def test_transforms_correctly_with_polarization_rotation(self):
# We test that rotating the lab frame correctly rotates
# the polarization.
# If we rotate (x0, y0) -> (y1, -x1), then the polarization
# in the new coordinates should be
# E1x = E0y, E1y = -E1x
scatterer = sphere
medium_wavevec = 2 * np.pi / wavelen
medium_index = index
theory = MieLens()
krho = np.linspace(0, 100, 11)
phi_0 = 0 * krho + np.pi / 180.0 # a small component along y
phi_1 = phi_0 - np.pi / 2
kz = np.full_like(krho, 20.0)
pol_0 = xr.DataArray([1.0, 0, 0])
pos_0 = np.array([krho, phi_0, kz])
pol_1 = xr.DataArray([0, -1.0, 0])
pos_1 = np.array([krho, phi_1, kz])
args = (scatterer, medium_wavevec, medium_index)
fields_0 = theory._raw_fields(pos_0, *args, pol_0)
fields_1 = theory._raw_fields(pos_1, *args, pol_1)
self.assertTrue(np.allclose(fields_1[0], fields_0[1], **TOLS))
self.assertTrue(np.allclose(fields_1[1], -fields_0[0], **TOLS))
def _get_theory_and_scaling(self, params):
if self.theory == 'mielens':
theory = MieLens(lens_angle=params['lens_angle']) # 0.0015 ms
scaling = 1.0
elif self.theory == 'mieonly':
theory = Mie()
scaling = params['alpha']
elif self.theory == 'mielensalpha':
theory = MieLens(lens_angle=params['lens_angle']) # 0.0015 ms
scaling = params['alpha']
return theory, scaling
def test_calculate_scattered_field_lensmie_same_as_mielens(self):
detector = test_common.xschema_lens
scatterer = test_common.sphere
medium_wavevec = 2 * np.pi / test_common.wavelen
medium_index = test_common.index
illum_polarization = test_common.xpolarization
theory_old = MieLens(lens_angle=LENS_ANGLE)
theory_new = LENSMIE
fields_old = theory_old.calculate_scattered_field(scatterer, detector)
fields_new = theory_new.calculate_scattered_field(scatterer, detector)
assert_allclose(fields_old, fields_new, atol=5e-3)
def test_holopy_hologram_equal_to_exact_calculation(self):
# Checks that phase shifts and wrappers for mielens are correct
theory_mielens = MieLens()
illum_wavelength = 0.66 # 660 nm red light
k = 2 * np.pi / illum_wavelength
center = (10, 10, 5.)
kwargs = {'particle_kz': center[2] * k,
'index_ratio': 1.2,
'size_parameter': 0.5 * k,
'lens_angle': theory_mielens.lens_angle}
detector = detector_grid(10, 2.0)
x = detector.x.values.reshape(-1, 1) - center[0]
y = detector.y.values.reshape(1, -1) - center[1]
rho = np.sqrt(x**2 + y**2)
phi = np.arctan2(y, x)
calculator = mielensfunctions.MieLensCalculator(**kwargs)
scatterer = Sphere(n=kwargs['index_ratio'],
r=kwargs['size_parameter'] / k,
center=center)
holo_calculate = calculator.calculate_total_intensity(k * rho, phi)
holo_holopy = calc_holo(
detector, scatterer, illum_wavelen=illum_wavelength,
medium_index=1., illum_polarization=(1, 0), theory=theory_mielens)
is_ok = np.allclose(holo_calculate, holo_holopy.values.squeeze(),
**TOLS)
self.assertTrue(is_ok)
def compare_fit_holo(data, fit_scatterer, fit_lens_angle):
guess_holo = hologram2array(
calc_holo(data,
fit_scatterer,
theory=MieLens(lens_angle=fit_lens_angle)))
data_holo = hologram2array(data)
compare_imgs(data_holo, guess_holo, ['Data', 'Model'])
def _forward(self, pars, detector):
"""
Compute a forward model (the hologram)
Parameters
-----------
pars: list
Values for each parameter used to compute the hologram. Ordering
is given by self._parameters
detector: xarray
dimensions of the resulting hologram. Metadata taken from
detector if not given explicitly when instantiating self.
