docs/tutorials/comparison.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison\n",
    "\n",
    "The distance between two fingerprints is calculated in two steps:\n",
    "\n",
    "1. Calculate __feature distances__: Calculate distance for each feature (e.g. distance between pairwise 85 size feature bits). Use L1 norm for discrete features and L2 norm for continuous features (scaled by number of bits per feature).\n",
    "2. Calculate __fingerprint distance__: Calculate the weighted sum of all feature distances (sum of feature weights equals 1).\n",
    "\n",
    "![The `kissim` fingerprint comparison.](../_static/kissim_comparison.png)\n",
    "\n",
    "_Figure 1_: The pairwise `kissim` fingerprint comparison.\n",
    "\n",
    "Respective objects performing these calculates are the `FeatureDistances` and `FingerprintDistance` objects.\n",
    "Furthermore, such distances can not only be generated between two fingerprints as described above but also in bulk for a set of fingerprints in an all-against-all comparison using the objects `FingerprintDistanceGenerator` and `FeatureDistancesGenerator`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the API logic in this table again:\n",
    "\n",
    "| Action                                                         | Module       | Single calculation    | Bulk calculation               |\n",
    "|----------------------------------------------------------------|--------------|-----------------------|--------------------------------|\n",
    "| Encode structures as fingerprint                               | `encoding`   | `Fingerprint`         | `FingerprintGenerator`         |\n",
    "| Compare fingerprint features (calculate feature distance**s**) | `comparison` | `FeatureDistances`    | `FeatureDistancesGenerator`    |\n",
    "| Compare fingerprints (calculate fingerprint distance)          | `comparison` | `FingerprintDistance` | `FingerprintDistanceGenerator` |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load path to test data\n",
    "from kissim.dataset.test import PATH as PATH_TEST_DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up local KLIFS session using the `opencadd.databases.klifs` module."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from opencadd.databases.klifs import setup_local\n",
    "\n",
    "KLIFS_LOCAL = setup_local(PATH_TEST_DATA / \"KLIFS_download\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select structure KLIFS IDs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "structure_klifs_ids = [109, 118, 12347, 1641, 3833, 9122]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate fingerprints\n",
    "\n",
    "Let's generate a few fingerprints for the structures in our local KLIFS download using the bulk fingerprint generator `FingerprintGenerator`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of fingerprints: 6\n"
     ]
    }
   ],
   "source": [
    "from kissim.encoding import FingerprintGenerator\n",
    "\n",
    "fingerprint_generator = FingerprintGenerator.from_structure_klifs_ids(\n",
    "    structure_klifs_ids=structure_klifs_ids, klifs_session=KLIFS_LOCAL\n",
    ")\n",
    "print(f\"Number of fingerprints: {len(fingerprint_generator.data.keys())}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Note__: If fingerprint cannot be generated (e.g. because structural data is missing), the structure is skipped."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare two fingerprints\n",
    "\n",
    "Let's first focus on the comparison between two fingerprints only.\n",
    "\n",
    "For two fingerprints (`Fingerprint` objects), we will \n",
    "\n",
    "1. Calculate the _feature distances_ using `FeatureDistances` and \n",
    "2. Calculate based on these _feature distances_ and given _feature weights_ the final _fingerprint distance_ using `FingerprintDistance`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate feature distances between two fingerprints (`FeatureDistances`)\n",
    "\n",
    "- Input: Two `Fingerprint` objects\n",
    "- Output: `FeatureDistances` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "fingerprints = list(fingerprint_generator.data.values())\n",
    "fingerprint1 = fingerprints[0]\n",
    "fingerprint2 = fingerprints[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kinase pair: ('ABL2', 'ABL2')\n",
      "Structure pair: (109, 118)\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature_type</th>\n",
       "      <th>feature_name</th>\n",
       "      <th>distance</th>\n",
       "      <th>bit_coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>size</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>hbd</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>hba</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>charge</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>aromatic</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>aliphatic</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>sco</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>physicochemical</td>\n",
       "      <td>exposure</td>\n",
       "      <td>0.294118</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>distances</td>\n",
