def test_ssb_rotate():
ctx = lt.Context(executor=InlineJobExecutor())
dtype = np.float64
scaling = 4
det = 45
shape = (29, 30, det, det)
# ? shape = np.random.uniform(1, 300, (4,1,))
# The acceleration voltage U in keV
U = 300
lamb = wavelength(U)
# STEM pixel size in m, here 50 STEM pixels on 0.5654 nm
dpix = 0.5654 / 50 * 1e-9
# STEM semiconvergence angle in radians
semiconv = 25e-3
# Diameter of the primary beam in the diffraction pattern in pixels
semiconv_pix = 78.6649 / scaling
cy = det // 2
cx = det // 2
input_data = (np.random.uniform(0, 1, np.prod(shape)) *
np.linspace(1.0, 1000.0, num=np.prod(shape)))
input_data = input_data.astype(np.float64).reshape(shape)
data_90deg = np.zeros_like(input_data)
# Rotate 90 degrees clockwise
for y in range(det):
for x in range(det):
data_90deg[:, :, x, det - 1 - y] = input_data[:, :, y, x]
udf = SSB_UDF(lamb=lamb,
dpix=dpix,
semiconv=semiconv,
semiconv_pix=semiconv_pix,
dtype=dtype,
cy=cy,
cx=cx,
transformation=rotate_deg(-90.))
dataset = MemoryDataSet(
data=data_90deg,
tileshape=(20, shape[2], shape[3]),
num_partitions=2,
sig_dims=2,
)
result = ctx.run_udf(udf=udf, dataset=dataset)
result_f, _ = reference_ssb(input_data,
U=U,
dpix=dpix,
semiconv=semiconv,
semiconv_pix=semiconv_pix,
cy=cy,
cx=cx)
assert np.allclose(result['pixels'].data, result_f)
def test_rotate_deg():
y, x = np.random.random((2, 7))
degrees = 23
r_y, r_x = c.rotate_deg(degrees) @ (y, x)
r_y2, r_x2 = rotate_deg(y, x, degrees)
assert np.allclose(r_y, r_y2)
assert np.allclose(r_x, r_x2)
def get_generic_results(self, img_sum, img_y, img_x):
ref_x = self.parameters["cx"]
ref_y = self.parameters["cy"]
y_centers_raw, x_centers_raw = center_shifts(img_sum, img_y, img_x, ref_y, ref_x)
shape = y_centers_raw.shape
if self.parameters["flip_y"]:
transform = flip_y()
else:
transform = identity()
# Transformations are applied right to left
transform = rotate_deg(self.parameters["scan_rotation"]) @ transform
y_centers, x_centers = transform @ (y_centers_raw.reshape(-1), x_centers_raw.reshape(-1))
y_centers = y_centers.reshape(shape)
x_centers = x_centers.reshape(shape)
if img_sum.dtype.kind == 'c':
x_real, x_imag = np.real(x_centers), np.imag(x_centers)
y_real, y_imag = np.real(y_centers), np.imag(y_centers)
return COMResultSet([
AnalysisResult(raw_data=x_real, visualized=visualize_simple(x_real),
key="x_real", title="x [real]", desc="x component of the center"),
AnalysisResult(raw_data=y_real, visualized=visualize_simple(y_real),
key="y_real", title="y [real]", desc="y component of the center"),
AnalysisResult(raw_data=x_imag, visualized=visualize_simple(x_imag),
key="x_imag", title="x [imag]", desc="x component of the center"),
AnalysisResult(raw_data=y_imag, visualized=visualize_simple(y_imag),
key="y_imag", title="y [imag]", desc="y component of the center"),
])
else:
f = CMAP_CIRCULAR_DEFAULT.rgb_from_vector((y_centers, x_centers))
d = divergence(y_centers, x_centers)
c = curl_2d(y_centers, x_centers)
m = magnitude(y_centers, x_centers)
return COMResultSet([
AnalysisResult(raw_data=(x_centers, y_centers), visualized=f,
key="field", title="field", desc="cubehelix colorwheel visualization",
include_in_download=False),
AnalysisResult(raw_data=m, visualized=visualize_simple(m),
key="magnitude", title="magnitude", desc="magnitude of the vector field"),
AnalysisResult(raw_data=d, visualized=visualize_simple(d),
key="divergence", title="divergence", desc="divergence of the vector field"),
AnalysisResult(raw_data=c, visualized=visualize_simple(c),
key="curl", title="curl", desc="curl of the 2D vector field"),
AnalysisResult(raw_data=x_centers, visualized=visualize_simple(x_centers),
key="x", title="x", desc="x component of the center"),
AnalysisResult(raw_data=y_centers, visualized=visualize_simple(y_centers),
key="y", title="y", desc="y component of the center"),
])
def test_transformation_rot90():
data_shape = np.random.randint(1, 77, 3, dtype=int)
data = np.random.random(data_shape)
source_shape = data_shape[1:]
target_shape = tuple(reversed(data_shape[1:]))
m = image_transformation_matrix(
source_shape=source_shape,
target_shape=target_shape,
