diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..64a2dfe --- /dev/null +++ b/.gitignore @@ -0,0 +1,111 @@ +# Prerequisites +*.d + +# Compiled object files +*.slo +*.lo +*.o +*.obj + +# Precompiled headers +*.gch +*.pch + +# Compiled dynamic libraries +*.so +*.so.[0-9]* +*.dylib +*.dll + +# Fortran module files +*.mod +*.smod + +# Compiled static libraries +*.lai +*.la +*.a +*.lib + +# Executables +*.exe +*.out +*.app + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +.installed.cfg +MANIFEST +*.egg-info/ +*.egg +*.manifest +*.spec +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*,cover +.pytest_cache/ + +# Documentation +doc/html/ +doc/latex/ +doc/man/ +doc/xml/ +doc/_build/ +doc/source +doc/modules + +# Environments +.env +.venv +env/ +venv/ +ENV/ + +# Editor junk +tags +[._]*.s[a-v][a-z] +[._]*.sw[a-p] +[._]s[a-v][a-z] +[._]sw[a-p] +*~ +\#*\# +.\#* +.ropeproject +.idea/ +.spyderproject +.spyproject +.vscode/ +# Mac .DS_Store +.DS_Store + +# jupyter notebook checkpoints +.ipynb_checkpoints + +# version file +graphchem/_version.py diff --git a/examples/comparison/train_cn.ipynb b/examples/comparison/train_cn.ipynb index 52dc7e6..c0f6fd9 100644 --- a/examples/comparison/train_cn.ipynb +++ b/examples/comparison/train_cn.ipynb @@ -16,12 +16,13 @@ "source": [ "from csv import DictReader\n", "\n", - "with open('schweidtmann_train.csv', 'r') as csv_file:\n", + "\n", + "with open(\"schweidtmann_train.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_train = [r for r in reader]\n", "csv_file.close()\n", "\n", - "with open('schweidtmann_test.csv', 'r') as csv_file:\n", + "with open(\"schweidtmann_test.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_test = [r for r in reader]\n", "csv_file.close()\n", @@ -39,26 +40,35 @@ "output_type": "stream", "text": [ "204 32\n", - "204 32\n" + "204 32\n", + "torch.Size([204, 1]) torch.Size([32, 1])\n" ] } ], "source": [ + "import torch\n", + "\n", + "\n", "smiles_train, cn_train = [], []\n", "smiles_test, cn_test = [], []\n", "\n", "for sample in rows_train:\n", - " if sample['Meas DCN'] != 'n.a.':\n", - " smiles_train.append(sample[' SMILES'])\n", - " cn_train.append([float(sample['Meas DCN'])])\n", + " if sample[\"Meas DCN\"] != \"n.a.\":\n", + " smiles_train.append(sample[\" SMILES\"])\n", + " cn_train.append([float(sample[\"Meas DCN\"])])\n", "\n", "for sample in rows_test:\n", - " if sample['Meas DCN'] != 'n.a.':\n", - " smiles_test.append(sample[' SMILES'])\n", - " cn_test.append([float(sample['Meas DCN'])])\n", + " if sample[\"Meas DCN\"] != \"n.a.\":\n", + " smiles_test.append(sample[\" SMILES\"])\n", + " cn_test.append([float(sample[\"Meas DCN\"])])\n", "\n", "print(len(smiles_train), len(smiles_test))\n", - "print(len(cn_train), len(cn_test))" + "print(len(cn_train), len(cn_test))\n", + "\n", + "cn_train = torch.tensor(cn_train)\n", + "cn_test = torch.tensor(cn_test)\n", + "\n", + "print(cn_train.shape, cn_test.shape)" ] }, { @@ -78,6 +88,7 @@ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", "encoding_train = encoder.encode_many(smiles_train)\n", @@ -97,30 +108,22 @@ "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "0: 61.74284714343501 | 795.7464592754841 | 795.7464592754841\n", - "25: 16.076067644007065 | 539.4501098524779 | 211.72807756066322\n", - "50: 9.909391216203279 | 321.94421773962677 | 157.69625366595574\n", - "75: 8.118035297767788 | 330.7769658435136 | 136.2820148949977\n", - "100: 4.977010726928711 | 126.15307217370719 | 126.15307217370719\n", - "125: 4.05040672713635 | 100.61456597534107 | 99.73899516346864\n", - "150: 3.098002835816028 | 86.74723993893713 | 86.25332806864753\n", - "175: 3.6347995739357146 | 89.04888651048532 | 80.64544883184135\n", - "200: 1.806081870022942 | 131.17046163489067 | 80.64544883184135\n", - "225: 1.318576272796182 | 93.5751825706102 | 80.64544883184135\n", - "250: 0.6833704616509232 | 95.6268904217286 | 69.75570413470268\n", - "275: 2.2236440836214553 | 115.3701195018366 | 69.75570413470268\n" + "0: 59.873857236376 | 893.1569682371119 | 893.1569682371119\n", + "25: 12.940126344269396 | 256.78371555171907 | 230.00700168521143\n", + "50: 8.715352469799566 | 181.79883558955044 | 148.44034498126712\n", + "75: 10.528010966731053 | 184.97101854289042 | 125.58490085601807\n", + "100: 5.29324197769165 | 104.20410126633942 | 101.58139284176286\n", + "125: 3.9122854120591106 | 83.46006474722526 | 81.64288164488971\n", + "150: 2.837108897227867 | 108.61055618838873 | 65.07187549872151\n", + "175: 4.191495483996821 | 165.71973400365096 | 65.07187549872151\n", + "200: 2.61629552934684 | 84.91348252853186 | 65.07187549872151\n", + "225: 1.0769017864676083 | 88.50968079734594 | 63.49760713002979\n", + "250: 0.7046413187887154 | 77.24297919708624 | 62.08507445192663\n", + "275: 0.9892499540366378 | 79.81229424569756 | 53.760969512106385\n" ] }, { @@ -159,6 +162,7 @@ "from torch_geometric.loader import DataLoader\n", "from copy import deepcopy\n", "\n", + "\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", "\n", @@ -172,7 +176,7 @@ " n_messages=3,\n", " n_readout=5,\n", " readout_dim=128,\n", - " dropout=0.0\n", + " p_dropout=0.0\n", ")\n", "\n", "init_lr = 0.001\n", @@ -190,7 +194,7 @@ "for epoch in range(300):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -217,7 +221,7 @@ " _best_epoch = epoch\n", "\n", " if epoch % 25 == 0:\n", - " print(f'{epoch}: {train_loss} | {test_loss} | {_lowest_loss}')\n", + " print(f\"{epoch}: {train_loss} | {test_loss} | {_lowest_loss}\")\n", "\n", "model.load_state_dict(_best_weights)\n", "\n", @@ -240,7 +244,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -252,16 +256,17 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", - "ax2.axvline(x=_best_epoch, color='black', linestyle='--')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", + "ax2.axvline(x=_best_epoch, color=\"black\", linestyle=\"--\")\n", "plt.show()" ] }, @@ -272,7 +277,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -288,12 +293,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental CN')\n", - "plt.ylabel('Predicted CN')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental CN\")\n", + "plt.ylabel(\"Predicted CN\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -306,195 +311,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.552288055419922\n", - "Test R2: 0.892784930555452\n" + "Test MAE: 5.052592046558857\n", + "Test R2: 0.9151456197241049\n" ] } ], "source": [ "from sklearn.metrics import mean_absolute_error, r2_score\n", "\n", - "e_test = [e[0] for e in exp_test]\n", - "p_test = [p[0] for p in pred_test]\n", - "\n", - "print(f'Test MAE: {mean_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1...\n", - "2...\n", - "3...\n", - "4...\n", - "5...\n", - "6...\n", - "7...\n", - "8...\n", - "9...\n", - "10...\n", - "11...\n", - "12...\n", - "13...\n", - "14...\n", - "15...\n", - "16...\n", - "17...\n", - "18...\n", - "19...\n", - "20...\n", - "21...\n", - "22...\n", - "23...\n", - "24...\n", - "25...\n", - "26...\n", - "27...\n", - "28...\n", - "29...\n", - "30...\n", - "31...\n", - "32...\n", - "33...\n", - "34...\n", - "35...\n", - "36...\n", - "37...\n", - "38...\n", - "39...\n" - ] - } - ], - "source": [ - "test_preds = []\n", - "\n", - "for i in range(40):\n", - "\n", - " print(f'{i}...')\n", - "\n", - " model = MoleculeGCN(\n", - " atom_vocab_size,\n", - " bond_vocab_size,\n", - " 1,\n", - " embedding_dim=64,\n", - " n_messages=3,\n", - " n_readout=5,\n", - " readout_dim=128,\n", - " dropout=0.0\n", - " )\n", - "\n", - " init_lr = 0.001\n", - " lr_decay = 1e-7\n", - " optimizer = torch.optim.Adam(model.parameters(), lr=init_lr)\n", - "\n", - " _lowest_loss = 1e10\n", - " _best_weights = None\n", - "\n", - " model.train()\n", - " for epoch in range(300):\n", - "\n", - " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", - "\n", - " for batch in train_loader:\n", - " optimizer.zero_grad()\n", - " pred, _, _ = model(batch)\n", - " loss = F.mse_loss(pred, batch.y)\n", - " loss.backward()\n", - " optimizer.step()\n", - "\n", - " test_loss = 0.0\n", - " for batch in test_loader:\n", - " pred, _, _ = model(batch)\n", - " loss = F.mse_loss(pred, batch.y)\n", - " test_loss += loss.detach().item()\n", - " test_loss /= len(test_loader.dataset)\n", - " test_losses.append(test_loss)\n", - "\n", - " if test_loss < _lowest_loss:\n", - " _lowest_loss = test_loss\n", - " _best_weights = deepcopy(model.state_dict())\n", - "\n", - " model.load_state_dict(_best_weights)\n", - " model.eval()\n", - "\n", - " pred_test = [model(mol)[0].detach().numpy() for mol in ds_test]\n", - " test_preds.append(pred_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Test MAE: 5.288445472717285\n", - "Test R2: 0.9163198665286514\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "\n", - "ave_test_preds = np.mean(np.array(test_preds), axis=0)\n", - "test_preds_1d = [p[0][0] for p in ave_test_preds]\n", "\n", "e_test = [e[0] for e in exp_test]\n", + "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {mean_absolute_error(e_test, test_preds_1d)}')\n", - "print(f'Test R2: {r2_score(e_test, test_preds_1d)}')\n", - "\n", - "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, test_preds_1d, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental CN')\n", - "plt.ylabel('Predicted CN')\n", - "plt.legend(loc='upper left')\n", - "plt.show()" + "print(f\"Test MAE: {mean_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -513,7 +344,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/comparison/train_mon.ipynb b/examples/comparison/train_mon.ipynb index b6e9317..ead382f 100644 --- a/examples/comparison/train_mon.ipynb +++ b/examples/comparison/train_mon.ipynb @@ -16,12 +16,13 @@ "source": [ "from csv import DictReader\n", "\n", - "with open('schweidtmann_train.csv', 'r') as csv_file:\n", + "\n", + "with open(\"schweidtmann_train.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_train = [r for r in reader]\n", "csv_file.close()\n", "\n", - "with open('schweidtmann_test.csv', 'r') as csv_file:\n", + "with open(\"schweidtmann_test.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_test = [r for r in reader]\n", "csv_file.close()\n", @@ -39,26 +40,35 @@ "output_type": "stream", "text": [ "267 51\n", - "267 51\n" + "267 51\n", + "torch.Size([267, 1]) torch.Size([51, 1])\n" ] } ], "source": [ + "import torch\n", + "\n", + "\n", "smiles_train, mon_train = [], []\n", "smiles_test, mon_test = [], []\n", "\n", "for sample in rows_train:\n", - " if sample['Meas MON'] != 'n.a.':\n", - " smiles_train.append(sample[' SMILES'])\n", - " mon_train.append([float(sample['Meas MON'])])\n", + " if sample[\"Meas MON\"] != \"n.a.\":\n", + " smiles_train.append(sample[\" SMILES\"])\n", + " mon_train.append([float(sample[\"Meas MON\"])])\n", "\n", "for sample in rows_test:\n", - " if sample['Meas MON'] != 'n.a.':\n", - " smiles_test.append(sample[' SMILES'])\n", - " mon_test.append([float(sample['Meas MON'])])\n", + " if sample[\"Meas MON\"] != \"n.a.\":\n", + " smiles_test.append(sample[\" SMILES\"])\n", + " mon_test.append([float(sample[\"Meas MON\"])])\n", "\n", "print(len(smiles_train), len(smiles_test))\n", - "print(len(mon_train), len(mon_test))" + "print(len(mon_train), len(mon_test))\n", + "\n", + "mon_train = torch.tensor(mon_train)\n", + "mon_test = torch.tensor(mon_test)\n", + "\n", + "print(mon_train.shape, mon_test.shape)" ] }, { @@ -78,6 +88,7 @@ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", "encoding_train = encoder.encode_many(smiles_train)\n", @@ -97,68 +108,60 @@ "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "0: 224.59681181604049 | 766.2189126897092 | 766.2189126897092\n", - "10: 39.15787691837839 | 358.72500635781347 | 358.72500635781347\n", - "20: 29.04885175612089 | 335.8209191055274 | 322.95146102436325\n", - "30: 19.19503138395731 | 269.52828650731664 | 269.52828650731664\n", - "40: 14.92072356149052 | 224.99149585909703 | 182.35998093879178\n", - "50: 12.00302326902468 | 194.66217001147714 | 171.57997838831415\n", - "60: 7.950684393836318 | 137.94115436365647 | 137.94115436365647\n", - "70: 12.51347099618519 | 120.28866314157551 | 108.65490461049565\n", - "80: 7.268649354856112 | 135.56527282487528 | 108.65490461049565\n", - "90: 8.300059229247132 | 144.3595129070694 | 95.06214994648654\n", - "100: 6.093581981873244 | 139.55177547417435 | 95.06214994648654\n", - "110: 5.520961847198143 | 113.2207920102987 | 95.06214994648654\n", - "120: 5.992239627052336 | 170.44080482920012 | 95.06214994648654\n", - "130: 5.575740792778101 | 114.16756938945721 | 91.70782640444882\n", - "140: 4.199668284212605 | 107.46815484974022 | 91.70782640444882\n", - "150: 4.276100887341446 | 102.80365986683789 | 91.70782640444882\n", - "160: 3.747537827223874 | 97.39216097471802 | 91.70782640444882\n", - "170: 3.469509896267666 | 99.75181225745702 | 89.42283797078291\n", - "180: 3.073789060785529 | 96.9123635758445 | 89.11834227932873\n", - "190: 5.348160104358687 | 120.0032659880817 | 89.11834227932873\n", - "200: 3.8021064858311573 | 115.87040213743846 | 79.09756981632582\n", - "210: 3.1140825078728493 | 96.03113364247952 | 79.09756981632582\n", - "220: 4.3132176988580255 | 79.77955250032977 | 79.09756981632582\n", - "230: 2.8138961363374517 | 103.85834544502637 | 79.09756981632582\n", - "240: 2.660619128509407 | 140.87765141737228 | 74.37835983364094\n", - "250: 3.014489170317346 | 117.53964759427689 | 74.37835983364094\n", - "260: 3.7546145264129067 | 99.21299771893331 | 74.37835983364094\n", - "270: 4.590105906854408 | 104.3202048201187 | 72.79448339202459\n", - "280: 2.5713448720924865 | 95.4547427811879 | 72.79448339202459\n", - "290: 2.5572046215614574 | 112.15940677418428 | 70.45065679650538\n", - "300: 1.9452345594484708 | 82.3751139285262 | 70.45065679650538\n", - "310: 1.3750198503558555 | 76.82506424309138 | 62.3081466195484\n", - "320: 2.2536417643229165 | 86.66834024940708 | 62.3081466195484\n", - "330: 2.025292753726802 | 84.7968473717132 | 61.60909206380123\n", - "340: 3.2219164773319546 | 97.23135070590412 | 61.60909206380123\n", - "350: 1.9283467714259688 | 67.06629191728436 | 61.60909206380123\n", - "360: 1.0622809370805262 | 74.08065878340572 | 61.60909206380123\n", - "370: 2.0955286383182368 | 121.75953617575122 | 61.60909206380123\n", - "380: 1.2889858560169234 | 84.39403549923252 | 61.60909206380123\n", - "390: 1.032978725790531 | 77.40099936559358 | 61.60909206380123\n", - "400: 2.7169044794661277 | 83.8960645897314 | 61.60909206380123\n", - "410: 1.0023790298776234 | 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224.38432657813618 | 169.11234682115415\n", + "60: 15.539590985587473 | 190.66626507628197 | 131.64072967452162\n", + "70: 10.94290615467543 | 115.97657638817441 | 114.9835569198225\n", + "80: 6.634394199214178 | 105.77819733489214 | 95.55925345238225\n", + "90: 11.496060832162922 | 107.23135404756256 | 95.55925345238225\n", + "100: 8.238873342449745 | 144.63393050140024 | 91.62965282739377\n", + "110: 5.234100541818455 | 92.52809256777354 | 91.62965282739377\n", + "120: 5.197570315014557 | 127.55831572641709 | 91.62965282739377\n", + "130: 5.898747297708462 | 142.33383077178516 | 91.62965282739377\n", + "140: 7.4685130172900935 | 134.3836373493952 | 88.54714517156576\n", + "150: 4.472165254171421 | 119.8304005668809 | 88.54714517156576\n", + "160: 4.009020816074329 | 117.50288008615448 | 88.54714517156576\n", + "170: 4.270359067881152 | 123.37491404955439 | 83.78854940886445\n", + "180: 3.7407682826010027 | 111.04656289138046 | 83.78854940886445\n", + "190: 2.849839114071278 | 83.88666910133963 | 83.78854940886445\n", + "200: 2.7334534898679355 | 118.35908012163446 | 83.78854940886445\n", + "210: 2.9809222096361023 | 88.78775749720779 | 83.78854940886445\n", + "220: 3.0602198540048207 | 84.62986551480843 | 76.23915432689496\n", + "230: 2.996120470739929 | 95.1325462387473 | 76.23915432689496\n", + "240: 2.1503091769272022 | 86.006127648786 | 73.85262752477738\n", + "250: 3.0140369143825345 | 85.75780820786295 | 73.85262752477738\n", + "260: 2.1986263182279324 | 64.33059078889589 | 64.33059078889589\n", + "270: 2.1157755333832586 | 76.05989863562817 | 64.33059078889589\n", + "280: 3.119409807612387 | 133.24752121813157 | 64.33059078889589\n", + "290: 2.676918794153335 | 84.97541062547666 | 64.33059078889589\n", + "300: 1.686193701926242 | 71.79285341585694 | 64.33059078889589\n", + "310: 2.463944592279441 | 85.55279693109732 | 64.33059078889589\n", + "320: 1.3401851189716925 | 69.65509192333283 | 64.33059078889589\n", + "330: 2.301397212882167 | 82.96008262096667 | 64.33059078889589\n", + "340: 1.7067175768734364 | 70.42974979901577 | 64.33059078889589\n", + "350: 1.1365089523658325 | 66.2498350378409 | 63.138342034767895\n", + "360: 2.1879252315906994 | 104.87575191124252 | 63.138342034767895\n", + "370: 1.3824661376324485 | 72.16468048475537 | 63.138342034767895\n", + "380: 1.4715755726960715 | 84.10761197269255 | 63.138342034767895\n", + "390: 1.5232696176021734 | 101.45013265881468 | 63.138342034767895\n", + "400: 0.8281212638826406 | 66.29595406627392 | 63.138342034767895\n", + "410: 0.7805803027492337 | 72.79664503417763 | 61.285581310407494\n", + "420: 1.461513051379486 | 68.22901699467398 | 61.285581310407494\n", + "430: 1.211136550046085 | 67.27310054091846 | 61.285581310407494\n", + "440: 0.8773995910244488 | 72.24587960039179 | 61.285581310407494\n", + "450: 1.2593703930744071 | 71.67287416086994 | 61.285581310407494\n", + "460: 0.9602449199233609 | 72.46647213417671 | 61.285581310407494\n", + "470: 1.1952889010254364 | 69.64755897601272 | 61.285581310407494\n", + "480: 0.8316331374064814 | 68.66357342243268 | 61.285581310407494\n", + "490: 0.6837784574272927 | 68.13284766966221 | 61.285581310407494\n" ] }, { @@ -194,6 +197,7 @@ "from torch_geometric.loader import DataLoader\n", "from copy import deepcopy\n", "\n", + "\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", "\n", @@ -207,7 +211,7 @@ " n_messages=3,\n", " n_readout=3,\n", " readout_dim=64,\n", - " dropout=0.0\n", + " p_dropout=0.0\n", ")\n", "\n", "init_lr = 0.001\n", @@ -225,7 +229,7 @@ "for epoch in range(500):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -252,7 +256,7 @@ " _best_epoch = epoch\n", "\n", " if epoch % 10 == 0:\n", - " print(f'{epoch}: {train_loss} | {test_loss} | {_lowest_loss}')\n", + " print(f\"{epoch}: {train_loss} | {test_loss} | {_lowest_loss}\")\n", "\n", "model.load_state_dict(_best_weights)\n", "\n", @@ -275,7 +279,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -287,16 +291,17 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", - "ax2.axvline(x=_best_epoch, color='black', linestyle='--')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", + "ax2.axvline(x=_best_epoch, color=\"black\", linestyle=\"--\")\n", "plt.show()" ] }, @@ -307,7 +312,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -323,12 +328,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental MON')\n", - "plt.ylabel('Predicted MON')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental MON\")\n", + "plt.ylabel(\"Predicted MON\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -341,27 +346,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.258297920227051\n", - "Test R2: 0.8412778408709513\n" + "Test MAE: 5.560410368676279\n", + "Test R2: 0.8421112959748325\n" ] } ], "source": [ "from sklearn.metrics import mean_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {mean_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {mean_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -380,7 +379,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/comparison/train_ron.ipynb b/examples/comparison/train_ron.ipynb index 5ad2d3e..f415e21 100644 --- a/examples/comparison/train_ron.ipynb +++ b/examples/comparison/train_ron.ipynb @@ -16,12 +16,13 @@ "source": [ "from csv import DictReader\n", "\n", - "with open('schweidtmann_train.csv', 'r') as csv_file:\n", + "\n", + "with open(\"schweidtmann_train.