def _simulate_sphere_data(params, theory):
detector = hp.detector_grid(shape=100, spacing=.1)
metadata = {
'medium_index': 1.33,
'illum_wavelen': 0.660,
'illum_polarization': (1, 0)
}
sphere = hp.scattering.Sphere(n=params['n'],
r=params['r'],
center=(params['x'], params['y'],
params['z']))
if theory == 'mieonly':
alpha = params['alpha']
metadata['scaling'] = alpha
elif theory == 'mielens':
lens_angle = params['lens_angle']
metadata['theory'] = hp.scattering.theory.MieLens(
lens_angle=lens_angle)
holo = hp.scattering.calc_holo(detector, sphere, **metadata)
np.random.seed(RANDOM_SEED)
noise = params['noise_sd'] * np.random.randn(*holo.shape)
noisy_holo = hp.core.metadata.copy_metadata(holo, holo + noise)
torch_holo = tensor(noisy_holo.values.squeeze(), dtype=torch.float32)
return {'x': noisy_holo, 'y': torch_holo}
def bisphere(a_p, n_p, z_p, theta, phi, noise=True):
px = int(feature_extent(a_p, n_p, z_p, config)) * 2
detector = hp.detector_grid(2 * px, mag)
center = (mag * px, mag * px, z_p)
delta = np.array([
np.cos(phi) * np.cos(theta),
np.sin(phi) * np.cos(theta),
np.sin(theta)
])
c1 = +1.001 * a_p * delta
c2 = -1.001 * a_p * delta
cluster = np.array([c1, c2])
cluster_return = cluster.copy().tolist()
cluster += center
s1 = Sphere(center=cluster[0], n=n_p, r=a_p)
s2 = Sphere(center=cluster[1], n=n_p, r=a_p)
dimer = Spheres([s1, s2])
holo = np.squeeze(
calc_holo(detector,
dimer,
medium_index=n_m,
illum_wavelen=wv,
illum_polarization=(1, 0))).data
#noise
if noise:
holo += np.random.normal(0., 0.05, holo.shape)
return holo, cluster_return
def make_field(particle_number, height, config):
#Angles to rotate agg
angle_1 = random.randint(1, 360)
angle_2 = random.randint(1, 360)
#Setting up medium, camera, and laser variables
shape, _ = config['shape']
spacing = config['instrument']['magnification']
medium_index = config['instrument']['n_m']
illum_wavelen = config['instrument']['wavelength']
illum_polarization = (1, 0)
detector = hp.detector_grid(shape=shape, spacing=spacing)
#Particle_params
radius = random.random(config['particle']['a_p'])
refractive = random.random(config['particle']['n_p'])
#choose random data_set
data_name = (str(random.randint(0, 19)) + '.csv')
#read in data
df = pd.read_csv(data_name)
x = df['x'].tolist()
y = df['y'].tolist()
z = df['z'].tolist()
#Clear non-essential items
x = x[0:particle_number + 1]
y = y[0:particle_number + 1]
z = z[0:particle_number + 1]
#adjust distance between particles for particle size
x = [item / (1 / (2 * radius)) for item in x]
y = [item / (1 / (2 * radius)) for item in y]
z = [item / (1 / (2 * radius)) for item in z]
#rotate around x and then y axis
x, y, z = rotation(x, y, z, angle_1, 'x')
x, y, z = rotation(x, y, z, angle_2, 'y')
#position agg
x = [(item + shape * spacing / 2) for item in x]
y = [(item + shape * spacing / 2) for item in y]
z = [(item + height) for item in z]
#scatter
field = scatter(x,
y,
z,
particle_number,
radius,
detector,
medium_index,
illum_wavelen,
illum_polarization,
theory=Mie,
refractive=refractive)
return field
def make_fake_data():
detector = holopy.detector_grid([40, 40], spacing=2.878e-7)
fake_data = calc_holo(
detector,
SPHERE,
medium_index=1.33,
illum_wavelen=6.58e-7,
illum_polarization=(1, 0),
theory='auto',
scaling=CORRECT_ALPHA,)
return fake_data
def sphere(a_p, n_p, z_p):
px = int(feature_extent(a_p, n_p, z_p, config))
detector = hp.detector_grid(2 * px, mag)
center = (mag * px, mag * px, z_p)
s = Sphere(center=center, n=n_p, r=a_p)
holo = np.squeeze(
calc_holo(detector,
s,
medium_index=n_m,
illum_wavelen=wv,
illum_polarization=(1, 0))).data
#noise
holo += np.random.normal(0., 0.05, holo.shape)
return holo
from holopy.scattering import Spheres
from holopy.scattering import Cylinder
from holopy.core.io import get_example_data_path
imagepath = get_example_data_path('image0002.h5')
exp_img = hp.load(imagepath)
"""
Qui se vuoi fissare due posizioni specifiche
"""
sphere1 = Sphere(center=(20, 20, 7), n=1.59, r=0.3) #all in micro m units
sphere2 = Sphere(center=(25.6, 25.6, 7), n=1.59, r=0.3)
collection = Spheres([sphere1, sphere2])
medium_index = 1.33
illum_wavelength = 0.660
illum_polarization = (1, 0)
detector = hp.detector_grid(shape=512, spacing=0.1) #spacing=pix size
holo = calc_holo(detector, collection, medium_index, illum_wavelength,
illum_polarization)
hp.show(holo)
"""
for look the trasversal profile of hologram centred in partice position
plt.title('Hologram')
plt.plot(holo[256])
plt.xlabel("Pixel")
plt.ylabel("Intensity")
plt.title('Holo Intensity')