       "      <td>distance_to_centroid</td>\n",
       "      <td>0.059839</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>distances</td>\n",
       "      <td>distance_to_hinge_region</td>\n",
       "      <td>0.122168</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>distances</td>\n",
       "      <td>distance_to_dfg_region</td>\n",
       "      <td>0.105499</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>distances</td>\n",
       "      <td>distance_to_front_pocket</td>\n",
       "      <td>0.070291</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>moments</td>\n",
       "      <td>moment1</td>\n",
       "      <td>0.060816</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>moments</td>\n",
       "      <td>moment2</td>\n",
       "      <td>0.116013</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>moments</td>\n",
       "      <td>moment3</td>\n",
       "      <td>0.204469</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       feature_type              feature_name  distance  bit_coverage\n",
       "0   physicochemical                      size  0.000000          1.00\n",
       "1   physicochemical                       hbd  0.000000          1.00\n",
       "2   physicochemical                       hba  0.000000          1.00\n",
       "3   physicochemical                    charge  0.000000          1.00\n",
       "4   physicochemical                  aromatic  0.000000          1.00\n",
       "5   physicochemical                 aliphatic  0.000000          1.00\n",
       "6   physicochemical                       sco  0.080000          0.88\n",
       "7   physicochemical                  exposure  0.294118          1.00\n",
       "8         distances      distance_to_centroid  0.059839          1.00\n",
       "9         distances  distance_to_hinge_region  0.122168          1.00\n",
       "10        distances    distance_to_dfg_region  0.105499          1.00\n",
       "11        distances  distance_to_front_pocket  0.070291          1.00\n",
       "12          moments                   moment1  0.060816          1.00\n",
       "13          moments                   moment2  0.116013          1.00\n",
       "14          moments                   moment3  0.204469          1.00"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from kissim.comparison import FeatureDistances\n",
    "\n",
    "feature_distances = FeatureDistances.from_fingerprints(fingerprint1, fingerprint2)\n",
    "print(f\"Kinase pair: {feature_distances.kinase_pair_ids}\")\n",
    "print(f\"Structure pair: {feature_distances.structure_pair_ids}\")\n",
    "feature_distances.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate fingerprint distance between two fingerprints (`FingerprintDistance`)\n",
    "\n",
    "- Input: `FeatureDistances` object and optionally feature weights\n",
    "- Output: `FingerprintDistance` object"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Use standard feature weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fingerprint distance: 0.07421423894307076\n",
      "Fingerprint bit coverage: 0.9919999999999999\n"
     ]
    }
   ],
   "source": [
    "from kissim.comparison import FingerprintDistance\n",
    "\n",
    "fingerprint_distance = FingerprintDistance.from_feature_distances(\n",
    "    feature_distances, feature_weights=None\n",
    ")\n",
    "print(f\"Fingerprint distance: {fingerprint_distance.distance}\")\n",
    "print(f\"Fingerprint bit coverage: {fingerprint_distance.bit_coverage}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Use user-defined feature weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fingerprint distance: 0.08417398268335104\n",
      "Fingerprint bit coverage: 0.9954999999999999\n"
     ]
    }
   ],
   "source": [
    "feature_weights = [0.3 / 8] * 8 + [0.5 / 4] * 4 + [0.2 / 3] * 3\n",
    "fingerprint_distance = FingerprintDistance.from_feature_distances(\n",
    "    feature_distances, feature_weights=feature_weights\n",
    ")\n",
    "print(f\"Fingerprint distance: {fingerprint_distance.distance}\")\n",
    "print(f\"Fingerprint bit coverage: {fingerprint_distance.bit_coverage}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare all-against-all fingerprints\n",
    "\n",
    "Let's now take a look at the bulk distance generators to generate all-against-all comparisons for a set of fingerprints.\n",
    "\n",
    "For a `FingerprintGenerator` object, which contains the fingerprints for a set of structures, we will \n",
    "\n",
    "1. Calculate _feature distances_ for all fingerprint pairs using `FeatureDistancesGenerator` and \n",
    "2. Calculate based on these _feature distances_ and given _feature weights_ the final _fingerprint distance_ for all fingerprint pairs using `FingerprintDistanceGenerator`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate feature distances for all pairwise structures/fingerprints (`FeatureDistancesGenerator`)\n",
    "\n",
    "- Input: `FingerprintGenerator` object\n",
    "- Output: `FeatureDistancesGenerator` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>structure.1</th>\n",
       "      <th>structure.2</th>\n",
       "      <th>kinase.1</th>\n",
