import nipy.neurospin.statistical_mapping as sm
#import nipy.neurospin.image as image
from nipy.io.imageformats import load
def ComputeResultsContents(zmap_file_path, mask_file_path,
output_html_path, threshold=0.001,
method='fpr', cluster=0, null_zmax='bonferroni',
null_smax=None, null_s=None, nmaxima=4):
# Read data: z-map and mask
zmap = load(zmap_file_path)
mask = load(mask_file_path)
# Compute cluster statistics
#if null_smax != None:
nulls={'zmax' : null_zmax, 'smax' : null_smax, 's' : null_s}
clusters, info = sm.cluster_stats(zmap, mask, height_th=threshold,
height_control=method.lower(),
cluster_th=cluster, nulls=nulls)
if clusters == None or info == None:
print "No results were writen for %s" % zmap_file_path
return
#else:
# clusters, info = sm.cluster_stats(zmap, mask, height_th=threshold,
# height_control=method, cluster_th=cluster,
# nulls={})
# Make HTML page
output = open(output_html_path, mode = "w")
output.write("<html><head><title> Result Sheet for %s \
</title></head><body><center>\n" % zmap_file_path)
output.write("<h2> Results for %s</h2>\n" % zmap_file_path)
output.write("<table border = 1>\n")
output.write("<tr><th colspan=4> Voxel significance </th>\
<th colspan=3> Coordinates in MNI referential</th>\
<th>Cluster Size</th></tr>\n")
output.write("<tr><th>p FWE corr<br>(Bonferroni)</th>\
<th>p FDR corr</th><th>Z</th><th>p uncorr</th>")
output.write("<th> x (mm) </th><th> y (mm) </th><th> z (mm) </th>\
<th>(voxels)</th></tr>\n")
for cluster in clusters:
maxima = cluster['maxima']
for j in range(min(len(maxima), nmaxima)):
temp = ["%f" % cluster['fwer_pvalue'][j]]
temp.append("%f" % cluster['fdr_pvalue'][j])
temp.append("%f" % cluster['zscore'][j])
temp.append("%f" % cluster['pvalue'][j])
for it in range(3):
temp.append("%f" % maxima[j][it])
if j == 0: ## Main local maximum
output.write('<tr><th align="center">' + '</th>\
<th align="center">'.join(temp) + '</th></tr>\n')
else: ## Secondary local maxima
output.write('<tr><td align="center">' + '</td>\
<td align="center">'.join(temp) + '</td><td></td></tr>\n')
output.write("</table>\n")
output.write("Number of voxels : %i<br>\n" % len(mask.get_data() > 0))
output.write("Threshold Z=%f (%s control at %f)<br>\n" \
% (info['threshold_z'], method, threshold))
output.write("</center></body></html>\n")
output.close()
