4v//h/N5h6Lz/Pc3kB8VyTU8xDKPNck9rhYWFg/p/7H0xnN87DO/3P5zfOwz99y/J4UIIMYRJkBdCiCFMgjwQCAS48sorCQQC/T2UPjec3zsM7/c/nN87DJ/3P6w2XoUQYriRmbwQQgxhEuSFEGIIkyAvhBBDmAR5IYQYwiTIt9JXDcMHquuuu465c+cSDocpLi7u7+H0ultvvZUJEyYQDAaZM2cOL7/8cn8Pqc+89NJLnHzyyYwePRqlFI8//nh/D6nPLF68mEMPPZSCggLKy8s55ZRT+OSTT/p7WL1GgnwrrRuGL1u2jBtuuIHf//73/PjHP+7vofWJVCrFggUL+N73vtffQ+l1Dz74IN///vf5yU9+wnvvvcfnP/95TjjhBDZu3NjfQ+sTzc3NHHTQQdx88839PZQ+9+KLL3L++efz+uuv88wzz2DbNvPnz6e5ubm/h9Y7tOjUL3/5Sz1hwoT+HkafuvPOO3VRUVF/D6NXHXbYYfrcc8/NuW3atGn6sssu66cR9R9AP/bYY/09jH5TU1OjAf3iiy/291B6hczk96ArDcPF4JJKpXjnnXeYP39+zu3z58/n1Vdf7adRif4SiUQAhux/5xLkO9HVhuFicNm5cyeO41BRUZFze0VFBdu2beunUYn+oLXmoosu4ogjjmDmzJn9PZxeMSyCfG83DB/I9ua9Dxe7l2fVWndaslUMPRdccAEffvgh999/f38PpdcMi1LDF1xwAaeddlqn14wfPz7750zD8MMPP5w//vGPvTy63tXd9z4clJWVYZpmm1l7TU1Nm9m9GLouvPBCnnjiCV566aVOS5APdsMiyJeVlVFWVtala1s3DL/zzjsxjMH9Zac77324sCyLOXPm8Mwzz3Dqqadmb3/mmWf48pe/3I8jE31Ba82FF17IY489xgsvvMCECRP6e0i9algE+a7qjYbhg8nGjRupq6tj48aNOI7D+++/D8CkSZPIz8/v38H1sIsuuohvfetbHHLIIdlvbBs3bhw2+y9NTU2sXr06+/u6det4//33KS0tpaqqqh9H1vvOP/987rvvPv76179SUFCQ/UZXVFREKBTq59H1gn7O7hlQ7rzzTg20+zMcLFy4sN33/vzzz/f30HrFLbfcoseNG6cty9KzZ88esil07Xn++efb/d964cKF/T20XtfRf+N33nlnfw+tV0ipYSGEGMIG94KzEEKITkmQF0KIIUyCvBBCDGES5IUQYgiTIC+EEEOYBHkhhBjCJMgLIcQQJkFeDEp91c1o/Pjx3Hjjjb3+Ou256667Ou3QtX79epRS2ZPJQrRHgrwYcGpqavjP//xPqqqqCAQCjBo1iuOOO47XXnste83WrVs54YQT+nGU7dtTYB5IPvjgA77xjW9QWVlJKBRi//3356abburvYYkeJrVrxIDz1a9+lXQ6zd13383EiRPZvn07zz77LHV1ddlrhkMtod72zjvvMHLkSO69914qKyt59dVX+e53v4tpmlxwwQX9PTzRU/q7roIQrdXX12tAv/DCC51eR6uWdevWrdOAfvDBB/URRxyhg8GgPuSQQ/Qnn3yi33zzTT1nzhydl5enjzvuOF1TU5N9jiOPPFL/93//d87zfvnLX86p3zJu3Dh9ww03ZH//9a9/rWfOnKnD4bAeO3as/t73vqej0ajWuv16MFdeeaXWWutkMqkvueQSPXr0aB0Oh/Vhhx3WpibQnXfeqSsrK3UoFNKnnHKK/tWvftVpG8bM+77//vv14YcfrgOBgJ4+ffo+1Ro677zz9Lx58/b68WLgkeUaMaDk5+eTn5/P448/TjKZ7NZjr7zySn7605/y7rvv4vP5+MY3vsGll17KTTfdxMsvv8yaNWu44oor9ml8hmHw29/+lqVLl3L33Xfz3HPPcemllwIwd+5cbrzxRgoLC9m6dStbt27l4osvBuDb3/42r7zyCg888AAffvghCxYs4Pjjj2fVqlUAvPHGG5x11lmcd955vP/++8ybN4+f/exnXRrTJZdcwg9/+EPee+895s6dy5e+9CVqa2v36v1Ju8shqL8/ZYTY3V/+8hddUlKig8Ggnjt3rr788sv1Bx98kHMN7czkb7/99uz9999/vwb0s88+m71t8eLFeurUqdnf92Ymv7uHHnpIjxgxIvt7e03QV69erZVS+tNPP825/ZhjjtGXX3651lrrb3zjG/r444/Puf/rX/96l2byv/jFL7K3pdNpPXbsWP2///u/HT6uI6+++qr2+/366aef7vZjxcAlM3kx4Hz1q19ly5YtPPHEExx33HG88MILzJ49m7vuuqvTxx144IHZP2c6PB1wwAE5t9XU1OzT2J5//nmOPfZYxowZQ0FBAWeeeSa1tbU0Nzd3+Jh3330XrTVTpkzJflPJz8/nxRdfZM2aNQAsX76cww8/POdxu//ekdbX+Xw+DjnkEJYvX96t97Vs2TK+/OUvc8UVV3Dsscd267FiYJONVzEgBYNBjj32WI499liuuOIKzjnnHK688koWLVrU4WP8fn/2z5lerbvf5rpu9nfDMNC7VdpOp9MdPv+GDRs48cQTOffcc7n22mspLS3l3//+N2effXanj3NdF9M0eeeddzBNM+e+TDOW3cexr7rTq/bjjz/m6KOP5jvf+Q4//elPe3Qcov/JTF4MCtOnT+90trw3Ro4cydatW7O/O47D0qVLO7z+7bffxrZtfv3rX/PZz36WKVOmsGXLlpxrLMvCcZyc22bNmoXjONTU1DBp0qScn0yW0PTp03n99ddzHrf77x1pfZ1t27zzzjtMmzatS49dtmwZ8+bNY+HChVx33XVdeowYXGQmLwaU2tpaFixYwFlnncWBBx5IQUEBb7/9Nr/85S97vP/q0UcfzUUXXcQ//vEPqqurueGGG2hoaOjw+urqamzb5ne/+x0nn3wyr7zyCr///e9zrhk/fjxNTU08++yzHHTQQYTDYaZMmcIZZ5zBmWeeya9//WtmzZrFzp07ee655zjggAM48cQT+a//+i/mzp3LL3/5S0455RSefvppnnrqqS69j1tuuYXJkyez//77c8MNN1BfX89ZZ521x8dlAvz8+fO56KKLsm3wTNNk5MiRXXptMQj0856AEDkSiYS+7LLL9OzZs3VRUZEOh8N66tSp+qc//amOxWLZ62hn4/W9997L3p9JZ6yvr8/etvumaCqV0t/73vd0aWmpLi8v14sXL97jxutvfvMbvd9+++lQKKSPO+44fc8997R5nXPPPVePGDEiJ4UylUrpK664Qo8fP177/X49atQofeqpp+oPP/ww+7g77rhDjx07VodCIX3yySd3OYXyvvvu05/5zGe0ZVl6//33z9ls7syVV17Zbhu8cePGdenxYnCQ9n9CCDGEyZq8EEIMYRLkhRiizj333JyUzdY/5557bn8PT/QRWa4RYoiqqamhsbGx3fsKCwspLy/v4xGJ/iBBXgghhjBZrhFCiCFMgrwQQgxhEuSFEGIIkyAvhBBDmAR5IYQYwiTICyHEECZBXgghhjAJ8kIIMYT9f3KlzPFuNqljAAAAAElFTkSuQmCC", "text/plain": [ - "
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" ] }, "metadata": {}, diff --git a/examples/rl.ipynb b/examples/rl.ipynb index 8d16aa8..88e95d2 100644 --- a/examples/rl.ipynb +++ b/examples/rl.ipynb @@ -5,13 +5,32 @@ "id": "6a4a80b6", "metadata": {}, "source": [ - "# Two-Armed Bandit Reinforcement Learning\n", + "# Model-Free Reinforcement Learning" + ] + }, + { + "cell_type": "markdown", + "id": "2e90d671", + "metadata": {}, + "source": [ + "## Two-Armed Bandit Task - 1Q1α1β Rescorla-Wagner Model\n", "\n", - "This example demonstrates parameter recovery for a simple two-armed bandit\n", - "reinforcement learning task. On each trial the participant chooses between two\n", - "options with different reward probabilities. Choices are generated with a\n", - "Rescorla–Wagner model using an inverse-temperature parameter (``beta``) and a\n", - "learning rate (``alpha``)." + "This example demonstrates parameter recovery for a simple two-armed bandit reinforcement learning task. On each trial the participant chooses between two options with different reward probabilities. Choices are generated with a Rescorla–Wagner model using an inverse-temperature parameter (``beta``) and a learning rate (``alpha``).\n", + "\n", + "$$\n", + "\\textbf{Expected value update:}\\quad\n", + "Q_{t+1}^k = Q_t^k + \\alpha \\cdot \\delta_t \\tag{1}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Prediction error:}\\quad\n", + "\\delta_t = r_t - Q_t^k \\tag{2}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Choice rule (softmax):}\\quad\n", + "p_t(\\text{choose }k)=\\frac{\\exp(\\beta \\cdot Q_t^k)}{\\sum_{k=1}^{K}\\exp(\\beta \\cdot Q_t^k)} \\tag{3}\n", + "$$" ] }, { @@ -24,7 +43,7 @@ "import numpy as np\n", "from scipy.stats import truncnorm, beta as beta_dist\n", "from pyem import EMModel\n", - "from pyem.models.rl import rw1a1b_simulate, rw1a1b_fit\n", + "from pyem.models.rl import rw1a1b_sim, rw1a1b_fit\n", "from pyem.utils.math import norm2beta, norm2alpha" ] }, @@ -55,9 +74,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -69,7 +88,7 @@ "model = EMModel(all_data=None, fit_func=rw1a1b_fit,\n", " param_names=[\"beta\", \"alpha\"],\n", " param_xform=[norm2beta, norm2alpha], \n", - " simulate_func=rw1a1b_simulate)\n", + " simulate_func=rw1a1b_sim)\n", "\n", "recovery = model.recover(true_params, \n", " pr_inputs=['choices','rewards'], \n", @@ -89,6 +108,271 @@ "`recovery['correlation']`, which provides a correlation coefficient for each\n", "parameter." ] + }, + { + "cell_type": "markdown", + "id": "b821e1ba", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "markdown", + "id": "fd59c93e", + "metadata": {}, + "source": [ + "## Model-Free Reinforcement Learning in Social Contexts\n", + "\n", + "The following two examples demonstrate parameter recovery for different versions of a two-armed bandit reinforcement learning task, in which the agent learns how their actions affect themselves and another target. On each trial the agent chooses between different options with different outcome probabilities. Choices are generated with an adapted Rescorla–Wagner model using an inverse-temperature parameter (``beta``) and distinct learning rates (``alpha``) depending on the target." + ] + }, + { + "cell_type": "markdown", + "id": "353cf6fd", + "metadata": {}, + "source": [ + "### Prosocial Learning Task ([Lockwood et al., 2016, *PNAS*](https://doi.org/10.1073/pnas.1603198113)) - 1Q3α1β Model\n", + "\n", + "Participants learn to make choices to win points for themselves (self), a stranger (other), or no one (no one) in separate conditions. Rewards include gaining points (+100) or not gaining points (0) on any given trial, which are later converted to real-world payouts.\n", + "\n", + "The model is an adapated Rescorla Wagner model with 3 different learning rates $\\alpha_i^\\ast$ for each target (self, other, noone):\n", + "\n", + "$$\n", + "\\textbf{Expected value update:}\\quad\n", + "Q_{t+1}^k = Q_t^k + \\alpha_i^\\ast \\cdot \\delta_t \\tag{1}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Prediction error:}\\quad\n", + "\\delta_t = r_t - Q_t^k \\tag{2}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Learning rates:}\\quad\n", + "\\alpha_i^\\ast =\n", + "\\begin{cases}\n", + "\\alpha_{\\text{self}}, & \\text{if } i=\\text{self}\\\\[4pt]\n", + "\\alpha_{\\text{other}}, & \\text{if } i=\\text{other}\\\\[4pt]\n", + "\\alpha_{\\text{no one}}, & \\text{if } i=\\text{no one}\n", + "\\end{cases}\n", + "\\tag{3}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Choice rule (softmax):}\\quad\n", + "p_t(\\text{choose }k)=\\frac{\\exp(\\beta \\cdot Q_t^k)}{\\sum_{k=1}^{K}\\exp(\\beta \\cdot Q_t^k)} \\tag{4}\n", + "$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "1df460ba", + "metadata": {}, + "outputs": [], + "source": [ + "from pyem.models.rl import rw3a1b_sim, rw3a1b_fit" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dfb822be", + "metadata": {}, + "outputs": [], + "source": [ + "# simulate computer agents completing the prosocial learning task (Lockwood et al., 2016)\n", + "nsubjects, nblocks, ntrials = 100, 9, 16\n", + "betamin, betamax = .75, 10 # inverse temperature\n", + "alphamin, alphamax = .05, .95 # learning rates\n", + "\n", + "# generate distribution of parameters within range\n", + "beta_rv = truncnorm((betamin-0)/1, (betamax-0)/1, loc=0, scale=2).rvs(nsubjects)\n", + "a_lo, a_hi = beta_dist.cdf([alphamin, alphamax], 1.1, 1.1)\n", + "alpha_rv = beta_dist.ppf(a_lo + np.random.rand(nsubjects, 3) * (a_hi - a_lo), 1.1, 1.1)\n", + "\n", + "# stack parameters together: beta + 4 alphas\n", + "true_params = np.column_stack((beta_rv, alpha_rv))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "bbdc0ca4", + "metadata": {}, + "outputs": [], + "source": [ + "# use EMModel.recover to run simulation, fitting and recovery metrics\n", + "model = EMModel(all_data=None, fit_func=rw3a1b_fit,\n", + " param_names=[\"beta\", \"a_self\", \"a_other\", \"a_noone\"],\n", + " param_xform=[norm2beta, norm2alpha, norm2alpha, norm2alpha], \n", + " simulate_func=rw3a1b_sim)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "b428f51c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "recovery = model.recover(true_params, \n", + " pr_inputs=['choices','rewards'], \n", + " nblocks=nblocks, ntrials=ntrials\n", + " )\n", + "\n", + "# scatter plot of recovered parameters\n", + "fig = model.plot_recovery(recovery)" + ] + }, + { + "cell_type": "markdown", + "id": "eb81fbf4", + "metadata": {}, + "source": [ + "### Dual-Outcome Social Learning Task ([Rhoads et al., 2025, *Nature Communications*](https://doi.org/10.1038/S41467-025-64424-9)) - 1Q4α1β Model\n", + "\n", + "Participants learn to make choices to earn points for themselves (self) and a stranger (other) simultaneously. Outcomes include gaining points (+100), losing points (-100), and receiving no points (0), which are later converted to real-world payouts.\n", + "\n", + "Possible options yield the following types of outcomes probabilistically (independently assigned to self and other targets):\n", + "* **A:** ++ Mutual Benefit (self gain, other gain)\n", + "* **B:** +- Instrumental Harm (self gain, other loss)\n", + "* **C:** -+ Altruism (self loss, other gain)\n", + "* **D:** -- Mutual Cost (self loss, other loss)\n", + "\n", + "In the two-option version of the task, agents learn to choose between each pair of options, $4!