def get_roi_center(roi_native_path, roi_mni_path):
"""Get ROI center of mass.
Get back coordinate in img space and in coordinate space.
Also actual center of mass.
"""
# computations in native space
if type(roi_native_path) is str:
img = nib.load(roi_native_path)
else:
img = roi_native_path
data = img.get_data()
data = as_ndarray(data)
my_map = data.copy()
center_coords = ndimage.center_of_mass(np.abs(my_map))
x_map, y_map, z_map = center_coords[:3]
native_coords = np.asarray(
coord_transform(x_map, y_map, z_map, img.get_affine())).tolist()
voxel = [round(x) for x in center_coords]
# computations in mni space
if type(roi_mni_path) is str:
img = nib.load(roi_mni_path)
else:
img = roi_mni_path
data = img.get_data()
data = as_ndarray(data)
my_map = data.copy()
mni_center_coords = ndimage.center_of_mass(np.abs(my_map))
x_map, y_map, z_map = mni_center_coords[:3]
mni_coords = np.asarray(
coord_transform(x_map, y_map, z_map, img.get_affine())).tolist()
# returns voxel and true center mass coords
# returns also native and mni space coords
return (voxel[:3], center_coords[:3], [round(x) for x in native_coords],
[round(x) for x in mni_coords])
def get_roi_center(roi_native_path, roi_mni_path):
"""Get ROI center of mass.
Get back coordinate in img space and in coordinate space.
Also actual center of mass.
"""
# computations in native space
if type(roi_native_path) is str:
img = nib.load(roi_native_path)
else:
img = roi_native_path
data = img.get_data()
data = as_ndarray(data)
my_map = data.copy()
center_coords = ndimage.center_of_mass(np.abs(my_map))
x_map, y_map, z_map = center_coords[:3]
native_coords = np.asarray(coord_transform(x_map, y_map, z_map,
img.get_affine())).tolist()
voxel = [round(x) for x in center_coords]
# computations in mni space
if type(roi_mni_path) is str:
img = nib.load(roi_mni_path)
else:
img = roi_mni_path
data = img.get_data()
data = as_ndarray(data)
my_map = data.copy()
mni_center_coords = ndimage.center_of_mass(np.abs(my_map))
x_map, y_map, z_map = mni_center_coords[:3]
mni_coords = np.asarray(coord_transform(x_map, y_map, z_map,
img.get_affine())).tolist()
# returns voxel and true center mass coords
# returns also native and mni space coords
return (voxel[:3], center_coords[:3], [round(x) for x in native_coords],
[round(x) for x in mni_coords])
def test_as_ndarray():
