format_embeddings.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cf21cbc0-bfb7-493f-83d7-37973427cced",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os\n",
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1f14ce4a-4f92-4952-a374-caee25e452f7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Open embedded GO Terms\n",
    "with zipfile.ZipFile('go_embeddings_20k.zip', 'r') as zip_ref:\n",
    "    zip_ref.extractall()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "26161754-449f-4217-957c-894a5ca8ee79",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "         filename     col_1     col_2     col_3     col_4     col_5     col_6  \\\n",
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       "\n",
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       "\n",
       "[20422 rows x 601 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compile embedded GO Terms into Pandas Dataframe\n",
    "dir_path = 'go_embeddings/'\n",
    "# Initialize an empty list to store the data\n",
    "data = []\n",
    "\n",
    "# Iterate over all .npy files in the directory\n",
    "for filename in os.listdir(dir_path):\n",
    "    if filename.endswith('.npy'):\n",
    "        # Load the numpy array\n",
    "        array = np.load(os.path.join(dir_path, filename))\n",
    "\n",
    "        # Add the filename and array data to the list\n",
    "        row = [filename] + array.tolist()\n",
    "        data.append(row)\n",
    "\n",
    "# Create a DataFrame from the list\n",
    "GO = pd.DataFrame(data)\n",
    "\n",
    "# Set the column names\n",
    "GO.columns = ['filename'] + ['col_{}'.format(i) for i in range(1, GO.shape[1])]\n",
    "\n",
    "# Print the DataFrame\n",
    "GO    # Load the numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f9e7bc68-3fb6-4b58-887b-39ac28f6960b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "GO['filename'] = GO['filename'].str.replace('.npy', '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e016d09-180a-471d-a467-2b7071d3ac8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compile embedded AA sequences into Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "61de11e7-306a-4ab0-be96-8497a4618b2e",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "      <th>col_2556</th>\n",
       "      <th>col_2557</th>\n",
       "      <th>col_2558</th>\n",
       "      <th>col_2559</th>\n",
       "      <th>col_2560</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A0A087X1C5.pt</td>\n",
       "      <td>-0.038923</td>\n",
       "      <td>0.016107</td>\n",
       "      <td>-0.076490</td>\n",
       "      <td>-0.044447</td>\n",
       "      <td>-0.026241</td>\n",
       "      <td>-0.062517</td>\n",
       "      <td>0.048793</td>\n",
       "      <td>-0.063152</td>\n",
       "      <td>0.047682</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014710</td>\n",
       "      <td>-0.065358</td>\n",
       "      <td>0.040060</td>\n",
       "      <td>-0.068655</td>\n",
       "      <td>-0.023912</td>\n",
       "      <td>0.035812</td>\n",
       "      <td>0.002793</td>\n",
       "      <td>0.128581</td>\n",
       "      <td>-0.037806</td>\n",
       "      <td>-0.037085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A0A0B4J2F0.pt</td>\n",
       "      <td>-0.010678</td>\n",
       "      <td>-0.010572</td>\n",
       "      <td>-0.099035</td>\n",
       "      <td>-0.062785</td>\n",
       "      <td>-0.039515</td>\n",
       "      <td>-0.043607</td>\n",
       "      <td>0.035617</td>\n",
       "      <td>-0.081518</td>\n",
       "      <td>0.031148</td>\n",
       "      <td>...</td>\n",
       "      <td>0.034861</td>\n",
       "      <td>-0.062966</td>\n",
       "      <td>0.050289</td>\n",
       "      <td>-0.016540</td>\n",
       "      <td>0.063586</td>\n",
       "      <td>-0.003878</td>\n",
       "      <td>0.004271</td>\n",
       "      <td>0.112121</td>\n",
       "      <td>-0.084403</td>\n",
       "      <td>-0.112586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A0A0B4J2F2.pt</td>\n",
       "      <td>-0.056983</td>\n",
       "      <td>0.015480</td>\n",
