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molecule_sampling_demo.ipynb 
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{
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  "nbformat": 4,
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  "nbformat_minor": 0,
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  "metadata": {
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    "colab": {
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      "name": "Molecule sampling demo",
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      "provenance": [],
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      "collapsed_sections": [],
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      "include_colab_link": true
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    },
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    "kernelspec": {
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      "name": "python3",
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      "display_name": "Python 3"
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    },
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    "language_info": {
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      "name": "python"
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    }
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  },
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  "cells": [
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    {
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "view-in-github",
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        "colab_type": "text"
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      },
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      "source": [
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        "<a href=\"https://colab.research.google.com/github/google-research/google-research/blob/master/graph_sampler/molecule_sampling_demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      ]
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    },
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    {
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      "metadata": {
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        "id": "DhWmZgAVwDGu",
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        "colab_type": "text"
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      },
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      "cell_type": "markdown",
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      "source": [
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        "Copyright 2022 Google LLC\n",
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        "\n",
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        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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        "you may not use this file except in compliance with the License.\n",
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        "You may obtain a copy of the License at\n",
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        "\n",
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        "https://www.apache.org/licenses/LICENSE-2.0\n",
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        "\n",
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        "Unless required by applicable law or agreed to in writing, software\n",
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        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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        "See the License for the specific language governing permissions and\n",
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        "limitations under the License."
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": null,
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      "metadata": {
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        "id": "NtzgAVZFf189"
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      },
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      "outputs": [],
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      "source": [
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        "# Install graph_sampler\n",
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        "!git clone https://github.com/google-research/google-research.git\n",
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        "!pip install google-research/graph_sampler"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "source": [
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        "from rdkit import Chem\n",
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        "import rdkit.Chem.Draw\n",
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        "from graph_sampler import molecule_sampler\n",
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        "from graph_sampler import stoichiometry\n",
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        "import numpy as np"
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      ],
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      "metadata": {
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        "id": "_TgiDMUlgNH3"
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      },
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      "execution_count": null,
