![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\"){kind=icon}
"
- ]
- },
- {
- "cell_type": "code",
- "source": [
- "# Importing Libraries\n",
- "import pandas as pd\n",
- "import numpy as np\n",
- "import timm\n",
- "import torch\n",
- "import torchvision\n",
- "import torch.nn as nn\n",
- "import torch.optim as optim\n",
- "from torch.utils.data import DataLoader\n",
- "from torchvision import datasets, transforms\n",
- "import torch.nn.functional as F\n",
- "import matplotlib.pyplot as plt\n",
- "import os\n",
- "from collections import OrderedDict\n",
- "import warnings\n",
- "warnings.filterwarnings('ignore')\n",
- "\n",
- "# Loading Raw Data\n",
- "# Load WITHOUT any transform → gives PIL images (0-255)\n",
- "train_set_raw = datasets.MNIST(\n",
- " root='./data',\n",
- " train=True,\n",
- " download=True,\n",
- " transform=None\n",
- ")\n",
- "\n",
- "test_set_raw = datasets.MNIST(\n",
- " root='./data',\n",
- " train=False,\n",
- " download=True\n",
- ")\n",
- "\n",
- "# Access one sample\n",
- "img_tr, label_tr = train_set_raw[0]\n",
- "\n",
- "print(\"####Train Data MNIST#####\")\n",
- "print(\"Type:\", type(img_tr))\n",
- "print(\"Size:\", img_tr.size)\n",
- "print(\"Label:\", label_tr)\n",
- "\n",
- "img_te, label_te = test_set_raw[0]\n",
- "\n",
- "print(\"####Test Data MNIST#####\")\n",
- "print(\"Type:\", type(img_te))\n",
- "print(\"Size:\", img_te.size)\n",
- "print(\"Label:\", label_te)\n",
- "\n",
- "# Working Directory/Folder\n",
- "save_dir = './saved_images'\n",
- "if not os.path.exists(save_dir):\n",
- " os.makedirs(save_dir)\n",
- " print(f\"Directory '{save_dir}' created successfully.\")\n",
- "else:\n",
- " print(f\"Directory '{save_dir}' already exists.\")\n",
- "\n",
- "# Visualizing Raw Data\n",
- "plt.imshow(img_tr, cmap='gray')\n",
- "plt.title(f\"Label: {label_tr}\")\n",
- "plt.axis('off')\n",
- "plt.show()\n",
- "\n",
- "# Show multiple train images\n",
- "fig, axes = plt.subplots(2, 5, figsize=(10, 4))\n",
- "for i, ax in enumerate(axes.flat):\n",
- " img_tr, lbl = train_set_raw[i]\n",
- " ax.imshow(img_tr, cmap='gray')\n",
- " ax.set_title(f\"{lbl}\")\n",
- " ax.axis('off')\n",
- "plt.tight_layout()\n",
- "plt.savefig(os.path.join(save_dir, 'train_images.png'))\n",
- "plt.show()\n",
- "\n",
- "# Show multiple test images\n",
- "fig, axes = plt.subplots(2, 5, figsize=(10, 4))\n",
- "for i, ax in enumerate(axes.flat):\n",
- " img_te, lbl = test_set_raw[i]\n",
- " ax.imshow(img_te, cmap='hot_r')\n",
- " ax.set_title(f\"{lbl}\")\n",
- " ax.axis('off')\n",
- "plt.tight_layout()\n",
- "plt.savefig(os.path.join(save_dir, 'test_images.png'))\n",
- "plt.show()\n",
- "# ==================== FIXED MODEL DEFINITIONS ====================\n",
- "\n",
- "# Simple Shared Layers Backbone (for 28x28 images)\n",
- "class MTMShared(nn.Module):\n",
- " def __init__(self):\n",
- " super(MTMShared, self).__init__()\n",
- " self.shared = nn.Sequential(\n",
- " nn.Flatten(),\n",
- " nn.Linear(784, 256),\n",
- " nn.ReLU(),\n",
- " nn.Linear(256, 128),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.digit_head = nn.Linear(128, 10)\n",
- " self.parity_head = nn.Linear(128, 2)\n",
- "\n",
- " def forward(self, x):\n",
- " features = self.shared(x)\n",
- " return self.digit_head(features), self.parity_head(features)\n",
- "\n",
- "print(\"✅ Simple Shared Backbone Defined\")\n",
- "\n",
- "# Simple Convolutional Backbone 1\n",
- "class SMTMConv(nn.Module):\n",
- " def __init__(self, in_channels=1, num_classes_digit=10, num_classes_parity=2):\n",
- " super(SMTMConv, self).__init__()\n",
- " self.backbone = nn.Sequential(\n",
- " nn.Conv2d(in_channels, 32, kernel_size=3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.MaxPool2d(2),\n",
- " nn.Conv2d(32, 64, kernel_size=3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.MaxPool2d(2),\n",
- " nn.Flatten(),\n",
- " nn.Linear(64 * 7 * 7, 128),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.digit_head = nn.Linear(128, num_classes_digit)\n",
- " self.parity_head = nn.Linear(128, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.parity_head(features)\n",
- "\n",
- "print(\"✅ Convolutional Backbone with ReLU Defined\")\n",
- "\n",
- "# Simple Convolution Backbone 2 (with Adaptive Pooling)\n",
- "class SimpleConvMTL(nn.Module):\n",
- " def __init__(self, in_channels=1, num_classes_digit=10, num_classes_parity=2):\n",
- " super(SimpleConvMTL, self).__init__()\n",
- " self.backbone = nn.Sequential(\n",
- " nn.Conv2d(in_channels, 32, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.MaxPool2d(2),\n",
- " nn.Conv2d(32, 64, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.MaxPool2d(2),\n",
- " nn.Conv2d(64, 128, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.AdaptiveAvgPool2d(1),\n",
- " nn.Flatten()\n",
- " )\n",
- " feat_dim = 128\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " feat = self.backbone(x)\n",
- " return self.digit_head(feat), self.aux_head(feat)\n",
- "\n",
- "print(\"✅ Simple Convolutional Backbone with Adaptive Pooling Defined\")\n",
- "\n",
- "# FIXED: ConvNeXt V2 - Using correct input size (224x224)\n",
- "class ConvNeXtV2_MTL(nn.Module):\n",
- " def __init__(self, num_classes_digit=10, num_classes_parity=2):\n",
- " super(ConvNeXtV2_MTL, self).__init__()\n",
- " self.resize = nn.Upsample(size=(224, 224), mode='bilinear', align_corners=False)\n",
- " self.backbone = timm.create_model('convnextv2_tiny', pretrained=False, in_chans=1, num_classes=0)\n",
- " feat_dim = 768\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.resize(x)\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.aux_head(features)\n",
- "\n",
- "print(\"✅ ConvNeXtV2 defined (224x224)\")\n",
- "\n",
- "# FIXED: EfficientNetV2 - Using correct input size (224x224 for tiny/small)\n",
- "class EfficientNetV2_MTL(nn.Module):\n",
- " def __init__(self, variant='efficientnetv2_s', num_classes_digit=10, num_classes_parity=2):\n",
- " super(EfficientNetV2_MTL, self).__init__()\n",
- " self.resize = nn.Upsample(size=(224, 224), mode='bilinear', align_corners=False)\n",
- " self.backbone = timm.create_model(variant, pretrained=False, in_chans=1, num_classes=0)\n",
- "\n",
- " # Get correct feature dimension based on variant\n",
- " if 's' in variant:\n",
- " feat_dim = 1280\n",
- " elif 'm' in variant:\n",
- " feat_dim = 1280\n",
- " elif 'l' in variant:\n",
- " feat_dim = 1408\n",
- " else:\n",
