{
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     "status": "ok",
     "timestamp": 1715679311815,
     "user": {
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      "userId": "06438787448544879581"
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    "id": "GR24N5HCGTsU",
    "outputId": "08edd7ec-1177-45bc-b7f3-127f408e91f3",
    "tags": []
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting MDAnalysis\n",
      "  Downloading MDAnalysis-2.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.1 MB)\n",
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      "\u001b[?25hRequirement already satisfied: numpy<2.0,>=1.22.3 in /usr/local/lib/python3.10/dist-packages (from MDAnalysis) (1.25.2)\n",
      "Collecting GridDataFormats>=0.4.0 (from MDAnalysis)\n",
      "  Downloading GridDataFormats-1.0.2-py3-none-any.whl (2.1 MB)\n",
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      "\u001b[?25hCollecting mmtf-python>=1.0.0 (from MDAnalysis)\n",
      "  Downloading mmtf_python-1.1.3-py2.py3-none-any.whl (25 kB)\n",
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      "Collecting mrcfile (from GridDataFormats>=0.4.0->MDAnalysis)\n",
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      "Installing collected packages: mrcfile, mmtf-python, mda-xdrlib, fasteners, GridDataFormats, MDAnalysis\n",
      "Successfully installed GridDataFormats-1.0.2 MDAnalysis-2.7.0 fasteners-0.19 mda-xdrlib-0.2.0 mmtf-python-1.1.3 mrcfile-1.5.0\n"
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   "source": [
    "!pip install MDAnalysis"
   ]
  },
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   "cell_type": "code",
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   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
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     "elapsed": 32892,
     "status": "ok",
     "timestamp": 1715679721635,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "\n",
    "drive.mount(\"/content/drive\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1934,
     "status": "ok",
     "timestamp": 1715680351112,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "n0uBRM6mGo2M",
    "outputId": "f7833b00-ea18-4112-b0dd-054968ba5a6f"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:MDAnalysis.coordinates.AMBER:netCDF4 is not available. Writing AMBER ncdf files will be slow.\n"
     ]
    }
   ],
   "source": [
    "import MDAnalysis as mda\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.mixture import GaussianMixture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 79736,
     "status": "ok",
     "timestamp": 1715680454745,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "6pr6s4nEGTsV",
    "outputId": "5961cf71-1f94-4bc7-bfe8-0406abe418a5",
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/MDAnalysis/coordinates/XDR.py:240: UserWarning: Reload offsets from trajectory\n",
      " ctime or size or n_atoms did not match\n",
      "  warnings.warn(\"Reload offsets from trajectory\\n \"\n"
     ]
    }
   ],
   "source": [
    "u = mda.Universe(\n",
    "    \"/content/drive/MyDrive/jj/simul/step5_1.tpr\",\n",
    "    \"/content/drive/MyDrive/jj/simul/centered.xtc\",\n",
    ")\n",
    "ag = u.select_atoms(\"name CA\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 49,
     "referenced_widgets": [
      "3efcab294b2048f7a0d645315820c9e8",
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      "01ec01c324ca49669bcda4b6c814b467",
      "da31b3a93ef94239a0024d4503a877eb",
      "741b307aa2fe4baaae05088e58251474",
      "e523538cca3943718824bd44f94effac"
     ]
    },
    "executionInfo": {
     "elapsed": 115456,
     "status": "ok",
     "timestamp": 1715680592259,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "52QE_RwhGTsW",
    "outputId": "20eefc0a-449e-44dd-b254-b066fde98dcf"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3efcab294b2048f7a0d645315820c9e8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10001 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ca_poss = []\n",
    "for ts in tqdm(u.trajectory):\n",
    "    ca_poss.append(ag.positions)\n",
    "\n",
    "ca_poss = np.array(ca_poss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 327,
     "status": "ok",
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    "id": "__NxpNBKk5Qp",
