def test_stride():
arr_in = np.arange(4 * 4 * 3).reshape((4, 4, 3)).astype(DTYPE)
arr_fb = np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb, stride=2)
assert arr_out.shape == (1, 1, 5)
def test_stride():
arr_in = np.arange(4*4*3).reshape((4, 4, 3)).astype(DTYPE)
arr_fb = np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb, stride=2)
assert arr_out.shape == (1, 1, 5)
def test_constant_arr_in_arange_fb():
a = 0.987
inh, inw, ind = 6, 7, 4
fbh, fbw, fbd, fn = 2, 3, 4, 4
arr_in = a * np.ones(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.arange(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = a * fbh * fbw * ind
beta = 0.5 * (fn * (ind - 1)
+ fn * ind * (fbw - 1)
+ fn * ind * fbw * (fbh - 1))
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for k in xrange(outd):
ref[:, :, k] = alpha * (k + beta)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_arange_arr_in_and_fb():
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 1, 5, 3, 8
arr_in = np.arange(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.arange(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = 0.5 * fbh * fbw * ind
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
for k in xrange(outd):
ref[i, j, k] = alpha * (
1. / 3. * (3 * i + 2 * fbh - 1) *
(inw * ind ** 2 * fn * fbw * (fbh - 1)) \
+ ind * inw * (2 * i + fbh - 1) *
(0.5 * ind * fn * (fbw - 1) + \
0.5 * fn * (ind - 1) + k) \
+ 1. / 3. * (3 * j + 2 * fbw - 1) *
(ind ** 2 * fn * (fbw - 1)) \
+ ind * (2 * j + fbw - 1) *
(0.5 * ind * fn * fbw * (fbh - 1) + 0.5 * fn *
(ind - 1) + k) \
+ fn * (ind - 1) *
(0.5 * fbw * (fbh - 1) + 0.5 * ind * (fbw - 1) \
+ 1. / 3. * (2 * ind - 1)) + (ind - 1) * k)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_arange_arr_in_and_fb():
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 1, 5, 3, 8
arr_in = np.arange(inh * inw * ind).reshape((inh, inw, ind)).astype(DTYPE)
arr_fb = np.arange(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = 0.5 * fbh * fbw * ind
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
for k in xrange(outd):
ref[i, j, k] = alpha * (
1. / 3. * (3 * i + 2 * fbh - 1) *
(inw * ind ** 2 * fn * fbw * (fbh - 1)) \
+ ind * inw * (2 * i + fbh - 1) *
(0.5 * ind * fn * (fbw - 1) + \
0.5 * fn * (ind - 1) + k) \
+ 1. / 3. * (3 * j + 2 * fbw - 1) *
(ind ** 2 * fn * (fbw - 1)) \
+ ind * (2 * j + fbw - 1) *
(0.5 * ind * fn * fbw * (fbh - 1) + 0.5 * fn *
(ind - 1) + k) \
+ fn * (ind - 1) *
(0.5 * fbw * (fbh - 1) + 0.5 * ind * (fbw - 1) \
+ 1. / 3. * (2 * ind - 1)) + (ind - 1) * k)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_max_filter_size():
a = 1.23
arr_in = np.arange(4 * 4 * 3).reshape((4, 4, 3)).astype(DTYPE)
arr_fb = a * np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert arr_out.shape == (1, 2, 5)
def test_input_d_1():
arr_in = np.zeros((2, 3, 1), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 1, 4), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
gt = np.array([[[0., 0., 0., 0.], [0., 1., 2., 3.], [0., 2., 4., 6.]],
[[0., 3., 6., 9.], [0., 4., 8., 12.], [0., 5., 10., 15.]]],
dtype=DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
def test_max_filter_size():
a = 1.23
arr_in = np.arange(4*4*3).reshape((4, 4, 3)).astype(DTYPE)
arr_fb = a * np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert arr_out.shape == (1, 2, 5)
def test_one_dot():
arr_in = np.zeros((3, 3, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4, 8), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
gt = np.array([[[ 119280., 119910., 120540., 121170.,
121800., 122430., 123060., 123690.]]],
dtype=DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
def test_one_dot():
arr_in = np.zeros((3, 3, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4, 8), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
gt = np.array([[[
119280., 119910., 120540., 121170., 121800., 122430., 123060., 123690.