affine_transformation=lambda x: x @ rotate_deg(90),
pre_transform=lambda x: x - np.array(target_shape) / 2 + 0.5,
post_transform=lambda x: np.round(x + np.array(source_shape) / 2 - 0.5
).astype(int))
res = apply_matrix(data, m, target_shape)
# positive rotations are clockwise, upper right corner
# is now lower right corner
assert np.allclose(data[:, 0, -1], res[:, -1, -1])
# alternative rotation: transpose and flip
assert np.allclose(np.flip(np.transpose(data, axes=(0, 2, 1)), axis=2),
res)
def apply_correction(y_centers,
x_centers,
scan_rotation,
flip_y,
forward=True):
shape = y_centers.shape
if flip_y:
transform = coordinates.flip_y()
else:
transform = coordinates.identity()
# Transformations are applied right to left
transform = coordinates.rotate_deg(scan_rotation) @ transform
y_centers = y_centers.reshape(-1)
x_centers = x_centers.reshape(-1)
if not forward:
transform = np.linalg.inv(transform)
y_transformed, x_transformed = transform @ (y_centers, x_centers)
y_transformed = y_transformed.reshape(shape)
x_transformed = x_transformed.reshape(shape)
return (y_transformed, x_transformed)
def get_generic_results(self, img_sum, img_y, img_x, damage):
from libertem.viz import CMAP_CIRCULAR_DEFAULT, visualize_simple
ref_x = self.parameters["cx"]
ref_y = self.parameters["cy"]
y_centers_raw, x_centers_raw = center_shifts(img_sum, img_y, img_x,
ref_y, ref_x)
shape = y_centers_raw.shape
if self.parameters["flip_y"]:
transform = flip_y()
else:
transform = identity()
# Transformations are applied right to left
transform = rotate_deg(self.parameters["scan_rotation"]) @ transform
y_centers, x_centers = transform @ (y_centers_raw.reshape(-1),
x_centers_raw.reshape(-1))
y_centers = y_centers.reshape(shape)
x_centers = x_centers.reshape(shape)
if img_sum.dtype.kind == 'c':
x_real, x_imag = np.real(x_centers), np.imag(x_centers)
y_real, y_imag = np.real(y_centers), np.imag(y_centers)
return COMResultSet([
AnalysisResult(raw_data=x_real,
visualized=visualize_simple(x_real,
damage=damage),
key="x_real",
title="x [real]",
desc="x component of the center"),
AnalysisResult(raw_data=y_real,
visualized=visualize_simple(y_real,
damage=damage),
key="y_real",
title="y [real]",
desc="y component of the center"),
AnalysisResult(raw_data=x_imag,
visualized=visualize_simple(x_imag,
damage=damage),
key="x_imag",
title="x [imag]",
desc="x component of the center"),
AnalysisResult(raw_data=y_imag,
visualized=visualize_simple(y_imag,
damage=damage),
key="y_imag",
title="y [imag]",
desc="y component of the center"),
])
else:
damage = damage & np.isfinite(x_centers) & np.isfinite(y_centers)
# Make sure that an all-False `damage` is handled since np.max()
# trips on an empty array.
# As a remark -- the NumPy error message
# "zero-size array to reduction operation maximum which has no identity"
# is probably wrong since -np.inf is the identity element for maximum on
# floating point numbers and should be returned here.
if np.count_nonzero(damage) > 0:
vmax = np.sqrt(
np.max(x_centers[damage]**2 + y_centers[damage]**2))
else:
vmax = 1
f = CMAP_CIRCULAR_DEFAULT.rgb_from_vector(
(x_centers, y_centers, 0), vmax=vmax)
d = divergence(y_centers, x_centers)
c = curl_2d(y_centers, x_centers)
m = magnitude(y_centers, x_centers)
return COMResultSet([
AnalysisResult(raw_data=(x_centers, y_centers),
visualized=f,
key="field",
title="field",
desc="cubehelix colorwheel visualization",
include_in_download=False),
AnalysisResult(raw_data=m,
visualized=visualize_simple(m, damage=damage),
key="magnitude",
title="magnitude",
desc="magnitude of the vector field"),
AnalysisResult(raw_data=d,
visualized=visualize_simple(d, damage=damage),
key="divergence",
title="divergence",
desc="divergence of the vector field"),
AnalysisResult(raw_data=c,
visualized=visualize_simple(c, damage=damage),
key="curl",
title="curl",
desc="curl of the 2D vector field"),
AnalysisResult(raw_data=x_centers,
visualized=visualize_simple(x_centers,
damage=damage),
key="x",
title="x",
desc="x component of the center"),
AnalysisResult(raw_data=y_centers,
visualized=visualize_simple(y_centers,
damage=damage),
key="y",
title="y",
desc="y component of the center"),
])