- " feat_dim = 1280\n",
- "\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.resize(x)\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.aux_head(features)\n",
- "\n",
- "print(\"✅ EfficientNetV2 defined (224x224)\")\n",
- "\n",
- "# FIXED: Swin Transformer V2 - Using correct input size (256x256)\n",
- "class SwinV2_MTL(nn.Module):\n",
- " def __init__(self, variant='swinv2_tiny_window8_256', num_classes_digit=10, num_classes_parity=2):\n",
- " super(SwinV2_MTL, self).__init__()\n",
- " self.resize = nn.Upsample(size=(256, 256), mode='bilinear', align_corners=False)\n",
- " self.backbone = timm.create_model(variant, pretrained=False, in_chans=1, num_classes=0)\n",
- " feat_dim = 768\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.resize(x)\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.aux_head(features)\n",
- "\n",
- "print(\"✅ Swin Transformer V2 defined (256x256)\")\n",
- "\n",
- "# FIXED: ViT - Using correct input size (224x224)\n",
- "class ViT_MTL(nn.Module):\n",
- " def __init__(self, variant='vit_base_patch16_224', num_classes_digit=10, num_classes_parity=2):\n",
- " super(ViT_MTL, self).__init__()\n",
- " self.resize = nn.Upsample(size=(224, 224), mode='bilinear', align_corners=False)\n",
- " self.backbone = timm.create_model(variant, pretrained=False, in_chans=1, num_classes=0)\n",
- " feat_dim = self.backbone.num_features\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.resize(x)\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.aux_head(features)\n",
- "\n",
- "print(\"✅ ViT defined (224x224)\")\n",
- "\n",
- "# FIXED: CoAtNet - Using correct input size (224x224)\n",
- "class CoAtNet_MTL(nn.Module):\n",
- " def __init__(self, variant='coatnet_0_rw_224', num_classes_digit=10, num_classes_parity=2):\n",
- " super(CoAtNet_MTL, self).__init__()\n",
- " self.resize = nn.Upsample(size=(224, 224), mode='bilinear', align_corners=False)\n",
- " self.backbone = timm.create_model(variant, pretrained=False, in_chans=1, num_classes=0)\n",
- " feat_dim = self.backbone.num_features\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.resize(x)\n",
- " features = self.backbone(x)\n",
- " return self.digit_head(features), self.aux_head(features)\n",
- "\n",
- "print(\"✅ CoAtNet defined (224x224)\")\n",
- "\n",
- "# U-Net Style Encoder\n",
- "class UNetLikeEncoderMTL(nn.Module):\n",
- " def __init__(self, in_channels=1, num_classes_digit=10, num_classes_parity=2):\n",
- " super(UNetLikeEncoderMTL, self).__init__()\n",
- " self.enc1 = nn.Sequential(\n",
- " nn.Conv2d(in_channels, 64, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.Conv2d(64, 64, 3, padding=1),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.pool1 = nn.MaxPool2d(2)\n",
- " self.enc2 = nn.Sequential(\n",
- " nn.Conv2d(64, 128, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.Conv2d(128, 128, 3, padding=1),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.pool2 = nn.MaxPool2d(2)\n",
- " self.enc3 = nn.Sequential(\n",
- " nn.Conv2d(128, 256, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.Conv2d(256, 256, 3, padding=1),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.pool3 = nn.MaxPool2d(2)\n",
- " self.bottleneck = nn.Sequential(\n",
- " nn.Conv2d(256, 512, 3, padding=1),\n",
- " nn.ReLU(),\n",
- " nn.Conv2d(512, 512, 3, padding=1),\n",
- " nn.ReLU()\n",
- " )\n",
- " self.global_pool = nn.AdaptiveAvgPool2d(1)\n",
- " self.flatten = nn.Flatten()\n",
- " feat_dim = 512\n",
- " self.digit_head = nn.Linear(feat_dim, num_classes_digit)\n",
- " self.aux_head = nn.Linear(feat_dim, num_classes_parity)\n",
- "\n",
- " def forward(self, x):\n",
- " e1 = self.enc1(x)\n",
- " p1 = self.pool1(e1)\n",
- " e2 = self.enc2(p1)\n",
- " p2 = self.pool2(e2)\n",
- " e3 = self.enc3(p2)\n",
- " p3 = self.pool3(e3)\n",
- " bott = self.bottleneck(p3)\n",
- " feat = self.flatten(self.global_pool(bott))\n",
- " return self.digit_head(feat), self.aux_head(feat)\n",
- "\n",
- "print(\"✅ UNet Like Encoder Defined\")\n",
- "\n",
- "# ResNet Implementation\n",
- "def conv3x3(in_planes, out_planes, stride=1):\n",
- " return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,\n",
- " padding=1, bias=False)\n",
- "\n",
- "class BasicBlock(nn.Module):\n",
- " expansion = 1\n",
- "\n",
- " def __init__(self, inplanes, planes, stride=1, downsample=None):\n",
- " super(BasicBlock, self).__init__()\n",
- " self.conv1 = conv3x3(inplanes, planes, stride)\n",
- " self.bn1 = nn.BatchNorm2d(planes)\n",
- " self.relu = nn.ReLU(inplace=True)\n",
- " self.conv2 = conv3x3(planes, planes)\n",
- " self.bn2 = nn.BatchNorm2d(planes)\n",
- " self.downsample = downsample\n",
- " self.stride = stride\n",
- "\n",
- " def forward(self, x):\n",
- " identity = x\n",
- " out = self.conv1(x)\n",
- " out = self.bn1(out)\n",
- " out = self.relu(out)\n",
- " out = self.conv2(out)\n",
- " out = self.bn2(out)\n",
- "\n",
- " if self.downsample is not None:\n",
- " identity = self.downsample(x)\n",
- "\n",
- " out += identity\n",
- " out = self.relu(out)\n",
- " return out\n",
- "\n",
- "class ResNet(nn.Module):\n",
- " def __init__(self, block, layers, num_classes_digit=10, num_classes_parity=2):\n",
- " super(ResNet, self).__init__()\n",
- " self.inplanes = 64\n",
- "\n",
- " self.conv1 = nn.Conv2d(1, 64, kernel_size=3, stride=1, padding=1, bias=False)\n",
- " self.bn1 = nn.BatchNorm2d(64)\n",
- " self.relu = nn.ReLU(inplace=True)\n",
- "\n",
- " self.layer1 = self._make_layer(block, 64, layers[0])\n",
- " self.layer2 = self._make_layer(block, 128, layers[1], stride=2)\n",
- " self.layer3 = self._make_layer(block, 256, layers[2], stride=2)\n",
- " self.layer4 = self._make_layer(block, 512, layers[3], stride=2)\n",
- "\n",
- " self.avgpool = nn.AdaptiveAvgPool2d((1, 1))\n",
- " self.fc_features = nn.Linear(512 * block.expansion, 512)\n",
- "\n",
- " self.head_digit = nn.Linear(512, num_classes_digit)\n",
- " self.head_parity = nn.Linear(512, num_classes_parity)\n",
- "\n",
- " for m in self.modules():\n",
- " if isinstance(m, nn.Conv2d):\n",
- " nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')\n",
- " elif isinstance(m, nn.BatchNorm2d):\n",
- " nn.init.constant_(m.weight, 1)\n",
- " nn.init.constant_(m.bias, 0)\n",
- "\n",
- " def _make_layer(self, block, planes, blocks, stride=1):\n",
- " downsample = None\n",
- " if stride != 1 or self.inplanes != planes * block.expansion:\n",
- " downsample = nn.Sequential(\n",
