diff --git a/model.torch b/model.torch index 25508d0..5461b85 100644 Binary files a/model.torch and b/model.torch differ diff --git a/phononDoS.ipynb b/phononDoS.ipynb index a0c3e3b..542ec94 100644 --- a/phononDoS.ipynb +++ b/phononDoS.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "f0f362c3", "metadata": {}, "outputs": [], @@ -52,10 +52,137 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "020da470", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1522/1522 [00:00<00:00, 12359.69it/s] \n" + ] + }, + { + "data": { + "text/html": [ + "
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mp_idstructurephfreqphdospdosformulaspecies
0mp-1000(Atom('Ba', [0.0, 0.0, 0.0], index=0), Atom('T...[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.0, 0.1603814665137704, 0.366293016390463, 0...{'Ba': [0.0, 0.17004785173719497, 0.4321591874...BaTe[Te, Ba]
1mp-1002124(Atom('Hf', [0.0, 0.0, 0.0], index=0), Atom('C...[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.02337731725373556, 0.030910686260937723, 0....{'Hf': [0.026541048236378005, 0.03587084551615...CHf[C, Hf]
2mp-1002164(Atom('Ge', [0.0, 0.0, 0.0], index=0), Atom('C...[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.0, 0.0017221473876927959, 0.005981246148731...{'Ge': [0.0, 0.00316167053214679, 0.0109190651...CGe[C, Ge]
3mp-10044(Atom('B', [4.440892098500626e-16, 6.194849927...[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.0, 0.002277293012378372, 0.0078646582782471...{'B': [0.0, 0.00029269193672558846, 0.00105324...AsB[B, As]
4mp-1008223(Atom('Ca', [0.0, 0.0, 0.0], index=0), Atom('S...[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.0, 0.258870972416879, 0.5505201512544314, 0...{'Ca': [0.0, 0.11150000312651394, 0.2215562000...CaSe[Se, Ca]
\n", + "
" + ], + "text/plain": [ + " mp_id structure \\\n", + "0 mp-1000 (Atom('Ba', [0.0, 0.0, 0.0], index=0), Atom('T... \n", + "1 mp-1002124 (Atom('Hf', [0.0, 0.0, 0.0], index=0), Atom('C... \n", + "2 mp-1002164 (Atom('Ge', [0.0, 0.0, 0.0], index=0), Atom('C... \n", + "3 mp-10044 (Atom('B', [4.440892098500626e-16, 6.194849927... \n", + "4 mp-1008223 (Atom('Ca', [0.0, 0.0, 0.0], index=0), Atom('S... \n", + "\n", + " phfreq \\\n", + "0 [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "1 [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "2 [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "3 [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "4 [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "\n", + " phdos \\\n", + "0 [0.0, 0.1603814665137704, 0.366293016390463, 0... \n", + "1 [0.02337731725373556, 0.030910686260937723, 0.... \n", + "2 [0.0, 0.0017221473876927959, 0.005981246148731... \n", + "3 [0.0, 0.002277293012378372, 0.0078646582782471... \n", + "4 [0.0, 0.258870972416879, 0.5505201512544314, 0... \n", + "\n", + " pdos formula species \n", + "0 {'Ba': [0.0, 0.17004785173719497, 0.4321591874... BaTe [Te, Ba] \n", + "1 {'Hf': [0.026541048236378005, 0.03587084551615... CHf [C, Hf] \n", + "2 {'Ge': [0.0, 0.00316167053214679, 0.0109190651... CGe [C, Ge] \n", + "3 {'B': [0.0, 0.00029269193672558846, 0.00105324... AsB [B, As] \n", + "4 {'Ca': [0.0, 0.11150000312651394, 0.2215562000... CaSe [Se, Ca] " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# load data\n", "df, species = load_data('data/data.csv')\n", @@ -73,10 +200,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "bcfe78e0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+/Fy7di1ffPEFR48etckJnUx1/vx52rRpw4YNG2jZsqXecayOGtUlHdZc/BTTzZ07l7p16zrMrQJvb2/8/PwyPPWnI1HFLx2q+CmKfVKtvTZo/Pjx+Pn56R1DM6tXr2bnzp1m366UMsVO0PbM0Y7XElTx08mNGzeYP3++wwxpbjAY+PrrrylSxLRBCDJi9uzZjBkzxuzbtVZHjx6lbdu2REdH6x3Fpqnip5MZM2YwZMgQ8ufPr3cUTaxfv54KFSrQsGFDs2974MCBeHl5MXPmTLNv2xo1atSIQoUKMWDAAHUGmAWq+OlASom/vz/Dhw/XO4pmLl26xBdffGGRbRcsWBAvLy9mzZqV4YFQbZmTkxMrV67kwYMHDlPwLUE1eCh2IzAwkJIlSzpMl6HQ0FCcnJwc5uohNaq1Nx2q+CmKfVKtvTYiMjLjI5DYA72O9/jx4wQEBOiybz3cvXuXI0eO6B3Dpqjip6HY2Fhefvll/P399Y6imb59+2Z4AANzOn78OB07diQkJETzfevh33//pVu3bg41OEZWqeKnobVr11K5cmWHGazUz8+Po0eP0qVLF833PXLkSNq3b4+Hh4dDdAlp1qwZ8+fPp3Pnzg51xpsVNlf8hBD9hRBnhBDhQoirQojxQoiceudKT0JCAlOnTmXs2LF6R9HMtGnT8PT0JHfu3Lrsf/r06dSvX98qZmrTQs+ePRk7dixXrlzRO4pNsKkGDyHEQGAZ8DHwB1Aj8evdUsr30llX1waP2NhY1qxZw8CBAx1m9JaNGzfSunVrChUqpHcUxY45RGuvEOIMcFtK6ZHkvVHAdMBNShmaxrqqtdfBSSkd5hfPM45wzI7S2isBQ7L3YhP/VHP+KWkaNGgQa9eu1TuGZhYvXsyIESPUhOipsLXitxjoLIRoI4yqAMOB1VLKpzpnS9XmzZuJiorSO4Zm9u3bx/379/WO8R+jR49m5MiR7Nu3T+8omujduzcHDhxg+vTpekexTlJKm3phvMSVGM/4JOAN5M3AelIPFy5ckMWLF5eRkZG67F9rkZGRslixYvLixYt6R0nRgQMHZJEiReT9+/f1jqKJwMBAWbZsWfnXX3/pHcViEn+2Ta4ltnbPbynQAfgMOAeUASZgPINtLqWMSrb8EGBI4pf19TjWAQMGUL16db788kvN962HxYsXs2vXLnbs2KF3lFTdvHmTChUq6B1DMwEBAZQsWZJs2bLpHcUi7L7BQwhRGbgKvCOlXJfk/UrAdWCAlHJVGutLrY81ODiYatWqcfXq1UzNV2FrpJTUrVuXBQsW0LRpU73jKA7CERo88iX+GZPs/Wc9WPNqmCVD3NzcuHbtmkMUPjD+Jzx06JBNFT4vLy+Huh979uxZh3rCKC22VPz+Bo4BU4UQ7YUQpYUQDYFVwD1gi57hUlOgQAG9I2jK1o531apV9OvXj/h4x+gscPToUTp27EhwcLDeUXRnM5e9AEIIN2Ac4AGUBoKAg8D3Usrr6ayr+WWvYv1iYmLo2LEjL7/8MvPmzbP7PnEAn3/+OUePHmXv3r3kypVL7zhZ5giXvUgpg6WUo6WUlaWUuaSUZaWU/dMrfFqLiIjAw8OD2NjY9Be2E4MHD+bq1at6xzCZi4sLW7ZsITIy0mFG3Jk8eTKvvvoqt2/f1juKrmzqzC8rtDzzmzdvHt7e3mzZYpVX4mZ3+vRpunbtyr///kuOHDn0jqM4mMye+dln27eODAYDM2bMYN26dekvbCemTJnCqFGj7KbwSQd4JCwpRzveZ2zqstcW3Lt3j06dOtGoUSO9o2giPj6e7NmzM3jwYL2jmEV8fDwtWrTg7NmzekfRzEcffcTKlSv1jqE5ddmrKMn8/vvvDB8+nCNHjjjE2IuXL1+mZcuWrFq1inbt2ukdx2R238k5q1TxU0wxb948lixZwtmzZ3F2dtY7jsX5+PjQrVs3zp49S+nSpfWOYxJV/NKhRfF7+PAhRYsWteg+rIm9H+/169d56aWX9I6hGVs9Xofo6mLNjh8/TtOmTR1m+KCwsDBefvllux4l2RYLQVY42vGq4mcmU6ZM4ZNPPnGYVrOffvqJtm3bUqJECb2jWJyUkl27dqX6iy0mJoaAgAD++ecfAgMDMRiSDzlpe7y9ve2/32NmhoKxxRcWHNLq8uXLskiRIjI8PNxi+7Am0dHRsmTJkvLMmTN6R9FERESErFOnjpw4ceIL71+6dEkO/egjmc+1gHQrXlwWr1BBFixWVLoWKiRHjR4t//33X50SZ93AgQOlu7u7NBgMekdJF44wpFVWWPKeX0hICBcuXKB58+YW2b61MRgM7N27l06dOukdRTN3796lcePGfP/993Tt2pXe/fpx7MQJqrzZmarunclbrNjzZUNv3+bqtp1c3e1Fl86d+GXJUnLmtPo5tl4QGxtL586dqVSpEosWLbLqKxrV4JEO1dqrZNXly5eZMWMGPsePkbN6NV4b7olz9uypLm+IjubopKnkj4jE+8+9us1il1lhYWF88sknzJ8/n3z58qW/gk5U8UuHKn5KVhkMBpq1aomhfDkaeH6YobMhmZCAz/8mU845Ozu3bbPqMyhbpVp7dRAaGsrSpUv1jqEZKSULFixwqPHvktq2bRv3nj6lwUdDn/3ApbuOcHKi8Rdj8D1/niNHjmiQ0nLs7eRBFb8sWLRoEYcOHdI7hmYOHjzI3Llz7eYZXlPNnDePKj26I5yciAwOZuuQj4gKDU13Pefs2Xmp65vMmjfP8iEtJCEhgXbt2uHr66t3FLNRxS+ToqKimDt3Lp9//rneUTQzZcoUxowZ4xBPPCR3+fJl/rl8mQotjY1aud3cKPlKPf4Y/QWG6Oh01oaqnTuyx8uLBw8eWDqqRTg5OeHp6Ym7uzs3btzQO45ZqOKXSd7e3jRo0ICaNWvqHUUT9+7d4+rVq/Tv31/vKLo4evQoZV9r8EIDx2sfDsa1TBkOT5mR7vou+fJRsmYNmz5z6tq1K9988w1dunSxi76MakirTOrcuTNt27bVO4ZmSpQoweXLlx32kvfJkydky/fiNDFCCFqM+5yIh0EZ2oZL/vyEZuAy2ZoNGzaM1q1bkz2NVm5boc78ssDRCoGjHW9SLi4uJKRwtuOcPTv5S5XM0DbiY2Ntrr9fSqpWrap3BLNQxU9RMqB06dI8DQhMc5n42FjunD6T4mdSSkJu3aJUqVKWiKcLKSV79uyx2VZgVfxM9NdffzFs2DC9Y2gmKCiIZs2aOczsZqnp0KEDITdvEhqQ+rwXEUGP+OvbHwg4dvw/n90/fwEXBK+99polY2oqNjaWcePG8eOPP+odJVNU8TPRlClTaNiwod4xNDN//nyqV6/ukC28Sbm4uPD+e+9xdev2VJfJX6ok7SdPwPuH//Hwn8svfHZty3ZGeHri5GQ/P3IuLi7s2rWLFStWsHz5cr3jmMx+/iU0cPr0afz8/OjTp4/eUTQRHh7OwoULGTNmjN5RrILnsGFc8/qTx9f/TXWZ4rVq0uLLz7n397nn7909+zd3TvkycOBADVJqq3jx4vzxxx8cO3bM5i5/1eNtJjhw4ACBgYH069fPTKms282bN1m7di1fffWV3lGsxm+//YbnqFG0nTkVtwrl013+waV/8B77FZvWraNNmzaWD+iA1LO96VDP9irmsmLlSkZ8Noqafd6hSueOuOT/70P/kcHBXNm2k8ubNrNmxQq6dOmiQ1J9SI1ng1PFLx2q+CnmdObMGSZNm8Yfu3dTsWVzXKtWJXvuXBgiI3l8/gIBx0/wVo8etGv9Bps2bWLDhg1ky2b/3WqDg4Px8PDg999/12yKA1X80pGV4hccHExcXJzNzVfx5MkTVq5cyaGjx3n6NAK3gq682ak93bt3x8XFJdX1EhISuH79OlWqVNEwrW16+PAhK1as4J8rV3jy9CmuBfJTr1Zt+vfvj6urKwaDAXd3d0qXLs3PP//sEKO6fPvtt3h5ebF//37y5Mlj8f2p4peOrBS/cePGERYWxvz5882cyjLCwsIYOWo069evJ2+FejiVqo1TjlzERz0l4dZJYh/d4pOPPfnum69TPBvZuXMn3333Hb6+vg7xw2pp4eHhtGzZkgEDBjB8+HC941iclJL333+fqKgofvvtN4vvTxW/dGS2+IWFhVGxYkVOnjxJxYoVLZDMvIKCgmjSvBWhuctQoFFvsuV1+88yMY8DCTu0lFcqlWDnts3/eXKjWbNmeHp60rt3b61i270HDx7g7OxM4cKF9Y6iCYPBwM2bNzW5elDFLx2ZLX7Tp0/n9OnTmvwGy6q4uDhebdiY+znL4dqkf5pnbTI+jse7p9GxYXVW/rLs+ftHjx6lX79+XL161SHuUSm2TxW/dGS2+N2/f5/Y2FjKli1rgVTmtXXrVj4YOY7CPSdn6HI1ITaKwOUfcuGs7/Oz2sjISG7cuOEwo9Xo4dGjRwQGBlK3bl29o2jCYDBw9OhRWrRoYZHtq5GcLaR48eI2UfgAps2aS46aHTJ8n84pRy7y1WjNvAULn7+XO3duVfgs7MyZM3Ts2JHr16/rHUUT9+7do3fv3uzcuVPvKC/I9JmfECIbUAeoBRQCnIEQ4DrgK6V8aq6Q5mDvXV2CgoIoW6ESZYf+glO2jI++EvM4kLAdP/Dogf1OPm6NlixZwpQpUzhy5AjFksz8Zq9OnjxJ586d2blzp9kfD9XszE8IUVMI8TPwGDgFfAf0AroCnwFewGMhxA4hRAdTt28tvL292b17t94xMuzBgwfkdi1sUuEDyOFanJDHjwgICGDOnDkWSqckN3jwYN59912bHtzUFK+99hq//vore/fu1TvKcybd0RZC/AQMAnYm/uktpQxNtowL0Ah4B9gohDgB9JRSBpslsQaklIwbN47Ro0frHSXDnJyckAkJJq8nZQJCCGbNmmVXD93bgm+++UbvCJrq3LkznTt31jvGc6Y25x0G5kgp/0ltASllDHAQOCiE+BZ4x5YKH8ChQ4cIDg6mW7duekfJsJIlSxL15DHxMRE4u2S8Y2lM0C2KFC/JihUrOH/+vAUTKop1MelXvZRydVqF7xkhRHEhxHgp5UMppc1dS+3du5fRo0fb1DBOrq6utG3XnqeX9pu0XvSlvbRu0YwePXpQunRpC6VT0rN06VK+/fZbvWNoxtfXl+7du+s6F4hZu7oIIZoDnhjv/0VKKQuabeP/3VdhjGeY94EOUso0v4umNnho/XC2ORw8eBCP3gMo1mdmhu79xYUHc2flcPz/vUaRIkVs7njtycOHD2ncuDFjxoxh6NChesexuLi4ODw8PChatCjLly/P0v893bq6CCFyCyGGCiHOAfuBpsD/AIsN9C+EcAZ+w5j/rfQKXyb3Ye5NWlzz5s1p3uhVQv6ci4yPS3PZ+KinPN4xkbFjRlO0aFGbPF57UrRoUby8vBg/fjwHDx7UO47FZcuWjQ0bNnDp0iVmzEh/9jtLyEpXlyoYz/IGAHmBvUBroIaUMvXRHs1ACDEJ+ABoKKXM0CSiGTnzS0hIsPmb/tHR0XTx6M7Zf++Rt2FvcpWq/kJhkwnxhP97ivBjaxjQqzuzZ063+WO2J1euXKF8+fJpDjxhT4KCgoiLi6NEiRKZ3obFnvAQQvQGRgG7pJTfCyE8MBa9NkAgsBxYLqUMEEI8BepktCBlhhCiK8azvjeklEdNWC/d4jdixAjq1q3LoEGDshZSZ3FxccxfsIAZs+cRGSdwLl0b6ZwTJ0M4Uf+eoEK5snz9xRji4+PZv38/P/30k96RFSXTLFn8bgA9gSNAMSAYeAiMBDZIKROSLGvR4ieEKAf8DdzC2FKdFzgBfCOlvJrOumkWv6CgIKpUqcI///yTpd9C1kRKibe3N6dOnSI8PJwCBQrQpk0b6tWrh5SSevXqMWHCBIcaaNOW+Pn54erqSvHixQEIDQ1lxYoVbN65g8ePH+MknChStAh93+5J7969yZ07t86JsyY0NBR/f3+TH/vLbPFDSpnmC5gNnAYOJH49FwgFIoBfgaZJln0KVExvm5l9YTzjiwHGArWBdoAv8AAoms66Mi3ffvut/OCDD9Jcxp54eXnJGjVqyPj4eL2jKKmYMmWKfOWVV+S1a9fkwPffk3kL5Jcvt2sj20/5n+y2dLHstmSRbDvhe1mlWVOZv2BB+cmIEfLJkyd6x860ffv2yWLFikk/Pz+T1kv82Ta5nmTonp8QoqCUMiTJ13mA/sBHQE3gCrAM+B6oJS1w5ieEyAk8AaZLKb9K8n4JjJff30spf0i2zhBgSOKX9dM61pUrV/L6669TuXJlc0e3Sj4+PoSHh9Ohg80+hGP3pJT06tWL7Tt2UL2rO7X7vUPuQoVSXDbs7l3OLV9J/K1b7NvzJyVLZmwidWuzfPlyJkyYwNGjR5+f8aZHt1FdhBAt+P/uLdmA34GZUspjWdrwf/dTArgLdJZS7k72WSDGe5Kp9hGw92d7Fftz584d6jdsCG4FaTluLAXLl0tzeSklf/+yktCjxzhx5CgFChTQKKl5TZw4kWrVqtG9e/cMLa/7kFaJxelDYDDGe4PHpZRNzLJxnndveQhMk1JOTvJ+KSAA+ERKuTCN9VXxU2xKJ3d3HhcrwivvD8zwOlJKjkyZTpNSZVi8YIHlwlkR3YtfkiDZgLeAj6SUZh3ASwjhCUwEPgYOAeWAGUAOoIGUMjaNdVMsfufPn6d06dK4uf13xGN7FBgYSGxsrE2MSu3IAgICqFGnDr02ryd7rlwmrRv+8CHb3n2fu7cDyZs3r4USWg9NOjkLIRYKIQYnnoWlSEoZJ6VcL6VsIYToIITYKIQwy7+AlHIBMBz4CrgGbASOAS3SKnypSUhIoE+fPpw6dcoc8WzC999/z4oVK/SOoaRj0eLFVO7QzuTCB5C3aFFKvlKP1atXWyCZtlavXm2xeaNN7d16HPgGuC2EmC2EeFMIUUYIkVMIkU0IUVQI0VII8Y0Q4hLG4nQeMNsTGFLKFVLKalLKHFLKYlLK4TLZyDIZtXv3brJnz067du3MFc+q3bt3j02bNvHJJ5/oHUVJx9r166nUsX2m16/QoT0rfltrxkT66NChA5s2bWKBBS7hTRrVRUq5UgixHmO/v37Ae0DyIUTigXMYu8H8KqUMMkNOi5g2bRqjR492mEe75s2bR69evRxmEh1b9vjRI/JlsLUzJflKFOd60CMzJtJH4cKF+eOPP2jWrBnVqlXjjTfeMNu2TX6uSUoZI6VcJaVsDxQAXsI4fl8T4GUgn5SygZRymjUXPjAOUT9//nzGjx8PwPjx403+uxDi+Xvm+Htmc2Qk06RJk9i9ezcxMTGW+YYqZpMQH49wzvxjh8LJieDgYKv6/5fZHBUrVqRQoUJMmzYt09+PFL9HjtICmlKDx+PHj2natCkffvghI0aM0CmZduLj4+nZsyc5cuRgzZo16pleK1a8dGlaz5pGgTKZG2bsju9pAlf/xpnjJ8ycTHuPHj2iSpUqXLp0KcWnr9QERplQqFAhvLy8mDVrFgEBAXrHsThnZ2dWr15NYGAg27Zt0zuOkoaOHdpzc59pYzMmdcv7AO6drGfU5KyYP38+b731ltkfO3XoM79noqKiyJWJVjVbFRUVRc6cOR3mXqct+vvvv3mjUyd6bFiDk4nzJ8eEh7Oxxztc8/PL8FMS1mzz5s3Url2bl156KcXPraafn7VSnZwVW1O/USNc27ehiomtvmdXrqb4w8ds3bTJQsmsi7rsNZP58+cTGBiodwzNeHl5OcTgmbbo5wUL8J2/iPvnL2R4nZsHD3N98zZmTp1qwWT2wSzFTwhRRAixRAjxhxDio2Sf7THHPrQSFRVFx44dCQ0N1TuKJrJnz87bb7/NxYsX9Y6iJFO/fn02rF2L95ffcG3PXhLi41NdNt5g4OLG3zk1YzZeO3faxRM8p0+f5v79+xbbvrnO/H4F/IFFQHshxJbEx9wAipppH5oYPXo0rVq1omvXrg7RJeSNN95g9uzZdOrUidu3b+sdR0mmffv2/OXlReCmLaxy78651WsJf/iQhLg44g0Gwu7c5fSS5Wx4qzdxJ09z/MgRXn31Vb1jZ5mUkoEDB3Lu3DmL7cPUqStTU1JK+b/Ev28XQowHdiSO+mxTns1hO2fOHBIyMQ+uLerTpw+xsSY/HejwpJT8/fffXL9+HYPBQJEiRWjevLnZh6Bv0KAB3d98kytXruASFs6OQUN4+uQJQghc3dx46623+GX/fmrUqGHW/epp9+7dZMuWzaJPX5mlwUMIcRJwl1LeT/LeNxgnMyoipXwlyzvJItXgoZhLbGwsq1atYvrsedx98IjcJSohhBNxTx8RG3qfIYM/YMQnH1OqVCmz7C8mJoayZcty7Nix55ezCQnGyebttcW+Xbt2DBo0iHfeeSfdZXVt7RVCtAd+ArpLKc8kef874Fsppe4T4Gal+D19+pR8+fKZOZH1ioiIIFeuXKoTdApCQ0Np3+lN/n0YTq56HuSpUA8h/v/7FPM4kMgLXkRfP8YfO7fx+uuvm2W/9+/ft4tuKxkVFBREwYIFyZaBbj66d3URQhQAkFI+SfZ+Dyml7m3umS1+UkoaNGjA6NGj6d27twWSWR9PT09cXFyYOXOm3lGsSkxMDM1avsGtOFcKtvwA4ZT67/Twf0/xZN8Cjh4+SM2aNTVM6Xh06eoihHB/9ncp5ZOkhU8IMTzxfd0LX1YIIVi+fDnDhw9n//7M97i3JRMmTGDPnj2q+CXz888/cyM4loKtBqdZ+ADyVmpA3oa9GfiB/U9Abquyel2zLnGMv5zP3hBClBVCeAOTsrhtq1G7dm3Wr1/P0KFDHaJhoGDBgnh5eTF37lyuX7+udxyrIKVkxux55Hml2wuXuWnJX7MNV65ezXQ3ooSEBAYNGkRISEj6C9uJ8ePHc/bsWU32ldXi1wRoDpwRQtQVQrwHXMA4pWSjrIazJq1ateLs2bPkyJFD7yiaKFOmDJcuXUr1kSJH4+PjQ1h0HLnKZLxFVThnI0+NtsxbuChT+9yxYwcXLlzA1dU1U+vbmsDAQObOnUu5cmnPVWIuWerqIqU8K4SoD0zAOKJyAvAdxgmM7K6fSJ48yYcutG+Odrxp8fPzw6V4FZNbV7MXr8KFS4dM3p+UksmTJzN27Fi7bdFNbtasWQwcOFCzKSXM0ZwngOyJr1jgiT0WvqQMBgNTpkwhOjpa7yiaWbp0qUOMfJOamJgYpHN2k9cTztkz1Vk+JCSEYsWKZXgGM1snpeTOnTt8+umnmu0zqw0ezYGLQDeME4h/BkwXQuwUQtjUkx2mcHZ25syZM/Tv399hOkKHhYXRoUMHgoOD9Y6ii0KFCkGk6ffe4sIfUyQTI2e7ubmxdetWnJ117yWmCSEE69ato0yZMprtM6tnfn8BJ4A6UkpvKeVyoC7GEZ4t91yKzpycnFixYgVBQUF8+umnOELn6VGjRtGhQwc8PDwc6oz3mfbt2xN26wJxkU/SXziJ+Os+9Ov9toVSKVmR1eL3rpSyb9IJhKSUNzE2gszK4ratWs6cOdm6dSvly5fXO4pmpk+fjru7O3FxcXpH0ZybmxseXbvy9OLeDK8TG3yX6Ic36NGjh0n7CgsLMzWeTdPreNV4foqSQRcvXuT1pi0o7PENOYtXSnPZBEMMQZu/49PBffnmq3EZ3setW7d4/fXX8ff3d4ieBXFxcVSrVo1t27Zl+tlkNZ6fFYiIiNA7gqYc7Xhr1qzJiuVLCNr2I+E3Tqd6u8MQFsSjLePp0OxVvh73pUn7mDlzJv369XOIwgewadMmihcvrsugDOrMz0xCQ0OpXbs2O3bsoE6dOhbbj7WQUtKkSRM8PT3p27ev3nE05e3tzbvvDyEyTpDj5ba4FHsJ4eSMISwIw9UDRNy+xKhPRzL+229Mej768ePHVK5cmYsXL1KyZEkLHoF1kFLyyiuv8OOPP9KlS5dMb0f3Z3utnRaXvRs2bOCzzz7Dx8dHs46aerp06RKtW7dmzZo1tGnTBvj/YZ7u3LlDTEwMBQsWpH79+hQoUEDntOYlpcTb25s58xdx5do1DLEGihYtyqD+79C3b1/y5s1r8jafPHnCgQMH8PCwuZHgMiU+Pp7169fTu3fvLA2ioYpfOrS65zdnzhz27t3Lzp07Lb4va3Do0CEGDRrEsWPH2LhxI4vmzSbqaQiVi7uSw1kQHBHLpduP6dGjB57DR1K3bl29Iyt2RhW/dGjZ4BEeHp6p3/y26s8//2RA33doVLEgg5uUoXnVoi88lfDgSRQrjviz7EgAnT26snDxkgwNVaQoGaGKXzpUa69l7N+/n15vdeXn/nVpUyPteVWfRht4d/lp8parycbN2xymA296DAYDa9euZcCAAQ7zKNv69evp1KmTWcbJVK29VigkJIR58+bZbSfoW7du0atHN34d9Eq6hQ8gX87srBvSgMf/nuebr0xrBbVn69ev59dff3WYwnft2jU+/vhj3Y9XFT8LcnJyYsmSJUy102kE582ZzTuvlaZ51WIZXidHNmeW9K/L4kWLHK4zb0qklEydOpWxY8fqHUUz06dPZ9iwYbrfGlLFz4IKFCjAH3/8wcKFC1m9erXeccwqKiqKFb/+wvtNy5u8bsmCuWlRrTirVq0yfzAbc/LkSZydnWnf3rSJyW1VREQE27dv55NPPtE7iip+llaqVCn++OMPu7v03bx5M/XKFaRikcz99v6gSWl+WjDHzKlsT8OGDfHx8dH9ElArefLk4fr16xQpUkTvKGabulJJw8svv8zLL7+sdwyz8vPzo0HpzF+2NKhYiGs3jpoxke1ytHETreV41ZmfDiIjI/WOkGXhYU/I7ZL51tpc2Z2JiTU45CAJinVQxU9jvr6+1K9fn8ePH+sdJUvyFXAlPDrzhSsiJo6cLtkdtr/f5cuXGTBggN4xNBMdHU379u2t6nlwVfw09uqrr+Lu7s6bb75JVFSU3nEyrXbt2hzxf5rp9X2uBVGzelUzJrIt06ZNo3LlynrH0MyqVatwcnKymktesOHiJ4RYLISQQojyemcx1aRJk6hYsSKTJtnuBHfu7u5cexjO5bumDe75zNIjgQz7RLshy61JYGAgW7duxdPTU+8omoiPj2fatGlW153HJq85hBADgT5658gsJycnli9fTnx8vN5RMi1Hjhx8MORDfj68mVm9TBvF5kZQOL43H7O5Vy8LpbNugYGBjBs3TrOJevT26NEj2rZtS4sWLfSO8gKbe7xNCFEPOAx8AiwHKkgp/TOwnnq8zczu379P/Tq1mNa9Ku71SmdonfBoAx3nHOWdIcP5fKx6ykPJOod4vE0I4QZsxjgh+n6d45jN9evX2bRpk94xTFa8eHG27/Zi5IaLbDh5K93lg8KicZ9/nHpN3yB3nnx21/dRsS02U/yEEE7AGuAyMFHnOGZlMBjw9PRkz549ekcxWf369dl34DAT/rxN+9lH2XjyFjGGFy/n/e4+YfSG89T/4S/a9RjArLkLWLZsGRMn2tU/Y7qio6N59OiR3jE0FRgYqHeE1EkpbeIF/AjcAtwSvy4PSKB8GusMAXwTX9Ka+fj4yMKFC0tfX1+9o2RKbGys3LRpk2zV7HVZqEBeWe+lUrJR9bKySumisnhhN/nVuC9lQEDA8+Xv3r0ry5cvL3/55Rf9Qmts0aJFsnv37nrH0MzZs2dl6dKlZVxcnEX3k/izbXJNsYl7fkKILsAmoIWU8kTie+WBm9jRPb9t27bh5uZGs2bN9I6SJXfu3OHu3bvExMTg6upKlSpVUpyT4sqVKxw6dIjBgwfrkFJbcXFxVK1alRUrVtC0aVO942iiT58+1KtXjzFjxlh0P3Y9np8QYhvQGQhP8rYTkA94ClyTUtZPZxtWX/wU+7V+/XrmzZuHj4+P3lE0cePGDV577TVu3LhB/vz5Lbovey9++YBCyd4ujbHVtxlwVUr5MJ1t2FTxk1ISGxuLi4uL3lE0Ex0dTc6cOfWOYRH37t3j8ePH1KxZU+8omoiIiODcuXM0btzY4vuy69ZeKeVTKaV/0hfw7E5qYHqFzxYtW7aMt99+22Gefb1w4QJ169YlKChI7ygWUaJECYcpfGAcvECLwpcVNlH8HNGAAQOIjo7G09PTIbqE1KpVi7feeosuXbpY1fOfiv2y2eKXeAYoMtLYYYty5MjB77//zqlTp9i2bZvecTQxYcIEqlWrxvfff693FLM5f/68w/z7gXHyrlmzZtnEL2ybuOdnDrZ2z++ZJ0+ekD9/focZ7NJgMBAbG2tVD8Bnxdtvv02TJk0YOXKk3lE0MWvWLI4dO8aGDRs026ddN3iYg60WP8V2Xbt2jcaNG3Pz5k3d56vQQmxsLJUqVWLr1q3Ur59m5wuzsusGD8Xo4MGDnDp1Su8YmgkICLDJx/6e2bZtm1VM1KOV48ePU6NGDU0LX1aoMz8b8uyH6fDhw1SqVEnvOBZ39epVWrRowbJly+jUqZPecTIlPj7eoeYn1uN41WVvOuyh+AH89NNPTJ8+naNHj1rFJDCWdvz4cdzd3dm1axcNGjTQO45ihTJb/GxyPD9HNnToUKKjo3n69KlDFL9GjRqxfPlyQkND9Y6SYVJKh2mgesYWj1md+SmKmc2YMQMnJyc+/dQxRqr28fFhwYIF/Pbbb7rsXzV4OKjY2Fib6FNlLlJKYmJi9I6RqpiYGGbOnEmrVq30jqKZKVOmWN0ozRmhip+NGzlyJD/88IPeMTSzZs0aunfvbrWP/a1evZpatWpRt25dvaNo4uLFi/j6+vLuu+/qHcVkqvjZuO+++46VK1eydOlSvaNoolevXkgp+fDDD63yjDd37tx8++23Ftn2hQsXGDb0A8qUKEruXC7kzZ2LimVKMuazUdy4ccMi+0xPZGQkU6dOJVeuXLrsPyvUPT87cO3aNVq0aIGPjw8VK1bUO47FhYeH06pVK0aPHk0vB5gE6fLlywx5713+vXaVQU3K8farpSleICcSCAyOZPWJ26w9dovXGjbk5+UrKFWqlN6RNaW6uqTDnosfQHBwsMPMBgYQGhpKvnz57L4P3bFjx+japRPjOr7EgCYVyO6c8sVaVGwc8/Zd59cT9/nT+wDVqlXTOKl+VPFLh70XP0VfN2/exM3NjQIFCphtm1evXqV540YseKcm7WuVzNA6K4/cZJp3IMdOnaZ48eJmy5JcaGgooaGhlC9f3mL7yCjV2qs8t379eh48eKB3DM2cOHGCkydP6prho48+YuPGjWbd5tjPRvJJq3IZLnwAA5pUoFO1AkycYNlGsHnz5tl8Q5sqfnbon3/+oUuXLoSHh6e/sB149OgRHh4eXLt2TZf9nzt3jvPnz9O/f3+zbTMwMJCDBw/xfjPT7+F+/EYl1qxebbFxESMjI5k/f77F5+awNFX87ND48eOpXbs2PXv2xGAw6B3H4jp37syPP/5Ihw4ddDnjnTZtGiNGjDDrlAM/LV5Ez9fKkjdndpPXLeOWh8aVi7B69Wqz5Unql19+oXHjxlSvXt0i29eKuudnpwwGA99//z2ff/65xSeQsRZz5syhffv2mt/s9/f3x83Nzazf5yavvcLXzVxpVrVoptb/7bg/f4UWY/1m8w+kGhoaSlhYGGXLljX7tjNDNXikw9GKn2LbalSpyC/vVOHlUq6ZWv/Pi/dYfCGBP/cfNm8wK6QaPJQ0xcbG6h1BUwaDwSo7QWdUtmzZiI1PyPT6sXEJKc6VrPw/VfwcgJSS1q1bs337dr2jaGbs2LEWe9LimeXLl+Pr62uRbZcsWYobDzPfYHUjKJwSpcqYMZFxMN3169ebdZt6UsXPAQghmDlzJu+//z7Hjx/XO44mvvjiC9atW8fixYstsv3w8HDGjh1r1n59SfUb9AErTtzL1LpSSlaeuEP/ge+ZNdP48ePtqgFNFT8H8dprr/Hrr7/Su3dvoqOj9Y5jcUWLFsXLy4vvv/+ey5cvm337S5cupWXLllSuXNns2wbo0aMHF++Ecu3BU5PXPXz1Idly5adZs2Zmy3Py5Elu3rxpV48TquLnQDp37oyvry85c+bUO4omKlWqxIULFyzSJcPHx4exY8eafbvPuLi4MGToMMZt+Yf4hIzf+4uMjePb7Vf4ZNQYsw4uevDgQUaPHk327KZ3vbFWqrVXUTJBi5GLY2Nj6dS+DcXj7jOvT91Un+t9JiImjgHLfSlSrSGr1q4zez5rHa1ZtfYqJklISGD58uV2dQ8nPVu3buX+/ftm2ZYWRSBHjhxs3bGb4Nxl6TL3KH9evEdCwn9/gRviE9hy+jZtZvpQomYTflm52iL5rLHwZYU683NQcXFxdOvWDTc3N3799Ve7+4+dkh9//JEtW7Zw8OBB8uXLl6ltxMXFkS2btlPfxMXFsXLlSubPnk7oo4f0qFecYvldkFJyOzSaDb53qVK1Kh+PHE2PHj3M+m+px/GaSnVyTocqfv8VERFB69atadu2LRMmTNA7jsU9GwTV39+fHTt2ZKofXMuWLZk4cSKNGzcmNDSUDRs2cO36vxgMBkqVLEGPHj2oUKGCBdIb8586dYrt27fxOOgBTsKJIsVL8vbbb1OjRg2L7HPMmDGULl2aESNGWGT75pDZ4oeU0iFexkNVknv48KH88ssvZXx8vN5RNGEwGOQXX3whHz9+bPK6Pj4+skKFCvLmzZtywMD3ZO68+WXRWs1l4Wb9ZJEW78qir3aWufO5ylZtO8jjx49bIL22QkJCZMGCBaW/v7/eUdKU+LNtck1QZ36KkkHu7u7UqVOHxUuW4VSxCfnrvUm2vAVfWCbBEEPYPwd5enwty39eRM+ePXVKm3WTJ0/m0qVLrFq1Su8oaVLz9ipmYTAY7Ko7Q3oyek9LSkn9+vWZv+gncrzam/w1Up6dzSm7C6512pGzRGXeGzKMokWL0rJlSzOn1kbVqlXx8PDQO4bFqNZe5bmwsDBq1aqFn5+f3lE006FDB7Zs2ZLuckIIHoc8QZR7LdXCl1TOohVwbTWEj4bb7ty93bp1s/lhq9Kiip/yXP78+fniiy/o2LEj9+5l7tEqWzNlyhSGDBnCkSNH0lwuMjKSX379lXx1O2d423lfasidew85depUVmMqFqCKn/KCgQMH8sEHHzBo0CC9o2iifv36rFq1it69e6c68vHhw4fZtGkTuUu8RA7XjM+LIZycyVXjDX5assxccTVx7tw5h/jlp4qf8h/jxo1j5cqVesfQTIcOHfD19SVPnjz/+Sw4OPj/h8gvYPqUkNncynDjVoA5YmpCSsn777/PiRMn9I5icar4Kf8hhKBo0cyNIGyrihUrluL7CxYswMPDI3GU5sx1Hk4w4dlcvXl7exMREYG7u7veUSxOFT8lTVFRUaxZs0bvGJqRUrJq1SpiY2MxGAwsWrSIzz//nJIlS8JT0x+NM4Tco1yZ0hZIahmzZ89mzJgxODnZf2mwuSMUQngIIY4LIZ4KIW4JIeYIISwzqJpCZGQkP/zwA/Pnz9c7iiYSEhLYvHkz7733Hs7Ozvj6+lK9enXc3d2JuP0PhqePMrwtKSUxfvv4YNC7FkxsXr/88gv9+vXTO4YmbKr4CSF6AJuAtUBNYCDQCVinYyy7VqhQIby8vJg0aRKbN2/WO47FOTs7s3btWm7cuMG4ceOMZ3xAvnz5eKfPOzw990eGtxXhf5ZC+fPQtGlTS8U1u8KFCzvM8Pc2VfyAL4GfpJRzpZS3pJT7ge+ADkKIl3TOZrcqVKjAjh07CAiwnRv3WZErVy527NhBXFwc8fHxz9//6ouxxF45wNPr6U+QHhtyj9C/FjBnxlSHGDTCFtnU421CiLJAkJQyKsl7b2E8G6wipUx11mr1eJuSUVJKhg4dysSJEylcuPALn508eZJ2HTuTs86b5K/dHmeX3C+umxBP+PUTPDm4lGmTJvDh0KFaRs+0iRMn0rZtWxo0aKB3FJM57KguQogtQG2gspQy1WY1VfzMyxaGOsosLy8vxowZw/nz55+ftSU93qtXr/LpmLHs9/YmX9WmCLdyCGdn4sOCiPY7QMUK5Zg68UfatWun52Fk2IMHD6hevTqXL19OtdXbmjnkYKZCiMGAO/BJSoVPCDFECOErhLDMFFsO6vz58zRq1IgnT57oHcUipkyZwueff/688EVGRlK3bl3++ecfAKpUqcKubVu45vcPn3RrQtuSMbRwe8KAxmU5tM+Lv31P2EzhA5g7dy69e/e2ycKXJZkZCsYaXkB/IA7wzODyGRoeR0lfQkKC/Oijj2Tr1q1lTEyM3nHM6smTJ7Jz584yNjb2hfdXrlwpy5UrJwMDA3VKZjl9+/aV169f1ztGpuFIQ1oJIYYAi4BRUso5GVxH2uKxWqv4+Hh69OhB9erVmThxot5xNDF58mS8vLzYv3+/asSwIg5zz08IMRKYAQyXUi4wYT1V/MwsKiqKmJgYXF1d9Y6iCSkl9+/fp0SJEnpHUZJwiOInhPgK+BH4FFjN/z9vJIHgtKqbKn5KesLDw8mbN6/eMTRjL8dr9w0eQojqwASMhW4W8AgISnw9Aj7UL53y4MED9uzZo3eMTLt37x6VK1cmKioq/YUxTiu5bp3t9q1PSEigQYMGnDlzRu8ourGZ4ielvCylFFJKZymlU+Lfk74W6Z3Rkd2/f5/+/ftz6NAhvaNkyuzZs3n77bfJlStXhpaPiIjghx9+YPbs2ZYNZiHbt28nT5481KtXT+8o+slMK4ktvlCtvRa3d+9eWbRoUXnx4kW9o5gkNDRUurm5yZs3b5q0nr+/vyxVqpRcv369ZYJZSEJCgmzUqJHcuHGj3lHMgky29trMmZ9i/dq0acOsWbO4ceOG3lFMIoTg559/pnz58iatV65cOXbt2mVzxyulxNPTk27duukdRVc21eCRFarBQ1Hsk903eCi2KenAAI7A0Y7Xlqnip1jMmjVr6Nu3r9WOZBwfH8+qVavMls/Pz4+GDRsSGhpqlu1Zwu+//263jyWaShU/xWK6d+/OnTt3GDNmjN5RUrRlyxYWLlxotqc1qlatSpMmTejatSvR0dFm2aY53bp1iyFDhqBu/xip4qdYTK5cudi+fTteXl78/vvvesd5gZSSKVOmMHbsWLMVPyEEM2fOpEiRInz11Vdm2aY5zZw5k/fff99hnshJj2rwUCzuwYMHuLm5kT17dr2jPHf27Fn69OnDpUuXzD5fRXR0NOHh4f8ZC1BPUVFRVKxYkdOnTz8fndpeOMTjbVmhip+S3NOnT8mXL5/eMTRjr8erWnsVm3D+/HkuXLigdwwATQrB48ePreaxP3ssfFmhip+iqcuXL9OpUydu376tdxRN3Lt3j/79++Pt7a13FCUZVfwUTfXq1YuRI0fSsWNHQkJCNN//jRs36NOnj2b7q1mzJuvXr6d3796cP39es/0+YzAY6Ny5s+rekgL7nIRBsWqjRo0iPDycwMBAChYsqOm+p0+fbvJjbFnVqlUr5s6dy5UrV6hdu7am+16/fj2RkZEUKKCmtk5ONXgoDuPhw4dUq1bNZifqMZWUkjp16jB16lQ6dOigdxyLUQ0eis1KSEjQpONtQEAAo0ePtorCp8VTL8HBwTRs2JD27dtbfF+2SJ35KbobPXo0JUqU4LPPPtM7iiZ+//131q1bx7p163B2dtY7js1TZ36KzRoxYgRz5szht99+0zuKJrp06UJQUBCffvqpetRMR6r4KborU6YMu3btYsSIEVy5csXs24+NjSUoKMjs280sFxcXtm7dire3t8UK/t27dy2yXXuiLnsVqxEQEECZMmXMPi3kr7/+yqZNm9i5c6dZt5tVDx48wNXVFRcXF7Nu9/Lly7Ru3ZqAgACreqTQUtTjbelQxc8xJSQkULNmTebOnUubNm30jqOJ9957jwoVKvDNN9/oHUUTmS1+qp+fYpX++usvXnnlFdzc3LK0nZ07d5IrVy7eeOMNMyWzjCtXrhAdHU2dOnWytJ3AwEC2bt3K9evXzZTMfql7fopV2rNnDx4eHlkeF69BgwYsW7bM7JfS5nbx4kU6d+7MrVu3srSdggULsnXr1iz/0nAE6rJXsUoJCQn06dMHg8HAhg0bHKJLyJw5c1i8eDE+Pj4UKlRI7zg2Q3V1UeyKk5MTK1asoGjRoro8A6yHESNG0Lt3b/z9/fWO4hDUmZ9ily5fvoyfn5/DTM8YFRXFTz/9xIgRI6z+Et/c1JmfYvdMeSRs0qRJ+Pn5WTCN5Zny2N+KFSvYt2+fwxW+rFDFT7EJUko6d+7M3r1701321q1b7Nq1i2HDhmmQzHK+++47pkyZku5ycXFxTJs2jbFjx2qQyn6o4qfYBCEE48aNo2/fvpw9ezbNZbdt28Z7771n8xP1DBs2jMWLF7Ny5co0l/P19aV06dI0bdpUo2T2Qd3zU2zKpk2bGDVqFH5+fuTOnTvV5eLi4siWzfa7sf7zzz+0atWKv/76i1q1aqW6nL0cb2aoJzzSoYqf/fD399d8QFI9+fv7U65cOXU/LxWq+KVDFT9FsU+qtVdxSNu3byc+Ph6AhQsXMnXqVJ0TWdahQ4d49OgRYLzX16NHD50T2S5V/BSbFR8fz9y5cxk+fDixsbFMnTqVFi1a6B3Lovbs2YO7uzuRkZFMmTKFJk2a6B3JZqnLXsWmhYWF0bx5c6pWrcqDBw84cOCA3pEsKiEhgXfffZe7d+9y/vx5bt68Sd68efWOpSt12as4pPz587N7924ePXrkEEM4OTk5sWzZMgoUKMC4ceMcvvBlhc0VPyHE20KIs0KIaCFEgBBiohAip965FP2ULFmSffv2cfjwYcaPHw/A+PHjU/27EOL5e5n9e3r7sGSOiRMnsmXLFjUXbxbZ1GWvEGIAsAwYA+wEqgBzgUtSSo901lWXvYpih+y+q0vi2V0gsFxK+XmS918BTgMdpZReaayvip+i2CFHuOfXAigErEn6ppTyDOAHqDZ/RVEyzJaKX/XEPy+n8Nll4GUNsyiKYuNsqfjlBeKklLEpfBYB5NM4j6IoNsyWnoQOB7IJIXKkUADzJH7+AiHEEGBIkq8tm1BRFJthS8Xv2ciU1YFzyT6rDhxNvoKU8mfgZwAhhK+U8lWLJrQSjnSsoI7XnlnyWG3psvcgEAz0SfqmEKIeUA34XY9QiqLYJps585NSRgkhxgILhRABgBdQCZgH/CGl3K1rQEVRbIrNFD8AKeVSIUQkMBaYCQQBvwHfZmD1ny2Zzco40rGCOl57ZrFjtZlOzoqiKOZkS/f8FEVRzMYuip+pgx0IIVoJIY4IIaKEEA+EEAuFEAW1zJwVQggPIcRxIcRTIcQtIcQcIUSBNJafJYSQyV6PtMycFUKILSnk901jeZsc/EIIUSaF40z6WpbKeiZ9f/QkhCglhDgthPBP4bO6QggvIUSEECJYCLFaCFE6ne1VEEJsFEI8Sfx52C6EqJ7WOs/YfPFLHOxgLbACqAl8CPQE1qeyfGtgD7AfqJu4bAPgTyFEdg0iZ4kQogewCeMx1wQGAp2AdWmsVhv4DiiS5FXGokHNqzbwHi/mb5zSgqb+f7AmUsrbGB/hLJLs1QQwAN6prJrh74+ehBCvAieBGil89jJwGAgAGgEdMH4vfFI7MRFCFAOOADmA1kBTIAQ4IoSomG4gKaXNvoCcwCNgarL3XwEk0CGFdS4CG5K9VxKIBj7U+5gycMyngfnJ3uuTeLwvpbLOQ6CT3tkzebx5gQTgZUv8f7CFF8Zfdv8ATln5/uh8DO5AJDALYyOGf7LPdwInkr2XG7gPTE5lm/MTi6VLkvcE8DewLr1Mtn7mZ9JgB0KIqhh/6yRf/i7GM0FbGByhG8YhvZKKSfzzP4+wCCFKYDwTuGThXJZSC4gDrmVgWbsb/CKxH2t34DspZUIKi5jy/dHTHWCYlPJTjMX6OSFEboxnemuTvi+ljAS2kPq/21vA71LKmCTrSIw9QNzTu5Kz9eJn6mAHNj84gpQyQEoZleztfsAN4N8UVnk22auXECJICHE18R6YrQwBXAvjWdulxPwXhRBjUvmPbfP/vimYgPGJpk2pfG7K90c3UsrTUsoVqXxcBXAm9X+3SkIIl6RvCiFcgeJprJMLqJBWJpvq55cCUwc7yJvks4wsb/WEEIMxXlK8mcqZwRngHYzF8SnwKjAFaCSEeCPxN6U1+wN4F7gKxALNgUkYz+AHJlvWrga/EEI0xng/1z2NfydTvj/WKr2fy2fLxCR5PyPrpPnvbevFz9TBDsKTfJZcioMjWDMhRH9gETBcpvKEi5TyES82hlwWQkRgfBywHsbiaLWksREgaf6LiS23M4QQo6SUwUk+M3nwCys3AeN9sB2pLWDi98dapfdzmXSZrKzzAlu/7E062EFy1THeJM7K8lYrccSaX4HPpJQLTFz9auKfttTim1Rq+e3p3/cNoBWQmVmZbO3f9xoQT+r/bjeS3tcDkFKGAg/SWCca49VOqmy9+Jk02IGU0g/j/YDky5fA+B/NJgZHEEKM5P/P+OZkYhNNMN50/tuMsbTUBONv9eQ3+e1p8Iv/AYeklHszsW5q3x+rJKWMAP7EeHvmOSFELqArqf+7bQbeEkLkSLKOSNzODimlIb0d2/QL+ADjvQ5PjAMdtAOuALsTP/8S4xlBicSv22PsMzUe443WpsBxjIUgh97Hk4Hj/Qpj4RqBsWWzcOKrEMbW3uTHOx+YhvEStxzG+0PBwGy9jyUDx+qMsX/eNxgbKyolHnc0MDJxmYWAL5ArI/8fbOEFvImxEaNZCp89P96MfH+s6QW4Jr6WY+yi8uxrJ4x9FSMw/lKvAdTH2P0lECiUuH5r4BbQPvHrEhjP/p7dwqmZuO0nQOV08+j9DTHTN7UPxhaxmMRv1rQkPwyTMA6AUC7J8m2BY4n/SR5i7HdUSO/jyMBxVk/8oYhPLIAy2WtY8uNN/A+zGwhN/P6cBwaQ+Fy3tb8wdmc4iPFMJgo4AXRJ8vla4CaQJyP/H6z9xf/3U1ufyucvHG963x9reqXw//XZq3zi568CfyUWwRCM9zLLJVm/S+JxdkvyXmWM3WHCEj/bDdTKSB41sIGiKA7J1u/5KYqiZIoqfoqiOCRV/BRFcUiq+CmK4pBU8VMUxSGp4qcoikNSxU9RFIekip+iKA5JFT/F4QghZgsh/IUQfdJfWrFXqvgpDkUI4YZxzLu3gU91jqPoSBU/xdGEYBzU9SjGgUD/I3FkEMXOqWd7FbuVOJPb61LKYcneF0BBmcJAn4kDxDaTUg7RKKaiE3Xmp9ilxNGM/4dxdJfk5gCPhRDdUvjsDDBICFHbkvkU/akzP8UuJZ7BTQPKyCSDWiZO3HSHxOG9pJRtUlh3C/BYSvmBVnkV7akzP8Ve9cc4P3Py0Xz7YZzkeiTwhhCiWgrrrgZ6JR0hWLE/qvgpVkEI0UcIYRBCtEzyXj0hRJQQoquJ23ICXgf2pfCxJ8ZpINdjHOjUM4VlvDHODlbHlP0qtkUVP8UqSCnXYixKy4QQuRPv2a0GVkopt5q4ufIYi9ffSd8UQrTAONT5UillPMYhzwckn8NYShmCcbj0Wih2SxU/xZp8hPGSdBLGaRudSdYXTwjRVQgRkcrl6jOFE/8MSva+J3BVSnkw8evlGItk/xS2EYRxXhTFTtn6vL2KHZFShgghBmKcySsOYzeVyGefCyHGAD2AyJS38Jxz4p9xSdYtCXTDOAHUs/3dEkL8ibHoLkq2jbgk21HskDrzU6xNOYydkBOAV569mXgfzxnjFKMR6WwjJPFPtyTvDcX4y/57IUT4sxfwBlAz6b3GJOuGoNgt1dVFsRpCiAoY++V9DuQHvgZqSyn9ky3nD3SQxnmYU9pOTowFtL2U0lsIkR3jVInHErf9wuIYZz87IqV8O8n6YUBHKWVKjSaKHVCXvYpVSDyzW4mxCC0WQjhjfP72FyFEa2nCb2kpZbQQ4hzQDGPLbXegODBTSnk9hX3/BHwthCgppbwLNMR4VeSb5QNTrJa67FWsxRiMk8i/B5DYGvs+0AjjRNym2gD0Tvy7J3BCSumTyrKLMd5H/DDx63eAPVLKJ5nYr2Ij1GWvYnPSu+xNXKYoxsm935ZS7jZh20WBG0AvKeWurGZVrJc681NshhDiayGEL1AC2CSEWJDaslLKh8BUjGePpugDnFSFz/6pMz/FbgkhcgHZpZRhJqzjBLhJKR9ZLpliDVTxUxTFIanLXkVRHJIqfoqiOCRV/BRFcUiq+CmK4pBU8VMUxSGp4qcoikNSxU9RFIf0f1wjo/jiSZynAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# plot an example structure\n", "i = 12 # structure index in dataframe\n", @@ -96,10 +236,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "dae3b60e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "average lattice parameter (a/b/c): 4.913216585660792 / 5.258921900844212 / 6.5187904554067595\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# lattice parameter statistics\n", "def get_lattice_parameters(df):\n", @@ -135,17 +295,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "57f3027d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 118/118 [00:00<00:00, 65139.23it/s] \n" + ] + } + ], "source": [ "# one-hot encoding atom type and mass\n", "type_encoding = {}\n", "specie_am = []\n", "for Z in tqdm(range(1, 119), bar_format=bar_format):\n", " specie = Atom(Z)\n", - " type_encoding[specie.symbol] = Z\n", + " type_encoding[specie.symbol] = Z - 1\n", " specie_am.append(specie.mass)\n", "\n", "type_onehot = torch.eye(len(type_encoding))\n", @@ -154,10 +322,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "cf5bfd7a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1522/1522 [00:09<00:00, 152.44it/s] \n" + ] + } + ], "source": [ "# build data\n", "def build_data(entry, type_encoding, type_onehot, r_max=5.):\n", @@ -196,10 +372,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "6842dfb2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "i = 244 # structure index in dataframe\n", "plot_example(df, i=i, label_edges=True)" @@ -216,12 +405,63 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "3cb75584", "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "split train/dev ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 64/64 [00:00<00:00, 318.30it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "split valid/test ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 62/62 [00:00<00:00, 435.15it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of training examples: 1192\n", + "number of validation examples: 141\n", + "number of testing examples: 189\n", + "total number of examples: 1522\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# train/valid/test split\n", "idx_train, idx_valid, idx_test = train_valid_test_split(df, species, valid_size=.1, test_size=.1, seed=12, plot=True)" @@ -237,7 +477,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "eb03c3c2", "metadata": {}, "outputs": [], @@ -256,10 +496,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "013a4311", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "average number of neighbors (train/valid/test): 15.837087001257574 / 15.272818455366098 / 15.455339153794492\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# calculate average number of neighbors\n", "def get_neighbors(df, idx):\n", @@ -299,7 +559,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "ce8485c0", "metadata": {}, "outputs": [], @@ -335,10 +595,49 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "60184949", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "PeriodicNetwork(\n", + " (layers): ModuleList(\n", + " (0): CustomCompose(\n", + " (first): Convolution(\n", + " (sc): FullyConnectedTensorProduct(64x0e x 64x0e -> 64x0e+32x1o | 262144 paths | 262144 weights)\n", + " (lin1): FullyConnectedTensorProduct(64x0e x 64x0e -> 64x0e | 262144 paths | 262144 weights)\n", + " (fc): FullyConnectedNet[10, 100, 128]\n", + " (tp): TensorProduct(64x0e x 1x0e+1x1o -> 64x0e+64x1o | 128 paths | 128 weights)\n", + " (lin2): FullyConnectedTensorProduct(64x0e+64x1o x 64x0e -> 64x0e+32x1o | 393216 paths | 393216 weights)\n", + " )\n", + " (second): Gate (64x0e+32x1o -> 32x0e+32x1o)\n", + " )\n", + " (1): CustomCompose(\n", + " (first): Convolution(\n", + " (sc): FullyConnectedTensorProduct(32x0e+32x1o x 64x0e -> 96x0e+32x1o+32x1e | 262144 paths | 262144 weights)\n", + " (lin1): FullyConnectedTensorProduct(32x0e+32x1o x 64x0e -> 32x0e+32x1o | 131072 paths | 131072 weights)\n", + " (fc): FullyConnectedNet[10, 100, 160]\n", + " (tp): TensorProduct(32x0e+32x1o x 1x0e+1x1o -> 64x0e+64x1o+32x1e | 160 paths | 160 weights)\n", + " (lin2): FullyConnectedTensorProduct(64x0e+64x1o+32x1e x 64x0e -> 96x0e+32x1o+32x1e | 589824 paths | 589824 weights)\n", + " )\n", + " (second): Gate (96x0e+32x1o+32x1e -> 32x0e+32x1o+32x1e)\n", + " )\n", + " (2): Convolution(\n", + " (sc): FullyConnectedTensorProduct(32x0e+32x1o+32x1e x 64x0e -> 51x0e | 104448 paths | 104448 weights)\n", + " (lin1): FullyConnectedTensorProduct(32x0e+32x1o+32x1e x 64x0e -> 32x0e+32x1o+32x1e | 196608 paths | 196608 weights)\n", + " (fc): FullyConnectedNet[10, 100, 64]\n", + " (tp): TensorProduct(32x0e+32x1o+32x1e x 1x0e+1x1o -> 64x0e | 64 paths | 64 weights)\n", + " (lin2): FullyConnectedTensorProduct(64x0e x 64x0e -> 51x0e | 208896 paths | 208896 weights)\n", + " )\n", + " )\n", + " (em): Linear(in_features=118, out_features=64, bias=True)\n", + ")\n" + ] + } + ], "source": [ "out_dim = len(df.iloc[0]['phfreq'])\n", "em_dim = 64 \n", @@ -362,10 +661,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "85748807", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# visualize tensor products of the model\n", "visualize_layers(model)" @@ -382,7 +694,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "2a8ea728", "metadata": {}, "outputs": [], @@ -396,12 +708,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "07b5d8bb", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch device: cuda:6\n", + "model_220423\n" + ] + } + ], "source": [ - "device = \"cuda:6\" if torch.cuda.is_available() else \"cpu\"\n", + "device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n", "print('torch device:' , device)\n", "\n", "run_name = 'model_' + time.strftime(\"%y%m%d\", time.localtime())\n", @@ -410,12 +731,319 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "11c3e2e8", "metadata": { "scrolled": true }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1192/1192 [01:11<00:00, 16.78it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration 1 train loss = 0.0325 valid loss = 0.0330 elapsed time = 00:01:11\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1192/1192 [01:05<00:00, 18.07it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration 2 train loss = 0.0285 valid loss = 0.0299 elapsed time = 00:02:30\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1192/1192 [01:04<00:00, 18.38it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration 3 train loss = 0.0254 valid loss = 0.0279 elapsed time = 00:03:48\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + 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opt, dataloader_train, dataloader_valid, loss_fn, loss_fn_mae, run_name,\n", @@ -424,10 +1052,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "00046bca", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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8cNjrUI0lYslHVYuB24FbRORGEekpIqcD04EPVPV9EblTRHKDCQbgFmCiiNwtIkeJyGice3pygWeDdd4GzhaRJ0Skv4j0EZH7gVOAB4Kv/Q3wCvAPETlHRLqLyGTg/wF3q+qh/V6NIHPIKdy76zgKY9KcAnERe+LVh/yBhOuGq6ncGOMkoKRJj5N8zWskTXo8Yt3UV111FUVFRUyePJn4eOd++QceeIBf//rXZGZm8vzzz/PLX/4S55bEmj399NP4fD46derE6NGjmTx5MsnJzuXvcePGMWrUKLp06cKQIUNIS0urtBT2T3/6U9q1a0fXrl35y1/+csixzznnHB5//HEmT55MUlISP//5z3n88ceZMGFCA/0m6ibiy2iLyCScJNQX2AW8BtylqsXBpHEVcKyqbgjWPw24BxgK7AfeAe4MTRgichLwv8AIwIsz/Pp+VX0vpI4H+APOvT9ZwBrgseC1ncPFfMTLaFc16p5ZnDogiz8OyKP0i6kkTHwAd0a3SnVq6r9OmvT4IeXGGNMU1bSMdsSTT3PUkMnnf56eS0CVVyYPpvCVa/EMPZ+4Yy+uVMe7eg6lnz9deaROTGxEuhGMMaah1JR8bGLRCOuZmcLaHQUQn4I7uz/+dd8cUsfTezTStjMQPGcutyUeY0yLYvO7RFjPDsnsK/aSV1BGarfhlM17gUD+FlxpnSrqBAry0D3r8Rw9AYmJo2zRv4npekwUo24YNnzcGFPOWj4RtnOfM2b+xD9/yGXvlQLgW7egUh1v7mxQ8PQbi6t9D0Dx727eM2Hb8HFjTChLPhE0Y/FmXp67ruL50j0ulpVmsHvZwQ9gDfjw5c7G3XkwrtQOuDOdG86a+zIMNnzcGBPKkk8EPTorl1Jf5SW0PynIIbVoM4Hg6Db/hsVo0V48/Zy5oiQ+FUnJJNDMl2Gw4ePGmFCWfCJoW37xIWWfFXYGwBcceOBd/hGS1A53l6EVddzte+DfuSYyQTaSqrM4HK7cGNOyWfKJoOy0hEPKNnlTWe9ri2/9AgL7tuHfshRPv7GI6+BMCK7MXmjBbrR4fyTDbVCeYy86tNDd+NOfGGOaJks+ETRlXF/iPZWn14n3uEnM6ERg2wqKXncWVdXYynOputs7132a8wqorvjgxOHxqRVl7p4jbbSbMa2UJZ8ImjAsh3smDqZ9ShwAaYkenj7JS+aBlZXqeb+ZVmkUmCujO4g066433+o5EJdM0s+eJOnq13C170Fg52qqLLFkjGklLPlE2IRhOXz6u9NIjHUzYWgOA3d9BP4qKxxWGQUmnnhcaTnNdsSbekvwbVhETI/jEXcMIoJn4Flo/lb8m5dEOzxjTBRY8okCt0vo17ENy7bk13oUmKt9TwK71tIcp0PyrV8AvlI8vU6oKIvpcTyS2Bbv0g+iGJkxJlos+UTJgJw2rNiyH5JqNwrMndkTLdmPFuyKRHgNyrdmLpKcgSurT0WZuGPw9D8d/+bvCezdHMXojDHRYMknSgZ0SqPY62dvn3NrtQiWq33zvNk0ULwP/+YlxPQ6gSpr+eHpNxbcHsp+mBml6Iwx0WLJJ0oG5rQBYJH0rdUiWK52XcAV0+wGHfjWfgUaICaky62cJKQS0/tEfKu+QEvCLzFujGmZbGLRKOmWkUxirJsfNudz3rmjDzvkWNwxuDK6Nbvh1r41c3G164K7XZew2z0Dz8SXOxtv7mxih5wb4eiMMdFiLZ8ocbmE/p3a8MPmfbXex92+J4Hd69BA8xieHNi/ncDO1WFbPeXc7Trj7jQI77JZaOj6RcaYFs2STxQNzEkjd+s+fP7aJRNX+57gLSGQv+Wwdb2r51A47SYKpl5K4bSbojJ7tG+Ns259TckHwDPoTLRwD74fD13byBjTMlnyiaKBOWmU+gKs3VlQq/oHZ7iuueutKSxfoKp418zBld0PV3JGjXXdnYcgbbLw/vB+hKIzxkSbJZ8oGhAcdPDD5vxa1Zc22eBJOOyIt7L5r0Z9+YJA3no0f2ule3uqI+LCM/BMAjvX4N+xOgLRGWOizZJPFHVpl0RyXEztk4+4nBmudx064k1LC/Cu+Jiid/+EFu0Nu78Gl22IBN/qOeByE9P9+FrV9xx1EsQm4l1qrR9jWgMb7RZFLpcwIKcNy7fUftCBuuMIbF1GwdRLkKR03N2PQwt349+wGAI+JK0jxCZCWdGhO4sL/861Fd13jUUDAXxr5zndafHJtdpHPPF4+p6Cd+n7BAp2H7arzhjTvFnLJ8oG5KSRu20/Zb7DDzrwrp5DYMvBudC0MA/fD+/j37QET/9TSTj/XhIvepi4E6449MZVdwx4Eij+zx8pXfivRh1Z5t+2HC3aS0yvus1Y7RkwDlC8yz5snMCMMU2GJZ8oG9CpDWW+AGt2HP4my7IF0yFM0pD4JOJGTcbdvqczaWfv0YfeuPqT60i69G/E9ByFd/GbFP/nTwTytzbCOwLfmjngSSCm6zF12s+V0h53txF4cz9BvSWNEpsxpmmwbrcoG5iTBjiDDvp3alNj3eonId1zSJmnd/gbV+NPuQlv12MonfMsRW/eQezxP3OutSx4HS3IQ5LTiR1+yRGvs6O+Mnw/ziem+3CkauurFmIHnUXxuvn4Vn+Jp/9pRxSDMabps+QTZZ3bJZKa4KnVdR9JTg87aKCuS1F7eo7EndWH0s+foWzuP0EEgrNllw/LBo4oAfk3fgve4sPe21MdV4ejcLXvQdkPHxDTb+wh88EZY1oG+8uOMpHymQ7yD1s3dvgltZqEtDZcSe2IP/MOiEuqSDwV6jEs27tmLpLQBnfHgUe0v631Y0zrYMmnCRiYk8aq7fsp8/lrrBf2Wk6YSUhrS0SgNMyoOKrv4quJlhbi37iYmJ6jEJf78DtUw9b6Mabls263JmBgpzZ4/crq7QcYELwGVJ3qruUcqYbqygPwrZsPAV+dR7kd8truGDz9T6Ns4RsE9m7G1TanXsczxjQ91vJpAnbsKwbgwr9/ydj7P2bG4sgtrtaQXXm+NXORNlm42veod1yefqfaWj/GtGARTz4icpGIfCsiJSKyUUTuE5H4GuqPEZG5IlIsIjtE5EkRaVulTkawfKOIHAjWHxfmWN+KiFZ5/Lsx3mdtzVi8mUdmrax4vjW/mLveWhKxBFS5Ky9YNuyCOreuAoV78G9dTkzPE5zuvHqShFRieo22tX6MaaEimnxE5HJgGvAiMBC4DrgYeL2a+qcAs4BPgSHBusOBD0XEE6wTC8wMbr8QGAx8DrwnIieEHCsG6AecCrQPPjKAun/Fb0CPzsqlxFv5Wk+J18+js3IjFoOn92iSJj1O0uVTISYOPYJlrX1r5wHaoF2CnkFngr8Mb+7sBjumMaZpiFjyCbZu/go8oqqPquoaVX0fJ6GcIyJnhNntb8A7qvoHVV2pqp8D5wKDgCuDdcYFn1+kqt+o6jpV/R3wI3B9yLH6ALHA16q6O/jIU9WoLiKzLb+4TuWNSeJT8fQbi2/NXAL7d9ZpX9/qObja98TVJrvB4nG364K700Bb68eYFiiSLZ+TgHTg1dBCVV0M5OK0WiqISB9gQJj6W3FaQuX1PwF6qmrVRW5KgdD+n8HABlUtrN/baFjZaQlhyxPj3Iy9/2P63z4joteBPIPHgwhlS2bUep/A3i0E8tYf8b09NcYzMLjWzzpb68eYliSSyadf8OeKMNtWAP2PpL6qFqlqpU9mERmCk7g+CikeBGSIyFoR2SUii0XkSmmICxT1MGVcX+I9hw5LLiz1szW/GCWy14FcSe2IOeokfCs/I1DN7NhVedfMARFieo5q8HjcXYYiqVk27NqYFiaSyScZ8KlqWZhthUBKmPrl22pTHwARScNpLc0DXgnZ9BJOV935wGnAv4CngD9Vc5xrRGShiCwMt72hTBiWwz0TB9MxLQEBOqYl0CbBc0i9SF4Hij36HAj48C45/PIGqopvzVzcnQbhSkxr8FictX7OILBzta31Y0wLEsn7fAqAGBGJDZOAkoLbq9Yv31ZVuPrliWdW8Ol5oddzVDUXp3uv3Hcikg3cIiL/q1r5Nn9VnQpMDR63yhQADWvCsBwmDDt4L0v/28N3eUXqOpCrTZYzAemKj4gdcm6NyyIEdq5GD+wk5pgLGi0eT5+TKVv4Bt4fPsDdoXejvY4xJnIi2fIp/+DvF2ZbP2B5feqLSAbOtaAUYKyq1mbltFVAavDRZFR3Hai68sbgGXIueEvwLptVYz3f6jng9hDTbXijxeKs9TMG349fEziCmReMMU1PJJPP58AeYFJooYgMBfoCb4aWB1sqK8LUzwbGhNYPln2O05I7WVW31zKmE4AfVbX2q7lFQLjrQPEeN1PG9Y1YDO52XXB3PYayHz6odnkDDfjw/vgVMV2PQWITGzUez4BxoAGK/vUbCqZeSuG0m/CuntOor2mMaTwRSz6qWgzcjtPNdaOI9BSR04HpwAeq+r6I3CkiucFkAnALMFFE7haRo0RkNPA2TqvoWQAR6QJ8CfiBiUAgeNNphogkBeukiMh7IvIrEektIn1E5H9xhnn/JlK/g9oKvQ4E4HYJ90wcXKlrLhJih5wHweW5w/FvXgolB+o9nU5t+LevAnGBtxjQitm3LQEZ0zxF9CZTVX0WmAxcg9Nt9jzwLlB+wSAVZzh2bLD+LOAsnHt5lgBvBX+ODblu9H9AT5zRb6uAXSGPH4N1CoF3gMuA74HFwGjgRFV9uzHea31NGJbDJ3eeyu1n98cfUEb2bh/xGNwdeuPuOADvkvdQ36HjRHxr5kBcEu7OQxo9lrIF00GrrPZaj9m3jTHRFfHpdVR1mqoerapxqpqjqrcFW0Wo6p2q2l5VN4TU/0hVR6pqvKpmquo1qpoXsv2nqiqqGhP8GfroEKwTUNV/qOoIVU1U1SRVHauq8yL9/utqUOc0AJZsqt2w54bmGXoeWrQX36ovKpWrtwTf+oXEdD8ecTf+uJXqF9Kza0DGNEc2sWgT179TG9wuYcmm/Ki8vrvjQFzte1L2/bto4OA0QL4NC8FX2qDT6dSk2lm2Y2LRsvDLQhhjmi5LPk1cQmwMR2WlsGRjdFo+IkLs0PPRAzvxrf2qoty3ei6SlI4rq09E4gg7+7a4wVdK0b9/i39r1cGSxpimzJJPMzC4c1t+2JxPINCotxtVy911GK62nfF+9w6qAbR4P/7N3xPT64SILXMddiG9k68n4dx7wBVD8X//H6Vfv4L6vRGJxxhTP7aYXDMwuHMar8/fwPrdBfTIDDuxQ6MSceEZei6lsx/Hv2ExgcI80AAxEepyK1fdQnqJFzxA6dev4F3yX/yblxA35kbc6V0jGpsxpm6s5dMMDOrsLF8Ures+ADE9RkJcCiUfP0rZ3H+Cy00gb2PU4gklnnjiT7yK+DNuR4v3U/z27yj77l00EDj8zqYS7+o5FE67ye6lMo3OWj7NQI/MZJLiYliyKZ/zjukclRh8a78CbxGUDzoI+Cn9cipAxAYdHE5Ml6G4L3qQki+fpeybafg2Lib+5BtwpWZGNA7v6jmULZiOFuQhyenEDr+kyfyOauJdPcc5p8Fh9eX3UkHTOcd11VzPRWtgLZ9mwO0SBuWkRW3QAQTvswlUXvSuKd5nI/GpxJ96C3En30AgbwNFb/4W78rPqDJ1X6Mp/wDXgt00l5th1VdGYO9mSr96qSLxVPCVUfb1KwSK8tGq91k1cc3xXDQljd0KtpZPMzGocxr//GItpV4/cWGWYGhszek+GxHBc9RPcGf3o/Szpyj9/Gl8GxYRf+LVSELjTeOnAR9lX79czQf4y7g79kcS0yI2SKMiLlW0ZD+6fweB/Tudnwd2ENi/A92/Ez3M0hlanE/RK9eBuJGktkhyOq6kdCQpHUluV+nfktCmVu+vIVsk6itFSw4c8ihb8HrYc1H61Yu42nbCldwe4pIaZNn3liYSrWCJ1DfC5kxEqk56HXEfL9vGL19ayLQbTmBo13YRf/3CaTcFv0FWJskZJE16POLx1JZqAO/SDyj75jUkLom4n1xDTNdjGubYvjICu9bi37Yc/7YVzpIPvtKad3LFIMkZuFLaIyntD/5Mbo+kZlb74X24D2v1+9CCXRUJJbB/B4ED5YlmJ1SZn0+S2iGpHXClZOJK7YCkZlL21ctocZhpDuNTiT3mArRwD1qQR6AwDy3IQwv3QNUVZmuRoHxbllL25bOVE0NMLHEnXkNM9+FhE4mWHICSA2hpQUjZfrSkAPzhVmmpJU+Ccw6S24c9J3VJTs21i08Dfuf/Sf4WZ2HIvZvx/fj1oeeWuv+9iwiqGvYXaMmnFppC8tm5v4ST7v2IOycM4PLRPSL++lW/CQEVHxjN4Q/Mv2cTpZ8+TiBvAzF9TyFu5OWIJ75Ox1BvCf4dq51ksz2XwM414PcCgiu9C+7sfnjXzIWSA4fuHJ9K3LEXETiwCz2wi0CB8/OQD3u352BySm6PKzUTf8Ee/CtnB18ryOVGOvTBJeIknMI8CP0/6vY4SSUkubhSO+BK6YCktEeq3jNF3c+xqkLJgYpkFCjMq5ygCvc4Caqhhr/HJSHxKUhcivMzPgWJT0biUw8+jzv4vOjt34X/wpSQRtzoK5xzUbCLwP7gzwO7gnMHhihPTuVJqUqSItZJTs3h70N9ZQT2batIMlqebPZtq5RoJKmdc97CEpKvea3Wr1lT8rFut2YiMzWerDbxURvxVv4H1By/2QG423Um4bw/U7bo33i/exf/lh+IH3MjgQO7qn1PWlaEf/tKp1WzbQWBXT+C+kFcuDK64xlwOu7s/riz+iBxzppHrva9wn8Ijbw8/Ae4rxQ9sNtppRzYdfAD8cAuArvX4yvZH/4NBfzo9hVoZi/cWX2dVkwwwUhK5hF179X1HIsIJKTiTkiFjO5h61RNUFq4h9K5z1cbQ+yIS8MmEuKSEFfduptjh18S9lzEHn8ZMd1HhI+1tLDii0HFF4XgT+/WZYe0IMuTU2Df9kNbYMHrZe72PSA2EYlNAHdsvbv5DtsKLismkL81mGQ2H0w2B3aEfEER5wtJWg6eLkNwtc3BldYJV1pHJDaxhp6OamYaOQLW8qmFptDyAfjVywvI3bqfD28fG+1QmjX/9lxKPn0SPbDTmSVBQwZSuGJwdRzgfGDmrXP+WF1uXO174s7u5zw69HE+SKrRoNczvCUU/nNyNVvr9i20qYhkF26DnotDktPBLwz+jYtrdxBxQ2wCUp6MYhMRT0KVfycerONJqFTft3kpZV+9XDnRudy4Og5AwEkyhXmVt7XJRtI6Ode50nKcn22yw7Z+Q39vDdGSs263emoqyefZz9bw8AcrmHfX6bRNiot2OM2alhVT+Mp11V6jcWf3x1WRbHojMdH7fTfX623VaQ5dVHVV3TkiPpW4kZeDtwgtK3bmIQz+1LJi1Bvy3FsMZUWHjiqtJVdGd6f10rZT8GeOcx3RdWQdXA2RuK3brYUY3CUNcG42Palvh+gG08xJbMKhI6FCJEy4K4LR1Kza7qPhl0QvqHpo7l244VR3jqrrbq2OqoLf6yQp78EkVf7v0s+eqmZPIXHi/fV7E1VUN6NIQ7Hk04wM6JSGS2CpJZ8GIcnp1bYompKW+GHd2B9skdZQ50hEICY22CWWdsj2soX/avRrMZFiyacZSYqLoVeH6M1w3dI0pxZFS/uwbokicY6a0//Zw7FrPrXQVK75AFz+9FwWrt8DCtlpCUwZ1zfiy2u3JM313gzTejWn/7M24KCemkrymbF4M7//93d4/Qdjife4uWfiYEtAxpgmp6bkY3O7NSOPzsqtlHgASrx+Hp2VG6WIjDHmyFjyaUa25RfXqdwYY5oqSz7NSHZa+Bsbqys3xpimypJPMzJlXF/iq8xo7RL41el9ohSRMcYcGRtq3YyUDyp4dFYu2/KLSU3wsK/Yy4a8wihHZowxdWOj3WqhqYx2q0pV+cO/v+ethZt44ufDOaV/VrRDMsaYCjbarYUSEe46bxADc9pw+/RvWberINohGWNMrVjyaebiPG4eu+xYPDEufvnSAgpLD10AyhhjmhpLPi1Ax7aJPDxpGOt2FfD7f31HU+wiNMaYUJZ8WoiRvdpz65n9mLV0G89/sTba4RhjTI0s+bQgV/ykJ+MGZfPXD1bw1Zpd0Q7HGGOqFfHkIyIXici3IlIiIhtF5D4Ria+h/hgRmSsixSKyQ0SeFJG2VepkBMs3isiBYP1xYY51g4isEJFSEVktIrdJXdcabsJEhHsvGkL39snc+MI3nHTvR/S/fQZj7/+YGYs3Rzs8Y4ypENEPXhG5HJgGvAgMBK4DLgZer6b+KcAs4FNgSLDucOBDEfEE68QCM4PbLwQGA58D74nICSHHugv4C/AA0A/4PXAb8EjDvsvoSoqLYeKxnSn2Bti5vwQFtuYXc9dbSywBGWOajIjd5xNs3WwGnlfV34aUDwMWAWeq6swq+/wALFfVi0PKOgI/AlNU9WkRmQD8G+ihqltC6q0CvlHVy0QkG9gQ3OfJkDoTg/sOUNUVNcTeJO/zqc7Y+z9ma5j53jqmJfDJnadGISJjTGvUVO7zOQlIB14NLVTVxUAuTqulgoj0AQaEqb8VpyVUXv8ToGdo4gkqBcrf9Dk4szlMq1LnXaAQuKDub6fpsglIjTFNXSSTT7/gz3AtjBVA/yOpr6pFqlqpP0lEhuAkro9CjrVdVfND66mqD1gd5rWbNZuA1BjT1EUy+SQDPlUtC7OtEEgJU798W23qAyAiaTitpXnAKyHHqm4CtLDHEpFrRGShiCysZr8mK9wEpLExLqaM6xuliIwxprJITixaAMSISGyYBJQU3F61fvm2qsLVL088s4JPzwu2bMqPFe445cc65Eq8qk4FpgaP23wu+HDoBKQi0KltAuOHdopyZMYY44hky6d8uc1+Ybb1A5bXp76IZOBcC0oBxqrq7irHygomp9B9YoDeYV672ZswLIdP7jyV5X+ZwJ0TBrJuVyHzVu8+/I7GGBMBkUw+nwN7gEmhhSIyFOgLvBlarqq5ONd2qtbPBsaE1g+WfY7TkjtZVbdXee0ZgB+4tEr5BJwuubeO6B01Excf14XstAQem5VrU+8YY5qEiCUfVS0GbgduEZEbRaSniJwOTAc+UNX3ReROEckNJhOAW4CJInK3iBwlIqOBt3FaMs8CiEgX4Euc5DIRCARvOs0QkaTga2/Bub/nARH5mYh0Dw6zfgp4WlWXRer3EA2xMW5uGHsUSzfnM3v5jmiHY4wxkV/PR0Qm4SShvsAu4DXgLlUtFpH7gauAY1V1Q7D+acA9wFBgP/AOcKeq5gW3v45z86kfqHyVHXaqaoeQ174ZuAHohnOd51ngQVX1HybmZnWfTzg+f4Dxf/2MuBgXb998Ei5X2KH3xhjTYGq6z6deyUdE2qjqviM+QDPREpIPwHvfbeE3ry3moUuHcfYQG3xgjGlcDXKTqYj8VERuCnn+H2BPsJvsqAaI0zSyMwd35KisFP7+0Up8/kC0wzHGtGJ1ueZzN860NojI2TgX/S8DfgD+2uCRmQbncgm/Or0vG3YX8s4im+fNGBM9dUk+3YDvg/++CGeOtteA3wKjGjgu00hO6d+BwZ3TePKTVZT5arzUZYwxjaYuyWc9MEZEMoHzgH8Fy2PreBwTRSJO62dbfjFvzN8Y7XCMMa1UXZLGwzhLIWzAmWl6brB8MvBhA8dlGtGo3hkM75HOM7NXU1TmO/wOxhjTwGqdfFT1WZyZqa8FzgjZNBf4dQPHZRqRiDBlXF92F5Ty6rz10Q7HGNMK2VDrWmgpQ62ruub5+SzZuJePbh9LSoIn2uEYY1oYG2ptwrp5XB/2FXt54csfox2KMaaVqXXLR0RWAL8OToNzNs7MBNfiLMQWr6rjGy/M6GqpLR+Am19eyKcrttMuOY6d+0rITktgyri+FTNjG2PMkWqolUy7YUOtW5xBndPw+pUd+0pQYGt+MXe9tYQZi+0+IGNM47Gh1q3ca1+tP6SsxOvn0Vm5h1Y2xpgGUpfF5MqHWpcB39pQ65ZhW35xncqNMaYh1Dr5qOqzIpIL9MCZWbrcXOCJBo7LREh2WgJbwySa7LSEKERjjGkt6tRdpqpzVPUlwB+yVs4MVd3UKNGZRjdlXF/iPZVXooj3uJkyrm+UIjLGtAZ1Sj4icrqIfI+zrs5+EVkqImc2TmgmEiYMy+GeiYPpGNLSOXVABxvtZoxpVHUZan0u8G+c5avnBYtPAM4HzlbVjxolwiagJQ+1DqWq3PDiAr5Zu5v3fj2GLOt6M8bUQ4MsJici84F/qepDVcp/A1yiqsfWO9ImqrUkH4DNe4oY//CnjOnXgUcua7Gn1BgTAQ11n89gnFZPVW8CA44kMNP05LRL5NpTejNz6TbmrNwZ7XCMMS1UXZLPAaBDmPJMoKBhwjFNwZUn9aRrRhL/7z8/UOq1NX+MMQ2vLsnnPeAxEelWXhD89yPA2w0blomm2Bg3fzx3IBvzCnnu87XRDscY0wLVJfn8FogD1ojIZhHZAqwBkoHbGyM4Ez0nHJXJGYM7MvXT1WzKK4x2OMaYFqZOSyqIiBv4GTAiWLQQeElVA40QW5PRmgYchNqxr5izHvqUY3uk8/TkEYiEvW5ojDFhHfFoNxF5spavoap645EE1xy01uQD8MIXa/nLe8v5++XHcuqA7GiHY4xpRuqTfNbV8jVUVXscSXDNQWtOPl5/gAv/9gUHir389zdjSIyty3SAxpjWrEHu82nNWnPyAVi0Lo/Lnp7H1Sf34tYz+0U7HGNMM1FT8rGvseawjumezvnHdOafX6zl3GE59OyQckTHmbF4M4/OymVbfrEtWmdMK2ctn1po7S0fgLyCUk594GMCCl5foM7JY8bizdz11hJKQu4bive4uWfiYEtAxrRQ1vIx9TZv1S78AcXrd5Lw1vxi/vDm9yzbkk//TmkUlfkoKvUHf/ooKvNTWOqrKF+0Pq9i33Lli9ZZ8jGm9bHkY2rl0Vm5hySPMl+AF+ccOiYlweMmMc5NUlwMibExJMa5D9m3nC1aZ0zrFPHkIyIXAb8D+gE7gVeAe1S1pJr6Y4A/A8NwlnJ4E/i9qu4NU/cm4FHgKlV9Icz2PUDbKsUPq+pvjvT9tBbVJQkB3r/NGQWXFBdDvMeN23VoK3vs/R/bonXGmAp1Ws+nvkTkcmAaznLcA4HrgIuB16upfwowC/gUGBKsOxz4UEQ8IfVigvckPQS4wxwKEemMk3j6AO2DjwycmRvMYVSXJLLTEuiWkUxmajxJcTFhEw+EX7TOJfCr0/s0eKzGmKYvYslHROKBvwKPqOqjqrpGVd/HSSjniMgZYXb7G/COqv5BVVeq6ufAucAg4MrgcROAD4DxwDk1hDAY2KWqq1R1d/CR19JnZ2go9V3xNHTROgHaJHoIKGzfF7bBa4xp4SLZ7XYSkA68GlqoqotFJBe4EJhZXi4ifXCWavh9lfpbReTTYP2nVbVYRD4BLgdqGpI2GFjWEG+kNSofFFCfodIThuVU1FdVfvPaYv7+0UpG9EhnaLd2jRK3MaZpimTyKb87cUWYbSuA/nWsf0n5E1V9AEBEsmp4/UHAYBHZACQAa4G/qOo7h43cAJWTR32JCHefP5glm/L5zfTFvH3zSaQmeA6/ozGmRYjkNZ9kwKeqZWG2FQJV71xMDtlWm/qH8zBwNXAmcDYwB3hbRCaHqywi14jIQhFZWMfXMbWUkuDh4UnD2LmvhLve/J7Wfi+VMa1JJJNPARAjIrFhtiVx6IJ0BSHbalO/Rqq6SFXfUtXlqrpAVW8DZgC3VlN/qqoe25KXB28KBnduy83j+jJr6Tb+9c3GaIdjjImQSCaf3ODPcJOD9QOW17P+kVgFdG6A45h6uOInPRnVO4P73v2B1dsPRDscY0wERDL5fA7sASaFForIUKAvzv07FVQ1F+faTtX62cCYqvWP0ChgcQMcx9SDyyU88NOhJMfHcOu0RZWm4DHGtEwRSz6qWoyz4uktInKjiPQUkdOB6cAHqvq+iNwpIrnBBANwCzBRRO4WkaNEZDTOkt25wLPlxxaReBFJA1KDRYkikiYiicHtOSLykYhMFpHuIjJQRJ7GuXH1d5F4/6Zm7VPieeDioazZcYAH/muDEo1p6SJ6k6mqPgtMBq7B6TZ7HngXuCBYJRVnOHZssP4s4CxgHLAEeCv4c2yVgQt3AHuBlcHnTwSfly+GtxP4EPg1TmtqLpAFDFPV+Q38Ns0RGt0nkyt+0pPXv97Ah0u3RjscY0wjslmta8FmtY6cMl+Ay56ay4a8Qt66+Sd0apsY7ZCMMUeoplmtI9ryMeZwYmNcPDRpGP6A8tvpi/H5bQIKY1oiSz6myemSnsTd5w9i8fq9PPHxqmiHY4xpBJZ8TJM0fmgO5x/TmWc+Xc38tbujHY4xpoFZ8jFN1u/PHUi3jCR+O/1b9haWRjscY0wDsuRjmqykuBgennQMewvL+N2/bPodY1oSG+1WCzbaLbpenvsj9727jHOGdmLhuj1HPKu2MSayahrtZsmnFiz5RJeqcsHfvmDF1v2VyuM9bu6ZONgSkDFNlA21Ns2aiLCn8NDJ0Eu8fh6dlRtmD2NMU2fJxzQLO6tZ8XRbfnGEIzHGNARLPqZZyE5LqFO5MaZps+RjmoUp4/oS73FXKnOLcPPpfaIUkTGmPiz5mGZhwrAc7pk4mI5pCQiQEh+DX5XvNuXbEGxjmiEb7VYLNtqt6VFVHv5gBc99vparTu7FrWf0RSTsoBpjTJTUNNotJtLBGNMQRIRfn9mPwlIfz362huS4GK49pXe0wzLG1JIlH9NsiQh/PHcQRWXOkOukuBguO6F7tMMyxtSCJR/TrLlcwr0XHk1RqY973/2BpLgYzj+2c7TDMsYchg04MM1ejNvFw5OGMap3Bn/493fMWmKroBrT1FnyMS1CbIybv18+nCFd23Lb9MV8nrsj2iEZY2pgyce0GImxMTw9+Th6Z6Vy88sL+eZHWwfImKbKko9pUVISPDx75XHktEvk+n9+w5JNe6MdkjEmDEs+psVpmxTH81ePJD05jmuem8+qbfsPv5MxJqIs+ZgWKTM1nuevHkmcx82Vz37N+t0F0Q7JGBPCko9psXLaJfL8VcfjV+WKf3zN1r1F0Q7JGBNkyce0aD07pPDslcdTUOLlime/ZveB0miHZIzBko9pBfp3asMzvziOnftKuPLZr8gvOnRhOmNMZFnyMa3C0G7tePznw1m3q5Brn59PYakv2iEZ06pZ8jGtxqje7XnkZ8ewbMs+bnzxG0q8/miHZEyrZcnHtCpjB2Rx/8VD+ObHPKa8spAyXyDaIRnTKtl6PrVg6/m0PG/M38Cf3lrC4M5p7DpQyvb8YrLTEpgyri8ThuVEOzxjWoSa1vOJeMtHRC4SkW9FpERENorIfSISX0P9MSIyV0SKRWSHiDwpIm2rqXuTiPhEZHKYbTEi8kcRWScipSKyVER+0YBvzTQjFx/XlfFDOrJkUz7b8otRYGt+MXe9tYQZizdHOzxjWryIJh8RuRyYBrwIDASuAy4GXq+m/inALOBTYEiw7nDgQxHxhNSLEZEngYcAdzUvPxW4Hvg10B94DHhCRG6p9xszzdLi9YdOvVPiddYGMsY0roit5xNs3fwVeERVHw0WrxGR7cAiETlDVWdW2e1vwDuq+ofg85Uici7wI3Al8LSIJADvAn2Ac3CSVdXXPhb4BXC2qr4fLF4rIqnAvSLygqraJGCtzLb84rDlW/OL+XDpVk7ul0VsjF0WNaYxRPIv6yQgHXg1tFBVFwO5wIWh5SLSBxgQpv5WnJbQhcHnxcAnwHHAkmpe+wJgD1A1ub0KJABn1/ndmGYvOy0hbLlL4OZXFnHyfR/xwIxlrN5+IMKRGdPyRTL59Av+XBFm2wqcrrAjqq+qD6jqtsO89kpVrTS0SVV3AHvDvLZpBaaM60u8p3IvbbzHzX0XDeGZX4xgRI90pn21jnMe+YyfPv4lb8zfQEGJN0rRGtOyRHIZ7WTAp6rhbi8vBFLC1C/fVpv6h3vtcMep9lgicg1wTR1ewzQz5aPaHp2Vy7Ywo91+0rcDewpKeffbzby5YBN/emsJD8xYxrjB2VwwvAvHdGuHSNiBPMaYw4hk8ikAYkQkNkwCSgpur1q/fFtV4eof7rUzq9kW9liqOhVnkAIiYuOsW6gJw3JqHFrdLjmOySf25Oeje7B0cz5vfrOR977fyjuLNtM1I4kLju3Mucd0JjO12gGbxpgwIpl8yocQ9QO+r7KtHzCvhvqrwtRfXsfXHi0irtCuNxHpALSt47FMKyQiDO7clsGd23L7hAF8uHQbby7YyF9n5vLYhys5sU8mFwzvzEl9OzDz+63VtqaMMY6I3WQaHJW2GXhWVW8PKR8KLKbySLTybcuBpar605CybGAdcKuqPlmlfhawDfiFqr4QUj4CmA+cpaofhJTfAtwH5KhqXg2x202mJqz1uwt4a8Em3lm0iV0HSkmOc1PsDeAPHPz/Eu9xc8/EwZaATKtT002mEZ3hQESuAp4EbsEZedYT+DuwVlXPEpE7gZ8DY1R1m4iMA/4L3Itzf1Amzr088cCI8u674DDu+OD2lcCNwfplqloUrPMyMAa4AViKM/ruceD/qepfDhO3JR9TI58/wJcrd3LrtEWUeA+dsqdjWgKf3HlqFCIzJnqazAwHqvosMBnnQv5y4Hmce3QuCFZJxRmOHRusPws4CxiHM4z6reDPsVWuG92BM2ptZfD5E8HnoS2jK4DncJJdLnAbTuupxsRjTG3EuF2M6Z9FaZjEA9XfU2RMa2Vzu9WCtXxMbY29/2O2VpNo/ueE7lx7Sm/Sk+MiHJUx0dFkWj7GtHTh7h2Ki3Exons7Xp23jtP/8gl//3Cl3S9kWj1r+dSCtXxMXcxYvDnsaLd1uwr426xcZi7dRlqih2vH9ObSkd2I81Q3HaExzVuTGXDQXFnyMQ3ph835PDJzBfNW7yarTTw3ntqH847JIcZtHRGmZbHkU0+WfExj+HrNbh6ZuYIlm/Lp3j6JKeP6ctrAbJs1wbQYlnzqyZKPaSyqysfLtvPYrFzW7ixgYE4bbjmjH6N6t492aMbUmyWferLkYxqbP6C8u3gzf/9oJdvyizm+Vwa3ntGPQZ3Toh2aMUfMkk89WfIxkVLm8zP96w08PXs1ewvLOG1gFjef3pflW/bZlD2m2bHkU0+WfEykFZb6eOGLtTz/xVqKyvy4XWJT9phmx5JPPVnyMdGyp6CU0x+cTWGp75Bt2WkJzLYpe0wTZjeZGtNMtUuOoyhM4gFnyp6bX17I9K/Xs353AfYFyTQnkVxSwRhzBLLTEsJO2ZMQ62bJpr18+IOziG92m3hG9m7P8b0yOL5XBu1TbI0h03RZt1stWLebiaYZizdz11tLKPH6K8rKr/mMH9qJ9bsL+XrNbr5as4tv1uaxr9iZuqdXhxRGBhPR8O7ppCR4ovUWTCtl13zqyZKPibbqpuypyh9Qcrfu46tgMlq0bg+lvgBulzAwJ43je2UwqlcGQ7q2JTbGpvUxjcuSTz1Z8jHNVanXz3cb9/LVmt18vWY3SzftJaAQ73ExrFs7RvZqz8heGfTt2Aa3S2qd5IypDUs+9WTJx7QUB4q9LFiXF+ym282aHQcAaJPooXO7RFZu24/Xb0O6TcOw5FNPlnxMS7Vzfwnz1zqtoncWbSIQ5r+5rcJqjpQNtTbGhJWZGs+EoTnce9EQqvt+tTW/mA27CyMbmGnxLPkYYwBnSHd1zvi/2Vzz/Hw+z91BIFzzyJg6sm63WrBuN9MaVDek+zdn9SO/sIzX529g14FSOrdL5NKR3Tj/2M6kJcZGMWLT1Nk1n3qy5GNai5pGu3n9AT7+YTuvfrWORev2EO9xMX5IDpNGdaNfxzZRjtw0RZZ86smSjzGV5W7dx7Sv1jPj282UeAMM69aWSSO7c9rAbGJjrDffOCz51JMlH2PC21dUxtuLNvHaV+vZmFdERkocPz2uKxcf15XMVJvep7Wz5FNPlnyMqVkgoMxZtZNpX63ni5U7cYtw6sBsfjaqG8d0a2dLg7dSlnzqyZKPMbW3Ma+Q6V+t582Fm9hf7KVPdiqTRnZj/NBOJMbaXMatiSWferLkY0zdFZf5eO+7rbw6bx252/aTmuDh/GM6c+nIbizZuNem8WkFLPnUkyUfY46cqvLthr28Om8dHy7dhi+guIRKsynYND4tkyWferLkY0zD2Lm/hPEPf8qBknArs8Yz+87TohCVaSw2vY4xpknITI2nIEziAdiWX8ItryxkxrebyS8qi3BkJtLs6p8xJqKqW5k1MdbNwvV7mLl0G26XcEy3dpzSP4tT+negc3pSFCI1jSniLR8RuUhEvhWREhHZKCL3iUi1NwSIyBgRmSsixSKyQ0SeFJG2Veq0F5HnRGSXiBSJyKciMirMsb4VEa3y+HdjvE9jTHhTxvUl3lN5Ibt4j5u7zx/M5787jek3juaqk3qyp7CMB/67jNMfnM05j3zGozNXsGTTXptbroWI6DUfEbkceA64DfgvcBTwN2CZqp4bpv4pwEzgQeBlIAt4KLh5lKp6RSQBWADsA24H8oArgF8CJ6vq18FjxQAFwNnA98FjKLBPVcP3AxyMw675GNOAarto3ca8Qj5dvoPZy7ezaP0e/AGlfUocY/p1YEz/LEb2yiDOYyuyNlVNYsBBsHWzGXheVX8bUj4MWAScqaozq+zzA7BcVS8OKesI/AhMUdWnReQ3wN1Ad1XdFVLvXSBTVY8PPh8ALAVSVLVO88Nb8jEm+vKLyvgidyefLt/OFyt3UlTmJzHWzaje7Rk7IIuT+mbSNiku2mGaEE0l+YzDacUMUdXvq2xbAcxV1atCyvoAucB5qvqfKvU/ADyqeqqIfAVsV9Xzq9T5KTAd6Kyqm0XkUuA+Ve1+BLFb8jGmCSnz+flmbR6fLN/Op8t3sGN/CS6BoV2d60Rj+nege/tkWxY8ympKPpEccNAv+HNFmG0rgP51rH9JSL1Pq6lD8LibgUFAhoisBVKBTcATOC0xyyzGNCOxMW5G98lkdJ9M7jpPWb5lH7OD3XP/9/5y/u/95bRPiWNPYRn+4DWirfnF3PXWEgBLQE1AJJNPMuBT1XBjKAuBlDD1y7fVVD+5hjqE1HsJ+A6nNeUCzgSeAjrjdNtVIiLXANeEOa4xpgkREQbkpDEgJ41fnt6HLXuL+HT5Dv7v/eUViadcidfPIzNXWPJpAiI52q0AiBGRcKtPJQW3V61fvq2m+gU11Kk4jqrmquobqrpEVb9T1fuBp4FbJMysh6o6VVWPVdVja3xXxpgmpVPbRC47oTteXyDs9m37SrjpxW94e+Em9haWRjg6Uy6SLZ/c4M9+HBxtRkjZvBrqrwpTf3lIvX4cqrxseZht5VbhdMGl4oyWM8a0EDXdT7Rsyz4+Wb7DuU7UrR1j+2dxSv8sumbY/USREskBBwk4116eVdXbQ8qHAouBs1X1/Sr7LAeWqupPQ8qygXXArar6pIj8FrgL6Kaqu0Pq/QfIVtURNcT0GjBCVXseJna7LGRMM1PdsuD3TBzM+KGdWL51H7OX7eCT5dtZuW0/AD0zkxk7wElEg3LScLlsKYj6aBKj3YKBXAU8CdyCM/KtJ/B3YK2qniUidwI/B8ao6rbgCLn/AvcC04BMnPt84nGSRpmIJOEM1d6Jc5/PnuAxfgOMVdUvRSQFZ+TbLOADnO7GScAfgAtV9e3DxG3Jx5hmqLaj3TbvKWL28u3MXr6dhesq3090yoAsju9p9xMdiSaTfILBTMJJEn2BXcBrwF2qWiwi9wNXAceq6oZg/dOAe4ChwH7gHeBOVc0LOWYHnBtRxwOJODed/kFVvwhudwFXAlcDA3FuLv0a+KOqVu3uCxezJR9jWony+4lmL9/OlyH3E40+KpNTBnTgpL4dSEsMd+naVNWkkk9zZMnHmNap1Otn/trdfLJsO7NX7GD3gdJK886NHZBFTrtEoPatrNbEkk89WfIxxgQCytLN+cxevp1Plm1n7U5nwG2f7FRy2ibw5apdlIWMsLM1iiz51JslH2NMVRt2FzqJaPl2Fq3bE7ZO+5Q4PrnzVDzu1rl6jSWferLkY4ypSf/bZ1DdJ4THLXRrn0zvDikclZVK76wUendIoVPbxBY/mq6pTK9jjDEtUnX3FKUlerhoRFdW7zjA9xv38v73Wyu2JXjc9OqQUpGMegcTU/uUOMLc916hpVxbspZPLVjLxxhTk5ruKQpNDIWlPtbsOMDq7QdYtX0/q3ccYM32A+wuODjTQptEz8FkFJKc2iTG1vp1mgrrdqsnSz7GmMOpT4tkT0Gpk5R2HGDVNicprd5+gILSg0uNdUiNJ7+ojNIw0wZ1TEvgkztPbbD30lAs+dSTJR9jTKSpKtv3lbA62EJatf0A7y7eXG39C4d3oXv7ZLq3T6J7ZjI5bROJifJAB0s+9WTJxxjTFIy9/+Ow15Y8bhfJ8THsLSwLKRM6t0uie/skurVPDiYmJznVZtG9hri2ZMmnniz5GGOagsNd88kvKmPdrgLW7ypk3a6CisfGvCK8/oPddW0SPXTPSK7UUuqekUzn9CRiY1wNdm3Jkk89WfIxxjQVR9Ii8fkDbNlbHExMwaS020lQuw8cHOzgdgmd2iayY19xg1xbsuRTT5Z8jDEt1YFiL+t3H2wprd9VwMyl28LWFWD5XybU+th2n48xxpiwUhI8DOqcxqDOaRVlS6q5tpSdltBgr9s653wwxhhTrSnj+hJfZQmJeI+bKeP6NthrWMvHGGNMJeXXkBpzJgW75lMLds3HGGPqrqZrPtbtZowxJuIs+RhjjIk4Sz7GGGMizpKPMcaYiLPkY4wxJuIs+RhjjIk4Sz7GGGMizpKPMcaYiLMZDmqppjXVjTHG1I3NcNCARGShqh4b7ThM9ewcNX12jpq+hjhH1u1mjDEm4iz5GGOMiThLPg1rarQDMIdl56jps3PU9NX7HNk1H2OMMRFnLR9jjDERZ8mnAYjIRSLyrYiUiMhGEblPROKjHVdrJiLnisjXInJARDaIyGMi0iZke3cR+ZeI7AvWeVdE+kUz5tZKRJ4WERWRbiFldn6aEBHJEJFlIvKJiHhCyo/4PFnyqScRuRyYBrwIDASuAy4GXo9mXK2ZiFwI/BvnvAwEJgNnAdOD2zsAc4FY4BRgNLAXmCsiPaIQcqslIpOBSVXK7Pw0ISLiBl7DyRcXqKo3WF6/86Sq9jjCBxAP7AYerFI+DFDgjGjH2BofwCLg8Splk4LnpBfwOLARiAvZLsB3wPRox99aHsBQoAD4RfDcdAuW2/lpQg/gfmAX0KNKeb3Ok7V86uckIB14NbRQVRcDucCF0QjKcD5wW5Wy0uBPAS4A3lTV8jLU+ct5DTgntFvBNA4RaQe8hfPB9mmVzXZ+mggROQ+YApyrqj9W2Vyv82TJp37K+zZXhNm2AugfwVhMkKpuVNXiKsWXAT8CeUAW1Z+zBKB740bYuomIC+cL2wrgvirb0rDz0ySISFfgn8BKYKqIrBeR10XkqIY4Tza3W/0kAz5VLQuzrRBIiXA8JgwRuRo4B5gAJAaLC8NULS+z89a4/hfni9lQVdUq8yYmB3/a+Ym+B3D+Xl4DPsBJNvcBXwLDg3WO+DxZ8qmfAiBGRGLDJKCk4HYTRSLyP8BTwK9U9f3gNzZwzk9V5WV23hqJiIzH6RI9SVX3hKlS/ru38xNFwdG6E4GHVPUvweIlIrIU2IwziAfqcZ4s+dRPbvBnP+D7Ktv6AfMiG44JJSLX4CSeW1X1CQBVzReRHRzsMg3VDyjB6Z4zjeNqnM+dWSEtnvLu/yXAasDOT/S1xRnFNje0UFW3icg2oBP1PE92zad+Pgf2cOhQ0aFAX+DNaARlQESmcLDF81iVzW8BF4hIbEh9AS4FZmhwKKlpFJfhjDgcEvI4K7jtLOBM7Pw0BTtxPtsGhxaKSCcgG+fLdv3OU7SH8TX3B3AVUAbcCPQETse5QPd+tGNrrQ/g90AAuBlnNGJG8JGOM9otG+db25s4w30HAs8D+4De0Y6/tT2AblQeam3npwk8gp9p+4D/AboCPwEWBBNPbH3Pk7V86klVn8Xp/7wGWI7zy38XZxiiibDg3dV/xvkwewTnPqxdwcdu4DpV3YZzQ5wLp/X6Nc7F1NGqujoacZuD7Pw0Dep0Vf8K58vcauBfwFc41+vK6nuebGJRY4wxEWctH2OMMRFnyccYY0zEWfIxxhgTcZZ8jDHGRJwlH2OMMRFnyccYY0zEWfIxppUIzkr8dLTjMAYs+RhjjIkCSz7GGGMizpKPMREgIrEicq+IbBSRIhFZKCJnBLfdLSJfiMiIYHmJiOSKyJlVjnGqiMwRkWIR2SMirwUX/Aqtc5aILAgeI09EnhGRNiFV3CLyJxHZLiJ7ReQlEUkJ2f9cEfk2+BobRORXwcXfjGlQ9p/KmMh4EmdG52txZjx/BHhDRI4Nbj8WuB1notqjgWXAmyLSGUBEjgNmAXNwZoI+FWgHfCoiCcE6o4AZOEt5DAXG4Ezy2DEkjstwlhQfgTMb+wXAXcH9u+PM3/UGcBTOnIVtcObJM6ZB2dxuxjQyETkKZ+2niar6Tkj5YxxcivhOIFmD09CLSAawHbhFVf8uIp8CLlU9KWT/dGAT8EdVfThYJ15VR1YTx3rgY1W9KqTsdZwZiIeJyEnAZ8AwVf22wX4BxoRhLR9jGt8wnKUcXhKR/PIHzkzoXYJ1VEPWP1HV3TjJp2ewaASHLuyVh7N8x6iQOp8fJhZfled7cVpQ4LSY3gXmici/RORSEfHU7i0aUzeWfIxpfOVJ5XwqL6LWDxhfw36ekH3BSWA1EerRRaaqXlU9FzgBZwr9vwFfhS4WZkxDsWW0jWl8CwA/0F1VP6m6MWQ56dCy3kAmztLSAAs52MIpr5MO9AGmBYu+xVlfpV5UdTGwWET+i9PaGhA8tjENxlo+xjQyVd2I04p4INiV1UVEjhGRR0XkZ8FqcSLyZxHpLSIjgFeBH4HXg9vvBEYHR8z1Di7VPg1nkbwngnX+GKzzoIj0EpFBIvKPqqPmqiMix4nIkyIyRES64CyHvBdY0xC/B2NCWfIxJjJuA+4PPtbiXFtJAD4Kbi8F8nFaGp8BO4ETVbUMQFXnAScBp+C0hj4F8oDjVbUoWGc2cBZwJs6quh8GjzunljGuwenq+wRntN3RwFmqeuDI3rIx1bPRbsZEmYjcDdyhqvHRjsWYSLGWjzHGmIiz5GOMMSbirNvNGGNMxFnLxxhjTMRZ8jHGGBNxlnyMMcZEnCUfY4wxEWfJxxhjTMRZ8jHGGBNx/x+MvBW8vqUjPQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# load pre-trained model and plot its training history\n", "run_name = 'model'\n", @@ -456,10 +1097,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "9894d03f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 24/24 [00:00<00:00, 36.67it/s] \n" + ] + } + ], "source": [ "# predict on all data\n", "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", @@ -486,40 +1135,90 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "98b42f42", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# compare to partial DoS\n", "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", @@ -540,10 +1239,78 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "ac684344", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1/1 [00:00<00:00, 4519.72it/s] \n" + ] + }, + { + "data": { + "text/html": [ + "