"""
alpha = read_map(self._maps['model'], pars)['alpha']
optics_kwargs = self._find_optics(pars, detector)
scatterer = self._scatterer_from_parameters(pars)
theory_kwargs = read_map(self._maps['theory'], pars)
# FIXME would be nice to have access to the interpolator kwargs
theory = MieLens(**theory_kwargs)
try:
return calc_holo(detector,
scatterer,
theory=theory,
scaling=alpha,
**optics_kwargs)
except InvalidScatterer:
return -np.inf
def test_raises_error_if_multiple_z_values(self):
theory = MieLens()
np.random.seed(10)
positions = np.random.randn(3, 10) # the zs will differ by chance
self.assertRaises(
ValueError, theory._raw_fields, positions, sphere, 1.0, 1.33,
xschema.illum_polarization)
def calculate_models(data, fits):
fitholos = [
calc_holo(datum,
fit.scatterer,
theory=MieLens(lens_angle=fit.parameters['lens_angle']))
if fit is not None else 0 * datum + 1
for datum, fit in zip(data, fits)
]
return fitholos
def calc_model(cls, data, params, theory_type='mielens'):
scatterer = cls._make_scatterer(params)
if theory_type == 'mielens':
theory = MieLens(lens_angle=params['lens_angle'])
scaling = 1.0
else:
theory = Mie()
scaling = params['alpha']
model = calc_holo(data, scatterer, theory=theory, scaling=scaling)
return model
def test_raw_fields_similar_mielens_ypolarization(self):
detector = SMALL_DETECTOR
scatterer = test_common.sphere
medium_wavevec = 2 * np.pi / test_common.wavelen
medium_index = test_common.index
illum_polarization = xr.DataArray([0, 1.0, 0])
theory_old = MieLens(lens_angle=LENS_ANGLE)
pos_old = theory_old._transform_to_desired_coordinates(
detector, scatterer.center, wavevec=medium_wavevec)
theory_new = LENSMIE
pos_new = theory_new._transform_to_desired_coordinates(
detector, scatterer.center, wavevec=medium_wavevec)
args = (scatterer, medium_wavevec, medium_index, illum_polarization)
f0x, f0y, f0z = theory_old._raw_fields(pos_old, *args)
fx, fy, fz = theory_new._raw_fields(pos_new, *args)
assert_allclose(f0x, fx, atol=2e-3)
assert_allclose(f0y, fy, atol=2e-3)
assert_allclose(f0z, fz, atol=2e-3)
def test_can_calculate_for_positive_and_negative_z(self):
theory = MieLens()
ka = 5.0
radius = ka * wavelen * 0.5 / np.pi
sphere_index = 1.59
is_ok = []
for kz in [-50., 0., 50.]:
center = (0, 0, kz * wavelen * 0.5 / np.pi)
this_sphere = Sphere(n=sphere_index, r=radius, center=center)
holo = calc_holo(xschema, this_sphere, index, wavelen,
xpolarization, theory=theory)
is_ok.append(holo.data.ptp() > 0)
self.assertTrue(all(is_ok))
def evaluate_model(self, params):
scatterer = self.make_scatterer(params)
if self.theory == 'mieonly':
theory = Mie()
else:
theory = MieLens(lens_angle=params['lens_angle'])
if self.theory == 'mielens':
scaling = 1.0
else:
scaling = params['alpha']
model = calc_holo(self.data, scatterer, theory=theory, scaling=scaling)
return model
def test_mielens_multiple_returns_nonzero(self):
scatterers = [
Sphere(n=1.59, r=5e-7, center=(1e-6, -1e-6, 10e-6)),
Sphere(n=1.59, r=1e-6, center=[8e-6, 5e-6, 5e-6]),
Sphere(n=1.59 + 0.0001j, r=5e-7, center=[5e-6, 10e-6, 3e-6]),
]
sphere_collection = Spheres(scatterers=scatterers)
theory = MieLens()
schema = yschema
holo = calc_holo(schema, sphere_collection, index, wavelen,
theory=theory)
self.assertTrue(holo is not None)
self.assertTrue(holo.values.std() > 0)
def calculate_central_lobe_at(zs):
illum_wavelength = 0.66 # 660 nm red light
k = 2 * np.pi / illum_wavelength
detector = detector_grid(4, 2.0)
central_lobes = []
for z in zs:
center = (0, 0, z)
scatterer = Sphere(n=1.59, r=0.5, center=center)
holo = calc_holo(
detector, scatterer, illum_wavelen=illum_wavelength,
medium_index=1.33, illum_polarization=(1, 0), theory=MieLens())
central_lobe = holo.values.squeeze()[0, 0]
central_lobes.append(central_lobe)
return np.array(central_lobes)
def test_mielens_x_polarization_differs_from_y(self):
