def __psfcaculator__(self,r=1,lambda_1=632*10**(-9),z=0.1):
"""
pupil: Exit pupil diameter
z: Distance from exit pupil to image plane
r: pupil radius, in unit of lambda
"""
pupil = l1 = 200 # exit pupil sample points
x = __np__.linspace(-r, r, l1)
[X,Y] = __np__.meshgrid(x,x)
Z = __interferometer__.__zernikecartesian__(self.__coefficients__,X,Y)
for i in range(len(Z)):
for j in range(len(Z)):
if x[i]**2+x[j]**2>r**2:
Z[i][j] = 0
d = 400 # background
A = __np__.zeros([d,d])
A[d/2-l1/2+1:d/2+l1/2+1,d/2-l1/2+1:d/2+l1/2+1] = Z
axis_1 = d/pupil*r
fig = __plt__.figure()
# ax = fig.gca()
# __plt__.imshow(A,extent=[-axis_1,axis_1,-axis_1,axis_1],cmap=__cm__.RdYlGn)
# ax.set_xlabel('mm',fontsize=14)
# __plt__.colorbar()
# __plt__.show()
abbe = __np__.exp(-1j*2*__np__.pi*A)
for i in range(len(abbe)):
for j in range(len(abbe)):
if abbe[i][j]==1:
abbe[i][j]=0
PSF = __fftshift__(__fft2__(__fftshift__(abbe)))**2
PSF = PSF/PSF.max()
return PSF
def __psfcaculator__(self,r=1,lambda_1=632*10**(-9),z=0.1):
"""
pupil: Exit pupil diameter
z: Distance from exit pupil to image plane
r: pupil radius, in unit of lambda
"""
pupil = l1 = 200 # exit pupil sample points
x = __np__.linspace(-r, r, l1)
[X,Y] = __np__.meshgrid(x,x)
Z = __zernikecartesian__(self.__coefficients__,X,Y)
for i in range(len(Z)):
for j in range(len(Z)):
if x[i]**2+x[j]**2>r**2:
Z[i][j] = 0
d = 400 # background
A = __np__.zeros([d,d])
A[d/2-l1/2+1:d/2+l1/2+1,d/2-l1/2+1:d/2+l1/2+1] = Z
axis_1 = d/pupil*r
fig = __plt__.figure()
# ax = fig.gca()
# __plt__.imshow(A,extent=[-axis_1,axis_1,-axis_1,axis_1],cmap=__cm__.RdYlGn)
# ax.set_xlabel('mm',fontsize=14)
# __plt__.colorbar()
# __plt__.show()
abbe = __np__.exp(-1j*2*__np__.pi*A)
for i in range(len(abbe)):
for j in range(len(abbe)):
if abbe[i][j]==1:
abbe[i][j]=0
PSF = __fftshift__(__fft2__(__fftshift__(abbe)))**2
PSF = PSF/PSF.max()
return PSF
def __psfcaculator__(self, lambda_1=632 * 10**(-9), z=0.1):
"""
height: Exit pupil height
width: Exit pupil width
z: Distance from exit pupil to image plane
"""
a = self.__a__
b = __sqrt__(1 - a**2)
l1 = 100
x1 = __np__.linspace(-a, a, l1)
y1 = __np__.linspace(-b, b, l1)
[X, Y] = __np__.meshgrid(x1, y1)
Z = __zernikecartesian__(self.__coefficients__, a, X, Y)
d = 400 # background
A = __np__.zeros([d, d])
A[d // 2 - l1 // 2 + 1:d // 2 + l1 // 2 + 1,
d // 2 - l1 // 2 + 1:d // 2 + l1 // 2 + 1] = Z
# fig = __plt__.figure()
# __plt__.imshow(A)
# __plt__.colorbar()
# __plt__.show()
abbe = __np__.exp(-1j * 2 * __np__.pi * A)
for i in range(len(abbe)):
for j in range(len(abbe)):
if abbe[i][j] == 1:
abbe[i][j] = 0
PSF = __fftshift__(__fft2__(__fftshift__(abbe)))**2
PSF = PSF / PSF.max()
return PSF
def __psfcaculator__(self,lambda_1=632*10**(-9),z=0.1): """ height: Exit pupil height width: Exit pupil width z: Distance from exit pupil to image plane """ a = self.__a__ b = __sqrt__(1-a**2) l1 = 100; x1 = __np__.linspace(-a, a, l1) y1 = __np__.linspace(-b, b, l1) [X,Y] = __np__.meshgrid(x1,y1) Z = __zernikecartesian__(self.__coefficients__,a,X,Y) d = 400 # background A = __np__.zeros([d,d]) A[d//2-l1//2+1:d//2+l1//2+1,d//2-l1//2+1:d//2+l1//2+1] = Z # fig = __plt__.figure() # __plt__.imshow(A) # __plt__.colorbar() # __plt__.show() abbe = __np__.exp(-1j*2*__np__.pi*A) for i in range(len(abbe)): for j in range(len(abbe)): if abbe[i][j]==1: abbe[i][j]=0 PSF = __fftshift__(__fft2__(__fftshift__(abbe)))**2 PSF = PSF/PSF.max() return PSF
def otf(self, r=1, lambda_1=632 * 10**(-9), z=0.1, matrix=False):
PSF = self.__psfcaculator__(r=r, lambda_1=lambda_1, z=z)
OTF = __fftshift__(__fft2__(PSF))
if matrix:
return OTF
else:
return 0
def mtf(self, r=1, lambda_1=632 * 10**(-9), z=0.1):
"""
Modulate Transfer function
"""
PSF = self.__psfcaculator__(r=r, lambda_1=lambda_1, z=z)
MTF = __fftshift__(__fft2__(PSF))
MTF = MTF / MTF.max()
f0 = r / 1000 / lambda_1 / z / 10000 # cutoff frequency?