    "outputId": "0d8865e4-54d8-4ed4-e088-229f94e040e4"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10001, 549, 3)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ca_poss.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "5iJQAlzyMKgf"
   },
   "outputs": [],
   "source": [
    "rgyr = []\n",
    "time = []\n",
    "protein = u.select_atoms(\"protein\")  ##protein\n",
    "for ts in u.trajectory:\n",
    "    time.append(u.trajectory.time)\n",
    "    rgyr.append(protein.radius_of_gyration())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
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     "height": 237
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    "executionInfo": {
     "elapsed": 863,
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     "timestamp": 1715680748250,
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    "id": "3fQb4h6LOZAs",
    "outputId": "d4e61281-ad68-4ec3-f742-eda589f4ffed"
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       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-26b112fa-ce7b-48c4-9f1e-6cb64261d465 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "           Radius of gyration (A)\n",
       "Time (ps)                        \n",
       "0.0                     21.477475\n",
       "10.0                    21.546591\n",
       "20.0                    21.546411\n",
       "30.0                    21.540754\n",
       "40.0                    21.546202"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "rgyr_df = pd.DataFrame(rgyr, columns=[\"Radius of gyration (A)\"], index=time)\n",
    "rgyr_df.index.name = \"Time (ps)\"\n",
    "\n",
    "rgyr_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "executionInfo": {
     "elapsed": 1306,
     "status": "ok",
     "timestamp": 1715680754355,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "uUysJtCZP--F",
    "outputId": "6b1de2d1-d0e1-4398-da22-49e808b9c703"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rgyr_df.plot(title=\"Radius of gyration\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 30,
     "status": "ok",
     "timestamp": 1715334662697,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "XTiRsDLEGTsX",
    "outputId": "25bac2f7-33fd-4e2f-f6e5-7e0085e90c15"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10001, 549, 3)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ca_poss.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "5QhFcoqgGTsX"
   },
   "outputs": [],
   "source": [
    "ca_poss = ca_poss[::10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 22,
     "status": "ok",
     "timestamp": 1715334662698,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "W5bvdjfVGTsX",
    "outputId": "745f25da-9a3b-4960-d941-d9821cd12d75"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1001, 549, 3)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ca_poss.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0Xztox1_GTsX"
   },
   "source": [
    "## pca 2 component"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 18,
     "status": "ok",
     "timestamp": 1715334662698,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "l8iWnLltGTsY",
    "outputId": "4d814bb1-944c-49fa-bc97-762b1fbddabf"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1001, 549, 3)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca = PCA(n_components=2)\n",
    "ca_poss.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "hoqOa4zhGTsY"
   },
   "outputs": [],
   "source": [
    "principal_components = pca.fit_transform(ca_poss.reshape((ca_poss.shape[0], 549 * 3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 678
    },
    "executionInfo": {
     "elapsed": 1022,
     "status": "ok",
     "timestamp": 1715334663704,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "40SXcg0NGTsZ",
    "outputId": "a3928d7f-18f2-4e34-a70d-3090cf36e5fc"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAAAAQGgR4AQAAAAAAAAQWgQ4AQAAAAAAAITW/w84pWQPqY8YgQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.scatter(principal_components[:, 0], principal_components[:, 1])\n",
    "plt.xlabel(\"component 0\")\n",
    "plt.ylabel(\"component 1\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 22,
     "status": "ok",
     "timestamp": 1715334663706,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "ruAi2E-uGTsZ",
    "outputId": "3a75b2b0-8128-4ee8-9504-f1cf6d9126fb"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1001, 2)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "principal_components.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 16,