# test holograms for orthogonal polarizations; make sure they're
# not the same, nor too different from one another.
theory = MieLens()
holo_x = calc_holo(xschema, sphere, index, wavelen,
illum_polarization=xpolarization, theory=theory)
holo_y = calc_holo(yschema, sphere, index, wavelen,
illum_polarization=ypolarization, theory=theory)
# the two arrays should not be equal
self.assertFalse(np.allclose(holo_x, holo_y, **SOFTTOLS))
# but their max and min values should be very close
# (really exact because we lose no symmetry from the grid)
self.assertTrue(np.isclose(holo_x.max(), holo_y.max(), **MEDTOLS))
self.assertTrue(np.isclose(holo_x.min(), holo_y.min(), **MEDTOLS))
def forward(self, pars, detector):
"""
Compute a forward model (the hologram)
Parameters
-----------
pars: dict(string, float)
Dictionary containing values for each parameter used to compute
the hologram. Possible parameters are given by self.parameters.
detector: xarray
dimensions of the resulting hologram. Metadata taken from
detector if not given explicitly when instantiating self.
"""
optics_kwargs, scatterer = self._optics_scatterer(pars, detector)
# We need the lens parameter(s) for the theory:
theory_kwargs = {name: self._get_parameter(name, pars, detector)
for name in self.theory_params}
# FIXME would be nice to have access to the interpolator kwargs
theory = MieLens(**theory_kwargs)
try:
return calc_holo(detector, scatterer, theory=theory,
scaling=1.0, **optics_kwargs)
except InvalidScatterer:
return -np.inf
def make_stack_figures(data, fits, n=None, r=None, z_positions=None):
scatterers = [fit.scatterer for fit in fits]
z = [fit.scatterer.center[2]
for fit in fits] if z_positions is None else z_positions
for scatterer, z_pos in zip(scatterers, z):
scatterer.n = n if n is not None else scatterer.n
scatterer.r = r if r is not None else scatterer.r
scatterer.center[
2] = z_pos if z_positions is not None else scatterer.center[2]
model_holos = [
calc_holo(dt, scatterer, theory=MieLens(lens_angle=1.0))
for dt, scatterer in zip(data, scatterers)
]
data_stack_xz = np.vstack([dt.values.squeeze()[50, :] for dt in data])
data_stack_yz = np.vstack([dt.values.squeeze()[:, 50] for dt in data])
model_stack_xz = np.vstack(
[holo.values.squeeze()[50, :] for holo in model_holos])
model_stack_yz = np.vstack(
[holo.values.squeeze()[:, 50] for holo in model_holos])
return data_stack_xz, data_stack_yz, model_stack_xz, model_stack_yz
def test_mielens_is_close_to_mieonly(self):
"""Tests that a mielens hologram is similar to a mie-only hologram."""
theory_mielens = MieLens()
theory_mieonly = Mie()
holo_mielens = calc_holo(
xschema, sphere, index, wavelen, xpolarization,
theory=theory_mielens)
holo_mieonly = calc_holo(
xschema, sphere, index, wavelen, xpolarization,
scaling=1.0, theory=theory_mieonly)
# the two arrays should not be equal
self.assertFalse(np.allclose(holo_mielens, holo_mieonly, **TOLS))
# but their max and min values should be close:
ptp_close_ish = np.isclose(
holo_mielens.values.ptp(), holo_mieonly.values.ptp(), atol=0.1)
# and their median should be close:
median_close_ish = np.isclose(
np.median(holo_mielens), np.median(holo_mieonly), atol=0.1)
self.assertTrue(ptp_close_ish)
self.assertTrue(median_close_ish)
def test_does_not_crash(self):
theory = MieLens()
holo = calc_holo(xschema, sphere, index, wavelen, xpolarization,
theory=theory)
self.assertTrue(holo is not None)