/(2! * (4-2)!) = 6$ pairs\n", + "\n", + "The model is an adapated Rescorla Wagner model with four different learning rates $\\alpha_i^\\ast$ for different targets (self, other) and valence (positive, negative), and predicts how agents learn how their actions affect dual outcomes (self, other) across **mutually beneficial**, **instrumentally harmful**, **altruistic**, and **mutually costly** scenarios:" + ] + }, + { + "cell_type": "markdown", + "id": "f845e29f", + "metadata": {}, + "source": [ + "$$\n", + "\\textbf{Expected value update:}\\quad\n", + "Q_{t+1}^k = Q_t^k + \\alpha_i^\\ast \\cdot \\delta_t \\tag{1}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Prediction error:}\\quad\n", + "\\delta_t = r_t - Q_t^k \\tag{2}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Learning rates:}\\quad\n", + "\\alpha_i^\\ast =\n", + "\\begin{cases}\n", + "\\alpha_{\\text{self}}^{+}, & \\text{if } i=\\text{self}, \\delta_t \\ge 0\\\\\n", + "\\alpha_{\\text{other}}^{+}, & \\text{if } i=\\text{other}, \\delta_t \\ge 0\\\\\n", + "\\alpha_{\\text{self}}^{-}, & \\text{if } i=\\text{self}, \\delta_t < 0\\\\\n", + "\\alpha_{\\text{other}}^{-}, & \\text{if } i=\\text{other}, \\delta_t < 0\n", + "\\end{cases}\n", + "\\tag{3}\n", + "$$\n", + "\n", + "$$\n", + "\\textbf{Choice rule (softmax):}\\quad\n", + "p_t(\\text{choose }k)=\\frac{\\exp(\\beta \\cdot Q_t^k)}{\\sum_{k=1}^{K}\\exp(\\beta \\cdot Q_t^k)} \\tag{4}\n", + "$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a9cd6702", + "metadata": {}, + "outputs": [], + "source": [ + "from pyem.models.rl import rw4a1b_sim, rw4a1b_fit" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "f2aa1275", + "metadata": {}, + "outputs": [], + "source": [ + "# simulate computer agents completing the prosocial learning task (Rhoads et al., 2025)\n", + "nsubjects, nblocks, ntrials = 50, 12, 20\n", + "betamin, betamax = .75, 10 # inverse temperature\n", + "alphamin, alphamax = .05, .95 # learning rates\n", + "\n", + "# generate distribution of parameters within range\n", + "beta_rv = truncnorm((betamin-0)/1, (betamax-0)/1, loc=0, scale=2).rvs(nsubjects)\n", + "a_lo, a_hi = beta_dist.cdf([alphamin, alphamax], 1.1, 1.1)\n", + "alpha_rv = beta_dist.ppf(a_lo + np.random.rand(nsubjects, 4) * (a_hi - a_lo), 1.1, 1.1)\n", + "\n", + "# stack parameters together: beta + 4 alphas\n", + "true_params = np.column_stack((beta_rv, alpha_rv))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2cead2fb", + "metadata": {}, + "outputs": [], + "source": [ + "# use EMModel.recover to run simulation, fitting and recovery metrics\n", + "model = EMModel(all_data=None, fit_func=rw4a1b_fit,\n", + " param_names=[\"beta\", \"a_self_pos\", \"a_self_neg\", \"a_other_pos\", \"a_other_neg\"],\n", + " param_xform=[norm2beta, norm2alpha, norm2alpha, norm2alpha, norm2alpha], \n", + " simulate_func=rw4a1b_sim)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "54d23b8a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "recovery = model.recover(true_params, \n", + " pr_inputs=['choices','outcomes_self','outcomes_other','option_pairs'],\n", + " nblocks=nblocks, ntrials=ntrials\n", + " )\n", + "\n", + "# scatter plot of recovered parameters\n", + "fig = model.plot_recovery(recovery)" + ] + }, + { + "cell_type": "markdown", + "id": "af35c050", + "metadata": {}, + "source": [ + "**References**\n", + "\n", + "Lockwood, P. L., Apps, M. A., Valton, V., Viding, E., & Roiser, J. P. (2016). Neurocomputational mechanisms of prosocial learning and links to empathy. *Proceedings of the National Academy of Sciences*, 113(35), 9763-9768. https://doi.org/10.1073/pnas.1603198113\n", + "\n", + "Rhoads, S. A., Gan, L., Berluti, K., OConnell, K., Cutler, J., Lockwood, P., & Marsh, A. (2025). Neurocomputational basis of learning when choices simultaneously affect both oneself and others. *Nature Communications*. 16, 9350. https://doi.org/10.1038/s41467-025-64424-9\n" + ] } ], "metadata": { diff --git a/pyem/api.py b/pyem/api.py index 571ec0c..a626db6 100644 --- a/pyem/api.py +++ b/pyem/api.py @@ -101,7 +101,7 @@ def fit( convergence_custom: str | None = None, convergence_crit: float = 1e-3, convergence_precision: int = 6, - njobs: int = -1, + njobs: int = -2, optim_method: str = "BFGS", optim_options: dict | None = None, max_restarts: int = 2, @@ -367,11 +367,18 @@ def recover(self, true_params: np.ndarray, pr_inputs: List[str], simulate_func: self._out = recovery_model._out return recovery_dict - def plot_recovery(self, recovery_dict: dict, show_line: bool = True, - figsize: tuple = (10, 4), show: bool = True) -> plt.Figure: + def plot_recovery( + self, + recovery_dict: dict, + show_line: bool = True, + figsize: tuple | None = None, + show: bool = True + ) -> plt.Figure: """ Plot parameter recovery as scatter plots of simulated vs estimated parameters. - + Creates 3 columns with as many rows as needed, with compact spacing and + subplot sizes that scale with the grid. + Args: recovery_dict: Output from recover() method, containing: - 'true_params' (array-like, shape [n_sims, n_params]) @@ -387,37 +394,62 @@ def plot_recovery(self, recovery_dict: dict, show_line: bool = True, estimated_params = recovery_dict['estimated_params'] nparams = true_params.shape[1] - # Create 1 x nparams layout (keep squeeze=False to always get 2D array, then ravel) - fig, axes = plt.subplots(1, nparams, figsize=figsize, squeeze=False) - axes = axes.ravel() + # Grid: 3 columns, compute rows + ncols = 3 + nrows = int(np.ceil(nparams / ncols)) + + # Figure size: scale per-subplot to avoid tiny axes. + # Aim for 5x5 inches per subplot (square-ish data area works well here). + per_ax_w, per_ax_h = 3.5, 3.5 + fig_w = per_ax_w * ncols + fig_h = per_ax_h * nrows + if figsize is None: + figsize = (fig_w, fig_h) + + fig, axes = plt.subplots( + nrows, ncols, + figsize=figsize, + constrained_layout=True, # let Matplotlib handle spacing + squeeze=False + ) - # In case self.param_names is longer than nparams + # Fine-tune constrained_layout paddings (reduces big gutters) + # w_pad/h_pad: padding around the figure edges; wspace/hspace: padding between subplots + fig.get_layout_engine().set() #h_pad=X, w_pad=Y, hspace=Z, wspace=W + + axes = axes.ravel() names = list(self.param_names)[:nparams] for i, param_name in enumerate(names): ax = axes[i] - - # Use the shared plotting helper plotting.plot_scatter( true_params[:, i], f'True {param_name}', estimated_params[:, i], f'Estimated {param_name}', ax=ax, show_line=show_line, - equal_limits=True, - s=75, + equal_limits=True, # still equalize limits (handled w/ box aspect below) + s=100, # slightly smaller markers to reduce overlap alpha=0.6, colorname='royalblue', annotate=True, ) + # Title & tick/label sizing tuned so they don't collide with data + ax.tick_params(labelsize=12) + ax.xaxis.label.set_size(12) + ax.yaxis.label.set_size(12) - # Title - ax.set_title(f'{param_name}') + # Keep plots square without blowing up gutters + # (avoid ax.set_aspect('equal', adjustable='box') here) + try: + ax.set_box_aspect(1) # Matplotlib >=3.4 + except Exception: + pass - # Hide any unused axes (just in case) + # Remove unused axes completely so they don't consume layout space for j in range(nparams, len(axes)): - axes[j].set_visible(False) + axes[j].remove() - plt.tight_layout() if show: plt.show() + return fig diff --git a/pyem/core/em.py b/pyem/core/em.py index 9611a1d..64837af 100644 --- a/pyem/core/em.py +++ b/pyem/core/em.py @@ -19,7 +19,7 @@ class EMConfig: convergence_custom: Literal["relative_npl","running_average", None] = None convergence_crit: float = 1e-3 convergence_precision: int = 6 - njobs: int = -1 + njobs: int = -2 optim: OptimConfig = field(default_factory=OptimConfig) seed: int | None = None max_subject_retries: int = 0 # additional retries if optimizer fails badly diff --git a/pyem/models/bayes.py b/pyem/models/bayes.py index 77157cd..2e185d3 100644 --- a/pyem/models/bayes.py +++ b/pyem/models/bayes.py @@ -1,4 +1,3 @@ -from __future__ import annotations import numpy as np from ..utils.math import norm2alpha, calc_fval @@ -15,7 +14,7 @@ def _generate_fishp(lambda1: float, n_fish: int) -> np.ndarray: fishp = np.eye(n_fish) * m + (1 - np.eye(n_fish)) * s return fishp -def simulate(params: np.ndarray, nblocks: int = 10, ntrials: int = 15, +def bayes_sim(params: np.ndarray, nblocks: int = 10, ntrials: int = 15, n_fish: int = 3) -> dict: """Simulate the fish task described in the repository documentation. @@ -68,7 +67,7 @@ def simulate(params: np.ndarray, nblocks: int = 10, ntrials: int = 15, "ponds": ponds, } -def fit(params, choices, observations, prior=None, output: str = 'npl'): +def bayes_fit(params, choices, observations, prior=None, output: str = 'npl'): """Likelihood for the fish task. Parameters are supplied in Gaussian space and transformed to ``lambda1`` diff --git a/pyem/models/rl.py b/pyem/models/rl.py index 5f6b5f5..d19898e 100644 --- a/pyem/models/rl.py +++ b/pyem/models/rl.py @@ -1,9 +1,9 @@ -from __future__ import annotations -import numpy as np +import numpy as np, random +from itertools import permutations, chain from ..utils.math import softmax, norm2alpha, norm2beta, calc_fval -def rw1a1b_simulate(params: np.ndarray, nblocks: int = 3, ntrials: int = 24, +def rw1a1b_sim(params: np.ndarray, nblocks: int = 3, ntrials: int = 24, outcomes: np.ndarray | None = None): """Simulate a simple Rescorla–Wagner model with one learning rate. @@ -117,8 +117,8 @@ def rw1a1b_fit(params, choices, rewards, prior=None, output="npl"): return calc_fval(nll, params, prior=prior, output=output) -def rw2a1b_simulate(params: np.ndarray, nblocks: int = 3, ntrials: int = 24, - outcomes: np.ndarray | None = None): +def rw2a1b_sim(params: np.ndarray, nblocks: int = 3, ntrials: int = 24, + outcomes: np.ndarray | None = None): """Simulate a Rescorla–Wagner model with separate learning rates for gains and losses.""" nsubjects = params.shape[0] choices = np.empty((nsubjects, nblocks, ntrials), dtype=object) @@ -231,3 +231,459 @@ def rw2a1b_fit(params, choices, rewards, prior=None, output="npl"): return subj_dict return calc_fval(nll, params, prior=prior, output=output) + +# -------------------------------------- +# 3α-1β SIMULATE (Lockwood et al., 2016) +# -------------------------------------- +def rw3a1b_sim(params: np.ndarray, + nblocks: int = 9, + ntrials: int = 16, + outcomes: np.ndarray | None = None): + """ + Two-option task (A/B each trial) with three binary outcome channels: + self, other, noone. NATURAL-SPACE params. + + params: (S,4) = [beta, a_self, a_other, a_noone], with: + beta in [1e-5, 20], alphas in [0,1]. + outcomes (optional): (B,T,2,3) last dim = [self, other, noone]; values in {0,1}. + + Returns: + - choices: (S,B,T) of 'A'/'B' + - EV: (S,B,T+1,2) + - ch_prob: (S,B,T,2) + - nll: (S,B,T) + - rewards_self/other/noone: (B,T,2) # same for all subjects unless customized + - PE_self/other/noone: (S,B,T) + - rewards: list of length S with the 3 reward arrays (for EMModel.recover) + - params: (S,4) = np.array([beta, a_self, a_other, a_noone]).T + """ + if params.ndim != 2 or params.shape[1] != 4: + raise ValueError("params must be (nsubjects, 4) = [beta, a_self, a_other, a_noone]") + + S = params.shape[0] + beta_all = params[:, 0] + a_self_all = params[:, 1] + a_other_all = params[:, 2] + a_noone_all = params[:, 3] + + if not ((beta_all >= 1e-5) & (beta_all <= 20.0)).all(): + raise ValueError("beta out of bounds [1e-5, 20]") + if not ((a_self_all >= 0.0) & (a_self_all <= 1.0)).all(): + raise ValueError("a_self must be in [0,1]") + if not ((a_other_all >= 0.0) & (a_other_all <= 1.0)).all(): + raise ValueError("a_other must be in [0,1]") + if not ((a_noone_all >= 0.0) & (a_noone_all <= 1.0)).all(): + raise ValueError("a_noone must be in [0,1]") + + rng = np.random.default_rng() + choice_labels = np.array(['A','B'], dtype=object) + + # outcomes + if outcomes is not None: + if outcomes.shape != (nblocks, ntrials, 2, 