] corrs = np.corrcoef(hemi_data) subj_data = corrs headers = ['%s(%s)' % (r, h) for h in hemi for r in rois] conn_titles = [ '%s - %s' % (headers[il[0][i]], headers[il[1][i]]) for i in range(len(il[0])) ] if s in g1: g1_data.append(np.array(subj_data)) elif s in g2: g2_data.append(np.array(subj_data)) elif s in g3: g3_data.append(np.array(subj_data)) res = [] g1_data = np.arctanh(g1_data).transpose([1, 2, 0]) g2_data = np.arctanh(g2_data).transpose([1, 2, 0]) g3_data = np.arctanh(g3_data).transpose([1, 2, 0]) print '=== nvVSper ===' pval, adj, null = nbs.compute_nbs(stats, g1_data, g2_data, thresh, nperms, tail) res.append([pval, adj]) print '=== nvVSrem ===' pval, adj, null = nbs.compute_nbs(stats, g1_data, g3_data, thresh, nperms, tail) res.append([pval, adj]) print '=== remVSper ===' pval, adj, null = nbs.compute_nbs(stats, g2_data, g3_data, thresh, nperms, tail) res.append([pval, adj])
x_sx = copy.deepcopy(g1_sx) for i in delme: x_sx.pop(i) delme = np.unique(np.nonzero(np.isnan(y))[2]) y = np.delete(y, delme, axis=2) if stats == 'linreg': y_sx = copy.deepcopy(g2_sx) for i in delme: y_sx.pop(i) if len(g3) > 0: z = np.array(g3_data[b]).transpose([1, 2, 0]) delme = np.unique(np.nonzero(np.isnan(z))[2]) z = np.delete(z, delme, axis=2) if stats in ['ttest', 'mwu']: pval, adj, null = nbs.compute_nbs(stats, x, y, thresh, nperms, tail) elif stats == 'linreg': adhd = np.dstack([x, y]) sx = np.array(x_sx + y_sx) pval, adj, null = nbs.compute_nbs(stats, adhd, sx, thresh, nperms) elif stats in ['anova', 'kw']: pval, adj, null = nbs.compute_nbs(stats, x, y, thresh, nperms, tail, z) res.append([pval, adj]) n1 = len(g1_data[0]) n2 = len(g2_data[0]) print 'size1 =', n1 print 'size2 =', n2 print 'g1 =', g1_fname print 'g2 =', g2_fname print 'g3 =', g3_fname
# if stats=='linreg': # y_sx = copy.deepcopy(g2_sx) # for i in delme: # y_sx.pop(i) # if len(g3)>0: # z = np.array(g3_data[b]).transpose([1,2,0]) # delme = np.unique(np.nonzero(np.isnan(z))[2]) # z = np.delete(z, delme, axis=2) for t in thresh: # anova[b].append(nbs.compute_nbs('anova',x,y,t,nperms,z)) # kruskal[b].append(nbs.compute_nbs('kw',x,y,t,nperms,z)) # nvVSper_mwu[b].append(nbs.compute_nbs('mwu',x,y,t,nperms)) # nvVSrem_mwu[b].append(nbs.compute_nbs('mwu',x,z,t,nperms)) # perVSrem_mwu[b].append(nbs.compute_nbs('mwu',y,z,t,nperms)) # nvVSper[b].append(nbs.compute_nbs('ttest',x,y,t,nperms)) nvVSrem[b].append(nbs.compute_nbs('ttest', x, z, t, nperms)) # perVSrem[b].append(nbs.compute_nbs('ttest',y,z,t,nperms)) # inatt[b].append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_inatt+g3_inatt),t,nperms)) # hi[b].append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_hi+g3_hi),t,nperms)) n1 = len(g1_data[0]) n2 = len(g2_data[0]) n3 = len(g3_data[0]) print 'size1 =', n1 print 'size2 =', n2 print 'size3 =', n3 print 'g1 =', g1_fname print 'g2 =', g2_fname print 'g3 =', g3_fname m = ['pli', 'imcoh', 'plv', 'wpli', 'pli2_unbiased', 'wpli2_debiased'] print m[cmethod]
nvVSper = [] nvVSrem = [] perVSrem = [] nvVSper_mwu = [] nvVSrem_mwu = [] perVSrem_mwu = [] anova = [] kruskal = [] inatt = [] hi = [] x = np.array(g1_data).transpose([1, 2, 0]) y = np.array(g2_data).transpose([1, 2, 0]) z = np.array(g3_data).transpose([1, 2, 0]) for t in thresh: anova.append(nbs.compute_nbs("anova", x, y, t, nperms, z)) kruskal.append(nbs.compute_nbs("kw", x, y, t, nperms, z)) nvVSper_mwu.append(nbs.compute_nbs("mwu", x, y, t, nperms)) nvVSrem_mwu.append(nbs.compute_nbs("mwu", x, z, t, nperms)) perVSrem_mwu.append(nbs.compute_nbs("mwu", y, z, t, nperms)) nvVSper.append(nbs.compute_nbs("ttest", x, y, t, nperms)) nvVSrem.append(nbs.compute_nbs("ttest", x, z, t, nperms)) perVSrem.append(nbs.compute_nbs("ttest", y, z, t, nperms)) inatt.append(nbs.compute_nbs("linreg", np.dstack([y, z]), np.array(g2_inatt + g3_inatt), t, nperms)) hi.append(nbs.compute_nbs("linreg", np.dstack([y, z]), np.array(g2_hi + g3_hi), t, nperms)) n1 = len(g1_data[0]) n2 = len(g2_data[0]) n3 = len(g3_data[0]) print "size1 =", n1 print "size2 =", n2
# create correlations for each subject il = np.tril_indices(2*len(rois), k=-1) g1_data = [] g2_data = [] g3_data = [] for s in subjs: hemi_data = [np.genfromtxt('%s/%s_%s_%s.1D'%(data_dir,s,r,h)) for h in hemi for r in rois] corrs = np.corrcoef(hemi_data) subj_data = corrs headers = ['%s(%s)'%(r,h) for h in hemi for r in rois] conn_titles = ['%s - %s'%(headers[il[0][i]],headers[il[1][i]]) for i in range(len(il[0]))] if s in g1: g1_data.append(np.array(subj_data)) elif s in g2: g2_data.append(np.array(subj_data)) elif s in g3: g3_data.append(np.array(subj_data)) res=[] g1_data = np.arctanh(g1_data).transpose([1,2,0]) g2_data = np.arctanh(g2_data).transpose([1,2,0]) g3_data = np.arctanh(g3_data).transpose([1,2,0]) print '=== nvVSper ===' pval, adj, null = nbs.compute_nbs(stats,g1_data,g2_data,thresh,nperms,tail) res.append([pval,adj]) print '=== nvVSrem ===' pval, adj, null = nbs.compute_nbs(stats,g1_data,g3_data,thresh,nperms,tail) res.append([pval,adj]) print '=== remVSper ===' pval, adj, null = nbs.compute_nbs(stats,g2_data,g3_data,thresh,nperms,tail) res.append([pval,adj])
x_sx = copy.deepcopy(g1_sx) for i in delme: x_sx.pop(i) delme = np.unique(np.nonzero(np.isnan(y))[2]) y = np.delete(y, delme, axis=2) if stats=='linreg': y_sx = copy.deepcopy(g2_sx) for i in delme: y_sx.pop(i) if len(g3)>0: z = np.array(g3_data[b]).transpose([1,2,0]) delme = np.unique(np.nonzero(np.isnan(z))[2]) z = np.delete(z, delme, axis=2) if stats in ['ttest','mwu']: pval, adj, null = nbs.compute_nbs(stats,x,y,thresh,nperms,tail) elif stats=='linreg': adhd = np.dstack([x, y]) sx = np.array(x_sx + y_sx) pval, adj, null = nbs.compute_nbs(stats,adhd,sx,thresh,nperms) elif stats in ['anova','kw']: pval, adj, null = nbs.compute_nbs(stats,x,y,thresh,nperms,tail,z) res.append([pval,adj]) n1 = len(g1_data[0]) n2 = len(g2_data[0]) print 'size1 =', n1 print 'size2 =', n2 print 'g1 =',g1_fname print 'g2 =',g2_fname print 'g3 =',g3_fname
nvVSper = [] nvVSrem = [] perVSrem = [] nvVSper_mwu = [] nvVSrem_mwu = [] perVSrem_mwu = [] anova = [] kruskal = [] inatt = [] hi = [] x = np.array(g1_data).transpose([1, 2, 0]) y = np.array(g2_data).transpose([1, 2, 0]) z = np.array(g3_data).transpose([1, 2, 0]) for t in thresh: anova.append(nbs.compute_nbs('anova', x, y, t, nperms, z)) kruskal.append(nbs.compute_nbs('kw', x, y, t, nperms, z)) nvVSper_mwu.append(nbs.compute_nbs('mwu', x, y, t, nperms)) nvVSrem_mwu.append(nbs.compute_nbs('mwu', x, z, t, nperms)) perVSrem_mwu.append(nbs.compute_nbs('mwu', y, z, t, nperms)) nvVSper.append(nbs.compute_nbs('ttest', x, y, t, nperms)) nvVSrem.append(nbs.compute_nbs('ttest', x, z, t, nperms)) perVSrem.append(nbs.compute_nbs('ttest', y, z, t, nperms)) inatt.append( nbs.compute_nbs('linreg', np.dstack([y, z]), np.array(g2_inatt + g3_inatt), t, nperms)) hi.append( nbs.compute_nbs('linreg', np.dstack([y, z]), np.array(g2_hi + g3_hi), t, nperms)) n1 = len(g1_data[0])
