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d7e1ce7cf4
* Use distances on all valid paths rather than just shortest distance. * Optimise BondPaths. * Optimise BondPaths. * Hash coded for the bond paths. * Faster find all paths. * Build in gcc working. * Comment. * Remove debugging code. * Update GettingStartedInPython.rst. * Now need to split the clique and keep the largest fragment. Lots of warnings about how slow this is. Split out long tests. * Back out a lot of changes. Remove the distance check with singleLargestFrag when building modular product. * Tidy code. Update docstrings. Add explanation to GettingStartedInPython.rst. * Fix single fragment test. * Response to review. --------- Co-authored-by: David Cosgrove <david@cozchemix.co.uk>
224 lines
9.1 KiB
Python
224 lines
9.1 KiB
Python
# Copyright (c) 2023 David Cosgrove and other RDKit contributors
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are
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# met:
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#
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above
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# copyright notice, this list of conditions and the following
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# disclaimer in the documentation and/or other materials provided
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# with the distribution.
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# * Neither the name of Novartis Institutes for BioMedical Research Inc.
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# nor the names of its contributors may be used to endorse or promote
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# products derived from this software without specific prior written
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# permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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# These tests are just to check that the Python wrappers are working
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# ok. The bulk of the tests are in the C++ code.
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import os
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import unittest
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from pathlib import Path
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from rdkit import Chem
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from rdkit.Chem import rdRascalMCES
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class TestCase(unittest.TestCase):
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def setUp(self):
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pass
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def test1(self):
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mol1 = Chem.MolFromSmiles("c1ccccc1Cl")
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mol2 = Chem.MolFromSmiles("c1ccccc1F")
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opts = rdRascalMCES.RascalOptions()
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(len(results), 1)
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self.assertEqual(results[0].smartsString, 'c1:c:c:c:c:c:1')
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self.assertEqual(len(results[0].bondMatches()), 6)
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self.assertEqual(len(results[0].atomMatches()), 6)
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def test2(self):
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# Test single largest fragment extraction from results
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ad1 = Chem.MolFromSmiles("CN(C)c1ccc(CC(=O)NCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL153934")
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ad2 = Chem.MolFromSmiles("N(C)c1ccc(CC(=O)NCCCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL157336")
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opts = rdRascalMCES.RascalOptions()
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results = rdRascalMCES.FindMCES(ad1, ad2, opts)
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self.assertEqual(len(results), 1)
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self.assertEqual(results[0].smartsString,
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'N(-C)-c1:c:c:c(-CC(=O)-NCCCCCCCCCC):c:c:1.NC12CC3CC(-C1)-CC(-C2)-C3')
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results[0].largestFragmentOnly()
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self.assertEqual(results[0].smartsString, 'N(-C)-c1:c:c:c(-CC(=O)-NCCCCCCCCCC):c:c:1')
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def test3(self):
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# Test not specifying options
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mol1 = Chem.MolFromSmiles("c1ccccc1Cl")
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mol2 = Chem.MolFromSmiles("c1ccccc1F")
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results = rdRascalMCES.FindMCES(mol1, mol2)
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self.assertEqual(len(results), 1)
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self.assertEqual(results[0].smartsString, 'c1:c:c:c:c:c:1')
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self.assertEqual(len(results[0].bondMatches()), 6)
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self.assertEqual(len(results[0].atomMatches()), 6)
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def test4(self):
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# Test setting non-default option
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mol1 = Chem.MolFromSmiles('Oc1cccc2C(=O)C=CC(=O)c12')
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mol2 = Chem.MolFromSmiles('O1C(=O)C=Cc2cc(OC)c(O)cc12')
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results = rdRascalMCES.FindMCES(mol1, mol2)
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self.assertEqual(len(results), 0)
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.5
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(len(results), 1)
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def test5(self):
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# Test setting non-default option singleLargestFrag
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ad1 = Chem.MolFromSmiles("CN(C)c1ccc(CC(=O)NCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL153934")
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ad2 = Chem.MolFromSmiles("N(C)c1ccc(CC(=O)NCCCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL157336")
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opts = rdRascalMCES.RascalOptions()
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opts.singleLargestFrag = True
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results = rdRascalMCES.FindMCES(ad1, ad2, opts)
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self.assertEqual(len(results), 1)
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self.assertEqual(results[0].smartsString, 'CNc1:c:c:c(-CC(=O)-NCCCCCCCCCC):c:c:1')
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def test6(self):
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# Test the threshold and examine the tier1 and tier2 similarities.