       "      <td>-0.107581</td>\n",
       "      <td>-0.050975</td>\n",
       "      <td>-0.049094</td>\n",
       "      <td>-0.015369</td>\n",
       "      <td>-0.000929</td>\n",
       "      <td>-0.073088</td>\n",
       "      <td>0.057361</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016309</td>\n",
       "      <td>-0.005781</td>\n",
       "      <td>0.025045</td>\n",
       "      <td>-0.051069</td>\n",
       "      <td>-0.013411</td>\n",
       "      <td>0.014069</td>\n",
       "      <td>-0.021879</td>\n",
       "      <td>0.093391</td>\n",
       "      <td>-0.077502</td>\n",
       "      <td>-0.016692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A0A0C5B5G6.pt</td>\n",
       "      <td>-0.000092</td>\n",
       "      <td>-0.037981</td>\n",
       "      <td>-0.069931</td>\n",
       "      <td>-0.040279</td>\n",
       "      <td>-0.072822</td>\n",
       "      <td>-0.058605</td>\n",
       "      <td>0.026483</td>\n",
       "      <td>-0.059635</td>\n",
       "      <td>0.052859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017898</td>\n",
       "      <td>-0.075702</td>\n",
       "      <td>-0.065242</td>\n",
       "      <td>-0.060032</td>\n",
       "      <td>0.097588</td>\n",
       "      <td>0.023318</td>\n",
       "      <td>-0.008654</td>\n",
       "      <td>0.071132</td>\n",
       "      <td>0.030236</td>\n",
       "      <td>-0.124704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A0A0K2S4Q6.pt</td>\n",
       "      <td>-0.024788</td>\n",
       "      <td>-0.012560</td>\n",
       "      <td>-0.061030</td>\n",
       "      <td>-0.032265</td>\n",
       "      <td>-0.039898</td>\n",
       "      <td>-0.053276</td>\n",
       "      <td>0.034171</td>\n",
       "      <td>-0.055207</td>\n",
       "      <td>0.009990</td>\n",
       "      <td>...</td>\n",
       "      <td>0.027765</td>\n",
       "      <td>-0.022588</td>\n",
       "      <td>0.024271</td>\n",
       "      <td>-0.145041</td>\n",
       "      <td>0.028161</td>\n",
       "      <td>0.047234</td>\n",
       "      <td>-0.067301</td>\n",
       "      <td>0.113494</td>\n",
       "      <td>-0.093726</td>\n",
       "      <td>-0.054095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9691</th>\n",
       "      <td>Q495M3.pt</td>\n",
       "      <td>-0.051883</td>\n",
       "      <td>0.016401</td>\n",
       "      <td>-0.055423</td>\n",
       "      <td>-0.080380</td>\n",
       "      <td>-0.031483</td>\n",
       "      <td>-0.053540</td>\n",
       "      <td>0.030414</td>\n",
       "      <td>-0.032083</td>\n",
       "      <td>0.038185</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006701</td>\n",
       "      <td>-0.043547</td>\n",
       "      <td>0.036076</td>\n",
       "      <td>-0.071274</td>\n",
       "      <td>0.002526</td>\n",
       "      <td>0.001005</td>\n",
       "      <td>-0.011456</td>\n",
       "      <td>0.136021</td>\n",
       "      <td>-0.072522</td>\n",
       "      <td>-0.039517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9692</th>\n",
       "      <td>Q495M9.pt</td>\n",
       "      <td>-0.077512</td>\n",
       "      <td>-0.081478</td>\n",
       "      <td>-0.086535</td>\n",
       "      <td>-0.056407</td>\n",
       "      <td>-0.059902</td>\n",
       "      <td>-0.070051</td>\n",
       "      <td>0.037212</td>\n",
       "      <td>-0.011500</td>\n",
       "      <td>0.046766</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017591</td>\n",
       "      <td>-0.044382</td>\n",
       "      <td>0.012516</td>\n",
       "      <td>-0.062807</td>\n",
       "      <td>0.006686</td>\n",
       "      <td>-0.028964</td>\n",
       "      <td>0.003466</td>\n",
       "      <td>0.153523</td>\n",
       "      <td>-0.080030</td>\n",
       "      <td>-0.082515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9693</th>\n",
       "      <td>Q495T6.pt</td>\n",
       "      <td>-0.054756</td>\n",
       "      <td>0.025106</td>\n",
       "      <td>-0.083150</td>\n",
       "      <td>-0.036703</td>\n",
       "      <td>-0.016852</td>\n",
