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49 lines
1.1 KiB
Python
Executable File
49 lines
1.1 KiB
Python
Executable File
# $Id$
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#
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# Copyright (C) 2001-2006 greg landrum and rational discovery llc
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#
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# @@ All Rights Reserved @@
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#
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""" Python functions for manipulating molecular graphs
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In theory much of the functionality in here should be migrating into the
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C/C++ codebase.
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"""
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from Numeric import *
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import Chem
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import DataStructs
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import types
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def CharacteristicPolynomial(mol,mat=None):
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""" calculates the characteristic polynomial for a molecular graph
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if mat is not passed in, the molecule's Weighted Adjacency Matrix will
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be used.
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The approach used is the Le Verrier-Faddeev-Frame method described
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in _Chemical Graph Theory, 2nd Edition_ by Nenad Trinajstic (CRC Press,
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1992), pg 76.
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"""
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nAtoms = mol.GetNumAtoms()
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if mat is None:
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# FIX: complete this:
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#A = mol.GetWeightedAdjacencyMatrix()
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pass
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else:
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A = mat
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I = 1.*identity(nAtoms)
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An = A
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res = zeros(nAtoms+1,Float)
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res[0] = 1.0
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for n in xrange(1,nAtoms+1):
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res[n] = 1./n*trace(An)
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Bn = An - res[n]*I
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An = matrixmultiply(A,Bn)
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res[1:] *= -1
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return res
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