{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting rows and columns of molecules with MolsMatrixToGridImage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This guest post by Jeremy Monat (GitHub: [@bertiewooster](https://github.com/bertiewooster/)), who contributed `MolsMatrixToGridImage` to the RDKit, is the third of a few posts covering some of the new or improved features in the 2023.09.1 RDKit release."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[`MolsMatrixToGridImage`](https://www.rdkit.org/docs/source/rdkit.Chem.Draw.html#rdkit.Chem.Draw.MolsMatrixToGridImage), new in RDKit 2023.09.1, is designed to easily plot a rectangular grid of molecules, that is, rows and columns of molecules."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing MolsMatrixToGridImage to MolsToGridImage\n",
    "\n",
    "`MolsMatrixToGridImage` builds on [`MolsToGridImage`](https://www.rdkit.org/docs/source/rdkit.Chem.Draw.html#rdkit.Chem.Draw.MolsToGridImage). In fact, `MolsMatrixToGridImage` internally calls `MolsToGridImage`, so they can output the same images and formats.\n",
    "\n",
    "The difference is that `MolsMatrixToGridImage` creates a rectangular row-and-column format by using nested input data structures. Each data substructure represents a row of molecules. `MolsMatrixToGridImage` automatically pads rows as needed so all rows are the length of the longest row, making it easy to plot molecules in a matrix without having to think about the length of each row.\n",
    "\n",
    "As a minimal example, if we want to plot a single interhalogen molecule at various cells in a grid, for example to represent a spatial arrangement:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "from rdkit.Chem.Draw import IPythonConsole\n",
    "from rdkit.Chem import AllChem as Chem\n",
    "from rdkit.Chem.Draw import MolsToGridImage, rdMolDraw2D, MolsMatrixToGridImage\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "mol = Chem.MolFromSmiles(\"FCl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "both of the following produce the same grid image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsMatrixToGridImage usage\n",
    "molsMatrix = [[mol, mol], [mol, None, mol]]\n",
    "MolsMatrixToGridImage(molsMatrix=molsMatrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsToGridImage usage\n",
    "mols = [mol, mol, None, mol, None, mol]\n",
    "MolsToGridImage(mols=mols, molsPerRow=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "where we had to add the first `None` (null molecule) item for `MolsToGridImage` to produce the empty cell at the end of the first row."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The advantage of `MolsMatrixToGridImage` is that you need not manually pad shorter (narrower) rows, and you can provide molecules in a nested format that explicitly identifies each row.\n",
    "\n",
    "While the nested data structure above for `MolsMatrixToGridImage` is a list of lists, you can use other pairs of iterables: a tuple of tuples, or a list of tuples, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choosing a grid image function\n",
    "\n",
    "Use `MolsToGridImage` if you want to plot a series of molecules in the least amount of space, where the row that each molecule is on is not important.\n",
    "\n",
    "Use `MolsMatrixToGridImage` if you want each row of molecules to represent something meaningful, and especially if the number of molecules per row can vary. The *columns* may or may not have meaning: You could plot an uninterrupted series of molecules in a row in no particular order, or you could assign molecules to columns based on some property—for example, a column may represent a spatial location. Or the columns may be used to space out molecules; for example in the retrosynthetic analysis tree below, the columns allow horizontal space for each subtree to avoid visually-confusing overlapping with adjacent subtrees.\n",
