def test_reorder_input():
incs, outcs, map, inv = voxel_to_world()
cm = CoordinateMap(map, incs, outcs, inv)
recm = reorder_input(cm, 'jki')
yield assert_equal, recm.input_coords.coord_names, ('j', 'k', 'i')
yield assert_equal, recm.output_coords.coord_names, outcs.coord_names
yield assert_equal, recm.input_coords.name, incs.name+'-reordered'
yield assert_equal, recm.output_coords.name, outcs.name
# default reverse reorder
recm = reorder_input(cm)
yield assert_equal, recm.input_coords.coord_names, ('k', 'j', 'i')
# reorder with order as indices
recm = reorder_input(cm, [2,0,1])
yield assert_equal, recm.input_coords.coord_names, ('k', 'i', 'j')
def test_iter():
img = load_image(funcfile)
# flip to time first version so this makes sense
from nipy.core.reference.coordinate_map import reorder_input
arr = np.asarray(img).T
coordmap = reorder_input(img.coordmap)
img_t1 = Image(arr, coordmap)
slice_shape = (arr.shape[0],) + arr.shape[2:]
j = 0
for i, d in fmri_generator(img_t1):
j += 1
yield nose.tools.assert_equal, d.shape, slice_shape
del(i); gc.collect()
yield nose.tools.assert_equal, j, 3