# All test cases
# input dtype, input order, should copy, output dtype, output order, copied
test_cases = [
# no-op
(np.float, "C", False, None, None, False),
(np.float, "F", False, None, None, False),
# simple copy
(np.float, "C", True, None, None, True),
(np.float, "F", True, None, None, True),
# dtype provided, identical
(np.float, "C", False, np.float, None, False),
(np.float, "F", False, np.float, None, False),
# dtype changed
(np.float, "C", False, np.float32, None, True),
(np.float, "F", False, np.float32, None, True),
# dtype and order provided, but identical
(np.float, "C", False, np.float, "C", False),
(np.float, "F", False, np.float, "F", False),
# order provided, unchanged
(np.float, "C", False, None, "C", False),
(np.float, "F", False, None, "F", False),
(np.float, "C", True, None, "C", True),
(np.float, "F", True, None, "F", True),
# order provided, changed
(np.float, "C", False, None, "F", True),
(np.float, "F", False, None, "C", True),
(np.float, "C", True, None, "F", True),
(np.float, "F", True, None, "C", True),
# Special case for int8 <-> bool conversion.
(np.int8, "C", False, np.bool, None, False),
(np.int8, "F", False, np.bool, None, False),
(np.int8, "C", False, np.bool, "C", False),
(np.int8, "F", False, np.bool, "F", False),
(np.int8, "C", False, np.bool, "F", True),
(np.int8, "F", False, np.bool, "C", True),
(np.int8, "C", True, np.bool, None, True),
(np.int8, "F", True, np.bool, None, True),
(np.int8, "C", True, np.bool, "C", True),
(np.int8, "F", True, np.bool, "F", True),
(np.bool, "C", False, np.int8, None, False),
(np.bool, "F", False, np.int8, None, False),
(np.bool, "C", False, np.int8, "C", False),
(np.bool, "F", False, np.int8, "F", False),
(np.bool, "C", False, np.int8, "F", True),
(np.bool, "F", False, np.int8, "C", True),
(np.bool, "C", True, np.int8, None, True),
(np.bool, "F", True, np.int8, None, True),
(np.bool, "C", True, np.int8, "C", True),
(np.bool, "F", True, np.int8, "F", True),
]
shape = (10, 11)
for case in test_cases:
in_dtype, in_order, copy, out_dtype, out_order, copied = case
arr1 = np.ones(shape, dtype=in_dtype, order=in_order)
arr2 = as_ndarray(arr1,
copy=copy, dtype=out_dtype, order=out_order)
assert_true(not are_arrays_identical(arr1[0], arr2[0]) == copied,
msg=str(case))
if out_dtype is None:
assert_true(arr2.dtype == in_dtype, msg=str(case))
else:
assert_true(arr2.dtype == out_dtype, msg=str(case))
result_order = out_order if out_order is not None else in_order
if result_order == "F":
assert_true(arr2.flags["F_CONTIGUOUS"], msg=str(case))
else:
assert_true(arr2.flags["C_CONTIGUOUS"], msg=str(case))
## memmap
filename = os.path.join(os.path.dirname(__file__), "data", "mmap.dat")
# same dtype, no copy requested
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(5,))
arr2 = as_ndarray(arr1)
assert(not are_arrays_identical(arr1, arr2))
# same dtype, copy requested
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(5,))
arr2 = as_ndarray(arr1, copy=True)
assert(not are_arrays_identical(arr1, arr2))
# different dtype
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(5,))
arr2 = as_ndarray(arr1, dtype=np.int)
assert(arr2.dtype == np.int)
assert(not are_arrays_identical(arr1, arr2))
# same dtype, explicitly provided: must copy
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(5,))
arr2 = as_ndarray(arr1, dtype=np.float32)
assert(arr2.dtype == np.float32)
assert(not are_arrays_identical(arr1, arr2))
# same dtype, order provided
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(10, 10))
arr2 = as_ndarray(arr1, order="F")
assert(arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert(arr2.dtype == arr1.dtype)
assert(not are_arrays_identical(arr1[0], arr2[0]))
# same dtype, order unchanged but provided
arr1 = np.memmap(filename, dtype='float32', mode='w+',
shape=(10, 10), order="F")
arr2 = as_ndarray(arr1, order="F")
assert(arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert(arr2.dtype == arr1.dtype)
assert(not are_arrays_identical(arr1[0], arr2[0]))
# dtype and order specified
arr1 = np.memmap(filename, dtype='float32', mode='w+',
shape=(10, 10), order="F")
arr2 = as_ndarray(arr1, order="F", dtype=np.int32)
assert(arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert(arr2.dtype == np.int32)
assert(not are_arrays_identical(arr1[0], arr2[0]))
## list
# same dtype, no copy requested
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1)
assert(not are_arrays_identical(arr1, arr2))
# same dtype, copy requested
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1, copy=True)
assert(not are_arrays_identical(arr1, arr2))
# different dtype
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1, dtype=np.float)
assert(arr2.dtype == np.float)
assert(not are_arrays_identical(arr1, arr2))
# order specified
arr1 = [[0, 1, 2, 3], [0, 1, 2, 3]]
arr2 = as_ndarray(arr1, dtype=np.float, order="F")
assert(arr2.dtype == np.float)
assert(arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert(not are_arrays_identical(arr1[0], arr2[0]))
## Unhandled cases
assert_raises(ValueError, as_ndarray, "test string")
assert_raises(ValueError, as_ndarray, [], order="invalid")
def test_as_ndarray():