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      "outputs": []
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    },
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    {
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      "cell_type": "markdown",
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      "source": [
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        "# Generating samples from a single stoichiometry"
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      ],
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      "metadata": {
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        "id": "MmZ9-Rm2gRfx"
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      }
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    },
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    {
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      "cell_type": "code",
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      "source": [
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        "stoich = stoichiometry.Stoichiometry({'C': 10, 'O': 2, 'N': 3, 'H': 16, 'F': 2, 'O-': 1, 'N+': 1})\n",
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        "assert stoichiometry.is_valid(stoich), 'Cannot form a connected graph with this stoichiometry.'\n",
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        "print('Number of heavy atoms:', sum(stoich.counts.values()) - stoich.counts['H'])"
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      ],
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/"
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        },
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        "id": "52YK9MpUgXK1",
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        "outputId": "3305185d-5efb-473a-a721-cd66f2338492"
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      },
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      "execution_count": null,
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      "outputs": [
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        {
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          "output_type": "stream",
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          "name": "stdout",
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          "text": [
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            "Number of heavy atoms: 19\n"
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          ]
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        }
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      ]
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    },
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    {
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      "cell_type": "code",
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      "source": [
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        "%%time\n",
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        "sampler = molecule_sampler.MoleculeSampler(stoich,\n",
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        "                                           relative_precision=0.03,\n",
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        "                                           rng_seed=2044365744)\n",
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        "weighted_samples = [graph for graph in sampler]\n",
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        "stats = sampler.stats()\n",
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        "rejector = molecule_sampler.RejectToUniform(weighted_samples,\n",
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        "                                            max_importance=stats['max_final_importance'],\n",
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        "                                            rng_seed=265580748)\n",
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        "uniform_samples = [graph for graph in rejector]\n",
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        "print(f'generated {len(weighted_samples)}, kept {len(uniform_samples)}, '\n",
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        "      f'estimated total: {stats[\"estimated_num_graphs\"]:.2E} ± '\n",
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        "      f'{stats[\"num_graphs_std_err\"]:.2E}')"
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      ],
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/"
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        },
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        "id": "tfIGyjY0gaSb",
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        "outputId": "bb38e50c-b09d-49b4-aa32-7c37d2cc4bf2"
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      },
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      "execution_count": null,
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      "outputs": [
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        {
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          "output_type": "stream",
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          "name": "stdout",
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          "text": [
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            "generated 3646, kept 115, estimated total: 7.06E+15 ± 2.11E+14\n",