     "status": "ok",
     "timestamp": 1715334663707,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "__zIJvODGTsa",
    "outputId": "0ba48068-e67e-4fad-a798-abbeb52d1231"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.4853555 , 0.32633677], dtype=float32)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "svGX_2lkGTsa"
   },
   "source": [
    "## TSNE 2 component"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 853
    },
    "executionInfo": {
     "elapsed": 8632,
     "status": "ok",
     "timestamp": 1715334672327,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "UI-kBnXjGTsb",
    "outputId": "5412803d-630c-4a54-c6e3-66ad9fd2676d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsne = TSNE(random_state=1, n_components=2)\n",
    "\n",
    "projected_tsne = tsne.fit_transform(ca_poss.reshape((ca_poss.shape[0], 549 * 3)))\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(12, 10))\n",
    "plt.title(\"MD t-SNE projection\")\n",
    "plt.scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], edgecolor=\"none\", alpha=0.7, s=40\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 211
    },
    "executionInfo": {
     "elapsed": 11,
     "status": "error",
     "timestamp": 1715345160676,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "LioAMToGGTsb",
    "outputId": "7b519250-8922-4404-9cf5-e49486a4590d"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-489c037ecaa6>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_title\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"FUS PCA\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprincipal_components\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprincipal_components\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0medgecolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'none'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m.8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m15\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(16, 8))\n",
    "\n",
    "ax[0].set_title(\"FUS PCA\")\n",
    "ax[0].scatter(\n",
    "    principal_components[:, 0],\n",
    "    principal_components[:, 1],\n",
    "    edgecolor=\"none\",\n",
    "    alpha=0.8,\n",
    "    s=15,\n",
    ")\n",
    "\n",
    "ax[1].set_title(\"FUS t-SNE\")\n",
    "ax[1].scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], edgecolor=\"none\", alpha=0.8, s=15\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "aXMK3R71GTsb"
   },
   "outputs": [],
   "source": [
    "def out_move_percent(cl):\n",
    "    n = len(cl)\n",
    "    on = 0\n",
    "    for i in range(1, len(cl)):\n",
    "        if cl[i] != cl[i - 1]:\n",
    "            on += 1\n",
    "    return on / n * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xb_eNs7cGTsb"
   },
   "source": [
    "## 2 component kmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 562,
     "status": "ok",
     "timestamp": 1715334674032,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "_BMJFCC-GTsb",
    "outputId": "3d190b64-7b0b-4dc5-e038-cdf612be43d1"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "intertias = []\n",
    "for i in range(2, 25):\n",
    "    kmeans = KMeans(n_clusters=i, random_state=0)\n",
    "    clusters = kmeans.fit_predict(projected_tsne)\n",
    "    intertias.append(kmeans.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 686
    },
    "executionInfo": {
     "elapsed": 15,
     "status": "ok",
     "timestamp": 1715334674033,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "FCc3OKV_GTsb",
    "outputId": "fde69dd4-d3d8-4fc2-fc11-8cc5708d8494"
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.title(\n",
    "    \"Sum of squared distances of samples to their closest cluster center vs number of cluster\"\n",
    ")\n",
    "plt.plot(range(2, 25), intertias, label=\"loss\")\n",
    "plt.plot(range(3, 25), -np.diff(intertias), label=\"delta(loss)\")\n",
    "plt.axvline(8, label=\"8\", c=\"r\")\n",
    "plt.grid()\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 885
    },
    "executionInfo": {
     "elapsed": 748,
     "status": "ok",
     "timestamp": 1715334674771,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "7sd_bzTnGTsc",
    "outputId": "573921ca-386a-4547-8d52-316283edc79b"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmeans = KMeans(n_clusters=6, random_state=0)\n",
