PROTEINS_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b761774c-9014-41e6-b112-0f262e4a9e9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch_geometric.datasets import TUDataset\n",
    "import numpy as np\n",
    "from sklearn.decomposition import PCA\n",
    "import torch\n",
    "from config import Dataset\n",
    "from dataset import get_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5eeb98fa-c475-4a2e-b2d9-ab19b489685a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 2, 1113)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = get_dataset(Dataset.PROTEINS)\n",
    "ds.num_features, ds.num_classes, len(ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b50daf34-5b00-4975-8a23-74099231e7f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0, 1])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.y.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4ad2e9a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.num_edge_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5718c7b2-e649-4edb-93de-57cfcf08ba55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(0.4043)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.y.sum()/ds.y.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d1adb20e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[23.,  1.,  0.,  0.],\n",
       "        [10.,  1.,  0.,  0.],\n",
       "        [25.,  1.,  0.,  0.],\n",
       "        ...,\n",
       "        [ 4.,  0.,  0.,  1.],\n",
       "        [ 4.,  0.,  0.,  1.],\n",
       "        [ 4.,  0.,  0.,  1.]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e1a1468f-3c47-4d40-ae2b-8c4f5bcb5571",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-538., -345., -344., -134., -125.,  -96.,    1.,    2.,    3.,\n",
       "          4.,    5.,    6.,    7.,    8.,    9.,   10.,   11.,   12.,\n",
       "         13.,   14.,   15.,   16.,   17.,   18.,   19.,   20.,   21.,\n",
       "         22.,   23.,   24.,   25.,   26.,   27.,   28.,   29.,   30.,\n",
       "         31.,   32.,   33.,   34.,   35.,   36.,   37.,   38.,   39.,\n",
       "         41.,   42.,   47.,   61.,   63.,   73.,   74.,   75.,   82.,\n",
       "        104.,  353.,  355.,  360.,  558.,  797.,  798.], dtype=float32)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(ds.x[:,0], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9fdd5d6f-ea70-47be-a349-39be357c0e02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(np.unique(ds.x[:,0], axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9ca5a889-cb32-47dd-a6ec-29b680f38443",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[    0,     0,     0,  ..., 43470, 43470, 43470],\n",
       "        [   11,    22,    32,  ..., 43438, 43468, 43469]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.edge_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5c7a7c6d-ce74-448c-85e4-283ef705e5da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.num_node_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c23d58ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(True)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = ds[0]\n",
    "d.y[0] == 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8f045aea-4499-4abc-ae22-c9961cf9d09e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visualize the graph\n",
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "66b07e9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "_, indexes = next(StratifiedShuffleSplit(n_splits=1, test_size=9, random_state=42).split(ds, ds.y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0a5d1b16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 6))\n",
    "gs = fig.add_gridspec(3, 3, wspace=0.05, hspace=0.05)\n",
    "axes = gs.subplots()\n",
    "color_map = [\"red\", \"green\", \"blue\"]\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        G = nx.Graph()\n",
    "        d = ds[indexes[i*3+j]]\n",
    "        G.add_edges_from(d.edge_index.T.tolist())\n",
    "        colors = [color_map[torch.nonzero(n[1:]).squeeze()] for n in d.x]\n",
    "        nx.draw_networkx(G, ax=axes[i, j], node_color=colors, with_labels=False, node_size=15)\n",
    "        \n",
    "        axes[i, j].set_title(\"Enzyme\" if d.y else \"Not Enzyme\")\n",
    "\n",
    "fig.legend([patches.Patch(color=c, capstyle=\"round\") for c in color_map], [\"helix\", \"sheet\", \"turn\"], loc=\"center left\")\n",
    "os.makedirs(\"./generated_images\", exist_ok=True)\n",
    "fig.savefig(\"./generated_images/PROTEINS-examples.svg\", format=\"svg\", dpi=1200)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ce00092e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>PCA(n_components=4)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;PCA<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.decomposition.PCA.html\">?<span>Documentation for PCA</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>PCA(n_components=4)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "PCA(n_components=4)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca = PCA(n_components=4)\n",
    "pca.fit(ds.x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e7106a29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9.96709412e-01 2.99395319e-03 2.96635179e-04 3.84787544e-33]\n"
     ]
    }
   ],
   "source": [
    "print(pca.explained_variance_ratio_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "15d7764c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.50952053e+01, -5.45326474e-01, -2.73841761e-02,\n",
       "        -6.03072446e-16],\n",
       "       [ 2.09592392e+00, -6.81488027e-01, -3.93894533e-02,\n",
       "        -6.03072446e-16],\n",
       "       [ 1.70950947e+01, -5.24378543e-01, -2.55372104e-02,\n",
       "        -6.03072446e-16],\n",
       "       ...,\n",
       "       [-3.91224373e+00, -4.10827076e-02,  1.18200422e+00,\n",
       "        -5.96923343e-15],\n",
       "       [-3.91224373e+00, -4.10827076e-02,  1.18200422e+00,\n",
       "        -5.96923343e-15],\n",
       "       [-3.91224373e+00, -4.10827076e-02,  1.18200422e+00,\n",
       "        -5.96923343e-15]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_x = pca.transform(ds.x)\n",
    "new_x"
   ]
  }
 ],
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