% (groups[i1], groups[i2]), Style_3)
# prepare data
Y1 = np.zeros([groups_n[i1], len(rois), len(effects)])
Y2 = np.zeros([groups_n[i2], len(rois), len(effects)])
for e in range(0, len(effects)):
sheet = xls.sheet_by_index(e)
for r in range(0, len(rois)):
for s in range(0, groups_n[i1]):
Y1[s, r, e] = sheet.cell(groups_row[i1] + s, r + 1).value
for s in range(0, groups_n[i2]):
Y2[s, r, e] = sheet.cell(groups_row[i2] + s, r + 1).value
# run the test
t, T, pu, p = permutation_test(Y1, Y2, permutations=nPERMUTATIONS)
# add to the spreadsheet
for r in range(0, len(rois)):
if pu[r] <= 0.05:
sheet_out.write(OUT_row, r + 1, pu[r], Style_1)
else:
sheet_out.write(OUT_row, r + 1, pu[r], Style_2)
if p[r] <= 0.05:
sheet_out.write(OUT_row + nTESTs + 2, r + 1, p[r], Style_1)
else:
sheet_out.write(OUT_row + nTESTs + 2, r + 1, p[r], Style_2)
OUT_row = OUT_row + 1
# writing results to file
import numpy as np from scikits.permuttest.two_sample import permutation_test, t_stat, hotelling_t_square, design_matrix """ Y = np.random.normal(size=(10, 10000)) t = t_stat(Y, 5) """ # 10 subjects, 7 regions, 2 contrasts Y = np.random.normal(size=(10, 100, 2)) # test hotelling stat without confounds T0 = hotelling_t_square(Y, 5) # test hotelling stat with confounds # age = np.random.rand(10) age = np.zeros(10) + 0.01 * np.random.rand(10) age[0:5] += 1.0 T1 = hotelling_t_square(Y, 5, confounds=(age,)) # test permutation test t, T, pu, p = permutation_test(Y[0:5, ...], Y[5:, ...], confounds=(age,), permutations=100) t, T, pu, p = permutation_test(Y[0:5, :, 0] + 5, Y[5:, :, 0], confounds=(age,), permutations=100, two_sided=False) # t, T, pu, p = permutation_test(Y[0:5, :, 0] + 2, Y[5:, :, 0], permutations=100)
# prepare data
Y1 = np.zeros([groups_n[i1], len(rois), len(effects)])
Y2 = np.zeros([groups_n[i2], len(rois), len(effects)])
for e in range(0, len(effects)):
sheet = xls.sheet_by_name( effects[e] )
for r in range(0, len(rois)):
for s in range(0, groups_n[i1]):
Y1[s, r, e] = sheet.cell(groups_row[i1] + s, r + 1).value
for s in range(0, groups_n[i2]):
Y2[s, r, e] = sheet.cell(groups_row[i2] + s, r + 1).value
# run the test
if len(covariates) == 0 or use_covariates == False :
t, T, pu, p = permutation_test(Y1, Y2, permutations=nPERMUTATIONS, confounds=None, two_sided=(True if nTAILS == 2 else False))
else :
# prepare covariates
CONFOUNDS = np.zeros([len(covariates), groups_n[i1]+groups_n[i2]])
sheet = xls.sheet_by_name( "Covariates" )
for c in range(0, len(covariates)):
for s in range(0, groups_n[i1]):
CONFOUNDS[c,s] = sheet.cell(groups_row[i1] + s, c + 1).value
for s in range(0, groups_n[i2]):
CONFOUNDS[c, groups_n[i1]+s] = sheet.cell(groups_row[i2] + s, c + 1).value
t, T, pu, p = permutation_test(Y1, Y2, permutations=nPERMUTATIONS, confounds=CONFOUNDS, two_sided=(True if nTAILS == 2 else False))
# add to the spreadsheet
for r in range(0, len(rois)):
if pu[r] <= 0.05: