mirror of
https://github.com/yosata/fourierOptics.git
synced 2026-10-29 20:51:10 +00:00
Added Atmospheric Seeing
This commit is contained in:
yosata committed
1 parent
04eb56d529
commit
914910e684
7 files changed
+404
-20
No files matched your search
@@ -49,8 +49,8 @@ if __name__ == '__main__':
|
||||
# fig_size=(12,5), show=False)
|
||||
figp1, axp1 = plot_real_valued_results(np.abs(footprint_p1)[850:2150,850:2150], x[850:2150,850:2150], y[850:2150,850:2150],
|
||||
labeltext='Amplitude', show=False, fig_size=None)
|
||||
plt.savefig('./figures/ELT-MCD-ADC_footprint_no_wfe_{}_{}.pdf'.format(hx,hy), bbox_inches='tight', transparent=True)
|
||||
plt.savefig('./figures/ELT-MCD-ADC_footprint_no_wfe_{}_{}.png'.format(hx,hy), bbox_inches='tight', transparent=True)
|
||||
# plt.savefig('./figures/ELT-MCD-ADC_footprint_no_wfe_{}_{}.pdf'.format(hx,hy), bbox_inches='tight', transparent=True)
|
||||
plt.savefig('./figures/ELT-MCD-ELT-M1.png', bbox_inches='tight', transparent=True)
|
||||
plt.show()
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,172 @@
|
||||
import numpy as np
|
||||
import sys
|
||||
sys.path.insert(0, '/Users/joost/Dropbox/Werk/PhD/Analyses/Python/Analytical/Fourier Optics')
|
||||
from fourierOptics import *
|
||||
import scipy.special as spc
|
||||
from pdb import set_trace
|
||||
'''
|
||||
def find_pixel_scale(x):
|
||||
""" Calculate the pixel size from the x, y plane """
|
||||
_dpix = np.mean(np.diff(x.real))
|
||||
if _dpix < 1e-99:
|
||||
_dpix = np.mean(np.diff((x.T).real))
|
||||
return _dpix
|
||||
|
||||
def seeing(wvl, r0):
|
||||
"""
|
||||
Seeing value in arcsec at wavelength wvl
|
||||
wvl in millimeter
|
||||
r0 in meter
|
||||
"""
|
||||
wvl *= 1e-3 # convert wvl from mm to meter
|
||||
return 3600*180/np.pi*0.976*wvl/r0
|
||||
|
||||
def fried_r0(wvl, seeing):
|
||||
"""
|
||||
Returns Fried's parameter value in meters
|
||||
wvl in millimeter
|
||||
"""
|
||||
wvl *= 1e-3 # convert wvl from mm to meter
|
||||
return 0.976*wvl/seeing*206264.8
|
||||
|
||||
def airmass(z):
|
||||
"""
|
||||
Converts zenith angle in degrees to airmass
|
||||
"""
|
||||
return 1/np.cos(np.deg2rad(z))
|
||||
|
||||
def spectrum(k, r0, L0=25):
|
||||
"""SPECTRUM Phase power spectrum density computes the phase power
|
||||
spectrum density from the spatial frequency f and an
|
||||
atmosphere object
|
||||
|
||||
Normal value for L0 = 25.
|
||||
"""
|
||||
cte = (24*spc.gamma(6/5)/5)**(5/6)*(spc.gamma(11/6)**2./(2*np.pi**(11/3)))
|
||||
return r0**(-5/3)*cte*(k**2 + 1/L0**2)**(-11/6)
|
||||
|
||||
def add_seeing(wvl, sng, field_tuple):
|
||||
"""
|
||||
Computes the seeing limited PSF for a supplied amplitude
|
||||
distribution.
|
||||
|
||||
Parameters:
|
||||
wvl - wavelength in mm
|
||||
sng - seeing in arcseconds
|
||||
field_tuple - tuple containing (amplitude array, x array, y array)
|
||||
|
||||
Returns:
|
||||
psf_seeing
|
||||
|
||||
"""
|
||||
r01 = fried_r0(wvl, seeing=sng) * 1e3
|
||||
A_psf, x_psf, y_psf = field_tuple
|
||||
n,m = np.shape(x_psf)
|
||||
fx = x_psf / (3200*wvl)
|
||||
fy = y_psf / (3200*wvl)
|
||||
dk = find_pixel_scale(fx)
|
||||
|
||||
# von-Karman spectrum of the atmosphere for the given frequencies in k-space
|
||||
psd = spectrum(np.hypot(fx.real, fy.real), r0=r01, L0=25*1e3)
|
||||
psd[int(n/2),int(m/2)] = 0
|
||||
|
||||
# Compute the atmospheric OTF
|
||||
# According to Roddier 1981, the atmospheric OTF can be derived from the phase structure function
|
||||
# assuming that the phase is stationary accross the pupil and behaves as a Gaussian variable
|
||||
Bphi = np.fft.fft2(np.fft.ifftshift(psd))*dk**2
|
||||
Dphi = np.fft.ifftshift((2 * (Bphi[0,0] - Bphi))) # ifftshift in Bphi en Dphi!