# if stats=='linreg': # y_sx = copy.deepcopy(g2_sx) # for i in delme: # y_sx.pop(i) # if len(g3)>0: # z = np.array(g3_data[b]).transpose([1,2,0]) # delme = np.unique(np.nonzero(np.isnan(z))[2]) # z = np.delete(z, delme, axis=2) for t in thresh: # anova[b].append(nbs.compute_nbs('anova',x,y,t,nperms,z)) # kruskal[b].append(nbs.compute_nbs('kw',x,y,t,nperms,z)) # nvVSper_mwu[b].append(nbs.compute_nbs('mwu',x,y,t,nperms)) # nvVSrem_mwu[b].append(nbs.compute_nbs('mwu',x,z,t,nperms)) # perVSrem_mwu[b].append(nbs.compute_nbs('mwu',y,z,t,nperms)) # nvVSper[b].append(nbs.compute_nbs('ttest',x,y,t,nperms)) nvVSrem[b].append(nbs.compute_nbs('ttest',x,z,t,nperms)) # perVSrem[b].append(nbs.compute_nbs('ttest',y,z,t,nperms)) # inatt[b].append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_inatt+g3_inatt),t,nperms)) # hi[b].append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_hi+g3_hi),t,nperms)) n1 = len(g1_data[0]) n2 = len(g2_data[0]) n3 = len(g3_data[0]) print 'size1 =', n1 print 'size2 =', n2 print 'size3 =', n3 print 'g1 =',g1_fname print 'g2 =',g2_fname print 'g3 =',g3_fname m = ['pli','imcoh','plv','wpli','pli2_unbiased','wpli2_debiased'] print m[cmethod]
# corrs.append(subj_corrs) nvVSper = [] nvVSrem = [] perVSrem = [] nvVSper_mwu = [] nvVSrem_mwu = [] perVSrem_mwu = [] anova = [] kruskal = [] inatt = [] hi = [] x = np.arctanh(np.array(corrs[0]).transpose([1,2,0])) y = np.arctanh(np.array(corrs[1]).transpose([1,2,0])) z = np.arctanh(np.array(corrs[2]).transpose([1,2,0])) for t in thresh: # anova.append(nbs.compute_nbs('anova',x,y,t,nperms,z)) # kruskal.append(nbs.compute_nbs('kw',x,y,t,nperms,z)) # nvVSper_mwu.append(nbs.compute_nbs('mwu',x,y,t,nperms)) # nvVSrem_mwu.append(nbs.compute_nbs('mwu',x,z,t,nperms)) # perVSrem_mwu.append(nbs.compute_nbs('mwu',y,z,t,nperms)) nvVSper.append(nbs.compute_nbs('ttest',x,y,t,nperms)) nvVSrem.append(nbs.compute_nbs('ttest',x,z,t,nperms)) perVSrem.append(nbs.compute_nbs('ttest',y,z,t,nperms)) # inatt.append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_inatt+g3_inatt),t,nperms)) # hi.append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_hi+g3_hi),t,nperms)) print [r[0] for r in nvVSper] print [r[0] for r in nvVSrem] print [r[0] for r in perVSrem]
# corrs.append(subj_corrs) nvVSper = [] nvVSrem = [] perVSrem = [] nvVSper_mwu = [] nvVSrem_mwu = [] perVSrem_mwu = [] anova = [] kruskal = [] inatt = [] hi = [] x = np.arctanh(np.array(corrs[0]).transpose([1, 2, 0])) y = np.arctanh(np.array(corrs[1]).transpose([1, 2, 0])) z = np.arctanh(np.array(corrs[2]).transpose([1, 2, 0])) for t in thresh: # anova.append(nbs.compute_nbs('anova',x,y,t,nperms,z)) # kruskal.append(nbs.compute_nbs('kw',x,y,t,nperms,z)) # nvVSper_mwu.append(nbs.compute_nbs('mwu',x,y,t,nperms)) # nvVSrem_mwu.append(nbs.compute_nbs('mwu',x,z,t,nperms)) # perVSrem_mwu.append(nbs.compute_nbs('mwu',y,z,t,nperms)) nvVSper.append(nbs.compute_nbs('ttest', x, y, t, nperms)) nvVSrem.append(nbs.compute_nbs('ttest', x, z, t, nperms)) perVSrem.append(nbs.compute_nbs('ttest', y, z, t, nperms)) # inatt.append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_inatt+g3_inatt),t,nperms)) # hi.append(nbs.compute_nbs('linreg',np.dstack([y, z]),np.array(g2_hi+g3_hi),t,nperms)) print[r[0] for r in nvVSper] print[r[0] for r in nvVSrem] print[r[0] for r in perVSrem]