Spaces:
Sleeping
Sleeping
add fraunhofer diffraction test
Browse files- fraunhofer_test.py +70 -0
- zern_generator.py +2 -2
fraunhofer_test.py
ADDED
|
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import astropy.units as u
|
| 2 |
+
import pyoptica as po
|
| 3 |
+
import matplotlib.pyplot as plt
|
| 4 |
+
import numpy as np
|
| 5 |
+
import math
|
| 6 |
+
import os
|
| 7 |
+
from scipy.fft import fft2, ifft2, fftshift, ifftshift
|
| 8 |
+
import aotools.opticalpropagation as op
|
| 9 |
+
import scipy.special as sc
|
| 10 |
+
import time
|
| 11 |
+
import multiprocessing
|
| 12 |
+
from multiprocessing import Pool
|
| 13 |
+
from zern_generator import generate_zern_wavefront
|
| 14 |
+
from scipy.ndimage import zoom
|
| 15 |
+
|
| 16 |
+
fig, axs = plt.subplots(2, 2)
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
f = 100 * 10 ** -3 # Форкусное расстояние линзы
|
| 20 |
+
|
| 21 |
+
|
| 22 |
+
radius = 5 * 10 ** -3 # Радиус линзы
|
| 23 |
+
|
| 24 |
+
span = (-(10 ** -2), 10 ** -2)
|
| 25 |
+
lens = po.ThinLens(radius, f)
|
| 26 |
+
z = 100 * 10 ** -3 # Расстояние
|
| 27 |
+
wavelength = 500 * 10 ** -9 # Длина волны
|
| 28 |
+
|
| 29 |
+
pixel_scale = 250 * 10 ** -4 # Размер пикселя
|
| 30 |
+
npix = 2**9 # Размер сетки
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
ddx = np.linspace(*span, npix)
|
| 34 |
+
ddy = np.linspace(*span, npix)
|
| 35 |
+
xv, yv = np.meshgrid(ddx, ddy)
|
| 36 |
+
f2 = generate_zern_wavefront(xv, yv, [0, 0, 0, 3, 0], norm_radius=radius)
|
| 37 |
+
|
| 38 |
+
dist_from_center = np.sqrt(xv**2 + yv**2)
|
| 39 |
+
mask = dist_from_center <= radius
|
| 40 |
+
f2[mask == 0] = 0
|
| 41 |
+
f2[np.isnan(f2)] = 0
|
| 42 |
+
k = 2*math.pi/wavelength
|
| 43 |
+
|
| 44 |
+
wf = np.zeros((npix, npix), dtype=np.complex64)
|
| 45 |
+
wf[mask] = 1 + 0j
|
| 46 |
+
wf += f2 * 1j
|
| 47 |
+
|
| 48 |
+
|
| 49 |
+
D = 2e-6
|
| 50 |
+
fscale = wavelength*z
|
| 51 |
+
|
| 52 |
+
target_min, target_max = -50e-6, 50e-6
|
| 53 |
+
v = np.fft.fftfreq(npix, d=D/npix)
|
| 54 |
+
v = fscale * np.fft.fftshift(v)
|
| 55 |
+
extent = [1e3 * v[0], 1e3 * v[-1], 1e3 * v[0], 1e3 * v[-1]]
|
| 56 |
+
|
| 57 |
+
phase_mul = ((np.exp(1j*k*z) * np.exp(1j*k*(xv**2 + yv**2)/(2*z)))/(1j*wavelength*z))
|
| 58 |
+
U_fraun = fft2(ifftshift(wf), overwrite_x=True)
|
| 59 |
+
U_fraun = fftshift(U_fraun * phase_mul)
|
| 60 |
+
|
| 61 |
+
|
| 62 |
+
I_fraun = np.abs(U_fraun)**2
|
| 63 |
+
I_fraun = I_fraun / np.max(I_fraun)
|
| 64 |
+
|
| 65 |
+
axs[0][1].imshow(I_fraun, cmap='grey', extent=(*span, *span))
|
| 66 |
+
axs[1][1].plot(np.linspace(extent[0], extent[1], I_fraun.shape[0]),
|
| 67 |
+
I_fraun[:, I_fraun.shape[0]//2], antialiased='none')
|
| 68 |
+
axs[0][0].imshow(np.abs(wf)**2, cmap='grey', extent=(*span, *span))
|
| 69 |
+
axs[1][0].imshow(f2, cmap='grey', extent=(*span, *span), interpolation='none')
|
| 70 |
+
plt.show()
|
zern_generator.py
CHANGED
|
@@ -8,14 +8,14 @@ SAMPLE_SIZE = 256
|
|
| 8 |
span = (-1, 1)
|
| 9 |
|
| 10 |
|
| 11 |
-
def generate_zern_wavefront(xv, yv, zerns):
|
| 12 |
num_zerns = len(zerns)
|
| 13 |
|
| 14 |
degree = math.ceil((-3 + math.sqrt(8 * num_zerns + 1)) / 2)
|
| 15 |
zerns = list(zerns) + [0] * int((((degree + 1) * (degree + 2) / 2) - len(zerns)))
|
| 16 |
|
| 17 |
cart = RZern(degree)
|
| 18 |
-
cart.make_cart_grid(xv, yv)
|
| 19 |
return np.array(cart.eval_grid(np.array(zerns), matrix=True))
|
| 20 |
|
| 21 |
|
|
|
|
| 8 |
span = (-1, 1)
|
| 9 |
|
| 10 |
|
| 11 |
+
def generate_zern_wavefront(xv, yv, zerns, norm_radius = 1):
|
| 12 |
num_zerns = len(zerns)
|
| 13 |
|
| 14 |
degree = math.ceil((-3 + math.sqrt(8 * num_zerns + 1)) / 2)
|
| 15 |
zerns = list(zerns) + [0] * int((((degree + 1) * (degree + 2) / 2) - len(zerns)))
|
| 16 |
|
| 17 |
cart = RZern(degree)
|
| 18 |
+
cart.make_cart_grid(xv/norm_radius, yv/norm_radius)
|
| 19 |
return np.array(cart.eval_grid(np.array(zerns), matrix=True))
|
| 20 |
|
| 21 |
|