]]],
dtype=DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
def test_input_d_1():
arr_in = np.zeros((2, 3, 1), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 1, 4), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
gt = np.array([[[ 0., 0., 0., 0.],
[ 0., 1., 2., 3.],
[ 0., 2., 4., 6.]],
[[ 0., 3., 6., 9.],
[ 0., 4., 8., 12.],
[ 0., 5., 10., 15.]]], dtype=DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
arr_out = fbcorr3(arr_in, arr_fb)
assert_allclose(arr_out, gt, rtol=RTOL, atol=ATOL)
def test_smoke_stride():
np.random.seed(42)
arr_in = np.random.randn(4, 4, 3).astype(DTYPE)
arr_fb = np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
idx = (0, 1, 3)
ref = -2.80072999
res = arr_out[idx]
assert (ref - res) < ATOL
def test_smoke_stride():
np.random.seed(42)
arr_in = np.random.randn(4, 4, 3).astype(DTYPE)
arr_fb = np.ones((4, 3, 3, 5)).astype(DTYPE)
arr_out = fbcorr3(arr_in, arr_fb)
idx = (0, 1, 3)
ref = -2.80072999
res = arr_out[idx]
assert (ref - res) < ATOL
def test_arr_out_3d():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 4, 8), dtype=DTYPE)
arr_out = np.zeros((20, 30, 8), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
idx = [2, 3], [10, 12]
gt = np.zeros((len(idx), arr_out.shape[-1]), dtype=DTYPE)
for i in xrange(gt.shape[0]):
for k in xrange(gt.shape[1]):
gt[i, k] = get_fbcorr_element(arr_in, arr_fb, idx[0][i], idx[1][i],
k)
arr_out = fbcorr3(arr_in, arr_fb)
gv = arr_out[idx]
assert_allclose(gv, gt, rtol=RTOL, atol=ATOL)
def test_arr_out_3d():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 4, 8), dtype=DTYPE)
arr_out = np.zeros((20, 30, 8), dtype=DTYPE)
arr_in[:] = np.arange(np.prod(arr_in.shape)).reshape(arr_in.shape)
arr_fb[:] = np.arange(np.prod(arr_fb.shape)).reshape(arr_fb.shape)
idx = [2, 3], [10, 12]
gt = np.zeros((len(idx), arr_out.shape[-1]), dtype=DTYPE)
for i in xrange(gt.shape[0]):
for k in xrange(gt.shape[1]):
gt[i, k] = get_fbcorr_element(arr_in, arr_fb,
idx[0][i], idx[1][i], k)
arr_out = fbcorr3(arr_in, arr_fb)
gv = arr_out[idx]
assert_allclose(gv, gt, rtol=RTOL, atol=ATOL)
def test_random_arr_in_and_arr_fb():
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 3, 5, 3, 8
arr_in = np.random.randn(inh * inw * ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.random.randn(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
for k in xrange(outd):
ref[i, j, k] = get_fbcorr_element(arr_in, arr_fb, i, j, k)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_constant_arr_in_random_arr_fb():
a = 4.827
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 3, 5, 3, 8
arr_in = a * np.ones(inh * inw * ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.random.randn(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for k in xrange(arr_fb.shape[-1]):
constant = a * arr_fb[..., k].sum()
ref[..., k] = constant
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_constant_arr_in_random_arr_fb():
a = 4.827
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 3, 5, 3, 8
arr_in = a * np.ones(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.random.randn(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for k in xrange(arr_fb.shape[-1]):
constant = a * arr_fb[..., k].sum()
ref[..., k] = constant
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_random_arr_in_and_arr_fb():
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 3, 5, 3, 8
arr_in = np.random.randn(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.random.randn(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
for k in xrange(outd):
ref[i, j, k] = get_fbcorr_element(arr_in, arr_fb,
i, j, k)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_constant_arr_in_and_fb():
a = 1.234
b = 2.345
inh, inw, ind = 4, 5, 6
fbh, fbw, fbd, fn = 2, 2, 6, 4
arr_in = a * np.ones(inh * inw * ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = b * np.ones(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
constant = a * b * fbh * fbw * fbd
ref = constant * np.ones(outh * outw * outd).reshape(
(outh, outw, outd)).astype(DTYPE)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_constant_arr_in_and_fb():
a = 1.234
b = 2.345
inh, inw, ind = 4, 5, 6
fbh, fbw, fbd, fn = 2, 2, 6, 4
arr_in = a * np.ones(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = b * np.ones(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
constant = a * b * fbh * fbw * fbd
ref = constant * np.ones(outh*outw*outd).reshape(
(outh, outw, outd)).astype(DTYPE)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_arange_arr_in_constant_fb():
b = 2.345
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 1, 5, 3, 8
arr_in = np.arange(inh * inw * ind).reshape((inh, inw, ind)).astype(DTYPE)
arr_fb = b * np.ones(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = 0.5 * b * fbh * fbw * ind
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
ref[i, j, :] = alpha * (ind - 1 + ind *
(2 * j + fbw - 1) + ind * inw *
(2 * i + fbh - 1))