    "\n",
    "A borderline situation is if each row will have the same number of molecules `n` (`n` = 2 below): you can create the same grid using either\n",
    "\n",
    "- `MolsToGridImage(molsPerRow=n)`, for example `MolsToGridImage([mol1a, mol1b, mol2a, mol2b, mol3a, mol3b], molsPerRow=2)`.\n",
    "- `MolsMatrixToGridImage` with `n` molecules in each row, for example `MolsMatrixToGridImage([[mol1a, mol1b], [mol2a, mol2b], [mol3a, mol3b]])`. You may find this format easier to use because each row is in its own sub-list. Also, you need not explicitly declare the number of molecules per row, so if you later change that number `n`, or have a different number of molecules on a given row, the grid will automatically adjust accordingly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both `MolsMatrixToGridImage` and `MolsToGridImage` are Python functions; they are not available in C++."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use cases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are three example use cases. Each comes from an external blog post by the author, which is linked to in the use case's heading, and which explains more about the chemistry background and how the parameters given below are generated. In each case, we show the `MolsMatrixToGridImage` usage and then the same output using `MolsToGridImage`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Synthetic accessibility](https://bertiewooster.github.io/2023/02/07/Are-the-Starting-Materials-for-Synthesizing-Your-Target-Molecules-Commercially-Available.html)\n",
    "\n",
    "Given molecules you want to synthesize, and the reaction to create each, this utility determines the starting materials, checks whether they are commercially available per PubChem, and tells you whether each target is accessible—whether all its starting materials are commercially available.\n",
    "\n",
    "Here, `MolsMatrixToGridImage` is useful because\n",
    "\n",
    "- each row represents a synthetic target\n",
    "- each target might have a different number of starting materials, and thus a different number of cells (columns). The first column represents the target. Subsequent columns represent the reactants, and are in no particular order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsMatrixToGridImage usage\n",
    "synSmilesMatrix = [['OCN1C2CC(C=C2)C1CC1NCCc2ccccc12', 'NCCc1ccccc1', 'O=CCC1C2C=CC(C2)N1CO'], ['c1ccc(NCC2NCCc3ccccc32)cc1', 'NCCc1ccccc1', 'O=CCNc1ccccc1'], ['[O-][N+](=O)C1=CC=C(C2NCCc3ccccc23)C2=C1C=CC=C2', 'Nc1ccc(C2NCCc3ccccc32)c2ccccc12']]\n",
    "synMolsMatrix = [[Chem.MolFromSmiles(smile) for smile in row] for row in synSmilesMatrix]\n",
    "synLegendsMatrix = [['Pictet-Spengler target accessible: No', 'Reactant available: Yes', 'Reactant available: No'], ['Pictet-Spengler target accesible: Yes', 'Reactant available: Yes', 'Reactant available: Yes'], ['Amine oxidation target accessible: No', 'Reactant available: No']]\n",
    "MolsMatrixToGridImage(molsMatrix=synMolsMatrix, legendsMatrix=synLegendsMatrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsToGridImage usage\n",
    "synSmiles = ['OCN1C2CC(C=C2)C1CC1NCCc2ccccc12', 'NCCc1ccccc1', 'O=CCC1C2C=CC(C2)N1CO', 'c1ccc(NCC2NCCc3ccccc32)cc1', 'NCCc1ccccc1', 'O=CCNc1ccccc1', '[O-][N+](=O)C1=CC=C(C2NCCc3ccccc23)C2=C1C=CC=C2', 'Nc1ccc(C2NCCc3ccccc32)c2ccccc12', '']\n",
    "synMols = [Chem.MolFromSmiles(smile) for smile in synSmiles]\n",
    "synLegends = ['Pictet-Spengler target accessible: No', 'Reactant available: Yes', 'Reactant available: No', 'Pictet-Spengler target accesible: Yes', 'Reactant available: Yes', 'Reactant available: Yes', 'Amine oxidation target accessible: No', 'Reactant available: No', '']\n",
    "MolsToGridImage(mols=synMols, legends=synLegends, molsPerRow=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Find the maximum common substructure and groups off it](https://bertiewooster.github.io/2022/12/25/RDKit-Find-Groups-Off-Common-Core.html)\n",
