fix two indexing bugs

README.md

@@ -17,7 +17,7 @@ It can be used for fine-tuning a language model.
 
 The data solely uses data from PDBind-cn.
 
-Contacts are calculated at three cut-off distances: 5, 8 and 11A.
+Contacts are calculated at four cut-off distances: 5, 8, 11A and 15A.
 
 ### Use the already preprocessed data
 

data/pdbbind_with_contacts.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3d715ac89988ff2b436c53390e408145d3e6d2a9dd6771d29b52d5a48f0cb29d
-size 157147287
+oid sha256:904aa3f182745b92c36d97fdc8a4b14a7a19bfe2f88cf05be38ea35f2287d6c3
+size 366634766

pdbbind.ipynb

@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 22,
    "id": "aa358835-55f3-4551-9217-e76a15de4fe8",
    "metadata": {},
    "outputs": [],
@@ -122,18 +122,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 23,
    "id": "802cb9bc-2563-4d7f-9a76-3be2d9263a36",
    "metadata": {},
    "outputs": [],
    "source": [
-    "cutoffs = [5,8,11]"
+    "cutoffs = [5,8,11,15]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "d6dda488-f709-4fe7-b372-080042cf7c66",
+   "execution_count": 24,
+   "id": "d8e71a8c-11a3-41f0-ab61-3ddc57e10961",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,99 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "aebc6791-5bb0-4828-9697-79bc243f8992",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>name</th>\n",
-       "      <th>seq</th>\n",
-       "      <th>smiles</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>10gs</td>\n",
-       "      <td>PYTVVYFPVRGRCAALRMLLADQGQSWKEEVVTVETWQEGSLKASC...</td>\n",
-       "      <td>[NH3+]C(CCC(=O)NC(CSCc1ccccc1)C(=O)NC(C(=O)O)c...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>184l</td>\n",
-       "      <td>MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...</td>\n",
-       "      <td>CC(C)Cc1ccccc1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>186l</td>\n",
-       "      <td>MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...</td>\n",
-       "      <td>CCCCc1ccccc1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>187l</td>\n",
-       "      <td>MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...</td>\n",
-       "      <td>Cc1ccc(C)cc1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>188l</td>\n",
-       "      <td>MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...</td>\n",
-       "      <td>Cc1ccccc1C</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   name                                                seq  \\\n",
-       "0  10gs  PYTVVYFPVRGRCAALRMLLADQGQSWKEEVVTVETWQEGSLKASC...   \n",
-       "1  184l  MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...   \n",
-       "2  186l  MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...   \n",
-       "3  187l  MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...   \n",
-       "4  188l  MNIFEMLRIDEGLRLKIYKDTEGYYTIGIGHLLTKSPSLNAAKSEL...   \n",
-       "\n",
-       "                                              smiles  \n",
-       "0  [NH3+]C(CCC(=O)NC(CSCc1ccccc1)C(=O)NC(C(=O)O)c...  \n",
-       "1                                     CC(C)Cc1ccccc1  \n",
-       "2                                       CCCCc1ccccc1  \n",
-       "3                                       Cc1ccc(C)cc1  \n",
-       "4                                         Cc1ccccc1C  "
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "list(dfs_complex.values())[0].head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 25,
    "id": "ed3fe035-6035-4d39-b072-d12dc0a95857",
    "metadata": {},
    "outputs": [],
@@ -249,18 +157,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 26,
    "id": "cd26125b-e68b-4fa3-846e-2b6e7f635fe0",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2046, 510)\n"
+     ]
+    }
+   ],
    "source": [
     "contacts_dask = [da.from_npy_stack('data/pdbbind_contacts_{}'.format(c)) for c in cutoffs]\n",
-    "contacts_dask = [c.reshape(-1,c.shape[-2]*c.shape[-1]) for c in contacts_dask]"
+    "shape = contacts_dask[0][0].shape\n",
+    "print(shape)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 27,
    "id": "9c7c9849-2345-4baf-89e7-d412f52353b6",
    "metadata": {},
    "outputs": [
@@ -275,40 +192,63 @@
        "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><th> Bytes </th><td> 1.70 GiB </td> <td> 1.70 GiB </td></tr>\n",
-       "    <tr><th> Shape </th><td> (438, 1043460) </td> <td> (438, 1043460) </td></tr>\n",
-       "    <tr><th> Count </th><td> 75 Tasks </td><td> 1 Chunks </td></tr>\n",