- " nn.Conv2d(self.inplanes, planes * block.expansion,\n",
- " kernel_size=1, stride=stride, bias=False),\n",
- " nn.BatchNorm2d(planes * block.expansion),\n",
- " )\n",
- "\n",
- " layers = []\n",
- " layers.append(block(self.inplanes, planes, stride, downsample))\n",
- " self.inplanes = planes * block.expansion\n",
- " for _ in range(1, blocks):\n",
- " layers.append(block(self.inplanes, planes))\n",
- "\n",
- " return nn.Sequential(*layers)\n",
- "\n",
- " def forward(self, x):\n",
- " x = self.conv1(x)\n",
- " x = self.bn1(x)\n",
- " x = self.relu(x)\n",
- "\n",
- " x = self.layer1(x)\n",
- " x = self.layer2(x)\n",
- " x = self.layer3(x)\n",
- " x = self.layer4(x)\n",
- "\n",
- " x = self.avgpool(x)\n",
- " x = torch.flatten(x, 1)\n",
- " features = self.fc_features(x)\n",
- " features = F.relu(features)\n",
- "\n",
- " return self.head_digit(features), self.head_parity(features)\n",
- "\n",
- "def resnet18_mtl(**kwargs):\n",
- " return ResNet(BasicBlock, [2, 2, 2, 2], **kwargs)\n",
- "\n",
- "print(\"✅ ResNet-18 defined\")\n",
- "\n",
- "# ==================== DATA PREPARATION ====================\n",
- "\n",
- "transform = transforms.Compose([\n",
- " transforms.ToTensor(),\n",
- " transforms.Normalize((0.1307,), (0.3081,))\n",
- "])\n",
- "\n",
- "train_dataset = datasets.MNIST(root='./data', train=True, download=True, transform=transform)\n",
- "test_dataset = datasets.MNIST(root='./data', train=False, download=True, transform=transform)\n",
- "\n",
- "def get_parity_labels(labels):\n",
- " return (labels % 2).long()\n",
- "\n",
- "train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True)\n",
- "test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False)\n",
- "\n",
- "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
- "print(f\"\\n✅ Using device: {device}\")\n",
- "\n",
- "# ==================== TRAINING SETUP ====================\n",
- "\n",
- "# Define all models with corrected names\n",
- "models = OrderedDict([\n",
- " ('MTMShared', MTMShared()),\n",
- " ('SMTMConv', SMTMConv()),\n",
- " ('SimpleConvMTL', SimpleConvMTL()),\n",
- " ('ConvNeXtV2', ConvNeXtV2_MTL()),\n",
- " ('EfficientNetV2', EfficientNetV2_MTL()),\n",
- " ('SwinV2', SwinV2_MTL()),\n",
- " ('ViT', ViT_MTL()),\n",
- " ('CoAtNet', CoAtNet_MTL()),\n",
- " ('UNetLikeEncoder', UNetLikeEncoderMTL()),\n",
- " ('ResNet18', resnet18_mtl())\n",
- "])\n",
- "\n",
- "# Training function\n",
- "def train_model(model, train_loader, num_epochs=2):\n",
- " model = model.to(device)\n",
- " criterion = nn.CrossEntropyLoss()\n",
- " optimizer = optim.Adam(model.parameters(), lr=0.001)\n",
- "\n",
- " model.train()\n",
- " for epoch in range(num_epochs):\n",
- " total_loss = 0\n",
- " for batch_idx, (images, digit_labels) in enumerate(train_loader):\n",
- " images, digit_labels = images.to(device), digit_labels.to(device)\n",
- " parity_labels = get_parity_labels(digit_labels)\n",
- "\n",
- " optimizer.zero_grad()\n",
- " digit_pred, parity_pred = model(images)\n",
- "\n",
- " loss_digit = criterion(digit_pred, digit_labels)\n",
- " loss_parity = criterion(parity_pred, parity_labels)\n",
- " loss = loss_digit + loss_parity\n",
- "\n",
- " loss.backward()\n",
- " optimizer.step()\n",
- " total_loss += loss.item()\n",
- "\n",
- " if batch_idx % 100 == 0:\n",
- " print(f\" Batch {batch_idx}/{len(train_loader)}, Loss: {loss.item():.4f}\")\n",
- "\n",
- " print(f\" Epoch {epoch+1}/{num_epochs}, Avg Loss: {total_loss / len(train_loader):.4f}\")\n",
- "\n",
- " return model\n",
- "\n",
- "# Evaluation function\n",
- "def evaluate_model(model, test_loader):\n",
- " model.eval()\n",
- " correct_digit, correct_parity, total = 0, 0, 0\n",
- "\n",
- " with torch.no_grad():\n",
- " for images, digit_labels in test_loader:\n",
- " images, digit_labels = images.to(device), digit_labels.to(device)\n",
- " parity_labels = get_parity_labels(digit_labels)\n",
- "\n",
- " digit_pred, parity_pred = model(images)\n",
- "\n",
- " correct_digit += (digit_pred.argmax(1) == digit_labels).sum().item()\n",
- " correct_parity += (parity_pred.argmax(1) == parity_labels).sum().item()\n",
- " total += digit_labels.size(0)\n",
- "\n",
- " digit_accuracy = 100.0 * correct_digit / total\n",
- " parity_accuracy = 100.0 * correct_parity / total\n",
- "\n",
- " return digit_accuracy, parity_accuracy\n",
- "\n",
- "# ==================== TRAINING LOOP ====================\n",
- "\n",
- "print(\"\\n\" + \"=\"*60)\n",
- "print(\"TRAINING AND EVALUATING MODELS\")\n",
- "print(\"=\"*60)\n",
- "\n",
- "model_names = []\n",
- "digit_accuracies = []\n",
- "parity_accuracies = []\n",
- "\n",
- "for name, model in models.items():\n",
- " print(f\"\\n{'='*50}\")\n",
- " print(f\"Training {name}\")\n",
- " print(f\"{'='*50}\")\n",
- "\n",
- " try:\n",
- " # Train model\n",
- " trained_model = train_model(model, train_loader, num_epochs=2)\n",
- "\n",
- " # Evaluate model\n",
- " digit_acc, parity_acc = evaluate_model(trained_model, test_loader)\n",
- "\n",
- " print(f\"\\n✅ Results for {name}:\")\n",
- " print(f\" Digit Accuracy: {digit_acc:.2f}%\")\n",
- " print(f\" Parity Accuracy: {parity_acc:.2f}%\")\n",
- "\n",
- " # Store results\n",
- " model_names.append(name)\n",
- " digit_accuracies.append(digit_acc)\n",
- " parity_accuracies.append(parity_acc)\n",
- "\n",
- " except Exception as e:\n",
- " print(f\"❌ Error training {name}: {str(e)}\")\n",
- " model_names.append(name)\n",
- " digit_accuracies.append(0.0)\n",
- " parity_accuracies.append(0.0)\n",
- "\n",
- "# ==================== RESULTS VISUALIZATION ====================\n",
- "\n",
- "# Create results DataFrame\n",
- "data = {\n",
- " 'Model': model_names,\n",
- " 'Digit Accuracy': digit_accuracies,\n",
- " 'Parity Accuracy': parity_accuracies\n",
- "}\n",
- "\n",
- "df_accuracies = pd.DataFrame(data)\n",
- "print(\"\\n\" + \"=\"*60)\n",
- "print(\"RESULTS SUMMARY\")\n",
- "print(\"=\"*60)\n",
- "print(df_accuracies.to_string(index=False))\n",
- "\n",
- "# Create comparison bar chart\n",
- "if len(model_names) > 0:\n",
- " plt.figure(figsize=(15, 8))\n",
- "\n",
- " x = np.arange(len(model_names))\n",
- " width = 0.35\n",
- "\n",
- " fig, ax = plt.subplots(figsize=(15, 8))\n",
- " rects1 = ax.bar(x - width/2, digit_accuracies, width, label='Digit Accuracy', color='skyblue')\n",
- " rects2 = ax.bar(x + width/2, parity_accuracies, width, label='Parity Accuracy', color='lightcoral')\n",