    "\n",
    "In drug discovery, the lead optimization step often involves creating analogues of a hit (a promising compound which produces a desired result in an assay) to optimize selectivity and minimize toxicity. Because it has historically been easier to chemically modify the periphery of the molecule (for example the functional groups) than the scaffold, it is helpful to compare the groups off of the common scaffold. A utility function uses the RDKit to find the maximum common substructure (MCS) between a set of molecules, then show the groups off of that core scaffold.\n",
    "\n",
    "Here, `MolsMatrixToGridImage` is useful because\n",
    "\n",
    "- each row represents a molecule in the set\n",
    "- each of those molecules might have a different number of groups off the core scaffold.\n",
    "The first column represents the molecule. Subsequent columns represent the groups off the core scaffold for that molecule, and are in no particular order.\n",
    "\n",
    "The following example is for a set of two pyridinols."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsMatrixToGridImage usage\n",
    "mcsStringsMatrix = [['[#6]1:[#6](-[#8]):[#6]:[#7]:[#6](:[#6]:1)-[#7]', 'NC1:C:C:C(O):C:N:1'], ['c1c(O)cnc(N)c(NC(=O)(C))1', '[2*]NC(C)=O'], ['c1c(O)cnc(N(CCC))c1(C)', '[0*]CCC', '[2*]C']]\n",
    "mcsMolsMatrix = [[Chem.MolFromSmiles(smile) for smile in row] for row in mcsStringsMatrix]\n",
    "\n",
    "mcsLegends = [['Max. substructure match', 'Core'], ['aldehyde off aromatic carbon', '[2*]NC(C)=O'], ['alkyl off amine', '[0*]CCC', '[2*]C']]\n",
    "mcsHighlightAtomLists = [[(), ()], [(0, 1, 2, 3, 4, 5, 7, 6), ()], [(0, 1, 2, 3, 4, 5, 10, 6), (), ()]]\n",
    "\n",
    "mcsMolForMatrix = Chem.MolFromSmarts(mcsStringsMatrix[0][0])\n",
    "\n",
    "# Align cores--optional, for easier visual comparison of molecules\n",
    "subms = [mcsMolsMatrix[0][1]]\n",
    "for row in mcsMolsMatrix[1:]:\n",
    "    subms += [row[0]]\n",
    "Chem.Compute2DCoords(mcsMolForMatrix)\n",
    "\n",
    "for m in subms:\n",
    "    _ = Chem.GenerateDepictionMatching2DStructure(m, mcsMolForMatrix)\n",
    "\n",
    "MolsMatrixToGridImage(molsMatrix=mcsMolsMatrix, highlightAtomListsMatrix=mcsHighlightAtomLists, legendsMatrix=mcsLegends, useSVG=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:rdkit=\"http://www.rdkit.org/xml\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" version=\"1.1\" baseProfile=\"full\" xml:space=\"preserve\" width=\"600px\" height=\"600px\" viewBox=\"0 0 600 600\">\n",
       "<!-- END OF HEADER -->\n",
       "<rect style=\"opacity:1.0;fill:#FFFFFF;stroke:none\" width=\"600.0\" height=\"600.0\" x=\"0.0\" y=\"0.0\"> </rect>\n",
       "<path class=\"bond-0 atom-0 atom-1\" d=\"M 86.5,116.6 L 72.7,92.7\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-0 atom-0 atom-1\" d=\"M 88.9,112.4 L 77.5,92.7\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-1 atom-1 atom-2\" d=\"M 72.7,92.7 L 61.2,92.7\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-1 atom-1 atom-2\" d=\"M 61.2,92.7 L 49.6,92.7\" style=\"fill:none;fill-rule:evenodd;stroke:#FF0000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-2 atom-1 atom-3\" d=\"M 72.7,92.7 L 86.5,68.8\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-3 atom-3 atom-4\" d=\"M 86.5,68.8 L 98.4,68.8\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-3 atom-3 atom-4\" d=\"M 98.4,68.8 L 110.2,68.8\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-3 atom-3 atom-4\" d=\"M 88.9,72.9 L 99.6,72.9\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-3 atom-3 atom-4\" d=\"M 99.6,72.9 L 110.2,72.9\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-4 atom-4 atom-5\" d=\"M 116.9,73.6 L 122.4,83.1\" style=\"fill:none;fill-rule:evenodd;stroke:#0000FF;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