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            "CPU times: user 17.4 s, sys: 1.44 s, total: 18.9 s\n",
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            "Wall time: 18.1 s\n"
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          ]
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        }
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      ]
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    },
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    {
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      "cell_type": "code",
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      "source": [
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        "#@title Draw some examples\n",
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        "mols = [molecule_sampler.to_mol(g) for g in uniform_samples]\n",
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        "Chem.Draw.MolsToGridImage(mols[:8], molsPerRow=4, subImgSize=(200, 140))"
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      ],
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/",
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          "height": 297
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        },
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        "id": "xO7SDND0g8jc",
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        "outputId": "acb74304-f154-4381-c3bd-89796923415e"
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      },
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      "execution_count": null,
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      "outputs": [
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        {
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          "output_type": "execute_result",
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          "data": {
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            "image/png": 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\n",
172
            "text/plain": [
173
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x280 at 0x7F0B2D4E8B10>"
174
            ]
175
          },
176
          "metadata": {},
177
          "execution_count": 5
178
        }
179
      ]
180
    },
181
    {
182
      "cell_type": "markdown",
183
      "source": [
184
        "# Combining samples from multiple stoichiometries\n",
185
        "Here we'll generate random molecules with 5 heavy atoms selected from C, N, and O. These small numbers are chosen just to illustrate the code. In this small an example, you could just enumerate all molecules. For large numbers of heavy atoms selected from a large set, you'd want to parallelize a lot of this."
186
      ],
187
      "metadata": {
188
        "id": "j2GpWm59hAgk"
189
      }
190
    },
191
    {
192
      "cell_type": "code",
193
      "source": [
194
        "#@title Enumerate valid stoichiometries subject to the given constraint\n",
195
        "heavy_elements = ['C', 'N', 'O']\n",
196
        "num_heavy = 5\n",
197
        "\n",
198
        "# We'll dump stoichiometries, samples, and statistics into a big dictionary.\n",
199
        "all_data = {}\n",
200
        "for stoich in stoichiometry.enumerate_stoichiometries(num_heavy, heavy_elements):\n",
201
        "  key = ''.join(stoich.to_element_list())\n",
202
        "  all_data[key] = {'stoich': stoich} \n",
203
        "\n",
204
        "max_key_size = max(len(k) for k in all_data.keys())\n",
205
        "print(f'{len(all_data)} stoichiometries')"
206
      ],
207
      "metadata": {
208
        "colab": {
209
          "base_uri": "https://localhost:8080/"
210
        },
211
        "id": "25GrPsRRhE_4",
212
        "outputId": "4ec1a8cf-d1c9-4cd1-b4e5-73ddb4a8220b"
213
      },
214
      "execution_count": null,
215
      "outputs": [
216
        {
217
          "output_type": "stream",
218
          "name": "stdout",
219
          "text": [
220
            "90 stoichiometries\n"
221
          ]
222
        }
223
      ]
224
    },
225
    {
226
      "cell_type": "code",
227
      "source": [
228
        "#@title For each stoichiometry, generate samples and estimate the number of molecules\n",
229
        "for key, data in all_data.items():\n",
230
        "  sampler = molecule_sampler.MoleculeSampler(data['stoich'], relative_precision=0.2)\n",
231
        "  data['weighted_samples'] = [graph for graph in sampler]\n",
232
        "  stats = sampler.stats()\n",
233
        "  data['stats'] = stats\n",
234
        "  rejector = molecule_sampler.RejectToUniform(data['weighted_samples'],\n",
235
        "                                              max_importance=stats['max_final_importance'])\n",
236
        "  data['uniform_samples'] = [graph for graph in rejector]\n",
237
        "  print(f'{key:>{max_key_size}}:\\tgenerated {len(data[\"weighted_samples\"])},\\t'\n",
238
        "        f'kept {len(data[\"uniform_samples\"])},\\t'\n",
239
        "        f'estimated total {int(stats[\"estimated_num_graphs\"])} ± {int(stats[\"num_graphs_std_err\"])}')"
240
      ],
241
      "metadata": {
242
        "colab": {
243
          "base_uri": "https://localhost:8080/"
244
        },
245
        "id": "x-Gjd5W8wKkz",
246
        "outputId": "6ca83d9f-105d-444d-d28a-1b848e74910b"
247
      },
248
      "execution_count": null,
249
      "outputs": [
250
        {
251
          "output_type": "stream",
252
          "name": "stdout",
253
          "text": [
254