    "clusters = kmeans.fit_predict(projected_tsne)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "fig = plt.figure(figsize=(12, 10))\n",
    "plt.scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], c=clusters, s=50, cmap=\"viridis\"\n",
    ")\n",
    "centers = kmeans.cluster_centers_\n",
    "plt.scatter(centers[:, 0], centers[:, 1], c=\"black\", s=200, alpha=0.5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 19,
     "status": "ok",
     "timestamp": 1715334674773,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "QBHHj8bNGTsc",
    "outputId": "7b7abb84-dc6f-4316-e09c-debdbe90c805"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6993006993006993"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_move_percent(clusters)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ynhJIjUQGTsc"
   },
   "source": [
    "## 2 component gmm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "27UmCIInGTsc"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 49,
     "referenced_widgets": [
      "31404fc3b3b643299757b583737dc7a5",
      "58e936af329d4a0ca446825e75822316",
      "9b4d79cba1654e79bfff75f21c574772",
      "c0e9050b25644ad5ba716d886b553e03",
      "340a29a414ca44e18b261effb72e2cff",
      "b35777a643d04b4eb4e708216f549ab0",
      "e1153efc64cf4401ae011f4e0f4a354a",
      "b391970c764345f995510a82d70ad530",
      "50f8be6c026d47978c7beb1ddca12c0b",
      "88bc6f3ca2d84efe962dcaf87913fee2",
      "d59ef63728ce4861a6a5a627bfb5747e"
     ]
    },
    "executionInfo": {
     "elapsed": 5249,
     "status": "ok",
     "timestamp": 1715334680010,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "uh4dX2CvGTsc",
    "outputId": "1ae20666-35c4-48ff-999d-113d7e06b5fe"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "31404fc3b3b643299757b583737dc7a5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/38 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bics = []\n",
    "aics = []\n",
    "losses = []\n",
    "for i in tqdm(range(2, 40)):\n",
    "    model = GaussianMixture(n_components=i, random_state=0)\n",
    "    clusters = model.fit_predict(projected_tsne)\n",
    "    bics.append(model.bic(projected_tsne))\n",
    "    aics.append(model.aic(projected_tsne))\n",
    "    losses.append(model.score(projected_tsne))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 497
    },
    "executionInfo": {
     "elapsed": 86514,
     "status": "ok",
     "timestamp": 1715334766511,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "lnwaD4vzGTsd",
    "outputId": "a8908ed2-605b-4356-8549-9b6a8cb050e8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Score')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "\n",
    "def SelBest(arr: list, X: int) -> list:\n",
    "    \"\"\"\n",
    "    returns the set of X configurations with shorter distance\n",
    "    \"\"\"\n",
    "    dx = np.argsort(arr)[:X]\n",
    "    return arr[dx]\n",
    "\n",
    "\n",
    "n_clusters = np.arange(2, 20)\n",
    "sils = []\n",
    "sils_err = []\n",
    "iterations = 20\n",
    "for n in n_clusters:\n",
    "    tmp_sil = []\n",
    "    for _ in range(iterations):\n",
    "        gmm = GaussianMixture(n, n_init=2).fit(projected_tsne)\n",
    "        labels = gmm.predict(projected_tsne)\n",
    "        sil = metrics.silhouette_score(projected_tsne, labels, metric=\"euclidean\")\n",
    "        tmp_sil.append(sil)\n",
    "    val = np.mean(SelBest(np.array(tmp_sil), int(iterations / 5)))\n",
    "    err = np.std(tmp_sil)\n",
    "    sils.append(val)\n",
    "    sils_err.append(err)\n",
    "\n",
    "plt.errorbar(n_clusters, sils, yerr=sils_err)\n",
    "plt.title(\"Silhouette Scores\", fontsize=20)\n",
    "plt.xticks(n_clusters)\n",
    "plt.xlabel(\"N. of clusters\")\n",
    "plt.ylabel(\"Score\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 1841,
     "status": "ok",
     "timestamp": 1715334768339,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "dpRmgaWtGTsd",
    "outputId": "94ca7940-7dc6-4def-c48b-d4e57c393723"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.title(\"Log liklihood\")\n",
    "plt.plot(range(2, 40), losses - losses[-1], label=\"loss\")\n",
    "plt.plot(range(3, 40), -np.diff(losses), label=\"delta(loss)\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.title(\"aic\")\n",
    "plt.plot(range(2, 40), aics - aics[-1], label=\"loss\")\n",
    "plt.plot(range(3, 40), -np.diff(aics), label=\"delta(loss)\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.title(\"bic\")\n",