       "<path class=\"bond-4 atom-4 atom-5\" d=\"M 122.4,83.1 L 127.9,92.7\" style=\"fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2.0px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1\"/>\n",
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       "<path class=\"atom-0\" d=\"M 483.1 489.9 Q 483.3 489.4, 483.7 489.1 Q 484.2 488.9, 484.8 488.9 Q 485.6 488.9, 486.0 489.3 Q 486.5 489.7, 486.5 490.5 Q 486.5 491.2, 485.9 491.9 Q 485.4 492.7, 484.2 493.5 L 486.6 493.5 L 486.6 494.1 L 483.1 494.1 L 483.1 493.6 Q 484.1 492.9, 484.6 492.4 Q 485.2 491.9, 485.5 491.4 Q 485.8 491.0, 485.8 490.5 Q 485.8 490.0, 485.5 489.7 Q 485.3 489.4, 484.8 489.4 Q 484.4 489.4, 484.1 489.6 Q 483.9 489.8, 483.7 490.2 L 483.1 489.9 \" fill=\"#191919\"/>\n",
       "<path class=\"atom-0\" d=\"M 487.8 491.0 L 489.0 489.9 L 487.5 489.5 L 487.7 488.8 L 489.1 489.5 L 488.9 487.9 L 489.7 487.9 L 489.5 489.5 L 490.9 488.8 L 491.2 489.5 L 489.6 489.8 L 490.7 491.0 L 490.0 491.5 L 489.3 490.0 L 488.5 491.5 L 487.8 491.0 \" fill=\"#191919\"/>\n",
       "<path class=\"legend\" d=\"M 483.0 574.5 L 486.4 574.5 L 486.4 575.7 L 484.4 575.7 L 484.4 588.8 L 486.4 588.8 L 486.4 590.0 L 483.0 590.0 L 483.0 574.5 \" fill=\"#000000\"/>\n",
       "<path class=\"legend\" d=\"M 487.4 577.7 Q 487.8 576.7, 488.8 576.1 Q 489.8 575.5, 491.1 575.5 Q 492.8 575.5, 493.8 576.4 Q 494.8 577.3, 494.8 579.0 Q 494.8 580.6, 493.5 582.2 Q 492.3 583.8, 489.7 585.6 L 495.0 585.6 L 495.0 586.9 L 487.3 586.9 L 487.3 585.8 Q 489.4 584.3, 490.7 583.2 Q 491.9 582.1, 492.6 581.1 Q 493.2 580.1, 493.2 579.0 Q 493.2 578.0, 492.6 577.3 Q 492.1 576.7, 491.1 576.7 Q 490.2 576.7, 489.6 577.1 Q 489.0 577.5, 488.6 578.3 L 487.4 577.7 \" fill=\"#000000\"/>\n",
       "<path class=\"legend\" d=\"M 497.0 579.9 L 498.7 578.2 L 496.5 577.7 L 496.8 576.6 L 498.9 577.6 L 498.6 575.4 L 499.8 575.4 L 499.4 577.6 L 501.5 576.7 L 501.8 577.7 L 499.6 578.2 L 501.2 579.9 L 500.2 580.6 L 499.1 578.5 L 498.0 580.6 L 497.0 579.9 \" fill=\"#000000\"/>\n",
       "<path class=\"legend\" d=\"M 506.3 574.5 L 506.3 590.0 L 502.9 590.0 L 502.9 588.8 L 505.0 588.8 L 505.0 575.7 L 502.9 575.7 L 502.9 574.5 L 506.3 574.5 \" fill=\"#000000\"/>\n",
       "<path class=\"legend\" d=\"M 508.2 581.2 Q 508.2 578.4, 509.5 576.9 Q 510.9 575.5, 513.4 575.5 Q 515.7 575.5, 517.0 577.1 L 515.9 578.0 Q 515.0 576.8, 513.4 576.8 Q 511.7 576.8, 510.8 577.9 Q 509.9 579.1, 509.9 581.2 Q 509.9 583.5, 510.8 584.6 Q 511.7 585.8, 513.6 585.8 Q 514.8 585.8, 516.3 585.0 L 516.7 586.2 Q 516.1 586.6, 515.2 586.8 Q 514.3 587.1, 513.3 587.1 Q 510.9 587.1, 509.5 585.6 Q 508.2 584.0, 508.2 581.2 \" fill=\"#000000\"/>\n",
       "</svg>"
      ],
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsToGridImage usage\n",
    "mcsStrings = ['[#6]1:[#6](-[#8]):[#6]:[#7]:[#6](:[#6]:1)-[#7]', 'NC1:C:C:C(O):C:N:1', '', 'c1c(O)cnc(N)c(NC(=O)(C))1', '[2*]NC(C)=O', '', 'c1c(O)cnc(N(CCC))c1(C)', '[0*]CCC', '[2*]C']\n",
    "molsPerRow = 3\n",
    "mcsMols = [Chem.MolFromSmiles(smile) for smile in mcsStrings]\n",
    "mcsLegends = ['Max. substructure match', 'Core', '', 'aldehyde off aromatic carbon', '[2*]NC(C)=O', '', 'alkyl off amine', '[0*]CCC', '[2*]C']\n",
    "mcsHighlightAtomLists = [(), (), (), (0, 1, 2, 3, 4, 5, 7, 6), (), (), (0, 1, 2, 3, 4, 5, 10, 6), (), ()]\n",
    "\n",
    "mcsMol = Chem.MolFromSmarts(mcsStrings[0])\n",
    "\n",
    "# Align cores--optional, just for easier visual comparison of molecules\n",
    "subms = [mcsMols[1]]\n",
    "for mol in mcsMols[molsPerRow::molsPerRow]:\n",
    "    subms += [mol]\n",
    "Chem.Compute2DCoords(mcsMol)\n",
    "for m in subms:\n",
    "    _ = Chem.GenerateDepictionMatching2DStructure(m, mcsMol)\n",
    "\n",