+       "    <tr><th> Bytes </th><td> 2.72 GiB </td> <td> 2.72 GiB </td></tr>\n",
+       "    <tr><th> Shape </th><td> (700, 2046, 510) </td> <td> (700, 2046, 510) </td></tr>\n",
+       "    <tr><th> Count </th><td> 25 Tasks </td><td> 1 Chunks </td></tr>\n",
        "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</td>\n",
        "<td>\n",
-       "<svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "<svg width=\"128\" height=\"195\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
        "\n",
        "  <!-- Horizontal lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"120\" x2=\"35\" y2=\"145\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Vertical lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"145\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Colored Rectangle -->\n",
-       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "  <polygon points=\"10.0,0.0 35.86269549127143,25.86269549127143 35.86269549127143,145.86269549127144 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"52\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"78\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"52\" y1=\"0\" x2=\"78\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"10.0,0.0 52.88780092952726,0.0 78.7504964207987,25.86269549127143 35.86269549127143,25.86269549127143\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"78\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"145\" x2=\"78\" y2=\"145\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"145\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"78\" y1=\"25\" x2=\"78\" y2=\"145\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"35.86269549127143,25.86269549127143 78.7504964207987,25.86269549127143 78.7504964207987,145.86269549127144 35.86269549127143,145.86269549127144\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
        "\n",
        "  <!-- Text -->\n",
-       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1043460</text>\n",
-       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,12.706308)\">438</text>\n",
+       "  <text x=\"57.306596\" y=\"165.862695\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >510</text>\n",
+       "  <text x=\"98.750496\" y=\"85.862695\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,98.750496,85.862695)\">2046</text>\n",
+       "  <text x=\"12.931348\" y=\"152.931348\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,12.931348,152.931348)\">700</text>\n",
        "</svg>\n",
        "</td>\n",
        "</tr>\n",
        "</table>"
       ],
       "text/plain": [
-       "dask.array<blocks, shape=(438, 1043460), dtype=float32, chunksize=(438, 1043460), chunktype=numpy.ndarray>"
+       "dask.array<blocks, shape=(700, 2046, 510), dtype=float32, chunksize=(700, 2046, 510), chunktype=numpy.ndarray>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -319,17 +259,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 28,
    "id": "0bd8e9b9-9713-4572-bd7f-dc47da9fce91",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[16206, 16181, 16172]"
+       "[16221, 16201, 16193, 16189]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -340,17 +280,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 29,
    "id": "87493934-3839-476a-a975-7da057c320da",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "16206"
+       "16221"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -361,31 +301,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "1f7815ec-cddf-4bae-b72c-89cdf56cc1f9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "name                                                   9lpr\n",
-       "seq       ANIVGGIEYSINNASLCSVGFSVTRGATKGFVTAGHCGTVNATARI...\n",
-       "smiles    CC(C)CC(NC(=O)C1CCCN1C(=O)C(C)NC(=O)C(C)[NH3+]...\n",
-       "Name: 16205, dtype: object"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dfs_complex[5].iloc[16205]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 30,
    "id": "42e95d84-ef27-4417-9479-8b356462b8c3",
    "metadata": {},
    "outputs": [],
@@ -396,7 +312,7 @@
     "    def chunk_to_sparse(rcut, chunk, idx_chunk):\n",
     "        res = dfs_complex[rcut].iloc[idx_chunk][['name']].copy()\n",
     "        # pad to account for [CLS] and [SEP]\n",
-    "        res['contacts_{}A'.format(rcut)] = [np.where(np.pad(a,pad_width=(1,1)))[0] for a in chunk]\n",
+    "        res['contacts_{}A'.format(rcut)] = [np.where(np.pad(a,pad_width=(1,1)).flatten())[0] for a in chunk]\n",
     "        return res\n",