- "\n",
- " ax.set_xlabel('Model', fontsize=12)\n",
- " ax.set_ylabel('Accuracy (%)', fontsize=12)\n",
- " ax.set_title('Comparison of Digit and Parity Accuracies by Model', fontsize=14, fontweight='bold')\n",
- " ax.set_xticks(x)\n",
- " ax.set_xticklabels(model_names, rotation=45, ha='right', fontsize=10)\n",
- " ax.legend(fontsize=11)\n",
- " ax.set_ylim(0, 105)\n",
- " ax.grid(True, axis='y', alpha=0.3)\n",
- "\n",
- " def autolabel(rects):\n",
- " for rect in rects:\n",
- " height = rect.get_height()\n",
- " ax.annotate(f'{height:.1f}%',\n",
- " xy=(rect.get_x() + rect.get_width() / 2, height),\n",
- " xytext=(0, 3),\n",
- " textcoords=\"offset points\",\n",
- " ha='center', va='bottom', fontsize=8)\n",
- "\n",
- " autolabel(rects1)\n",
- " autolabel(rects2)\n",
- "\n",
- " plt.tight_layout()\n",
- " plt.savefig(os.path.join(save_dir, 'model_accuracy_comparison.png'), dpi=150, bbox_inches='tight')\n",
- " plt.show()\n",
- "\n",
- "# Visualize sample prediction\n",
- "if len(models) > 0:\n",
- " first_model_name = list(models.keys())[0]\n",
- " first_model = models[first_model_name].to(device)\n",
- "\n",
- " images, digit_labels = next(iter(test_loader))\n",
- " images, digit_labels = images.to(device), digit_labels.to(device)\n",
- "\n",
- " first_model.eval()\n",
- " with torch.no_grad():\n",
- " digit_pred, parity_pred = first_model(images)\n",
- "\n",
- " sample_img = images[0].cpu().squeeze().numpy()\n",
- " plt.figure(figsize=(8, 6))\n",
- " plt.imshow(sample_img, cmap='gray')\n",
- "\n",
- " true_digit = digit_labels[0].item()\n",
- " pred_digit = digit_pred[0].argmax().item()\n",
- " true_parity = 'Even' if true_digit % 2 == 0 else 'Odd'\n",
- " pred_parity = 'Even' if parity_pred[0].argmax().item() == 0 else 'Odd'\n",
- "\n",
- " plt.title(f\"Model: {first_model_name}\\n\"\n",
- " f\"True Digit: {true_digit}, Predicted: {pred_digit}\\n\"\n",
- " f\"True Parity: {true_parity}, Predicted: {pred_parity}\")\n",
- " plt.axis('off')\n",
- " plt.tight_layout()\n",
- " plt.savefig(os.path.join(save_dir, 'sample_prediction.png'))\n",
- " plt.show()\n",
- "\n",
- "print(f\"\\n✅ Results saved to: {save_dir}\")\n",
- "print(\"\\n✅ Training and evaluation completed successfully!\")"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 7617
- },
- "id": "CjlwL4I4x0HB",
- "outputId": "24111d17-3b53-4022-89d6-939c95952db6"
- },
- "execution_count": 1,
- "outputs": [
- {
- "output_type": "stream",
- "name": "stderr",
- "text": [
- "100%|██████████| 9.91M/9.91M [00:00<00:00, 59.1MB/s]\n",
- "100%|██████████| 28.9k/28.9k [00:00<00:00, 1.62MB/s]\n",
- "100%|██████████| 1.65M/1.65M [00:00<00:00, 14.5MB/s]\n",
- "100%|██████████| 4.54k/4.54k [00:00<00:00, 7.60MB/s]\n"
- ]
- },
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "####Train Data MNIST#####\n",
- "Type: Generated on: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
\n", - "\n", - "Dataset: MNIST (28x28 grayscale images)
\n", - "Tasks: Digit Classification (10 classes) + Parity Classification (Even/Odd)
\n", - "Number of Models: {len(model_names) if 'model_names' in globals() else 'N/A'}
\n", - "Device: {device}
\n", - "No results available
'}\n", - "\n", - "![\"Accuracy](\"model_accuracy_comparison.png\")
\n",
- " | \n", + " | HAEMATOCRIT | \n", + "HAEMOGLOBINS | \n", + "ERYTHROCYTE | \n", + "LEUCOCYTE | \n", + "THROMBOCYTE | \n", + "MCH | \n", + "MCHC | \n", + "MCV | \n", + "AGE | \n", + "SEX | \n", + "SOURCE | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "35.1 | \n", + "11.8 | \n", + "4.65 | \n", + "6.3 | \n", + "310 | \n", + "25.4 | \n", + "33.6 | \n", + "75.5 | \n", + "1 | \n", + "F | \n", + "out | \n", + "
| 1 | \n", + "43.5 | \n", + "14.8 | \n", + "5.39 | \n", + "12.7 | \n", + "334 | \n", + "27.5 | \n", + "34.0 | \n", + "80.7 | \n", + "1 | \n", + "F | \n", + "out | \n", + "
| 2 | \n", + "33.5 | \n", + "11.3 | \n", + "4.74 | \n", + "13.2 | \n", + "305 | \n", + "23.8 | \n", + "33.7 | \n", + "70.7 | \n", + "1 | \n", + "F | \n", + "out | \n", + "
| 3 | \n", + "39.1 | \n", + "13.7 | \n", + "4.98 | \n", + "10.5 | \n", + "366 | \n", + "27.5 | \n", + "35.0 | \n", + "78.5 | \n", + "1 | \n", + "F | \n", + "out | \n", + "
| 4 | \n", + "30.9 | \n", + "9.9 | \n", + "4.23 | \n", + "22.1 | \n", + "333 | \n", + "23.4 | \n", + "32.0 | \n", + "73.0 | \n", + "1 | \n", + "M | \n", + "out | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 4407 | \n", + "32.8 | \n", + "10.4 | \n", + "3.49 | \n", + "8.1 | \n", + "72 | \n", + "29.8 | \n", + "31.7 | \n", + "94.0 | \n", + "92 | \n", + "F | \n", + "in | \n", + "
| 4408 | \n", + "33.7 | \n", + "10.8 | \n", + "3.67 | \n", + "6.7 | \n", + "70 | \n", + "29.4 | \n", + "32.0 | \n", + "91.8 | \n", + "92 | \n", + "F | \n", + "in | \n", + "
| 4409 | \n", + "33.2 | \n", + "11.2 | \n", + "3.47 | \n", + "7.2 | \n", + "235 | \n", + "32.3 | \n", + "33.7 | \n", + "95.7 | \n", + "93 | \n", + "F | \n", + "out | \n", + "
| 4410 | \n", + "31.5 | \n", + "10.4 | \n", + "3.15 | \n", + "9.1 | \n", + "187 | \n", + "33.0 | \n", + "33.0 | \n", + "100.0 | \n", + "98 | \n", + "F | \n", + "in | \n", + "
| 4411 | \n", + "33.5 | \n", + "10.9 | \n", + "3.44 | \n", + "5.8 | \n", + "275 | \n", + "31.7 | \n", + "32.5 | \n", + "97.4 | \n", + "99 | \n", + "F | \n", + "out | \n", + "
4412 rows × 11 columns
\n", + "| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "source | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "1 | \n", + "35.1 | \n", + "11.8 | \n", + "4.65 | \n", + "6.3 | \n", + "310 | \n", + "25.4 | \n", + "33.6 | \n", + "75.5 | \n", + "out | \n", + "
| 1 | \n", + "1 | \n", + "43.5 | \n", + "14.8 | \n", + "5.39 | \n", + "12.7 | \n", + "334 | \n", + "27.5 | \n", + "34.0 | \n", + "80.7 | \n", + "out | \n", + "
| 2 | \n", + "1 | \n", + "33.5 | \n", + "11.3 | \n", + "4.74 | \n", + "13.2 | \n", + "305 | \n", + "23.8 | \n", + "33.7 | \n", + "70.7 | \n", + "out | \n", + "
| 3 | \n", + "1 | \n", + "39.1 | \n", + "13.7 | \n", + "4.98 | \n", + "10.5 | \n", + "366 | \n", + "27.5 | \n", + "35.0 | \n", + "78.5 | \n", + "out | \n", + "
| 4 | \n", + "1 | \n", + "30.9 | \n", + "9.9 | \n", + "4.23 | \n", + "22.1 | \n", + "333 | \n", + "23.4 | \n", + "32.0 | \n", + "73.0 | \n", + "out | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 4407 | \n", + "92 | \n", + "32.8 | \n", + "10.4 | \n", + "3.49 | \n", + "8.1 | \n", + "72 | \n", + "29.8 | \n", + "31.7 | \n", + "94.0 | \n", + "in | \n", + "