    "MolsToGridImage(mcsMols, highlightAtomLists=mcsHighlightAtomLists, legends=mcsLegends, molsPerRow=molsPerRow, useSVG=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Retrosynthetic analysis](https://bertiewooster.github.io/2022/11/11/RDKit-Recap-decomposition-tree.html)\n",
    "\n",
    "Retrosynthetic analysis involves decomposing a target molecule into a set of fragments that could be combined to make the parent molecule using common reactions. The [Recap algorithm](https://www.semanticscholar.org/paper/RECAP-%E2%80%94-Retrosynthetic-Combinatorial-Analysis-A-New-Lewell-Judd/fbfb10d1f63aa803f6d47df6587aa0e41109f5ee) by X. Lewell et al. accomplishes that. [Recap is implemented in the RDKit](https://www.rdkit.org/docs/GettingStartedInPython.html#recap-implementation). \n",
    "\n",
    "Here, `MolsMatrixToGridImage` is useful because\n",
    "\n",
    "- each row represents a level of fragmentation, with the parent molecule at the top and increasing fragmentation towards the bottom\n",
    "- we want to arrange the fragments hierarchically and allow horizontal space for each subtree to avoid visually-confusing overlapping with adjacent subtrees.\n",
    "The columns have no inherent meaning, except that the parent molecule is in the first column, and fragments (of the parent molecule and its fragments) are arrayed to the right.\n",
    "\n",
    "Here is an example retrosynthetic analysis of [6-(hydroxymethoxy)pyridin-2-yl]oxymethanol."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsMatrixToGridImage usage\n",
    "retrosynSmilesMatrix = [['OCOc1cccc(OCO)n1', '', ''],\n",
    " ['*CO', '*c1cccc(OCO)n1', ''],\n",
    " ['', '*CO', '*c1cccc(*)n1']]\n",
    "retrosynMolsMatrix = [[Chem.MolFromSmiles(smile) for smile in row] for row in retrosynSmilesMatrix]\n",
    "retrosynLegendsMatrix = copy.deepcopy(retrosynSmilesMatrix)\n",
    "retrosynLegendsMatrix[0][0] = \"Parent molecule\"\n",
    "MolsMatrixToGridImage(retrosynMolsMatrix, legendsMatrix=retrosynLegendsMatrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MolsToGridImage usage\n",
    "retrosynSmiles = ['OCOc1cccc(OCO)n1', '', '', '*CO', '*c1cccc(OCO)n1', '', '', '*CO', '*c1cccc(*)n1']\n",
    "retrosynMols = [Chem.MolFromSmiles(smile) for smile in retrosynSmiles]\n",
    "retrosynLegends = ['Parent molecule', '', '', '*CO', '*c1cccc(OCO)n1', '', '', '*CO', '*c1cccc(*)n1']\n",
    "MolsToGridImage(mols=retrosynMols, legends=retrosynLegends, molsPerRow=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MolsMatrixToGridImage parameters\n",
    "\n",
    "The only required parameter to `MolsMatrixToGridImage` is `molsMatrix`.\n",
    "\n",
    "`MolsMatrixToGridImage` nests data structures one additional level beyond the analogous parameter in `MolsToGridImage`. The following table compares those parameters for the two functions, where the example parameters would produce the same output for their respective functions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Key to table lines within a cell:<br>`MolsToGridImage`_<br>`MolsMatrixToGridImage`<br>_ |\n",
    "|---------------------------------------------------------------------------------------------|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "|  | Elements mean                   | Parameter name                                   | Data structure                                                     | Example                                                                                                                                                                                      |\n",
    "|----------------------------------------------------|-------------------------------|--------------------------------------------------|---------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n",
    "| Molecules                                          | RDKit molecule                | mols<br>_molsMatrix_                             | Iterable[mol]<br>_Iterable[<wbr>Iterable[mol]]_                    | [FCl, FCl, None, FCl, None, FCl]<br>_[[FCl, FCl], [FCl, None, FCl]]_                                                                                                                         |\n",
