def testStudyVariance(self):
alnFileName = "../../alignmentFiles/mmult.list-FINAL.aln"
workingDirectory = "../../alignmentFiles/"
resultsFileName2 = "../../alignmentFiles/results2.results"
generateMultipleAlignment.getResidues(0.8, resultsFileName2, alnFileName, workingDirectory, False, True, False)
AtomicresultsFileName = "../../alignmentFiles/results2.Atomic"
generateMultipleAlignment.composeAtomicMatrix(resultsFileName2, AtomicresultsFileName)
filteredAtomicMatrixFileName = "../../alignmentFiles/filteredResults2.Atomic"
generateMultipleAlignment.filterAtomicMatrix(AtomicresultsFileName, filteredAtomicMatrixFileName)
caMatrixFileName = "../../alignmentFiles/filteredResults2.Atomic"
dimensions = generateMultipleAlignment.getDimensions(caMatrixFileName)
(mask, matrix) = svdAnalysis.loadCAmatrix(caMatrixFileName, dimensions)
(caMatrix, caMask) = svdAnalysis.getCovarianceMatrix(mask, matrix)
(atoms_variance, atoms_variance_mask) = svdAnalysis.getAtomsVariance(caMatrix, caMask)
(max, min, mean, normalizedAtoms) = svdAnalysis.atoms_variance_statistics(atoms_variance, atoms_variance_mask)
print ("max %f \n" % (max,))
print ("min %f \n" % (min,))
print ("mean %f \n" % (mean,))
print normalizedAtoms
print "\n\n"
workingDirectory = "../../alignmentFiles/"
varianceFileName = workingDirectory + "variance.atomic"
maskFileName = workingDirectory + "variance_mask.atomic"
svdAnalysis.serializeAtomsVariance(atoms_variance, atoms_variance_mask, varianceFileName, maskFileName)
(atoms_variance, atoms_variance_mask) = svdAnalysis.encarnateAtomsVariance(varianceFileName, maskFileName)
assert 30 == len(atoms_variance[0])
for variance in atoms_variance[0]:
print ("%3.f \n" % (variance,))
def serialize_variance_results(self):
svdAnalysis.serializeAtomsVariance(self.atoms_variance, self.atoms_variance_mask, self.varianceFileName, self.maskFileName)