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mp_idstructurephfreqphdospdosformulaspecies
0NaN{}[0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14...[0.0, 0.37267476543017564, 0.8879380855551154,...{}Mg3Bi1.5Sb0.5['Mg', 'Bi', 'Sb']
\n", + "
" + ], + "text/plain": [ + " mp_id structure phfreq \\\n", + "0 NaN {} [0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 14... \n", + "\n", + " phdos pdos formula \\\n", + "0 [0.0, 0.37267476543017564, 0.8879380855551154,... {} Mg3Bi1.5Sb0.5 \n", + "\n", + " species \n", + "0 ['Mg', 'Bi', 'Sb'] " + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# load calculated alloy example\n", "df_alloy, _ = load_data('data/data_alloy.csv')\n", @@ -552,10 +1319,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "43b05950", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "index of Mg3Sb2: 474 \n", + "index of Mg3Bi2: 1521\n" + ] + } + ], "source": [ "# get indices of parent structures\n", "idx_Mg3Sb2 = df.loc[df['mp_id'] == 'mp-2646'].index.to_numpy()[0]\n", @@ -565,10 +1341,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "9aa217c5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 99/99 [00:00<00:00, 185.72it/s] \n" + ] + } + ], "source": [ "# interpolate atomic positions and lattice constants\n", "# 2-hot encode the atomic mass, weighted by the fraction of each species\n", @@ -613,10 +1397,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "82e59c46", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 4/4 [00:00<00:00, 49.77it/s] \n" + ] + } + ], "source": [ "# predict on all alloy structures\n", "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", @@ -638,10 +1430,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "id": "dee5de9a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "# plot predictions, and compare with calculated result for selected compound\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,6), gridspec_kw={'width_ratios': [1,2]})\n", diff --git a/phononDoS_colab.ipynb b/phononDoS_colab.ipynb index 1add92a..8ecc279 100644 --- a/phononDoS_colab.ipynb +++ b/phononDoS_colab.ipynb @@ -1,859 +1,867 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "phononDoS_colab.ipynb", - "provenance": [], - "collapsed_sections": [], - "authorship_tag": "ABX9TyP9WdY8pU0J3fdzaTpnaMJ8", - "include_colab_link": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "view-in-github", - "colab_type": "text" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "_v7BmDsQgutC" - }, - "source": [ - "## Tutorial | Predicting phonon DoS with `e3nn`\n", - "### Getting started\n", - "* Go to Runtime > Change runtime type, and select GPU.\n", - "* Clone the GitHub repository to access the tutorial files:" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "Xd4k295fOzl7" - }, - "source": [ - "!git clone https://github.com/ninarina12/phononDoS_tutorial.git\n", - "%cd phononDoS_tutorial" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cumoRx6GhLKW" - }, - "source": [ - "* Install some relevant packages (should take < 1 minute).\n", - "\n" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "JobVnat5O5fT" - }, - "source": [ - "!pip install ase e3nn\n", - "!pip install torch-scatter torch-cluster torch-sparse torch-spline-conv -f https://pytorch-geometric.com/whl/torch-$(python -c \"import torch; print(torch.__version__)\").html\n", - "!pip install torch-geometric" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "iKp3KG4HhZqh" - }, - "source": [ - "### Tutorial" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "l45yb_JnQ0eD" - }, - "source": [ - "# model\n", - "import torch\n", - "import torch.nn as nn\n", - "import torch.nn.functional as F\n", - "import torch_geometric as tg\n", - "import torch_scatter\n", - "import e3nn\n", - "from e3nn import o3\n", - "from typing import Dict, Union\n", - "\n", - "# crystal structure data\n", - "from ase import Atom, Atoms\n", - "from ase.neighborlist import neighbor_list\n", - "from ase.visualize.plot import plot_atoms\n", - "\n", - "# data pre-processing and visualization\n", - "import numpy as np\n", - "import matplotlib as mpl\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n", - "from IPython.display import HTML\n", - "\n", - "# utilities\n", - "import time\n", - "from tqdm import tqdm\n", - "from utils.utils_data import (load_data, train_valid_test_split, plot_example, plot_predictions, plot_partials,\n", - " palette, colors, cmap)\n", - "from utils.utils_model import Network, visualize_layers, train\n", - "from utils.utils_plot import plotly_surface, plot_orbitals, get_middle_feats\n", - "\n", - "bar_format = '{l_bar}{bar:10}{r_bar}{bar:-10b}'\n", - "default_dtype = torch.float64\n", - "torch.set_default_dtype(default_dtype)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "I1Z-W3T75bfM" - }, - "source": [ - "### Data provenance\n", - "We train our model using the database of Density Functional Perturbation Theory (DFPT)-calculated phonon densities of states (DoS), containing approximately 1,500 crystalline solids [[Petretto et al. 2018]](https://doi.org/10.1038/sdata.2018.65)." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "zTXZExsvWWey" - }, - "source": [ - "# load data\n", - "df, species = load_data('data/data.csv')\n", - "df.head()" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nPWFGltW54MI" - }, - "source": [ - "### Data structures\n", - "Crystal structures are represented as [ASE](https://wiki.fysik.dtu.dk/ase/ase/atoms.html?highlight=atoms#the-atoms-object) (Atomic Simulation Environment) `Atoms` objects, which store the atomic species and positions of each atom in the unit cell, as well as the lattice vectors of the unit cell." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "dMnXRZ8RhCGr" - }, - "source": [ - "# plot an example structure\n", - "i = 12 # structure index in dataframe\n", - "\n", - "struct = df.iloc[i]['structure']\n", - "symbols = np.unique(list(struct.symbols))\n", - "z = dict(zip(symbols, range(len(symbols))))\n", - "\n", - "fig, ax = plt.subplots(figsize=(6,5))\n", - "norm = plt.Normalize(vmin=0, vmax=len(symbols)-1)\n", - "color = [mpl.colors.to_hex(k) for k in cmap(norm([z[j] for j in list(struct.symbols)]))]\n", - "plot_atoms(struct, ax, radii=0.25, colors=color, rotation=('0x,90y,0z'))\n", - "\n", - "ax.set_xlabel(r'$x_1\\ (\\AA)$')\n", - "ax.set_ylabel(r'$x_2\\ (\\AA)$');" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "1GymBzWq6ThN" - }, - "source": [ - "# lattice parameter statistics\n", - "def get_lattice_parameters(df):\n", - " a = []\n", - " for entry in df.itertuples():\n", - " a.append(entry.structure.cell.cellpar()[:3])\n", - " return np.stack(a)\n", - "\n", - "a = get_lattice_parameters(df)\n", - "\n", - "fig, ax = plt.subplots(1,1, figsize=(5,4))\n", - "b = 0.\n", - "bins = 50\n", - "for d, c, n in zip(['a', 'b', 'c'], colors.values(), [a[:,0], a[:,1], a[:,2]]):\n", - " color = [int(c.lstrip('#')[i:i+2], 16)/255. for i in (0,2,4)]\n", - " y, bins, _, = ax.hist(n, bins=bins, fc=color+[0.7], ec=color, bottom=b, label=d)\n", - " b += y\n", - "ax.set_xlabel('lattice parameter')\n", - "ax.set_ylabel('number of examples')\n", - "ax.legend(frameon=False)\n", - "\n", - "print('average lattice parameter (a/b/c):', a[:,0].mean(), '/', a[:,1].mean(), '/', a[:,2].mean())" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6dn1JFrY6ZWz" - }, - "source": [ - "### Feature representation\n", - "We construct the inputs to our neural network following the `e3nn` [Documentation](https://docs.e3nn.org/en/latest/guide/periodic_boundary_conditions.html) on handling point inputs with periodic boundary conditions. For a given crystal, each atom in the unit cell is associated with a feature vector that one-hot encodes its atomic mass in the index corresponding to its atomic number. The unit cell of the crystal is encoded as a graph in which two atoms (nodes) are joined by an edge if they are within a cutoff radius `r_max` of one another." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "CEjH-a586Z8V" - }, - "source": [ - "# one-hot encoding atom type and mass\n", - "type_encoding = {}\n", - "specie_am = []\n", - "for Z in tqdm(range(1, 119), bar_format=bar_format):\n", - " specie = Atom(Z)\n", - " type_encoding[specie.symbol] = Z\n", - " specie_am.append(specie.mass)\n", - "\n", - "type_onehot = torch.eye(len(type_encoding))\n", - "am_onehot = torch.diag(torch.tensor(specie_am))" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "2pEoARfd6eb2" - }, - "source": [ - "# build data\n", - "def build_data(entry, type_encoding, type_onehot, r_max=5.):\n", - " symbols = list(entry.structure.symbols).copy()\n", - " positions = torch.from_numpy(entry.structure.positions.copy())\n", - " lattice = torch.from_numpy(entry.structure.cell.array.copy()).unsqueeze(0)\n", - "\n", - " # edge_src and edge_dst are the indices of the central and neighboring atom, respectively\n", - " # edge_shift indicates whether the neighbors are in different images or copies of the unit cell\n", - " edge_src, edge_dst, edge_shift = neighbor_list(\"ijS\", a=entry.structure, cutoff=r_max, self_interaction=True)\n", - " \n", - " # compute the relative distances and unit cell shifts from periodic boundaries\n", - " edge_batch = positions.new_zeros(positions.shape[0], dtype=torch.long)[torch.from_numpy(edge_src)]\n", - " edge_vec = (positions[torch.from_numpy(edge_dst)]\n", - " - positions[torch.from_numpy(edge_src)]\n", - " + torch.einsum('ni,nij->nj', torch.tensor(edge_shift, dtype=default_dtype), lattice[edge_batch]))\n", - "\n", - " # compute edge lengths (rounded only for plotting purposes)\n", - " edge_len = np.around(edge_vec.norm(dim=1).numpy(), decimals=2)\n", - " \n", - " data = tg.data.Data(\n", - " pos=positions, lattice=lattice, symbol=symbols,\n", - " x=am_onehot[[type_encoding[specie] for specie in symbols]], # atomic mass (node feature)\n", - " z=type_onehot[[type_encoding[specie] for specie in symbols]], # atom type (node attribute)\n", - " edge_index=torch.stack([torch.LongTensor(edge_src), torch.LongTensor(edge_dst)], dim=0),\n", - " edge_shift=torch.tensor(edge_shift, dtype=default_dtype),\n", - " edge_vec=edge_vec, edge_len=edge_len,\n", - " phdos=torch.from_numpy(entry.phdos).unsqueeze(0)\n", - " )\n", - " \n", - " return data\n", - "\n", - "r_max = 4. # cutoff radius\n", - "df['data'] = df.progress_apply(lambda x: build_data(x, type_encoding, type_onehot, r_max), axis=1)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "1AGI3yIx6ho9" - }, - "source": [ - "i = 12 # structure index in dataframe\n", - "plot_example(df, i=i, label_edges=True)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "hY_oakVo6j4Q" - }, - "source": [ - "### Training, validation, and testing datasets\n", - "Split the data into training, validation, and testing datasets with balanced representation of different elements in each set." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "1R6i_FUQ6mml" - }, - "source": [ - "# train/valid/test split\n", - "idx_train, idx_valid, idx_test = train_valid_test_split(df, species, valid_size=.1, test_size=.1, seed=12, plot=True)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "z20LxeLP61m6" - }, - "source": [ - "For use with the trained model provided, the indices of the training, validation, and test sets are loaded below. These indices were generated with a specific seed using the above `train_valid_test_split` function." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "NLEaj3-J62Nz" - }, - "source": [ - "# load train/valid/test indices\n", - "with open('data/idx_train.txt', 'r') as f: idx_train = [int(i.split('\\n')[0]) for i in f.readlines()]\n", - "with open('data/idx_valid.txt', 'r') as f: idx_valid = [int(i.split('\\n')[0]) for i in f.readlines()]\n", - "with open('data/idx_test.txt', 'r') as f: idx_test = [int(i.split('\\n')[0]) for i in f.readlines()]\n", - "\n", - "# format dataloaders\n", - "batch_size = 1\n", - "dataloader_train = tg.loader.DataLoader(df.iloc[idx_train]['data'].values, batch_size=batch_size, shuffle=True)\n", - "dataloader_valid = tg.loader.DataLoader(df.iloc[idx_valid]['data'].values, batch_size=batch_size)\n", - "dataloader_test = tg.loader.DataLoader(df.iloc[idx_test]['data'].values, batch_size=batch_size)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "blEhP5Bh64s3" - }, - "source": [ - "# calculate average number of neighbors\n", - "def get_neighbors(df, idx):\n", - " n = []\n", - " for entry in df.iloc[idx].itertuples():\n", - " N = entry.data.pos.shape[0]\n", - " for i in range(N):\n", - " n.append(len((entry.data.edge_index[0] == i).nonzero()))\n", - " return np.array(n)\n", - "\n", - "n_train = get_neighbors(df, idx_train)\n", - "n_valid = get_neighbors(df, idx_valid)\n", - "n_test = get_neighbors(df, idx_test)\n", - "\n", - "fig, ax = plt.subplots(1,1, figsize=(5,4))\n", - "b = 0.