plt.xlim(100, 400)
"""
import holopy as hp
from holopy.scattering import calc_holo, Sphere
sphere = Sphere(n=1.59, r=.5, center=(4, 4, 5))
detector = hp.detector_grid(shape=100, spacing=.1)
medium_index = 1.33
illum_wavelen = 0.660
illum_polarization = (1, 0)
from holopy.core.io import get_example_data_path
imagepath = get_example_data_path('image01.jpg')
exp_img = hp.load_image(imagepath,
spacing=0.0851,
medium_index=medium_index,
illum_wavelen=illum_wavelen,
illum_polarization=illum_polarization)
exp_img = exp_img[{'x': slice(0, 100), 'y': slice(0, 100)}]
from holopy.scattering import Spheres
s1 = Sphere(center=(5, 5, 5), n=1.59, r=.5)
s2 = Sphere(center=(4, 4, 5), n=1.59, r=.5)
collection = Spheres([s1, s2])
holo = calc_holo(exp_img, collection)
hp.show(holo)
def trisphere(a_p, n_p, z_p, alpha, theta, phi, check_geom=False):
'''
alpha: angle of 3rd monomer wrt dimer
-alpha=pi/3: equilateral triangle
-alpha between pi/3 and 5pi/3 (no overlaps)
theta, phi: rotation angles
-theta=0 : aligned along xy plane
-theta between 0 and 2pi
-phi between 0 and 2pi
'''
px = int(feature_extent(a_p, n_p, z_p, config)) * 2
detector = hp.detector_grid(2 * px, mag)
center = (mag * px, mag * px, z_p)
if alpha < np.pi / 3 or alpha > 5 * np.pi / 3:
raise Exception("Invalid value for alpha")
#rotation about origin
#delta = np.array([np.cos(phi)*np.cos(theta), np.sin(phi)*np.cos(theta), np.sin(theta)])
delta = np.array([1, 0, 0])
#angle of third monomer wrt dimer
delta_2 = np.array([-np.cos(alpha), np.sin(alpha), 0])
c1 = 1.001 * a_p * delta
c2 = -1.001 * a_p * delta
c3 = c1 + 2.001 * a_p * delta_2
cluster = np.array([c1, c2, c3])
#get centroid of trimer and re-center
centroid = np.mean(np.array([c1, c2, c3]), axis=0)
cluster -= centroid
#rotate trimer
zax = np.array([0, 0, 1])
xax = np.array([1, 0, 0])
zrot = lambda c: rotate(c, zax, phi)
xrot = lambda c: rotate(c, xax, theta)
cluster = zrot(cluster)
cluster = xrot(cluster)
cluster_return = cluster.copy().tolist()
#place in particle position
cluster += center
s1 = Sphere(center=cluster[0], n=n_p, r=a_p)
s2 = Sphere(center=cluster[1], n=n_p, r=a_p)
s3 = Sphere(center=cluster[2], n=n_p, r=a_p)
trimer = Spheres([s1, s2, s3])
r_sum = 4 * a_p
if check_geom:
#geometry check
npix = 60 #npix x npix grid
coord_range = np.linspace(mag * px - r_sum, mag * px + r_sum, num=npix)
x, y = np.meshgrid(coord_range, coord_range)
trimer_points = np.zeros((npix, npix))
for i in range(npix):
for j in range(npix):
coord = [x[i][j], y[i][j], z_p]
if trimer.contains(coord):
trimer_points[i][j] = 1
plt.imshow(trimer_points)
plt.show()
holo = np.squeeze(
calc_holo(detector,
trimer,
medium_index=n_m,
illum_wavelen=wv,
illum_polarization=(1, 0))).data
#noise
holo += np.random.normal(0., 0.05, holo.shape)
return holo, cluster_return
## If the figures do not pop out in a different window,
## use this command in the console window:
## %matplotlib qt
import holopy as hp
from holopy.scattering import calc_holo, Sphere
import numpy as np
from holopy.scattering import calc_scat_matrix, calc_intensity, calc_field
import matplotlib.pyplot as plt
medium_index = 1.33
illum_wavelen = 0.750 # 750nm
illum_polarization = (1, 0) # x polarized
sphere_z_position = 2 # in microns
detector = hp.detector_grid(shape=201, spacing=.1)
distant_sphere = Sphere(r=0.5,
n=1.59,
center=(10.05, 10.05, sphere_z_position))
## Calculate the field here given above paramters
scat = calc_field(detector, distant_sphere, medium_index, illum_wavelen,
illum_polarization)
scattered_matrix = scat.data
scat_intensity_x = scattered_matrix[0, :, :, 0]
scat_intensity_y = scattered_matrix[1, :, :, 0]
scat_intensity_z = scattered_matrix[2, :, :, 0]
# real value
scat_x_real = scat_intensity_x.real
# imaginary value
import holopy as hp
from holopy.scattering import calc_holo, Sphere
sphere = Sphere(n = 1.59, r = .5, center = (4, 4, 5))
detector = hp.detector_grid(shape = 100, spacing = .1)
medium_index = 1.33
illum_wavelen = 0.660
illum_polarization = (1,0)
from holopy.core.io import get_example_data_path
imagepath = get_example_data_path('image01.jpg')
exp_img = hp.load_image(imagepath, spacing=0.0851, medium_index=medium_index, illum_wavelen=illum_wavelen, illum_polarization=illum_polarization)
exp_img = exp_img[{'x':slice(0,100),'y':slice(0,100)}]
from holopy.scattering import Spheres
s1 = Sphere(center=(5, 5, 5), n = 1.59, r = .5)
s2 = Sphere(center=(4, 4, 5), n = 1.59, r = .5)
collection = Spheres([s1, s2])
holo = calc_holo(exp_img, collection)
hp.show(holo)