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_train = [r for r in reader]\n", "csv_file.close()\n", "\n", - "with open('schweidtmann_test.csv', 'r') as csv_file:\n", + "with open(\"schweidtmann_test.csv\", \"r\") as csv_file:\n", " reader = DictReader(csv_file)\n", " rows_test = [r for r in reader]\n", "csv_file.close()\n", @@ -39,26 +40,35 @@ "output_type": "stream", "text": [ "284 51\n", - "284 51\n" + "284 51\n", + "torch.Size([284, 1]) torch.Size([51, 1])\n" ] } ], "source": [ + "import torch\n", + "\n", + "\n", "smiles_train, ron_train = [], []\n", "smiles_test, ron_test = [], []\n", "\n", "for sample in rows_train:\n", - " if sample['Meas RON'] != 'n.a.':\n", - " smiles_train.append(sample[' SMILES'])\n", - " ron_train.append([float(sample['Meas RON'])])\n", + " if sample[\"Meas RON\"] != \"n.a.\":\n", + " smiles_train.append(sample[\" SMILES\"])\n", + " ron_train.append([float(sample[\"Meas RON\"])])\n", "\n", "for sample in rows_test:\n", - " if sample['Meas RON'] != 'n.a.':\n", - " smiles_test.append(sample[' SMILES'])\n", - " ron_test.append([float(sample['Meas RON'])])\n", + " if sample[\"Meas RON\"] != \"n.a.\":\n", + " smiles_test.append(sample[\" SMILES\"])\n", + " ron_test.append([float(sample[\"Meas RON\"])])\n", "\n", "print(len(smiles_train), len(smiles_test))\n", - "print(len(ron_train), len(ron_test))" + "print(len(ron_train), len(ron_test))\n", + "\n", + "ron_train = torch.tensor(ron_train)\n", + "ron_test = torch.tensor(ron_test)\n", + "\n", + "print(ron_train.shape, ron_test.shape)" ] }, { @@ -78,6 +88,7 @@ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", "encoding_train = encoder.encode_many(smiles_train)\n", @@ -97,68 +108,60 @@ "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "0: 270.4911651611328 | 1429.946828272705 | 1429.946828272705\n", - "10: 88.07537669866858 | 664.2493297410946 | 450.2728079931409\n", - "20: 25.275780959868094 | 726.077336362764 | 322.974974718164\n", - "30: 24.39661651933697 | 259.13441748807537 | 258.8361125042041\n", - "40: 17.131954354299626 | 246.22596918747706 | 223.07706070779915\n", - "50: 13.056305321169571 | 184.9880481321803 | 184.9880481321803\n", - "60: 8.89223309637795 | 155.54116689687703 | 155.54116689687703\n", - "70: 8.69895271516182 | 148.46103826924866 | 139.69060867652297\n", - "80: 8.147858579393844 | 161.76155886390046 | 128.82029606022087\n", - "90: 9.038049241186867 | 197.2254438163603 | 121.68539364271176\n", - "100: 6.275687352032729 | 128.49902243473952 | 114.52369965021225\n", - "110: 6.223301578575457 | 113.97076032836648 | 109.13165741895928\n", - "120: 6.954329222020968 | 157.03752182915295 | 109.13165741895928\n", - "130: 4.307053752348456 | 118.3777114512335 | 100.35754123176721\n", - "140: 4.6849873032368405 | 108.31195327141049 | 100.35754123176721\n", - "150: 7.555337905883789 | 157.59299099386908 | 91.42026430103635\n", - "160: 6.075061482442936 | 135.2933475114314 | 91.42026430103635\n", - "170: 5.2390640957254755 | 126.80002602788747 | 90.02386588681782\n", - "180: 3.6640821107676333 | 117.33389055261425 | 90.02386588681782\n", - "190: 3.422422207577128 | 131.10411371378336 | 90.02386588681782\n", - "200: 3.7219140496052487 | 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140.11145045782678 | 79.17805491723851\n", + "410: 2.071878836188518 | 101.03846956044436 | 79.17805491723851\n", + "420: 2.9834824212839908 | 176.45323159881667 | 79.17805491723851\n", + "430: 2.216132224445612 | 144.3813637646609 | 79.17805491723851\n", + "440: 2.0843883568132426 | 117.21643929435945 | 79.17805491723851\n", + "450: 1.437448373982604 | 104.60250125533226 | 79.17805491723851\n", + "460: 1.7780628439406274 | 98.36716948069778 | 79.17805491723851\n", + "470: 1.6435706111746775 | 97.1818781886889 | 79.17805491723851\n", + "480: 1.1497493965525023 | 108.13526677285485 | 79.17805491723851\n", + "490: 3.1167207301502495 | 152.92751588540918 | 79.17805491723851\n" ] }, { @@ -194,6 +197,7 @@ "from torch_geometric.loader import DataLoader\n", "from copy import deepcopy\n", "\n", + "\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", "\n", @@ -207,7 +211,7 @@ " n_messages=3,\n", " n_readout=3,\n", " readout_dim=64,\n", - " dropout=0.0\n", + " p_dropout=0.0\n", ")\n", "\n", "init_lr = 0.001\n", @@ -225,7 +229,7 @@ "for epoch in range(500):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -252,7 +256,7 @@ " _best_epoch = epoch\n", "\n", " if epoch % 10 == 0:\n", - " print(f'{epoch}: {train_loss} | {test_loss} | {_lowest_loss}')\n", + " print(f\"{epoch}: {train_loss} | {test_loss} | {_lowest_loss}\")\n", "\n", "model.load_state_dict(_best_weights)\n", "\n", @@ -275,7 +279,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -287,16 +291,17 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", - "ax2.axvline(x=_best_epoch, color='black', linestyle='--')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", + "ax2.axvline(x=_best_epoch, color=\"black\", linestyle=\"--\")\n", "plt.show()" ] }, @@ -307,7 +312,7 @@ "outputs": [ { "data": { - "image/png": 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", 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qSMWjg14Ph12vOci2crPbzapVsu5l5045tykaaKLN89xumVZ66y1Ys0bW3dTXy9M1NUk2s9nkW0hKkjDT2SnPYzbL7Waz7K6qr5fpqEShwUYppZSKh+JiuOAC+NvfYO/e7jmcwTro9eOwrXBiOHXZ7XZz8cXw4Yeyrmb//t7N83JyYN8++Ogjadq3YIFMVVVVSQ7z+WDpUjn76aOPJOSkpspzFRbKbFtDg3yLGzfCaaclzkYZDTZKKaXUkeqZRtrb5bbcXDj33CFd9Q+bWa6J4H62eyGMgengbicntrx5OGvKMK9fD8XFHHusmeOOk8qM1dq7eZ5hwObNElTcbgkqhiFDrquT19y6FfLy4IMPpIIUicjjbDZZSOxwSGWnomL0j00YjAYbpZRS6kgMlEaqquDpp2HatJiqNaEQPPywTB+53TIFZTJ1t8IpK4OXH62kpK4CU0EBjR5Tr91OSUkm8hz5FHjLaVlUiXVuEcXFEkz6LvtpbpbKTH4+ZLoiZDRXYg34ODEvnX82F9LcYqa2VrZzp6XJOp1IRKo+7e1jf2zCYDTYKKWUUsPVdytRND04nRjuefjfKcP36/UEriumsMg8YOGmvFxCzdNPS3ior5dlOdFpo+ghldXlPtoiHbQ5HLz9Tu/dTl4vlG53sL+9hr/+0EfbLFlfY7EcuuynvFxe54z8ck5+bR3OugoswQ7CVjvHu0pYl7mKDfVuamrk6+fOlQXHDkdiHJswGA02Siml1HANcGS29I4x4a/NJ2VLOc9WVZJ9QlG/R0ZFCz47d0rYmDwZwmGZEvJ65RTtnBwJFU2RdAJmO7s2+2lrc3aFHr9fXjMl7CdgstMcTid3klRlLBYpGu3f331w5nHHwZxQOR9/fy2WJg8VkQL8OHDgZ/r+Ur6YUYVzzmrOvt7Nyy/LGVMzZiT2WYhRGmyOYj/4wQ94+umnOeaYY9i9ezcffPABq1atoqmpiZdffpmysjKK4jjp+aMf/YgtW7YQiUR47rnnyMnJ0dO1lVITWz+N+Robu3vHZDgdZJlqyE3zsbF7bW9XuOk5/TRtmizoDYelKpKT091cLztbwktrViHe1BL4sBRX7jxMJhOGIQWjjnaDmVRTlraYcn8hU43uKazJk+V1/X6pruTnRfjninV01HjYbZ+HzW7CboFg2MlHHfOYUVvGmTnrOetTxcyYYWbt2rhs9hoVCTSUcSISkX7WmzfLxxE8F2TatGls2rSJP/zhD1x++eVkZmby+OOP8/zzz/O73/1uyM/X0NDAE0880e99f/rTn3j33Xf505/+xBNPPMHGjRtJS0uL6XkfeOCBIY9FKaWOCj274SFVjIqK7t4x6SY/4WQ7yVnpzJsnQeV3v5N1Ly++CDfdJNNPe/bAu+/K0zQ0yPNE19d4PN1rYkrmmQmctQpvUjbTvGXYOry0HAjRUe9lelsZVR3ZPBFYSV29mX37uqewKiokfHQdnFldyeSmCuosBRiYen1LBibqLPlMOVAOlZVjehbicGjFJp5G+Lj6vlatWjXg2Ufnnntu1wndsQgEAnzxi1/kc5/7XL/3/+c//+k67wlg/vz5XHLJJYd93h/84Ada1VFKjV99GvN5vSYaG6Xi4m81yGypprFwMV5XIR6PTC+99x68/WaE8O5KUkI+JpNO8qxCQhEzfr/0mqmulmAUXaxbXi5rXFauBHuKm3/PX83S2nXk7Ksg2VNDeqedLSmL+XfaSnYZbgJt0sfGapVL0f79Mq0VVbfNh9HWwaRCB95WCWKBgISf9HTISHMQaamhbpuPaTPlElZcnDjHJgxGg028xNBXIN7hJjs7e8D7UlJS6Ozs5I477sDn8/Gvf/2L73//+3zmM5+hpqaGBx98EJPJxNq1a3njjTf46KOPKCsr46mnnqK5uZlvfOMbvZ5v+fLlfOlLX2Lq1Kn86Ec/wm63c/HFF3fdv2/fPn7xi1/Q3NzM+++/z8MPP4zP5+PFF1/E6/Vy8803c8stt5CamhrX90AppcZUn8Z8nkA+DXUOUg0/U4LVbE3O5p+TVtKxzcz27XJZmNFRzukfrGN6WwV2OmiL2Kn0l1A6fRXWfDfV1fLUbW0QaI8wpaOSs6b5+OyqdKy2QkpLzbzR5OaPdcVktVZiC/vwmtPx2guxJZsJtclOpn374IUXJISEw/D44xJ03G7wkU4HdnJS/biynAQC0Z1VEsqsHX46Wuz4SO/1rSbKlu7BaLCJh0FWxXdNcB7sKzCa8fbOO+/k1FNP5ZRTTuH444/n85//PNXV1dx7771cdNFFLF26lFmzZgFw4YUX8sADD3DRRRfx5S9/+ZDn+uIXv8j777/Pz372M/7yl79wzz33cP7553fdf+211/Lb3/4Wp9PJ6tWrufLKK/n3v//N6aefzp49e7jjjjtG69tWSqnRdXCupuE366j7awX5flmhuydrMS9nrOTDFjfeV6VyssBSzrn715IV9lBvLaDB4sDU5qfYX8q0XVU8x2oCOW7a2uCzs8qZvXkdxzormFXTQdWNNjb7pvJ//pPxB4/lQHshdZ1FmM0SXEwHpIme3S5dgsNhCSvJyTBlipzovXat/J6dMreQ+qwSiptKacqdh93ee1Ww40A127IWM31uAq0KjpEGm3gYYFU80D3BWV4+6h2MHnvsMVJSUnj33XdpbW1l+fLl1NfXk5aWxle/+lV++ctfcuGFFxIKhWJ6vnvuuYfPfvazXHPNNVxwwQV87Wtf48EHH6S2tpZ33nmHhx9+GICkpCQyMjJG8DtTSqnEEil281B2MVXFlXRO8tLe4MM6KR2SU3BaI9TUmLGYIiw98AwFkb1UWwpJtkToMJsJ2p2Ud8xjfrCM46vWUze/mGktW/nYO2vJS/aQMbuAd8ramdL4IR9re5UTIs9QZl7Am8YynjFWscPsxmyWs53a2qQqEw01HR3yu3dqqhyV0Noqv2ffcIOZ/zt1FfV/q2JaYxktznyCVgfWoB9nSzXVkWyaV6yksCgB55oOQ4NNPCTQcfU9VVVVcemll5Kbm9vr9ptuuon6+npOPfVUzjnnHH7/+98f9rl27NjB7NmzOe200/jwww9Zs2YNP/3pTznrrLOYNm0aVqv1kOkrpZQal/o5yKmy0kz5VjPTU9uZH3geh7cCa1MHEaudXdYSHousYsr+Gj4b/Aup5g4KQ3sJh5NoSspmZ3IJdck5NJjzmd5WTmjHHlYE11E42YN98Tw+et1DUf0m7LRRHcol3fCSYXhYkvwe0yJVPGheTa3LTWenrM9paenuLmy1ylqY6NRUUpKcD1VdDR+/ws2T+1Yz56N1zPFWkGaqocOw837SYnYsWcnFl7tjnmQ47NlWo0iDTTwk0HH1PeXm5vL0009zzTXXAFBXV0coFCIcDvPLX/6Sr33ta1x44YXcfffd3HbbbYM+19NPP831119PcnIySUlJ3H333Tz77LPs2LGDE044ge3bt/Phhx9yzDHHALBx40aWLl064t+jUkqNqgE2iex0rsL7Fizcv5aMkIcaSwF+swNH2M+sllJuCnxIeqSZSZEGDhg5dBoWzETIDteS1tmMLWkenaSQEdlPQVsFJZYKDjgKqHsXChsrSDO30WTJIRgx4Q2Dw2hls2kak821nB1czyOmYqwOM4FAd9UmKUka9GVlSdDJyZHGf7t2yULiY4+Fi7/vZt3TxbzzXiUmvw/DkU7O8YVcfL455mWho7xv5rA02MTDWBxX30c4HD5kSumSSy7hpptuIhKJsGDBAp588kl++ctf8t3vfpc1a9awaNEivvGNb9DQ0ACA1WqlqamJrVu3Ulxc3Ou5mpqauOOOO/je974HgM/nw+/3c8YZZ1BYWMiJJ57IypUrueuuu0hKSmLz5s0sXbq06zk9Hg9ms5msrKwRew+UUmpEDbBJpOWVUoydlZxbbyfL4qE6Yx6RiAlzADpMTpomuVlc+QzWSCsWwuQZNQCEMRMkiexIPVOCNbSSjoUwlyY9SZGjgTerp5PU7mVSxEO7zYX54LWlEytJhg9LOEhDcj4lgXKyWiupNBd1HX3Q0SEVE5NJfqfOzpa/p6RIqIlOILjdUPwdM5WVRcOqtozBvpnD0mATD3E+rn6o3n33XZ588kkaGhp46KGHuPjii3E6nXzve9+jsbGR73//+8yaNYtHH30Us9lMbW0tH//4x7nkkkuora3lBz/4AQD/9V//xZo1a3C5XIcEG4BbbrmF559/nmOOOYba2lrWrl3LokWLAPjjH//IZZddxmWXXcYZZ5zRtd7mM5/5DPfddx+33HILv/zlL0fk+1dKqRE3wCYRI93JB53zyGzdRKFRxxumFWAykZQkX+L1QlJrC9bONjLwEsGMCYNW0rASYBL7MWHQRgRIY58plylGPZN9u8g1T6HFlIo5EqKDZEwm6SJsCgcJmZJoj9joNDmYYqnBZfbh88nv0iCXG6tVtnDv3i23TZrUvWqi5wTCcHc7Jei+GUyGEX0bxr+WlhZcLhderxdnnymjjo4Odu/ezYwZMwbsDXNY/dXj3O4hHVev4i8u/22VUhPbnj1wyy3yi2qP60dzM7z8MhQEdzKj+lX+ZT+X/UzCbJbfbUMhmBTax3nhp7EToJICMmnCShArQZLoxISBCYM9pll8kPkJ9jOJM1qfIRwx8U7aJ1jU8goBSyqG1YZhGKS1N1Jn5PKG+WQyk1qYbNnP9yK3sSNUhM0mC4ctFgk50UXFKSlycKXVKkcj3Hffke9lGeAt6eL1Sv+c22478tca7Prdl1Zs4ulo6mCklFIqdgNsEon2f+l0uKTykdVMIDiJxkbZcp2UBCmRILZwkBBJBJPTqQulMtnYRxqtXV1/DUxUppTQkZ5DchDebV3M8aG3mOzdjtdIIytygJZOJy6zj3ZzKluNEiIRyAtXU2FfzJ72QlJS5LITDVWGIWMwm6XJX2qqrLNZvjw+KyMSdN+MBpu4O1o6GCmllIrdAJtEbDYJL8FwEu0pWWRF9jM5ZyY+nwmHQ6ZnTP5k6DQIY6G100YEEwZTcOAngA0bHYRIpiY0mY42CSEtpkKyTA1sYw6F7CXXtI9cYx815LOFhXSarCyylxHOzOadjJWY95jJypIzoUACRWenDNkwZJu3zQYzZ8ZvZUSC7pvRYKOUUkod1gCbRFwuyM6KkFq+jWrXAoxIhKx9W2iIFGCkODD5/RSZq2gmi3ZsTKKRFpxEMBPGjJUAnVhpJoMAdrxeeeosi59G02TW8g0sVjPLUz5gcftr5LKPqZYDdBh2OG4xx/9gJd46N5u+J7uf0lIjTAlUMivTR7U3nR3BQgJBMyYTHHNMfBfzJsC+mX5psFFKKaUOZ4BNIqaqKo7Z9S7NzUF2N0cIWWzYjHZyQruIdNggxc6O3JN4p3UuJZEy0vCRfXDBcJgkDMK0kkY1+Xg6XUQMMJsMJlHNO8ZiGtKKSHOa+UeoiL9xDtPClRwzw8fkWensdxSycK6Zz58Gf/gDBD8o53NN6yhqr8Aa6SBgtrPTWsKfwqswH+Pm/vtljc0IvyVjfvK3Bps+JtBa6glD/5sqpeIiesx1dJNIeTmBil14m618kPoxasyF2MJ+coOV+LDxV/PFZH7sWN6sKWQaf2cZbzCVfUQw00kSHibhogWAGvKxECYNP4VU4zFl8zfTSpJtZvLyZDFwMGjG5ysi7WOQmg3V22T9SlISfGdVOfveWUtai4eGtALCdgeWDj/T95dyTUoVUy9ZjdXaf6nmSJrr9X1LauQ0CRYvHrt9MxpsDkpOTgagra2NlJSUMR6Niqe2tjag+7+xUkoNW3STyJ49eL53H9uazbzafgKGSZKAxeIkkDafhZYyFrSVcc+b51DQtpWzI8/TTCadJOPEh50O0mnlAJl8wHGAgTtpG60hO5uTF/N/KSupNbsxGbKdOjqdEz0Lqtf6lUiEFU3rqHV7eLF2HvsPmAi3y1jInccnc8vIa14PkUP3XcejuV6i7ZvRYHOQxWIhIyOjq1ldamoqpr7nPqmjimEYtLW10dDQQEZGBhaLZayHpJRKYNHKRbSBXXq6rKE55CJtNrNjl5m9rzRR5i8Bixnrwd+bQiHwtpjYZs9nbqicKZ17+EznOrLx8BbLMQEuvFgJEMTKNGqooJg/cwnZZj9tKek0phQyfYYZl0fG0tYmocPnky3bTqcEkq71KwfPK7TNLmC61YTJLLu1bDYoLDRhK+j/vMJ4NtdLpH0zGmx6mDp1KkBXuFHjQ0ZGRtd/W6WU6k+0cvH223LkgN8vF/qZM2HZst4VjEgE/r3eR0FzB20mBzZb98JZs1l2IzX6HWSZazghcxsLmyuoChcAJgygmQwATEAEMyVsxcBM/eSFHHss2Gu7dxq1t8uOpro62aodPVO51/oVn4+Whg7eanDg75CdUcnJMo76evB7HZw8uQZnj33XidpcLx402PRgMpnIzc1l8uTJdHZ2jvVwVBwkJydrpUYpNaho5WLXLgkQoRBkZEio2L1bqiU9KxiVlfDe9nRyTHbSLX46DGdXMDCZJAgkh/20GXZCYXBYOvAjzV6i8wDGwT9+HEyjhnR8ZM2AWbOkerJ1q4QOux06AxHmWiuZbfeR6kun5PhCVh48yykSgeqmdPbttRPo8JNT2D0Wm03CUGutn72GnfmOdKIZ5WCRh4KC3ruZot9Dfv9FnqOCBpt+WCwWvRgqpdR4dnDeKeL18dLj6XgaCunsNBMKScUjesZStNFeY2N3BcPng71GIXvtJcz1l7Klcx7JVhMmk3T9DQYMphvVvBtezNsH5vJpkx0Hflpw0nMrgwlIx08Hdnyk490tnYyzs+V1FiyA1k3lXFiwjpOyK4j4O0jCTiolmFlFebmbdevg3U2FLK0r4dhIKZXGPLJzTF1N80wYFFBNOYtJp5Cig6+dqM314kGDjVJKqQklsqUc7yOyYjbU2sExe+1MzSrh975VtGe5e1VfnE45FmDGjO4KRno6pKaZ+bdzFdMiVbj9ZVQH8mk3O0gO+ikMV9NINs+ykkpzEeVGCcdQyhbm0V2zATDIp5p3WUytpZA8s+x+qqmRILU0vZwveddyXL4H54wei2DeL+XA5iqeZDUfhd040s28lnUex7aUMbvxTRp9BXQUTcWV3IazpZpWZzZv5qzE7e+eU0rU5nrxoMFGKaXUhLHzuXKab1tLqN5Do62AVsNBwOtnbmcpn/NX8Xz6aqps3StmrVapWlgs8tHng/nzZeHun7e5eYzVnGVfR663AqO9hraInXdZzLOsZLvFjd0GzwZWkUcV8ymjinz8OHDgp4BqGsjmOctKUtPMZGR0n/PU0hzhxPZ1HDvDg3N570Uwhnse9c+UMdu0HmNVMbY9W0lte5aUsI+p1FHQsoNQhYNA/kxq8pezKX8l+w13r5CSqM314kGDjVJKqQmhfEuErT9cx5RaDy3580i1mgj7oK7Bybtt85jdWcbHGtZT7Sju2r4dDEqfmHC4u4JhNsMFqyLUv13JjvdDPJ30OVLyoX6XnyYjnb1GIUlWMxZkumdz2M1aVrOSdZRQwTRqCNAdgLZG3KR0ypTX8cdLYSbNU8mcd/tfBONtMbE3nM9cUzmh3S8xr/xp2iIedptmsSdrIRkddeS0V2E1pVE+91ze87gPCSmJ2lwvHjTYKKWUGvciEXjpkUrm76vAyC/AZpew4HRCZiZ4PCYqyWdqUzk5UytpSC3CMKClBaZOlW3Xxx9/MByUl+N+dh0/NFew295B9X47H3pK+GNoFTXJRZjC8pqhkLwuQAVu7qSYQipJx4fflE4lhRgmM2aTVGlqayU4nXkmZId9WDo76LA4cPX5XgIBWXScTzVzt/2V1DYPDYXzCNaa6OyAoLWAqkg+S9rKyHrtr+Sc5GblSvMhISURm+vFgwYbpZRSR52hdsutrISaCh8n2TrwWrtXzLa1SQAJhWB/p4NsUw37tvtonCpTMlarbJ3OyTlYwdja3fwlY1YBxy10UFTrp/C1UqbuqeJXSavZjBvDkEJLUpI8t8kEhmFm78Hlu2bTwfstMu60NKnu7NkjC4gtoXQiyXbsYT/QexGMzQYO/ISDYVwt1XgzinDYTEybJjupfD7oDJmot+ZzTFI5yy6sZLa7qN/3JdGa68WDBhullFJHleF0y/X5wBtJx7DbsXb6Cdic+P3dp2A7nWD2+Qmb7DSF0qmpkUrNjBmwfPnBCkZxhMjt62jb68FfOA9r2MSBvbBtmxNPaB4ZoTI+FVrPZksx4YiZpB5X2P5OdomGB7NZ/qSkyFSQxwN1gUI+PqeEdG8p5PdeBONyGky3VLMrVMB0agkmS1BzOKQzcW2tHIi5/AQHGQ01mKYMvrUpkZrrxYMGG6WUUkeN4XbLTU+H1qxCaptLKGoqpSF7Hh6Pic5OCQPhkEGhtZqW2Ys56fhCJm2T07C/8Q256JvNsOPFStr/UkF1RwH7t5lobpaKj1RmTFhM+bgj5eRHKtkVKSIUkq+Tak33WJKSuj+PPsYw5E+0ErVggZmCL6/C/Pyhi2BM1dVMWZDN/7Weg2PzYxg+P0a6k2BQdnBZrVKFyUj2Y0o5Src2HYGjuNiklFJqvIlEZDpm82b5GF2jEr2vZ7dcp1PWpkS75Xo80mum59dE5efD5KlmnjFW0WTJJqO2DJPPS4o1hCPkJd9XRkdaNnXLVjIl18ysWdKcr7ZWvr68HP70oA9fYweBJAd+vwSqYFAqPh0d4Is4sNFBmiEVkmhQ6RlqeoYY08G1NdEuwS0t8vny5RLQZn324CKYRYsksWzbJh8XLybr+6s5887TMIpLSD1QRW2NwZ49UpkKBOCD9w0qXqymfpL76NzadAS0YqOUUiohHG6KabjdcqPPu20bfFTvZk/7as4z1pEfqMAZqcEftrMjfTEHPr6SepObitegoUHWutx5pxyp4PFAsDWd1Cw7nU1+AgFn1+tGt2inW/wEI3b85nRMEbkvNVWqMlarfOw8uPsJuqs1waAUVTIz4VOfgttvp3saa5BFMG6g+OerqLmpisgHZeyz55M62UGayU9aUzWV4WyerFvJxVvNR+1C4OEY82Dz4osv8j//8z888cQTFB38l+j3+7nhhhtwuVz4/X7uvvtubDYbAPX19Xzve98jIyOD5ORkfvSjH+lhlUopdZSLZYopFBp6t9yezztrFuTlwYcfurlrdzHOcCXTM3xkFqSTdZzsUHr7bZlestslaOTkwIsvSvVmyfGFVKWV4Npbisc2D19Irj0WCxgR6fD7rnkx+6yFpB48M8rhkApKdA2Nz9ddxTEMCUWhkIxv2TL49rfptTYHGHwRjNvN32evJn3POuaZK0jy1xBKstNYsJhtxSv5qNGNdf3ReebTcI1psGlsbKS1tZWNGzf2uv2qq65i1apVrFq1iscee4w1a9Zwzz33AHDRRRdx3333sWjRIm677Tbuv/9+Vq9ePRbDV0opFQexHsj4X/81tG65/T2v0wmnnw5NTWb+/vcidprhvz4pF/3XXpNQk5YmX5OSIlNiHo9UcP7zuhnz5FWcZ1RR1FZGICTdhtMtfvKMapqt2fzDtJJQCOba95Bi8eFITWdjSyGWZDMmk+xosljkHKpwuPd7sG9f/9Nog6mshNcPuMk5o5gGoxJrwEfQlo7XJUEt33b0nvk0XCbD6G+t9uiJRCJYLBZ2795NUVERtbW1zJo1i6amJux2O42NjUyfPp36+nq2bNnCxRdfTGVlJQCbNm3i/PPPp7KyMqaqTUtLCy6XC6/Xi7O//yuUUkqNuj174JZbpClcfz+avV5ZWvKDH8Cf/zxwt9yyMunBctNNElQO97y7d8Obb8Ls2ZCbC6++KidpR9epRCLyPFarhJDkZPmT5y3n3Mg6iqnATgcB7GyzuHltkoSaT/rWURypIIV2Jk8KU2vJ59+p57LBfBrNLWa8Xhm7ySTVmujzhkJw8cXwv/8be3Vl82b44Q+lItPfEYehkEzBfe97sHBhbM+ZiIZy/R7zqShzn/96GzZsIDs7G7vdDkBOTg42m42NGzfy9ttvM3369K7Hzp07l+rqanbt2sWsWbMOee5AIEAgEOj6vKWlZYS+C6WUUsMV64GMfv/QuuUO9LyGIWHJZpNAM3u2BITaWrmvs1MCAUi4if49ejlpwk15j2Z7LaRTGS7khLatXBFYSzYeQqmpTDd7KEmpZ0n7Rk6q/yeLwp/mV+Er8JrdWCwSlqxWqTAlJcGBA/D66xLIZs6M7b0bz2c+DVfCzbjV1NSQlZXV67a0tDRqa2sPuS8tLQ2A2uiy9T5uv/12XC5X15+CgoKRG7hSSqlh6Xlx7k/Pi7N74I1CrF4tlYvorqpoeOn5vI2NMuX08suwYYOEpORkCUUpKd1rXgZjMkEEM3tNRWxmYVfTvU+2riMj5KEpOYd5kS0UWOtJmerCOncGLqfBqaEXuarzPooj5UQi3aHGapUAZbNJGNu2Lfb3LnrmU1XVob1yomc+uSfYxqgxr9j0ZTKZuqo1UcFgkOTk5EPuCwaDACQnJ/f7XGvWrOH666/v+rylpUXDjVJKJZihHsg40EahrVvhjju6d1XZbFBfL+tjli+XtTLRxcFOp1RgMjPltupqCTQHLyuDigaI6EeTCaYblbipwGPPZ17oA1IML8lTnZgwwGwmtWASqf42prdUcmHSen6TUYw5ydzV4yYQkGDV33TSYMbzmU/DlXDBJi8vD6/X2+u21tZW8vLyyMvLY8eOHV23+w4ufc/Ly+v3uWw2W9duKqWUUolpOBfnvhuFBtpV1dAgz/Hmm3T1nnE6pXLT0SGhorkZ6uq6t2EfjsnUvfams1MqPpPCPlKCHTiMBuYZZZiNEMl1zRg+M6bUVEyTJpHlCuNtn8TMQDl5oUr2JUkTv0BAnsNikY7Bc+cO7f0br2c+DVfCBZtPfOITXH755QSDQaxWa9c009KlS7HZbPz2t7/teuyOHTuYOXMmhROpxqaUUuPQkVyco7ufGhth2jTZcRSJgMsllZq33pLb6upkLUtzc3efnKwsqdRUV/d/7MFAopWWpCTIyIBIRzop4QCLLO/jiLTRnpxOG0nYTGGSWluhrQ1HRgaZRS78uxswtfpoDUmYsdsl2ACsWDG83Uvj8cyn4RrzYBPdlBX9mJuby1lnncUrr7zCGWecwQsvvMDVV1+N3W5n2bJlZGZmsn37dubMmcMLL7zQa6pJKaXU0Wu4F+fKSplO8nhg+3YJKklJUukpKZHpre3bYfp0mDJFglM4LD1tzGYJQUOZAor2oIk22APYFczHmdxOOi2EkuyYzCaMsImIOQlsFmhqwpSWxvEnWviow05yJB17RMaZkiIfFyyAyy8ffhgZb2c+DdeYBpvW1lZ+//vfA/Doo49yzTXXkJ2dza9//Wtuvvlm3n77bQ4cOMAdd9zR9TVPPPEEP/nJT7qqNFdfffWYjF0ppdTQHe5U7uFcnD/4AD76SKaGMjK6jyioq5MFxCecIMcV1NRIqGlp6d7CnZ0tIcVi6Q45sejZg6a+HualVpOalYK/M4d0fz1JnW2EzGmYIxFo615AY927nZb8U2htLQSPjDMtTXrrXHHFxJs2Gglj3sdmNGkfG6WUGjvDOZU7aqBAFIlI35onn5St2z33nhiGrLEJBuVjINC948lslgCUkiIhZ//+7uMNhiLaj2ZpymZ+nvVDLDlZTN33Pq7G7VhNndjSrZjS0sDpJFjfxIdpJ/L47B9gmucmFJLg5fHI93PddRpsBnJU9bFRSik1/g33VO7o1w4UiFJSpGNvfj40NclOqOj6l+ZmCTQHDsjzJCUd3KodkT/BoISdJHOE2cmVuMw+fEnplLcVYgzSDUVO85ZFyJ2d8nlTRzq1B+xkTkrlLdeZ5KfO5biUrZg6W8BsxujsZL85m79P+xqu5e6unV+TJsGMGd3dlSfS0QcjRYONUkqpERXrkQn9XdQPF4jOOkvCyYIF8MYbcpvNJpWQAwcOrcD03KptGFBCOedH1rEwUkFSoIN2w06FqYRnjFVUcGjSilZ6DEPGEZ2S2hUp5L3OEk6rLGXqsfOY7Z5JSvYMjKZmWvd6CO6o5E3HMryLVpA+hAM81dBpsFFKKTWihnsqdyyB6PXXZcfTzp0yTdXUJH1qIpFDXysc7r4tGmpWs5Zsw0NtqAC/yUGK4ec4o5R8qljLaraa3F3HHfSs9JjNvY9bwGLm2c5VnGCtYoWlDH9jPh+UtpO6azMZvmo6I0mksZ2Sv91F3bJVRIp7h6b+DvBUw6PBRiml1IiK9ciEvhf1WALRpk0SipqbwZoUIbezEgc+vKRTaymkE/Mhh00CmIiwknVk42EL8zBFTJjN4Lc4KQvPYx5lnMd67jKKSUoydx1cCd1VH6tVxmGxSNVoe5Kbh9NWs+O9dSzwv82cwEckEWK3NZ/GKQtp8KWS31BK5otVlLG6V7iZiEcfjBQNNkoppUbUcM8zOlwgamuD996Tx8wKlnNeYB0lVJBCB+3Y2Ros4VnTKsoOTin17RRcQgVVFID0B+6xI8pEFfm4KaeQSmqCRf1uBzeM7sAVPTDzlQY3LwXmcId5DdakdnYkudkfzsDiMZGeDjvN85gdKCN343pq5sjcW3/dldXw6RIlpZRSI2q45xkNdoaUYcC//y3hZ2awnGtZy2JK2U82WylmP9ksopTVprW4KT/ka9PwkUIHflLJoJkp1JNBM2BgAH4c2Okgw+zDYoHU1O4metHniB6Q2dHR3QcnFIKZ1mqyw/XssC2gzZaJPcVEOCwVn2SriVpzPjmeciJ7KvF6ZUptIh59MFK0YqOUUmpEDfc8o8HOkNqxA/buBYwI55vWMRkPZcwjbMiDWnCyhXnMj5RxLuupoLjXTicf6VgJsIKXSaeVZEJ0ksR+simnhCBWAtjxkd51hILZTNep3IbRvdbGkRKhJLWSjkYfYVs6TrzYjQ7qzVJqMpkkFAWD0hk5YHWQ1FhD/Q4f7Uzcow9GigYbpZRSI244RyYMFIhaW2XRcDgM05EppWqTTCmZgUhXVUimlOYdnFKKnsINkIqfqdQxjVqqyceLFSudTKUOJ172M4kNrKCSQghJCOvs7D5GISVFxlNilHNm+zomNVRAuINQu50m2xRspgApET9tZpl7s1jk681mKMzyYxh2Lr0inemnTtyjD0aKBhullFJxcbiuwsM5MqG/QBQ6eMaSzQauoA97pINWHJgOPo/JgGi2aSOVSWxjMe8CSFABzuNZmsnEQhgnLbTgJIiVFtLJp4YwFv7KuYQiZglLB49d6NmleFpLOZd0rCU96KEmuYD6gAOXyc9sdpNj7MMW6OAD83JMZlPXjqzkJANbYzWB+Ys55fOFmPUqHHf6liqllDpisXYVHs6RCX0DUU0N3Hef9Krxh9LpiNhJNfy0Gr1XJmfTyHG8Tx51XG5+mEbjWcqMEjaylBIqKGMek9hPMVtx4cXARIhk9jKdJlM27Ub3VJLJJEcfTJ4sFZt9tRE+vn8dqSYPuxzzSHWYsAShqdPJB6H5HG/4cEaamdm+hXprAU1BB5PsfiZ7qvGnZmM6ZyWV1Wat1owADTZKKTVWDlfiOEocSVfhWPUMROnpsi4nPx+2tRayNVLCIqOULZHuhTjZNPIx3mKKqZ5qcxEfJS3CYWrj+I7Sg2GnlnyqmMQBkunEhKy72UYx1aYCSizbmZbqY8bxspMrFJKGf/v3S6fjyR2VzOqsoCmrgClTTAQCMiaPB8IRE9ss8yhkFzuNGUzuqCfbVIPNZqcidTHvFqyk8VU39o2xHymhYqfBRimlxsKRHJyUQI6kq3Asz91f7isslLeooQF8PjN/q1pFQbiK+ZRRTT6tpLKI98m11FPPVD6yHIvFlkRbxEkZ8ziVlymhggNkcoBsvCRjpRMnXtyUYQBBi52gLZ1kQ9bTbN8uzf9aW2U6Ksfuwx7ooC7k4ECN3DZ7NrhcUlFqbXMQMGw8kfQFkrNdXHy2j12N6dRYCimYbqZ4BMKfEhpslFJqtI1GiWOUDLer8OEcLvdFFxUbBlTb3Py2ajVntq1jrlFBiWUbheY6Gu1FlIaOZb+Rg7XHmMxGiCRCmDAIYMWEiQA2GskhhwZOML/Hh8WX0hoopKlaxpJ08GoZDst/ro5AOp1JdmwhP80RJ1Zr92GWkyZB0OPH3mrnhAUumjOKqMqAmub4hz91KH0LlVJqNPUtcTidsho1epXzeOQq190tLqHF0lW4o2NoRwVEc19pqUzvFBfLx9JSub28XMLNZz4jj29pgTLDzU+TbubutNt4eeZltOS52ZK9gv2mHMxm2ZEUDoPT8OLERzMZBLGRQyN2OjARwUaAZEKkWIJ0LFyKM8PM/v0yBeXxQGOjPE9nJ+wKFbI3pYRCUxWdQYPkZGkYGAhIu798o5rO2W6yjiukuTn28KeOnFZslFJqNI1UiWOMDLercE89p5wcDnjmme7cB7JIOBCAvDyZ5onmvuefl/vT0uR4g5QUM52RIt434JPBZ0mxtWGzOens7D7ryW4KYDcC+HBSynFMo4YcPKThI0wSdeZ8TEk2tnmn0NoqXxc9MBO6TwRPTzezadoqZjVU4W4royWUj9/kIKnNT05LNW2p2VSUrKS1zYzZLK891CMl1PBosFFKqdE03IOTEtRgTfRiOSqgvByeflqORoh2GK6vh2OPlXBTUSEfQyGZDkpLgzfflCpKY6PcbjZ350TDgKqGQrZbSpi5v5RgWAaVkiLhJ6nVis0fwMNkKk0zqDLNYFKSl+RIgJDFRlIy5JgPUFaVTiQi2XLnzu5TwqNbvW02aJjk5knzao5tW0dxRwVTkmpwdtqpy1tMRclKGrPdVJdJdamu7sjCn4qdBhullBpN8ShxJJDhdhUGCTW33goffdQ989bRIUGmtVXehkhEFuQmJ8sU0P798lo+H8ycKYt6Xa7egSqCmd81reJaowo3Zey35eMNOTD7/GQFaqhnKq045HRum4nmUAahCFgtBovMZXxkXcy2jkJcmRKGsrLkkM2UFAlSKSkylo4O2BxyUzm/mH/UVpJt87HoY+l05hbS2mam+uBRCV/6Ejz77PDDnxoaDTZKKTWajrTEkYCG01U4EoHf/EZO57bZusOLz9cdXqILhqOnaEcf5/VCba3sQoqunWltlapKS4tUcgIBN790rObTwXUs7KzAFajB12lno3E8H/FlzrE8zwJzGbXhfNrMDhwmP9Mj1ew3Z/N27ko6280EgzJOq1UyqM0mga2jQ16zsVEqSM4MM5kzipg6FXYcgI7th37/ZvPwwp8aOg02Sik1mo6kxJHAhtpVeM8eeOUVmdrJyenOd9HDJKOLdHfu7O5bk5oqz52XJ1NR1dW9p6Q6OuRrIxEJSVvNbkpDxcw2V5KV4qPeSGdPpJCwYabSPIv/sq1jQVIFKaYa/FY773Us5l+spN7vprFRntcwJLwce6ysramuluAVCkngmTEDli+X/2SDff/DCX9qeEyG0fes1fGrpaUFl8uF1+vF2V8JWCmlRkt/+5nd7rG/yo1S08B//hOuuAKmTpWpHZBsV1Mj1Re/X0KFyyVhx2KRgJGZCXPmwBtvSNAIh7sXBgeD8jWdnRKCwuFDN5dZrXI/gDUpwvE5lThNPprD6XzQVEgoYiYclq8FeT2HQz4uXSqBqaxMpsGuvFJuH8pbNE56Mo66oVy/tWKjlFJjYTgHJ420EW4a2POiXl/f+z7DkLU1nZ3yVgQCElhAqjkdHRJKLBaZxTtwoHuaCOR+i0VuM4yD265NsuA4HJa31TDkfrNZXqO93Yw3s4ic2VD3PhgmWU8zebJMd+3bJ887ebIErQ8+gNxcmQIbbquh4RwpoYZGg41SSo2VRLrKxbFpYH9Via1be2emzk6psOzbJ29BICB9YGw2CSgmU/c0lc0G7f4I9oZKnJ0+MNLxJBeSkWWmpQXa2yW0RLdmQ/duqei0FEjICQYlr0UrNz6fjNXrldtzc+WjwyHVor17pcNxerrsbDrpJPjKV3TqKJFpsFFKqYkujuci9Ff0ycqSUODzyVqZKVMktHz0kVRuotNM4bCED69XnstsljUtxZFyPheUrsIp/g4CJjvbLCX8m1WEnO6u5nhRZrNMZ/WcUrJY5LmTkuT+YFA+trXJuJzO3hUgkHAzc6aM57jjZGHy5z+voSbRabBRSqmJLk5NA/sr+rS2wnPPyW2TJ0sFJClJAs4JJ8Brr0lhyGTqbn4XCMhjsrJgyoFyLu9cS5bhoYoC2k0OnBY/x4ZLKfJX8ZvQanYkuwkEJKhMmtQdZoLB7oBjMsl6mPR0eb0DB7orOS4XHH+8BK3OTqkQRVmt8rxJSfLcLld833oVf7pkSSmlJjqfD6O9g+ZOB/X10rOl17aSGM5FGOikiOiRBJ2dUh3JypKFvXV10oNm8WKZ/pk6VQKE3y/TSKEQNNZH+ExwHVMsHsqYhw8n5mQLAZscZukMevhU23paWyIEAvJ6fr+8Tnq6ZDCbTZ7XapVvIzlZqkiFhTB3rhzLcMIJErqys6U60/N7Dwa7vw+3+6jahT9hacVGKaUmuB316bTtsLOn1I/XkAMdc3PlQp6TQ0xNA/sr+hiGrK3p7JSgEwzK3+12ed7GRpnemTy5u0oT7exrNsPUjkpmU8HucAFgwmLpsdPJZKLayKfYKGe6uZLtkaKuxcHRRcPRJUxVVbIOZ88eCTgulxShjjkGrrmmu3lecbEEm8ZGGW9ysgQam00CzVG4C39C0mCjlFITWHk53Pa/hSyrLaGkvZQW6zwMTOzfL4tmT/24QU7j4ZsG9ndShNcrwSXaYC8S6b3TyemUxcMg9zmd3fe3t0MaPux00IoDAwiFITpRZjJBKw6mGTU4Ij5MJgk92dmywDctTaahyg52//X5uqeRolvEP/MZmD+/u3leY6N8Xlkp4/L5pLp0xhlw+eW6tuZoocFGKaUmqGj337c3mWlxrKKQKuaFy9iXlE9TpwNvlZ+af1Uz6ZPZmA9TrujvpIjoluu0NAk4yclSSYlKTpZpr9TU7kpKtH9NIACtpNOOHQd+WpAnNegON2m0YjFC5FFDMCWdloxCHA5z11qYbdtkWsrhkC3aCxZI1chqlX45mzfDpz99aPO87GxZj1NQAOecA6edppWao4kGG6WUSjSj1MWtZ/ff1jw369tWc7JnHdPbKphirsEbsfNq62Imnb+SgsOUK/o7KcJmk/ASPQYhunYl2kwvOs2TmSkBJC1NQk59/cG3gEIqKGExpWxhHtFIYwCTjAZO5VU6SebL4d8SCqawL1jCsw2r2L/fTSgkxy6EwxK0SkrkdaLM5t7roROxrZAaHg02SimVSEa4SV5P27bJwt6pUyWIVDrc/Cm1mCmBSlJCPg50SjfeuREzBYd5roFOikhLk51QeXnRpngSHCwWCTUf/7iMYevW7mMKgsHoziYz65FK0nzKqCIfPw4KqORkXsOEiddNx1NtKiQdP8VtpVxhreKNutVsa3DT1gazZvVYK9RDf4eoJ1JbITV8GmyUUipRxLFJ3nAZJjP77EXAwcZ3psEf31N/5yFlZ0tgyciQ+0Mhqd7s3y8VkWuvlcdv3y5rerxeCVnRBcgVhpu1rGYl6yihgnyqmc0O2nDwH06hyTwZqxXacbLFmMcyaxnfP24975xWzIMPmZk+vXttjWHI80e3lNtsR80h6moINNgopVQiiGOTvFjNnSvbr5uapDDU96DxAwfk/rlzY39Ot1vOcnrrLZlSmjJFgsXf/ta7CHXKKb1Pvt68Gf71L7k/2jEYZEzbcHNnpJhCKimmgq/xIJVMx4cLC7LTShYjm2hy5GPfVc6nrq7kvROKKC2Vt9DjkdePHtvg90shzO+Py1upEogGG6WUSgRxapI3FEVFcOqpEjqiW5yjU0EtLRIuVqwY2ssNNJN23nlw6aUDnHxdHOHacypp3+ijmnTKWguJRMxdW7YBQiEzeyNFpOMjQhJ+0oDuAGSzwfTpEGxzEPLXYPb7uqbG3npL+uZEt5pHD9cEeOCBUSmEqVGkwUYppRJBf/ule+pvUcgRMpvlhO19+6TrbnQayDBk99KSJbLNOdYCUSwzaQsX9vNF69Yx/80Kbu7swJJjp2JyCb/et4oPgm4iEVmPE90G7iOdDuykm/z4Lc6us6BSUyXkOPCT5JCeO+4i6VPzzW/K9+ZwyGPy8iRsZWePSCFMjTENNkoplQj62y/dUwxN8obD7Ybvfx+efhree09exuGQIwbOP7+7ktFzo1Y0e/n93dUXGMZMWo8kZJ5cQEOmg4xkPyd0lHJbdhU/OLCajT43hiFhy2SCGlMhFZESjqeUCmMeZrOp6y1p8RqckFpN6gndPXccDpkOKyiQapTNJtWa6PhGoBCmxpgGG6WUSgT97ZeOMgw5DfIwTfKGy+2G73xn4K3OPaeXGhpk7QxIYJg8WYa9dOkQZ9L6rClyYiJrN1RVOWl1ziO/s4xrC9ezurqYjqCZcFiCSWammZf9q5jVXsUCyqgz52MYDpICfuamVDNlQTbmVSu7Bu/zyULhoiKp/PTlcMhbW1Gh27zHCw02SimVCAbaL+33y5U3O/vQnv5x7Hcz0FbnntNLqakSbFpbJaw0Nkq4KS2F99+XdTnTp/f//IfMpPVZU+RplF42Bw5Afb0JjyWf3JZyTphcyXsHirDbpWBVVATt7W7+VLuaU/avo8SowNFWgy3DzvTzF5N1xcpeC2YOVwirrIQdO+DBB2X6bQR316tRosFGKaUSRX/7pe12qdREtxBFjUK/m0gEnnlG+tDk58O770qn4JwcmdLxeCRznXQSvPOOVHJaW/s/AfuQmbQea4oaG+HttyXY5OfLepg2n4NgSw1hi4/Jk+XrfD4JU3Y7VKW5+XNaMW5HJXNzfVx2XTpTTz802A1WCGtokNPFHQ4JZGlpR7i7fpQaK6rBabBRSqlEEksL3KH0uzmCi+1LL8Ff/iJB4+235SmSkuRzp7N7G3VLi2wJr6uTRntLlsQwk3awlGK0+qmocNLWJoHJZJKeN6YWPza/ndy8dNzHScFq0ybYtat7IfDMmWaWLC9i5UqYO0AAGagQ1toKr74qr3fKKd1hbNi760exsaIanAYbpZRKNIO1wB1Kv5utW4d9sS0vl+mZ2lq6Ts02m+XvHR3yeXQTVyAAkybJtFRaWneASE2VHVdVVbIW59xze4SEg6UU/2uleBrn4XKZur4VEwY5gWrqChaTtbAQzwHJal/4goSaaEZzuWLLaf0VwkIh2U11/PEytp6GvLs+ARorqm4abJRS6mgSa7+bl16SrU7DuNhGs5PPJ0/Z2SkhJRiUEBEOdwccw5BFvX6/BIQvfhE2bpQKz65d3busUlLg2Wfl691uukopgfermNpURiQln1DEgTXox9lSjT81m03TVtLaZmb/fhnLsccO/23rWwirqYHf/nbgtdgx764fg8aKanAabJRS6mgSS7+b6mrpujfMi200O+XmSg4ymWRHkcUi4Sb60WqVx/ecajrtNPm6LVvkY0GBfGxr6ydTud10XL6aqu3rmOGrwNVaQyjJznbnYp5lJe994Ka9Xaorjz8ur3ckhY+ehbD0dAlbR7y7fgwaK6rBabBRSqmjSXo6hs1OS62fDqvzkL4s+P1SUqmqkgvpMC620eyUkSFTS9GzncJhqd4Eg92nd9vtcl2fNUvWN4NUZoJB+NjHDp+pck9zs+OCYja8Ucn8Qh/7/On8s6wQf7sZp1OeZ/Jk2L1bZnviNasTt931Y9BYUQ1Og41SSiWqfhb+lvsL2VdfQurWUiod80hKNpGdLRfpnOyDV+SCAlkcc5iLbcTro3LPoeuKo1ukw2GpzkSPLTCbZV1KKCQX/2BQ/n7ccfCVr0jg2LNHgk50d1P0sMlo+OqbqcxmWHWBmbU1RbzcKAuQfX55fEuLDPXYY+PfJXg4u+v7NUaNFdXANNgopVQi6meXTUNWCU/uW0WTaRUXuapwd5ax35JPfY2DQKOfpbnVOGdmwznnwGOPDXqxbQ7Y+cPj6bxdf+i64uJi+fu770qFprNTDsM0DAk7gYBM44RCMHMm/OhH3dNSPp9so66qkipPe7sEmuxsCUBZWYcWMKKLex9+WLofJyXJmHJzDwa2HHlcvGd1hrK7fkBj2FhR9S9hg015eTkPPPAAs2fPZvv27Vx++eUcd9xx+P1+brjhBlwuF36/n7vvvhubzTbWw1VKqfjpZ5eN0epn/79K+Vh7FVvPXE3p7NWUVKwj21PBJEsNHq+d93IX8/FrVmJ2F8sK3gEuti1l1WxoXswryYXkF8rC4Lo62LBBqhdr1kjA2bJFAobVKgElKal7N5HdLhWOzEwpDkWDRn29LBoOBKTSE63q1NdLP5wTTpBqTN8Chtstu56i1ZOUlD5TbIzMrE4su+sHFbfSj4qXhA02//3f/82zzz7LtGnTqKys5Mwzz6S8vJyrrrqKVatWsWrVKh577DHWrFnDPffcM9bDVUqp+Bhgl43XcFJhnsdMSxnmret5/eSbeP3km3F5K7EGfHgC6ezsLKTIYabIzIAX20hVNdubs9mQsRL3fDMeD3zwgbxcZ6fsEG9shHvugYsvhg8/lJDS3Cwfk5Nl7U1+PsyZI52Co0EjFIJ//EPCUHOzPDYlpXtay+uF//xHdk71V8BwuWTbuMMxurM6g+2uj0lcSj8qXhI22JSXl+M7+H9LSkoKXq+X2tpannrqKR588EEAzj77bK688kpuvfVW0nX+Uik1HgywyyYQgFDYRGtmPtmecpzNlew1FbEvUITNBo4saN/eo5oxwMXWO3MxT3WuxDzLjcfT3fHX5equxFRUwE9+IutmjjtOKjbJyd07oex2CR41NVLJ8XqluvPII/JyLS0SbsJhqfJEz2hKTpbwNFDF5aie1Tni0o+Kl4QNNhdeeCFf/epX+cc//sHjjz/O/fffz4YNG8jOzsZutwOQk5ODzWZj48aNfPKTnzzkOQKBAIFAoOvzlpaWURu/UkoNywC7bGw2CQgHOhyYD9Tw7gYfHxrd4SEtTWY9ev2O18/FttpbyK4fm5mbKpWanh1/QZ4nEJCqzcaN8uUffNA7aDQ2ylEEO3dKwLnrLmnEl5TU3dcmOVmeu6WlOxBFqzANDf2vkznqZ3WOuPSj4iFR/3nwi1/8guTkZJYsWUJaWhoXXHABNTU1ZGVl9XpcWloatbW1/T7H7bffjsvl6vpTUFAwGkNXSqnh67nLpodgUG6q2+FnT72dD3al09QkUz0pKbJ+Zd++Q76s+2K7cCEUFZHuMmO3y5oaj+fQdSzBoASU/Hyp3Cxf3r0jyeuV1/jPf2DbNpmSOukkWSRcWyshJrrAODVVppVSUuTvRUXSmTg9XWbbBqraRAtNixbJ827bJh8XL9YGvio2CVux6ejo4POf/zy1tbV84xvfYMaMGZhMpq5qTVQwGCQ5Obnf51izZg3XX3991+ctLS0abpRSia2f+Zho9QTDIDdczbumxXhSC+lsl+pGWhpMnSpB469/lYv/QFWN6NNv2CDTQsnJEkYCAVkj09wsj8nNhe3bJYxEZ7TKy7tP8Z47F6ZNk4By4IAEoWiwCYW6K0mpqfI6II/NzJSdUYOtHtBZHXUkEjbYfOELX+DPf/4zGRkZmEwmLrnkEu699168Xm+vx7W2tpKXl9fvc9hsNt0xpZRKWP2fT9l7PsaYls/WMgeG188CczXl9mxeSl5JMGTGMCQ0pKXB0qUyXXW47dDRpy8rk4XCIFNGra1SrUlOlgpNdbU8n9crVZ3PfU5uu/tumVZqapKFxa2tUvlpb5fH2e1SpWlpke/JYpGg09gooSYtTfLa4dbJ6KyOGq6EDDYej4cPPviAjIwMAL773e/yyCOPUFhYSHV1NcFgEKvV2jUFtXTp0jEcrVJKDd3gh0F3L/z1v1NB8q4apjrsVCQt5hfmlWzDjWHIFFJqqoQHq7X7NIWKioErHZGIBI8LLpAxbNsmz2O1SiUl2hjvpZfka3/zG6nm2O0STJoPRHB5K0lv8+FypVObVUhLi5mWFnmcwyHTRh98IKEnOs2VmSmBaebMBF8no456CRlssrKysNvt1NTUMG3aNAAmTZrEsccey1lnncUrr7zCGWecwQsvvMDVV199yPSUUkolstgOg5b5mOoXKnny5z7s2ek892Ehe8JmUm0SaMJhCUUej6yZ6eyUSszPfy4Lde12maI6+WTp3uv3y3EHFRVSYfH7uzsN5+RINSW6a8nrlUW+S5fK7X4/tG4q51Ol65hnqiArtYOg387e1BKetK7ig6C761DMOXOk2lJaKp2IXS6ZXpo/X3c/q5GXkMHGbDazfv16brvtNo4//njq6+u5++67cTqd/PrXv+bmm2/m7bff5sCBA9xxxx1jPVyllIrZ0A6DNmMvKaJhsjS96wxL5cPvlwpLUlL3dNGrr0ogsVjkOaPnLL36KjzzDEyfLl+XkSEBo7NTtmhnZMhUUVtb9wGXJpO8TkqKBBWLBWYGyjmueS2eTg+1lgJaUxykRPzMbS3lKlMV97Ga9zrdXU38bDZZgzNrFlx0kaxdBhnDnj26ZkaNnIQMNgDHHnssv/nNbw65PTs7m4ceemgMRqSUUkduqIdBFxZK1eXVV2VBr8MhAaStTcKN3y9hyeORCs3s2RIstm2T5ywslMfv3CkVnuiRCJGIvF5hoew6ysyU8BEMwjvvSKhpbZXHmowIJRXrSPF72J0yj2CniVArdKY68afMo7C1jM+ynp3pxRgmMzt2yKLj44/vPhjzz38eaNptNN99NREkbLBRSqnxaKiHQZvNMpX0zDPdC3nz8uSIAq+3u8piNsvtaWkSiqKVl5YW+Zp9+6Rq09YmAWPBgu4jEpxOCTF2u3xNOCyvHa0IubyVZHsqaHIVYGs1YTJL8OnshEDERI05n+OSyrl4uTQNvPxyCS6FhbJA+fDTbqPz3quJQYONUkqNouEcBn3ssRJEPB4JIKGQVFhycmQdjMkk27SdTqmwtLXJc4D83eHoPqnb6ZTnAVnMW1cn/WZ8vu6TuC0W2fVUUCChyNrgIznUgSnLgc0mj8vPl9cNhSDZ7CCvtQaz38eST8CnPiVBa2jTbiP5rquJRP8pKaXUKIr2kamqkvUrPUWPDXC7e2+HLiyEZctkKmrFCvj4x+Wog6QkCSRNTVI92bdPPo9EJJxYLPL3UKj771arfB4MyjhSU+Xrol8D8vdwWAKHyQRBWzqdSXasnX6sVqkKRStKqalg6/Tj8dux56T32vE0lGk3peJFKzZKKTWKhnNsQM+vqa2VMPHRR9IYLxLp3vLt9Xavn4lOJ5nNEmSysuS+nouOMzJk19Orr0r/mt275fHLlkllqLFRHhd2FFKdVsKkvaVkTpnH3GIT9fVSifG1GBT6q2kvWcwXvlPYa1ppqNNuSsWDBhullBplwzkMOvo1Tz8tfzweCSbRKktmplQ+/H65LVoNSkqS6aTiYlnvUlMja21SU+Xx1dWySDknR54zEpFqTm6ufP3+/VBTY6YzexUXh6r4eEYZzin5zJnhoGWfH6qqMU3OJm3NSszze08CDGfaTakjpcFGKaXGwHCODXC74dJL4b33ZM3NpEndW7orK2U6KrrrKdp0b/p0WLJEFvvu399drfnb3yRYJCXJc6SlyS6mwkK5vapKnv+LX5QdTg6Hm+Qdq/E/vw7z3goclhpcKXb4xMBp7Kg+rVsdtTTYKKXUGBnOsQHRMFJUJJWZxsbu+6KnfHd0yMeMDFnfcuCAVEZWrJAeNk8+2X3Q5a5dUsWJRKSvTVqaVG+ii3s3bYJzz41u13YTaC9mGpW4p3g5Y7mPooXpkpoikUNS2VF/Wrc6KmmwUUqpBNXfWVI9p3fS02UqKxKRgkl0R1RnJ5xxhqzHmTkTPv95mY7Kz4e77pLHfexjsianqUkChtUqIamiQj6PLu596y0JPIFAdLu2GUdlO44Nz7PvhQqyZnbgnDxwY5rhTLspdSQ02Cil1Ajo/4DL2L5uzx548UV44w0JH0lJUhQpKYHzzuue3snLk3UxLpcEEZtN+tbk5cmaG4tFdjy5XFLh2bOn9y6l6Ineycny2jabVFeqquQxqalS0cnNlSBkMkF2YznLtqwlNeJhl1HAhwEHJ03yYxqkMY2e1n0EhvsPaQLTYKOUUnE2+AGXg3/db34D//d/MlUTDsvUzYwZ8nXR7PCZz8jH8nI58yk9XV6npUXCSEmJhJC+u4767lKy2SQ0eb3ytX6/3P/aaxJsMjLktmgQinYgTm3z0Jgzj+SAicYD4DWcZBymMY2e1j0Mw/2HNMFp7FNKqTiKHnBZWipTOsXF8rG0VG4vLx/46269VQ6pbGiQKkpGhvzCvn07vPtu986lzZvhmmukcV8oJI9vb5fKyrJl8jg4dNdRz2kskEpOSooUBFpbJXzY7RJ86upg40YJPtEdUtEOxC0uSTrRnjiBANqYJt6G+w9JxR5sjL6dpJRSSvXSt9Ou09nd7XfePLl9/Xp5XN+ve+YZ6U1jNkuYSE2lqxleUpKEl4oKOViyvFzCx+23wwUXSCVkxQo5eiEaavpr9jdYc8DoNu/o60bvt1i6g5A1IB2Ig8lS8gkGu3dZATKojg5tTHOkhvsPSQFDCDZPPvnkSI5DKaVGVHTtyubN8nEkrgnD7bRbWSkVmXBYgkzPLsDRtTORiFRRQqHu7JCUBJddJido19bKdFIoJFNLZWWH7jqK7lLKzpb7q6sltEyd2n22VFKSPH9enoQlu1363xhG7w7EhiGvl50tlR9AG9PEi7ZsPiIxr7G56qqrePbZZ7FHDyBBqjgmk4kDBw7Q0tLCvHnzeOCBB0ZkoEopNVyjtVRhuJ12fT6ZCoqGGLNZQk7SwZ/Q0dARDEpo6ZkdhrrrqOfj33xTzpiKnuw9bZqM0WaTsBIOy06ptDQJQgXTCmnIKmFydSlVSfNIdZi61vNoY5o40pbNRyTmYPPTn/6Uyy677JDbf/e733Httddy/vnnc9ddd8V1cEopdaSiSxVG43Tp4XbaTU+X8GAYEmpSUyXoRANNOCz3JSdLk71TTumdHYa668jthjlzJNy0tEgDvpKSQx/v98PkydKkb+NGqKgw8w/bKj5rqmKhpYzJ8/KZlOkArzamiStt2XxEYg42n/vc53p97vf7ufLKK3n66ae57777+NrXvhb3wSml1JE4ktOlh7PLdriddgsLpevvtm1SkcnO7u5JY7XK3w1Dgk5hYf/ZYSi7jqIVrPJyad63Z4+8R273oWt0Fi+G006TP/J+uMmqX03u2+swb62AbdqYJu60ZfMRiTnYpKamdv29tLSU//qv/8IwDN544w2OO+64kRibUkodkaEsVegZCoY7dTXUTrs9w9OyZfDhh9LpNxSS4wyam+VPJCKB41OfgssvP7Ls0LeCdfLJ8PrrEqo8HjjxRNkp1d94u96jhW44TRvTjBht2XxEhtzH5v777+eGG27gM5/5DL/73e9w9lcmU0qpBDCcpQpDmrrqp6zjdptjWvPSX3jKzZWgsXmzVFJMJhnD8cfDl74kVZMjuZb1V8FyOmVqq7wcdu6UkHPccTEUYLQxzcjSls3DFnOwaW5u5itf+Qr/+Mc/uPPOO7nuuusOecwbb7zBiSeeGNcBKqXUcA11qcKQpq62DlzWcbvdg655GSg8VVVBVhZ885vyeWoqnHSSHIvQX5VnqIWSgSpYOTlSBCgqksXCV1whlRstCIwxbdk8LDEHm2OOOYbq6mrOPPNMvF4vt912W6/7Ozs7+ec//8mmTZviPkillBqOoS5ViHXqqu6lcqY93X9ZJ1JZRc35q9kSkd+o587tfS0aLDzl5MhJ3Rs3wuzZkpU++kiqOMceKy/x7LPD3901WAXLZJIt3q2tsiNKr50JQitjQxZzsMnMzOT//u//eq216SkcDtPa2hq3gSml1JEa6lKFWKauaqsjmP/WnUwMTHi9EAg48dvn4X2xjP88u557kosxTGaysmDRIjnj6dhjJdj0DU+GIWcyvfdedxXJapXbXn1VmvdNny6hIzNTTugezu4u3WyjJoKYg833vvc93If5v+b6668/4gEppVQ8DWWpQiwX/mnhStKrKqCogEaPiYoKyTh+P3g8Jqwd+UyzlHPcnEp2houorJQjEf71L3nNoiLpIjx9ujxnY6NUgcrKZBeU3S5bsN9+W8JNbq4sIN65U7Z9h8OyS8rpjG13V0+62UZNBDEHmwsvvBCALVu28Mgjj1BeXo7FYmHBggV85StfYfbs2RQUFIzYQJVSarh6LlXweruXK6SkSAUlGgZiufCfWeDDUdtBg9/Ba292h6DOTgkcwYiDfGowtfrY3ybPYbVKJcjjkZCyZ49UXKZMkWknr1d2QqWnS3Bpa5OPc+dK0ElJgfp6CUXt7RLQsrMPHkw5yO6uvnSzjZoIhrQr6q677uI73/kOU6dOpaCgAIvFwhNPPMHPfvYzfvrTn3LNNdeM1DiVUuqwBltYazZLKHj++YHXqMRy4V9xTjretXb+808/lc1OrFYJJm1tEn4yk/20h+zsbEgnaJWvD4dlGmnbNtnG3dQEL74ofzeZ5LDL5mbpU9PeLh8tFglCqandnYiju5g8HnnNjAz53obSiFY326jxLuZg8+STT/Lyyy/z0UcfUVJS0uu+vXv3ct1111FQUMB5550X90EqpdThHK73TKzbuA934e+MFPLPyhLSG0tJdc7DajPR0SEVl0jYIJdqPkxezPZAIa5UCSORiIyps1MW6E6fDnv3yvlOaWkSXgyju9uwzSZVmrY2qQJFz44yDKn++HwHT9Q+aKhrY3SzjRrPYg42zzzzDOvXr8fWdYxrt+nTp/OXv/yFr371qxpslFKj7nCh5ZprZDdRrB2IB7rwA9xxh5mdqas4w1bF3FAZjUn5GEkOMs1+JoeqqY9k838pK4l0mjGZugNLJCIhJiVFwklzs4wxGJRppqQkeczUqfI5yOfRQy+zsiTMWK29T9Qe7toY3WyjxquYg82UKVP6DTVdT5SUxNSpU+MyKKWUilUsvWcefVROxh5KB+L+Lvx79kgVJ9nt5s/7V3Nm+zpmBirIjtTQlGTn/dBi/spKanF3hZpoMElKkoBkGBJqrAenqSwWqeQsWCCvHz1GIVq9aW6WKafjjpNFyDU1UvFxOGQ6StfGKNVbzMEmHA4f9jFNTU1HNBillBqqWHvPRCIDVyhiXaMS3Q5eWAh78t08UFvMgtxKUsM+9gfTeau2kAPNZqx+qah0dEiQAfk8GJRw1N4uU0d2u4zLbpfDJnNz5XsJhWQdjmHI7cccI5WeAwck7GRnS8jRtTFKHSrmYGOxWHjppZc47bTT+r3/73//e0zhRyml4imW3jPRnU9H2r8luh28rU3W73i9Zjb7inA6wZoKkzqhIyjVmehCYLNZQonJJJ+DhByzWYJK8ODjN22CJUtg4UK5f+ZMWY/T2SmPs9thxQo491z5nnRtjFL9G1IfmxNPPJElS5bwqU99imnTpmEYBnv37uUf//gH77zzDm+99dZIjlUppQ4RS++ZrCxZu7Jnz5H1b+m7HXzZMrr62Ph8Eng+9jE5EgFkfc+WLfDnP0tvmrQ0SE6WsBIOS4ff5ma5rbFRet0sWCBnN61cqQt8lRqOmINNdnY2//nPf7j22mv56le/SiQSwTAMzGYz55xzDq+//jq5ubkjOVallDpErE3nzj0XHnjgyPq39LcdfPlyWb9TXS1HInznO9IZOGrXLjkWobJSKkfRXU7Rqam0NAk4J50k02HFxXDDDVLFAV3gq9RQDamPzZQpU3jyySfxer1s27YNgLlz5+JyuQCoq6vTcKOUGlWxNp2LV/+WgZ7nE5/o/3miFaM5c+CDD2S9j8kk62jS0qSXTXTNzfz5sG+fjFsDjVLDM6RgE+VyuViyZMkhtz/44IN8//vfP+JBKaXUUMQaWgbrQBwKSaCIZdpnKH1golNlKSmyCLixUW6zWqVqEwh0b98eSqM9pVT/hhRs9u/fz6uvvkp2djannHJKr/v+9re/cdddd2mwUUqNiVjDRn8diAMBuS0lRQJGLKdmx9oHpudUWV6eNOOz2eSPYcjam9xcmY5qadFDKJU6UjEHm9dee41Pf/rTtLa2YjKZOOOMM3juuecwmUysWbOG++67jx/+8IcjOVallBpULGGjbzO/tjZ44w3ZeZSVJWtdUlKGdmr24cYUnSqrqZHppwMHZKGzzydBJ9rMXQ+hVOrIxby+/qabbuKqq67i/fff56WXXqKtrY2f/OQnnHTSSTz11FO88sor3HjjjSM5VqWUOiJ9m/mlp0s/mFBItleHQnKeU3q63O/xSEfiSOTIXjc6VbZ4saz5CQZlLU1mJpxwgkxLlZVpoz2l4mFInYfvvPPOrs/Xr19PUVERZ5xxBv/85z/JyMggEAgM2p1YKRUfgx32qAbWt5lfc7OEF5dL3r++B0zGemp2LHpOlX3wAbz2moSbaI8abbSnVHzEHGwmTZrU6/OsrCy++tWvcs8993Tdtm7dOj73uc/Fb3RKqUMc7rBHNbC+zfwCAanSJCfL530PmIz3Yt7oVFlREZxzjoZTpUbCkA7B3Lp1a6/b9u7dy4YNGwA5cmHHjh0abJQaQbGeUK3617eZn80mO5I6O7v7yvQ8YHKop2YPhR5CqdTIiDnYFBYWcuqpp5KU1P+XhEIhnnvuubgNTCnVWyyHPfY8oVodqm8zP5dL1rXU1cnHnjuUhntqtlJqbMUcbO69915OPfXUQR/zyU9+8ogHpJTqX6yHPcZjPch41V8zvzlzpLfMrl3djfRaWrqb+517rk4ZKXU0iTnYHC7UAKxYseJIxqKUGkQshz1qc7fD69vMr6MDZsyQSo3d3nsx78KF8Oyzup5JqaPJsDoPK6VGXyyHPWpzt9j018wvP79352G/X86W8njkvlBIdlG99pp83XXXabhRKhFpsFHqKBHrYY+6HiQ2/S3ejX4eicAdd0ioycmBDz+Uv4dCYLFIsElJgZ/9TKellEo0cftfMhKJsGPHjng9nVKqj+j6kOxsWR/i9cqF1uvV5m7xFl3PlJoKGzfK4uLUVDmw0uGQ7eDPPw8vvTTWI42vSAT27IHNm+XjkTYmVGosxFSx+fGPf0w4HB70MY2Njfh8Ph555JF4jKvLG2+8wZtvvsmsWbM45ZRTsNvt3HDDDbhcLvx+P3fffbc2BVQTRrxOqFaD8/nk7CiPR45cyMnprpDZbDB1KuzeDX/7G5x22vgIk9ofSY0XMQWbsrIyqqurKSoqwmw2s3HjRiwWC8cff3zXY6qqqnC5XHEd3EMPPcTu3bv58Y9/3HXbF7/4RVatWsWqVat47LHHWLNmTa8mgUqNd0M5WXo0jWY35JF+rfR0CIelM3BGxqG70Do75TFVVeNjF5r2R1LjSUzB5gc/+AFOp5MpU6YA8PWvf51f/OIXvR4TDoe5/PLL4zawDRs28MQTT/DCCy903VZbW8tTTz3Fgw8+CMDZZ5/NlVdeya233kp6PysmA4EAgWgLUaClpSVu41NqLCVac7fR/G1/NF6rsFAu8Js2yRRfT9ETuadOlfU2o7ELbSSDnPZHUuNNTMFmzpw5vT7PyMg45DH79u3jH//4R1wGBXD99ddz8sknc+2117Jz505uueUWdu/eTXZ2Nna7HYCcnBxsNhsbN27st4fO7bffzq233hq3MSmlDjWav+3391qtrbJT6f334fLLj3Bq6GCCMPt8XLQknX/+vZD6ejNZWXLcQjAooSY1VcKFYRx+F9qRhpKRDnLaH0mNN8PaFZWVlcWXvvQlPv3pT5OWlkZ5eTn3338/p512WlwGtXXrVt5//30effRRFi5cyN13382ZZ57J9773PbKysno9Ni0tjdra2n6fZ82aNVx//fVdn7e0tFBQUBCXMSqlRve3/f5eq7FRLsqNjdJ/Zvt2uPBCOP/82C/60eAR/KCcnNfWkbGvAlOgg5Nsdn6WU8KDjavY0+bG55PjFnJz5ftpbDz8LrQjDSWjERq1P5Iab4YVbL71rW/x7LPPcvfdd/Phhx/idDq56KKL+NGPfhSXQW3ZsoWsrCwWLlwIwDXXXMOtt96KYRhd1ZqoYDBIcvQEuz5sNpsuLFZqBI3mb/t9X6uxEd5+Wxb3ulwSGnw+eP112foey0U/Gjxa3i7ntI/W0hTyQH4BMxc6yEn18/GGUtKbq/hjxmraprtxuSTc1NQcfhfakYaS0QqN2h9JjTfD7mNz3nnncfrpp+NwOAgEAnENEKFQqNcurJSUFObMmUNnZyder7fXY1tbW8nLy4vbayulYjeav+33fC3DkJDTc8dSJCIX4cJCCQOHu+hHg8f+xghf8qwjz+qhJmce3iYTje/AsmVOcpbPYxFlRFjPIxTT0GCOaRdaPELJaIVG7Y+kxpth5fxNmzYxZ84cLr74YgC2bdvGDTfcQF1dXVwGdcwxx9Dc3IzH4+m6LSkpifz8fKqrqwkGgwBdU1BLly6Ny+sqpYam52/7/Ynnb/s9X8vrldDgcnVfiKMnc9vtvS/6/ekZPD42rZJprRX4Mgqw2U3k5EhgqqgAAxPOefmsmFzOj6+o5Hvfg9tug5tuGrzaMpRQMpBYQmNHx5GHRu2PpMabYf1TXb16NVdffTWLFi0CYOHChZx++un893//d1wGVVJSwtlnn81f/vIXAJqbmwmFQnzhC1/grLPO4pVXXgHghRde4Oqrrz5kekopNTqiv+1XVclv9z1Ff9t3u+Pz237P1+rokItvdBY6ulMpO1vCzuEu+j2Dhy3oIznUQTBZEoTJJJUVj0cu7jgcmAId5Lt8LFwo1ZHDXeTjEUpGMzRG+yMtWgT798O2bfJx8WLd6q2OPsOaijr55JP55je/yX333dd1W319Pe+++27cBvbYY49x3XXX0d7eTlVVFX/84x+xWCz8+te/5uabb+btt9/mwIED3HHHHXF7TaXU0PR3WnZ0LUn0dOx4/bbf87X27pWqSyAgQSS6U6mkRD4/3EW/Z/AIRtLpTLJj7fQTsMkiE6tVHhMIAKahJ4h4rFsZ7SmiRO2PpNRQDSvYpKenU1VVheng/2l///vf+fa3v80ZZ5wRt4FlZ2fzhz/8od/bH3roobi9jlLqyIxmN+Toaz39tBxzUFsLmZmyU6mkRNbbxHLR7xk8klyFeLJLyK0rpTFHEkR0WstmHV6CiEcoGc3Q2PM1dUu3OtqZDKNvAfnwWltbu3ZG+Xw+QqEQF110EQ888EC/PW4SRUtLCy6XC6/Xi7O/X6OUUsM22p2HX3oJHnxQ+tjMnQtpab0v+oNNoUQPuYwGjxxPOcveXktqmwdvej61XgcFk/wsya3GnHOYJxtAz11R/YWSWJ+yvy3jbrceoaEmlqFcv4cVbOrq6sjNzcUwDBobG8nOzqa6uprc3NwBt14nAg02So2NWELPgI8Z5IuP5KLfN3gUtZcza/M60qorSE/qYNYCOxnLjyxBxCuUjGZoVCoRjXiw+c53vsNPfvKTXrcFg0E+//nP89RTTw316UaNBhulRl8sTeoGesx/HVPOrA8H/+Ijuej3fd0UW4RluZWcdZKPmcfGJ0FoKFHqyI1YsHnggQdYt24dO3fuZObMmb3ua2pqoqWlhZ07dw5v1KNAg41So2ugJnVVVd3TMdD/YyJbyjm/ei3H5Xtwzh/gi+MwF6PBQ6nEN5Tr95AWD19zzTWkpaXx9NNPc+GFF/a6z2q1smLFiiEPVik1PsXSpG7dOnlcz8cYBhjhCCua1mHa7+GDKfM4Od0kXx9jh7uhhBVdMKvU+DLkXVFf/vKXWbFiBUX6k0ApNYhYmtS98458XlTU++wna20lK2or2GEuIFBmYlo+dBWJD9N2dzRPGldKJZ5hFVwbGho488wzaWxsBOCNN97g5z//eVdHYKWUiqVJnd8vfxyO7rOf6upgktVHenIHkRQHbW3w7rtyf68v7qfDXXTqq7RUZquKi+VjaancXl4+ct+vUioxDCvYXH/99SxYsKBrnuvEE09k+vTpXHnllXEdnFLq6BKJwJ49sHmzdO212SS4mIwIGc17mFy/mYzmPZiMSFegcThky3bPs59CKel0WuykGH5SUuS4hIqKHt2N++lw13fqy+kEi6V79ip6flQkMhbvjFJqtAyrQd/pp5/OD37wg163ZWRksG7dOh5++OF4jEspdZTpOwVks0F9Pdh2lfNp2zqy91eQHOqgM8mOZ1IJzyWv4oRT3UQi8MYbUpGJnv1Ubytkb2oJhftL6cyax6RJpq4jDjJc/Xe4G82TxpVSiWtYwSYUCvHhhx9yzDHHAPDmm2/y9a9/ncWLF8d1cEqpo8NAu59su8o5vXwt1mQPTXkFkCl3OLaVcr6rimnHrCY4y82HH0JTE6SkSEUlGDTzV/MqvmyrYqGljHYjH3/QQed+P9T033Z3NE8aV0olrmEFmxtvvJGvfOUr/Oc//yEQCODz+Tj55JN55JFH4jw8pVSiG2j3kys9wqdt67Ame9jrmIcjbCLcBElJTrLnzuO45DKcm9fDp4u5/HIz27dL6Ghtlec0st28s2A1Gb51uOoqyG+rIcVvhyX9n9UQj/OZlFJHv2EFG6fTydNPP82+ffuorKwkLy+P/Pz8eI9NKXUUGGgKyOWtJHt/BU15BTjCJk44QaanbDZwuUyYWrrnhk47rYgLLoAXXuheE+zzwT863GzKKmZaTiUfX+RjyXXpUNT/3u3RPjRSKZWYYlo83NHR0e/tU6dOZenSpV2h5rHHHovfyJRSR4WBpoCsAR/JIbkjHJZAM2UKZGQcDB09djaZzXDccbB/vxxsmZICWVmy+HfrdjPv7i9i6hkLMc8sGrAhTfTQyOxsaXPj9UIoJB/Lykbm0EilVOKJ6X9xt9vNo48+2vV5YWEhFoul1x+z2cxXvvKVERuoUiox9ZwC6iloS6czSe5ISpJg00uPuaFIBD78UBb4zp0L4bCsuQmHZct2fr7stOq7o6nnLqw9e+Sxq1fDokUSkrZtk4+LF8etUbFSKsHFNBX18ssvk5eX1/X5ddddx9KlSykoKMB0sN4biUR4/PHHR2aUSqmENdAUkNdViGdSCY5tpWTPnYfL1f/cUCS/kDfegDfflAAzbRq0tEAgEJ22ks/77mgarBHfzTfrMQlKTVQxBZu+XYZXr159yCnekUhEKzZKTUDRKaCqKpnyyc+P7ooy81zyKs53VXFccpmsqYlul6qWnU07F67kibvMvPkmvP8+ZGZK5aWkRKatovruaBpoF1ZpqYxDqzNKTVwxBZvf//73HO6szMbGRiorK7nvvvviMjCl1NHD7ZYwEa2g1NRIBcW9ws20hatxftjnjsWL2blwJT993o3HA5Mny9qbpCTpPOz1wrJl0qwPeu9oiuUMqkGOkVJKjXMxBZs///nPbN26lWnTpmE2m9m9ezd+v58FCxZ0Paa+vp7c3NwRG6hSKrG53RImDp0CchM5q5jatyppq/eROiWdqUsLeeKn5q5wAlKpqauTRb4ej+Sg7Gy5r+eOJm3Ep5QaTEzB5oc//CE5OTkUFBQAcPnll/PAAw9gtVq7HtPW1saaNWtGZpRKqaNCfydly1oYMxUVRV1rYaY8Kwt7Z83qDiclJVKp8XhkbU1Dg0wr+Xy9dzRpIz6l1GBiKtQuXry4K9QATJs2rVeoAelGvH79+rgOTil1dBvoUMoPPoCPPoL29u7H5uTI9FNurmzTbm6WYxb67mgaaBdWlDbiU2piG1aDvkAgwPe//30+/elPk5aWRnl5OT/5yU96TU0ppSa2wdbCuN2wdats0548ufu+nBwJPtXVUrG56SY48cTea2W0EZ9SajDDWlr34x//mKysLC644AIWLlzI5z73OaZPn65HKiilugy2FiYjQ9bCVFVJZaavlhYJNH1DDWgjPqXU4EzG4bY7HcaBAwdIS0s7ZGoqEbW0tOByufB6vTj7O0xGKRU3mzfDD38o008Wy6H379sH//qXrLOZP/+QneCH3bLdXx8bt7vfY6SUUke5oVy/hzUVtXPnTq688koyMzN58skn2bRpEy+88AKrV68mXSe2lUoIkcjYNqk73KGUKSmwYIF0Gq6v77UTPKZwMvAurBH5dpRSR4lhBZuvfOUrLFq0qKtJ35IlS6itreWyyy7jqaeeiusAlVJDN1hX3tGqZsSyFmb5crjhBvn7cMJJf7uwRttYB0ilVG/DCjbHHXcc9913X69mfKFQiH/9619xG5hSangSpSvvwB2Ju6ebVq6UpnxjHU6GKxECpFKqt2H9XpGRkUFra2vXOVEfffQRN954I0uXLo3r4JRSQ9N3J5LTKetbol15PR7pytv3MMmREu1IPB4PpRxoK3tpqdxeXj7WI1RqYhpWxebrX/86l112Ge+88w6/+tWv2LZtGyeeeCIPP/xwvMenlBqCROzKW1wMn/uchBqQNTVFRUf3dI0e66BU4hpWsPF4PDz44IO0t7dTVVVFbm5urwZ+SqmxkWhdecfrVE0iBkillBjW7xKnnHIK69evJzc3l6VLl2qoUSpBJFJX3vE8VRNLgOzo0GMdlBoLwwo2d9xxB0X9/BqiDfqUGlvRnUhVVbLzqKfoTiS3e+S78ibaWp94S6QAqZTqbVhTUQ899BDbtm0jMzOzawFxKBSirq6OL3/5y/Ecn1JqCGLdiTTS6z7G+1SNHuugVOIaVrA5++yzWb16Nfn5+V3BxjAM/vjHP8Z1cEqpoYvuRIqubYml8V28e7Ek2lqfeEuUAKmUOtSQg01zczPf/va3SU1NxdKnT/qiRYviNjCl1PANpSvvsBf4DpKGDtd1eDxM1QwnQCqlRl7Mwcbj8XDJJZfw0ksvYTab+dznPsfDDz/c1X0YwOVyjcgglVJDF0tX3mE38ztMGpooUzV6rINSiSfm//2++c1v0tLSws9+9jPuuusuysrKuOeee0ZybEoppDCyZ48cKrlnT/wW3A57gW8M250m0gnc0QC5cOHR359HqfEg5opNTU0Nr7/+OklJ8iVXXHEFN9xwQ6/HhEKhrvuVUkduJPvADGuB7xA607ndZp2qUUqNuphTSH5+fq/Qkpqayty5c3s95plnnuHiiy+O3+iUmsBG+synYS3wHWIa0qkapdRoiznYPPfcc3z84x/vdVtdXR1PP/00AOFwmC1btmiwUSoORqNl/7AW+A4jDSXCCdxKqYkj5mAzffp0Tj311AGnmkKhEG1tbXEbmFIT2Wj0gRnWAt+JsN1JKXVUiznY3HfffYdUbPo6/fTTj3hASiWaePd4icVo9IEZVi+WibLdSSl11Io52Bwu1ACceuqpRzQYpRLNWB3iOFqFkSH3YtHOdEqpBKdbmJQawEgv3h3MaBZGhrzAN5Y0NBZlLqWUQoONUv2KRGDd0xFMeytZUeijM5KO11yI02mO2+LdwYx2YWTIC3wHS0NjVeZSSimOgmATDAZZsmQJ9913HytWrMDv93PDDTfgcrnw+/3cfffd2Gy2sR6mGmfqXipn9tPrOCNQQereDjqT7HiyS6goWYUnxz0qhzgmfMv+/tLQWJa5lFKKoyDY3H333ezZs6fr86uuuopVq1axatUqHnvsMdasWaMdkFV8lZdjf3AtBR4PwbwC2mwOrJ1+cutKcXmreHvZakKZ7lE5xPGo6gMzGnvUlVLqMBL6p8sbb7xBbm4umZmZANTW1vLUU09x9tlnA3LK+K9//Wt8R+sRwSrxHLw421o97MucR6vZiWG2ELA5acyZR2qbh5KK9bS1RkZtV/NR07J/KHvUlVJqhCTqj0j8fj9PPfUUl112WddtGzZsIDs7G7vdDkBOTg42m42NGzf2+xyBQICWlpZef5Qa1MGLs6O4gOwcE16vLNYFwGSixZlPdmM5Hdsqcbt1V3MvsexR7+gY+TKXUmpCS9hgc+edd7JmzZpet9XU1JCVldXrtrS0NGpra/t9jttvvx2Xy9X1p6CgYMTGq8aJgxdnU5qDkhJITYXGRrkeRyLQEnHQdqCD3DSf7mruq+ce9f5o8z6l1ChIyB/L//znPznhhBOYPHlyr9tNJlNXtSYqGAySnJzc7/OsWbMGr9fb9aeqqmrExqzGiR4X55wcWLYMcnOhvR327wfD5yc9x84ll6frGti+onvUq6p6lLkOiu5R1zKXUmqEJeTi4Z/97GeUlpZ2fd7U1MR5553Ht771Lbxeb6/Htra2kpeX1+/z2Gw23TGlhqZPA5mcHBPZ2eD1QqDDwFFZTerJizGfphfnQ2jzPqVUAjAZRt9frcZeY2MjgUCg6/OPfexj3HPPPSxdupT58+dz4MABrFYrtbW1zJkzh/379x9SyelPS0sLLpcLr9eLs792rkpB7y3L/V2cE3DLckL1w+uvj43bnSB71JVSR6OhXL8TsmKTk5PT63OLxUJOTg7Tp0/nrLPO4pVXXuGMM87ghRde4Oqrr44p1CgVszg2kBmNwJFw/fCOqj3qSqnxJiGDzWB+/etfc/PNN/P2229z4MAB7rjjjrEekhqP4nBxjmfgGCggJWw/vCG3MlZKqfhIyKmokaJTUWq0DBQ4qqqGPps1UEA67zx49tmBz5MqK5Mi0003abFEKXV0O+qnopQ6msWzAe9gFZmyMqngzJp1+H54WjxRSk0U+nucUnEWrwa8fQOS0wkWS3dAamiAXbuk105/tB+eUmoi0mCjVJzFqwHv4QJSQYFUb+rq+v967YenlJqINNgoFWfxasB7uIA0darcp/3wlFKqmwYbpeIsXg14DxeQ2tpg5kzIyZH1Nl4vhELysaxM++EppSYm/ZGnxqVIBPbsgc2b5WMkMnqvHW3Am519ZIEjloC0fDl85zuwaJEc+bBtm3xcvDgh+wgqpdSI011RatxJhIZ18ejx1/OEgi1bZNFwUpKEpJYWqdREn8vt1n54SikFGmzUOJNIDevi0YDX7YbPfEa+p/feg85OSE6GOXPgy1/u/l60H55SSgkNNmrciGf/mHg50sBRXg7PPy/fwyc+Idu9w2GZ1nr+eelho9NNSinVTYONGjeG0j+mb9hIqEMke4wpGtTmz+/9PeXnj01QU0qpRKfBRo0bsfSPqak5tH9MIqzJ6c+RBDWllJqoNNiocaPn9uj+jhLpr39Mf2tyWlvhtdfg/ffh8svhtNOGVxE50irQcIOaUkpNZBps1LgR3R490KGQ1dWyKynaP6a/NTmNjVIlaWyEpibYvh0uuED+DKV6E48q0HCCmlJKTXQ6M6/GjaH2j+k71dPYCG+/LUcUOByQlweBALzxhlR1ystjG0e0ClRaKq9ZXCwfS0uH9jzxavSnlFITiQYbNa5E+8fE0rCu51SPYUjIaWuT/jA2m/wxmSQ4eDyyUPdwjf76VoHS0+V12tslKDU2xvY8EL9Gf0opNZHoVJQad2LtH9Nzqicchtpa6RETCEioCQalIZ7dHvtC3Z5VII9H/u7xSCBJSoK0NHjrrdgX/Maj0Z9SSk0kGmzUuBRL/5joVM8rr8h6mtpasFrla1NSpGdMURG4XBJ8YlmoG60CtbXBO+/IR5dLAlNnp1SP9u2DDz6IfSdTPBr9KaXURKE/GtWEZTbDMcfIWpXKSgkyycky/XTggBxbMHmyfO73SxXH6x38/Kn0dHnc5s29p7XMZvnockn15vXXh3Z+VTSoLVwoHzXUKKVU/7RioyasSAQ+/FCmmaZMkXUrra1SrZk0ScJDQ4McX1BWJl/zm9/IVNVAu5wKC2HqVHj1VcjNPXRnls8nr1dXp/1nlFJqJGiwURNWdD3M/PlSaZk2Tc5jCgQk2BiGTE9t2CBTSPn5UoEZ7PwpsxlOPhmeeUaqOyDTW8GgVIBSU6XqcuCA9p9RSqmRoMFGTVg9d0WZTHLuktPZveC3s1Omk0IhCTXLl8d2/tSxx8KCBfIcra3yOklJUsEpKZGgo/1nlFJqZGiwURNWfw3wcnJkG7XXK1WahgapssyYEfuxBoWFsGyZVH+mTZNqTXR9DUgY6tkoUCmlVPzoEkQ1IUUi8icjQyo0PRfymkwSQjo6pMKSlDT4sQYdHb2nlaL9Z3JyZCrLbpdt3i0t2n9GKaVGmlZs1ITT87iDhgbYtUsqLscfL/1n/H7ZKZWdDeecA489NvRjDbT/jFJKjQ0NNmpC6Xvo5fTpsiPq3XfhzTehvl62eEcDSHExbNwY+/lTPWn/GaWUGn0abNSE0d+hlyDrZ6ZPl4Z6c+bAddf17hWzapXsfiorkzU10V1R0arOYNNKsTQKVEopFT8abFTiikTiWu7oe+hlT2azVFf275e/93wZnVZSSqmjhwYblZh6LoTp6Bi4I94Q9Nze3R+HY+BjE3RaSSmljg4abFTi6bsQZrCOeEPQ3/bungZaCByl00pKKZX49PdNlVj6LoRxOuUQp2hHPI9HOuIN5aClg6KHXlZVycLfnqILgd1u7S+jlFJHMw02KrEMthCmb0e8IYr2l8nOloXAXq90FfZ6tb+MUkqNF/ojXCWWWBbC9O2INwTRhcCLFslC4W3b5OPixcOe4VJKKZVAdI2NSixHuhAmBroQWCmlxi8NNmrUDbqLO7oQZjgd8YZAFwIrpdT4pMFGjarD7uKOLoQZbkc8pZRSE5oGGzVqYt7FPQ464sW5t6BSSqkYabBRo2Kg4wyiu7jLymQXd3HxwQBwFC+EGYHegkoppWKkwUaNiqHs4u5a+3IULoQZod6CSimlYpT4v/6qcWGEd3EnhBHsLaiUUipGGmzUqOi5i7s/cdjFPeZGsLegUkqpGGmwUaNiIhxn0LMqZTIiZDTvYXL9ZjKa92AyIuOiKqWUUolO19ioUTERdnFHq1KOynJOqF5HtqeC5FAHnUl2PNklbMpfhd3uPqqrUkopleg02KhRMw52cQ+qsBBOyipnxt/Wkmvz0OIqwJvswNrpJ7eulOP3VDHp3NUUFh7l36hSSiUwDTZqVB3Fu7gPy0yEVayjyvCwxZiH0zBhBbyGkypjHrOMMo5lPWaK0VlgpZQaGRps1Kg7Cndxx6aykskHKrCcUkBbtQmPR8JbUhLk5pkompbPpP1997QrpZSKp4QNNn//+99ZvXo1Bw4c4POf/zw///nPSUpKor6+nu9973tkZGSQnJzMj370I0x9t6AoNRYOrh6eVOzg5CLweiEQAJsNXC4whR2wrUZXDyul1AhKyHq4x+PhD3/4A3/605+4//77+d3vfse9994LwEUXXcRVV13FXXfdhc1m4/777x/bwSoV1WNPu8kEGRkwZYp8NJkYH3valVIqwSVkxWbHjh089NBDpKSksGTJEj788ENefvllTj75ZPbs2cOiRYsAOPvsszn//PO59tpr+63aBAIBAoFA1+ctLS2j9j2oCWiUTiZXSik1sISs2CxfvpyUlJSuz6dNm0Z+fj4vvfQS06dP77p97ty5VFdXs2vXrn6f5/bbb8flcnX9KSgoGPGxqwksuqc9O1v2tHu9EArJx7Ky8bGnXSmlEtxR8RN206ZNXHHFFdTU1JCVldV1e1paGgC1tbX9ft2aNWvwer1df6qqqkZlvGoCi+5pX7QI9u+Hbdvk4+LFelCUUkqNgoSciupp9+7dZGZmsnjxYh5++GHsdnvXfcFgEIDk5OR+v9Zms2Gz2UZlnEp1Gc972pVSKsEldLCJRCL86le/4q677gIgLy+PHTt2dN3vO7i7JC8vb0zGp45OkcgoZI5xu6ddKaUSW0IHm3vvvZdvfOMbXVWaT37yk/z2t7/tun/Hjh3MnDmTQl2MqWJUXt7d+bijQzYplZTI0hidJVJKqaNfwtbG77nnHoqLiwkGg+zatYuHH36YSZMmkZmZyfbt2wF44YUXuP7668d4pOpoUV4Oa9fKpqXsbJktys6Wz9eulfuVUkod3RKyYrN27Vq+9a1v9brN7XZz2WWX8cQTT/CTn/ykq0pz9dVXj8UQ1VEmEpFKjcfTeye20ymfl5XB+vUSdnQpjFJKHb1MhmEYYz2I0dLS0oLL5cLr9eJ0Osd6OGoU7dkDt9wiFZr+/tN7vbJ56bbbdGmMUkolmqFcv/V3UzUhHDztAIej//sdDrlfTztQSqmjmwYbNSH0OO2gX3ragVJKjQ8abNSEED3toKpKTjfoKXragdutpx0opdTRToONmhD0tAOllJoY9Me4mjD0tAOllBr/EnK7t1IjRU87UEqp8U2DjZpw9LQDpZQav/T3VKWUUkqNGxpslFJKKTVuaLBRSiml1LihwUYppZRS44YuHlZqGCIR3VmllFKJSIONUkNUXi4nhVdUyPlSdrt0NV61SnvhKKXUWNNgo9QQlJfD2rXg8UBBgRye6fdDaakc16CN/pRSamxp8VypGEUiUqnxeGDePHA6wWKRj/Pmye3r18vjlFJKjQ0NNkrFqLJSpp8KCsBk6n2fyQT5+VLRqawcm/EppZTSYKNUzHw+WVPjcPR/v8Mh9/t8ozsupZRS3TTYKBWj9HRZKOz393+/3y/3p6eP7riUUkp102CjVIwKC2X3U1UVGEbv+wwDqqtl4XBh4diMTymllAYbpWJmNsuW7uxsKCsDrxdCIflYVia3r1yp/WyUUmos6XbvUTYajd20edzIcbtlS3e0j01NjUw/LV4soUa3eiul1NjSYDOKRqOxmzaPG3luNxQXa3hUSqlEpMFmlIxGYzdtHjd6zGYoKhrrUSillOpLf8ccBaPR2E2bxymllFIabEbFaDR20+ZxSimllAabUTEajd20eZxSSimlwWZUjEZjN20ep5RSSmmwGRWj0dhNm8cppZRSGmxGxWg0dtPmcUoppRSYDKPv7/fjV0tLCy6XC6/Xi9PpHPXX76/HjNsd38Zuo/EaSiml1GgayvVb+9iMotFo7KbN45RSSk1kGmxG2Wg0dtPmcUoppSYq/T1eKaWUUuOGVmxGmR5QqZRSSo0cDTajSA+oVEoppUaWBptRogdUKqWUUiNPJ0FGgR5QqZRSSo0ODTajQA+oVEoppUaHBptRoAdUKqWUUqNDg80o0AMqlVJKqdGhwWYU6AGVSiml1OjQYDMK9IBKpZRSanTopXSUuN2ypXvRIti/H7Ztk4+LF+tWb6WUUipetI/NKHK7YdYsePZZmZYqKIDzzgOrdaxHppRSSo0PR2Ww8fv93HDDDbhcLvx+P3fffTc2m22sh3VYzz0nTfp27IDOTkhOhv/9X6nYfPazoz8ePd5BKaXUeHNUBpurrrqKVatWsWrVKh577DHWrFnDPffcM9bDGtRzz8FNN8m6msmTITUV2tpkjc1NN8ljRjPc6PEOSimlxiOTYfTdp5PYamtrmTVrFk1NTdjtdhobG5k+fTr19fWkH2a/dEtLCy6XC6/Xi9PpHKURy0LhT39aQszMmb2rIpEI7NoF8+fD889D0ihEzYGOd6iqkoXMuuZHKaVUIhnK9fuom3jYsGED2dnZ2O12AHJycrDZbGzcuPGQxwYCAVpaWnr9GQtvvSXTT5MnHzrVYzZDTg5s3y6PG2l6vINSSqnx7KgLNjU1NWRlZfW6LS0tjdra2kMee/vtt+Nyubr+FBQUjNYwe6mvlzU1qan93+9wyP319SM/Fj3eQSml1Hh21AUbk8nUVa2JCgaDJCcnH/LYNWvW4PV6u/5UVVWNyJgiEdizBzZvlo99qx1TpshC4ba2/r/e75f7p0wZkeH1osc7KKWUGs+OusXDeXl5eL3eXre1traSl5d3yGNtNtuI75aKZRHu8uUwe7assUlLO3SNTWOjrLFZvnxEhwr0Pt6hv2lKPd5BKaXU0eyoq9h84hOfoLq6mmAwCNA1BbV06dJRH0t0EW5pqSy6LS6Wj6Wlcnt5uTwuKUkW5LpcslC4Z+fhXbvk9muvHZ2Fw3q8g1JKqfHsqAs2ubm5nHXWWbzyyisAvPDCC1x99dWHTE+NtKEuwv3sZ+HOO+U+rxf27pWP8+fL7aO11VuPd1BKKTWeHXXbvQE8Hg8333wzRUVFHDhwgDvuuANrDO1747nde88euOUWCQL9PZXXK0cm3HYbFBV13x4Kye6n+npZU7N8+ehUavrqbwrN7ZZQo1u9lVJKJZKhXL+PujU2ANnZ2Tz00ENjOoZYFuHW1By6CDcpCU4+eeTHdzhut0ydaedhpZRS48lRGWwSwXhYhGs2964mKaWUUkc7/f18mHQRrlJKKZV4NNgMky7CVUoppRKPXnaPgNst27gXLZKFwtu2ycfFi/W8JaWUUmos6BqbI6SLcJVSSqnEocEmDnQRrlJKKZUYtK6glFJKqXFDg41SSimlxg0NNkoppZQaNzTYKKWUUmrc0GCjlFJKqXFDg41SSimlxg0NNkoppZQaNzTYKKWUUmrc0GCjlFJKqXFjQnUeNg4ew93S0jLGI1FKKaVUrKLX7eh1fDATKtj4fD4ACgoKxngkSimllBoqn8+Hy+Ua9DEmI5b4M05EIhFqa2tJT0/HZDKN2ThaWlooKCigqqoKp9M5ZuNIZPoeHZ6+R4en79Hh6Xt0ePoeHd5Iv0eGYeDz+cjLy8N8mFOmJ1TFxmw2k5+fP9bD6OJ0OvV/ksPQ9+jw9D06PH2PDk/fo8PT9+jwRvI9OlylJkoXDyullFJq3NBgo5RSSqlxQ4PNGLDZbHz/+9/HZrON9VASlr5Hh6fv0eHpe3R4+h4dnr5Hh5dI79GEWjyslFJKqfFNKzZKKaWUGjc02CillFJq3NBgo5RSSqlxQ4ONUkoppcYNDTajzO/3c/XVV7NmzRpWr15NIBAY6yGNub///e/Mnj2brKwsrr32WkKhEAD19fVcfvnl3HjjjfzP//xPTGeEjHfBYJBjjz2WDRs2APrvaSBvvPEGP/vZz1i/fj379+/X96mH8vJyvv71r/Pzn/+cq6++mvfffx/Qf0sAL774IsuWLWPPnj1dtw32vkzEn1H9vUcD/QyHMXqPDDWq/vu//9t45plnDMMwjEcffdT45je/OcYjGluNjY3GpZdeamzcuNF4/PHHDYfDYdx9992GYRjGKaecYrz33nuGYRjGrbfeatx3331jOdSE8KMf/chwOp3Gyy+/bBiG/nvqz//+7/8a3/nOd3rdpu9Tt+OPP96orq42DMMw9u7da5SUlBiGoe9RQ0ODsW7dOgMwdu/e3XX7YO/LRPsZ1d97NNjPcMMYm/dIg80oqqmpMex2u9He3m4YhvwjSUlJMVpaWsZ4ZGPnzTffNNra2ro+v/HGG41Pf/rTxptvvmkUFBR03b5x40YjPz/fiEQiYzHMhPD6668bv/3tb43p06cbL7/8sv576sfLL79snH766b3+nej71FtqaqpRXl5uGIa8F7m5ufoeHRQOh3tdtAd7Xybqz6i+79FAP8Oj943Fe6RTUaNow4YNZGdnY7fbAcjJycFms7Fx48YxHtnYWb58OSkpKV2fT5s2jfz8fF566SWmT5/edfvcuXOprq5m165dYzHMMef3+3nqqae47LLLum7Tf0+Huv7663G73Vx77bWcffbZvPnmm/o+9XHhhRfy1a9+FZ/Px+OPP87999+v79FBfQ9XHOx9mag/o/q+RwP9DAfG7D3SYDOKampqyMrK6nVbWloatbW1YzSixLNp0yauuOKKQ96rtLQ0gAn7Xt15552sWbOm123676m3rVu38v777/O1r32NBx54gNNOO40zzzxT36c+fvGLX5CcnMySJUtIS0vjggsu0PdoAIO9L/ozqn/Rn+Fw6Ps3Wu+RBptRZDKZupJ/VDAYJDk5eYxGlFh2795NZmYmixcvPuS9CgaDABPyvfrnP//JCSecwOTJk3vdrv+eetuyZQtZWVksXLgQgGuuuYZIJIJhGPo+9dDR0cHnP/95Lr30Ur7xjW/w4osv6r+lAQz2vujPqEP1/BkOh75/o/UeJY3os6te8vLy8Hq9vW5rbW0lLy9vjEaUOCKRCL/61a+46667AHmvduzY0XW/z+frun2i+dnPfkZpaWnX501NTZx33nl861vf0n9PPYRCIcLhcNfnKSkpzJkzh87OTn2fevjCF77An//8ZzIyMjCZTFxyySXce++9+h71Y7Cf2fozqre+P8NhDH+Oj+gKHtVLbW2t4XA4jEAgYBiGLExLTU3tWpg2kf3sZz8zampquj5/6623jJkzZ3Z9/vrrr/f6fCJpaGgwqqqquv7k5+cbTz75pLFnzx7999RDeXm5ARiNjY1dt51wwgnGI488ou/TQY2NjcbUqVO7Po9EIsbMmTONV199Vd+jg+ixMHawn9kT+WcUfXaOGcahP8MNY+x+jutU1CjKzc3lrLPO4pVXXgHghRde4Oqrrz6k1DnR3HPPPRQXFxMMBtm1axcPP/wwkyZNIjMzk+3btwPyXl1//fVjPNKxkZOTQ35+ftcfi8VCTk4O06dP139PPZSUlHD22Wfzl7/8BYDm5mZCoRBf+MIX9H06KCsrC7vdTk1NTddtkyZN4thjj9X3CLp6rEQ/DvYze9myZRPyZ1Tf9wj6/xm+Y8eOMXuP9HTvUebxeLj55pspKiriwIED3HHHHVit1rEe1phZu3Yt1113Xa/b3G43ZWVl7Ny5k5/85CcUFv7/9u40JqpzjQP4f4Aipo4MhWhRgk2qEVITIDIUNWpDsE0aSUaSKksVWRQcMUzRSiyV0fGDaNto1GBbUiAoi0awNUVUZEkbI7jjlghWwFEWNaIIioLz3A9ez3UArZhraYb/78vMvMs5z3khcx7e9xyOJ0QERqMRKpVqiCL99/jggw+Qk5ODTz75hL9Pfdy5cwdJSUnw9/eH2WzGkiVL4O3tzXF6QW1tLTIyMjB16lS0tbVh1qxZmD179rAfo87OTuzatQt6vR5GoxGJiYlwc3N75bgMt++ogcYoPz//pd/hwNCMERMbIiIishlciiIiIiKbwcSGiIiIbAYTGyIiIrIZTGyIiIjIZjCxISIiIpvBxIaIiIhsBhMbIiIishlMbIiIiMhmMLEhoiFz7Ngx+Pr6DnUYVhoaGhAXF4f4+PihDoWI3gATG6Jh6NSpU/j888+hVqthMBhgMBiQlJSEgIAAbN269R+Lw9vbG998880/tr/X8f7770OlUuHx48f96hobG2EwGKBSqTB37lzExcXBz88PJpMJA/0T98zMTERFRSE5ORmLFy/GypUrlSccX7hwAUuXLoVKpcLevXut+v3555/w8/ODwWDA9evX386BEtmqt/6YTSL6V8rMzJTx48dblXV3d0tubu4QRfT2HThwoN9TiQeSlpYmUVFRA9bV19cLAKmvrxcRkXPnzomDg4NkZGRYtVu2bJksXrxYent7lbKsrCyZOnWqdHV1KWVarVacnZ3l2rVrVv1TU1Pl6tWrr3lkRPQcZ2yIhikHB4d+ZSNGjMAXX3wxBNG8fTdu3IBer3+ttq96SF/fcfPx8cGUKVNw8OBBpezgwYPIzs7Gli1bYG9vr5RHR0fD3t4eRqNRKZs4cSI+/PBDhIWFoaenx2o/L/YlotfDxIaIFDk5OXByckJzczPmzZsHlUqF4uJinDx5Ep6enjh27Bjq6uoQHR2NhIQEGI1GjB49GnPmzMGdO3cAAD09PUhPT0dqaioCAgJQUlKC+/fvIy0tDVqtFj/99BNcXFxQW1uLtLQ0+Pv7AwDKysoQFBSEzMxM6PV6uLq6YtWqVaivr8esWbPw3nvv4ffff1diLS0thclkwmeffYbExERYLBb8+uuv0Gq1KC4uRkhICDQaDfbv3w8AyM/Px40bN7Bp0yYcOHAAnZ2diI2NxebNmxEcHIyCgoI3Hrd79+7Bzc1N+ZyVlYWAgABoNJp+bYODg5GTk6MsXTk6OmLfvn2oq6vDmjVr3jgGIvqvoZ4yIqKhkZ2dLWq1WlJSUiQlJUVCQkLkyy+/VOofPXokkydPlvXr18uPP/4ox48fFxGR3t5eWb58ufj6+sqJEyfk2rVr4uHhIbGxsSIismHDBvnjjz9ERKSoqEicnZ2lo6NDcnNzRa1WS3l5ufzyyy9y69Yt2b17t0yYMEFERB4+fCheXl4SFxcn7e3tUl1dLXZ2dpKZmSm9vb3yww8/yMcffywiIn/99ZckJCQo/caOHSu5ubny+PFjcXFxkRUrVsiDBw9k8+bNEhgYqBwTAGUpavv27RIdHS0iInv37pUpU6Yo7YxG40uXohoaGpSlKIvFIt999504OzvLhQsXlDbe3t4SHh4+YP+dO3cKAGlraxMRUfazf/9+UalUUlJSosTwOstmRGSt/1w0EQ0bo0ePRnp6OgDg6dOn2LJli1Ln5OSEjIwM6HQ6fP311wgMDAQA2Nvbw83NDT4+PtBqtQCAxMREpW9ubi5GjhyJ06dPo7OzE4GBgbh16xY8PDzg4uKCoKAgZR/jxo1T3o8cORJjxozBjBkzoNFo4O/vD4vFguDgYNjb28PX1xc7duwAABQWFuLu3bvKhc6zZ89GV1cXHB0doVarERoailGjRsHPzw87d+4c8NhDQ0MxZ84ctLe348yZM+js7BzU2G3btg2VlZV49913cf78eXh6elrVywAXEz8fvxdfn9PpdEhOTkZUVBRqa2sHFQsR/Q8TGyIC8OxEq9PprMqCgoLg6emJy5cvv7LvRx99hPv37wMAzGYzIiIi4O7ubtXGbDb3u3blVZ/7nvjt7OxgsViUbfn6+sJgMACA8tp3Gw4ODkqfvsaMGYNdu3ZBo9FgxowZg16KiomJQVBQEBYsWIC2tjarxMbb2xtNTU0D9mttbYW7uztcXV371aWnp6O6uhqRkZGYOXPmoOIhomd4jQ0RKSZOnIjr168rtyTn5eVhw4YNKC0tRXl5+Uv7PXnyBJMmTQIAuLu7o6ioSKlraWmB2Wz+v8bp7u6O4uJiq7ITJ04MahsmkwkPHz5EfHw8Ro0a9UZx6HQ6xMfHIywsDB0dHUr5woULcerUKdy+fbtfn8rKSsTGxg64PQcHBxQWFuLixYv4+eef3ygmouGOiQ3RMGWxWPotl1gsFmzduhVqtRo3b95EQ0MD5s2bB5PJBL1ej+7ubqVtS0uL8r6qqkq54yg8PBwpKSnYtm0bKioqsH79eowfPx7As+WuF4mIVQx9P/f1vG7+/Pk4e/YsIiIiUFFRAZPJhN7e3gGP68X377zzDtrb23HlyhWcPXsWt2/fRk9PD6qqqvDo0SM0NDT8bRzP9/P8WL7//ntoNBrExMQofXQ6HcLCwpCUlKS0B4A9e/agu7sbqampStmLYwoAHh4eyMvLGzApIqK/x8SGaBg6efIkCgoK0NraiuXLl2PVqlX46quvMH36dNjZ2aGtrQ2hoaHKnT4TJkxAXV0dFi1apJxwm5ubsXHjRmzcuBHOzs5YsmQJAGDt2rWIjIyE0WjE6tWrsWLFCnR0dCAvLw/Nzc3IysoCADx48AD79u1Da2srDh8+jJqaGly6dAmlpaVobm5WZix2796NmzdvKvGWlJTAy8sL+fn5OH78OMLDw+Hq6orp06fj0KFDaGlpQVFREZqamvDbb7+htbUVhw4dAvBsJmX+/Pm4d+8eEhISUFhYiODgYEybNg1PnjzB0aNHYTabUV5ejurq6n7XujQ2NmL79u0Ant35dPXqVTg6OmLPnj04cuQIQkJCUFVVBeDZHWZarRaRkZFYuXIl9Ho9zp07h7KyMjg5OeHp06coKCjA4cOHkZ2dja6uLmU/n376Kb799tu39NMnsm0qedWfR0REA1i3bh0aGxuRk5Mz1KEQEVnhjA0RDdrfLRkREQ0VJjZENCi1tbUoKytDTU0NampqhjocIiIrXIoiIiIim8EZGyIiIrIZTGyIiIjIZjCxISIiIpvBxIaIiIhsBhMbIiIishlMbIiIiMhmMLEhIiIim8HEhoiIiGzGfwBs17rSeoIaFAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -323,12 +328,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental RON')\n", - "plt.ylabel('Predicted RON')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental RON\")\n", + "plt.ylabel(\"Predicted RON\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -341,27 +346,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.323033809661865\n", - "Test R2: 0.8880797305442842\n" + "Test MAE: 6.524505764830346\n", + "Test R2: 0.8509000273173078\n" ] } ], "source": [ "from sklearn.metrics import mean_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {mean_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {mean_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -380,7 +379,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/predict_cn.ipynb b/examples/predict_cn.ipynb index 124da0a..4597527 100644 --- a/examples/predict_cn.ipynb +++ b/examples/predict_cn.ipynb @@ -24,6 +24,7 @@ "from graphchem.datasets import load_cn\n", "from sklearn.model_selection import train_test_split\n", "\n", + "\n", "# load cetane number data\n", "smiles, cn = load_cn()\n", "\n", @@ -31,11 +32,11 @@ "smiles_train, smiles_test, cn_train, cn_test = train_test_split(smiles, cn, test_size=0.2, random_state=42)\n", "\n", "print(len(smiles_train), len(smiles_test), type(smiles))\n", - "print(len(cn_train), len(cn_test), type(cn), cn.shape, '\\n')\n", + "print(len(cn_train), len(cn_test), type(cn), cn.shape, \"\\n\")\n", "\n", "for i in range(5):\n", "\n", - " print(f'{smiles[i]}\\t{cn[i]}')" + " print(f\"{smiles[i]}\\t{cn[i]}\")" ] }, { @@ -56,20 +57,13 @@ "\n", "368 92\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem-2.1.0-py3.11.egg\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] } ], "source": [ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "# construct encoder using training data\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", @@ -77,7 +71,7 @@ "encoding_train = encoder.encode_many(smiles_train)\n", "encoding_test = encoder.encode_many(smiles_test)\n", "\n", - "print('\\n', encoding_train[0], '\\n')\n", + "print(\"\\n\", encoding_train[0], \"\\n\")\n", "\n", "# construct graphs using encoded data\n", "graphs_train = [MoleculeGraph(e[0], e[1], e[2], cn_train[i]) for i, e in enumerate(encoding_train)]\n", @@ -99,86 +93,86 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: 49.57554535243822\n", - "5: 25.19924847976021\n", - "10: 27.242681524027947\n", - "15: 24.52878072987432\n", - "20: 18.552562091661535\n", - "25: 17.024141643358313\n", - "30: 16.06946746162746\n", - "35: 14.341543156167734\n", - "40: 16.814889285875402\n", - "45: 11.754811514978824\n", - "50: 10.715770597043244\n", - "55: 10.235421823418658\n", - "60: 10.56846226816592\n", - "65: 8.232471745947134\n", - "70: 8.92014885985333\n", - "75: 7.110177973042363\n", - "80: 7.351929985958597\n", - "85: 6.856772884078648\n", - "90: 7.353273961855018\n", - "95: 5.75025140720865\n", - "100: 7.883484591608462\n", - "105: 5.373804076858189\n", - "110: 5.6871991675833\n", - "115: 5.150080183277959\n", - "120: 5.2621465869571855\n", - "125: 5.565489945204361\n", - "130: 5.611542722453242\n", - "135: 5.318315785864125\n", - "140: 5.104230870371279\n", - "145: 4.736013324364372\n", - "150: 3.895174337470013\n", - "155: 4.047365608422653\n", - "160: 6.471494809440944\n", - "165: 4.1432661854702495\n", - "170: 3.526315207066743\n", - "175: 3.0083033805308133\n", - "180: 3.7389309147129888\n", - "185: 3.2366091686746348\n", - "190: 4.018196401388749\n", - "195: 3.052056885283926\n", - "200: 5.32833805291549\n", - "205: 3.747665928757709\n", - "210: 2.935333391894465\n", - "215: 2.9285237374513047\n", - "220: 2.4842829056408093\n", - "225: 3.2523732392684273\n", - "230: 3.1595141006552656\n", - "235: 2.9586927605711897\n", - "240: 2.3214061247265856\n", - "245: 2.4827929372372837\n", - "250: 2.578958938951078\n", - "255: 2.9904658068781313\n", - "260: 2.57642780697864\n", - "265: 2.5940834024678106\n", - "270: 2.117831789928934\n", - "275: 2.538074871768122\n", - "280: 2.655972631081291\n", - "285: 1.8350979919018953\n", - "290: 1.996585716371951\n", - "295: 1.781811158294263\n", - "300: 2.2096335162287173\n", - "305: 1.6511712761028954\n", - "310: 3.70668769919354\n", - "315: 1.913068359312804\n", - "320: 