    "| Legends                                            | Legend text                   | legends<br>_legendsMatrix_                       | Iterable[str]<br>_Iterable[<wbr>Iterable[<wbr>str]]_                    | [\"no highlighting\", \"bond highlighted\", \"\", \"F highlighted\", \"\", \"Cl and bond highlighted\"]<br>_[[\"no highlighting\", \"bond highlighted\"], [\"F highlighted\", \"\", \"Cl and bond highlighted\"]]_ |\n",
    "| Highlight atoms                                    | Indices of atoms to highlight | highlightAtomLists<br>_highlightAtomListsMatrix_ | Iterable[Iterable[int]]<br>_Iterable[<wbr>Iterable[<wbr>Iterable[<wbr>Int]]_ | [[], [], None, [0], None, [1]]<br>_[[[], []], [[0], None, [1]]]_                                                                                                                               |\n",
    "| Highlight bonds                                    | Indices of bonds to highlight | highlightBondLists<br>_highlightBondListsMatrix_ | Iterable[Iterable[int]]<br>_Iterable[<wbr>Iterable[<wbr>Iterable[<wbr>Int]]_ | [[], [0], None, [], None, [0]]<br>_[[[], [0]], [[], None, [0]]]_                                                                                                                               |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the optional highlighting parameters (`highlightAtomLists`, `highlightAtomListsMatrix`, `highlightBondLists`, and `highlightBondListsMatrix`), to highlight nothing for a given molecule, you can use either `None` or an empty iterable such as `[]`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you provide the parameter names in the function call, for example `MolsMatrixToGridImage(molsMatrix=molsMatrix, legendsMatrix=legendsMatrix)`, be careful to include the suffix \"Matrix\" in those last three parameter names: if you use the parameter name from `MolsToGridImage`, such as `legends`, it will be passed to `MolsToGridImage` as a keyword argument and you will get an error like:\n",
    "\n",
    "`TypeError: rdkit.Chem.Draw.IPythonConsole.ShowMols() got multiple values for keyword argument 'legends'`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unlike `MolsToGridImage`, `MolsMatrixToGridImage` does not take a `molsPerRow` parameter because `MolsMatrixToGridImage` automatically sets the number of molecules per row to the length of the longest row in `molsMatrix`. Other than that, and the per-molecule parameters having a more nested structure, `MolsMatrixToGridImage` can accept all the same parameters as `MolsToGridImage`: `useSVG`, `returnPNG`, and `**kwargs` such as `drawOptions`. Indeed, `MolsMatrixToGridImage` passes those three parameters to `MolsToGridImage`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Requirements for agreement of dimensions of per-molecule parameters\n",
    "\n",
    "`molsMatrix` sets the dimensions, and any other supplied Matrix (per-molecule) parameters must match those dimensions. In the example in the table above, `molsMatrix` has two rows (sub-lists), so `legendsMatrix`, `highlightAtomListsMatrix`, and `highlightBondListsMatrix` (if supplied) must also have two rows. Also, because the first row (sub-list) of `molsMatrix` has two columns (elements), that must true for those three other parameters. And because the second row (sub-list) of `molsMatrix` has three columns (elements), that must true for those three other parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inserting blank cells\n",
    "\n",
    "For blank cells at the end of a row, `MolsMatrixToGridImage` will automatically create them so that all rows have the same number of cells.\n",
    "\n",