    "plt.plot(range(2, 40), bics - bics[-1], label=\"loss\")\n",
    "plt.plot(range(3, 40), -np.diff(bics), label=\"delta(loss)\")\n",
    "plt.grid()\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 830
    },
    "executionInfo": {
     "elapsed": 19,
     "status": "ok",
     "timestamp": 1715334768340,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "sVxWMuNCGTsd",
    "outputId": "361ee833-1725-4998-8341-3f98fa0a6406"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = GaussianMixture(n_components=11, random_state=0)\n",
    "clusters = model.fit_predict(projected_tsne)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "fig = plt.figure(figsize=(12, 10))\n",
    "plt.scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], c=clusters, s=50, cmap=\"viridis\"\n",
    ")\n",
    "centers = model.means_\n",
    "plt.scatter(centers[:, 0], centers[:, 1], c=\"black\", s=200, alpha=0.5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 830
    },
    "executionInfo": {
     "elapsed": 15,
     "status": "ok",
     "timestamp": 1715334768340,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "DIUrpw7MGTsd",
    "outputId": "5fb58ce0-1929-4a71-e471-349c6c69edad"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 10))\n",
    "plt.plot(clusters);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 13,
     "status": "ok",
     "timestamp": 1715334768341,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "YzQggkHKGTsd",
    "outputId": "38c77c06-4eb9-492f-c430-a74d42b30f7a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.696303696303696"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_move_percent(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 686
    },
    "executionInfo": {
     "elapsed": 1172,
     "status": "ok",
     "timestamp": 1715334769503,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "BKNWw-ytGTsd",
    "outputId": "290cdc13-6a19-427e-c311-d3597519600c"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(16, 8))\n",
    "\n",
    "ax[0].set_title(\"FUS K-means\")\n",
    "\n",
    "clusters = kmeans.fit_predict(projected_tsne)\n",
    "\n",
    "\n",
    "ax[0].scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], c=clusters, s=50, cmap=\"viridis\"\n",
    ")\n",
    "centers = kmeans.cluster_centers_\n",
    "ax[0].scatter(centers[:, 0], centers[:, 1], c=\"black\", s=200, alpha=0.5)\n",
    "ax[1].set_title(\"FUS GMM\")\n",
    "\n",
    "clusters = model.fit_predict(projected_tsne)\n",
    "\n",
    "ax[1].scatter(\n",
    "    projected_tsne[:, 0], projected_tsne[:, 1], c=clusters, s=50, cmap=\"viridis\"\n",
    ")\n",
    "centers = model.means_\n",
    "ax[1].scatter(centers[:, 0], centers[:, 1], c=\"black\", s=200, alpha=0.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d3LpA1JdGTse"
   },
   "source": [
    "## pca 3 component"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "oC_MNNzTGTse"
   },
   "outputs": [],
   "source": [
    "pca = PCA(n_components=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "fDiSK3Z5GTse"
   },
   "outputs": [],
   "source": [
    "principal_components = pca.fit_transform(ca_poss.reshape((ca_poss.shape[0], 549 * 3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 29,
     "status": "ok",
     "timestamp": 1715334769505,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "eBiD9YxYGTse",
    "outputId": "bd5d2aef-c9fd-4b35-ceef-4024a0bd8410"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1001, 3)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "principal_components.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 26,
     "status": "ok",
     "timestamp": 1715334769506,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "BQnC9h_LGTsf",
    "outputId": "e544318e-1295-40a0-82e1-b25435b18e40"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='6d91b91f-3c82-4a03-9e2e-94d4ae3419ad'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.5, 'component 1')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax = fig.add_subplot(111, projection=\"3d\")\n",
    "ax.scatter(\n",
    "    principal_components[:800, 0],\n",
    "    principal_components[:800, 1],\n",
    "    principal_components[:800, 2],\n",
    ")\n",
    "plt.xlabel(\"component 0\")\n",
    "plt.ylabel(\"component 1\")\n",
    "# plt.ylabel(\"component 2\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 22,
     "status": "ok",
