def generateSVGGridMolsByLabel(topicModel,
label,
idLabelToMatch=0,
baseRad=0.5,
molSize=(250, 150),
svgsPerRow=4):
result = generateMoleculeSVGsbyLabel(topicModel,
label,
idLabelToMatch=idLabelToMatch,
baseRad=baseRad,
molSize=molSize)
if len(result) == 1:
print(result)
return
svgs, namesSVGs, labelName = result
svgGrid = utilsDrawing.SvgsToGrid(svgs,
namesSVGs,
svgsPerRow=svgsPerRow,
molSize=molSize)
return svgGrid
def generateSVGGridFragemntsForTopic(topicModel, topicIdx, n_top_frags=10, molSize=(100,100),\
svg=True, prior=-1.0, fontSize=0.9,svgsPerRow=4):
svgs = generateTopicRelatedFragmentSVGs(topicModel, topicIdx, n_top_frags=n_top_frags, molSize=molSize,\
svg=svg, prior=prior, fontSize=fontSize)
scores = topicModel.getTopicFragmentProbabilities()
namesSVGs = list(map(lambda x: "p(k={0})={1:.2f}".format(topicIdx,x), \
filter(lambda y: y > prior, sorted(scores[topicIdx,:], reverse=True)[:n_top_frags])))
svgGrid = utilsDrawing.SvgsToGrid(svgs,
namesSVGs,
svgsPerRow=svgsPerRow,
molSize=molSize)
return svgGrid
def generateSVGGridMolsbyTopic(topicModel, topicIdx, idsLabelToShow=[0], topicProbThreshold = 0.5, baseRad=0.5, \
molSize=(250,150), svgsPerRow=4, color=(1.,1.,1.)):
result = generateMoleculeSVGsbyTopicIdx(topicModel, topicIdx, idsLabelToShow=idsLabelToShow, \
topicProbThreshold = topicProbThreshold, baseRad=baseRad,\
molSize=molSize,color=color)
if len(result) == 1:
print(result)
return
svgs, namesSVGs = result
svgGrid = utilsDrawing.SvgsToGrid(svgs, namesSVGs, svgsPerRow=svgsPerRow, molSize=molSize)
return svgGrid