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_arange_arr_in_constant_fb():
b = 2.345
inh, inw, ind = 8, 7, 3
fbh, fbw, fbd, fn = 1, 5, 3, 8
arr_in = np.arange(inh*inw*ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = b * np.ones(fbh*fbw*fbd*fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = 0.5 * b * fbh * fbw * ind
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for i in xrange(outh):
for j in xrange(outw):
ref[i, j, :] = alpha * (ind - 1
+ ind * (2 * j + fbw - 1)
+ ind * inw * (2 * i + fbh - 1))
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def test_constant_arr_in_arange_fb():
a = 0.987
inh, inw, ind = 6, 7, 4
fbh, fbw, fbd, fn = 2, 3, 4, 4
arr_in = a * np.ones(inh * inw * ind).reshape(
(inh, inw, ind)).astype(DTYPE)
arr_fb = np.arange(fbh * fbw * fbd * fn).reshape(
(fbh, fbw, fbd, fn)).astype(DTYPE)
outh, outw, outd = (inh - fbh + 1), (inw - fbw + 1), fn
alpha = a * fbh * fbw * ind
beta = 0.5 * (fn * (ind - 1) + fn * ind * (fbw - 1) + fn * ind * fbw *
(fbh - 1))
ref = np.zeros((outh, outw, outd), dtype=DTYPE)
for k in xrange(outd):
ref[:, :, k] = alpha * (k + beta)
res = fbcorr3(arr_in, arr_fb)
assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
def _get_feature_map(self, tmp_in,
layer_idx, op_idx, kwargs,
op_params, op_name):
if op_name == 'lnorm':
inker_shape = kwargs['inker_shape']
outker_shape = kwargs['outker_shape']
remove_mean = kwargs['remove_mean']
stretch = kwargs['stretch']
threshold = kwargs['threshold']
# SLM PLoS09 / FG11 constraints:
assert inker_shape == outker_shape
tmp_out = lcdnorm3(tmp_in, inker_shape,
contrast=remove_mean,
stretch=stretch,
threshold=threshold)
elif op_name == 'fbcorr':
max_out = kwargs['max_out']
min_out = kwargs['min_out']
fbkey = layer_idx, op_idx
if fbkey not in self.filterbanks:
initialize = op_params['initialize']
if isinstance(initialize, np.ndarray):
fb = initialize
if len(fb.shape) == 3:
fb = fb[..., np.newaxis]
else:
filter_shape = list(initialize['filter_shape'])
generate = initialize['generate']
n_filters = initialize['n_filters']
fb_shape = [n_filters] + filter_shape + [tmp_in.shape[-1]]
# generate filterbank data
method_name, method_kwargs = generate
assert method_name == 'random:uniform'
rseed = method_kwargs.get('rseed', None)
rng = np.random.RandomState(rseed)
fb = rng.uniform(size=fb_shape)
for fidx in xrange(n_filters):
filt = fb[fidx]
# zero-mean, unit-l2norm
filt -= filt.mean()
filt_norm = np.linalg.norm(filt)
assert filt_norm != 0
filt /= filt_norm
fb[fidx] = filt
fb = np.ascontiguousarray(np.rollaxis(fb, 0, 4)).astype(DTYPE)
self.filterbanks[fbkey] = fb
print fb.shape
fb = self.filterbanks[fbkey]
# -- filter
assert tmp_in.dtype == np.float32
tmp_out = fbcorr3(tmp_in, fb)
# -- activation
min_out = -np.inf if min_out is None else min_out
max_out = +np.inf if max_out is None else max_out
# insure that the type is right before calling numexpr
min_out = np.array([min_out], dtype=tmp_in.dtype)
max_out = np.array([max_out], dtype=tmp_in.dtype)
# call numexpr
tmp_out = ne.evaluate('where(tmp_out < min_out, min_out, tmp_out)')
tmp_out = ne.evaluate('where(tmp_out > max_out, max_out, tmp_out)')
assert tmp_out.dtype == tmp_in.dtype
elif op_name == 'lpool':
ker_shape = kwargs['ker_shape']
order = kwargs['order']
stride = kwargs['stride']
tmp_out = lpool3(tmp_in, ker_shape, order=order, stride=stride)
else:
raise ValueError("operation '%s' not understood" % op_name)
assert tmp_out.dtype == tmp_in.dtype
assert tmp_out.dtype == np.float32
return tmp_out
def test_error_arr_in_ndim():
arr_in = np.zeros((1, 4, 4, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 4, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_d_too_large():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 5, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_wrong_dtype():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 5, 8), dtype='float64')
fbcorr3(arr_in, arr_fb)
def test_error_too_few_filters():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4, 1), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_w_too_big():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 31, 4, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_in_ndim():
arr_in = np.zeros((1, 4, 4, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 4, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_ndim():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_ndim():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_too_few_filters():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((3, 3, 4, 1), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_w_too_big():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 31, 4, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_d_too_large():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 5, 8), dtype=DTYPE)
fbcorr3(arr_in, arr_fb)
def test_error_arr_fb_wrong_dtype():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
arr_fb = np.zeros((1, 1, 5, 8), dtype='float64')
fbcorr3(arr_in, arr_fb)