|
||||
otf_atm = np.exp(-0.5*Dphi)
|
||||
|
||||
# Compute the OTF of the supplied PSF
|
||||
# We can derive the OTF from the inverse Fourier transform of the PSF
|
||||
psf = np.abs(A_psf)**2
|
||||
otf_psf = np.fft.fftshift(np.fft.ifft2(np.fft.fftshift(psf)))
|
||||
otf_psf = otf_psf/otf_psf.max()
|
||||
|
||||
# Compute the seeing-limited PSF
|
||||
# Multiplication of OTF and then Fourier transform
|
||||
otf = otf_psf * otf_atm
|
||||
psf_seeing = np.fft.fftshift(np.fft.ifft2(np.fft.ifftshift(otf)))
|
||||
return psf_seeing
|
||||
'''
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
l = 0.5e-3 # mm
|
||||
D_GT = 400 # mm
|
||||
dpix = 1.6
|
||||
n,m = 1001, 1001
|
||||
x,y = np.meshgrid(np.linspace(-n/2*dpix, n/2*dpix, n), np.linspace(-m/2*dpix, m/2*dpix, m))
|
||||
wfe = WavefrontError(n, m)
|
||||
|
||||
# Create the Bahtinov mask and set it on the entrance pupil (ELT-M1)
|
||||
GT_MASK = Profiles().bahtinov_mask(D_GT/2, 186.53/2, n, m, dpix=1.6, N=30, oversample=1).astype('complex128')
|
||||
GT_M1 = ParabolicMirror(dx=0, dy=0, name='GT_Paraxial', CA=400, f=3200)
|
||||
GT_platescale = (3600*180/np.pi) / (GT_M1.CA * 8)
|
||||
|
||||
# Set up
|
||||
Elist = []
|
||||
lList = np.linspace(0.398e-3, 0.727e-3, 25).tolist()
|
||||
|
||||
# Dispersion over the band
|
||||
dispMax = 1.5 / 3600 # maximum dispersion in degrees
|
||||
dispersion = np.linspace(0, dispMax, len(lList)).tolist()
|
||||
|
||||
# Seeing conditions
|
||||
sng = 1.5
|
||||
|
||||
|
||||
# Iterate over the wavelengths
|
||||
for i in range(len(lList)):
|
||||
|
||||
l = lList[i]
|
||||
print(l)
|
||||
# Generating the tilt to the input field.
|
||||
d = dispersion[i]
|
||||
field_tilt = wfe.generate_tilt(x,y,tx=0, ty=d)
|
||||
|
||||
# Adding the tilt to the input field
|
||||
Ein = GT_MASK * np.exp(-1j * 2*np.pi/l * field_tilt) * GT_M1.phase_delay(x,y,l, paraxial=True)
|
||||
|
||||
# Propagate the input field throug the paraxial model
|
||||
# Output diffraction limited PSF
|
||||
fou = FourierOptics(l)
|
||||
oC = [-0.6, 0.6, -0.6, 0.6]
|
||||
Eout, xout, yout = fou.fresnel_propagation(Ein, x, y, dz=GT_M1.f, show=False,
|
||||
outputCoordinates=oC, apply_interpolation=True)
|
||||
psf_GT_DL = (Eout, xout, yout)
|
||||
|
||||
psf_seeing = add_seeing(l, sng, psf_GT_DL)
|
||||
|
||||
Elist.append(psf_seeing)
|
||||
# Elist.append(Eout)
|
||||
|
||||
# Average over all the wavelengths to get the final field.
|
||||
Eca = np.asarray([np.abs(x) for x in Elist]).mean(axis=0) # Amplitude # Intensity
|
||||
Ecp = np.asarray([np.angle(x) for x in Elist]).mean(axis=0) # Phase
|
||||
|
||||
Eca = Eca/Eca.max() * 64000
|
||||
|
||||
# Adding background level and nosie, estimated from FITS data of the Gratama Telescope
|
||||
Eca = Eca + np.random.normal(2000, 13.5, np.shape(Eca))
|
||||
|
||||
# Convert the scale to sky-angles using the plate scale
|
||||
x = xout * GT_platescale
|
||||
y = yout * GT_platescale
|
||||
|
||||
# save_variable('GT_psf_with_dispersion.pkl', (Eca, x, y))
|
||||
|
||||
# Plotting the results
|
||||
fig = plt.figure(figsize=(9,7))
|
||||
ax = fig.add_subplot(111)
|
||||
im = ax.imshow(Eca, cmap='hot', origin='lower', extent=[x.min(),x.max(),y.min(),y.max()], norm=LogNorm())
|
||||
ax.set_xlim([x.min(),x.max()])
|
||||
ax.set_ylim([y.min(),y.max()])
|
||||
ax.set_xlabel('x [arcsec]')
|
||||
ax.set_ylabel('y [arcsec]')
|
||||
fig.colorbar(im, ax=ax, label='Amplitude')
|
||||
plt.tight_layout()
|
||||
plt.show()
|
||||
|
||||
plot_real_valued_results(np.sqrt(Eca), x, y, fig_size=(9,7))
|
||||
Reference in new issue
Block a user