| 4408 | \n", + "92 | \n", + "33.7 | \n", + "10.8 | \n", + "3.67 | \n", + "6.7 | \n", + "70 | \n", + "29.4 | \n", + "32.0 | \n", + "91.8 | \n", + "in | \n", + "
| 4409 | \n", + "93 | \n", + "33.2 | \n", + "11.2 | \n", + "3.47 | \n", + "7.2 | \n", + "235 | \n", + "32.3 | \n", + "33.7 | \n", + "95.7 | \n", + "out | \n", + "
| 4410 | \n", + "98 | \n", + "31.5 | \n", + "10.4 | \n", + "3.15 | \n", + "9.1 | \n", + "187 | \n", + "33.0 | \n", + "33.0 | \n", + "100.0 | \n", + "in | \n", + "
| 4411 | \n", + "99 | \n", + "33.5 | \n", + "10.9 | \n", + "3.44 | \n", + "5.8 | \n", + "275 | \n", + "31.7 | \n", + "32.5 | \n", + "97.4 | \n", + "out | \n", + "
4412 rows × 10 columns
\n", + "| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| age | \n", + "1.000000 | \n", + "-0.256384 | \n", + "-0.246294 | \n", + "-0.425167 | \n", + "0.218915 | \n", + "0.008661 | \n", + "0.390483 | \n", + "0.013401 | \n", + "0.422861 | \n", + "
| haematocrit | \n", + "-0.256384 | \n", + "1.000000 | \n", + "0.975507 | \n", + "0.865635 | \n", + "-0.189172 | \n", + "-0.006640 | \n", + "0.061793 | \n", + "0.114275 | \n", + "0.032718 | \n", + "
| haemoglobins | \n", + "-0.246294 | \n", + "0.975507 | \n", + "1.000000 | \n", + "0.826160 | \n", + "-0.187054 | \n", + "-0.039613 | \n", + "0.155858 | \n", + "0.303282 | \n", + "0.054590 | \n", + "
| erythrocyte | \n", + "-0.425167 | \n", + "0.865635 | \n", + "0.826160 | \n", + "1.000000 | \n", + "-0.171997 | \n", + "0.040957 | \n", + "-0.341033 | \n", + "0.013233 | \n", + "-0.403894 | \n", + "
| leucocyte | \n", + "0.218915 | \n", + "-0.189172 | \n", + "-0.187054 | \n", + "-0.171997 | \n", + "1.000000 | \n", + "0.358341 | \n", + "-0.002554 | \n", + "-0.007933 | \n", + "0.002358 | \n", + "
| thrombocyte | \n", + "0.008661 | \n", + "-0.006640 | \n", + "-0.039613 | \n", + "0.040957 | \n", + "0.358341 | \n", + "1.000000 | \n", + "-0.134679 | \n", + "-0.175218 | \n", + "-0.072532 | \n", + "
| mch | \n", + "0.390483 | \n", + "0.061793 | \n", + "0.155858 | \n", + "-0.341033 | \n", + "-0.002554 | \n", + "-0.134679 | \n", + "1.000000 | \n", + "0.487823 | \n", + "0.893668 | \n", + "
| mchc | \n", + "0.013401 | \n", + "0.114275 | \n", + "0.303282 | \n", + "0.013233 | \n", + "-0.007933 | \n", + "-0.175218 | \n", + "0.487823 | \n", + "1.000000 | \n", + "0.115496 | \n", + "
| mcv | \n", + "0.422861 | \n", + "0.032718 | \n", + "0.054590 | \n", + "-0.403894 | \n", + "0.002358 | \n", + "-0.072532 | \n", + "0.893668 | \n", + "0.115496 | \n", + "1.000000 | \n", + "
| source | \n", + "in | \n", + "All | \n", + "out | \n", + "All | \n", + "
|---|---|---|---|---|
| age | \n", + "88335.00 | \n", + "88335.00 | \n", + "117381.00 | \n", + "117381.00 | \n", + "
| erythrocyte | \n", + "7707.77 | \n", + "7707.77 | \n", + "12328.27 | \n", + "12328.27 | \n", + "
| haematocrit | \n", + "64636.70 | \n", + "64636.70 | \n", + "103891.50 | \n", + "103891.50 | \n", + "
| haemoglobins | \n", + "21579.40 | \n", + "21579.40 | \n", + "34637.10 | \n", + "34637.10 | \n", + "
| leucocyte | \n", + "17055.50 | \n", + "17055.50 | \n", + "21411.00 | \n", + "21411.00 | \n", + "
| mch | \n", + "50293.70 | \n", + "50293.70 | \n", + "74277.80 | \n", + "74277.80 | \n", + "
| mchc | \n", + "59531.10 | \n", + "59531.10 | \n", + "87578.40 | \n", + "87578.40 | \n", + "
| mcv | \n", + "150615.00 | \n", + "150615.00 | \n", + "222697.30 | \n", + "222697.30 | \n", + "
| thrombocyte | \n", + "399413.00 | \n", + "399413.00 | \n", + "736785.00 | \n", + "736785.00 | \n", + "
| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "1 | \n", + "35.1 | \n", + "11.8 | \n", + "4.65 | \n", + "6.3 | \n", + "310 | \n", + "25.4 | \n", + "33.6 | \n", + "75.5 | \n", + "
| 1 | \n", + "1 | \n", + "43.5 | \n", + "14.8 | \n", + "5.39 | \n", + "12.7 | \n", + "334 | \n", + "27.5 | \n", + "34.0 | \n", + "80.7 | \n", + "
| 2 | \n", + "1 | \n", + "33.5 | \n", + "11.3 | \n", + "4.74 | \n", + "13.2 | \n", + "305 | \n", + "23.8 | \n", + "33.7 | \n", + "70.7 | \n", + "
| 3 | \n", + "1 | \n", + "39.1 | \n", + "13.7 | \n", + "4.98 | \n", + "10.5 | \n", + "366 | \n", + "27.5 | \n", + "35.0 | \n", + "78.5 | \n", + "
| 4 | \n", + "1 | \n", + "30.9 | \n", + "9.9 | \n", + "4.23 | \n", + "22.1 | \n", + "333 | \n", + "23.4 | \n", + "32.0 | \n", + "73.0 | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 4407 | \n", + "92 | \n", + "32.8 | \n", + "10.4 | \n", + "3.49 | \n", + "8.1 | \n", + "72 | \n", + "29.8 | \n", + "31.7 | \n", + "94.0 | \n", + "
| 4408 | \n", + "92 | \n", + "33.7 | \n", + "10.8 | \n", + "3.67 | \n", + "6.7 | \n", + "70 | \n", + "29.4 | \n", + "32.0 | \n", + "91.8 | \n", + "
| 4409 | \n", + "93 | \n", + "33.2 | \n", + "11.2 | \n", + "3.47 | \n", + "7.2 | \n", + "235 | \n", + "32.3 | \n", + "33.7 | \n", + "95.7 | \n", + "
| 4410 | \n", + "98 | \n", + "31.5 | \n", + "10.4 | \n", + "3.15 | \n", + "9.1 | \n", + "187 | \n", + "33.0 | \n", + "33.0 | \n", + "100.0 | \n", + "
| 4411 | \n", + "99 | \n", + "33.5 | \n", + "10.9 | \n", + "3.44 | \n", + "5.8 | \n", + "275 | \n", + "31.7 | \n", + "32.5 | \n", + "97.4 | \n", + "
4412 rows × 9 columns
\n", + "| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| 4407 | \n", + "2.087942 | \n", + "-0.903411 | \n", + "-1.125883 | \n", + "-1.340737 | \n", + "-0.122520 | \n", + "-1.627802 | \n", + "0.585675 | \n", + "-1.337258 | \n", + "1.368555 | \n", + "
| 4408 | \n", + "2.087942 | \n", + "-0.752778 | \n", + "-0.933566 | \n", + "-1.111172 | \n", + "-0.399800 | \n", + "-1.645350 | \n", + "0.436011 | \n", + "-1.093091 | \n", + "1.047813 | \n", + "
| 4409 | \n", + "2.133959 | \n", + "-0.836463 | \n", + "-0.741250 | \n", + "-1.366244 | \n", + "-0.300772 | \n", + "-0.197631 | \n", + "1.521080 | \n", + "0.290525 | \n", + "1.616401 | \n", + "
| 4410 | \n", + "2.364043 | \n", + "-1.120992 | \n", + "-1.125883 | \n", + "-1.774360 | \n", + "0.075537 | \n", + "-0.618786 | \n", + "1.782994 | \n", + "-0.279199 | \n", + "2.243305 | \n", + "
| 4411 | \n", + "2.410059 | \n", + "-0.786252 | \n", + "-0.885487 | \n", + "-1.404505 | \n", + "-0.578052 | \n", + "0.153331 | \n", + "1.296583 | \n", + "-0.686145 | \n", + "1.864247 | \n", + "
| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "1 | \n", + "35.1 | \n", + "11.8 | \n", + "4.65 | \n", + "6.3 | \n", + "310 | \n", + "25.4 | \n", + "33.6 | \n", + "75.5 | \n", + "
| 1 | \n", + "1 | \n", + "43.5 | \n", + "14.8 | \n", + "5.39 | \n", + "12.7 | \n", + "334 | \n", + "27.5 | \n", + "34.0 | \n", + "80.7 | \n", + "
