def get_int_var(masked_spectrum, distance, wavelength):
propagation_array = get_propagation_array(masked_spectrum.shape, distance,
wavelength)
propagated = propagation_array * masked_spectrum
reconstructed = get_shifted_idft(propagated)
intensity = get_intensity(reconstructed)
fitness = intensity.var()
return fitness
def get_int_var(masked_spectrum, distance, wavelength):
propagation_array = get_propagation_array(masked_spectrum.shape, distance,
wavelength)
propagated = propagation_array * masked_spectrum
reconstructed = get_shifted_idft(propagated)
intensity = get_intensity(reconstructed)
fitness = intensity.var()
return fitness
def get_lowpass_var(masked_spectrum, distance):
propagation_array = get_propagation_array(masked_spectrum.shape, distance)
propagated = propagation_array * masked_spectrum
lowpass_mask = get_lowpass_mask(propagated.shape, .4)
propagated = lowpass_mask * propagated
reconstructed = get_shifted_idft(propagated)
intensity = get_intensity(reconstructed)
fitness = intensity.var()
return fitness
def get_lowpass_var(masked_spectrum, distance):
propagation_array = get_propagation_array(masked_spectrum.shape, distance)
propagated = propagation_array * masked_spectrum
lowpass_mask = get_lowpass_mask(propagated.shape, .4)
propagated = lowpass_mask * propagated
reconstructed = get_shifted_idft(propagated)
intensity = get_intensity(reconstructed)
fitness = intensity.var()
return fitness
def phase_detection(masked_spectrum, distance):
shape = masked_spectrum.shape
shape_center = [dim / 2 for dim in shape]
filtered_hologram = get_shifted_idft(masked_spectrum)
focus_mask = get_mask(shape, np.ones(20), shape_center)
focus_feature = filtered_hologram * focus_mask
feature_spectrum = get_shifted_dft(focus_feature)
propagation_array = get_propagation_array(shape, distance)
propagated_spectrum = propagation_array * feature_spectrum
propagated_hologram = get_shifted_idft(propagated_spectrum)
radious = 50
separation = 400
window = np.ones(radious)
spectrum2sensor = np.angle
spectrum2sensor = np.abs
spectrum2sensor = get_intensity
spectrum2sensor = normalize
left_center = shape_center[0], shape_center[1] - separation / 2
left_mask = get_mask(shape, window, left_center)
# left_bundle = left_mask * propagated_spectrum
left_bundle = left_mask * propagated_hologram
left_sensor = spectrum2sensor(get_shifted_dft(left_bundle))
left_peak = get_circles(left_sensor, 1, 50)[0][1]
right_center = shape_center[0], shape_center[1] + separation / 2
right_mask = get_mask(shape, window, right_center)
right_bundle = right_mask * propagated_hologram
right_sensor = spectrum2sensor(get_shifted_dft(right_bundle))
right_peak = get_circles(right_sensor, 1, 50)[0][1]
# showimage(normalize(np.maximum(left_bundle, right_bundle)))
# showimage(normalize(np.maximum(left_sensor, right_sensor)))
distance = get_distance(left_peak, right_peak)
fitness = distance
return fitness
def phase_detection(masked_spectrum, distance):
shape = masked_spectrum.shape
shape_center = [dim / 2 for dim in shape]
filtered_hologram = get_shifted_idft(masked_spectrum)
focus_mask = get_mask(shape, np.ones(20), shape_center)
focus_feature = filtered_hologram * focus_mask
feature_spectrum = get_shifted_dft(focus_feature)
propagation_array = get_propagation_array(shape, distance)
propagated_spectrum = propagation_array * feature_spectrum
propagated_hologram = get_shifted_idft(propagated_spectrum)
radious = 50
separation = 400
window = np.ones(radious)
spectrum2sensor = np.angle
spectrum2sensor = np.abs
spectrum2sensor = get_intensity
spectrum2sensor = normalize
left_center = shape_center[0], shape_center[1] - separation / 2
left_mask = get_mask(shape, window, left_center)
# left_bundle = left_mask * propagated_spectrum
left_bundle = left_mask * propagated_hologram
left_sensor = spectrum2sensor(get_shifted_dft(left_bundle))
left_peak = get_circles(left_sensor, 1, 50)[0][1]
right_center = shape_center[0], shape_center[1] + separation / 2
right_mask = get_mask(shape, window, right_center)
right_bundle = right_mask * propagated_hologram
right_sensor = spectrum2sensor(get_shifted_dft(right_bundle))
right_peak = get_circles(right_sensor, 1, 50)[0][1]
# showimage(normalize(np.maximum(left_bundle, right_bundle)))
# showimage(normalize(np.maximum(left_sensor, right_sensor)))
distance = get_distance(left_peak, right_peak)
fitness = distance
return fitness
def reconstruct(propagated, **kw):
reconstructed = get_shifted_idft(propagated)
return reconstructed
return mask
def get_lowpass_mask(shape, radius=0.2, softness=0):
radius = round(min(shape) * radius)
window = np.kaiser(radius, softness)
mask = get_mask(shape, window)
return mask
@methods
def get_var(masked_spectrum, distance, wavelength, (dx, dy)):
propagation_array = get_propagation_array(masked_spectrum.shape, distance,
wavelength, (dx, dy))
propagated = propagation_array * masked_spectrum
reconstructed = get_shifted_idft(propagated)
module = get_module(reconstructed)
module_zone = get_best_contrast_zone(module)
# showimage(normalize(module_zone))
fitness = module_zone.var()
return fitness
@methods
def get_diff_var(masked_spectrum, distance, wavelength, (dx, dy)):
fitness = get_var(masked_spectrum, distance, wavelength, (dx, dy))
fitness -= get_var(masked_spectrum, -distance, wavelength, (dx, dy))
return fitness
@methods
def reconstructed(self):
print("IDFT(Propagated)")
return get_shifted_idft(self.propagated)
def reconstruct(propagated, **kw):
reconstructed = get_shifted_idft(propagated)
return reconstructed
def reconstructed(self):
print("IDFT(Propagated)")
return get_shifted_idft(self.propagated)
return mask
def get_lowpass_mask(shape, radius=0.2, softness=0):
radius = round(min(shape) * radius)
window = np.kaiser(radius, softness)
mask = get_mask(shape, window)
return mask
@methods
def get_var(masked_spectrum, distance, wavelength, (dx, dy)):
propagation_array = get_propagation_array(masked_spectrum.shape,
distance, wavelength, (dx, dy))
propagated = propagation_array * masked_spectrum
reconstructed = get_shifted_idft(propagated)
module = get_module(reconstructed)
module_zone = get_best_contrast_zone(module)
# showimage(normalize(module_zone))
fitness = module_zone.var()
return fitness
@methods
def get_diff_var(masked_spectrum, distance, wavelength, (dx, dy)):
fitness = get_var(masked_spectrum, distance, wavelength, (dx, dy))
fitness -= get_var(masked_spectrum, -distance, wavelength, (dx, dy))
return fitness
@methods