     "\n",
     "    partitions = [delayed(chunk_to_sparse)(cutoff,b,k)\n",
@@ -407,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 31,
    "id": "5520a925-693f-43f0-9e76-df2e128f272e",
    "metadata": {},
    "outputs": [
@@ -440,27 +356,27 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>10gs</td>\n",
-       "      <td>[1021, 1022, 1070, 1073, 1075, 3071, 3072, 307...</td>\n",
+       "      <td>[1025, 1026, 1074, 1077, 1079, 3083, 3084, 308...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>184l</td>\n",
-       "      <td>[39279, 39280, 39281, 39282, 42332, 42334, 423...</td>\n",
+       "      <td>[39945, 39946, 39947, 39948, 43010, 43012, 430...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>186l</td>\n",
-       "      <td>[39277, 39278, 39279, 42332, 42333, 42334, 423...</td>\n",
+       "      <td>[39943, 39944, 39945, 43010, 43011, 43012, 430...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>187l</td>\n",
-       "      <td>[39271, 39272, 39281, 42331, 42332, 42334, 423...</td>\n",
+       "      <td>[39937, 39938, 39947, 43009, 43010, 43012, 430...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>188l</td>\n",
-       "      <td>[39271, 39272, 39274, 39275, 42331, 42332, 423...</td>\n",
+       "      <td>[39937, 39938, 39940, 39941, 43009, 43010, 430...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -468,14 +384,14 @@
       ],
       "text/plain": [
        "   name                                        contacts_5A\n",
-       "0  10gs  [1021, 1022, 1070, 1073, 1075, 3071, 3072, 307...\n",
-       "1  184l  [39279, 39280, 39281, 39282, 42332, 42334, 423...\n",
-       "2  186l  [39277, 39278, 39279, 42332, 42333, 42334, 423...\n",
-       "3  187l  [39271, 39272, 39281, 42331, 42332, 42334, 423...\n",
-       "4  188l  [39271, 39272, 39274, 39275, 42331, 42332, 423..."
+       "0  10gs  [1025, 1026, 1074, 1077, 1079, 3083, 3084, 308...\n",
+       "1  184l  [39945, 39946, 39947, 39948, 43010, 43012, 430...\n",
+       "2  186l  [39943, 39944, 39945, 43010, 43011, 43012, 430...\n",
+       "3  187l  [39937, 39938, 39947, 43009, 43010, 43012, 430...\n",
+       "4  188l  [39937, 39938, 39940, 39941, 43009, 43010, 430..."
       ]
      },
-     "execution_count": 18,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -486,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 32,
    "id": "4982c3b1-5ce9-4f17-9834-a02c4e136bc2",
    "metadata": {},
    "outputs": [],
@@ -496,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 33,
    "id": "f6cdee43-33c6-445c-8619-ace20f90638c",
    "metadata": {},
    "outputs": [],
@@ -513,7 +429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 34,
    "id": "8f49f871-76f6-4fb2-b2db-c0794d4c07bf",
    "metadata": {},
    "outputs": [
@@ -521,8 +437,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 6min 9s, sys: 12min 7s, total: 18min 17s\n",
-      "Wall time: 7min 36s\n"
+      "CPU times: user 8min 48s, sys: 12min 3s, total: 20min 52s\n",
+      "Wall time: 3min 20s\n"
      ]
     }
    ],
@@ -533,7 +449,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 35,
    "id": "45e4b4fa-6338-4abe-bd6e-8aea46e2a09c",
    "metadata": {},
    "outputs": [],
@@ -543,17 +459,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 36,
    "id": "7c3db301-6565-4053-bbd4-139bb41dd1c4",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(array([6.35008182]), array([3.56554195]))"
+       "(array([6.34974652]), array([3.56691843]))"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -567,7 +483,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 37,
    "id": "c9d674bb-d6a2-4810-aa2b-e3bc3b4bbc98",
    "metadata": {},
    "outputs": [],
@@ -579,7 +495,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "02addbaf-094d-4e40-8904-4fe306647298",
+   "id": "8e5f99f3-4aa6-44c9-afd8-9c62bdef9d5f",
    "metadata": {},
    "outputs": [],
    "source": []

pdbbind.py

@@ -71,7 +71,8 @@ def parse_complex(fn):
         neighbor_search = NeighborSearch(atoms)
 
         close_residues = [neighbor_search.search(center=t, level='R', radius=cutoff) for t in token_pos]
-        residue_id = [[c.get_id()[1]-1 for c in query] for query in close_residues] # zero-based
+        first_residue = next(structure.get_residues()).get_id()[1]
+        residue_id = [[c.get_id()[1]-first_residue for c in query] for query in close_residues] # zero-based
 
         # contact map
         contact_map = np.zeros((max_seq, max_smiles),dtype=np.float32)