def create_dataset(self, dataset_file):
"""Create a dataset for testing this module.
Only called with setUp detects that `dataset_file` has been deleted.
"""
import libimage
amplitude = libimage.load("cryptomeria", 128)
phase = libimage.load("bombus", 128)
original = amplitude * np.exp(1j * phase * np.pi)
self.original = np.expand_dims(original, axis=0).astype('complex64')
np.random.seed(0)
self.flow = np.empty((*self.original.shape, 2), dtype='float32')
self.flow[..., :] = 5 * (np.random.rand(2) - 0.5)
self.shift = 2 * (np.random.rand(*self.original.shape[:-2], 2) - 0.5)
self.data = tike.align.simulate(
original=self.original,
flow=self.flow,
shift=self.shift,
padded_shape=None,
angle=None,
)
setup_data = [
self.data,
self.original,
self.flow,
self.shift,
]
with lzma.open(dataset_file, 'wb') as file:
pickle.dump(setup_data, file)
def test_image(self, s=32, ntheta=16 * 16 * 16):
import libimage
import matplotlib.pyplot as plt
f = libimage.load('satyre', s)
f = np.tile(f, (s, 1, 1))
f = self.xp.asarray(f, dtype='complex64')
x = [
g.ravel() for g in np.meshgrid(
np.linspace(-0.5, 0.5, s),
np.linspace(-0.5, 0.5, s),
np.linspace(-0.5, 0.5, s),
)
]
x = np.stack(x, -1)
print(x.shape)
x = self.xp.asarray(x, dtype='float32')
d = self.operator.fwd(f, x, s)
m = self.operator.adj(d, x, s)
plt.figure()
plt.imshow(m[s // 2].real.get())
plt.figure()
plt.imshow(f[s // 2].real.get())
plt.show()
def debug_show(self):
import libimage
import matplotlib.pyplot as plt
x = self.xp.asarray(libimage.load('coins', 256), dtype='complex64')
y = self.operator.fwd(x[None], 4 * np.pi)
print(x.shape, y.shape)
plt.figure()
plt.imshow(x.real.get())
plt.figure()
plt.imshow(y[0].real.get())
plt.show()
def create_dataset(
self,
dataset_file,
pw=16,
eigen=1,
width=128,
):
"""Create a dataset for testing this module.
Only called with setUp detects that `dataset_file` has been deleted.
"""
import libimage
# Create a stack of phase-only images
phase = np.stack(
[libimage.load('satyre', width),
libimage.load('satyre', width)],
axis=0,
)
amplitude = np.stack(
[
1 - 0 * libimage.load('coins', width),
1 - libimage.load('coins', width)
],
axis=0,
)
original = amplitude * np.exp(1j * phase * np.pi)
self.original = original.astype('complex64')
leading = self.original.shape[:-2]
# Create a multi-probe with gaussian amplitude decreasing as 1/N
phase = np.stack(
[
1 - libimage.load('cryptomeria', pw),
1 - libimage.load('bombus', pw)
],
axis=0,
)
weights = 1.0 / np.arange(1, len(phase) + 1)[:, None, None]
weights = weights * tike.ptycho.probe.gaussian(pw, rin=0.8, rout=1.0)
probe = weights * np.exp(1j * phase * np.pi)
self.probe = np.tile(
probe.astype('complex64'),
(*leading, 1, eigen, 1, 1, 1),
)
pad = 2
v, h = np.meshgrid(
np.linspace(pad, original.shape[-2] - pw - pad, 13, endpoint=True),
np.linspace(pad, original.shape[-1] - pw - pad, 13, endpoint=True),
indexing='ij',
)
scan = np.stack((np.ravel(v), np.ravel(h)), axis=1)
self.scan = np.tile(
scan.astype('float32'),
(*leading, 1, 1),
)
self.data = tike.ptycho.simulate(
detector_shape=pw * 2,
probe=self.probe,
scan=self.scan,
psi=self.original,
)
assert self.data.shape == (*leading, 13 * 13, pw * 2, pw * 2)
assert self.data.dtype == 'float32', self.data.dtype
setup_data = [
self.data,
self.scan,
self.probe,
self.original,
]
with lzma.open(dataset_file, 'wb') as file:
pickle.dump(setup_data, file)