       "      <th>kinase.2</th>\n",
       "      <th>distance.1</th>\n",
       "      <th>distance.2</th>\n",
       "      <th>distance.3</th>\n",
       "      <th>distance.4</th>\n",
       "      <th>distance.5</th>\n",
       "      <th>distance.6</th>\n",
       "      <th>...</th>\n",
       "      <th>bit_coverage.6</th>\n",
       "      <th>bit_coverage.7</th>\n",
       "      <th>bit_coverage.8</th>\n",
       "      <th>bit_coverage.9</th>\n",
       "      <th>bit_coverage.10</th>\n",
       "      <th>bit_coverage.11</th>\n",
       "      <th>bit_coverage.12</th>\n",
       "      <th>bit_coverage.13</th>\n",
       "      <th>bit_coverage.14</th>\n",
       "      <th>bit_coverage.15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>109</td>\n",
       "      <td>118</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>109</td>\n",
       "      <td>12347</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>0.410256</td>\n",
       "      <td>0.397436</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.243590</td>\n",
       "      <td>0.141026</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>109</td>\n",
       "      <td>1641</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>0.388235</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.364706</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.141176</td>\n",
       "      <td>0.223529</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>109</td>\n",
       "      <td>3833</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>0.505882</td>\n",
       "      <td>0.505882</td>\n",
       "      <td>0.411765</td>\n",
       "      <td>0.211765</td>\n",
       "      <td>0.082353</td>\n",
       "      <td>0.270588</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>109</td>\n",
       "      <td>9122</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.623529</td>\n",
       "      <td>0.470588</td>\n",
       "      <td>0.435294</td>\n",
       "      <td>0.258824</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>0.305882</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>118</td>\n",
       "      <td>12347</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>0.410256</td>\n",
       "      <td>0.397436</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.243590</td>\n",
       "      <td>0.141026</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>118</td>\n",
       "      <td>1641</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>0.388235</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.364706</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.141176</td>\n",
       "      <td>0.223529</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.84</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>118</td>\n",
       "      <td>3833</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>0.505882</td>\n",
       "      <td>0.505882</td>\n",
       "      <td>0.411765</td>\n",
       "      <td>0.211765</td>\n",
       "      <td>0.082353</td>\n",
       "      <td>0.270588</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>118</td>\n",
       "      <td>9122</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.623529</td>\n",
       "      <td>0.470588</td>\n",
       "      <td>0.435294</td>\n",
       "      <td>0.258824</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>0.305882</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12347</td>\n",
       "      <td>1641</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>0.346154</td>\n",
       "      <td>0.423077</td>\n",
       "      <td>0.346154</td>\n",
       "      <td>0.243590</td>\n",
       "      <td>0.115385</td>\n",
       "      <td>0.217949</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>12347</td>\n",
       "      <td>3833</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>0.435897</td>\n",
       "      <td>0.474359</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>0.102564</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12347</td>\n",
       "      <td>9122</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.576923</td>\n",
       "      <td>0.371795</td>\n",
       "      <td>0.397436</td>\n",
       "      <td>0.256410</td>\n",
       "      <td>0.269231</td>\n",
       "      <td>0.282051</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1641</td>\n",
       "      <td>3833</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.411765</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.082353</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.84</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1641</td>\n",
       "      <td>9122</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.611765</td>\n",
       "      <td>0.494118</td>\n",
       "      <td>0.541176</td>\n",
       "      <td>0.317647</td>\n",
       "      <td>0.282353</td>\n",
       "      <td>0.317647</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3833</td>\n",
       "      <td>9122</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.611765</td>\n",
       "      <td>0.482353</td>\n",
       "      <td>0.494118</td>\n",
       "      <td>0.282353</td>\n",
       "      <td>0.223529</td>\n",
