dofB = len(open("%s/../copesB.txt" %(input_directory),"r").readlines())-2
except:
dofB = 44
for groupB in groupB_maps:
mrB = nib.load(groupB)
mrB = IT.t_to_z(mrB,dofB)
contrast_task_B = os.path.basename(groupB).replace("_groupB_tstat1.nii.gz","")
for thresh in thresholds:
print "Processing threshold %s" %(thresh)
for absolute_value in ["pos","posneg"]:
if absolute_value == "posneg":
# Group A is always unthresholded, B is thresholded
mrthresh = IT.threshold_abs(mrB,thresholds=[thresh])[thresh]
else:
mrthresh = IT.threshold_pos(mrB,thresholds=[thresh])[thresh]
ids.append(contrast_task_B)
thresh_id.append(thresh)
# 3/12/2015: confirmed that first returns +/- values, second returns only positive
# If the image is empty thresholded, we append NaN
if len(np.unique(mrthresh.get_data()))==1:
cca_pearson.append(np.nan)
svi_pearson.append(np.nan)
cca_spearman.append(np.nan)
svi_spearman.append(np.nan)
sizes.loc[idx] = [0,0]
nanlog_cca.append("nan_mrthresh_empty")
nanlog_svi.append("nan_mrthresh_empty")
size_ids.append("%s_%s" %(thresh,absolute_value))
else:
# Generate a union (svi) and intersection (cca) mask
max = 0
min = 0
for input_map in input_maps:
img = nibabel.load(input_map)
img = IT.t_to_z(img, 46).get_data()
if img.max() > max:
max = img.max()
if img.min() < min:
min = img.min()
for i in range(0, len(input_maps)):
print "Processing %s of %s" % (i, len(input_maps))
input_map = input_maps[i]
mapname = os.path.basename(input_map).replace("_groupA_tstat1.nii.gz", "")
task = lookup.task[lookup.id == mapname].tolist()[0]
contrast = lookup.contrasts[lookup.id == mapname].tolist()[0]
title = "%s_%s" % (task, contrast)
image = nibabel.load(input_map)
Z = IT.t_to_z(image, 46)
for thresh in range(0, 10):
print thresh
pos = IT.threshold_pos(image, thresholds=[thresh])[thresh]
posneg = IT.threshold_abs(image, thresholds=[thresh])[thresh]
fig = plot_stat_map(pos, vmax=max, title="%s Positive Only" % title, cut_coords=(0, 0, 0))
fig.savefig("%s/%s_%s_pos.png" % (outdir, thresh, mapname))
fig.close()
fig = plot_stat_map(posneg, vmax=max, title="%s Positive and Negative" % title, cut_coords=(0, 0, 0))
fig.savefig("%s/%s_%s_posneg.png" % (outdir, thresh, mapname))
fig.close()