| 2 | \n", + "1 | \n", + "33.5 | \n", + "11.3 | \n", + "4.74 | \n", + "13.2 | \n", + "305 | \n", + "23.8 | \n", + "33.7 | \n", + "70.7 | \n", + "
| 3 | \n", + "1 | \n", + "39.1 | \n", + "13.7 | \n", + "4.98 | \n", + "10.5 | \n", + "366 | \n", + "27.5 | \n", + "35.0 | \n", + "78.5 | \n", + "
| 4 | \n", + "1 | \n", + "30.9 | \n", + "9.9 | \n", + "4.23 | \n", + "22.1 | \n", + "333 | \n", + "23.4 | \n", + "32.0 | \n", + "73.0 | \n", + "
| 5 | \n", + "1 | \n", + "34.3 | \n", + "11.6 | \n", + "4.53 | \n", + "6.6 | \n", + "185 | \n", + "25.6 | \n", + "33.8 | \n", + "75.7 | \n", + "
| 6 | \n", + "1 | \n", + "31.1 | \n", + "8.7 | \n", + "5.06 | \n", + "11.1 | \n", + "416 | \n", + "17.2 | \n", + "28.0 | \n", + "61.5 | \n", + "
| 7 | \n", + "1 | \n", + "40.3 | \n", + "13.3 | \n", + "4.73 | \n", + "8.1 | \n", + "257 | \n", + "28.1 | \n", + "33.0 | \n", + "85.2 | \n", + "
| 8 | \n", + "1 | \n", + "33.6 | \n", + "11.5 | \n", + "4.54 | \n", + "11.4 | \n", + "262 | \n", + "25.3 | \n", + "34.2 | \n", + "74.0 | \n", + "
| 9 | \n", + "1 | \n", + "35.4 | \n", + "11.4 | \n", + "4.80 | \n", + "2.6 | \n", + "183 | \n", + "23.8 | \n", + "32.2 | \n", + "73.8 | \n", + "
| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| 4402 | \n", + "92 | \n", + "29.1 | \n", + "9.5 | \n", + "3.24 | \n", + "8.9 | \n", + "116 | \n", + "29.3 | \n", + "32.6 | \n", + "89.8 | \n", + "
| 4403 | \n", + "92 | \n", + "28.3 | \n", + "9.4 | \n", + "3.08 | \n", + "7.5 | \n", + "105 | \n", + "30.5 | \n", + "33.2 | \n", + "91.9 | \n", + "
| 4404 | \n", + "92 | \n", + "31.9 | \n", + "10.3 | \n", + "3.42 | \n", + "8.7 | \n", + "110 | \n", + "30.1 | \n", + "32.3 | \n", + "93.3 | \n", + "
| 4405 | \n", + "92 | \n", + "28.3 | \n", + "9.2 | \n", + "3.03 | \n", + "8.4 | \n", + "100 | \n", + "30.4 | \n", + "32.5 | \n", + "93.4 | \n", + "
| 4406 | \n", + "92 | \n", + "33.7 | \n", + "10.4 | \n", + "3.48 | \n", + "11.4 | \n", + "112 | \n", + "29.9 | \n", + "30.9 | \n", + "96.8 | \n", + "
| 4407 | \n", + "92 | \n", + "32.8 | \n", + "10.4 | \n", + "3.49 | \n", + "8.1 | \n", + "72 | \n", + "29.8 | \n", + "31.7 | \n", + "94.0 | \n", + "
| 4408 | \n", + "92 | \n", + "33.7 | \n", + "10.8 | \n", + "3.67 | \n", + "6.7 | \n", + "70 | \n", + "29.4 | \n", + "32.0 | \n", + "91.8 | \n", + "
| 4409 | \n", + "93 | \n", + "33.2 | \n", + "11.2 | \n", + "3.47 | \n", + "7.2 | \n", + "235 | \n", + "32.3 | \n", + "33.7 | \n", + "95.7 | \n", + "
| 4410 | \n", + "98 | \n", + "31.5 | \n", + "10.4 | \n", + "3.15 | \n", + "9.1 | \n", + "187 | \n", + "33.0 | \n", + "33.0 | \n", + "100.0 | \n", + "
| 4411 | \n", + "99 | \n", + "33.5 | \n", + "10.9 | \n", + "3.44 | \n", + "5.8 | \n", + "275 | \n", + "31.7 | \n", + "32.5 | \n", + "97.4 | \n", + "
| \n", + " | age | \n", + "haematocrit | \n", + "haemoglobins | \n", + "erythrocyte | \n", + "leucocyte | \n", + "thrombocyte | \n", + "mch | \n", + "mchc | \n", + "mcv | \n", + "source | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 1 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 3 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 5 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 7 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 4406 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 4407 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 4408 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 4409 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
| 4411 | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "False | \n", + "
3693 rows × 10 columns
\n", + "| \n", + " | cross_references | \n", + "organism | \n", + "pref_name | \n", + "score | \n", + "species_group_flag | \n", + "target_chembl_id | \n", + "target_components | \n", + "target_type | \n", + "tax_id | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "[{'xref_id': 'P11511', 'xref_name': None, 'xre... | \n", + "Homo sapiens | \n", + "Cytochrome P450 19A1 | \n", + "19.0 | \n", + "False | \n", + "CHEMBL1978 | \n", + "[{'accession': 'P11511', 'component_descriptio... | \n", + "SINGLE PROTEIN | \n", + "9606 | \n", + "
| 1 | \n", + "[{'xref_id': 'P22443', 'xref_name': None, 'xre... | \n", + "Rattus norvegicus | \n", + "Cytochrome P450 19A1 | \n", + "19.0 | \n", + "False | \n", + "CHEMBL3859 | \n", + "[{'accession': 'P22443', 'component_descriptio... | \n", + "SINGLE PROTEIN | \n", + "10116 | \n", + "
| \n", + " | activity_comment | \n", + "activity_id | \n", + "activity_properties | \n", + "assay_chembl_id | \n", + "assay_description | \n", + "assay_type | \n", + "bao_endpoint | \n", + "bao_format | \n", + "bao_label | \n", + "canonical_smiles | \n", + "data_validity_comment | \n", + "data_validity_description | \n", + "document_chembl_id | \n", + "document_journal | \n", + "document_year | \n", + "ligand_efficiency | \n", + "molecule_chembl_id | \n", + "molecule_pref_name | \n", + "parent_molecule_chembl_id | \n", + "pchembl_value | \n", + "potential_duplicate | \n", + "qudt_units | \n", + "record_id | \n", + "relation | \n", + "src_id | \n", + "standard_flag | \n", + "standard_relation | \n", + "standard_text_value | \n", + "standard_type | \n", + "standard_units | \n", + "standard_upper_value | \n", + "standard_value | \n", + "target_chembl_id | \n", + "target_organism | \n", + "target_pref_name | \n", + "target_tax_id | \n", + "text_value | \n", + "toid | \n", + "type | \n", + "units | \n", + "uo_units | \n", + "upper_value | \n", + "value | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "None | \n", + "1480935 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "Cc1noc(C)c1CN1C(=O)C(=O)c2cc(C#N)ccc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '18.28', 'le': '0.33', 'lle': '3.25', ... | \n", + "CHEMBL187579 | \n", + "None | \n", + "CHEMBL187579 | \n", + "5.14 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384103 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "7200.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "7.2 | \n", + "
| 1 | \n", + "None | \n", + "1480936 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(Cc2ccc(F)cc2Cl)c2ccc(I)cc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '12.10', 'le': '0.33', 'lle': '1.22', ... | \n", + "CHEMBL188487 | \n", + "None | \n", + "CHEMBL188487 | \n", + "5.03 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "383984 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "9400.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "9.4 | \n", + "
| 2 | \n", + "None | \n", + "1481061 | \n", + "[] | \n", + "CHEMBL830868 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(CC2COc3ccccc3O2)c2ccc(I)cc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '11.56', 'le': '0.29', 'lle': '2.21', ... | \n", + "CHEMBL185698 | \n", + "None | \n", + "CHEMBL185698 | \n", + "4.87 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384106 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "13500.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "13.5 | \n", + "
| \n", + " | activity_comment | \n", + "activity_id | \n", + "activity_properties | \n", + "assay_chembl_id | \n", + "assay_description | \n", + "assay_type | \n", + "bao_endpoint | \n", + "bao_format | \n", + "bao_label | \n", + "canonical_smiles | \n", + "data_validity_comment | \n", + "data_validity_description | \n", + "document_chembl_id | \n", + "document_journal | \n", + "document_year | \n", + "ligand_efficiency | \n", + "molecule_chembl_id | \n", + "molecule_pref_name | \n", + "parent_molecule_chembl_id | \n", + "pchembl_value | \n", + "potential_duplicate | \n", + "qudt_units | \n", + "record_id | \n", + "relation | \n", + "src_id | \n", + "standard_flag | \n", + "standard_relation | \n", + "standard_text_value | \n", + "standard_type | \n", + "standard_units | \n", + "standard_upper_value | \n", + "standard_value | \n", + "target_chembl_id | \n", + "target_organism | \n", + "target_pref_name | \n", + "target_tax_id | \n", + "text_value | \n", + "toid | \n", + "type | \n", + "units | \n", + "uo_units | \n", + "upper_value | \n", + "value | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "None | \n", + "1480935 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "Cc1noc(C)c1CN1C(=O)C(=O)c2cc(C#N)ccc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '18.28', 'le': '0.33', 'lle': '3.25', ... | \n", + "CHEMBL187579 | \n", + "None | \n", + "CHEMBL187579 | \n", + "5.14 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384103 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "7200.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "7.2 | \n", + "
| 1 | \n", + "None | \n", + "1480936 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(Cc2ccc(F)cc2Cl)c2ccc(I)cc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '12.10', 'le': '0.33', 'lle': '1.22', ... | \n", + "CHEMBL188487 | \n", + "None | \n", + "CHEMBL188487 | \n", + "5.03 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "383984 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "9400.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "9.4 | \n", + "
| 2 | \n", + "None | \n", + "1481061 | \n", + "[] | \n", + "CHEMBL830868 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(CC2COc3ccccc3O2)c2ccc(I)cc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '11.56', 'le': '0.29', 'lle': '2.21', ... | \n", + "CHEMBL185698 | \n", + "None | \n", + "CHEMBL185698 | \n", + "4.87 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384106 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "13500.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "13.5 | \n", + "
| 3 | \n", + "None | \n", + "1481065 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2ccccc21 | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '16.64', 'le': '0.32', 'lle': '1.25', ... | \n", + "CHEMBL426082 | \n", + "None | \n", + "CHEMBL426082 | \n", + "4.88 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384075 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "13110.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "13.11 | \n", + "
| 4 | \n", + "None | \n", + "1481066 | \n", + "[] | \n", + "CHEMBL829584 | \n", + "In vitro inhibitory concentration against SARS... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000357 | \n", + "single protein format | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2c1cccc2[N+](=O)[O-] | \n", + "None | \n", + "None | \n", + "CHEMBL1139624 | \n", + "Bioorg. Med. Chem. Lett. | \n", + "2005 | \n", + "{'bei': '16.84', 'le': '0.32', 'lle': '2.16', ... | \n", + "CHEMBL187717 | \n", + "None | \n", + "CHEMBL187717 | \n", + "5.70 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "384234 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "2000.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "2.0 | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 128 | \n", + "None | \n", + "12041507 | \n", + "[] | \n", + "CHEMBL2150313 | \n", + "Inhibition of SARS-CoV PLpro expressed in Esch... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000019 | \n", + "assay format | \n", + "COC(=O)[C@@]1(C)CCCc2c1ccc1c2C(=O)C(=O)c2c(C)c... | \n", + "None | \n", + "None | \n", + "CHEMBL2146458 | \n", + "Bioorg. Med. Chem. | \n", + "2012 | \n", + "{'bei': '14.70', 'le': '0.27', 'lle': '1.57', ... | \n", + "CHEMBL2146517 | \n", + "METHYL TANSHINONATE | \n", + "CHEMBL2146517 | \n", + "4.97 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "1727226 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "10600.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "10.6 | \n", + "
| 129 | \n", + "None | \n", + "12041508 | \n", + "[] | \n", + "CHEMBL2150313 | \n", + "Inhibition of SARS-CoV PLpro expressed in Esch... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000019 | \n", + "assay format | \n", + "C[C@H]1COC2=C1C(=O)C(=O)c1c2ccc2c1CCCC2(C)C | \n", + "None | \n", + "None | \n", + "CHEMBL2146458 | \n", + "Bioorg. Med. Chem. | \n", + "2012 | \n", + "{'bei': '16.86', 'le': '0.31', 'lle': '1.56', ... | \n", + "CHEMBL187460 | \n", + "CRYPTOTANSHINONE | \n", + "CHEMBL187460 | \n", + "5.00 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "1727227 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "10100.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "10.1 | \n", + "
| 130 | \n", + "None | \n", + "12041509 | \n", + "[] | \n", + "CHEMBL2150313 | \n", + "Inhibition of SARS-CoV PLpro expressed in Esch... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000019 | \n", + "assay format | \n", + "Cc1coc2c1C(=O)C(=O)c1c-2ccc2c(C)cccc12 | \n", + "None | \n", + "None | \n", + "CHEMBL2146458 | \n", + "Bioorg. Med. Chem. | \n", + "2012 | \n", + "{'bei': '17.88', 'le': '0.32', 'lle': '0.84', ... | \n", + "CHEMBL363535 | \n", + "TANSHINONE I | \n", + "CHEMBL363535 | \n", + "4.94 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "1727228 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "11500.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "11.5 | \n", + "