1.654385761074398\n", - "325: 1.8202240881712541\n", - "330: 2.1663010431372602\n", - "335: 1.5489913678687552\n", - "340: 1.3393834634967472\n", - "345: 1.8181434390337572\n", - "350: 1.7282072616660076\n", - "355: 2.1539330339950062\n", - "360: 1.5165145695209503\n", - "365: 1.0939296807931818\n", - "370: 1.7570706761401633\n", - "375: 1.0603702573672584\n", - "380: 1.023310847904371\n", - "385: 1.6046273967494136\n", - "390: 1.7054815085037895\n", - "395: 0.9954941700334135\n" + "0: 45.48255091128142\n", + "5: 24.12971305847168\n", + "10: 21.691882506660793\n", + "15: 20.83861311622288\n", + "20: 18.170073260431703\n", + "25: 15.088495907576188\n", + "30: 13.174198565275773\n", + "35: 12.11010735967885\n", + "40: 15.740696222885795\n", + "45: 12.118018917415453\n", + "50: 12.115683130595995\n", + "55: 10.430063465367192\n", + "60: 8.476993405300638\n", + "65: 7.219965395720108\n", + "70: 8.835112571716309\n", + "75: 12.430914277615754\n", + "80: 7.068413319795028\n", + "85: 7.056585104569145\n", + "90: 6.93636095005533\n", + "95: 6.518541667772376\n", + "100: 6.021286135134489\n", + "105: 7.491281250248784\n", + "110: 7.9189115607220195\n", + "115: 8.761742115020752\n", + "120: 4.991386151832083\n", + "125: 5.570005328758903\n", + "130: 7.095310231913691\n", + "135: 4.012576180955638\n", + "140: 5.218108664388242\n", + "145: 4.669180082238239\n", + "150: 4.541343009990195\n", + "155: 4.254670656245688\n", + "160: 4.720760599426601\n", + "165: 4.597779818203138\n", + "170: 5.328923090644505\n", + "175: 3.4664850079494975\n", + "180: 4.370316774948783\n", + "185: 3.4234728087549624\n", + "190: 3.703721601030101\n", + "195: 5.217348591141079\n", + "200: 3.487929053928541\n", + "205: 3.6500425390575244\n", + "210: 3.560427748638651\n", + "215: 3.2958570148633872\n", + "220: 3.093842029571533\n", + "225: 3.307894201382347\n", + "230: 2.900452173274496\n", + "235: 3.1003369870393174\n", + "240: 4.3223241308461064\n", + "245: 5.84370291751364\n", + "250: 3.3234128666960676\n", + "255: 3.170888473158297\n", + "260: 2.787338850290879\n", + "265: 2.9189993765043174\n", + "270: 3.1556410530339116\n", + "275: 2.4105438538219617\n", + "280: 2.9455686807632446\n", + "285: 2.485566998305528\n", + "290: 2.0926729958990347\n", + "295: 3.4880915102751358\n", + "300: 2.1835390769917034\n", + "305: 3.222949427107106\n", + "310: 1.9737049082051152\n", + "315: 2.097203923308331\n", + "320: 2.3308406549951304\n", + "325: 2.249627779359403\n", + "330: 1.9815904990486477\n", + "335: 2.9114266426666924\n", + "340: 1.6598594603331194\n", + "345: 2.054753903461539\n", + "350: 1.7982034449991973\n", + "355: 2.3571781749310703\n", + "360: 2.7603408694267273\n", + "365: 2.041544918132865\n", + "370: 2.1634433049222697\n", + "375: 1.7984742314919182\n", + "380: 1.4898298965848011\n", + "385: 1.479749039463375\n", + "390: 1.4765300063983253\n", + "395: 1.3474621604318204\n" ] }, { @@ -186,7 +180,7 @@ "text/plain": [ "MoleculeGCN(\n", " (emb_atom): Embedding(42, 128)\n", - " (emb_bond): Embedding(34, 128)\n", + " (emb_bond): Embedding(29, 128)\n", " (atom_conv): GeneralConv(128, 128)\n", " (bond_conv): EdgeConv(nn=Sequential(\n", " (0): Linear(in_features=256, out_features=128, bias=True)\n", @@ -213,6 +207,7 @@ "import torch.nn.functional as F\n", "from torch_geometric.loader import DataLoader\n", "\n", + "\n", "# prepare training set for training\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", @@ -228,7 +223,7 @@ " n_messages=3, # number of message-passing ops to perform (>= 1)\n", " n_readout=3, # number of post-graph-operation feed-forward layers (>= 1)\n", " readout_dim=128, # number of neurons in each readout layer (>= 1)\n", - " dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", + " p_dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", ")\n", "\n", "# construct torch optimizer\n", @@ -244,7 +239,7 @@ "for epoch in range(400):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -271,7 +266,7 @@ " test_losses.append(test_loss)\n", "\n", " if epoch % 5 == 0:\n", - " print(f'{epoch}: {train_loss}')\n", + " print(f\"{epoch}: {train_loss}\")\n", "\n", "# done training\n", "model.eval()" @@ -293,7 +288,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -305,15 +300,16 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", "plt.show()" ] }, @@ -324,7 +320,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -340,12 +336,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental CN')\n", - "plt.ylabel('Predicted CN')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental CN\")\n", + "plt.ylabel(\"Predicted CN\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -358,32 +354,26 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.428378105163574\n", - "Test R2: 0.8749652639665292\n" + "Test MAE: 4.828453063964844\n", + "Test R2: 0.8844475017075569\n" ] } ], "source": [ "from sklearn.metrics import median_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {median_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {median_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3.6.13 ('graphchem')", + "display_name": "graphchem", "language": "python", "name": "python3" }, @@ -397,14 +387,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "7b712ff9cd32652e56b63efe35a56ffcbb9145d3b2abc83659e2bd8c0cb9ba4d" - } - } + "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 diff --git a/examples/predict_lhv.ipynb b/examples/predict_lhv.ipynb index eed36f9..4b87fc6 100644 --- a/examples/predict_lhv.ipynb +++ b/examples/predict_lhv.ipynb @@ -24,6 +24,7 @@ "from graphchem.datasets import load_lhv\n", "from sklearn.model_selection import train_test_split\n", "\n", + "\n", "# load LHV data\n", "smiles, lhv = load_lhv()\n", "\n", @@ -31,11 +32,11 @@ "smiles_train, smiles_test, lhv_train, lhv_test = train_test_split(smiles, lhv, test_size=0.2, random_state=42)\n", "\n", "print(len(smiles_train), len(smiles_test), type(smiles))\n", - "print(len(lhv_train), len(lhv_test), type(lhv), lhv.shape, '\\n')\n", + "print(len(lhv_train), len(lhv_test), type(lhv), lhv.shape, \"\\n\")\n", "\n", "for i in range(5):\n", "\n", - " print(f'{smiles[i]}\\t{lhv[i]}')" + " print(f\"{smiles[i]}\\t{lhv[i]}\")" ] }, { @@ -53,20 +54,13 @@ "\n", "310 78\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem-2.1.0-py3.11.egg\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] } ], "source": [ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "# construct encoder using training data\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", @@ -74,7 +68,7 @@ "encoding_train = encoder.encode_many(smiles_train)\n", "encoding_test = encoder.encode_many(smiles_test)\n", "\n", - "print('\\n', encoding_train[0], '\\n')\n", + "print(\"\\n\", encoding_train[0], \"\\n\")\n", "\n", "# construct graphs using encoded data\n", "graphs_train = [MoleculeGraph(e[0], e[1], e[2], lhv_train[i]) for i, e in enumerate(encoding_train)]\n", @@ -96,86 +90,86 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: 26.09936833535471\n", - "5: 6.545895836430211\n", - "10: 2.851555904265373\n", - "15: 1.4007623980122228\n", - "20: 1.045286343174596\n", - "25: 0.9547821360249673\n", - "30: 0.3742928685680513\n", - "35: 0.3164090068109574\n", - "40: 0.4506806981179022\n", - "45: 0.526952322067753\n", - "50: 0.41907658346237675\n", - "55: 0.39961191954151276\n", - "60: 0.15864104513199098\n", - "65: 0.2903070022982936\n", - "70: 0.12326773289711244\n", - "75: 0.1307665632617089\n", - "80: 0.15309021184521338\n", - "85: 0.0940049579066615\n", - "90: 0.09767268367352024\n", - "95: 0.1813660035210271\n", - "100: 0.15303031206130982\n", - "105: 0.06872039177725392\n", - "110: 0.23819863161733074\n", - "115: 0.17259144263882792\n", - "120: 0.08698000398374373\n", - "125: 0.04699701008296782\n", - "130: 0.07663023664105323\n", - "135: 0.06875550304689715\n", - "140: 0.08945667195704675\n", - 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"370: 0.036151562871471525\n", + "375: 0.05763447875938108\n", + "380: 0.06299875907359585\n", + "385: 0.03618240954895174\n", + "390: 0.07900455017243663\n", + "395: 0.08292426101623043\n" ] }, { @@ -183,7 +177,7 @@ "text/plain": [ "MoleculeGCN(\n", " (emb_atom): Embedding(63, 128)\n", - " (emb_bond): Embedding(55, 128)\n", + " (emb_bond): Embedding(54, 128)\n", " (atom_conv): GeneralConv(128, 128)\n", " (bond_conv): EdgeConv(nn=Sequential(\n", " (0): Linear(in_features=256, out_features=128, bias=True)\n", @@ -210,6 +204,7 @@ "import torch.nn.functional as F\n", "from torch_geometric.loader import DataLoader\n", "\n", + "\n", "# prepare training set for training\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", @@ -225,7 +220,7 @@ " n_messages=3, # number of message-passing ops to perform (>= 1)\n", " n_readout=3, # number of post-graph-operation feed-forward layers (>= 1)\n", " readout_dim=128, # number of neurons in each readout layer (>= 1)\n", - " dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", + " p_dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", ")\n", "\n", "# construct torch optimizer\n", @@ -241,7 +236,7 @@ "for epoch in range(400):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -268,7 +263,7 @@ " test_losses.append(test_loss)\n", "\n", " if epoch % 5 == 0:\n", - " print(f'{epoch}: {train_loss}')\n", + " print(f\"{epoch}: {train_loss}\")\n", "\n", "# done training\n", "model.eval()" @@ -290,7 +285,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -302,15 +297,16 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", "plt.show()" ] }, @@ -321,7 +317,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -337,12 +333,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental LHV (MJ/kg)')\n", - "plt.ylabel('Predicted LHV (MJ/kg)')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental LHV (MJ/kg)\")\n", + "plt.ylabel(\"Predicted LHV (MJ/kg)\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -355,27 +351,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 0.532928466796875\n", - "Test R2: 0.9719837758486892\n" + "Test MAE: 0.5752601623535156\n", + "Test R2: 0.910885327344299\n" ] } ], "source": [ "from sklearn.metrics import median_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {median_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {median_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -394,7 +384,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/predict_mon.ipynb b/examples/predict_mon.ipynb index 2f1afcf..0e9a448 100644 --- a/examples/predict_mon.ipynb +++ b/examples/predict_mon.ipynb @@ -24,6 +24,7 @@ "from graphchem.datasets import load_mon\n", "from sklearn.model_selection import train_test_split\n", "\n", + "\n", "# load MON data\n", "smiles, mon = load_mon()\n", "\n", @@ -31,11 +32,11 @@ "smiles_train, smiles_test, mon_train, mon_test = train_test_split(smiles, mon, test_size=0.2, random_state=42)\n", "\n", "print(len(smiles_train), len(smiles_test), type(smiles))\n", - "print(len(mon_train), len(mon_test), type(mon), mon.shape, '\\n')\n", + "print(len(mon_train), len(mon_test), type(mon), mon.shape, \"\\n\")\n", "\n", "for i in range(5):\n", "\n", - " print(f'{smiles[i]}\\t{mon[i]}')" + " print(f\"{smiles[i]}\\t{mon[i]}\")" ] }, { @@ -53,20 +54,13 @@ "\n", "246 62\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem-2.1.0-py3.11.egg\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] } ], "source": [ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "# construct encoder using training data\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", @@ -74,7 +68,7 @@ "encoding_train = encoder.encode_many(smiles_train)\n", "encoding_test = encoder.encode_many(smiles_test)\n", "\n", - "print('\\n', encoding_train[0], '\\n')\n", + "print(\"\\n\", encoding_train[0], \"\\n\")\n", "\n", "# construct graphs using encoded data\n", "graphs_train = [MoleculeGraph(e[0], e[1], e[2], mon_train[i]) for i, e in enumerate(encoding_train)]\n", @@ -96,86 +90,86 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: 180.32071270206112\n", - "5: 44.80305642228785\n", - "10: 37.49040129126572\n", - "15: 29.7110879789523\n", - "20: 35.630869485498444\n", - "25: 26.029433583825583\n", - "30: 22.89028546092956\n", - "35: 21.400253478104506\n", - "40: 17.54082737124063\n", - "45: 20.98001880180545\n", - "50: 13.188910786698504\n", - "55: 11.839052650017466\n", - "60: 12.247812751832047\n", - "65: 9.191805599181633\n", - "70: 10.078719425976761\n", - "75: 13.465394431013403\n", - "80: 8.881324550969813\n", - "85: 10.263081310241203\n", - "90: 6.613140586915055\n", - "95: 5.881887180049245\n", - "100: 6.869870689826283\n", - "105: 9.211403870001071\n", - "110: 5.956209496753972\n", - "115: 6.957728502227039\n", - "120: 4.844930896914102\n", - "125: 7.17860192399684\n", - "130: 6.414997372200818\n", - "135: 4.1823702013589505\n", - "140: 4.97351754196291\n", - "145: 4.5911256898709425\n", - "150: 5.190685024106406\n", - "155: 3.9237324474303703\n", - "160: 4.278482499161387\n", - "165: 2.895515569826452\n", - "170: 4.144749308020119\n", - "175: 2.260328374257902\n", - "180: 3.179225557218722\n", - "185: 3.6314331768004875\n", - "190: 2.9624404907226562\n", - "195: 7.316111471594834\n", - "200: 4.171598186337851\n", - "205: 2.528739146100796\n", - "210: 3.212485460731072\n", - "215: 2.8826907049349653\n", - "220: 2.165668235561712\n", - "225: 5.724862176228345\n", - "230: 2.5135661644664236\n", - "235: 3.017758477994097\n", - "240: 1.6551100994513286\n", - "245: 1.5360152488801537\n", - "250: 1.5479250729568605\n", - "255: 1.7214179000234215\n", - "260: 2.180850862487545\n", - "265: 2.2562073381935677\n", - "270: 3.7339694499969482\n", - "275: 2.060468921816446\n", - "280: 1.7724115867924883\n", - "285: 1.4361960878217124\n", - "290: 1.4122294953198937\n", - "295: 1.6326726936712497\n", - "300: 0.9660756975654664\n", - "305: 1.0481295391796082\n", - "310: 2.0698541586961205\n", - "315: 2.201678272185287\n", - "320: 3.205120171957869\n", - "325: 1.382062532068268\n", - "330: 3.676889334267717\n", - "335: 2.150407628315251\n", - "340: 1.9884679840832222\n", - "345: 1.1659112034774408\n", - "350: 2.569074231434644\n", - "355: 1.4523772107876414\n", - "360: 1.0875173933137723\n", - "365: 1.9585967742330659\n", - "370: 0.8291697385834484\n", - "375: 1.0195645355596774\n", - "380: 0.8582279546474053\n", - "385: 1.7606388689056645\n", - "390: 1.07080447189207\n", - "395: 0.7256398443284073\n" + "0: 151.20433503437818\n", + "5: 35.13049558313882\n", + "10: 27.143416738122458\n", + "15: 42.71362565203411\n", + "20: 26.2057907600713\n", + "25: 23.34175885208254\n", + "30: 38.96219870714637\n", + "35: 17.10893804658719\n", + "40: 18.653206615913206\n", + "45: 28.50565356743045\n", + "50: 11.533691623346593\n", + "55: 11.199008724553797\n", + "60: 13.35597805860566\n", + "65: 7.130166356156512\n", + "70: 8.229130582111639\n", + "75: 6.953425260094123\n", + "80: 7.691548107116203\n", + "85: 6.31917299100054\n", + "90: 7.3836471278493\n", + "95: 6.194722679572377\n", + "100: 10.176945911190375\n", + "105: 9.009554312481143\n", + "110: 6.815917976503449\n", + "115: 4.450276975709248\n", + "120: 6.1216814692427475\n", + "125: 5.166240622357624\n", + "130: 3.8285986427369156\n", + "135: 2.943356312387358\n", + "140: 6.721435794985391\n", + "145: 3.5099363327026367\n", + "150: 3.5661863854260947\n", + "155: 2.2013820206246724\n", + "160: 2.705324556769394\n", + "165: 5.519323550588716\n", + "170: 2.4304807709484564\n", + "175: 3.1547675714260195\n", + "180: 2.6983093750186082\n", + "185: 1.6038423127275172\n", + "190: 1.6972255357881871\n", + "195: 2.4735430353056125\n", + "200: 2.3068761980630517\n", + "205: 2.102024721905468\n", + "210: 1.6169766061674289\n", + "215: 2.0684811972021087\n", + "220: 2.1629398082329976\n", + "225: 2.234312623496947\n", + "230: 1.590574245142743\n", + "235: 1.206056505683961\n", + "240: 1.348552420856507\n", + "245: 1.324899615311041\n", + "250: 1.4368755371589972\n", + "255: 1.4009209648380434\n", + "260: 3.4556972340839667\n", + "265: 1.8301960394634464\n", + "270: 1.3865687498232213\n", + "275: 1.69990585586889\n", + "280: 2.5609489650261112\n", + "285: 1.2636997021310699\n", + "290: 1.6625328529171828\n", + "295: 1.4100029216549261\n", + "300: 0.8062672082001601\n", + "305: 4.193663442037939\n", + "310: 1.2651016479585229\n", + "315: 1.1451285525066097\n", + "320: 0.6999763725249748\n", + "325: 0.5345239658665851\n", + "330: 1.1020880850349986\n", + "335: 0.7037105356774679\n", + "340: 0.576764136795106\n", + "345: 1.0845883125212135\n", + "350: 0.7829269994565142\n", + "355: 0.6819117214621567\n", + "360: 0.8442331484662808\n", + "365: 1.798054850198389\n", + "370: 1.1032669505452721\n", + "375: 1.4951228785320996\n", + "380: 0.9840347611807226\n", + "385: 0.852560807049759\n", + "390: 0.6844104693187931\n", + "395: 1.9081519367249031\n" ] }, { @@ -183,7 +177,7 @@ "text/plain": [ "MoleculeGCN(\n", " (emb_atom): Embedding(45, 128)\n", - " (emb_bond): Embedding(33, 128)\n", + " (emb_bond): Embedding(32, 128)\n", " (atom_conv): GeneralConv(128, 128)\n", " (bond_conv): EdgeConv(nn=Sequential(\n", " (0): Linear(in_features=256, out_features=128, bias=True)\n", @@ -210,6 +204,7 @@ "import torch.nn.functional as F\n", "from torch_geometric.loader import DataLoader\n", "\n", + "\n", "# prepare training set for training\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", @@ -225,7 +220,7 @@ " n_messages=3, # number of message-passing ops to perform (>= 1)\n", " n_readout=3, # number of post-graph-operation feed-forward layers (>= 1)\n", " readout_dim=128, # number of neurons in each readout layer (>= 1)\n", - " dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", + " p_dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", ")\n", "\n", "# construct torch optimizer\n", @@ -268,7 +263,7 @@ " test_losses.append(test_loss)\n", "\n", " if epoch % 5 == 0:\n", - " print(f'{epoch}: {train_loss}')\n", + " print(f\"{epoch}: {train_loss}\")\n", "\n", "# done training\n", "model.eval()" @@ -290,7 +285,7 @@ }, { 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", 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", "text/plain": [ "