       "      <td>0.341176</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    structure.1  structure.2 kinase.1 kinase.2  distance.1  distance.2  \\\n",
       "0           109          118     ABL2     ABL2    0.000000    0.000000   \n",
       "1           109        12347     ABL2     BRAF    0.410256    0.397436   \n",
       "2           109         1641     ABL2     CHK1    0.388235    0.352941   \n",
       "3           109         3833     ABL2     AAK1    0.505882    0.505882   \n",
       "4           109         9122     ABL2    ADCK3    0.623529    0.470588   \n",
       "5           118        12347     ABL2     BRAF    0.410256    0.397436   \n",
       "6           118         1641     ABL2     CHK1    0.388235    0.352941   \n",
       "7           118         3833     ABL2     AAK1    0.505882    0.505882   \n",
       "8           118         9122     ABL2    ADCK3    0.623529    0.470588   \n",
       "9         12347         1641     BRAF     CHK1    0.346154    0.423077   \n",
       "10        12347         3833     BRAF     AAK1    0.435897    0.474359   \n",
       "11        12347         9122     BRAF    ADCK3    0.576923    0.371795   \n",
       "12         1641         3833     CHK1     AAK1    0.352941    0.411765   \n",
       "13         1641         9122     CHK1    ADCK3    0.611765    0.494118   \n",
       "14         3833         9122     AAK1    ADCK3    0.611765    0.482353   \n",
       "\n",
       "    distance.3  distance.4  distance.5  distance.6  ...  bit_coverage.6  \\\n",
       "0     0.000000    0.000000    0.000000    0.000000  ...            1.00   \n",
       "1     0.333333    0.243590    0.141026    0.230769  ...            0.92   \n",
       "2     0.364706    0.247059    0.141176    0.223529  ...            1.00   \n",
       "3     0.411765    0.211765    0.082353    0.270588  ...            1.00   \n",
       "4     0.435294    0.258824    0.235294    0.305882  ...            1.00   \n",
       "5     0.333333    0.243590    0.141026    0.230769  ...            0.92   \n",
       "6     0.364706    0.247059    0.141176    0.223529  ...            1.00   \n",
       "7     0.411765    0.211765    0.082353    0.270588  ...            1.00   \n",
       "8     0.435294    0.258824    0.235294    0.305882  ...            1.00   \n",
       "9     0.346154    0.243590    0.115385    0.217949  ...            0.92   \n",
       "10    0.333333    0.230769    0.102564    0.230769  ...            0.92   \n",
       "11    0.397436    0.256410    0.269231    0.282051  ...            0.92   \n",
       "12    0.352941    0.200000    0.082353    0.235294  ...            1.00   \n",
       "13    0.541176    0.317647    0.282353    0.317647  ...            1.00   \n",
       "14    0.494118    0.282353    0.223529    0.341176  ...            1.00   \n",
       "\n",
       "    bit_coverage.7  bit_coverage.8  bit_coverage.9  bit_coverage.10  \\\n",
       "0             0.88            1.00            1.00             1.00   \n",
       "1             0.67            0.92            0.92             0.92   \n",
       "2             0.86            1.00            1.00             1.00   \n",
       "3             0.86            1.00            1.00             1.00   \n",
       "4             0.88            0.98            1.00             1.00   \n",
       "5             0.65            0.92            0.92             0.92   \n",
       "6             0.84            1.00            1.00             1.00   \n",
       "7             0.85            1.00            1.00             1.00   \n",
       "8             0.86            0.98            1.00             1.00   \n",
       "9             0.65            0.92            0.92             0.92   \n",
       "10            0.65            0.92            0.92             0.92   \n",
       "11            0.68            0.89            0.92             0.92   \n",
       "12            0.84            1.00            1.00             1.00   \n",
       "13            0.86            0.98            1.00             1.00   \n",
       "14            0.87            0.98            1.00             1.00   \n",
       "\n",
       "    bit_coverage.11  bit_coverage.12  bit_coverage.13  bit_coverage.14  \\\n",
       "0              1.00             1.00              1.0              1.0   \n",
       "1              0.92             0.92              1.0              1.0   \n",
       "2              1.00             1.00              1.0              1.0   \n",
       "3              1.00             1.00              1.0              1.0   \n",
       "4              1.00             1.00              1.0              1.0   \n",
       "5              0.92             0.92              1.0              1.0   \n",
       "6              1.00             1.00              1.0              1.0   \n",
       "7              1.00             1.00              1.0              1.0   \n",
       "8              1.00             1.00              1.0              1.0   \n",
       "9              0.92             0.92              1.0              1.0   \n",
       "10             0.92             0.92              1.0              1.0   \n",