| 131 | \n", + "None | \n", + "12041510 | \n", + "[] | \n", + "CHEMBL2150313 | \n", + "Inhibition of SARS-CoV PLpro expressed in Esch... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000019 | \n", + "assay format | \n", + "Cc1cccc2c3c(ccc12)C1=C(C(=O)C3=O)[C@@H](C)CO1 | \n", + "None | \n", + "None | \n", + "CHEMBL2146458 | \n", + "Bioorg. Med. Chem. | \n", + "2012 | \n", + "{'bei': '17.86', 'le': '0.32', 'lle': '1.68', ... | \n", + "CHEMBL227075 | \n", + "DIHYDROTANSHINONE I | \n", + "CHEMBL227075 | \n", + "4.97 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "1727229 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "10700.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "10.7 | \n", + "
| 132 | \n", + "None | \n", + "12041511 | \n", + "[] | \n", + "CHEMBL2150313 | \n", + "Inhibition of SARS-CoV PLpro expressed in Esch... | \n", + "B | \n", + "BAO_0000190 | \n", + "BAO_0000019 | \n", + "assay format | \n", + "CC(C)C1=Cc2ccc3c(c2C(=O)C1=O)CCCC3(C)C | \n", + "None | \n", + "None | \n", + "CHEMBL2146458 | \n", + "Bioorg. Med. Chem. | \n", + "2012 | \n", + "{'bei': '14.53', 'le': '0.27', 'lle': '-0.01',... | \n", + "CHEMBL45830 | \n", + "MILTIRONE | \n", + "CHEMBL45830 | \n", + "4.10 | \n", + "False | \n", + "http://www.openphacts.org/units/Nanomolar | \n", + "1727230 | \n", + "= | \n", + "1 | \n", + "True | \n", + "= | \n", + "None | \n", + "IC50 | \n", + "nM | \n", + "None | \n", + "78900.0 | \n", + "CHEMBL3927 | \n", + "SARS coronavirus | \n", + "SARS coronavirus 3C-like proteinase | \n", + "227859 | \n", + "None | \n", + "None | \n", + "IC50 | \n", + "uM | \n", + "UO_0000065 | \n", + "None | \n", + "78.9 | \n", + "
133 rows × 43 columns
\n", + "| \n", + " | molecule_chembl_id | \n", + "canonical_smiles | \n", + "bioactivity_class | \n", + "standard_value | \n", + "
|---|---|---|---|---|
| 0 | \n", + "CHEMBL187579 | \n", + "Cc1noc(C)c1CN1C(=O)C(=O)c2cc(C#N)ccc21 | \n", + "intermediate | \n", + "7200.0 | \n", + "
| 1 | \n", + "CHEMBL188487 | \n", + "O=C1C(=O)N(Cc2ccc(F)cc2Cl)c2ccc(I)cc21 | \n", + "intermediate | \n", + "9400.0 | \n", + "
| 2 | \n", + "CHEMBL185698 | \n", + "O=C1C(=O)N(CC2COc3ccccc3O2)c2ccc(I)cc21 | \n", + "inactive | \n", + "13500.0 | \n", + "
| 3 | \n", + "CHEMBL426082 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2ccccc21 | \n", + "inactive | \n", + "13110.0 | \n", + "
| 4 | \n", + "CHEMBL187717 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2c1cccc2[N+](=O)[O-] | \n", + "intermediate | \n", + "2000.0 | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 128 | \n", + "CHEMBL2146517 | \n", + "COC(=O)[C@@]1(C)CCCc2c1ccc1c2C(=O)C(=O)c2c(C)c... | \n", + "inactive | \n", + "10600.0 | \n", + "
| 129 | \n", + "CHEMBL187460 | \n", + "C[C@H]1COC2=C1C(=O)C(=O)c1c2ccc2c1CCCC2(C)C | \n", + "inactive | \n", + "10100.0 | \n", + "
| 130 | \n", + "CHEMBL363535 | \n", + "Cc1coc2c1C(=O)C(=O)c1c-2ccc2c(C)cccc12 | \n", + "inactive | \n", + "11500.0 | \n", + "
| 131 | \n", + "CHEMBL227075 | \n", + "Cc1cccc2c3c(ccc12)C1=C(C(=O)C3=O)[C@@H](C)CO1 | \n", + "inactive | \n", + "10700.0 | \n", + "
| 132 | \n", + "CHEMBL45830 | \n", + "CC(C)C1=Cc2ccc3c(c2C(=O)C1=O)CCCC3(C)C | \n", + "inactive | \n", + "78900.0 | \n", + "
133 rows × 4 columns
\n", + "| \n", + " | molecule_chembl_id | \n", + "canonical_smiles | \n", + "standard_value | \n", + "
|---|---|---|---|
| 0 | \n", + "CHEMBL187579 | \n", + "Cc1noc(C)c1CN1C(=O)C(=O)c2cc(C#N)ccc21 | \n", + "7200.0 | \n", + "
| 1 | \n", + "CHEMBL188487 | \n", + "O=C1C(=O)N(Cc2ccc(F)cc2Cl)c2ccc(I)cc21 | \n", + "9400.0 | \n", + "
| 2 | \n", + "CHEMBL185698 | \n", + "O=C1C(=O)N(CC2COc3ccccc3O2)c2ccc(I)cc21 | \n", + "13500.0 | \n", + "
| 3 | \n", + "CHEMBL426082 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2ccccc21 | \n", + "13110.0 | \n", + "
| 4 | \n", + "CHEMBL187717 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2c1cccc2[N+](=O)[O-] | \n", + "2000.0 | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 128 | \n", + "CHEMBL2146517 | \n", + "COC(=O)[C@@]1(C)CCCc2c1ccc1c2C(=O)C(=O)c2c(C)c... | \n", + "10600.0 | \n", + "
| 129 | \n", + "CHEMBL187460 | \n", + "C[C@H]1COC2=C1C(=O)C(=O)c1c2ccc2c1CCCC2(C)C | \n", + "10100.0 | \n", + "
| 130 | \n", + "CHEMBL363535 | \n", + "Cc1coc2c1C(=O)C(=O)c1c-2ccc2c(C)cccc12 | \n", + "11500.0 | \n", + "
| 131 | \n", + "CHEMBL227075 | \n", + "Cc1cccc2c3c(ccc12)C1=C(C(=O)C3=O)[C@@H](C)CO1 | \n", + "10700.0 | \n", + "
| 132 | \n", + "CHEMBL45830 | \n", + "CC(C)C1=Cc2ccc3c(c2C(=O)C1=O)CCCC3(C)C | \n", + "78900.0 | \n", + "
133 rows × 3 columns
\n", + "| \n", + " | molecule_chembl_id | \n", + "canonical_smiles | \n", + "bioactivity_class | \n", + "standard_value | \n", + "0 | \n", + "
|---|---|---|---|---|---|
| 0 | \n", + "CHEMBL187579 | \n", + "Cc1noc(C)c1CN1C(=O)C(=O)c2cc(C#N)ccc21 | \n", + "intermediate | \n", + "7200.0 | \n", + "intermediate | \n", + "
| 1 | \n", + "CHEMBL188487 | \n", + "O=C1C(=O)N(Cc2ccc(F)cc2Cl)c2ccc(I)cc21 | \n", + "intermediate | \n", + "9400.0 | \n", + "intermediate | \n", + "
| 2 | \n", + "CHEMBL185698 | \n", + "O=C1C(=O)N(CC2COc3ccccc3O2)c2ccc(I)cc21 | \n", + "inactive | \n", + "13500.0 | \n", + "inactive | \n", + "
| 3 | \n", + "CHEMBL426082 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2ccccc21 | \n", + "inactive | \n", + "13110.0 | \n", + "inactive | \n", + "
| 4 | \n", + "CHEMBL187717 | \n", + "O=C1C(=O)N(Cc2cc3ccccc3s2)c2c1cccc2[N+](=O)[O-] | \n", + "intermediate | \n", + "2000.0 | \n", + "intermediate | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 128 | \n", + "CHEMBL2146517 | \n", + "COC(=O)[C@@]1(C)CCCc2c1ccc1c2C(=O)C(=O)c2c(C)c... | \n", + "inactive | \n", + "10600.0 | \n", + "inactive | \n", + "
| 129 | \n", + "CHEMBL187460 | \n", + "C[C@H]1COC2=C1C(=O)C(=O)c1c2ccc2c1CCCC2(C)C | \n", + "inactive | \n", + "10100.0 | \n", + "inactive | \n", + "
| 130 | \n", + "CHEMBL363535 | \n", + "Cc1coc2c1C(=O)C(=O)c1c-2ccc2c(C)cccc12 | \n", + "inactive | \n", + "11500.0 | \n", + "inactive | \n", + "
| 131 | \n", + "CHEMBL227075 | \n", + "Cc1cccc2c3c(ccc12)C1=C(C(=O)C3=O)[C@@H](C)CO1 | \n", + "inactive | \n", + "10700.0 | \n", + "inactive | \n", + "
| 132 | \n", + "CHEMBL45830 | \n", + "CC(C)C1=Cc2ccc3c(c2C(=O)C1=O)CCCC3(C)C | \n", + "inactive | \n", + "78900.0 | \n", + "inactive | \n", + "
133 rows × 5 columns
\n", + "