Example #1
0
def mean_std_rand(labels_all):
    # labels_all is nvert x nsub matrix
    # delete subjects for which parcellation is not done
    labs1 = labels_all
    ind = (sp.sum(labs1, axis=0) != 0)
    labs1 = labs1[:, ind]

    labs = reorder_labels(labs1)

    labs_mode, freq = sp.stats.mode(labs, axis=1)
    freq1 = sp.double(freq.squeeze())
    freq1 /= labs.shape[1]

    ars = sp.zeros(labs.shape[1])
    for ind in range(labs.shape[1]):
        ars[ind] = adjusted_rand_score(labs_mode.squeeze(), labs[:, ind])

    return ars.mean(), ars.std(), freq1, labs_mode
Example #2
0
a2009s.32k_fs.reduce3.very_smooth.left.dfs'))
count1 = 0
rho_rho = []
rho_all = []

s1 = sp.load('labs_all_split2_data_1common_30clusters.npz')
l = s1['lab_sub1']
l1 = sp.reshape(l, (l.shape[0] * l.shape[1]), order='F')

l = s1['lab_sub2']
l2 = sp.reshape(l, (l.shape[0] * l.shape[1]), order='F')

l12 = sp.concatenate((l1[:, None], l2[:, None]), axis=1)

print sp.sum(sp.absolute(l12[:, 1] - l12[:, 0]))
l12 = reorder_labels(l12)

print sp.sum(sp.absolute(l12[:, 1] - l12[:, 0]))

l1 = sp.reshape(l12[:, 0], (l.shape[0], l.shape[1]), order='F')
l2 = sp.reshape(l12[:, 1], (l.shape[0], l.shape[1]), order='F')

perm1 = sp.mod(17 * sp.arange(max(l1.flatten()) + 1), max(l1.flatten()) + 1)

# Plot labels
ind = 19
ind2 = 0
lab1 = l1[:, ind]
lab2 = l2[:, ind2]
nVert = dfs_left_sm.vertices.shape[0]
Example #3
0
print sp.sum(sp.absolute(l12[:, 1] - l12[:, 0]))

print sp.sum(sp.absolute(l12[:, 1] - l12[:, 0]))

l1 = sp.reshape(l12[:, 0], (l.shape[0], 40), order='F')
l2 = sp.reshape(l12[:, 1], (l.shape[0], 40), order='F')

#perm1 = sp.mod(19*sp.arange(max(l1.flatten())+1), max(l1.flatten())+1)
nVert = l.shape[0]
#cat_data = s1['cat_data']

for ind in range(30):
    lab1 = l1[:, ind]
    lab2 = l2[:, ind]
    tlab[:, 1] = lab1
    lab22, ind1 = reorder_labels(tlab)
    lab1 = ind1[sp.int16(lab1), 1]
    lab2 = ind1[sp.int16(lab2), 1]

    dfs_left_sm.labels = lab1
    s = sp.ones(
        nVert)  #silhouette_samples(cat_data[nVert*(ind):nVert*(ind+1), :],
    #                  dfs_left_sm.labels)
    s[s < 0] = 0
    s = s / sp.median(s)
    s[s > 1.0] = 1.0
    dfs_left_sm = patch_color_labels(dfs_left_sm, shuffle=False)
    view_patch_vtk(dfs_left_sm,
                   azimuth=90,
                   elevation=180,
                   roll=90,