       "11             0.92             0.92              1.0              1.0   \n",
       "12             1.00             1.00              1.0              1.0   \n",
       "13             1.00             1.00              1.0              1.0   \n",
       "14             1.00             1.00              1.0              1.0   \n",
       "\n",
       "    bit_coverage.15  \n",
       "0               1.0  \n",
       "1               1.0  \n",
       "2               1.0  \n",
       "3               1.0  \n",
       "4               1.0  \n",
       "5               1.0  \n",
       "6               1.0  \n",
       "7               1.0  \n",
       "8               1.0  \n",
       "9               1.0  \n",
       "10              1.0  \n",
       "11              1.0  \n",
       "12              1.0  \n",
       "13              1.0  \n",
       "14              1.0  \n",
       "\n",
       "[15 rows x 34 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from kissim.comparison import FeatureDistancesGenerator\n",
    "\n",
    "feature_distances_generator = FeatureDistancesGenerator.from_fingerprint_generator(\n",
    "    fingerprint_generator\n",
    ")\n",
    "feature_distances_generator.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate fingerprint distance for all pairwise structures/fingerprints (`FingerprintDistanceGenerator`)\n",
    "\n",
    "- Input: `FeatureDistancesGenerator` object (or `FingerprintGenerator` object) and optionally feature weights\n",
    "- Output: `FingerprintDistanceGenerator` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e13f101d607c4312a4aae679fb02b14e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Calculate pairwise fingerprint distance:   0%|          | 0/15 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d21170f9ba954df2ab2bb618c6aca131",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Calculate pairwise fingerprint coverage:   0%|          | 0/15 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kissim.comparison import FingerprintDistanceGenerator\n",
    "\n",
    "fingerprint_distance_generator = FingerprintDistanceGenerator.from_feature_distances_generator(\n",
    "    feature_distances_generator\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**: Fingerprint distances can also be calculated directy from the fingerprints (`FingerprintGenerator` > `FingerprintDistanceGenerator`) instead of using the feature distances explicitly as show above (`FingerprintGenerator` > `FeatureDistancesGenerator` > `FingerprintDistanceGenerator`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0dd9b34d3c74297862f875deee01bf0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Calculate pairwise fingerprint distance:   0%|          | 0/15 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3de95b094d8d402bb0e8cda11dab66f4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Calculate pairwise fingerprint coverage:   0%|          | 0/15 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fingerprint_distance_generator = FingerprintDistanceGenerator.from_fingerprint_generator(\n",
    "    fingerprint_generator\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>structure.1</th>\n",
       "      <th>structure.2</th>\n",
       "      <th>kinase.1</th>\n",
       "      <th>kinase.2</th>\n",
       "      <th>distance</th>\n",
       "      <th>bit_coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>109</td>\n",
       "      <td>118</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>0.074214</td>\n",
       "      <td>0.992000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>109</td>\n",
       "      <td>12347</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>BRAF</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.919333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>109</td>\n",
       "      <td>1641</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>CHK1</td>\n",
       "      <td>0.253045</td>\n",
       "      <td>0.990667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>109</td>\n",
       "      <td>3833</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>AAK1</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.990667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>109</td>\n",
       "      <td>9122</td>\n",
       "      <td>ABL2</td>\n",
       "      <td>ADCK3</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.990667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   structure.1  structure.2 kinase.1 kinase.2  distance  bit_coverage\n",
       "0          109          118     ABL2     ABL2  0.074214      0.992000\n",
       "1          109        12347     ABL2     BRAF  0.259053      0.919333\n",
       "2          109         1641     ABL2     CHK1  0.253045      0.990667\n",
       "3          109         3833     ABL2     AAK1  0.277368      0.990667\n",
       "4          109         9122     ABL2    ADCK3  0.358882      0.990667"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Kinase distance matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kinase.2</th>\n",
       "      <th>AAK1</th>\n",
       "      <th>ABL2</th>\n",
       "      <th>ADCK3</th>\n",
       "      <th>BRAF</th>\n",
       "      <th>CHK1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.303542</td>\n",
       "      <td>0.307277</td>\n",
       "      <td>0.229590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABL2</th>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.246844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>0.303542</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.376875</td>\n",
       "      <td>0.347142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAF</th>\n",
       "      <td>0.307277</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.376875</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.303330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>0.229590</td>\n",
       "      <td>0.246844</td>\n",
       "      <td>0.347142</td>\n",
       "      <td>0.303330</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kinase.2      AAK1      ABL2     ADCK3      BRAF      CHK1\n",
       "kinase.1                                                  \n",
       "AAK1      0.000000  0.277368  0.303542  0.307277  0.229590\n",
       "ABL2      0.277368  0.000000  0.358882  0.259053  0.246844\n",
       "ADCK3     0.303542  0.358882  0.000000  0.376875  0.347142\n",
       "BRAF      0.307277  0.259053  0.376875  0.000000  0.303330\n",
       "CHK1      0.229590  0.246844  0.347142  0.303330  0.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distance_matrix(by=\"minimum\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Show on diagonal experimental values for structure pairs representing each kinase pair (as opposed to simply setting the diagonal to 0 by default)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kinase.2</th>\n",
       "      <th>AAK1</th>\n",
       "      <th>ABL2</th>\n",
       "      <th>ADCK3</th>\n",
       "      <th>BRAF</th>\n",
       "      <th>CHK1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.303542</td>\n",
       "      <td>0.307277</td>\n",
       "      <td>0.229590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABL2</th>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.074214</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.246844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>0.303542</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.376875</td>\n",
       "      <td>0.347142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAF</th>\n",
       "      <td>0.307277</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.376875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.303330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>0.229590</td>\n",
       "      <td>0.246844</td>\n",
       "      <td>0.347142</td>\n",
       "      <td>0.303330</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kinase.2      AAK1      ABL2     ADCK3      BRAF      CHK1\n",
       "kinase.1                                                  \n",
       "AAK1           NaN  0.277368  0.303542  0.307277  0.229590\n",
       "ABL2      0.277368  0.074214  0.358882  0.259053  0.246844\n",
       "ADCK3     0.303542  0.358882       NaN  0.376875  0.347142\n",
       "BRAF      0.307277  0.259053  0.376875       NaN  0.303330\n",
       "CHK1      0.229590  0.246844  0.347142  0.303330       NaN"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distance_matrix(by=\"minimum\", fill_diagonal=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More structure-kinase mapping methods are available, e.g. `maximum` or `mean`. Additionally, the number of structure pairs per kinase pair can be fetched."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kinase.2</th>\n",
       "      <th>AAK1</th>\n",
       "      <th>ABL2</th>\n",
       "      <th>ADCK3</th>\n",
       "      <th>BRAF</th>\n",
       "      <th>CHK1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABL2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAF</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kinase.2  AAK1  ABL2  ADCK3  BRAF  CHK1\n",
       "kinase.1                               \n",
       "AAK1         0     2      1     1     1\n",
       "ABL2         2     1      2     2     2\n",
       "ADCK3        1     2      0     1     1\n",
       "BRAF         1     2      1     0     1\n",
       "CHK1         1     2      1     1     0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distance_matrix(by=\"size\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kinase.2</th>\n",
       "      <th>AAK1</th>\n",
       "      <th>ABL2</th>\n",
       "      <th>ADCK3</th>\n",
       "      <th>BRAF</th>\n",
       "      <th>CHK1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABL2</th>\n",
       "      <td>0.004</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAF</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kinase.2   AAK1   ABL2  ADCK3  BRAF   CHK1\n",
       "kinase.1                                  \n",
       "AAK1      0.000  0.004    NaN   NaN    NaN\n",
       "ABL2      0.004  0.000  0.001  0.01  0.004\n",
       "ADCK3       NaN  0.001  0.000   NaN    NaN\n",
       "BRAF        NaN  0.010    NaN  0.00    NaN\n",
