def save_qa_img_dirnme(in4d, outdir):
pth, nme = os.path.split(in4d)
img = nipy.load_image(in4d)
diag.plot_tsdiffs(diag.time_slice_diffs(img))
cleantime = time.asctime().replace(' ','-').replace(':', '_')
figfile = os.path.join(outdir, 'QA_%s_%s.png'%(nme, cleantime))
pylab.savefig(figfile)
def save_qa_img_dirnme(in4d, outdir):
pth, nme = os.path.split(in4d)
img = nipy.load_image(in4d)
diag.plot_tsdiffs(diag.time_slice_diffs(img))
cleantime = time.asctime().replace(' ', '-').replace(':', '_')
figfile = os.path.join(outdir, 'QA_%s_%s.png' % (nme, cleantime))
pylab.savefig(figfile)
def test_screen():
img = ni.load_image(funcfile)
res = nad.screen(img)
yield assert_equal(res['mean'].ndim, 3)
yield assert_equal(res['pca'].ndim, 4)
yield assert_equal(sorted(res.keys()),
['max', 'mean', 'min',
'pca', 'pca_res',
'std', 'ts_res'])
data = np.asarray(img)
yield assert_array_equal(np.max(data, axis=-1),
res['max'])
yield assert_array_equal(np.mean(data, axis=-1),
res['mean'])
yield assert_array_equal(np.min(data, axis=-1),
res['min'])
yield assert_array_equal(np.std(data, axis=-1),
res['std'])
pca_res = nad.pca.pca(data, axis=-1, standardize=False, ncomp=10)
for key in pca_res:
yield assert_array_equal(pca_res[key], res['pca_res'][key])
ts_res = nad.time_slice_diffs(data)
for key in ts_res:
yield assert_array_equal(ts_res[key], res['ts_res'][key])