\n", - "bins = 50\n", - "for (d, c), n in zip(colors.items(), [n_train, n_valid, n_test]):\n", - " color = [int(c.lstrip('#')[i:i+2], 16)/255. for i in (0,2,4)]\n", - " y, bins, _, = ax.hist(n, bins=bins, fc=color+[0.7], ec=color, bottom=b, label=d)\n", - " b += y\n", - "ax.set_xlabel('number of neighbors')\n", - "ax.set_ylabel('number of examples')\n", - "ax.legend(frameon=False)\n", - "\n", - "print('average number of neighbors (train/valid/test):', n_train.mean(), '/', n_valid.mean(), '/', n_test.mean())" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "LZtSOwB9Cols" - }, - "source": [ - "### Network architecture\n", - "We build a model based on the `Network` described in the `e3nn` [Documentation](https://docs.e3nn.org/en/latest/api/nn/models/gate_points_2101.html), modified to incorporate the periodic boundaries we imposed on the crystal graphs. The network applies equivariant convolutions to each atomic node and finally takes an average over all nodes, normalizing the output." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "X3xO0DoQ69uo" - }, - "source": [ - "class PeriodicNetwork(Network):\n", - " def __init__(self, in_dim, em_dim, **kwargs): \n", - " # override the `reduce_output` keyword to instead perform an averge over atom contributions \n", - " self.pool = False\n", - " if kwargs['reduce_output'] == True:\n", - " kwargs['reduce_output'] = False\n", - " self.pool = True\n", - " \n", - " super().__init__(**kwargs)\n", - "\n", - " # embed the mass-weighted one-hot encoding\n", - " self.em = nn.Linear(in_dim, em_dim)\n", - "\n", - " def forward(self, data: Union[tg.data.Data, Dict[str, torch.Tensor]]) -> torch.Tensor:\n", - " data.x = F.relu(self.em(data.x))\n", - " data.z = F.relu(self.em(data.z))\n", - " output = super().forward(data)\n", - " output = torch.relu(output)\n", - " \n", - " # if pool_nodes was set to True, use scatter_mean to aggregate\n", - " if self.pool == True:\n", - " output = torch_scatter.scatter_mean(output, data.batch, dim=0) # take mean over atoms per example\n", - " \n", - " maxima, _ = torch.max(output, dim=1)\n", - " output = output.div(maxima.unsqueeze(1))\n", - " \n", - " return output" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "d904KAn77BBl" - }, - "source": [ - "out_dim = len(df.iloc[0]['phfreq'])\n", - "em_dim = 64 \n", - "\n", - "model = PeriodicNetwork(\n", - " in_dim=118, # dimension of one-hot encoding of atom type\n", - " em_dim=em_dim, # dimension of atom-type embedding\n", - " irreps_in=str(em_dim)+\"x0e\", # em_dim scalars (L=0 and even parity) on each atom to represent atom type\n", - " irreps_out=str(out_dim)+\"x0e\", # out_dim scalars (L=0 and even parity) to output\n", - " irreps_node_attr=str(em_dim)+\"x0e\", # em_dim scalars (L=0 and even parity) on each atom to represent atom type\n", - " layers=2, # number of nonlinearities (number of convolutions = layers + 1)\n", - " mul=32, # multiplicity of irreducible representations\n", - " lmax=1, # maximum order of spherical harmonics\n", - " max_radius=r_max, # cutoff radius for convolution\n", - " num_neighbors=n_train.mean(), # scaling factor based on the typical number of neighbors\n", - " reduce_output=True # whether or not to aggregate features of all atoms at the end\n", - ")\n", - "\n", - "print(model)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "pIb6-dq87DqK" - }, - "source": [ - "# visualize tensor products of the model\n", - "visualize_layers(model)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-5cuaOFOC_D_" - }, - "source": [ - "### Training\n", - "The model is trained using a mean-squared error loss function with an Adam optimizer." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "ERK8uX1vC_Zy" - }, - "source": [ - "opt = torch.optim.AdamW(model.parameters(), lr=0.005, weight_decay=0.05)\n", - "scheduler = torch.optim.lr_scheduler.ExponentialLR(opt, gamma=0.96)\n", - "\n", - "loss_fn = torch.nn.MSELoss()\n", - "loss_fn_mae = torch.nn.L1Loss()" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "38dUj1WpDBLh" - }, - "source": [ - "device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n", - "print('torch device:' , device)\n", - "\n", - "run_name = 'model_' + time.strftime(\"%y%m%d\", time.localtime())\n", - "print(run_name)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "mC7DaaymDLTP" - }, - "source": [ - "model.pool = True\n", - "train(model, opt, dataloader_train, dataloader_valid, loss_fn, loss_fn_mae, run_name,\n", - " max_iter=1, scheduler=scheduler, device=device)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "VRCWlA-xDQaK" - }, - "source": [ - "# load pre-trained model and plot its training history\n", - "run_name = 'model'\n", - "\n", - "history = torch.load(run_name + '.torch', map_location=device)['history']\n", - "steps = [d['step'] + 1 for d in history]\n", - "loss_train = [d['train']['loss'] for d in history]\n", - "loss_valid = [d['valid']['loss'] for d in history]\n", - "\n", - "fig, ax = plt.subplots(figsize=(6,5))\n", - "ax.plot(steps, loss_train, 'o-', label=\"Training\", color=colors['train'])\n", - "ax.plot(steps, loss_valid, 'o-', label=\"Validation\", color=colors['valid'])\n", - "ax.set_xlabel('epochs')\n", - "ax.set_ylabel('loss')\n", - "ax.legend(frameon=False);" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "5kpYlnpwEFW3" - }, - "source": [ - "### Results\n", - "We evaluate our model by visualizing the predicted and true DoS in each error quartile. We further compare the hidden features learned for each node to the partial DoS." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "p04FoU5dEFr2" - }, - "source": [ - "# predict on all data\n", - "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", - "model.pool = True\n", - "\n", - "dataloader = tg.loader.DataLoader(df['data'].values, batch_size=64)\n", - "df['mse'] = 0.\n", - "df['phdos_pred'] = np.empty((len(df), 0)).tolist()\n", - "\n", - "model.to(device)\n", - "model.eval()\n", - "with torch.no_grad():\n", - " i0 = 0\n", - " for i, d in tqdm(enumerate(dataloader), total=len(dataloader), bar_format=bar_format):\n", - " d.to(device)\n", - " output = model(d)\n", - " loss = F.mse_loss(output, d.phdos, reduction='none').mean(dim=-1).cpu().numpy()\n", - " df.loc[i0:i0 + len(d.phdos) - 1, 'phdos_pred'] = [[k] for k in output.cpu().numpy()]\n", - " df.loc[i0:i0 + len(d.phdos) - 1, 'mse'] = loss\n", - " i0 += len(d.phdos)\n", - " \n", - "df['phdos_pred'] = df['phdos_pred'].map(lambda x: x[0])" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "zyQH05qpEIoD" - }, - "source": [ - "plot_predictions(df, idx_train, 'Training')" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "lcZPaHO3EKy4" - }, - "source": [ - "plot_predictions(df, idx_valid, 'Validation')" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "akcuwjRrEK2y" - }, - "source": [ - "plot_predictions(df, idx_test, 'Testing')" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "l2WWbtwsEQVV" - }, - "source": [ - "# compare to partial DoS\n", - "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", - "model.pool = False\n", - "\n", - "# plot example predicted and true partial dos\n", - "plot_partials(model, df, idx_train, device=device)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Vg3iENN5ESa2" - }, - "source": [ - "### Alloys\n", - "The current framework extends easily to the representation of alloy structures. As an example, we will predict the phonon DoS of the Mg3(Bi,Sb)2 system, incrementally varying the relative fractions of Bi and Sb. Note that both parent compounds, Mg3Sb2 and Mg3Bi2, are present in our training data. We will check the validity by comparing the predicted and calculated phonon DoS of Mg3Bi1.5Sb0.5." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "9qgk-qwcERhz" - }, - "source": [ - "# load calculated alloy example\n", - "df_alloy, _ = load_data('data/data_alloy.csv')\n", - "df_alloy.head()" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "YU3ynm06EZLu" - }, - "source": [ - "# get indices of parent structures\n", - "idx_Mg3Sb2 = df.loc[df['mp_id'] == 'mp-2646'].index.to_numpy()[0]\n", - "idx_Mg3Bi2 = df.loc[df['mp_id'] == 'mp-569018'].index.to_numpy()[0]\n", - "print(f'index of Mg3Sb2: {idx_Mg3Sb2}', f'\\nindex of Mg3Bi2: {idx_Mg3Bi2}')" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "t9Jl5-HLEa-2" - }, - "source": [ - "# interpolate atomic positions and lattice constants\n", - "# 2-hot encode the atomic mass, weighted by the fraction of each species\n", - "data_alloy = []\n", - "x_Bi = np.linspace(0.01, 0.99, 99)\n", - "\n", - "for i, p in tqdm(enumerate(x_Bi), total=len(x_Bi), bar_format=bar_format):\n", - " symbols = df['data'][idx_Mg3Bi2].symbol.copy()\n", - " positions = torch.lerp(df['data'][idx_Mg3Sb2].pos.clone(), df['data'][idx_Mg3Bi2].pos.clone(), p)\n", - " lattice = torch.lerp(df['data'][idx_Mg3Sb2].lattice.clone(), df['data'][idx_Mg3Bi2].lattice.clone(), p)\n", - "\n", - " # edge_src and edge_dst are the indices of the central and neighboring atom, respectively\n", - " # edge_shift indicates whether the neighbors are in different images or copies of the unit cell\n", - " struct = df.iloc[idx_Mg3Bi2].structure.copy()\n", - " struct.positions = positions.numpy().copy()\n", - " struct.cell = lattice.numpy().squeeze().copy()\n", - " edge_src, edge_dst, edge_shift = neighbor_list(\"ijS\", a=struct, cutoff=r_max, self_interaction=True)\n", - " \n", - " # compute the relative distances and unit cell shifts from periodic boundaries\n", - " edge_batch = positions.new_zeros(positions.shape[0], dtype=torch.long)[torch.from_numpy(edge_src)]\n", - " edge_vec = (positions[torch.from_numpy(edge_dst)]\n", - " - positions[torch.from_numpy(edge_src)]\n", - " + torch.einsum('ni,nij->nj', torch.tensor(edge_shift, dtype=default_dtype), lattice[edge_batch]))\n", - "\n", - " # compute edge lengths (rounded only for plotting purposes)\n", - " edge_len = np.around(edge_vec.norm(dim=1).numpy(), decimals=2)\n", - " \n", - " data_alloy.append(\n", - " tg.data.Data(\n", - " pos=positions, \n", - " lattice=lattice, \n", - " symbol=symbols,\n", - " x=torch.lerp(df['data'][idx_Mg3Sb2].x, df['data'][idx_Mg3Bi2].x, p),\n", - " z=torch.lerp(df['data'][idx_Mg3Sb2].z, df['data'][idx_Mg3Bi2].z, p),\n", - " edge_index=torch.stack([torch.LongTensor(edge_src), torch.LongTensor(edge_dst)], dim=0),\n", - " edge_shift=torch.tensor(edge_shift, dtype=default_dtype),\n", - " edge_vec=edge_vec, edge_len=edge_len,\n", - " phdos=df['data'][idx_Mg3Bi2].phdos.clone()\n", - " )\n", - " )" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "JU4IhPPlEcvU" - }, - "source": [ - "# predict on all alloy structures\n", - "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", - "model.pool = True\n", - "\n", - "dataloader = tg.loader.DataLoader([df.iloc[idx_Mg3Sb2]['data']] + data_alloy + [df.iloc[idx_Mg3Bi2]['data']],\n", - " batch_size=32)\n", - "\n", - "output = np.zeros((len(data_alloy) + 2, len(df_alloy['phdos'][0])))\n", - "model.to(device)\n", - "model.eval()\n", - "with torch.no_grad():\n", - " i0 = 0\n", - " for i, d in tqdm(enumerate(dataloader), total=len(dataloader), bar_format=bar_format):\n", - " d.to(device)\n", - " output[i0:i0 + len(d.phdos),:] = model(d).cpu().numpy()\n", - " i0 += len(d.phdos)" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "wVkxRig3Ekdb" - }, - "source": [ - "# plot predictions, and compare with calculated result for selected compound\n", - "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,6), gridspec_kw={'width_ratios': [1,2]})\n", - "color = cmap(np.linspace(0, 1, len(output)))\n", - "f = df_alloy['phfreq'][0]\n", - "\n", - "# waterfall plot of alloy predictions\n", - "s = 2./len(x_Bi)\n", - "for i in range(len(output)):\n", - " ax1.plot(f, output[i]/output[i].max() + i*s, c=color[i])\n", - "ax1.set_yticklabels([])\n", - "ax1.set_xlabel('$Frequency\\ (cm^{-1})$')\n", - "ax1.set_ylabel('$Intensity$')\n", - "\n", - "sm = mpl.cm.ScalarMappable(cmap=cmap)\n", - "sm.set_array([])\n", - "cax = inset_axes(ax1, width=\"40%\", height=\"4%\", loc=3, bbox_to_anchor=(0.5,0.9,1,1), bbox_transform=ax1.transAxes) \n", - "cbar = fig.colorbar(sm, cax=cax, aspect=16, orientation='horizontal', pad=-0.1)\n", - "cbar.ax.set_xlabel('$x_{Bi}$', fontsize=16, labelpad=-5)\n", - " \n", - "# comparison to calculation\n", - "p = x_Bi.tolist().index(0.75)\n", - "ax2.remove()\n", - "ax2 = fig.add_subplot(122, projection='3d')\n", - "\n", - "# plot calculations\n", - "ax2.plot(f, [0.75]*len(f), df_alloy['phdos'][0], lw=1.5, c='black', label='Calculated')\n", - "ax2.plot(f, [0]*len(f), df.iloc[idx_Mg3Sb2]['phdos'], lw=1.5, c='black')\n", - "ax2.plot(f, [1]*len(f), df.iloc[idx_Mg3Bi2]['phdos'], lw=1.5, c='black')\n", - "\n", - "# plot predictions\n", - "ax2.plot(f, [0.75]*len(f), output[p]/output[p].max(), lw=2, c=palette[1], label='Predicted (alloy)')\n", - "ax2.plot(f, [0]*len(f), output[0]/output[0].max(), lw=2, c=palette[0], label='Predicted (pure)')\n", - "ax2.plot(f, [1]*len(f), output[-1]/output[-1].max(), lw=2, c=palette[0])\n", - "\n", - "ax2.view_init(elev=20, azim=-50)\n", - "ax2.w_xaxis.set_pane_color((1., 1., 1., 1.))\n", - "ax2.w_yaxis.set_pane_color((1., 1., 1., 1.))\n", - "ax2.w_zaxis.set_pane_color((0.9, 0.9, 0.9, 1.))\n", - "ax2.grid(False)\n", - "ax2.w_xaxis.line.set_color('dimgray'); ax2.w_yaxis.line.set_color('dimgray'); ax2.w_zaxis.line.set_color('dimgray')\n", - " \n", - "ax2.set_xlabel('$Frequency\\ (cm^{-1})$', labelpad=14)\n", - "ax2.set_ylabel('$x_{Bi}$', labelpad=10)\n", - "ax2.set_zlabel('$Intensity$', labelpad=10)\n", - "ax2.legend(frameon=False, bbox_to_anchor=(0.9,0.4), bbox_transform=fig.transFigure);" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "wN1vfDM5FyFs" - }, - "source": [ - "### Visualization of intermediate features\n", - "We can visualize the intermediate features on each node projected onto the basis of spherical harmonics." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "XHt1kAUHFvDP" - }, - "source": [ - "d = next(iter(dataloader_train))\n", - "specie = d.symbol[0]\n", - "sts, st_feats = get_middle_feats(d, model, normalize=True)\n", - "\n", - "for sts_idx in range(len(sts)):\n", - " traces, traces_species = plotly_surface(sts[sts_idx], st_feats[sts_idx].detach().cpu(), centers=d.pos.cpu(),\n", - " res=20, radius=True, species=specie)\n", - " fig_html = plot_orbitals(traces, traces_species, title_str=f'feature: {str(sts[sts_idx])}')\n", - " \n", - " with open(f'feature_{str(sts[sts_idx])}.html', 'w') as f:\n", - " f.write(fig_html)\n", - "\n", - "imgs = [f'feature_{str(sts[sts_idx])}.html' for sts_idx in range(len(sts))]\n", - "\n", - "for img in imgs:\n", - " display(HTML(filename=img))" - ], - "execution_count": null, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "5_CCJ5mEkjEN" - }, - "source": [ - "" - ], - "execution_count": null, - "outputs": [] - } - ] -} \ No newline at end of file + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "view-in-github" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_v7BmDsQgutC" + }, + "source": [ + "## Tutorial | Predicting phonon DoS with `e3nn`\n", + "### Getting started\n", + "* Go to Runtime > Change runtime type, and select GPU.\n", + "* Clone the GitHub repository to access the tutorial files:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Xd4k295fOzl7" + }, + "outputs": [], + "source": [ + "!git clone https://github.com/ninarina12/phononDoS_tutorial.git\n", + "%cd phononDoS_tutorial" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cumoRx6GhLKW" + }, + "source": [ + "* Install some relevant packages (should take < 1 minute).\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JobVnat5O5fT" + }, + "outputs": [], + "source": [ + "!pip install ase e3nn\n", + "!pip install torch-scatter torch-cluster torch-sparse torch-spline-conv -f https://pytorch-geometric.com/whl/torch-$(python -c \"import torch; print(torch.__version__)\").html\n", + "!pip install torch-geometric" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iKp3KG4HhZqh" + }, + "source": [ + "### Tutorial" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "l45yb_JnQ0eD" + }, + "outputs": [], + "source": [ + "# model\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch_geometric as tg\n", + "import torch_scatter\n", + "import e3nn\n", + "from e3nn import o3\n", + "from typing import Dict, Union\n", + "\n", + "# crystal structure data\n", + "from ase import Atom, Atoms\n", + "from ase.neighborlist import neighbor_list\n", + "from ase.visualize.plot import plot_atoms\n", + "\n", + "# data pre-processing and visualization\n", + "import numpy as np\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n", + "from IPython.display import HTML\n", + "\n", + "# utilities\n", + "import time\n", + "from tqdm import tqdm\n", + "from utils.utils_data import (load_data, train_valid_test_split, plot_example, plot_predictions, plot_partials,\n", + " palette, colors, cmap)\n", + "from utils.utils_model import Network, visualize_layers, train\n", + "from utils.utils_plot import plotly_surface, plot_orbitals, get_middle_feats\n", + "\n", + "bar_format = '{l_bar}{bar:10}{r_bar}{bar:-10b}'\n", + "default_dtype = torch.float64\n", + "torch.set_default_dtype(default_dtype)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "I1Z-W3T75bfM" + }, + "source": [ + "### Data provenance\n", + "We train our model using the database of Density Functional Perturbation Theory (DFPT)-calculated phonon densities of states (DoS), containing approximately 1,500 crystalline solids [[Petretto et al. 2018]](https://doi.org/10.1038/sdata.2018.65)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zTXZExsvWWey" + }, + "outputs": [], + "source": [ + "# load data\n", + "df, species = load_data('data/data.csv')\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nPWFGltW54MI" + }, + "source": [ + "### Data structures\n", + "Crystal structures are represented as [ASE](https://wiki.fysik.dtu.dk/ase/ase/atoms.html?highlight=atoms#the-atoms-object) (Atomic Simulation Environment) `Atoms` objects, which store the atomic species and positions of each atom in the unit cell, as well as the lattice vectors of the unit cell." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "dMnXRZ8RhCGr" + }, + "outputs": [], + "source": [ + "# plot an example structure\n", + "i = 12 # structure index in dataframe\n", + "\n", + "struct = df.iloc[i]['structure']\n", + "symbols = np.unique(list(struct.symbols))\n", + "z = dict(zip(symbols, range(len(symbols))))\n", + "\n", + "fig, ax = plt.subplots(figsize=(6,5))\n", + "norm = plt.Normalize(vmin=0, vmax=len(symbols)-1)\n", + "color = [mpl.colors.to_hex(k) for k in cmap(norm([z[j] for j in list(struct.symbols)]))]\n", + "plot_atoms(struct, ax, radii=0.25, colors=color, rotation=('0x,90y,0z'))\n", + "\n", + "ax.set_xlabel(r'$x_1\\ (\\AA)$')\n", + "ax.set_ylabel(r'$x_2\\ (\\AA)$');" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1GymBzWq6ThN" + }, + "outputs": [], + "source": [ + "# lattice parameter statistics\n", + "def get_lattice_parameters(df):\n", + " a = []\n", + " for entry in df.itertuples():\n", + " a.append(entry.structure.cell.cellpar()[:3])\n", + " return np.stack(a)\n", + "\n", + "a = get_lattice_parameters(df)\n", + "\n", + "fig, ax = plt.subplots(1,1, figsize=(5,4))\n", + "b = 0.\n", + "bins = 50\n", + "for d, c, n in zip(['a', 'b', 'c'], colors.values(), [a[:,0], a[:,1], a[:,2]]):\n", + " color = [int(c.lstrip('#')[i:i+2], 16)/255. for i in (0,2,4)]\n", + " y, bins, _, = ax.hist(n, bins=bins, fc=color+[0.7], ec=color, bottom=b, label=d)\n", + " b += y\n", + "ax.set_xlabel('lattice parameter')\n", + "ax.set_ylabel('number of examples')\n", + "ax.legend(frameon=False)\n", + "\n", + "print('average lattice parameter (a/b/c):', a[:,0].mean(), '/', a[:,1].mean(), '/', a[:,2].mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6dn1JFrY6ZWz" + }, + "source": [ + "### Feature representation\n", + "We construct the inputs to our neural network following the `e3nn` [Documentation](https://docs.e3nn.org/en/latest/guide/periodic_boundary_conditions.html) on handling point inputs with periodic boundary conditions. For a given crystal, each atom in the unit cell is associated with a feature vector that one-hot encodes its atomic mass in the index corresponding to its atomic number. The unit cell of the crystal is encoded as a graph in which two atoms (nodes) are joined by an edge if they are within a cutoff radius `r_max` of one another." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "CEjH-a586Z8V" + }, + "outputs": [], + "source": [ + "# one-hot encoding atom type and mass\n", + "type_encoding = {}\n", + "specie_am = []\n", + "for Z in tqdm(range(1, 119), bar_format=bar_format):\n", + " specie = Atom(Z)\n", + " type_encoding[specie.symbol] = Z - 1\n", + " specie_am.append(specie.mass)\n", + "\n", + "type_onehot = torch.eye(len(type_encoding))\n", + "am_onehot = torch.diag(torch.tensor(specie_am))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2pEoARfd6eb2" + }, + "outputs": [], + "source": [ + "# build data\n", + "def build_data(entry, type_encoding, type_onehot, r_max=5.):\n", + " symbols = list(entry.structure.symbols).copy()\n", + " positions = torch.from_numpy(entry.structure.positions.copy())\n", + " lattice = torch.from_numpy(entry.structure.cell.array.copy()).unsqueeze(0)\n", + "\n", + " # edge_src and edge_dst are the indices of the central and neighboring atom, respectively\n", + " # edge_shift indicates whether the neighbors are in different images or copies of the unit cell\n", + " edge_src, edge_dst, edge_shift = neighbor_list(\"ijS\", a=entry.structure, cutoff=r_max, self_interaction=True)\n", + " \n", + " # compute the relative distances and unit cell shifts from periodic boundaries\n", + " edge_batch = positions.new_zeros(positions.shape[0], dtype=torch.long)[torch.from_numpy(edge_src)]\n", + " edge_vec = (positions[torch.from_numpy(edge_dst)]\n", + " - positions[torch.from_numpy(edge_src)]\n", + " + torch.einsum('ni,nij->nj', torch.tensor(edge_shift, dtype=default_dtype), lattice[edge_batch]))\n", + "\n", + " # compute edge lengths (rounded only for plotting purposes)\n", + " edge_len = np.around(edge_vec.norm(dim=1).numpy(), decimals=2)\n", + " \n", + " data = tg.data.Data(\n", + " pos=positions, lattice=lattice, symbol=symbols,\n", + " x=am_onehot[[type_encoding[specie] for specie in symbols]], # atomic mass (node feature)\n", + " z=type_onehot[[type_encoding[specie] for specie in symbols]], # atom type (node attribute)\n", + " edge_index=torch.stack([torch.LongTensor(edge_src), torch.LongTensor(edge_dst)], dim=0),\n", + " edge_shift=torch.tensor(edge_shift, dtype=default_dtype),\n", + " edge_vec=edge_vec, edge_len=edge_len,\n", + " phdos=torch.from_numpy(entry.phdos).unsqueeze(0)\n", + " )\n", + " \n", + " return data\n", + "\n", + "r_max = 4. # cutoff radius\n", + "df['data'] = df.progress_apply(lambda x: build_data(x, type_encoding, type_onehot, r_max), axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1AGI3yIx6ho9" + }, + "outputs": [], + "source": [ + "i = 12 # structure index in dataframe\n", + "plot_example(df, i=i, label_edges=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hY_oakVo6j4Q" + }, + "source": [ + "### Training, validation, and testing datasets\n", + "Split the data into training, validation, and testing datasets with balanced representation of different elements in each set." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1R6i_FUQ6mml" + }, + "outputs": [], + "source": [ + "# train/valid/test split\n", + "idx_train, idx_valid, idx_test = train_valid_test_split(df, species, valid_size=.1, test_size=.1, seed=12, plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "z20LxeLP61m6" + }, + "source": [ + "For use with the trained model provided, the indices of the training, validation, and test sets are loaded below. These indices were generated with a specific seed using the above `train_valid_test_split` function." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NLEaj3-J62Nz" + }, + "outputs": [], + "source": [ + "# load train/valid/test indices\n", + "with open('data/idx_train.txt', 'r') as f: idx_train = [int(i.split('\\n')[0]) for i in f.readlines()]\n", + "with open('data/idx_valid.txt', 'r') as f: idx_valid = [int(i.split('\\n')[0]) for i in f.readlines()]\n", + "with open('data/idx_test.txt', 'r') as f: idx_test = [int(i.split('\\n')[0]) for i in f.readlines()]\n", + "\n", + "# format dataloaders\n", + "batch_size = 1\n", + "dataloader_train = tg.loader.DataLoader(df.iloc[idx_train]['data'].values, batch_size=batch_size, shuffle=True)\n", + "dataloader_valid = tg.loader.DataLoader(df.iloc[idx_valid]['data'].values, batch_size=batch_size)\n", + "dataloader_test = tg.loader.DataLoader(df.iloc[idx_test]['data'].values, batch_size=batch_size)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "blEhP5Bh64s3" + }, + "outputs": [], + "source": [ + "# calculate average number of neighbors\n", + "def get_neighbors(df, idx):\n", + " n = []\n", + " for entry in df.iloc[idx].itertuples():\n", + " N = entry.data.pos.shape[0]\n", + " for i in range(N):\n", + " n.append(len((entry.data.edge_index[0] == i).nonzero()))\n", + " return np.array(n)\n", + "\n", + "n_train = get_neighbors(df, idx_train)\n", + "n_valid = get_neighbors(df, idx_valid)\n", + "n_test = get_neighbors(df, idx_test)\n", + "\n", + "fig, ax = plt.subplots(1,1, figsize=(5,4))\n", + "b = 0.\n", + "bins = 50\n", + "for (d, c), n in zip(colors.items(), [n_train, n_valid, n_test]):\n", + " color = [int(c.lstrip('#')[i:i+2], 16)/255. for i in (0,2,4)]\n", + " y, bins, _, = ax.hist(n, bins=bins, fc=color+[0.7], ec=color, bottom=b, label=d)\n", + " b += y\n", + "ax.set_xlabel('number of neighbors')\n", + "ax.set_ylabel('number of examples')\n", + "ax.legend(frameon=False)\n", + "\n", + "print('average number of neighbors (train/valid/test):', n_train.mean(), '/', n_valid.mean(), '/', n_test.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LZtSOwB9Cols" + }, + "source": [ + "### Network architecture\n", + "We build a model based on the `Network` described in the `e3nn` [Documentation](https://docs.e3nn.org/en/latest/api/nn/models/gate_points_2101.html), modified to incorporate the periodic boundaries we imposed on the crystal graphs. The network applies equivariant convolutions to each atomic node and finally takes an average over all nodes, normalizing the output." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "X3xO0DoQ69uo" + }, + "outputs": [], + "source": [ + "class PeriodicNetwork(Network):\n", + " def __init__(self, in_dim, em_dim, **kwargs): \n", + " # override the `reduce_output` keyword to instead perform an averge over atom contributions \n", + " self.pool = False\n", + " if kwargs['reduce_output'] == True:\n", + " kwargs['reduce_output'] = False\n", + " self.pool = True\n", + " \n", + " super().