       "CHK1        NaN  0.004    NaN   NaN  0.000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distance_matrix(by=\"std\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The kinase distance matrix can also be filtered for kinase pairs with a user-defined bit coverage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kinase.2</th>\n",
       "      <th>AAK1</th>\n",
       "      <th>ABL2</th>\n",
       "      <th>ADCK3</th>\n",
       "      <th>CHK1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABL2</th>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.253045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.253045</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kinase.2      AAK1      ABL2     ADCK3      CHK1\n",
       "kinase.1                                        \n",
       "AAK1      0.000000  0.277368       NaN       NaN\n",
       "ABL2      0.277368  0.000000  0.358882  0.253045\n",
       "ADCK3          NaN  0.358882  0.000000       NaN\n",
       "CHK1           NaN  0.253045       NaN  0.000000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distance_matrix(by=\"minimum\", coverage_min=0.99)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you are interested in more information about selected structure pairs (in case of methods `minimum` and `maximum`), please use the following method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>structure.1</th>\n",
       "      <th>structure.2</th>\n",
       "      <th>distance</th>\n",
       "      <th>bit_coverage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kinase.1</th>\n",
       "      <th>kinase.2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">ABL2</th>\n",
       "      <th>ABL2</th>\n",
       "      <td>0</td>\n",
       "      <td>109</td>\n",
       "      <td>118</td>\n",
       "      <td>0.074214</td>\n",
       "      <td>0.992000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAF</th>\n",
       "      <td>1</td>\n",
       "      <td>109</td>\n",
       "      <td>12347</td>\n",
       "      <td>0.259053</td>\n",
       "      <td>0.919333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHK1</th>\n",
       "      <td>6</td>\n",
       "      <td>118</td>\n",
       "      <td>1641</td>\n",
       "      <td>0.246844</td>\n",
       "      <td>0.989333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAK1</th>\n",
       "      <td>3</td>\n",
       "      <td>109</td>\n",
       "      <td>3833</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.990667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADCK3</th>\n",
       "      <td>4</td>\n",
       "      <td>109</td>\n",
       "      <td>9122</td>\n",
       "      <td>0.358882</td>\n",
       "      <td>0.990667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   index  structure.1  structure.2  distance  bit_coverage\n",
       "kinase.1 kinase.2                                                         \n",
       "ABL2     ABL2          0          109          118  0.074214      0.992000\n",
       "         BRAF          1          109        12347  0.259053      0.919333\n",
       "         CHK1          6          118         1641  0.246844      0.989333\n",
       "         AAK1          3          109         3833  0.277368      0.990667\n",
       "         ADCK3         4          109         9122  0.358882      0.990667"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fingerprint_distance_generator.kinase_distances(by=\"minimum\").head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Structure distance matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "structure.2     109       118       1641      3833      9122      12347\n",
       "structure.1                                                            \n",
       "109          0.000000  0.074214  0.253045  0.277368  0.358882  0.259053\n",
       "118          0.074214  0.000000  0.246844  0.282949  0.360833  0.273133\n",
       "1641         0.253045  0.246844  0.000000  0.229590  0.347142  0.303330\n",
       "3833         0.277368  0.282949  0.229590  0.000000  0.303542  0.307277\n",
       "9122         0.358882  0.360833  0.347142  0.303542  0.000000  0.376875\n",
       "12347        0.259053  0.273133  0.303330  0.307277  0.376875  0.000000"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "fingerprint_distance_generator.structure_distance_matrix()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The structure distance matrix can also be filtered for structure pairs with a user-defined bit coverage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "structure.2      109       118       1641      3833      9122\n",
       "structure.1                                                  \n",
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       "1641         0.253045       NaN  0.000000       NaN       NaN\n",
       "3833         0.277368       NaN       NaN  0.000000       NaN\n",
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     "execution_count": 20,
     "metadata": {},
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    "fingerprint_distance_generator.structure_distance_matrix(coverage_min=0.99)"
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