# All test cases
# input dtype, input order, should copy, output dtype, output order, copied
test_cases = [
# no-op
(np.float, "C", False, None, None, False),
(np.float, "F", False, None, None, False),
# simple copy
(np.float, "C", True, None, None, True),
(np.float, "F", True, None, None, True),
# dtype provided, identical
(np.float, "C", False, np.float, None, False),
(np.float, "F", False, np.float, None, False),
# dtype changed
(np.float, "C", False, np.float32, None, True),
(np.float, "F", False, np.float32, None, True),
# dtype and order provided, but identical
(np.float, "C", False, np.float, "C", False),
(np.float, "F", False, np.float, "F", False),
# order provided, unchanged
(np.float, "C", False, None, "C", False),
(np.float, "F", False, None, "F", False),
(np.float, "C", True, None, "C", True),
(np.float, "F", True, None, "F", True),
# order provided, changed
(np.float, "C", False, None, "F", True),
(np.float, "F", False, None, "C", True),
(np.float, "C", True, None, "F", True),
(np.float, "F", True, None, "C", True),
# Special case for int8 <-> bool conversion.
(np.int8, "C", False, np.bool, None, False),
(np.int8, "F", False, np.bool, None, False),
(np.int8, "C", False, np.bool, "C", False),
(np.int8, "F", False, np.bool, "F", False),
(np.int8, "C", False, np.bool, "F", True),
(np.int8, "F", False, np.bool, "C", True),
(np.int8, "C", True, np.bool, None, True),
(np.int8, "F", True, np.bool, None, True),
(np.int8, "C", True, np.bool, "C", True),
(np.int8, "F", True, np.bool, "F", True),
(np.bool, "C", False, np.int8, None, False),
(np.bool, "F", False, np.int8, None, False),
(np.bool, "C", False, np.int8, "C", False),
(np.bool, "F", False, np.int8, "F", False),
(np.bool, "C", False, np.int8, "F", True),
(np.bool, "F", False, np.int8, "C", True),
(np.bool, "C", True, np.int8, None, True),
(np.bool, "F", True, np.int8, None, True),
(np.bool, "C", True, np.int8, "C", True),
(np.bool, "F", True, np.int8, "F", True),
]
shape = (10, 11)
for case in test_cases:
in_dtype, in_order, copy, out_dtype, out_order, copied = case
arr1 = np.ones(shape, dtype=in_dtype, order=in_order)
arr2 = as_ndarray(arr1, copy=copy, dtype=out_dtype, order=out_order)
assert_true(not are_arrays_identical(arr1[0], arr2[0]) == copied,
msg=str(case))
if out_dtype is None:
assert_true(arr2.dtype == in_dtype, msg=str(case))
else:
assert_true(arr2.dtype == out_dtype, msg=str(case))
result_order = out_order if out_order is not None else in_order
if result_order == "F":
assert_true(arr2.flags["F_CONTIGUOUS"], msg=str(case))
else:
assert_true(arr2.flags["C_CONTIGUOUS"], msg=str(case))
# memmap
filename = os.path.join(os.path.dirname(__file__), "data", "mmap.dat")
# same dtype, no copy requested
arr1 = np.memmap(filename, dtype='float32', mode='w+', shape=(5, ))
arr2 = as_ndarray(arr1)
assert (not are_arrays_identical(arr1, arr2))
# same dtype, copy requested
arr1 = np.memmap(filename, dtype='float32', mode='readwrite', shape=(5, ))
arr2 = as_ndarray(arr1, copy=True)
assert (not are_arrays_identical(arr1, arr2))
# different dtype
arr1 = np.memmap(filename, dtype='float32', mode='readwrite', shape=(5, ))
arr2 = as_ndarray(arr1, dtype=np.int)
assert (arr2.dtype == np.int)
assert (not are_arrays_identical(arr1, arr2))
# same dtype, explicitly provided: must copy
arr1 = np.memmap(filename, dtype='float32', mode='readwrite', shape=(5, ))
arr2 = as_ndarray(arr1, dtype=np.float32)
assert (arr2.dtype == np.float32)
assert (not are_arrays_identical(arr1, arr2))
# same dtype, order provided
arr1 = np.memmap(filename,
dtype='float32',
mode='readwrite',
shape=(10, 10))
arr2 = as_ndarray(arr1, order="F")
assert (arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert (arr2.dtype == arr1.dtype)
assert (not are_arrays_identical(arr1[0], arr2[0]))
# same dtype, order unchanged but provided
arr1 = np.memmap(filename,
dtype='float32',
mode='readwrite',
shape=(10, 10),
order="F")
arr2 = as_ndarray(arr1, order="F")
assert (arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert (arr2.dtype == arr1.dtype)
assert (not are_arrays_identical(arr1[0], arr2[0]))
# dtype and order specified
arr1 = np.memmap(filename,
dtype='float32',
mode='readwrite',
shape=(10, 10),
order="F")
arr2 = as_ndarray(arr1, order="F", dtype=np.int32)
assert (arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert (arr2.dtype == np.int32)
assert (not are_arrays_identical(arr1[0], arr2[0]))
# list
# same dtype, no copy requested
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1)
assert (not are_arrays_identical(arr1, arr2))
# same dtype, copy requested
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1, copy=True)
assert (not are_arrays_identical(arr1, arr2))
# different dtype
arr1 = [0, 1, 2, 3]
arr2 = as_ndarray(arr1, dtype=np.float)
assert (arr2.dtype == np.float)
assert (not are_arrays_identical(arr1, arr2))
# order specified
arr1 = [[0, 1, 2, 3], [0, 1, 2, 3]]
arr2 = as_ndarray(arr1, dtype=np.float, order="F")
assert (arr2.dtype == np.float)
assert (arr2.flags["F_CONTIGUOUS"] and not arr2.flags["C_CONTIGUOUS"])
assert (not are_arrays_identical(arr1[0], arr2[0]))
# Unhandled cases
assert_raises(ValueError, as_ndarray, "test string")
assert_raises(ValueError, as_ndarray, [], order="invalid")