            "          OOOOOHH:\tgenerated 500,\tkept 500,\testimated total 1 ± 0\n",
255
            "            OOOOO:\tgenerated 366,\tkept 366,\testimated total 1 ± 0\n",
256
            "         NOOOOHHH:\tgenerated 500,\tkept 336,\testimated total 3 ± 0\n",
257
            "           NOOOOH:\tgenerated 438,\tkept 378,\testimated total 4 ± 0\n",
258
            "        NNOOOHHHH:\tgenerated 500,\tkept 94,\testimated total 8 ± 0\n",
259
            "          NNOOOHH:\tgenerated 460,\tkept 197,\testimated total 15 ± 0\n",
260
            "            NNOOO:\tgenerated 455,\tkept 121,\testimated total 4 ± 0\n",
261
            "       NNNOOHHHHH:\tgenerated 500,\tkept 126,\testimated total 10 ± 0\n",
262
            "         NNNOOHHH:\tgenerated 472,\tkept 205,\testimated total 23 ± 0\n",
263
            "           NNNOOH:\tgenerated 469,\tkept 138,\testimated total 14 ± 0\n",
264
            "      NNNNOHHHHHH:\tgenerated 500,\tkept 93,\testimated total 6 ± 0\n",
265
            "        NNNNOHHHH:\tgenerated 468,\tkept 91,\testimated total 18 ± 0\n",
266
            "          NNNNOHH:\tgenerated 477,\tkept 182,\testimated total 17 ± 0\n",
267
            "            NNNNO:\tgenerated 489,\tkept 363,\testimated total 4 ± 0\n",
268
            "     NNNNNHHHHHHH:\tgenerated 500,\tkept 245,\testimated total 2 ± 0\n",
269
            "       NNNNNHHHHH:\tgenerated 461,\tkept 187,\testimated total 6 ± 0\n",
270
            "         NNNNNHHH:\tgenerated 474,\tkept 127,\testimated total 8 ± 0\n",
271
            "           NNNNNH:\tgenerated 491,\tkept 334,\testimated total 4 ± 0\n",
272
            "        COOOOHHHH:\tgenerated 500,\tkept 65,\testimated total 5 ± 0\n",
273
            "          COOOOHH:\tgenerated 463,\tkept 185,\testimated total 5 ± 0\n",
274
            "            COOOO:\tgenerated 455,\tkept 216,\testimated total 2 ± 0\n",
275
            "       CNOOOHHHHH:\tgenerated 500,\tkept 105,\testimated total 16 ± 0\n",
276
            "         CNOOOHHH:\tgenerated 475,\tkept 67,\testimated total 31 ± 1\n",
277
            "           CNOOOH:\tgenerated 470,\tkept 148,\testimated total 18 ± 0\n",
278
            "      CNNOOHHHHHH:\tgenerated 500,\tkept 109,\testimated total 26 ± 0\n",
279
            "        CNNOOHHHH:\tgenerated 479,\tkept 86,\testimated total 70 ± 2\n",
280
            "          CNNOOHH:\tgenerated 478,\tkept 52,\testimated total 63 ± 2\n",
281
            "            CNNOO:\tgenerated 494,\tkept 153,\testimated total 11 ± 0\n",
282
            "     CNNNOHHHHHHH:\tgenerated 500,\tkept 63,\testimated total 21 ± 0\n",
283
            "       CNNNOHHHHH:\tgenerated 470,\tkept 108,\testimated total 68 ± 2\n",
284
            "         CNNNOHHH:\tgenerated 476,\tkept 57,\testimated total 87 ± 3\n",
285
            "           CNNNOH:\tgenerated 487,\tkept 130,\testimated total 33 ± 0\n",
286
            "    CNNNNHHHHHHHH:\tgenerated 500,\tkept 23,\testimated total 7 ± 0\n",
287
            "      CNNNNHHHHHH:\tgenerated 473,\tkept 113,\testimated total 29 ± 0\n",
288
            "        CNNNNHHHH:\tgenerated 475,\tkept 82,\testimated total 48 ± 1\n",
289
            "          CNNNNHH:\tgenerated 487,\tkept 132,\testimated total 30 ± 1\n",
290
            "            CNNNN:\tgenerated 490,\tkept 123,\testimated total 5 ± 0\n",
291
            "      CCOOOHHHHHH:\tgenerated 500,\tkept 34,\testimated total 10 ± 0\n",
292
            "        CCOOOHHHH:\tgenerated 483,\tkept 75,\testimated total 20 ± 0\n",
293
            "          CCOOOHH:\tgenerated 483,\tkept 89,\testimated total 19 ± 0\n",
294
            "            CCOOO:\tgenerated 470,\tkept 191,\testimated total 5 ± 0\n",
295
            "     CCNOOHHHHHHH:\tgenerated 500,\tkept 47,\testimated total 30 ± 1\n",
296
            "       CCNOOHHHHH:\tgenerated 474,\tkept 57,\testimated total 84 ± 3\n",
297
            "         CCNOOHHH:\tgenerated 490,\tkept 52,\testimated total 104 ± 4\n",
298
            "           CCNOOH:\tgenerated 490,\tkept 134,\testimated total 40 ± 1\n",
299
            "    CCNNOHHHHHHHH:\tgenerated 500,\tkept 41,\testimated total 29 ± 1\n",
300
            "      CCNNOHHHHHH:\tgenerated 479,\tkept 126,\testimated total 111 ± 4\n",
301
            "        CCNNOHHHH:\tgenerated 472,\tkept 54,\testimated total 175 ± 7\n",
302
            "          CCNNOHH:\tgenerated 488,\tkept 121,\testimated total 117 ± 3\n",
303
            "            CCNNO:\tgenerated 498,\tkept 34,\testimated total 19 ± 0\n",
304
            "   CCNNNHHHHHHHHH:\tgenerated 500,\tkept 68,\testimated total 13 ± 0\n",
305
            "     CCNNNHHHHHHH:\tgenerated 470,\tkept 45,\testimated total 54 ± 2\n",
306
            "       CCNNNHHHHH:\tgenerated 475,\tkept 68,\testimated total 109 ± 4\n",
307
            "         CCNNNHHH:\tgenerated 484,\tkept 155,\testimated total 96 ± 2\n",
308
            "           CCNNNH:\tgenerated 497,\tkept 37,\testimated total 34 ± 1\n",
309
            "    CCCOOHHHHHHHH:\tgenerated 500,\tkept 65,\testimated total 11 ± 0\n",
310
            "      CCCOOHHHHHH:\tgenerated 480,\tkept 29,\testimated total 36 ± 2\n",
311
            "        CCCOOHHHH:\tgenerated 491,\tkept 72,\testimated total 53 ± 2\n",
312
            "          CCCOOHH:\tgenerated 490,\tkept 109,\testimated total 34 ± 1\n",
313
            "            CCCOO:\tgenerated 494,\tkept 190,\testimated total 7 ± 0\n",
314
            "   CCCNOHHHHHHHHH:\tgenerated 500,\tkept 40,\testimated total 21 ± 0\n",
315
