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])