     "timestamp": 1715334769506,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "XdW2g36-GTsf",
    "outputId": "1dba7706-45c3-469b-d555-1c8cbeb72f52"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.48535544, 0.32633665, 0.12284613], dtype=float32)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h3ffBuyWGTsf"
   },
   "source": [
    "## TSNE 3 component"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "executionInfo": {
     "elapsed": 14534,
     "status": "ok",
     "timestamp": 1715334784023,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "SM8J5HJ8GTsf",
    "outputId": "280ddda7-96b3-495a-b320-2b210b42fc68"
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='cd647550-f987-49f9-890d-63b9019ef32f'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsne = TSNE(random_state=17, n_components=3)\n",
    "\n",
    "projected_tsne = tsne.fit_transform(ca_poss.reshape((ca_poss.shape[0], 549 * 3)))\n",
    "\n",
    "%matplotlib notebook\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax = fig.add_subplot(111, projection=\"3d\")\n",
    "ax.scatter(projected_tsne[:, 0], projected_tsne[:, 1], projected_tsne[:, 2])\n",
    "plt.xlabel(\"component 0\")\n",
    "plt.ylabel(\"component 1\")\n",
    "plt.ylabel(\"component 2\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 836
    },
    "executionInfo": {
     "elapsed": 4497,
     "status": "ok",
     "timestamp": 1715334788502,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "aUgHj5ckGTsg",
    "outputId": "6edaefb7-7148-4644-a035-2ab786ab196b"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "intertias = []\n",
    "for i in range(2, 25):\n",
    "    kmeans = KMeans(n_clusters=i, random_state=0)\n",
    "    clusters = kmeans.fit_predict(projected_tsne)\n",
    "    intertias.append(kmeans.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 690
    },
    "executionInfo": {
     "elapsed": 1003,
     "status": "ok",
     "timestamp": 1715334789492,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "Rq4qOBFxGTsg",
    "outputId": "bb1d1eba-2905-43b8-95f9-3f7458f1bd63"
   },
   "outputs": [
    {
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       "        'box-sizing: content-box;' +\n",
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       "};\n",
       "\n",
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       "\n",
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       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
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       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='280e0ff8-72cd-400b-8e71-9cc042cd2e06'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='70b9be0c-6c4d-4b04-9f5e-a7b0bb2a74ff'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.title(\n",
    "    \"Sum of squared distances of samples to their closest cluster center vs number of cluster\"\n",
    ")\n",
    "plt.plot(range(2, 25), intertias, label=\"loss\")\n",
    "plt.plot(range(3, 25), -np.diff(intertias), label=\"delta(loss)\")\n",
    "plt.axvline(8, label=\"8\", c=\"r\")\n",
    "plt.grid()\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 72
    },
    "executionInfo": {
     "elapsed": 26,
     "status": "ok",
     "timestamp": 1715334789492,
     "user": {
      "displayName": "Yevgeni Mamasakhlisov",
      "userId": "06438787448544879581"
     },
     "user_tz": -240
    },
    "id": "VoViNupXGTsg",
    "outputId": "c19fd132-ff53-4941-f4c8-d486e3b08e71",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='0a72fc77-e213-4d3a-9204-f686151d94ee'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmeans = KMeans(n_clusters=10, random_state=0)\n",
    "clusters = kmeans.fit_predict(projected_tsne)\n",
    "kmeans.cluster_centers_.shape\n",
    "\n",
    "%matplotlib notebook\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "\n",
    "ax = fig.add_subplot(111, projection=\"3d\")\n",
    "ax.scatter(\n",
    "    projected_tsne[:, 0],\n",
    "    projected_tsne[:, 1],\n",
    "    projected_tsne[:, 2],\n",
    "    c=clusters,\n",
    "    s=50,\n",
    "    cmap=\"viridis\",\n",
    ")\n",
    "centers = kmeans.cluster_centers_\n",
    "ax.scatter(centers[:, 0], centers[:, 1], centers[:, 2], c=\"black\", s=200, alpha=0.5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "a85FRdMAGTsg"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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