def DegreeNetAlgs(undirected=False, startdeg=10, enddeg=10):
for i in range(startdeg, enddeg + 1):
print i
count = 0
for key, value in data.iteritems():
count += 1
print count, i
mats = value[1]
corr = mats['corr']
lcorr = mats['lcorr']
lacorr = mats['lacorr']
if undirected:
corr += transpose(corr)
lcorr += transpose(lcorr)
lacorr += transpose(lacorr)
corr = corr > findThresh(corr, i)
lcorr = lcorr > findThresh(lcorr, i)
lacorr = lacorr > findThresh(lacorr, i)
corr = myallmeasures(nx.DiGraph(corr))
lcorr = myallmeasures(nx.DiGraph(lcorr))
lacorr = myallmeasures(nx.DiGraph(lacorr))
for k in range(len(corr[0])):
measure = corr[0][k]
value[0][(measure, 'corr')] = corr[1][k]
value[0][(measure, 'lcorr')] = lcorr[1][k]
value[0][(measure, 'lacorr')] = lacorr[1][k]
dump(convert('AD', i), open('totalD_AD_D' + str(i) + '.pkl', 'wb'))
dump(convert('NL', i), open('totalD_NL_D' + str(i) + '.pkl', 'wb'))
dump(convert('MCI', i), open('totalD_MCI_D' + str(i) + '.pkl', 'wb'))
dump(convert('CONVERT', i),
open('totalD_CONVERT_D' + str(i) + '.pkl', 'wb'))
def DegreeNetAlgs(undirected = False,startdeg = 10,enddeg = 10):
for i in range(startdeg,enddeg+1):
print i
count = 0
for key, value in data.iteritems():
count += 1
print count, i
mats = value[1]
corr = mats['corr']
lcorr = mats['lcorr']
lacorr = mats['lacorr']
if undirected:
corr += transpose(corr)
lcorr += transpose(lcorr)
lacorr += transpose(lacorr)
corr = corr > findThresh(corr,i)
lcorr = lcorr > findThresh(lcorr,i)
lacorr = lacorr > findThresh(lacorr,i)
corr = myallmeasures(nx.DiGraph(corr))
lcorr = myallmeasures(nx.DiGraph(lcorr))
lacorr = myallmeasures(nx.DiGraph(lacorr))
for k in range(len(corr[0])):
measure = corr[0][k]
value[0][(measure,'corr')] = corr[1][k]
value[0][(measure,'lcorr')] = lcorr[1][k]
value[0][(measure,'lacorr')] = lacorr[1][k]
dump(convert('AD',i),open('totalD_AD_D'+str(i)+'.pkl','wb'))
dump(convert('NL',i),open('totalD_NL_D'+str(i)+'.pkl','wb'))
dump(convert('MCI',i),open('totalD_MCI_D'+str(i)+'.pkl','wb'))
dump(convert('CONVERT',i),open('totalD_CONVERT_D'+str(i)+'.pkl','wb'))
def RandomDegrees(undirected=False, startdeg=10, enddeg=10):
for des in range(startdeg, enddeg + 1):
print des
count = 0
anslist = []
orderedans = []
for nn in range(100):
x = random.rand(88, 88)
x -= diag(diag(x))
if undirected:
x = triu(x, 1)
x += x.T
x = x > findThresh(x, des)
patientGraph = nx.DiGraph(x)
m = myallmeasures(patientGraph)
anslist.append(m[1])
if nn % 10 == 0:
print nn, des
mnames = m[0]
for j in range(len(mnames)):
measure = [i[j] for i in anslist]
measure = [i for i in measure if i != None]
orderedans.append(measure)
corr = zip(mnames, orderedans)
g = lambda n: n[0]
corr.sort(key=g)
dump([mnames, orderedans],
open("ufinal_rand_D" + str(des) + ".pkl", "wb"))
def RandomDegrees(undirected = False,startdeg = 10, enddeg = 10):
for des in range(startdeg,enddeg + 1):
print des
count = 0
anslist = []
orderedans = []
for nn in range(100):
x = random.rand(88,88)
x -= diag(diag(x))
if undirected:
x = triu(x,1)
x += x.T
x = x > findThresh(x, des)
patientGraph = nx.DiGraph(x)
m = myallmeasures(patientGraph)
anslist.append(m[1])
if nn % 10 == 0:
print nn, des
mnames = m[0];
for j in range(len(mnames)):
measure = [i[j] for i in anslist]
measure = [i for i in measure if i != None]
orderedans.append(measure)
corr = zip(mnames,orderedans)
g = lambda n: n[0]
corr.sort(key = g)
dump([mnames,orderedans], open("ufinal_rand_D"+str(des)+".pkl","wb"))
def RunNetAlgs(dumpData=True):
for key, value in data.iteritems():
print key
mats = value[1]
corr = myallmeasures(nx.DiGraph(mats['tcorr']))
lcorr = myallmeasures(nx.DiGraph(mats['tlcorr']))
lacorr = myallmeasures(nx.DiGraph(mats['tlacorr']))
for i in range(len(corr[0])):
measure = corr[0][i]
value[0][(measure, 'corr')] = corr[1][i]
value[0][(measure, 'lcorr')] = lcorr[1][i]
value[0][(measure, 'lacorr')] = lacorr[1][i]
if dumpData:
dump(data, open('computed_data', 'wb'))
dump(convert('AD'), open('final_AD.pkl', 'wb'))
dump(convert('NL'), open('final_NL.pkl', 'wb'))
dump(convert('MCI'), open('final_MCI.pkl', 'wb'))
dump(convert('CONVERT'), open('final_CONVERT.pkl', 'wb'))
def RunNetAlgs(dumpData = True):
for key, value in data.iteritems():
print key
mats = value[1]
corr = myallmeasures(nx.DiGraph(mats['tcorr']))
lcorr = myallmeasures(nx.DiGraph(mats['tlcorr']))
lacorr = myallmeasures(nx.DiGraph(mats['tlacorr']))
for i in range(len(corr[0])):
measure = corr[0][i]
value[0][(measure,'corr')] = corr[1][i]
value[0][(measure,'lcorr')] = lcorr[1][i]
value[0][(measure,'lacorr')] = lacorr[1][i]
if dumpData:
dump(data,open('computed_data','wb'))
dump(convert('AD'),open('final_AD.pkl','wb'))
dump(convert('NL'),open('final_NL.pkl','wb'))
dump(convert('MCI'),open('final_MCI.pkl','wb'))
dump(convert('CONVERT'),open('final_CONVERT.pkl','wb'))