            "     CCCNOHHHHHHH:\tgenerated 486,\tkept 77,\testimated total 82 ± 3\n",
316
            "       CCCNOHHHHH:\tgenerated 490,\tkept 77,\testimated total 162 ± 6\n",
317
            "         CCCNOHHH:\tgenerated 496,\tkept 104,\testimated total 132 ± 4\n",
318
            "           CCCNOH:\tgenerated 493,\tkept 67,\testimated total 43 ± 1\n",
319
            "  CCCNNHHHHHHHHHH:\tgenerated 500,\tkept 46,\testimated total 13 ± 0\n",
320
            "    CCCNNHHHHHHHH:\tgenerated 481,\tkept 43,\testimated total 60 ± 2\n",
321
            "      CCCNNHHHHHH:\tgenerated 488,\tkept 31,\testimated total 131 ± 7\n",
322
            "        CCCNNHHHH:\tgenerated 493,\tkept 74,\testimated total 164 ± 6\n",
323
            "          CCCNNHH:\tgenerated 499,\tkept 72,\testimated total 82 ± 3\n",
324
            "            CCCNN:\tgenerated 499,\tkept 70,\testimated total 13 ± 0\n",
325
            "  CCCCOHHHHHHHHHH:\tgenerated 500,\tkept 29,\testimated total 6 ± 0\n",
326
            "    CCCCOHHHHHHHH:\tgenerated 485,\tkept 94,\testimated total 25 ± 1\n",
327
            "      CCCCOHHHHHH:\tgenerated 485,\tkept 51,\testimated total 53 ± 2\n",
328
            "        CCCCOHHHH:\tgenerated 489,\tkept 82,\testimated total 62 ± 2\n",
329
            "          CCCCOHH:\tgenerated 494,\tkept 37,\testimated total 36 ± 1\n",
330
            "            CCCCO:\tgenerated 497,\tkept 133,\testimated total 7 ± 0\n",
331
            " CCCCNHHHHHHHHHHH:\tgenerated 500,\tkept 50,\testimated total 8 ± 0\n",
332
            "   CCCCNHHHHHHHHH:\tgenerated 475,\tkept 33,\testimated total 33 ± 1\n",
333
            "     CCCCNHHHHHHH:\tgenerated 480,\tkept 40,\testimated total 87 ± 4\n",
334
            "       CCCCNHHHHH:\tgenerated 490,\tkept 78,\testimated total 111 ± 4\n",
335
            "         CCCCNHHH:\tgenerated 498,\tkept 53,\testimated total 82 ± 3\n",
336
            "           CCCCNH:\tgenerated 497,\tkept 55,\testimated total 26 ± 1\n",
337
            "CCCCCHHHHHHHHHHHH:\tgenerated 500,\tkept 10,\testimated total 4 ± 0\n",
338
            "  CCCCCHHHHHHHHHH:\tgenerated 475,\tkept 99,\testimated total 10 ± 0\n",
339
            "    CCCCCHHHHHHHH:\tgenerated 483,\tkept 91,\testimated total 27 ± 1\n",
340
            "      CCCCCHHHHHH:\tgenerated 487,\tkept 22,\testimated total 42 ± 2\n",
341
            "        CCCCCHHHH:\tgenerated 496,\tkept 50,\testimated total 40 ± 2\n",
342
            "          CCCCCHH:\tgenerated 497,\tkept 73,\testimated total 21 ± 0\n",
343
            "            CCCCC:\tgenerated 498,\tkept 74,\testimated total 5 ± 0\n"
344
          ]
345
        }
346
      ]
347
    },
348
    {
349
      "cell_type": "code",
350
      "source": [
351
        "#@title Combine into one big uniform sampling of the whole space\n",
352
        "bucket_sizes = [data['stats']['estimated_num_graphs'] for data in all_data.values()]\n",
353
        "sample_sizes = [len(data['uniform_samples']) for data in all_data.values()]\n",
354
        "base_iters = [data['uniform_samples'] for data in all_data.values()]\n",
355
        "\n",
356
        "aggregator = molecule_sampler.AggregateUniformSamples(bucket_sizes, sample_sizes, base_iters)\n",
357
        "merged_uniform_samples = [graph for graph in aggregator]\n",
358
        "\n",
359
        "total_estimate = sum(data['stats']['estimated_num_graphs'] for data in all_data.values())\n",
360
        "total_variance = sum(data['stats']['num_graphs_std_err']**2 for data in all_data.values())\n",
361
        "total_std = np.sqrt(total_variance)\n",
362
        "\n",
363
        "print(f'{len(merged_uniform_samples)} samples after merging, of an estimated '\n",
364
        "      f'{total_estimate:.1f} ± {total_std:.1f}')"
365
      ],
366
      "metadata": {
367
        "colab": {
368
          "base_uri": "https://localhost:8080/"
369
        },
370
        "id": "TfgR7VZqwgia",
371
        "outputId": "abf4939f-cf9c-4d60-b0d5-c82c76089f42"
372
      },
373
      "execution_count": null,
374
      "outputs": [
375
        {
376
          "output_type": "stream",
377
          "name": "stdout",
378
          "text": [
379
            "842 samples after merging, of an estimated 3563.4 ± 22.0\n"
380
          ]
381
        }
382
      ]
383
    },
384
    {
385
      "cell_type": "code",
386
      "source": [
387
        "#@title Draw some examples\n",
388
        "mols = [molecule_sampler.to_mol(g) for g in merged_uniform_samples]\n",
389
        "Chem.Draw.MolsToGridImage(np.random.choice(mols, size=16), molsPerRow=4, subImgSize=(200, 140))"
390
      ],
391
      "metadata": {
392
        "colab": {
393
          "base_uri": "https://localhost:8080/",
394
          "height": 577
395
        },
396
        "id": "KiHlfH8VwnOW",
397
        "outputId": "2a24825f-de0a-46b7-dbd4-486895b80283"
398
      },
399
      "execution_count": null,
400
      "outputs": [
401
        {
402
          "output_type": "execute_result",
403
          "data": {
404
            "image/png": 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\n",
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            "text/plain": [
406
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x560 at 0x7F0B2812DF10>"
407
            ]
408
          },
409
          "metadata": {},
410
          "execution_count": 9
411
        }
412
      ]
413
    }
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  ]
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}
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