" ] @@ -302,15 +297,16 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", "plt.show()" ] }, @@ -321,7 +317,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -337,12 +333,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental MON')\n", - "plt.ylabel('Predicted MON')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental MON\")\n", + "plt.ylabel(\"Predicted MON\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -355,27 +351,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.2223358154296875\n", - "Test R2: 0.659589097798132\n" + "Test MAE: 6.958827972412109\n", + "Test R2: 0.6110250148333667\n" ] } ], "source": [ "from sklearn.metrics import median_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {median_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {median_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -394,7 +384,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/predict_ron.ipynb b/examples/predict_ron.ipynb index e74c9b8..dff3329 100644 --- a/examples/predict_ron.ipynb +++ b/examples/predict_ron.ipynb @@ -24,6 +24,7 @@ "from graphchem.datasets import load_ron\n", "from sklearn.model_selection import train_test_split\n", "\n", + "\n", "# load RON data\n", "smiles, ron = load_ron()\n", "\n", @@ -31,11 +32,11 @@ "smiles_train, smiles_test, ron_train, ron_test = train_test_split(smiles, ron, test_size=0.2, random_state=42)\n", "\n", "print(len(smiles_train), len(smiles_test), type(smiles))\n", - "print(len(ron_train), len(ron_test), type(ron), ron.shape, '\\n')\n", + "print(len(ron_train), len(ron_test), type(ron), ron.shape, \"\\n\")\n", "\n", "for i in range(5):\n", "\n", - " print(f'{smiles[i]}\\t{ron[i]}')" + " print(f\"{smiles[i]}\\t{ron[i]}\")" ] }, { @@ -53,20 +54,13 @@ "\n", "246 62\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem-2.1.0-py3.11.egg\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] } ], "source": [ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "# construct encoder using training data\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", @@ -74,7 +68,7 @@ "encoding_train = encoder.encode_many(smiles_train)\n", "encoding_test = encoder.encode_many(smiles_test)\n", "\n", - "print('\\n', encoding_train[0], '\\n')\n", + "print(\"\\n\", encoding_train[0], \"\\n\")\n", "\n", "# construct graphs using encoded data\n", "graphs_train = [MoleculeGraph(e[0], e[1], e[2], ron_train[i]) for i, e in enumerate(encoding_train)]\n", @@ -96,86 +90,86 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: 179.20905682323425\n", - "5: 47.42880348267594\n", - "10: 37.33869251778455\n", - "15: 34.4677535886687\n", - "20: 36.96308954750619\n", - "25: 24.63335958341273\n", - "30: 36.10259491835183\n", - "35: 25.577006394301005\n", - "40: 16.082689424840414\n", - "45: 14.177709005712494\n", - "50: 20.979057839246302\n", - "55: 18.45824395156488\n", - "60: 10.975152364591272\n", - "65: 15.633901053327856\n", - "70: 10.963673196187834\n", - "75: 8.698282660507575\n", - "80: 6.01106751449709\n", - "85: 10.97610490690402\n", - "90: 7.729772335145531\n", - "95: 11.450505155857986\n", - "100: 7.4117520727762365\n", - "105: 5.186962057904499\n", - "110: 7.936537362695709\n", - "115: 11.179709876455911\n", - "120: 8.350231628107831\n", - "125: 3.811022983333929\n", - "130: 3.875870561212059\n", - "135: 4.90076959811575\n", - "140: 5.465586243606195\n", - "145: 4.88633579161109\n", - "150: 2.8939322417344506\n", - "155: 3.925412410643043\n", - "160: 3.314504421823393\n", - "165: 4.1491592376212765\n", - "170: 2.1254176860902367\n", - "175: 4.562057254760246\n", - "180: 4.654210827214931\n", - "185: 2.3847403410004406\n", - "190: 4.250825060092337\n", - "195: 2.2304176528279376\n", - "200: 3.134421643202867\n", - "205: 3.6092328715130564\n", - "210: 3.0634376246754718\n", - "215: 2.479766302961644\n", - "220: 2.6914259980364545\n", - "225: 2.1703429687313918\n", - "230: 3.1839900985965883\n", - "235: 2.6413223258848113\n", - "240: 2.3269640139447962\n", - "245: 1.6997379074251748\n", - "250: 3.4092047621564165\n", - "255: 3.6085104748485533\n", - "260: 3.3300327169216746\n", - "265: 1.6497811767143933\n", - "270: 2.795744481125498\n", - "275: 2.8014432821816544\n", - "280: 1.7889330639102594\n", - "285: 3.131376243219143\n", - "290: 2.1714619272123508\n", - "295: 1.8073246944241408\n", - "300: 1.948198469673715\n", - "305: 2.751487018616219\n", - "310: 2.1826873756036527\n", - "315: 3.5718204994511797\n", - "320: 2.127437033304354\n", - "325: 1.1316297054290771\n", - "330: 3.4864795576266157\n", - "335: 1.286911776395348\n", - "340: 1.7549997267684316\n", - "345: 1.273822600279397\n", - "350: 1.8011415489320832\n", - "355: 4.6704840660095215\n", - "360: 1.5428491888976679\n", - "365: 2.053589111421166\n", - "370: 1.351487294445193\n", - "375: 1.6349181780001012\n", - "380: 1.1441744963328044\n", - "385: 1.3248766340860507\n", - "390: 0.9179530318190412\n", - "395: 0.9939506693584162\n" + "0: 175.71514954605723\n", + "5: 61.8490244547526\n", + "10: 44.49844583650915\n", + "15: 53.276211498229486\n", + "20: 34.00811655928449\n", + "25: 38.04908411289618\n", + "30: 22.18044067010647\n", + "35: 26.53273159120141\n", + "40: 32.055257161458336\n", + "45: 18.979082650285427\n", + "50: 15.5240222961922\n", + "55: 35.50328553982867\n", + "60: 13.34881818197607\n", + "65: 10.646614291803624\n", + "70: 10.426652923832094\n", + "75: 10.767795531730341\n", + "80: 12.2146109914392\n", + "85: 8.696504042400576\n", + "90: 12.103760789080363\n", + "95: 12.088107582030258\n", + "100: 8.200205050832857\n", + "105: 5.152597272299169\n", + "110: 4.564228918494248\n", + "115: 5.2222380289217325\n", + "120: 9.167281608271406\n", + "125: 6.212573888825207\n", + "130: 4.903275807698567\n", + "135: 5.069726688105885\n", + "140: 3.534015950148668\n", + "145: 3.5542993002790744\n", + "150: 3.5301251605274233\n", + "155: 4.540775516168858\n", + "160: 8.090586204838946\n", + "165: 3.6052522426698266\n", + "170: 3.0618908269618585\n", + "175: 3.3773361144027088\n", + "180: 4.421454918093797\n", + "185: 2.6744833457760695\n", + "190: 3.097078315610808\n", + "195: 2.371688897047586\n", + "200: 2.530230599690259\n", + "205: 7.114695448216384\n", + "210: 2.860130108468901\n", + "215: 2.8025816553007297\n", + "220: 1.7946735979095707\n", + "225: 2.3408045768737793\n", + "230: 2.084617804705612\n", + "235: 2.004291007189247\n", + "240: 2.1125312704380934\n", + "245: 1.678413313578784\n", + "250: 2.5681047749713186\n", + "255: 1.606080318854107\n", + "260: 2.0743477674034554\n", + "265: 3.2798806903808098\n", + "270: 1.6283806513964645\n", + "275: 2.2941823974857485\n", + "280: 2.5910272966555463\n", + "285: 1.082999407760496\n", + "290: 2.6021127390667673\n", + "295: 1.134457607579425\n", + "300: 1.3555143790516426\n", + "305: 3.164633277955094\n", + "310: 5.206766221581436\n", + "315: 2.662559540291143\n", + "320: 1.5684817515737641\n", + "325: 1.2055465225281754\n", + "330: 2.1737859578636605\n", + "335: 2.1233563907747346\n", + "340: 1.976990841268524\n", + "345: 1.1365623299668475\n", + "350: 1.1867004448805398\n", + "355: 1.2837211077775412\n", + "360: 1.1254122354150788\n", + "365: 1.5521876172321598\n", + "370: 1.552501957590987\n", + "375: 1.6294487705075644\n", + "380: 1.2648175324850934\n", + "385: 1.0585883962429636\n", + "390: 2.5732782914386534\n", + "395: 0.8412826894744625\n" ] }, { @@ -183,7 +177,7 @@ "text/plain": [ "MoleculeGCN(\n", " (emb_atom): Embedding(45, 128)\n", - " (emb_bond): Embedding(33, 128)\n", + " (emb_bond): Embedding(32, 128)\n", " (atom_conv): GeneralConv(128, 128)\n", " (bond_conv): EdgeConv(nn=Sequential(\n", " (0): Linear(in_features=256, out_features=128, bias=True)\n", @@ -210,6 +204,7 @@ "import torch.nn.functional as F\n", "from torch_geometric.loader import DataLoader\n", "\n", + "\n", "# prepare training set for training\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", @@ -225,7 +220,7 @@ " n_messages=3, # number of message-passing ops to perform (>= 1)\n", " n_readout=3, # number of post-graph-operation feed-forward layers (>= 1)\n", " readout_dim=128, # number of neurons in each readout layer (>= 1)\n", - " dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", + " p_dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", ")\n", "\n", "# construct torch optimizer\n", @@ -241,7 +236,7 @@ "for epoch in range(400):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -268,7 +263,7 @@ " test_losses.append(test_loss)\n", "\n", " if epoch % 5 == 0:\n", - " print(f'{epoch}: {train_loss}')\n", + " print(f\"{epoch}: {train_loss}\")\n", "\n", "# done training\n", "model.eval()" @@ -290,7 +285,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -302,15 +297,16 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", "plt.show()" ] }, @@ -321,7 +317,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -337,12 +333,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental RON')\n", - "plt.ylabel('Predicted RON')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental RON\")\n", + "plt.ylabel(\"Predicted RON\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -355,27 +351,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 5.456787109375\n", - "Test R2: 0.7487984874194098\n" + "Test MAE: 5.648372650146484\n", + "Test R2: 0.7576746499447579\n" ] } ], "source": [ "from sklearn.metrics import median_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {median_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {median_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -394,7 +384,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/examples/predict_ysi.ipynb b/examples/predict_ysi.ipynb index 62fc505..da6319e 100644 --- a/examples/predict_ysi.ipynb +++ b/examples/predict_ysi.ipynb @@ -24,6 +24,7 @@ "from graphchem.datasets import load_ysi\n", "from sklearn.model_selection import train_test_split\n", "\n", + "\n", "# load YSI data\n", "smiles, ysi = load_ysi()\n", "\n", @@ -31,11 +32,11 @@ "smiles_train, smiles_test, ysi_train, ysi_test = train_test_split(smiles, ysi, test_size=0.2, random_state=42)\n", "\n", "print(len(smiles_train), len(smiles_test), type(smiles))\n", - "print(len(ysi_train), len(ysi_test), type(ysi), ysi.shape, '\\n')\n", + "print(len(ysi_train), len(ysi_test), type(ysi), ysi.shape, \"\\n\")\n", "\n", "for i in range(5):\n", "\n", - " print(f'{smiles[i]}\\t{ysi[i]}')" + " print(f\"{smiles[i]}\\t{ysi[i]}\")" ] }, { @@ -53,20 +54,13 @@ "\n", "446 112\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\tjkessler\\.conda\\envs\\graphchem\\Lib\\site-packages\\graphchem-2.1.0-py3.11.egg\\graphchem\\data\\structs.py:32: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", - " y=torch.tensor(target).type(torch.float).reshape(1, len(target))\n" - ] } ], "source": [ "from graphchem.data import MoleculeGraph, MoleculeDataset\n", "from graphchem.preprocessing import MoleculeEncoder\n", "\n", + "\n", "# construct encoder using training data\n", "encoder = MoleculeEncoder(smiles_train)\n", "\n", @@ -74,7 +68,7 @@ "encoding_train = encoder.encode_many(smiles_train)\n", "encoding_test = encoder.encode_many(smiles_test)\n", "\n", - "print('\\n', encoding_train[0], '\\n')\n", + "print(\"\\n\", encoding_train[0], \"\\n\")\n", "\n", "# construct graphs using encoded data\n", "graphs_train = [MoleculeGraph(e[0], e[1], e[2], ysi_train[i]) for i, e in enumerate(encoding_train)]\n", @@ -96,86 +90,86 @@ "name": "stdout", "output_type": "stream", "text": [ - "0: 2881.531232483184\n", - "5: 757.127286218207\n", - "10: 481.2818585040858\n", - "15: 410.095636889539\n", - "20: 265.08493175421063\n", - "25: 277.2931927052314\n", - "30: 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61.226537918296096\n", - "200: 101.43313241111858\n", - "205: 77.36076993044182\n", - "210: 66.60875406821212\n", - "215: 81.08583443474876\n", - "220: 63.8403003504458\n", - "225: 53.788245881084904\n", - "230: 39.361363500757605\n", - "235: 38.320945089708\n", - "240: 121.60605326254806\n", - "245: 46.456381502707444\n", - "250: 41.37130591046115\n", - "255: 43.35143357007493\n", - "260: 35.431957595551495\n", - "265: 84.79175926858534\n", - "270: 65.99436098791558\n", - "275: 53.272997270250535\n", - "280: 28.21087286825137\n", - "285: 60.55778445256665\n", - "290: 61.57404424898293\n", - "295: 126.68315107405454\n", - "300: 42.96147960183866\n", - "305: 89.35630654647211\n", - "310: 40.785167488816604\n", - "315: 36.67935083158348\n", - "320: 38.74400791459019\n", - "325: 58.41449167054865\n", - "330: 41.78832729835681\n", - "335: 46.183609282489314\n", - "340: 29.095252625076224\n", - "345: 35.92259314669622\n", - "350: 41.47386731374424\n", - "355: 31.90913938513786\n", - "360: 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130.17210446344896\n", + "130: 95.1549573479212\n", + "135: 107.19627979090396\n", + "140: 134.02475061117266\n", + "145: 92.52890464543228\n", + "150: 86.59638265430125\n", + "155: 144.66948888120095\n", + "160: 132.95766544769697\n", + "165: 115.44160505902072\n", + "170: 80.12379819929868\n", + "175: 99.37093510649129\n", + "180: 204.99640568275623\n", + "185: 133.6435219461073\n", + "190: 77.70601205868572\n", + "195: 79.48810375538642\n", + "200: 88.96489547934767\n", + "205: 110.93731757878189\n", + "210: 151.56487848940452\n", + "215: 57.402964707447275\n", + "220: 73.59831053045299\n", + "225: 110.39626827154459\n", + "230: 63.01873613366097\n", + "235: 62.905723896796395\n", + "240: 77.45423562858137\n", + "245: 56.688191845812604\n", + "250: 68.14252564297664\n", + "255: 56.0357046426679\n", + "260: 94.42998672280076\n", + "265: 125.25691223144531\n", + "270: 62.563321536966505\n", + "275: 85.953203398016\n", + "280: 48.74512395302811\n", + "285: 72.40498345208275\n", + "290: 48.161513426913274\n", + "295: 41.99819144860511\n", + "300: 43.51623772078031\n", + "305: 87.46145472505168\n", + "310: 47.96657212432724\n", + "315: 53.44402301258036\n", + "320: 47.10669930633408\n", + "325: 39.2562028517103\n", + "330: 58.522024830360586\n", + "335: 32.44502773199381\n", + "340: 47.48666531515763\n", + "345: 70.95054520405996\n", + "350: 43.941102126254094\n", + "355: 59.850712352804\n", + "360: 39.044028320654625\n", + "365: 39.46373722264585\n", + "370: 73.26985380574726\n", + "375: 39.35711285244724\n", + "380: 59.076416584408335\n", + "385: 64.14437249957713\n", + "390: 46.09010831550632\n", + "395: 39.50672052152488\n" ] }, { @@ -183,7 +177,7 @@ "text/plain": [ "MoleculeGCN(\n", " (emb_atom): Embedding(68, 128)\n", - " (emb_bond): Embedding(58, 128)\n", + " (emb_bond): Embedding(56, 128)\n", " (atom_conv): GeneralConv(128, 128)\n", " (bond_conv): EdgeConv(nn=Sequential(\n", " (0): Linear(in_features=256, out_features=128, bias=True)\n", @@ -210,6 +204,7 @@ "import torch.nn.functional as F\n", "from torch_geometric.loader import DataLoader\n", "\n", + "\n", "# prepare training set for training\n", "train_loader = DataLoader(ds_train, batch_size=16, shuffle=True)\n", "test_loader = DataLoader(ds_test, batch_size=1, shuffle=False)\n", @@ -225,7 +220,7 @@ " n_messages=3, # number of message-passing ops to perform (>= 1)\n", " n_readout=3, # number of post-graph-operation feed-forward layers (>= 1)\n", " readout_dim=128, # number of neurons in each readout layer (>= 1)\n", - " dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", + " p_dropout=0.0 # neuron dropout rate [0.0, 1.0]\n", ")\n", "\n", "# construct torch optimizer\n", @@ -241,7 +236,7 @@ "for epoch in range(400):\n", "\n", " for g in optimizer.param_groups:\n", - " g['lr'] = max(0, init_lr - (epoch * lr_decay))\n", + " g[\"lr\"] = max(0, init_lr - (epoch * lr_decay))\n", "\n", " train_loss = 0.0\n", " for batch in train_loader:\n", @@ -268,7 +263,7 @@ " test_losses.append(test_loss)\n", "\n", " if epoch % 5 == 0:\n", - " print(f'{epoch}: {train_loss}')\n", + " print(f\"{epoch}: {train_loss}\")\n", "\n", "# done training\n", "model.eval()" @@ -290,7 +285,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -302,15 +297,16 @@ "source": [ "from matplotlib import pyplot as plt\n", "\n", + "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", "fig, ax = plt.subplots()\n", - "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color='blue')\n", - "ax.set_xlabel('Epochs')\n", - "ax.set_ylabel('Training MSE Loss', color='blue')\n", + "ax.plot([i for i in range(len(train_losses[1:]))], train_losses[1:], color=\"blue\")\n", + "ax.set_xlabel(\"Epochs\")\n", + "ax.set_ylabel(\"Training MSE Loss\", color=\"blue\")\n", "ax2 = ax.twinx()\n", - "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color='red')\n", - "ax2.set_ylabel('Test MSE Loss', color='red')\n", + "ax2.plot([i for i in range(len(test_losses[1:]))], test_losses[1:], color=\"red\")\n", + "ax2.set_ylabel(\"Test MSE Loss\", color=\"red\")\n", "plt.show()" ] }, @@ -321,7 +317,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -337,12 +333,12 @@ "exp_test = [mol.y.numpy() for mol in ds_test]\n", "\n", "plt.clf()\n", - "plt.rcParams['font.family'] = 'Times New Roman'\n", - "plt.scatter(exp_train, pred_train, color='blue', label='Training Set', alpha=0.5)\n", - "plt.scatter(exp_test, pred_test, color='red', label='Test Set', alpha=0.5)\n", - "plt.xlabel('Experimental YSI')\n", - "plt.ylabel('Predicted YSI')\n", - "plt.legend(loc='upper left')\n", + "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n", + "plt.scatter(exp_train, pred_train, color=\"blue\", label=\"Training Set\", alpha=0.5)\n", + "plt.scatter(exp_test, pred_test, color=\"red\", label=\"Test Set\", alpha=0.5)\n", + "plt.xlabel(\"Experimental YSI\")\n", + "plt.ylabel(\"Predicted YSI\")\n", + "plt.legend(loc=\"upper left\")\n", "plt.show()" ] }, @@ -355,27 +351,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "Test MAE: 7.845876693725586\n", - "Test R2: 0.979695723042698\n" + "Test MAE: 5.645942687988281\n", + "Test R2: 0.9799255455197715\n" ] } ], "source": [ "from sklearn.metrics import median_absolute_error, r2_score\n", "\n", + "\n", "e_test = [e[0] for e in exp_test]\n", "p_test = [p[0] for p in pred_test]\n", "\n", - "print(f'Test MAE: {median_absolute_error(e_test, p_test)}')\n", - "print(f'Test R2: {r2_score(e_test, p_test)}')" + "print(f\"Test MAE: {median_absolute_error(e_test, p_test)}\")\n", + "print(f\"Test R2: {r2_score(e_test, p_test)}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -394,7 +384,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.11" }, "orig_nbformat": 4 }, diff --git a/graphchem/data/structs.py b/graphchem/data/structs.py index 9de7f5a..8777031 100644 --- a/graphchem/data/structs.py +++ b/graphchem/data/structs.py @@ -1,71 +1,117 @@ -r"""Molecule graph structure, graph dataset""" +from typing import Iterable, Optional -from typing import List import torch -import torch_geometric - - -class MoleculeGraph(torch_geometric.data.Data): - - def __init__(self, atom_attr: 'torch.tensor', bond_attr: 'torch.tensor', - connectivity: 'torch.tensor', target: 'torch.tensor' = None): - """ MoleculeGraph object, extends torch_geometric.data.Data object; a - singular molecule graph/data point - - Args: - atom_attr (torch.tensor): atom features, shape (n_atoms, - n_atom_features); dtype assumed torch.float32 - bond_attr (torch.tensor): bond features, shape (n_bonds, - n_bond_features); dtype assumed torch.float32 - connectivity (torch.tensor): COO graph connectivity index, size - (2, n_bonds); dtype assumed torch.long - target (torch.tensor, default=None): target value(s), shape - (1, n_targets); if not supplied (None), set to [0.0]; dtype - assumed torch.float32 +from torch_geometric.data import Data, Dataset + + +class MoleculeGraph(Data): + """ + A custom graph class representing a molecular structure. + + This class extends the `Data` class from PyTorch Geometric to represent + molecules with node attributes (atoms), edge attributes (bonds), and + connectivity information. It also includes an optional target value. + + Attributes + ---------- + x : torch.Tensor + The node features (atom attributes). + edge_index : torch.Tensor + A 2D tensor describing the connectivity between atoms. + edge_attr : torch.Tensor + Edge features (bond attributes). + y : torch.Tensor + Target value(s) of the molecule. + """ + + def __init__(self, atom_attr: torch.Tensor, + bond_attr: torch.Tensor, + connectivity: torch.Tensor, + target: Optional[torch.Tensor] = None): + """ + Initialize the MoleculeGraph object. + + Parameters + ---------- + atom_attr : torch.Tensor + A 2D tensor of shape (num_atoms, num_atom_features) representing + the attributes of each atom in the molecule. + bond_attr : torch.Tensor + A 2D tensor of shape (num_bonds, num_bond_features) representing + the attributes of each bond in the molecule. + connectivity : torch.Tensor + A 2D tensor of shape (2, num_bonds) where each column represents an + edge (bond) between two atoms. The first row contains the source + atom indices and the second row contains the target atom indices. + target : Optional[torch.Tensor] + An optional 1D or 2D tensor representing the target value(s) of the + molecule. If not provided, it defaults to a tensor with a single + element set to 0.0. """ if target is None: + # Set default target to a tensor with shape (1, 1) and value 0.0 target = torch.tensor([0.0]).type(torch.float32).reshape(1, 1) + elif len(target.shape) == 1: + # Reshape target if it's a 1D tensor to (1, target.shape[0]) + target = target.reshape(1, -1) + if target.shape[0] != 1: + raise ValueError("Target tensor must have shape (1, num_targets)") - super(MoleculeGraph, self).