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ad1 = Chem.MolFromSmiles("CN(C)c1ccc(CC(=O)NCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL153934")
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ad2 = Chem.MolFromSmiles("N(C)c1ccc(CC(=O)NCCCCCCCCCCCCNC23CC4CC(C2)CC(C3)C4)cc1 CHEMBL157336")
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.95
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results = rdRascalMCES.FindMCES(ad1, ad2, opts)
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self.assertEqual(len(results), 0)
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opts.returnEmptyMCES = True
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results = rdRascalMCES.FindMCES(ad1, ad2, opts)
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self.assertEqual(len(results), 1)
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def testRascalCluster(self):
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cdk2_file = Path(os.environ['RDBASE']) / 'Contrib' / 'Fastcluster' / 'cdk2.smi'
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suppl = Chem.SmilesMolSupplier(str(cdk2_file), '\t', 1, 0, False)
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mols = [mol for mol in suppl]
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clusters = rdRascalMCES.RascalCluster(mols)
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self.assertEqual(len(clusters), 8)
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expClusters = [7, 7, 6, 2, 2, 2, 2, 20]
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for clus, expClusSize in zip(clusters, expClusters):
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self.assertEqual(expClusSize, len(clus))
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clusOpts = rdRascalMCES.RascalClusterOptions()
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clusOpts.similarityCutoff = 0.6
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clusters = rdRascalMCES.RascalCluster(mols, clusOpts)
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expClusters = [9, 8, 6, 2, 2, 2, 2, 2, 2, 2, 11]
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for clus, expClusSize in zip(clusters, expClusters):
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self.assertEqual(expClusSize, len(clus))
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def testRascalButinaCluster(self):
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cdk2_file = Path(os.environ['RDBASE']) / 'Contrib' / 'Fastcluster' / 'cdk2.smi'
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suppl = Chem.SmilesMolSupplier(str(cdk2_file), '\t', 1, 0, False)
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mols = [mol for mol in suppl]
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clusters = rdRascalMCES.RascalButinaCluster(mols)
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self.assertEqual(len(clusters), 29)
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expClusters = [
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6, 6, 6, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
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]
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for clus, expClusSize in zip(clusters, expClusters):
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self.assertEqual(expClusSize, len(clus))
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def testMaxBondMatchPairs(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.0
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opts.returnEmptyMCES = True
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opts.allBestMCESs = False
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opts.completeAromaticRings = False
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opts.timeout = -1
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too_long_1 = Chem.MolFromSmiles('CCCC=CCCCC=CCCCCCCCCCCCCCCCCCCCCC1CNCCC1')
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too_long_2 = Chem.MolFromSmiles('CCCC=CCCCCC=CCCCCCCCCCCCCCCCCCCCC1CNCCC1')
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results = rdRascalMCES.FindMCES(too_long_1, too_long_2, opts)
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self.assertEqual(len(results[0].bondMatches()), 0)
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opts.maxBondMatchPairs = 1200
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results = rdRascalMCES.FindMCES(too_long_1, too_long_2, opts)
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self.assertEqual(len(results[0].bondMatches()), 34)
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def testExactConnectionsMatch(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.5
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opts.allBestMCESs = True
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mol1 = Chem.MolFromSmiles('c1ccccc1C1CCC(C(C)C)C1')
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mol2 = Chem.MolFromSmiles('c1ccccc1C(C)C')
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(results[0].numFragments, 1)
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self.assertEqual(results[0].smartsString, 'c1:c:c:c:c:c:1-C(-C)-C')
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opts.exactConnectionsMatch = True
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(results[0].numFragments, 2)
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self.assertEqual(results[0].smartsString,
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'[#6&a&D2]1:[#6&a&D2]:[#6&a&D2]:[#6&a&D2]:[#6&a&D2]:[#6&a&D3]:1.[#6&A&D3](-[#6&A&D1])-[#6&A&D1]')
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def testEquivalentAtoms(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.5
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opts.equivalentAtoms = "[F,Cl,Br,I]"
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mol1 = Chem.MolFromSmiles('c1ccccc1F')
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mol2 = Chem.MolFromSmiles('c1ccccc1Br')
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(results[0].numFragments, 1)
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self.assertEqual(results[0].smartsString, 'c1:c:c:c:c:c:1-[F,Cl,Br,I]')
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def testEquivalentBonds(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.5
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opts.ignoreBondOrders = True
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mol1 = Chem.MolFromSmiles('CC=CC')
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mol2 = Chem.MolFromSmiles('CCCC')
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(results[0].numFragments, 1)
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self.assertEqual(results[0].smartsString, 'C~C~C~C')
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def testExactAtomTypeMatch(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.1
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opts.ignoreAtomAromaticity = False
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mol1 = Chem.MolFromSmiles('c1ccccc1NCC')
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mol2 = Chem.MolFromSmiles('C1CCCCC1NCC')
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertEqual(results[0].numFragments, 1)
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self.assertEqual(results[0].smartsString, 'NCC')
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def testMinCliqueSize(self):
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opts = rdRascalMCES.RascalOptions()
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opts.similarityThreshold = 0.1
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opts.minCliqueSize = 17
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mol1 = Chem.MolFromSmiles('CC12CCC3C(C1CCC2O)CCC4=CC(=O)CCC34C')
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mol2 = Chem.MolFromSmiles('CC12CCC3C(C1CCC2O)CCC4=C3C=CC(=C4)O')
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results = rdRascalMCES.FindMCES(mol1, mol2, opts)
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self.assertFalse(results)
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if __name__ == "__main__":
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unittest.main()
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