__init__(**kwargs)\n", + "\n", + " # embed the mass-weighted one-hot encoding\n", + " self.em = nn.Linear(in_dim, em_dim)\n", + "\n", + " def forward(self, data: Union[tg.data.Data, Dict[str, torch.Tensor]]) -> torch.Tensor:\n", + " data.x = F.relu(self.em(data.x))\n", + " data.z = F.relu(self.em(data.z))\n", + " output = super().forward(data)\n", + " output = torch.relu(output)\n", + " \n", + " # if pool_nodes was set to True, use scatter_mean to aggregate\n", + " if self.pool == True:\n", + " output = torch_scatter.scatter_mean(output, data.batch, dim=0) # take mean over atoms per example\n", + " \n", + " maxima, _ = torch.max(output, dim=1)\n", + " output = output.div(maxima.unsqueeze(1))\n", + " \n", + " return output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "d904KAn77BBl" + }, + "outputs": [], + "source": [ + "out_dim = len(df.iloc[0]['phfreq'])\n", + "em_dim = 64 \n", + "\n", + "model = PeriodicNetwork(\n", + " in_dim=118, # dimension of one-hot encoding of atom type\n", + " em_dim=em_dim, # dimension of atom-type embedding\n", + " irreps_in=str(em_dim)+\"x0e\", # em_dim scalars (L=0 and even parity) on each atom to represent atom type\n", + " irreps_out=str(out_dim)+\"x0e\", # out_dim scalars (L=0 and even parity) to output\n", + " irreps_node_attr=str(em_dim)+\"x0e\", # em_dim scalars (L=0 and even parity) on each atom to represent atom type\n", + " layers=2, # number of nonlinearities (number of convolutions = layers + 1)\n", + " mul=32, # multiplicity of irreducible representations\n", + " lmax=1, # maximum order of spherical harmonics\n", + " max_radius=r_max, # cutoff radius for convolution\n", + " num_neighbors=n_train.mean(), # scaling factor based on the typical number of neighbors\n", + " reduce_output=True # whether or not to aggregate features of all atoms at the end\n", + ")\n", + "\n", + "print(model)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "pIb6-dq87DqK" + }, + "outputs": [], + "source": [ + "# visualize tensor products of the model\n", + "visualize_layers(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-5cuaOFOC_D_" + }, + "source": [ + "### Training\n", + "The model is trained using a mean-squared error loss function with an Adam optimizer." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ERK8uX1vC_Zy" + }, + "outputs": [], + "source": [ + "opt = torch.optim.AdamW(model.parameters(), lr=0.005, weight_decay=0.05)\n", + "scheduler = torch.optim.lr_scheduler.ExponentialLR(opt, gamma=0.96)\n", + "\n", + "loss_fn = torch.nn.MSELoss()\n", + "loss_fn_mae = torch.nn.L1Loss()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "38dUj1WpDBLh" + }, + "outputs": [], + "source": [ + "device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n", + "print('torch device:' , device)\n", + "\n", + "run_name = 'model_' + time.strftime(\"%y%m%d\", time.localtime())\n", + "print(run_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "mC7DaaymDLTP" + }, + "outputs": [], + "source": [ + "model.pool = True\n", + "train(model, opt, dataloader_train, dataloader_valid, loss_fn, loss_fn_mae, run_name,\n", + " max_iter=1, scheduler=scheduler, device=device)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "VRCWlA-xDQaK" + }, + "outputs": [], + "source": [ + "# load pre-trained model and plot its training history\n", + "run_name = 'model'\n", + "\n", + "history = torch.load(run_name + '.torch', map_location=device)['history']\n", + "steps = [d['step'] + 1 for d in history]\n", + "loss_train = [d['train']['loss'] for d in history]\n", + "loss_valid = [d['valid']['loss'] for d in history]\n", + "\n", + "fig, ax = plt.subplots(figsize=(6,5))\n", + "ax.plot(steps, loss_train, 'o-', label=\"Training\", color=colors['train'])\n", + "ax.plot(steps, loss_valid, 'o-', label=\"Validation\", color=colors['valid'])\n", + "ax.set_xlabel('epochs')\n", + "ax.set_ylabel('loss')\n", + "ax.legend(frameon=False);" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "5kpYlnpwEFW3" + }, + "source": [ + "### Results\n", + "We evaluate our model by visualizing the predicted and true DoS in each error quartile. We further compare the hidden features learned for each node to the partial DoS." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "p04FoU5dEFr2" + }, + "outputs": [], + "source": [ + "# predict on all data\n", + "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", + "model.pool = True\n", + "\n", + "dataloader = tg.loader.DataLoader(df['data'].values, batch_size=64)\n", + "df['mse'] = 0.\n", + "df['phdos_pred'] = np.empty((len(df), 0)).tolist()\n", + "\n", + "model.to(device)\n", + "model.eval()\n", + "with torch.no_grad():\n", + " i0 = 0\n", + " for i, d in tqdm(enumerate(dataloader), total=len(dataloader), bar_format=bar_format):\n", + " d.to(device)\n", + " output = model(d)\n", + " loss = F.mse_loss(output, d.phdos, reduction='none').mean(dim=-1).cpu().numpy()\n", + " df.loc[i0:i0 + len(d.phdos) - 1, 'phdos_pred'] = [[k] for k in output.cpu().numpy()]\n", + " df.loc[i0:i0 + len(d.phdos) - 1, 'mse'] = loss\n", + " i0 += len(d.phdos)\n", + " \n", + "df['phdos_pred'] = df['phdos_pred'].map(lambda x: x[0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zyQH05qpEIoD" + }, + "outputs": [], + "source": [ + "plot_predictions(df, idx_train, 'Training')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lcZPaHO3EKy4" + }, + "outputs": [], + "source": [ + "plot_predictions(df, idx_valid, 'Validation')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "akcuwjRrEK2y" + }, + "outputs": [], + "source": [ + "plot_predictions(df, idx_test, 'Testing')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "l2WWbtwsEQVV" + }, + "outputs": [], + "source": [ + "# compare to partial DoS\n", + "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", + "model.pool = False\n", + "\n", + "# plot example predicted and true partial dos\n", + "plot_partials(model, df, idx_train, device=device)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Vg3iENN5ESa2" + }, + "source": [ + "### Alloys\n", + "The current framework extends easily to the representation of alloy structures. As an example, we will predict the phonon DoS of the Mg3(Bi,Sb)2 system, incrementally varying the relative fractions of Bi and Sb. Note that both parent compounds, Mg3Sb2 and Mg3Bi2, are present in our training data. We will check the validity by comparing the predicted and calculated phonon DoS of Mg3Bi1.5Sb0.5." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "9qgk-qwcERhz" + }, + "outputs": [], + "source": [ + "# load calculated alloy example\n", + "df_alloy, _ = load_data('data/data_alloy.csv')\n", + "df_alloy.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "YU3ynm06EZLu" + }, + "outputs": [], + "source": [ + "# get indices of parent structures\n", + "idx_Mg3Sb2 = df.loc[df['mp_id'] == 'mp-2646'].index.to_numpy()[0]\n", + "idx_Mg3Bi2 = df.loc[df['mp_id'] == 'mp-569018'].index.to_numpy()[0]\n", + "print(f'index of Mg3Sb2: {idx_Mg3Sb2}', f'\\nindex of Mg3Bi2: {idx_Mg3Bi2}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t9Jl5-HLEa-2" + }, + "outputs": [], + "source": [ + "# interpolate atomic positions and lattice constants\n", + "# 2-hot encode the atomic mass, weighted by the fraction of each species\n", + "data_alloy = []\n", + "x_Bi = np.linspace(0.01, 0.99, 99)\n", + "\n", + "for i, p in tqdm(enumerate(x_Bi), total=len(x_Bi), bar_format=bar_format):\n", + " symbols = df['data'][idx_Mg3Bi2].symbol.copy()\n", + " positions = torch.lerp(df['data'][idx_Mg3Sb2].pos.clone(), df['data'][idx_Mg3Bi2].pos.clone(), p)\n", + " lattice = torch.lerp(df['data'][idx_Mg3Sb2].lattice.clone(), df['data'][idx_Mg3Bi2].lattice.clone(), p)\n", + "\n", + " # edge_src and edge_dst are the indices of the central and neighboring atom, respectively\n", + " # edge_shift indicates whether the neighbors are in different images or copies of the unit cell\n", + " struct = df.iloc[idx_Mg3Bi2].structure.copy()\n", + " struct.positions = positions.numpy().copy()\n", + " struct.cell = lattice.numpy().squeeze().copy()\n", + " edge_src, edge_dst, edge_shift = neighbor_list(\"ijS\", a=struct, cutoff=r_max, self_interaction=True)\n", + " \n", + " # compute the relative distances and unit cell shifts from periodic boundaries\n", + " edge_batch = positions.new_zeros(positions.shape[0], dtype=torch.long)[torch.from_numpy(edge_src)]\n", + " edge_vec = (positions[torch.from_numpy(edge_dst)]\n", + " - positions[torch.from_numpy(edge_src)]\n", + " + torch.einsum('ni,nij->nj', torch.tensor(edge_shift, dtype=default_dtype), lattice[edge_batch]))\n", + "\n", + " # compute edge lengths (rounded only for plotting purposes)\n", + " edge_len = np.around(edge_vec.norm(dim=1).numpy(), decimals=2)\n", + " \n", + " data_alloy.append(\n", + " tg.data.Data(\n", + " pos=positions, \n", + " lattice=lattice, \n", + " symbol=symbols,\n", + " x=torch.lerp(df['data'][idx_Mg3Sb2].x, df['data'][idx_Mg3Bi2].x, p),\n", + " z=torch.lerp(df['data'][idx_Mg3Sb2].z, df['data'][idx_Mg3Bi2].z, p),\n", + " edge_index=torch.stack([torch.LongTensor(edge_src), torch.LongTensor(edge_dst)], dim=0),\n", + " edge_shift=torch.tensor(edge_shift, dtype=default_dtype),\n", + " edge_vec=edge_vec, edge_len=edge_len,\n", + " phdos=df['data'][idx_Mg3Bi2].phdos.clone()\n", + " )\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JU4IhPPlEcvU" + }, + "outputs": [], + "source": [ + "# predict on all alloy structures\n", + "model.load_state_dict(torch.load(run_name + '.torch', map_location=device)['state'])\n", + "model.pool = True\n", + "\n", + "dataloader = tg.loader.DataLoader([df.iloc[idx_Mg3Sb2]['data']] + data_alloy + [df.iloc[idx_Mg3Bi2]['data']],\n", + " batch_size=32)\n", + "\n", + "output = np.zeros((len(data_alloy) + 2, len(df_alloy['phdos'][0])))\n", + "model.to(device)\n", + "model.eval()\n", + "with torch.no_grad():\n", + " i0 = 0\n", + " for i, d in tqdm(enumerate(dataloader), total=len(dataloader), bar_format=bar_format):\n", + " d.to(device)\n", + " output[i0:i0 + len(d.phdos),:] = model(d).cpu().numpy()\n", + " i0 += len(d.phdos)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wVkxRig3Ekdb" + }, + "outputs": [], + "source": [ + "# plot predictions, and compare with calculated result for selected compound\n", + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,6), gridspec_kw={'width_ratios': [1,2]})\n", + "color = cmap(np.linspace(0, 1, len(output)))\n", + "f = df_alloy['phfreq'][0]\n", + "\n", + "# waterfall plot of alloy predictions\n", + "s = 2./len(x_Bi)\n", + "for i in range(len(output)):\n", + " ax1.plot(f, output[i]/output[i].max() + i*s, c=color[i])\n", + "ax1.set_yticklabels([])\n", + "ax1.set_xlabel('$Frequency\\ (cm^{-1})$')\n", + "ax1.set_ylabel('$Intensity$')\n", + "\n", + "sm = mpl.cm.ScalarMappable(cmap=cmap)\n", + "sm.set_array([])\n", + "cax = inset_axes(ax1, width=\"40%\", height=\"4%\", loc=3, bbox_to_anchor=(0.5,0.9,1,1), bbox_transform=ax1.transAxes) \n", + "cbar = fig.colorbar(sm, cax=cax, aspect=16, orientation='horizontal', pad=-0.1)\n", + "cbar.ax.set_xlabel('$x_{Bi}$', fontsize=16, labelpad=-5)\n", + " \n", + "# comparison to calculation\n", + "p = x_Bi.tolist().index(0.75)\n", + "ax2.remove()\n", + "ax2 = fig.add_subplot(122, projection='3d')\n", + "\n", + "# plot calculations\n", + "ax2.plot(f, [0.75]*len(f), df_alloy['phdos'][0], lw=1.5, c='black', label='Calculated')\n", + "ax2.plot(f, [0]*len(f), df.iloc[idx_Mg3Sb2]['phdos'], lw=1.5, c='black')\n", + "ax2.plot(f, [1]*len(f), df.iloc[idx_Mg3Bi2]['phdos'], lw=1.5, c='black')\n", + "\n", + "# plot predictions\n", + "ax2.plot(f, [0.75]*len(f), output[p]/output[p].max(), lw=2, c=palette[1], label='Predicted (alloy)')\n", + "ax2.plot(f, [0]*len(f), output[0]/output[0].max(), lw=2, c=palette[0], label='Predicted (pure)')\n", + "ax2.plot(f, [1]*len(f), output[-1]/output[-1].max(), lw=2, c=palette[0])\n", + "\n", + "ax2.view_init(elev=20, azim=-50)\n", + "ax2.w_xaxis.set_pane_color((1., 1., 1., 1.))\n", + "ax2.w_yaxis.set_pane_color((1., 1., 1., 1.))\n", + "ax2.w_zaxis.set_pane_color((0.9, 0.9, 0.9, 1.))\n", + "ax2.grid(False)\n", + "ax2.w_xaxis.line.set_color('dimgray'); ax2.w_yaxis.line.set_color('dimgray'); ax2.w_zaxis.line.set_color('dimgray')\n", + " \n", + "ax2.set_xlabel('$Frequency\\ (cm^{-1})$', labelpad=14)\n", + "ax2.set_ylabel('$x_{Bi}$', labelpad=10)\n", + "ax2.set_zlabel('$Intensity$', labelpad=10)\n", + "ax2.legend(frameon=False, bbox_to_anchor=(0.9,0.4), bbox_transform=fig.transFigure);" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wN1vfDM5FyFs" + }, + "source": [ + "### Visualization of intermediate features\n", + "We can visualize the intermediate features on each node projected onto the basis of spherical harmonics." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "XHt1kAUHFvDP" + }, + "outputs": [], + "source": [ + "d = next(iter(dataloader_train))\n", + "specie = d.symbol[0]\n", + "sts, st_feats = get_middle_feats(d, model, normalize=True)\n", + "\n", + "for sts_idx in range(len(sts)):\n", + " traces, traces_species = plotly_surface(sts[sts_idx], st_feats[sts_idx].detach().cpu(), centers=d.pos.cpu(),\n", + " res=20, radius=True, species=specie)\n", + " fig_html = plot_orbitals(traces, traces_species, title_str=f'feature: {str(sts[sts_idx])}')\n", + " \n", + " with open(f'feature_{str(sts[sts_idx])}.html', 'w') as f:\n", + " f.write(fig_html)\n", + "\n", + "imgs = [f'feature_{str(sts[sts_idx])}.html' for sts_idx in range(len(sts))]\n", + "\n", + "for img in imgs:\n", + " display(HTML(filename=img))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5_CCJ5mEkjEN" + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "authorship_tag": "ABX9TyP9WdY8pU0J3fdzaTpnaMJ8", + "collapsed_sections": [], + "include_colab_link": true, + "name": "phononDoS_colab.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}