jupyter notebook - ValueError: need more than 1 value to unpack in network reconstruction -
from io import stringio import numpy np import random #import networkx nx import os import io sklearn.linear_model import lasso sklearn import metrics multiprocessing import pool data = np.loadtxt('c1.txt') # adjlist.txt #print data[:,2] fadj = np.matrix(data[:,2]) print fadj def cal_phi(s,ni,sim): """ calculate phi matrix , y vector args: s: binary state timeseries array ni: index of node sim: hamming similarity threshold returns: phi: phi matrix yv: y vector """ = ni idof0, = np.where(s[:-1,i]==0) s0 = s[idof0,:] y1 = s[idof0+1,i] lbase,num_nodes = s0.shape x = s0 #~ base = np.random.randint(0,lbase,size=num_nodes) base = range(lbase) random.shuffle(base) base = x[base[:num_nodes],:] base = np.transpose(base) hammatrix = num_nodes - (np.dot(x,base)+np.dot((1-x),(1-base))) yv = np.zeros((num_nodes,1)) phi = np.zeros((num_nodes,num_nodes)) ibase in xrange(num_nodes): idofsim, = np.where(hammatrix[:,ibase]<sim) phi[ibase,:] = np.mean(s0[idofsim,:],0) yv[ibase,0] = np.mean(y1[idofsim]) del base #~ print phi,yv del s return phi,yv def cal_x(phi,yv,nt=0.5): """ calculate x vector lasso args: phi: phi matrix m*n dimension yv: y vectors m*1 dimension nt: fraction of used equations returns: xv: solution of x vector """ m,n = phi.shape nt = int(nt*n) xv = 0 in xrange(5): ntv = np.random.randint(0,m,size=nt) #~ print ntv[0] phi = phi[ntv,:] yv = yv[ntv,0] clf = lasso(alpha=0.0001,fit_intercept=false,max_iter=100000) #100000 clf.fit(phi,yv) xv += clf.coef_/5.0 return xv def cal_auc(xx,xv): fpr,tpr,threshold = metrics.roc_curve(xx,xv) auc = metrics.auc(fpr,tpr) return auc def cal_aupr(xx,xv): pre,rec,threshold = metrics.precision_recall_curve(np.array(xx),np.array(xv)) aupr = metrics.auc([1-i in rec],pre) return aupr def cal_sr(xv,fadj=np.matrix(data[:,2])): #adj.txt: # fadj='adjlist.txt' :fadj=np.matrix(data[:,2]) """ calculate success rates args: xv: dict, results of lasso fadj: file name of exact adjacency matrix """ auc = 0 aupr = 0 # new line: xx = np.loadtxt(fadj,dtype=int) # fadj[:,2]: 3rd column of data has been loaded: ii in xv: xxi = xx[:,ii] xvi = xv[ii] auc += cal_auc(xxi,xvi) aupr += cal_aupr(xxi,xvi) return (auc/len(xv),aupr/len(xv)) def cal_individual(s,ii,sim): #print ii, phi,yv = cal_phi(s,ii,sim) xv = cal_x(phi,yv,0.1) ##print ii,xv return (ii,xv) def calall(s,num_nodes): # print nl, stemp = s[:,:] sim = 0.45 sim = sim * num_nodes xv = {} pool = pool(2) results = [pool.apply_async(cal_individual,(stemp,ii,sim)) ii in xrange(num_nodes)] roots = [r.get() r in results] xv={rts[0]:rts[1] rts in roots} print '\n finished 1 network' #auroc,aupr = cal_auroc_aupr(xv) auroc,aupr = cal_sr(xv) return (auroc,aupr) ## main function def main(num_node): s = np.loadtxt('binaryd.txt',dtype=int) # datasetfinal.txt: #binaryd.txt ltime,num_nodes = s.shape #print ltime,num_nodes auroc,aupr = calall(s,num_nodes) #auroc = (auroc * aupr)**0.5 return auroc,aupr if __name__ == '__main__': import gc num_nodes = 100 #size of graph # 100 ii = np.arange(100) print 'start' auroc,aupr = main(num_nodes) # main function xv = main(num_nodes) # newline print 'auroc: %s'%auroc print 'aupr: %s'%aupr #print 'ii:%s'%ii # added new line: gc.collect() my question has answers in stack overflow, not able debug goes wrong. getting following error:
traceback (most recent call last): file "test2.py", line 141, in auroc,aupr = main(num_nodes) # main function
file "test2.py", line 130, in main ltime,num_nodes = s.shape valueerror: need more 1 value unpack
any suggestions me out fix issue.
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