__init__( + super().__init__( x=atom_attr, edge_index=connectivity, edge_attr=bond_attr, - y=torch.tensor(target).type(torch.float).reshape(1, len(target)) + y=target ) -class MoleculeDataset(torch_geometric.data.Dataset): +class MoleculeDataset(Dataset): + """ + A custom dataset class for molecular graphs. + + This class extends the `Dataset` class from PyTorch Geometric to create a + dataset of molecular graphs. Each graph in the dataset is an instance of + `MoleculeGraph`. - def __init__(self, graphs: List['MoleculeGraph']): - """ MoleculeDataset object, extends torch_geometric.data.Dataset - object; a torch_geometric-iterable dataset comprised of MoleculeGraph - objects + Attributes + ---------- + _graphs : List[MoleculeGraph] + A list containing all the molecule graphs in the dataset. + """ - Args: - graphs (List[MoleculeGraph]): list of molecule graphs + def __init__(self, graphs: Iterable[MoleculeGraph]): """ + Initialize the MoleculeDataset object. - super(MoleculeDataset, self).__init__() - self._graphs = graphs + Parameters + ---------- + graphs : Iterable[MoleculeGraph] + An iterable of `MoleculeGraph` instances representing the + molecules in the dataset. + """ - def len(self) -> int: - """ torch_geometric.data.Dataset.len definition (required) + super().__init__() + self._graphs = list(graphs) - Returns: - int: number of molecule graphs + def len(self) -> int: """ + Returns the number of molecules in the dataset. + Returns + ------- + int + The number of molecule graphs in the dataset. + """ return len(self._graphs) - def get(self, idx: int) -> 'MoleculeGraph': - """ torch_geometric.data.Dataset.get definition (required) - - Args: - idx (int): index of item - - Returns: - MoleculeGraph: indexed item + def get(self, idx: int) -> MoleculeGraph: """ + Retrieves a molecule graph from the dataset by index. + Returns + ------- + MoleculeGraph + The molecule graph at the specified index. + """ return self._graphs[idx] diff --git a/graphchem/datasets/sets.py b/graphchem/datasets/sets.py index afff919..40cae5c 100644 --- a/graphchem/datasets/sets.py +++ b/graphchem/datasets/sets.py @@ -1,83 +1,107 @@ -r"""Pre-packaged fuel property datasets""" - from csv import DictReader from os import path -from typing import List, Tuple, Union +from typing import List, Tuple import torch -_CSV_PATH = path.join(path.dirname(path.abspath(__file__)), 'static') - - -def _load_set(prop: str) -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads data for a given property +_CSV_PATH = path.join(path.dirname(path.abspath(__file__)), "static") - Args: - prop (str): property to obtain data for - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, property values) +def _load_set(prop: str) -> Tuple[List[str], torch.Tensor]: """ - - filename = path.join(_CSV_PATH, f'{prop}.csv') - with open(filename, 'r') as csv_file: + Loads data for a given property from a CSV file. + + Parameters + ---------- + prop : str + The property to obtain data for. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of property values with dtype float32. + """ + filename = path.join(_CSV_PATH, f"{prop}.csv") + with open(filename, "r") as csv_file: reader = DictReader(csv_file) rows = [r for r in reader] csv_file.close() return ( - [r['SMILES'] for r in rows], - torch.tensor([[float(r[f'{prop.upper()}'])] for r in rows]).type( + [r["SMILES"] for r in rows], + torch.tensor([[float(r[f"{prop.upper()}"])] for r in rows]).type( torch.float32 ) ) -def load_cn() -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads cetane number data - - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, CN values) +def load_cn() -> Tuple[List[str], torch.Tensor]: """ - - return _load_set('cn') - - -def load_lhv() -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads lower heating value data - - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, LHV values) + Loads cetane number data. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of CN values with dtype float32. """ + return _load_set("cn") - return _load_set('lhv') - -def load_mon() -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads motor octane number data - - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, MON values) +def load_lhv() -> Tuple[List[str], torch.Tensor]: """ + Loads lower heating value data. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of LHV values with dtype float32. + """ + return _load_set("lhv") - return _load_set('mon') - - -def load_ron() -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads research octane number data - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, RON values) +def load_mon() -> Tuple[List[str], torch.Tensor]: """ + Loads motor octane number data. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of MON values with dtype float32. + """ + return _load_set("mon") - return _load_set('ron') +def load_ron() -> Tuple[List[str], torch.Tensor]: + """ + Loads research octane number data. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of RON values with dtype float32. + """ + return _load_set("ron") -def load_ysi() -> Tuple[Union[List[str], 'torch.tensor']]: - """ loads yield sooting index data - Returns: - Tuple[Union[List[str], 'torch.tensor']]: (SMILES, YSI values) +def load_ysi() -> Tuple[List[str], torch.Tensor]: """ - - return _load_set('ysi') + Loads yield sooting index data. + + Returns + ------- + Tuple[List[str], torch.Tensor] + A tuple containing two elements: + - List[str]: A list of SMILES strings. + - torch.Tensor: A tensor of YSI values with dtype float32. + """ + return _load_set("ysi") diff --git a/graphchem/nn/gcn.py b/graphchem/nn/gcn.py index dc6f216..b09e378 100644 --- a/graphchem/nn/gcn.py +++ b/graphchem/nn/gcn.py @@ -1,58 +1,78 @@ -r"""MoleculeGCN, graph convolutions on vector representations of molecules""" +from typing import Optional, Tuple -from typing import Tuple import torch import torch.nn as nn import torch.nn.functional as F import torch_geometric -import torch_geometric.nn as gnn +from torch_geometric.nn import GeneralConv, EdgeConv, global_add_pool class MoleculeGCN(nn.Module): + """ + A Graph Convolutional Network (GCN) model for molecular property + prediction. + + Attributes + ---------- + _p_dropout : float + Probability of an element to be zeroed in dropout layers. + _n_messages : int + Number of message passing steps. + emb_atom : nn.Embedding + Embedding layer for atoms. + emb_bond : nn.Embedding + Embedding layer for bonds. + atom_conv : GeneralConv + General convolution layer for atoms. + bond_conv : EdgeConv + Edge convolution layer for bonds. + readout : nn.ModuleList + Readout network consisting of fully connected layers. + """ def __init__(self, atom_vocab_size: int, bond_vocab_size: int, - output_dim: int, embedding_dim: int = 64, n_messages: int = 2, - n_readout: int = 2, readout_dim: int = 64, - dropout: float = 0.0): - """ MoleculeGCN, extends torch.nn.Module; combination of GeneralConv - and EdgeConv modules and feed-forward readout layer(s) for regressing - on target variables using molecular structure - - Molecule graphs are first embedded (torch.nn.Embedding), then each - message passing operation consists of: - - bond_embedding > EdgeConv > updated bond_embedding - atom_embedding + bond_embedding > GeneralConv > updated - atom_embedding - - The sum of all atom states is then passed through a series of fully- - connected readout layers to regress on a variable: - - atom_embedding > fully-connected readout layers > target variable - - Args: - atom_vocab_size (int): num features (MoleculeEncoder.vocab_sizes) - bond_vocab_size (int): num features (MoleculeEncoder.vocab_sizes) - output_dim (int): number of target values per compound - embedding_dim (int): number of embedded features for atoms and - bonds - n_messages (int): number of message passes between atoms - n_readout (int): number of feed-forward post-readout - layers (think standard NN/MLP) - readout_dim (int): number of neurons in readout layers - dropout (float): random neuron dropout during training + output_dim: int, embedding_dim: Optional[int] = 128, + n_messages: Optional[int] = 2, + n_readout: Optional[int] = 2, + readout_dim: Optional[int] = 64, + p_dropout: Optional[float] = 0.0, + aggr: Optional[str] = "add"): """ + Initialize the MoleculeGCN object. + + Parameters + ---------- + atom_vocab_size : int + Number of unique atom representations in the dataset. + bond_vocab_size : int + Number of unique bond representations in the dataset. + output_dim : int + Dimensionality of the output space. + embedding_dim : int, optional (default=128) + Dimensionality of the atom and bond embeddings. + n_messages : int, optional (default=2) + Number of message passing steps. + n_readout : int, optional (default=2) + Number of fully connected layers in the readout network. + readout_dim : int, optional (default=64) + Dimensionality of the hidden layers in the readout network. + p_dropout : float, optional (default=0.0) + Dropout probability for the dropout layers. + aggr : str, optional (default="add") + Aggregation scheme to use in the GeneralConv layer. + """ + super().__init__() - super(MoleculeGCN, self).__init__() - self._dropout = dropout + self._p_dropout = p_dropout self._n_messages = n_messages self.emb_atom = nn.Embedding(atom_vocab_size, embedding_dim) self.emb_bond = nn.Embedding(bond_vocab_size, embedding_dim) - self.atom_conv = gnn.GeneralConv(embedding_dim, embedding_dim, - embedding_dim, aggr='add') - self.bond_conv = gnn.EdgeConv(nn.Sequential( + self.atom_conv = GeneralConv( + embedding_dim, embedding_dim, embedding_dim, aggr=aggr + ) + self.bond_conv = EdgeConv(nn.Sequential( nn.Linear(2 * embedding_dim, embedding_dim) )) @@ -69,24 +89,29 @@ def __init__(self, atom_vocab_size: int, bond_vocab_size: int, nn.Linear(readout_dim, output_dim) )) - def forward(self, - data: 'torch_geometric.data.Data') -> Tuple['torch.tensor']: - """ forward operation for PyTorch module; given a sample of - torch_geometric.data.Data, with atom/bond attributes and connectivity, - perform message passing operations and readout - - Args: - data ('torch_geometric.data.Data'): torch_geometric data object or - inheritee - - Returns: - Tuple['torch.tensor']: (readout output (target prediction), atom - embeddings, bond embeddings); embeddings represent pre-sum/ - readout values present at each atom/bond, useful for - determining which atoms/bonds contribute to target value + def forward( + self, + data: torch_geometric.data.Data + ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: """ - - x, edge_attr, edge_index, batch = data.x, data.edge_attr,\ + Forward pass of the MoleculeGCN. + + Parameters + ---------- + data : torch_geometric.data.Data + Input data containing node features (x), edge attributes + (edge_attr), edge indices (edge_index), and batch vector (batch). + + Returns + ------- + out : torch.Tensor + The final output predictions for the input molecules. + out_atom : torch.Tensor + Atom-level representations after message passing. + out_bond : torch.Tensor + Bond-level representations after message passing. + """ + x, edge_attr, edge_index, batch = data.x, data.edge_attr, \ data.edge_index, data.batch if data.num_node_features == 0: x = torch.ones(data.num_nodes, 1) @@ -101,20 +126,26 @@ def forward(self, out_bond = self.bond_conv(out_bond, edge_index) out_bond = F.softplus(out_bond) - out_bond = F.dropout(out_bond, p=self._dropout, - training=self.training) + out_bond = F.dropout( + out_bond, p=self._p_dropout, training=self.training + ) out_atom = self.atom_conv(out_atom, edge_index, out_bond) out_atom = F.softplus(out_atom) - out_atom = F.dropout(out_atom, p=self._dropout, - training=self.training) + out_atom = F.dropout( + out_atom, p=self._p_dropout, training=self.training + ) - out = gnn.global_add_pool(out_atom, batch) + out = global_add_pool(out_atom, batch) for layer in self.readout[:-1]: + out = layer(out) out = F.softplus(out) - out = F.dropout(out, p=self._dropout, training=self.training) + out = F.dropout( + out, p=self._p_dropout, training=self.training + ) + out = self.readout[-1](out) return (out, out_atom, out_bond) diff --git a/graphchem/preprocessing/features.py b/graphchem/preprocessing/features.py index 98353b1..900566d 100644 --- a/graphchem/preprocessing/features.py +++ b/graphchem/preprocessing/features.py @@ -1,41 +1,67 @@ -r"""Encoding/tokenizing SMILES strings (preparing for graph construction)""" - import pickle -from typing import List, Tuple, Union -import rdkit +from typing import Iterable, List, Optional, Tuple, Union + import numpy as np +import rdkit import torch -def get_ring_size(obj: Union['rdkit.Chem.Atom', 'rdkit.Chem.Bond'], - max_size: int = 12): - """ determine whether rdkit.Chem.Atom or rdkit.Chem.Bond is in a ring, and - of which size - - Args: - obj (Union[rdkit.Chem.Atom, rdkit.Chem.Bond]): atom or bond - max_size (int): maximum ring size to consider +def get_ring_size( + obj: Union[rdkit.Chem.Atom, rdkit.Chem.Bond], + max_size: Optional[int] = 12 + ) -> int: + """ + Determine the size of the smallest ring that an atom or bond is part of. + + Parameters + ---------- + obj : Union[rdkit.Chem.Atom, rdkit.Chem.Bond] + An RDKit Atom or Bond object to check for ring membership. + max_size : Optional[int], default 12 + The maximum size of the ring to consider. If no ring is found with a + size less than or equal to `max_size`, this value will be returned. + + Returns + ------- + int + The size of the smallest ring that the atom or bond is part of, or + `max_size` if no smaller ring is found. """ - if not obj.IsInRing(): return 0 for i in range(max_size): if obj.IsInRingSize(i): return i - return max_size + 1 - + return max_size -def atom_to_str(atom: 'rdkit.Chem.Atom') -> str: - """ prepare to tokenize an atom's attributes by constructing a unique - string - Args: - atom (rdkit.Chem.Atom): atom to tokenize - - Returns: - str: atom properties +def atom_to_str(atom: rdkit.Chem.Atom) -> str: + """ + Convert an RDKit Atom object to a string representation. + + The string representation includes various properties of the atom, + such as chiral tag, degree, explicit valence, formal charge, hybridization, + implicit valence, aromaticity, number of implicit hydrogen atoms, and more. + + Parameters + ---------- + atom : rdkit.Chem.Atom + An RDKit Atom object representing a single atom in a molecule. + + Returns + ------- + str + A string representation of the atom, including its properties. + + Examples + -------- + >>> from rdkit import Chem + >>> mol = Chem.MolFromSmiles('C1=CC=CC=C1') + >>> atom = mol.GetAtomWithIdx(0) + >>> atom_to_str(atom) + '(CHIRAL_NONE, 3, 4, 0, , 0, True, False, 0, 0, 0, + 'C', 3, 1, 4, 5)' """ - return str(( atom.GetChiralTag(), atom.GetDegree(), @@ -56,16 +82,32 @@ def atom_to_str(atom: 'rdkit.Chem.Atom') -> str: )) -def bond_to_str(bond: 'rdkit.Chem.Bond') -> str: - """ prepare to tokenize a bond's attributes by constructing a unique string - - Args: - bond (rdkit.Chem.Bond): bond to tokenize - - Returns: - str: bond properties +def bond_to_str(bond: rdkit.Chem.Bond) -> str: + """ + Convert an RDKit Bond object to a string representation. + + The string representation includes various properties of the bond, + including bond type, conjugation, stereochemistry, ring size, and + connected atom symbols. + + Parameters + ---------- + bond : rdkit.Chem.Bond + An RDKit Bond object representing a single bond in a molecule. + + Returns + ------- + str + A string representation of the bond, including its properties. + + Examples + -------- + >>> from rdkit import Chem + >>> mol = Chem.MolFromSmiles('C=C') + >>> bond = mol.GetBondWithIndices(0, 1) + >>> bond_to_str(bond) + "(DOUBLE, False, NONE, None, ['C', 'C'])" """ - return str(( bond.GetBondType(), bond.GetIsConjugated(), @@ -77,27 +119,54 @@ def bond_to_str(bond: 'rdkit.Chem.Bond') -> str: class Tokenizer(object): + """ + A simple tokenizer that assigns a unique integer to each token (word) in + the input data. If the tokenizer is in training mode, it will add new + tokens to the vocabulary. Otherwise, it will return the integer + corresponding to 'unk' for unknown tokens. + + Attributes + ---------- + _data : dict + A dictionary mapping each token to a unique integer. Initialized with + {"unk": 1}. + num_classes : int + The number of unique classes (tokens) in the vocabulary, including + 'unk'. + train : bool + A flag indicating whether the tokenizer is in training mode. + unknown : list + A list to store tokens that were encountered during inference but are + not in the vocabulary. + """ def __init__(self): - """ Tokenizer object: integer tokenizer for unique atom/bond strings """ - - self._data = {'unk': 1} + Initialize the Tokenizer with default values. + """ + self._data = {"unk": 1} self.num_classes = 1 self.train = True self.unknown = [] def __call__(self, item: str) -> int: - """ Tokenizer(): returns integer value of atom/bond string, otherwise - 'unknown', or 1; if training the tokenizer, add item to vocabulary - - Args: - item (str): atom/bond string - - Returns: - int: integer value of atom/bond string """ - + Tokenizes a given string by returning its corresponding integer from + the vocabulary. + + Parameters + ---------- + item : str + The token (word) to be tokenized. + + Returns + ------- + int + The unique integer assigned to the token. If the token is not in + the vocabulary and the tokenizer is in training mode, it will add + the token and return its corresponding integer. Otherwise, it + returns 1, which corresponds to 'unk'. + """ try: return self._data[item] except KeyError: @@ -111,38 +180,58 @@ def __call__(self, item: str) -> int: @property def vocab_size(self) -> int: - """ vocab_size: returns the total number of unique atom/bond strings - in the tokenizer's vocabulary - - Returns: - int: number of strings in vocabulary """ + Returns the size of the vocabulary, which is the number of unique + tokens plus one. + Returns + ------- + int + The total number of classes (tokens) in the vocabulary plus one. + """ return self.num_classes + 1 class MoleculeEncoder(object): + """ + A class to encode molecular SMILES strings into numerical (integer) + representations using tokenized atom and bond information. + + Attributes + ---------- + _atom_tokenizer : Tokenizer + integer Tokenizer for atom representations. + _bond_tokenizer : Tokenizer + integer Tokenizer for bond representations. + """ def __init__(self, smiles: List[str]): - """ MoleculeEncoder object: given a list of SMILES strings, construct/ - train integer tokenizers to tokenize atom/bond features, parse - molecule connectivity - - Args: - smiles (List[str]): SMILES strings to consider for encoder - construction """ - + Initializes the MoleculeEncoder with a list of SMILES strings and + creates/trains integer tokenizers for atoms and bonds. + + Parameters + ---------- + smiles : List[str] + A list of SMILES strings representing molecules used for tokenizer + creation/training. + + Raises + ------ + ValueError + If any provided SMILES string cannot be parsed by RDKit. + """ mols = [rdkit.Chem.MolFromSmiles(smi) for smi in smiles] for idx, mol in enumerate(mols): if mol is None: - raise ValueError(f'Unable to parse SMILES: {smiles[idx]}') + raise ValueError(f"Unable to parse SMILES: {smiles[idx]}") atoms = np.concatenate([mol.GetAtoms() for mol in mols]) atom_reprs = [atom_to_str(atom) for atom in atoms] - bond_reprs = np.concatenate( - [[bond_to_str(bond) for bond in atom.GetBonds()] for atom in atoms] - ) + bond_reprs = np.concatenate([ + [bond_to_str(bond) for bond in atom.GetBonds()] + for atom in atoms + ]) self._atom_tokenizer = Tokenizer() for rep in atom_reprs: @@ -152,117 +241,143 @@ def __init__(self, smiles: List[str]): self._bond_tokenizer = Tokenizer() for rep in bond_reprs: self._bond_tokenizer(rep) - self._atom_tokenizer.train = False + self._bond_tokenizer.train = False @property - def vocab_sizes(self) -> Tuple[int]: - """ total vocabulary/dictionary sizes for tokenizers, in form (atom - vocab size, bond vocab size) - - Returns: - Tuple[int]: (atom vocab size, bond vocab size) + def vocab_sizes(self) -> Tuple[int, int]: """ + Returns the vocabulary sizes of the atom and bond tokenizers. - return (self._atom_tokenizer.vocab_size, - self._bond_tokenizer.vocab_size) - - def encode_many(self, smiles: List[str]) -> List[Tuple['torch.tensor']]: - """ batch encoding of SMILES strings - - Args: - smiles (List[str]): list of SMILES strings - - Returns: - List[Tuple['torch.tensor']]: List of: (atom encoding, bond - encoding, connectivity matrix) for each compound + Returns + ------- + Tuple[int, int] + A tuple containing two integers representing the sizes of the atom + and bond tokenizers' vocabularies respectively. """ + return ( + self._atom_tokenizer.vocab_size, + self._bond_tokenizer.vocab_size + ) - encoded_compounds = [] - for smi in smiles: - encoded_compounds.append(self.encode(smi)) - return encoded_compounds - - def encode(self, smiles: str) -> Tuple['torch.tensor']: - """ encode a molecule using its SMILES string - - Args: - smiles (str): molecule's SMILES string - - Returns: - Tuple['torch.tensor']: (encoded atom features, encoded bond - features, molecule connectivity matrix) + def encode( + self, + smiles: str + ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: + """ + Encodes a single SMILES string into three tensors representing atoms, + bonds, and connectivity. + + Parameters + ---------- + smiles : str + A SMILES string representing the molecule to be encoded. + + Returns + ------- + Tuple[torch.Tensor, torch.Tensor, torch.Tensor] + A tuple containing: + - A tensor of atom encodings, shape (n_atoms,). + - A tensor of bond encodings, shape (n_bonds,). + - A connectivity matrix as a tensor, shape (2, n_bonds). + + Raises + ------ + ValueError + If the provided SMILES string cannot be parsed by RDKit. """ - mol = rdkit.Chem.MolFromSmiles(smiles) if mol is None: - raise ValueError(f'Unable to parse SMILES: {smiles}') + raise ValueError(f"Unable to parse SMILES string: {smiles}") atoms = mol.GetAtoms() atom_reprs = [atom_to_str(atom) for atom in atoms] - enc_atoms = torch.tensor([self._atom_tokenizer(atom) - for atom in atom_reprs]).type(torch.int) - - bond_reprs = np.concatenate( - [[bond_to_str(bond) for bond in atom.GetBonds()] for atom in atoms] - ) - enc_bonds = torch.tensor([self._bond_tokenizer(bond) - for bond in bond_reprs]).type(torch.int) + enc_atoms = torch.tensor([ + self._atom_tokenizer(atom) for atom in atom_reprs + ]).type(torch.int) + + bond_reprs = np.concatenate([ + [bond_to_str(bond) for bond in atom.GetBonds()] + for atom in atoms + ]) + enc_bonds = torch.tensor([ + self._bond_tokenizer(bond) for bond in bond_reprs + ]).type(torch.int) connectivity = np.zeros((2, 2 * mol.GetNumBonds())) bond_index = 0 for atom in atoms: start_idx = atom.GetIdx() for bond in atom.GetBonds(): - reverse = bond.GetBeginAtomIdx() != start_idx - if not reverse: + if bond.GetBeginAtomIdx() == start_idx: connectivity[0, bond_index] = bond.GetBeginAtomIdx() connectivity[1, bond_index] = bond.GetEndAtomIdx() else: connectivity[0, bond_index] = bond.GetEndAtomIdx() connectivity[1, bond_index] = bond.GetBeginAtomIdx() bond_index += 1 - connectivity = torch.from_numpy(connectivity).type(torch.long) + connectivity = torch.tensor(connectivity).type(torch.long) - return (enc_atoms, enc_bonds, connectivity) + return enc_atoms, enc_bonds, connectivity - def save(self, filename: str) -> None: - """ save the encoder to a file - - Args: - filename (str): new filename/path for model - - Returns: - None + def encode_many( + self, + smiles: Iterable[str] + ) -> List[Tuple[torch.Tensor, torch.Tensor, torch.Tensor]]: """ + Encodes a list of SMILES strings into tensors representing atoms, + bonds, and connectivities. + + Parameters + ---------- + smiles : Iterable[str] + An iterable collection of SMILES strings representing molecules to + be encoded. + + Returns + ------- + List[Tuple[torch.Tensor, torch.Tensor, torch.Tensor]] + A list containing tuples with three elements: + - A tensor of atom encodings, shape (n_atoms,). + - A tensor of bond encodings, shape (n_bonds,). + - A connectivity matrix as a tensor, shape (2, n_bonds). + + Raises + ------ + ValueError + If any provided SMILES string cannot be parsed by RDKit. + """ + encodings = [] + for smi in smiles: + encodings.append(self.encode(smi)) + return encodings - with open(filename, 'wb') as outp: - pickle.dump(self, outp, pickle.HIGHEST_PROTOCOL) - - def load(self, filename: str) -> None: - """ load an encoder from file (current encoder attributes, including - pre-trained tokenizers, are overwritten) - - Args: - filename (str): filename/path of model - - Returns: - None + def save(self, filename: str) -> None: """ + Save the encoder to a file. - with open(filename, 'rb') as inp: - self.__dict__.update(pickle.loads(inp).__dict__) + Parameters + ---------- + filename : str + filename/path to save the encoder to. + """ + with open(filename, "wb") as outp: + pickle.dump(self, outp, pickle.HIGHEST_PROTOCOL) def load_encoder(filename: str) -> MoleculeEncoder: - """ loads a pre-saved `MoleculeEncoder` object + """ + Loads a pre-saved `MoleculeEncoder` object from a file. - Args: - filename (str): filename/path of saved encoder + Parameters + ---------- + filename : str + The path to the saved encoder file. - Returns: - MoleculeEncoder: loaded encoder object + Returns + ------- + MoleculeEncoder + The loaded `MoleculeEncoder` object. """ - - with open(filename, 'rb') as inp: - encoder = pickle.loads(inp) + with open(filename, "rb") as inp: + encoder = pickle.load(inp) return encoder diff --git a/graphchem/version.py b/graphchem/version.py index 8b380bc..834a452 100644 --- a/graphchem/version.py +++ b/graphchem/version.py @@ -1,3 +1,3 @@ -import pkg_resources +from importlib.metadata import version -__version__ = pkg_resources.get_distribution("graphchem").version +__version__ = version("graphchem") diff --git a/pyproject.toml b/pyproject.toml index 1f7cff9..2918387 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,7 @@ include-package-data = true [project] name = "graphchem" -version = "2.1.4" +version = "2.2.0" authors = [ { name="Travis Kessler", email="travis.j.kessler@gmail.com" }, ] @@ -16,9 +16,8 @@ readme = "README.md" requires-python = ">=3.11" dependencies = [ "rdkit-pypi==2022.9.5", - "torch==2.4.0", - "torch-geometric==2.3.0", - "numpy==1.26.4" + "torch==2.5.1", + "torch-geometric==2.6.1" ] classifiers = [ "Programming Language :: Python :: 3.11", diff --git a/tests/test_all.py b/tests/test_all.py deleted file mode 100644 index d1828ca..0000000 --- a/tests/test_all.py +++ /dev/null @@ -1,5 +0,0 @@ -import graphchem - - -def test_placeholder(): - assert 1 == 1 diff --git a/tests/test_features.py b/tests/test_features.py new file mode 100644 index 0000000..e79fc6f --- /dev/null +++ b/tests/test_features.py @@ -0,0 +1,168 @@ +from rdkit import Chem + +from graphchem.preprocessing.features import get_ring_size, atom_to_str, \ + bond_to_str, Tokenizer, MoleculeEncoder, load_encoder + + +# Helper function to create a simple molecule for testing +def create_test_molecule(smiles): + + return Chem.MolFromSmiles(smiles) + + +# Test cases for get_ring_size +def test_get_ring_size(): + + # Create a benzene ring (C6H6) + mol = create_test_molecule("C1=CC=CC=C1") + + # Check ring size for each atom in the molecule + for atom in mol.GetAtoms(): + assert get_ring_size(atom) == 6 + + # Create an ethane molecule (C2H6) + mol = create_test_molecule("CC") + + # Check that there are no rings in this molecule + for atom in mol.GetAtoms(): + assert get_ring_size(atom) == 0 + + # Test max_size parameter + mol = create_test_molecule("C1=CC=CC=C1") + for atom in mol.GetAtoms(): + assert get_ring_size(atom, max_size=5) == 5 + + +# Test cases for atom_to_str +def test_atom_to_str(): + + # Create a benzene ring (C1=CC=CC=C1) + mol = create_test_molecule("C1=CC=CC=C1") + + # Check the string representation of each atom in the molecule + for i, expected in enumerate([ + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)", + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)", + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)", + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)", + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)", + "(rdkit.Chem.rdchem.ChiralType.CHI_UNSPECIFIED, 2, 3, 0, rdkit.Chem." + "rdchem.HybridizationType.SP2, 1, True, False, 0, 1, 0, 'C', 3, " + "1, 4, 6)" + ]): + assert atom_to_str(mol.GetAtomWithIdx(i)) == expected + + +# Test cases for bond_to_str +def test_bond_to_str(): + + # Create a benzene ring (C1=CC=CC=C1) + mol = create_test_molecule("C1=CC=CC=C1") + + # Check the string representation of each bond in the molecule + for i, expected in enumerate([ + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])", + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])", + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])", + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])", + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])", + "(rdkit.Chem.rdchem.BondType.AROMATIC, True, rdkit.Chem.rdchem." + "BondStereo.STEREONONE, 6, [['C', 'C']])" + ]): + bond = mol.GetBondWithIdx(i) + assert bond_to_str(bond) == expected + + +# Test cases for max_size parameter in get_ring_size +def test_get_ring_size_max_size(): + + # Create a benzene ring (C1=CC=CC=C1) + mol = create_test_molecule("C1=CC=CC=C1") + + # Check ring size with different max_size values + for atom in mol.GetAtoms(): + assert get_ring_size(atom, max_size=5) == 5 + assert get_ring_size(atom, max_size=6) == 6 + assert get_ring_size(atom, max_size=7) == 6 + + +# Test cases adding tokens to a Tokenizer object +def test_tokenizer(): + + tokenizer = Tokenizer() + # Test training mode + tokenizer.train = True + assert tokenizer("test") == 2 + assert tokenizer("another_test") == 3 + + # Test inference mode + tokenizer.train = False + assert tokenizer("unknown_token") == 1 + assert tokenizer.unknown == ["unknown_token"] + + +# Test cases for MoleculeEncoder class, vocab sizes +def test_molecule_encoder_vocab_sizes(): + + smiles_list = ["C", "N"] + encoder = MoleculeEncoder(smiles_list) + vocab_sizes = encoder.vocab_sizes + assert len(vocab_sizes) == 2 + # Check the number of unique atoms and bonds + assert vocab_sizes[0] > 1 + assert vocab_sizes[1] > 1 + + +# Test cases for MoleculeEncoder class, feature shapes +def test_molecule_encoder_encode(): + + smiles = "C=C" + encoder = MoleculeEncoder([smiles]) + enc_atoms, enc_bonds, connectivity = encoder.encode(smiles) + # Check the shape of output tensors + assert enc_atoms.shape == (2,) + assert enc_bonds.shape == (2 * 1,) # one bond, seen from two atoms + assert connectivity.shape == (2, 2 * 1) + + +# Test cases for MoleculeEncoder class, encoding multiple molecules +def test_molecule_encoder_encode_many(): + + smiles_list = ["C", "N"] + encoder = MoleculeEncoder(smiles_list) + encodings = encoder.encode_many(smiles_list) + # Check the number of encodings + assert len(encodings) == len(smiles_list) + # Check the shape of each encoding + for atoms, bonds, connectivity in encodings: + assert len(atoms) > 0 + if len(bonds) > 0 and connectivity is not None: + assert connectivity.shape == (2, len(bonds)) + + +# Test cases for MoleculeEncoder class, saving and loading encoders +def test_molecule_encoder_save_load(tmpdir): + + smiles_list = ["C", "N"] + encoder = MoleculeEncoder(smiles_list) + filename = tmpdir.join("encoder.pkl") + # Save the encoder + encoder.save(str(filename)) + # Load the encoder + loaded_encoder = load_encoder(str(filename)) + assert loaded_encoder.vocab_sizes == encoder.vocab_sizes diff --git a/tests/test_gcn.py b/tests/test_gcn.py new file mode 100644 index 0000000..6125ff0 --- /dev/null +++ b/tests/test_gcn.py @@ -0,0 +1,59 @@ +# test_gcn.py + +import torch +from graphchem.nn import MoleculeGCN +from torch_geometric.data import Data + + +# Test instantiation of the MoleculeGCN class with various parameters +def test_moleculgcn_instantiation(): + + model = MoleculeGCN( + atom_vocab_size=10, + bond_vocab_size=5, + output_dim=2, + embedding_dim=64, + n_messages=3, + n_readout=3, + readout_dim=128, + p_dropout=0.2 + ) + + assert model._p_dropout == 0.2 + assert model._n_messages == 3 + + +# Test the forward pass of the MoleculeGCN model +def test_moleculgcn_forward_pass(): + + atom_vocab_size = 10 + bond_vocab_size = 5 + n_atoms = 3 + n_bonds = 5 + + model = MoleculeGCN( + atom_vocab_size=atom_vocab_size, + bond_vocab_size=bond_vocab_size, + output_dim=2, + embedding_dim=64, + n_messages=3, + n_readout=3, + readout_dim=128, + p_dropout=0.2 + ) + + n_atoms = 3 + + # Create a mock input for the forward pass + data = Data( + x=torch.randint(0, atom_vocab_size, (n_atoms,)), + edge_index=torch.randint(0, n_atoms, (2, n_bonds)), + edge_attr=torch.randint(0, bond_vocab_size, (n_bonds,)), + batch=torch.tensor([0, 0, 0], dtype=torch.long) + ) + + out, out_atom, out_bond = model.forward(data) + + assert out.shape == (1, 2) + assert out_atom.shape == (3, 64) + assert out_bond.shape == (5, 64) diff --git a/tests/test_sets.py b/tests/test_sets.py new file mode 100644 index 0000000..0729410 --- /dev/null +++ b/tests/test_sets.py @@ -0,0 +1,24 @@ +import torch + +from graphchem.datasets import load_cn, load_lhv, load_mon, load_ron, load_ysi + + +# Test cases for loading property datasets +def test_loading_datasets(): + + datasets = [ + load_cn, + load_lhv, + load_mon, + load_ron, + load_ysi, + ] + + for dataset in datasets: + + smiles, prop = dataset() + assert len(smiles) == len(prop) + assert type(smiles) is list + assert type(smiles[0]) is str + assert type(prop) is torch.Tensor + assert prop.dtype == torch.float32 diff --git a/tests/test_structs.py b/tests/test_structs.py new file mode 100644 index 0000000..ef9dfe0 --- /dev/null +++ b/tests/test_structs.py @@ -0,0 +1,104 @@ +import pytest +import torch + +from graphchem.data.structs import MoleculeGraph, MoleculeDataset + + +# Test cases for MoleculeGraph initialization +def test_moleculargraph_initialization(): + + # Test initialization with no target + atom_attr = torch.rand((10, 5)) # 10 atoms, each with 5 features + bond_attr = torch.rand((20, 4)) # 20 bonds, each with 4 features + connectivity = torch.randint(0, 10, (2, 20)) + + mol_graph_no_target = MoleculeGraph(atom_attr, bond_attr, connectivity) + assert mol_graph_no_target.x.shape == atom_attr.shape + assert mol_graph_no_target.edge_index.shape == connectivity.shape + assert mol_graph_no_target.edge_attr.shape == bond_attr.shape + assert mol_graph_no_target.y.shape == (1, 1) and torch.allclose( + mol_graph_no_target.y, torch.tensor([[0.]]) + ) + + # Test initialization with a 1D target tensor + target = torch.tensor([2.5]) + mol_graph_1d_target = MoleculeGraph(atom_attr, bond_attr, connectivity, + target) + assert mol_graph_1d_target.y.shape == (1, 1) and torch.allclose( + mol_graph_1d_target.y, torch.tensor([[2.5]]) + ) + + # Test initialization with a 2D target tensor + target = torch.rand((1, 3)) + mol_graph_2d_target = MoleculeGraph(atom_attr, bond_attr, connectivity, + target) + assert mol_graph_2d_target.y.shape == target.shape + + # Test initialization with a 1D target tensor, multiple values + target = torch.rand(3) + mol_graph_1d_multi_target = MoleculeGraph( + atom_attr, bond_attr, connectivity, target + ) + assert mol_graph_1d_multi_target.y.shape == (1, 3) + + +# Test cases for MoleculeGraph with invalid target shape +def test_moleculargraph_invalid_target(): + + # Test initialization with a 2D target tensor that cannot be reshaped to + # (1, num_targets) + target = torch.rand((2, 3)) # This will raise an error + with pytest.raises(ValueError): + MoleculeGraph(torch.rand((10, 5)), torch.rand((20, 4)), + torch.randint(0, 10, (2, 20)), target) + + +# Test cases for MoleculeDataset initialization +def test_moleculardataset_initialization(): + + # Test initialization with a list of MoleculeGraphs + atom_attr = torch.rand((10, 5)) # 10 atoms, each with 5 features + bond_attr = torch.rand((20, 4)) # 20 bonds, each with 4 features + connectivity = torch.randint(0, 10, (2, 20)) + + graphs = [MoleculeGraph(atom_attr, bond_attr, connectivity) + for _ in range(5)] + dataset = MoleculeDataset(graphs) + + assert len(dataset) == 5 + assert isinstance(dataset[0], MoleculeGraph) + + +# Test cases for MoleculeDataset lengths +def test_moleculardataset_len(): + + # Test len method with an empty dataset + dataset = MoleculeDataset([]) + assert len(dataset) == 0 + + # Test len method with a non-empty dataset + atom_attr = torch.rand((10, 5)) # 10 atoms, each with 5 features + bond_attr = torch.rand((20, 4)) # 20 bonds, each with 4 features + connectivity = torch.randint(0, 10, (2, 20)) + + graphs = [MoleculeGraph(atom_attr, bond_attr, connectivity) + for _ in range(5)] + dataset = MoleculeDataset(graphs) + assert len(dataset) == 5 + + +# Test cases for MoleculeDataset indexing +def test_moleculardataset_get(): + + # Test get method with a non-empty dataset + atom_attr = torch.rand((10, 5)) # 10 atoms, each with 5 features + bond_attr = torch.rand((20, 4)) # 20 bonds, each with 4 features + connectivity = torch.randint(0, 10, (2, 20)) + + graphs = [MoleculeGraph(atom_attr, bond_attr, connectivity) + for _ in range(5)] + dataset = MoleculeDataset(graphs) + + assert isinstance(dataset[0], MoleculeGraph) + with pytest.raises(IndexError): + _ = dataset[5] # Trying to access an index out of bounds