    "For blank cells in the middle of a row (when there is a molecule after the blank cell), you need to have a blank entry in the iterable. For molecules, this blank entry can either be `None` or a molecule with no atoms, for example using `Chem.MolFromSmiles(\"\")`. For legends, a blank cell can be `\"\"` (an empty string) but not `None`, which will give a type error. If you create molecules using `Chem.MolFromSmiles(\"\")`, or use those SMILES strings to create legends, entering an empty string will prevent type errors in both situations. For example, this works:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smilesMatrixEmptyString = [[\"FCl\", \"FCl\"], [\"FCl\", \"\", \"FCl\"]]\n",
    "molsMatrixEmptyString = [[Chem.MolFromSmiles(smiles) for smiles in row] for row in smilesMatrixEmptyString]\n",
    "MolsMatrixToGridImage(molsMatrix=molsMatrixEmptyString, legendsMatrix=smilesMatrixEmptyString)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Whereas this gives a type error because `Chem.MolFromSmiles()` needs a string as input:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No registered converter was able to produce a C++ rvalue of type std::__1::basic_string<wchar_t, std::__1::char_traits<wchar_t>, std::__1::allocator<wchar_t>> from this Python object of type NoneType\n"
     ]
    }
   ],
   "source": [
    "smilesMatrixNone = [[\"FCl\", \"FCl\"], [\"FCl\", None, \"FCl\"]]\n",
    "try:\n",
    "    molsMatrixNone = [[Chem.MolFromSmiles(smiles) for smiles in row] for row in smilesMatrixNone]\n",
    "except TypeError as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "as does this because of the `None` element in `legendsMatrix`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No registered converter was able to produce a C++ rvalue of type std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> from this Python object of type NoneType\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    MolsMatrixToGridImage(molsMatrix=molsMatrixEmptyString, legendsMatrix=smilesMatrixNone)\n",
    "except TypeError as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example with all parameters\n",
    "\n",
    "Here is an example of supplying all parameters to `MolsMatrixToGridImage`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "legendsMatrix = [[\"no highlighting\", \"bond highlighted\"], [\"F highlighted\", \"\", \"Cl and bond highlighted\"]]\n",
    "highlightAtomListsMatrix = [[[],[]], [[0], None, [1]]]\n",
    "highlightBondListsMatrix = [[[],[0]], [[], None, [0]]]\n",
    "\n",
    "# Add atom indices to drawing\n",
    "dopts = rdMolDraw2D.MolDrawOptions()\n",
    "dopts.addAtomIndices = True\n",
    "\n",
    "MolsMatrixToGridImage(molsMatrix=molsMatrix, subImgSize=(200, 150), legendsMatrix=legendsMatrix, highlightAtomListsMatrix=highlightAtomListsMatrix, highlightBondListsMatrix=highlightBondListsMatrix, useSVG=False, returnPNG=False, drawOptions=dopts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the same image created using `MolsToGridImage`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=600x300>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "legends = [\"no highlighting\", \"bond highlighted\", \"\", \"F highlighted\", \"\", \"Cl and bond highlighted\"]\n",
    "highlightAtomLists = [[],[], None, [0], None, [1]]\n",
    "highlightBondLists = [None,[0], [], [], None, [0]]\n",
    "\n",
    "MolsToGridImage(mols, molsPerRow=3, subImgSize=(200, 150), legends=legends, highlightAtomLists=highlightAtomLists, highlightBondLists=highlightBondLists, useSVG=False, returnPNG=False, drawOptions=dopts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Share your examples\n",
    "\n",
    "If you use `MolsMatrixToGridImage` in a public project, please post a link in the comments below."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "my-rdkit-env",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
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