       "      <td>-0.064474</td>\n",
       "      <td>0.057104</td>\n",
       "      <td>-0.035241</td>\n",
       "      <td>0.009740</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006994</td>\n",
       "      <td>-0.068897</td>\n",
       "      <td>0.025549</td>\n",
       "      <td>-0.056556</td>\n",
       "      <td>0.017730</td>\n",
       "      <td>-0.002070</td>\n",
       "      <td>-0.009403</td>\n",
       "      <td>0.103031</td>\n",
       "      <td>-0.095598</td>\n",
       "      <td>-0.078120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9694</th>\n",
       "      <td>Q495W5.pt</td>\n",
       "      <td>-0.057126</td>\n",
       "      <td>-0.010426</td>\n",
       "      <td>-0.056482</td>\n",
       "      <td>0.004159</td>\n",
       "      <td>-0.017741</td>\n",
       "      <td>-0.040794</td>\n",
       "      <td>0.017283</td>\n",
       "      <td>-0.064886</td>\n",
       "      <td>0.023010</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009183</td>\n",
       "      <td>-0.069116</td>\n",
       "      <td>0.048938</td>\n",
       "      <td>-0.052468</td>\n",
       "      <td>0.020132</td>\n",
       "      <td>0.003001</td>\n",
       "      <td>-0.024289</td>\n",
       "      <td>0.093942</td>\n",
       "      <td>-0.090845</td>\n",
       "      <td>-0.042279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9695</th>\n",
       "      <td>Q496A3.pt</td>\n",
       "      <td>-0.043111</td>\n",
       "      <td>-0.003976</td>\n",
       "      <td>-0.044006</td>\n",
       "      <td>-0.023041</td>\n",
       "      <td>-0.035140</td>\n",
       "      <td>-0.057001</td>\n",
       "      <td>0.011127</td>\n",
       "      <td>-0.026880</td>\n",
       "      <td>0.014060</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016318</td>\n",
       "      <td>-0.116398</td>\n",
       "      <td>0.019991</td>\n",
       "      <td>-0.035673</td>\n",
       "      <td>0.023899</td>\n",
       "      <td>-0.000386</td>\n",
       "      <td>-0.033021</td>\n",
       "      <td>0.085320</td>\n",
       "      <td>-0.021390</td>\n",
       "      <td>-0.087311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9696 rows × 2561 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           filename     col_1     col_2     col_3     col_4     col_5  \\\n",
       "0     A0A087X1C5.pt -0.038923  0.016107 -0.076490 -0.044447 -0.026241   \n",
       "1     A0A0B4J2F0.pt -0.010678 -0.010572 -0.099035 -0.062785 -0.039515   \n",
       "2     A0A0B4J2F2.pt -0.056983  0.015480 -0.107581 -0.050975 -0.049094   \n",
       "3     A0A0C5B5G6.pt -0.000092 -0.037981 -0.069931 -0.040279 -0.072822   \n",
       "4     A0A0K2S4Q6.pt -0.024788 -0.012560 -0.061030 -0.032265 -0.039898   \n",
       "...             ...       ...       ...       ...       ...       ...   \n",
       "9691      Q495M3.pt -0.051883  0.016401 -0.055423 -0.080380 -0.031483   \n",
       "9692      Q495M9.pt -0.077512 -0.081478 -0.086535 -0.056407 -0.059902   \n",
       "9693      Q495T6.pt -0.054756  0.025106 -0.083150 -0.036703 -0.016852   \n",
       "9694      Q495W5.pt -0.057126 -0.010426 -0.056482  0.004159 -0.017741   \n",
       "9695      Q496A3.pt -0.043111 -0.003976 -0.044006 -0.023041 -0.035140   \n",
       "\n",
       "         col_6     col_7     col_8     col_9  ...  col_2551  col_2552  \\\n",
       "0    -0.062517  0.048793 -0.063152  0.047682  ...  0.014710 -0.065358   \n",
       "1    -0.043607  0.035617 -0.081518  0.031148  ...  0.034861 -0.062966   \n",
       "2    -0.015369 -0.000929 -0.073088  0.057361  ...  0.016309 -0.005781   \n",
       "3    -0.058605  0.026483 -0.059635  0.052859  ...  0.017898 -0.075702   \n",
       "4    -0.053276  0.034171 -0.055207  0.009990  ...  0.027765 -0.022588   \n",
       "...        ...       ...       ...       ...  ...       ...       ...   \n",
       "9691 -0.053540  0.030414 -0.032083  0.038185  ...  0.006701 -0.043547   \n",
       "9692 -0.070051  0.037212 -0.011500  0.046766  ... -0.017591 -0.044382   \n",
       "9693 -0.064474  0.057104 -0.035241  0.009740  ...  0.006994 -0.068897   \n",
