def calculate_flux(mm, topic_labels, A=[8], B=[2, 13]):
#A=[8],B=[2,13],
# Calculate the flux between two states camp arrival and camp liquidiation / camp transfer )
tpt = msm.tpt(mm, A, B)
nCut = 1
(bestpaths, bestpathfluxes) = tpt.pathways(fraction=0.7)
cumflux = 0
# Print the best path between the two states
print("Path flux\t\t%path\t%of total\tpath")
topic_sequences = {}
for i in range(len(bestpaths)):
cumflux += bestpathfluxes[i]
flux = 100.0 * bestpathfluxes[i] / tpt.total_flux
if flux > 0:
#print(bestpathfluxes[i],'\t','%3.1f'%(100.0*bestpathfluxes[i]/tpt.total_flux),'%\t','%3.1f'%(100.0*cumflux/tpt.total_flux),'%\t\t',bestpaths[i])
topic_sequence = []
for element in bestpaths[i]:
#print (topic_labels[element])
topic_sequence.append(topic_labels[element])
topic_sequence = '-'.join(topic_sequence)
topic_sequences[
topic_sequence] = 100.0 * bestpathfluxes[i] / tpt.total_flux
return topic_sequences
if i == 12:
break
# Print the eigenvalues of states
'''for element in mm.eigenvalues().argsort()[::-1]:
print (topic_list[element])
'''
# Calculate the flux between two states (topic_2, selection and topic_8_14 camp liquidiation / camp transfer )
A = [8]
B = [2, 13]
tpt = msm.tpt(mm, A, B)
nCut = 1
(bestpaths, bestpathfluxes) = tpt.pathways(fraction=0.5)
cumflux = 0
# Print the best path between the two states
print("Path flux\t\t%path\t%of total\tpath")
for i in range(len(bestpaths)):
cumflux += bestpathfluxes[i]
print(bestpathfluxes[i], '\t',
'%3.1f' % (100.0 * bestpathfluxes[i] / tpt.total_flux), '%\t',
'%3.1f' % (100.0 * cumflux / tpt.total_flux), '%\t\t',
bestpaths[i])
topic_sequence = []