__plt__.imshow(abs(MTF), cmap=__cm__.bwr)
__plt__.colorbar()
__plt__.show()
return 0
def mtf(self,r=1,lambda_1=632*10**(-9),z=0.1): """ Modulate Transfer function """ PSF = self.__psfcaculator__(r=r,lambda_1=lambda_1,z=z) MTF = __fftshift__(__fft2__(PSF)) MTF = MTF/MTF.max() f0 = r/1000/lambda_1/z/10000 # cutoff frequency? __plt__.imshow(abs(MTF),cmap=__cm__.bwr) __plt__.colorbar() __plt__.show() return 0
def mtf(self,lambda_1=632*10**(-9),z=0.1,matrix = False): """ Modulate Transfer function """ PSF = self.__psfcaculator__(lambda_1=lambda_1,z=z) MTF = __fftshift__(__fft2__(PSF)) MTF = MTF/MTF.max() fig = __plt__.figure(figsize=(9, 6), dpi=80) __plt__.imshow(abs(MTF),cmap=__cm__.bwr) __plt__.colorbar() __plt__.show() if matrix == True: return MTF else: return 0
def mtf(self, lambda_1=632 * 10**(-9), z=0.1, matrix=False):
"""
Modulate Transfer function
"""
PSF = self.__psfcaculator__(lambda_1=lambda_1, z=z)
MTF = __fftshift__(__fft2__(PSF))
MTF = MTF / MTF.max()
fig = __plt__.figure(figsize=(9, 6), dpi=80)
__plt__.imshow(abs(MTF), cmap=__cm__.bwr)
__plt__.colorbar()
__plt__.show()
if matrix == True:
return MTF
else:
return 0
def ptf(self): """ Phase transfer function """ PSF = self.__psfcaculator__() PTF = __fftshift__(__fft2__(PSF)) PTF = __np__.angle(PTF) l1 = 100 d = 400 A = __np__.zeros([d,d]) A[d/2-l1/2+1:d/2+l1/2+1,d/2-l1/2+1:d/2+l1/2+1] = PTF[d/2-l1/2+1:d/2+l1/2+1,d/2-l1/2+1:d/2+l1/2+1] __plt__.imshow(abs(A),cmap=__cm__.rainbow) __plt__.colorbar() __plt__.show() return 0
def ptf(self): """ Phase transfer function """ PSF = self.__psfcaculator__() PTF = __fftshift__(__fft2__(PSF)) PTF = __np__.angle(PTF) l1 = 100 d = 400 A = __np__.zeros([d,d]) A[d//2-l1//2+1:d//2+l1//2+1,d//2-l1//2+1:d//2+l1//2+1] = PTF[d//2-l1//2+1:d//2+l1//2+1,d//2-l1//2+1:d//2+l1//2+1] __plt__.imshow(abs(A),cmap=__cm__.rainbow) __plt__.colorbar() __plt__.show() return 0
def ptf(self): """ Phase transfer function """ PSF = self.__psfcaculator__() PTF = __fftshift__(__fft2__(PSF)) PTF = __np__.angle(PTF) b = 400 R = (200)**2 for i in range(b): for j in range(b): if (i-b/2)**2+(j-b/2)**2>R: PTF[i][j] = 0 __plt__.imshow(abs(PTF),cmap=__cm__.rainbow) __plt__.colorbar() __plt__.show() return 0
def ptf(self): """ Phase transfer function """ PSF = self.__psfcaculator__() PTF = __fftshift__(__fft2__(PSF)) PTF = __np__.angle(PTF) b = 400 R = (200)**2 for i in range(b): for j in range(b): if (i-b/2)**2+(j-b/2)**2>R: PTF[i][j] = 0 __plt__.imshow(abs(PTF),cmap=__cm__.rainbow) __plt__.colorbar() __plt__.show() return 0
def mtf(self,
r=1,
lambda_1=632 * 10**(-9),
z=0.1,
draw=True,
matrix=False):
"""
Modulate Transfer function
"""
PSF = self.__psfcaculator__(r=r, lambda_1=lambda_1, z=z)
MTF = __fftshift__(__fft2__(PSF))
MTF = MTF / MTF.max()
f0 = r / 1000 / lambda_1 / z / 10000 # cutoff frequency?