3): + raise ValueError("outcomes must be (nblocks, ntrials, 2, 3) with last dim [self, other, noone]") + Rself = outcomes[..., 0].astype(float) + Rother = outcomes[..., 1].astype(float) + Rnone = outcomes[..., 2].astype(float) + else: + # Bernoulli(0/1) per option/channel + Rself = rng.integers(0, 2, size=(nblocks, ntrials, 2)).astype(float) + Rother = rng.integers(0, 2, size=(nblocks, ntrials, 2)).astype(float) + Rnone = rng.integers(0, 2, size=(nblocks, ntrials, 2)).astype(float) + + # alloc + EV = np.zeros((S, nblocks, ntrials + 1, 2), dtype=float) + ch_prob = np.zeros((S, nblocks, ntrials, 2), dtype=float) + choices = np.empty((S, nblocks, ntrials), dtype=object) + nll = np.zeros((S, nblocks, ntrials), dtype=float) + PE_self = np.zeros((S, nblocks, ntrials), dtype=float) + PE_other = np.zeros((S, nblocks, ntrials), dtype=float) + PE_noone = np.zeros((S, nblocks, ntrials), dtype=float) + + for s in range(S): + beta = float(beta_all[s]) + a_self = float(a_self_all[s]) + a_other = float(a_other_all[s]) + a_noone = float(a_noone_all[s]) + + for b in range(nblocks): + EV[s, b, 0, :] = 0.0 + for t in range(ntrials): + p = softmax(EV[s, b, t, :], beta) # over A/B + ch_prob[s, b, t, :] = p + c = int(rng.choice([0, 1], p=p)) # 0='A', 1='B' + choices[s, b, t] = choice_labels[c] + + v = EV[s, b, t, c] + r_self = float(Rself[b, t, c]) + r_other = float(Rother[b, t, c]) + r_noone = float(Rnone[b, t, c]) + + pe_self = r_self - v + pe_other = r_other - v + pe_noone = r_noone - v + PE_self[s, b, t] = pe_self + PE_other[s, b, t] = pe_other + PE_noone[s, b, t] = pe_noone + + delta = a_self * pe_self + a_other * pe_other + a_noone * pe_noone + EV[s, b, t + 1, :] = EV[s, b, t, :] + EV[s, b, t + 1, c] = v + delta + + nll[s, b, t] = -np.log(ch_prob[s, b, t, c] + 1e-12) + + # rewards payload (same arrays for all subjects here) + rewards_payload = [ + {"rewards_self": Rself, "rewards_other": Rother, "rewards_noone": Rnone} + for _ in range(S) + ] + + return { + "params" : np.column_stack([beta_all, a_self_all, a_other_all, a_noone_all]), + "choices" : choices, + "EV" : EV, + "ch_prob" : ch_prob, + "nll" : nll, + "rewards_self" : Rself, + "rewards_other" : Rother, + "rewards_noone" : Rnone, + "PE_self" : PE_self, + "PE_other" : PE_other, + "PE_noone" : PE_noone, + "rewards" : rewards_payload, # for EMModel.recover(pr_inputs=['choices','rewards']) + } + +# -------------------------------------- +# 3α-1β FIT (Lockwood et al., 2016) +# -------------------------------------- +def rw3a1b_fit(params: np.ndarray, + choices: np.ndarray, + rewards, + prior=None, + output: str = "npl"): + """ + choices: (B,T) of 'A'/'B' + rewards: dict with keys {'rewards_self','rewards_other','rewards_noone'} + or tuple (Rself, Rother, Rnone). + """ + # unpack rewards + if isinstance(rewards, dict): + Rself = rewards["rewards_self"] # (B,T,2) + Rother = rewards["rewards_other"] # (B,T,2) + Rnone = rewards["rewards_noone"] # (B,T,2) + else: + Rself, Rother, Rnone = rewards + + nblocks, ntrials = Rself.shape[:2] + choice_to_idx = {'A': 0, 'B': 1} + + # normalized → natural + beta = float(norm2beta(params[0])) + a_self = float(norm2alpha(params[1])) + a_other = float(norm2alpha(params[2])) + a_noone = float(norm2alpha(params[3])) + + # bounds + if not (1e-5 <= beta <= 20.0): + return 1e7 + for a in (a_self, a_other, a_noone): + if not (0.0 <= a <= 1.0): + return 1e7 + + EV = np.zeros((nblocks, ntrials + 1, 2), dtype=float) + ch_prob = np.zeros((nblocks, ntrials, 2), dtype=float) + PE_self = np.zeros((nblocks, ntrials), dtype=float) + PE_other = np.zeros((nblocks, ntrials), dtype=float) + PE_noone = np.zeros((nblocks, ntrials), dtype=float) + NLL = 0.0 + + for b in range(nblocks): + EV[b, 0, :] = 0.0 + for t in range(ntrials): + p = softmax(EV[b, t, :], beta) + ch_prob[b, t, :] = p + + cchr = choices[b, t] + c = choice_to_idx[cchr] + NLL += -np.log(p[c] + 1e-12) + + v = EV[b, t, c] + r_self = float(Rself[b, t, c]) + r_other = float(Rother[b, t, c]) + r_noone = float(Rnone[b, t, c]) + + pe_self = r_self - v + pe_other = r_other - v + pe_noone = r_noone - v + PE_self[b, t] = pe_self + PE_other[b, t] = pe_other + PE_noone[b, t] = pe_noone + + delta = a_self * pe_self + a_other * pe_other + a_noone * pe_noone + EV[b, t + 1, :] = EV[b, t, :] + EV[b, t + 1, c] = v + delta + + if output == "all": + n = nblocks * ntrials + k = len(params) + BIC = k * np.log(n) + 2.0 * NLL + return { + "params" : [beta, a_self, a_other, a_noone], + "EV" : EV, + "choices" : choices, + "ch_prob" : ch_prob, + "rewards_self" : Rself, + "rewards_other" : Rother, + "rewards_noone" : Rnone, + "PE_self" : PE_self, + "PE_other" : PE_other, + "PE_noone" : PE_noone, + "nll" : NLL, + "BIC" : BIC, + } + + return calc_fval(NLL, params, prior=prior, output=output) + +# ---------------------------------------- +# 1Q–4α–1β SIMULATE (Rhoads et al., 2025) +# ---------------------------------------- +def gen_rnd_blocks(items, nblocks=2, nsubjects=100): + perms = list(permutations(items)) + for _ in range(nsubjects): + # Randomly pick nblocks permutations with replacement + blocks = random.choices(perms, k=nblocks) + combined = tuple(chain.from_iterable(blocks)) + yield combined + +def rw4a1b_sim(params: np.ndarray, + nblocks: int = 12, + ntrials: int = 20): + """ + Simulate a 4-option 1Q RW with one beta and four learning rates: + a_self_pos, a_self_neg, a_other_pos, a_other_neg + + Each trial shows a PAIR OF OPTIONS (indices 0..3) and the agent picks one of those two. + Outcomes for SELF and OTHER are drawn independently from option-specific marginals over {-1,0,+1} + + Fixed design: + - There are 6 unique option-pairs from {0,1,2,3}: (0,1),(0,2),(0,3),(1,2),(1,3),(2,3). + - For 12 blocks, we cycle those 6 pairs twice (blocks 0..11). + - Each block also has a fixed pattern type for outcome marginals, cycled over 4 types: + (+/+), (+/-), (-/+), (-/-) and then repeat. + Pattern type is fixed within a block. + + Returns: + - choices : (S,B,T) int indices 0..3 (chosen option among the shown pair) + - outcomes_self : (S,B,T) int in {-1,0,+1} + - outcomes_other : (S,B,T) int in {-1,0,+1} + - option_pairs : (S,B,T,2) int indices for the two shown options on each trial + - also EV, ch_prob (over 4), and PE components + """ + assert nblocks % 6 == 0, "nblocks should be multiple of 6 for full counterbalancing" + + # Bounds check + beta_all, a_self_pos_all, a_self_neg_all, a_other_pos_all, a_other_neg_all = (params[:, i].astype(float) for i in range(5)) + if not ((beta_all > 1e-5) & (beta_all <= 20.0)).all(): + raise ValueError("beta out of bounds") + for arr, name in [(a_self_pos_all, "a_self_pos"), (a_self_neg_all, "a_self_neg"), + (a_other_pos_all, "a_other_pos"), (a_other_neg_all, "a_other_neg")]: + if not ((0.0 <= arr) & (arr <= 1.0)).all(): + raise ValueError(f"{name} out of bounds") + + rng = np.random.default_rng() + nsubjects = params.shape[0] + + # Outputs + choices = np.zeros((nsubjects, nblocks, ntrials), dtype=object) # A,B,C,D + outcomes_self = np.zeros((nsubjects, nblocks, ntrials), dtype=int) # -1/0/+1 + outcomes_other = np.zeros((nsubjects, nblocks, ntrials), dtype=int) # -1/0/+1 + option_pairs = np.zeros((nsubjects, nblocks, ntrials, 2), dtype=object) + + # Optional diagnostics + EV = np.zeros((nsubjects, nblocks, ntrials + 1, 4), dtype=float) + ch_prob = np.zeros((nsubjects, nblocks, ntrials, 4), dtype=float) + pe_self = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + pe_other = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + pe_self_pos = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + pe_self_neg = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + pe_other_pos = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + pe_other_neg = np.zeros((nsubjects, nblocks, ntrials), dtype=float) + + # create task structure + all_pairs = ['AB', 'AC', 'AD', 'BC', 'BD', 'CD'] + letter_to_idx = {'A':0, 'B':1, 'C':2, 'D':3} + block_orders = list(gen_rnd_blocks(['AB', 'AC', 'AD', 'BC', 'BD', 'CD'], + nblocks=nblocks, nsubjects=nsubjects)) + if ntrials == 20: + # high 75%, mid 15%, low 10% + opt_templates = {'+': [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, -1, -1], + '-': [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 1, 1]} + else: # get proportion of good (1,0,-1) and bad (-1,0,1) at high 75%, mid 15%, low 10% + opt_templates = {'+': np.random.choice([1, 0, -1], size=ntrials, p=[0.75, 0.15, 0.10]), + '-': np.random.choice([-1, 0, 1], size=ntrials, p=[0.75, 0.15, 0.10])} + opt_types = {'A': ('+','+'), 'B': ('+','-'),'C': ('-','+'), 'D': ('-','-')} + + for s in range(nsubjects): + beta = beta_all[s] + a_self_pos = a_self_pos_all[s] + a_self_neg = a_self_neg_all[s] + a_other_pos = a_other_pos_all[s] + a_other_neg = a_other_neg_all[s] + + for b in range(nblocks): + # get block pair + opt1, opt2 = block_orders[s][b] + o1, o2 = letter_to_idx[opt1], letter_to_idx[opt2] + + # create possible outcomes for this block + all_outcomes = {'A_self' :[np.nan]*ntrials, 'A_other':[np.nan]*ntrials, + 'B_self' :[np.nan]*ntrials, 'B_other':[np.nan]*ntrials, + 'C_self' :[np.nan]*ntrials, 'C_other':[np.nan]*ntrials, + 'D_self' :[np.nan]*ntrials, 'D_other':[np.nan]*ntrials + } + for this_opt in (opt1, opt2): + self_kind, other_kind = opt_types[this_opt] + all_outcomes[f'{this_opt}_self'] = rng.permutation(opt_templates[self_kind]) + all_outcomes[f'{this_opt}_other'] = rng.permutation(opt_templates[other_kind]) + + EV[s, b, 0, :] = 0 + for t in range(ntrials): + # the two shown options on this trial (fixed per block) + option_pairs[s, b, t, 0] = opt1 + option_pairs[s, b, t, 1] = opt2 + + # softmax over the two shown options + shown_vals = np.array([EV[s, b, t, o1], EV[s, b, t, o2]], dtype=float) + p = softmax(shown_vals, beta) + ch_prob[s, b, t, o1] = p[0] + ch_prob[s, b, t, o2] = p[1] + choices[s, b, t] = rng.choice([opt1, opt2], p=p) + c = letter_to_idx[choices[s, b, t]] + + # get outcomes from choices and all_outcomes + outcomes_self[s, b, t] = all_outcomes[f'{choices[s, b, t]}_self'][t] + outcomes_other[s, b, t] = all_outcomes[f'{choices[s, b, t]}_other'][t] + + # compute prediction errors + pe_self[s, b, t] = outcomes_self[s, b, t] - EV[s, b, t, c] + pe_other[s, b, t] = outcomes_other[s, b, t] - EV[s, b, t, c] + + pe_self_pos[s, b, t] = pe_self[s, b, t] if pe_self[s, b, t] >= 0.0 else 0.0 + pe_self_neg[s, b, t] = pe_self[s, b, t] if pe_self[s, b, t] < 0.0 else 0.0 + pe_other_pos[s, b, t] = pe_other[s, b, t] if pe_other[s, b, t] >= 0.0 else 0.0 + pe_other_neg[s, b, t] = pe_other[s, b, t] if pe_other[s, b, t] < 0.0 else 0.0 + + # update the chosen option + EV[s, b, t+1, :] = EV[s, b, t, :].copy() + EV[s, b, t+1, c] = EV[s, b, t, c] + (a_self_pos * pe_self_pos[s, b, t] + + a_self_neg * pe_self_neg[s, b, t] + + a_other_pos * pe_other_pos[s, b, t] + + a_other_neg * pe_other_neg[s, b, t]) + + return {"params": params, + "choices": choices, # chosen option indices (A,B,C,D) + "outcomes_self": outcomes_self, # -1/0/+1 + "outcomes_other": outcomes_other, # -1/0/+1 + "option_pairs": option_pairs, # which two options were shown on each trial + "EV": EV, + "ch_prob": ch_prob, + "pe_self": pe_self, + "pe_other": pe_other, + "pe_self_pos": pe_self_pos, + "pe_self_neg": pe_self_neg, + "pe_other_pos": pe_other_pos, + "pe_other_neg": pe_other_neg, + } + +# ---------------------------------- +# 1Q–4α–1β FIT (Rhoads et al., 2025) +# ---------------------------------- +def rw4a1b_fit(params: np.ndarray, + choices: np.ndarray, # (B,T) chosen options (A,B,C,D) + outcomes_self: np.ndarray, # (B,T) in {-1,0,+1} + outcomes_other: np.ndarray, # (B,T) in {-1,0,+1} + option_pairs: np.ndarray, # (B,T,2) indices of shown options per trial + prior=None, + output: str = "npl"): + + beta = norm2beta(params[0]) + a_self_pos = norm2alpha(params[1]) + a_self_neg = norm2alpha(params[2]) + a_other_pos = norm2alpha(params[3]) + a_other_neg = norm2alpha(params[4]) + + # Bounds + if not (1e-5 <= beta <= 20.0): + return 1e7 + for a in (a_self_pos, a_self_neg, a_other_pos, a_other_neg): + if not (0.0 <= a <= 1.0): + return 1e7 + + # Convert choices (accepts letters or indices) + choices_arr = np.asarray(choices) + if not np.issubdtype(choices_arr.dtype, np.number): + letter_to_idx = {'A':0, 'B':1, 'C':2, 'D':3} + choices_arr = np.vectorize(letter_to_idx.get)(choices_arr) + choices_arr = choices_arr.astype(int, copy=False) + + nblocks, ntrials = outcomes_self.shape + EV = np.zeros((nblocks, ntrials + 1, 4), dtype=float) + ch_prob = np.zeros((nblocks, ntrials, 4), dtype=float) + pe_self = np.zeros((nblocks, ntrials), dtype=float) + pe_other = np.zeros((nblocks, ntrials), dtype=float) + pe_self_pos = np.zeros((nblocks, ntrials), dtype=float) + pe_self_neg = np.zeros((nblocks, ntrials), dtype=float) + pe_other_pos = np.zeros((nblocks, ntrials), dtype=float) + pe_other_neg = np.zeros((nblocks, ntrials), dtype=float) + + nll = 0.0 + for b in range(nblocks): + EV[b, 0, :] = 0.0 + for t in range(ntrials): + # get shown options + opt1, opt2 = option_pairs[b, t, 0], option_pairs[b, t, 1] + o1, o2 = letter_to_idx[opt1], letter_to_idx[opt2] + + # get probability of the chosen option + c = letter_to_idx[choices[b, t]] + shown_vals = np.array([EV[b, t, o1], EV[b, t, o2]], dtype=float) + probs_two = softmax(shown_vals, beta) # len=2 + ch_prob[b, t, o1] = probs_two[0] + ch_prob[b, t, o2] = probs_two[1] + nll += -np.log(probs_two[0] if c == o1 else probs_two[1] + 1e-12) + + # compute prediction errors + pe_self[b, t] = outcomes_self[b, t] - EV[b, t, c] + pe_other[b, t] = outcomes_other[b, t] - EV[b, t, c] + + pe_self_pos[b, t] = pe_self[b, t] if pe_self[b, t] >= 0.0 else 0.0 + pe_self_neg[b, t] = pe_self[b, t] if pe_self[b, t] < 0.0 else 0.0 + pe_other_pos[b, t] = pe_other[b, t] if pe_other[b, t] >= 0.0 else 0.0 + pe_other_neg[b, t] = pe_other[b, t] if pe_other[b, t] < 0.0 else 0.0 + + # update chosen option + EV[b, t+1, :] = EV[b, t, :].copy() + EV[b, t+1, c] = EV[b, t, c] + (a_self_pos * pe_self_pos[b, t] + + a_self_neg * pe_self_neg[b, t] + + a_other_pos * pe_other_pos[b, t] + + a_other_neg * pe_other_neg[b, t]) + + if output == "all": + return { + "params": [beta, a_self_pos, a_self_neg, a_other_pos, a_other_neg], + "choices": choices_arr, + "outcomes_self": outcomes_self, + "outcomes_other": outcomes_other, + "option_pairs": option_pairs, + "EV": EV, + "nll": nll, + "ch_prob": ch_prob, + "pe_self": pe_self, + "pe_other": pe_other, + "pe_self_pos": pe_self_pos, + "pe_self_neg": pe_self_neg, + "pe_other_pos": pe_other_pos, + "pe_other_neg": pe_other_neg, + } + else: + return calc_fval(nll, params, prior=prior, output=output) \ No newline at end of file diff --git a/pyem/utils/plotting.py b/pyem/utils/plotting.py index d71c21c..95a7afb 100644 --- a/pyem/utils/plotting.py +++ b/pyem/utils/plotting.py @@ -71,10 +71,10 @@ def plot_scatter( x = np.asarray(x) y = np.asarray(y) - # Create axes if needed created_fig = None if ax is None: - created_fig, ax = plt.subplots(1, 1, figsize=(5, 4)) + # If used standalone, give it a sensible size and turn on constrained layout + created_fig, ax = plt.subplots(1, 1, figsize=(3.6, 3.6), constrained_layout=True) # Scatter ax.scatter(x, y, s=s, alpha=alpha, color=colorname) @@ -85,31 +85,34 @@ def plot_scatter( # Pearson r annotation if annotate: - # Be robust to NaNs mask = np.isfinite(x) & np.isfinite(y) if mask.any() and mask.sum() > 1: corr = np.corrcoef(x[mask], y[mask])[0, 1] ax.annotate(f'Pearson r = {corr:.2f}', xy=(0.05, 0.95), xycoords='axes fraction', va='top', fontsize=11) - # Optional x=y line + # Optional x=y line and equal limits if show_line: - # Determine common bounds from data & current limits data_min = np.nanmin([np.nanmin(x, initial=np.nan), np.nanmin(y, initial=np.nan)]) data_max = np.nanmax([np.nanmax(x, initial=np.nan), np.nanmax(y, initial=np.nan)]) - # Fall back to current axis limits if needed cur_xmin, cur_xmax = ax.get_xlim() cur_ymin, cur_ymax = ax.get_ylim() lo = np.nanmin([data_min, cur_xmin, cur_ymin]) hi = np.nanmax([data_max, cur_xmax, cur_ymax]) - ax.plot([lo, hi], [lo, hi], linestyle='--', color='k', alpha=0.75, zorder=0) + ax.plot([lo, hi], [lo, hi], linestyle='--', color='k', alpha=0.6, zorder=0) if equal_limits: ax.set_xlim(lo, hi) ax.set_ylim(lo, hi) - ax.set_aspect('equal', adjustable='box') - + # Keep the box square without triggering excessive outer padding + try: + ax.set_box_aspect(1) + except Exception: + pass + + # A touch of margin so points/labels aren’t flush against the frame + ax.margins(0.05) + sns.despine() - # Important: don't call plt.show() in library/helper code return ax diff --git a/tests/test_compare.py b/tests/test_compare.py index 5bb8f6b..d008064 100644 --- a/tests/test_compare.py +++ b/tests/test_compare.py @@ -1,7 +1,7 @@ import numpy as np from pyem.api import EMModel -from pyem.models.rl import rw1a1b_simulate as rw_simulate, rw1a1b_fit as rw_fit +from pyem.models.rl import rw1a1b_sim as rw_simulate, rw1a1b_fit as rw_fit from pyem.core.compare import compare_models from pyem.utils.stats import calc_BICint from test_helpers import _simulate_rw_params diff --git a/tests/test_emmodel_methods.py b/tests/test_emmodel_methods.py index 426df25..f602eb4 100644 --- a/tests/test_emmodel_methods.py +++ b/tests/test_emmodel_methods.py @@ -5,7 +5,7 @@ import numpy as np, matplotlib.pyplot as plt import pytest from pyem.api import EMModel -from pyem.models.rl import rw1a1b_simulate as rw_simulate, rw1a1b_fit as rw_fit +from pyem.models.rl import rw1a1b_sim as rw_simulate, rw1a1b_fit as rw_fit from pyem.core.compare import ModelComparison from pyem.utils.math import norm2alpha, alpha2norm, norm2beta, beta2norm from test_helpers import _simulate_rw_params diff --git a/tests/test_fitting.py b/tests/test_fitting.py index 2c1e4aa..8ef1a8d 100644 --- a/tests/test_fitting.py +++ b/tests/test_fitting.py @@ -1,28 +1,27 @@ import numpy as np from pyem.api import EMModel from pyem.models.rl import ( - rw1a1b_simulate, rw1a1b_fit, - rw2a1b_simulate, rw2a1b_fit, + rw1a1b_sim, rw1a1b_fit, + rw2a1b_sim, rw2a1b_fit, ) -from pyem.models.bayes import simulate as bayes_simulate, fit as bayes_fit -from pyem.models.glm import glm_sim as glm_simulate, glm_fit, glm_decay_sim as simulate_decay, glm_decay_fit as fit_decay +from pyem.models.bayes import bayes_sim, bayes_fit +from pyem.models.glm import glm_sim, glm_fit, glm_decay_sim, glm_decay_fit from test_helpers import _simulate_rw_params def test_rw1a1b_fit(): nsubjects, nblocks, ntrials = 10, 2, 12 params = _simulate_rw_params(nsubjects) - sim = rw1a1b_simulate(params, nblocks=nblocks, ntrials=ntrials) + sim = rw1a1b_sim(params, nblocks=nblocks, ntrials=ntrials) all_data = [[c, r] for c, r in zip(sim["choices"], sim["rewards"])] model = EMModel(all_data=all_data, fit_func=rw1a1b_fit, param_names=["beta", "alpha"]) res = model.fit(mstep_maxit=5, verbose=0, njobs=1) assert res.m.shape == (2, nsubjects) assert res.NPL.shape == (nsubjects,) - def test_rw2a1b_fit(): nsubjects, nblocks, ntrials = 10, 2, 12 params = _simulate_rw_params(nsubjects, 3) - sim = rw2a1b_simulate(params, nblocks=nblocks, ntrials=ntrials) + sim = rw2a1b_sim(params, nblocks=nblocks, ntrials=ntrials) all_data = [[c, r] for c, r in zip(sim["choices"], sim["rewards"])] model = EMModel( all_data=all_data, @@ -33,37 +32,34 @@ def test_rw2a1b_fit(): assert res.m.shape == (3, nsubjects) assert res.NPL.shape == (nsubjects,) - def test_bayes_fit(): nsubjects, nblocks, ntrials = 10, 2, 10 true_lambda = np.random.uniform(0.2, 0.8, size=(nsubjects, 1)) - sim = bayes_simulate(true_lambda, nblocks=nblocks, ntrials=ntrials) + sim = bayes_sim(true_lambda, nblocks=nblocks, ntrials=ntrials) all_data = [[sim["choices"][i], sim["observations"][i]] for i in range(nsubjects)] model = EMModel(all_data=all_data, fit_func=bayes_fit, param_names=["lambda"]) res = model.fit(mstep_maxit=5, verbose=0, njobs=1) assert res.m.shape == (1, nsubjects) assert res.NPL.shape == (nsubjects,) - def test_glm_fit(): nsubjects, nparams, ntrials = 10, 3, 50 true_params = np.random.randn(nsubjects, nparams) - X, Y = glm_simulate(true_params, ntrials=ntrials) + X, Y = glm_sim(true_params, ntrials=ntrials) all_data = [[X[i], Y[i]] for i in range(nsubjects)] model = EMModel(all_data=all_data, fit_func=glm_fit, param_names=[f"b{i}" for i in range(nparams)]) res = model.fit(mstep_maxit=5, verbose=0, njobs=1) assert res.m.shape == (nparams, nsubjects) assert res.NPL.shape == (nsubjects,) - def test_glm_decay_fit(): nsubjects, nparams, ntrials = 10, 2, 50 true_params = np.random.randn(nsubjects, nparams + 1) # all random normal true_params[:, -1] = np.random.uniform(0, 1, size=nsubjects) # overwrite last param with uniform(0,1) - X, Y = simulate_decay(true_params, ntrials=ntrials) + X, Y = glm_decay_sim(true_params, ntrials=ntrials) all_data = [[X[i], Y[i]] for i in range(nsubjects)] param_names = [f"b{i}" for i in range(nparams)] + ["gamma"] - model = EMModel(all_data=all_data, fit_func=fit_decay, param_names=param_names) + model = EMModel(all_data=all_data, fit_func=glm_decay_fit, param_names=param_names) res = model.fit(mstep_maxit=5, verbose=0, njobs=1) assert res.m.shape == (nparams + 1, nsubjects) assert res.NPL.shape == (nsubjects,) diff --git a/tests/test_priors.py b/tests/test_priors.py index 5a0c413..9a085ab 100644 --- a/tests/test_priors.py +++ b/tests/test_priors.py @@ -1,13 +1,13 @@ import numpy as np from pyem.api import EMModel from pyem.core.priors import GaussianPrior -from pyem.models.rl import rw1a1b_fit as rw_fit, rw1a1b_simulate as rw_simulate +from pyem.models.rl import rw1a1b_fit as rw_fit, rw1a1b_sim as rw_sim from test_helpers import _simulate_rw_params def test_uniform_prior_and_fit(): nsubjects, nblocks, ntrials = 10, 1, 4 params = _simulate_rw_params(nsubjects) - sim = rw_simulate(params, nblocks=nblocks, ntrials=ntrials) + sim = rw_sim(params, nblocks=nblocks, ntrials=ntrials) all_data = [[c, r] for c, r in zip(sim["choices"], sim["rewards"])] prior = GaussianPrior(mu=[0.0, 0.0], sigma=[100.0, 100.0]) diff --git a/tests/test_utils.py b/tests/test_utils.py index 1088d3a..13794b4 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -2,8 +2,8 @@ from pyem.core.posterior import parameter_recovery, model_identifiability from pyem.api import EMModel from pyem.models.rl import ( - rw1a1b_simulate, rw1a1b_fit, - rw2a1b_simulate, rw2a1b_fit, + rw1a1b_sim, rw1a1b_fit, + rw2a1b_sim, rw2a1b_fit, ) from test_helpers import _simulate_rw_params @@ -18,10 +18,10 @@ def test_parameter_recovery_function(): def test_model_identifiability(): # two simple RL models cand1 = EMModel(all_data=None, fit_func=rw1a1b_fit, param_names=["beta", "alpha"], - simulate_func=rw1a1b_simulate) + simulate_func=rw1a1b_sim) cand2 = EMModel(all_data=None, fit_func=rw2a1b_fit, param_names=["beta", "alpha_pos", "alpha_neg"], - simulate_func=rw2a1b_simulate) + simulate_func=rw2a1b_sim) models = [cand1, cand2] params1 = _simulate_rw_params(10, nparams=2) params2 = _simulate_rw_params(10, nparams=3)