       "9694 -0.040794  0.017283 -0.064886  0.023010  ... -0.009183 -0.069116   \n",
       "9695 -0.057001  0.011127 -0.026880  0.014060  ...  0.016318 -0.116398   \n",
       "\n",
       "      col_2553  col_2554  col_2555  col_2556  col_2557  col_2558  col_2559  \\\n",
       "0     0.040060 -0.068655 -0.023912  0.035812  0.002793  0.128581 -0.037806   \n",
       "1     0.050289 -0.016540  0.063586 -0.003878  0.004271  0.112121 -0.084403   \n",
       "2     0.025045 -0.051069 -0.013411  0.014069 -0.021879  0.093391 -0.077502   \n",
       "3    -0.065242 -0.060032  0.097588  0.023318 -0.008654  0.071132  0.030236   \n",
       "4     0.024271 -0.145041  0.028161  0.047234 -0.067301  0.113494 -0.093726   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "9691  0.036076 -0.071274  0.002526  0.001005 -0.011456  0.136021 -0.072522   \n",
       "9692  0.012516 -0.062807  0.006686 -0.028964  0.003466  0.153523 -0.080030   \n",
       "9693  0.025549 -0.056556  0.017730 -0.002070 -0.009403  0.103031 -0.095598   \n",
       "9694  0.048938 -0.052468  0.020132  0.003001 -0.024289  0.093942 -0.090845   \n",
       "9695  0.019991 -0.035673  0.023899 -0.000386 -0.033021  0.085320 -0.021390   \n",
       "\n",
       "      col_2560  \n",
       "0    -0.037085  \n",
       "1    -0.112586  \n",
       "2    -0.016692  \n",
       "3    -0.124704  \n",
       "4    -0.054095  \n",
       "...        ...  \n",
       "9691 -0.039517  \n",
       "9692 -0.082515  \n",
       "9693 -0.078120  \n",
       "9694 -0.042279  \n",
       "9695 -0.087311  \n",
       "\n",
       "[9696 rows x 2561 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir_path = 'GO_AA_Embeddings/'\n",
    "# Initialize an empty list to store the data\n",
    "data = []\n",
    "\n",
    "# Iterate over all .npy files in the directory\n",
    "for filename in os.listdir(dir_path):\n",
    "    if filename.endswith('.pt'):\n",
    "        # Load the numpy array\n",
    "        array = torch.load(os.path.join(dir_path, filename))\n",
    "\n",
    "        # Add the filename and array data to the list\n",
    "        row = [filename] + array.tolist()\n",
    "        data.append(row)\n",
    "\n",
    "# Create a DataFrame from the list\n",
    "AA = pd.DataFrame(data)\n",
    "\n",
    "# Set the column names\n",
    "AA.columns = ['filename'] + ['col_{}'.format(i) for i in range(1, AA.shape[1])]\n",
    "\n",
    "# Print the DataFrame\n",
    "AA    # Load the numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e476907f-4282-4966-89ab-77dda8eaf3c7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "AA['filename'] = AA['filename'].str.replace('.pt', '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "01d14873-7201-40ff-9c5f-8b0d45e5a01d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9696, 2561)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AA.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b152093c-8de3-4fd4-9fff-46701e7c23dd",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "filenames = AA['filename'].tolist()\n",
    "\n",
    "# Filter GO based on filenames present in AA\n",
    "filtered_GO = GO[GO['filename'].isin(filenames)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3312c4d7-301a-478c-8f4f-27cddad47596",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "AA_tensor = torch.tensor(AA.iloc[:, 1:].values)\n",
    "GO_tensor = torch.tensor(filtered_GO.iloc[:, 1:].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "281c79a2-c1ff-4eb0-953a-ac45a6b90578",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "torch.save(AA_tensor, 'GO_AA_embeddings.pt')\n",
    "torch.save(GO_tensor, 'GO_term_embeddings.pt')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
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  "language_info": {
   "codemirror_mode": {
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    "version": 3
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   "file_extension": ".py",
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   "name": "python",
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