if draw:
fig = __plt__.figure(figsize=(9, 6), dpi=80)
__plt__.imshow(abs(MTF), cmap=__cm__.bwr)
__plt__.colorbar()
__plt__.show()
if matrix == True:
return MTF
else:
return 0
def otf(self,r=1,lambda_1=632*10**(-9),z=0.1): PSF = self.__psfcaculator__(r=r,lambda_1=lambda_1,z=z) OTF = __fftshift__(__fft2__(PSF)) return 0
l1 = 100 #Generate test surface matrix from a detector x = __np__.linspace(-1, 1, l1) y = __np__.linspace(-1, 1, l1) [X,Y] = __np__.meshgrid(x,y) r = __sqrt__(X**2+Y**2) #Z = 20*X Z = __sqrt__(14)*(8*X**4-8*X**2*r**2+r**4)*(6*r**2-5) for i in range(len(Z)): for j in range(len(Z)): if x[i]**2+y[j]**2>1: Z[i][j]=0 d = 400 A = __np__.zeros([d,d]) A[d/2-49:d/2+51,d/2-49:d/2+51] = Z __plt__.imshow(A) __plt__.show() def exp_func(a): if a == 0: return 0 else: return __np__.exp(1j*2*__np__.pi*a) exp_func1 = __np__.vectorize(exp_func,otypes=[__np__.complex64]) abbe = exp_func1(A) fig = __plt__.figure(2) AP = abs(__fftshift__(__fft2__(__fftshift__(abbe))))**2 AP = AP/AP.max() __plt__.imshow(AP) __plt__.show()
def otf(self,r=1,lambda_1=632*10**(-9),z=0.1): PSF = self.__psfcaculator__(r=r,lambda_1=lambda_1,z=z) OTF = __fftshift__(__fft2__(PSF)) return 0
def lens_param_to_psf():
import numpy as __np__
from numpy import sqrt as __sqrt__
from numpy import cos as __cos__
from numpy import sin as __sin__
import matplotlib.pyplot as __plt__
from matplotlib import cm as __cm__
from matplotlib.ticker import LinearLocator as __LinearLocator__
from matplotlib.ticker import FormatStrFormatter as __FormatStrFormatter__
from mpl_toolkits.mplot3d import Axes3D
from numpy.fft import fftshift as __fftshift__
from numpy.fft import ifftshift as __ifftshift__
from numpy.fft import fft2 as __fft2__
def __apershow__(obj):
obj = -abs(obj)
__plt__.imshow(obj)
__plt__.set_cmap('Greys')
__plt__.show()
l1 = 100
# Generate test surface matrix from a detector
x = __np__.linspace(-1, 1, l1)
y = __np__.linspace(-1, 1, l1)
[X, Y] = __np__.meshgrid(x, y)
r = __sqrt__(X**2 + Y**2)
Z = __sqrt__(14) * (8 * X**4 - 8 * X**2 * r**2 + r**4) * (6 * r**2 - 5)
for i in range(len(Z)):
for j in range(len(Z)):
if x[i]**2 + y[j]**2 > 1:
Z[i][j] = 0
fig = __plt__.figure(1)
ax = fig.gca(projection='3d')
surf = ax.plot_surface(X,
Y,
Z,
rstride=1,
cstride=1,
cmap=__cm__.RdYlGn,
linewidth=0,
antialiased=False,
alpha=0.6)
v = max(abs(Z.max()), abs(Z.min()))
ax.set_zlim(-v * 5, v * 5)
cset = ax.contourf(X, Y, Z, zdir='z', offset=-v * 5, cmap=__cm__.RdYlGn)
ax.zaxis.set_major_locator(__LinearLocator__(10))
ax.zaxis.set_major_formatter(__FormatStrFormatter__('%.02f'))
fig.colorbar(surf, shrink=1, aspect=30)
__plt__.show()
d = 800
A = __np__.zeros([d, d])
A[d // 2 - 49:d // 2 + 51, d // 2 - 49:d // 2 + 51] = Z
__plt__.imshow(A)
__plt__.show()
abbe = __np__.exp(1j * 2 * __np__.pi * A)
for i in range(len(abbe)):
for j in range(len(abbe)):
if abbe[i][j] == 1:
abbe[i][j] = 0
fig = __plt__.figure(2)
AP = abs(__fftshift__(__fft2__(__fftshift__(abbe))))**2
AP = AP / AP.max()
__plt__.imshow(AP)
__plt__.show()
