def init(self):
'''
; Pre-compute the parameters and save them in the COMMOM block
:return:
'''
ngrid = self.ngrid
d = self.d
eps = self.eps
alambda = self.alambda
pixel = self.pixel
self.sflag = 0 # fast seeing blur, set to 1 for slow calc.
# Find reasonable limits on the grid parameters
asperpix = 206265.*(1e-6*alambda)/d # maximum fine-pixel size
ccdpix = float(pixel)
k = np.floor(np.log10(ccdpix/asperpix)/np.log10(2.)) +1.
npixperpix = 2**k
fovpix = 2*ngrid/npixperpix # CCD field size
asperpix = ccdpix/npixperpix
size = 206266.*(1e-6*alambda)/asperpix
Rpix = ngrid/size*d
# log.info('Rebinning factor: %s'% npixperpix)
# log.info('Grid pixel: %s arcsec'%asperpix)
# log.info('Grid size: %s m'%size)
# log.info('CCD pixel: %s arcsec'%ccdpix)
# log.info('CCD field: %s arcsec'%(fovpix*ccdpix))
# log.info('CCD format: %s'% fovpix)
r = np.roll(np.roll(ztools.dist(2*ngrid),
ngrid,
axis=0),
ngrid,
axis=1) #distance from grid center, pixs
# # log.debug('INIT: %s %s'%(Rpix,Rpix*eps))
inside = np.bitwise_and( r <= Rpix ,
r >= Rpix*eps )
pupil = np.zeros((2*ngrid,2*ngrid)) # zero array
pupil[inside] = 1
n = inside.size
# x = (findgen(2*ngrid) - ngrid) # replicate(1.,2*ngrid)
x = np.array([(np.arange(2*ngrid) - ngrid)]*2*ngrid) # replicate(1.,2*ngrid)
theta = np.arctan2(x.T,x)
# theta[ngrid]=0.
self.zgrid = np.zeros((2,r[inside].shape[0]))
# print self.zgrid.shape,r[inside].shape,inside.shape,n
flat_inside=[i for i in inside.flat]
# log.debug('flat_inside: %s %s'%(len(flat_inside),self.zgrid.shape))
self.zgrid[0] = r[inside]/Rpix
self.zgrid[1] = theta[inside]
self.inside = inside
self.fovpix = fovpix
self.asperpix = asperpix
self.ccdpix = ccdpix
self.npixperpix = npixperpix
self.Rpix = Rpix
def init(self):
'''
; Pre-compute the parameters and save them in the COMMOM block
:return:
'''
ngrid = self.ngrid
d = self.d
eps = self.eps
alambda = self.alambda
pixel = self.pixel
self.sflag = 0 # fast seeing blur, set to 1 for slow calc.
# Find reasonable limits on the grid parameters
asperpix = 206265.*(1e-6*alambda)/d # maximum fine-pixel size
ccdpix = float(pixel)
k = np.floor(np.log10(ccdpix/asperpix)/np.log10(2.)) +1.
npixperpix = 2**k
fovpix = 2*ngrid/npixperpix # CCD field size
asperpix = ccdpix/npixperpix
size = 206266.*(1e-6*alambda)/asperpix
Rpix = ngrid/size*d
# log.info('Rebinning factor: %s'% npixperpix)
# log.info('Grid pixel: %s arcsec'%asperpix)
# log.info('Grid size: %s m'%size)
# log.info('CCD pixel: %s arcsec'%ccdpix)
# log.info('CCD field: %s arcsec'%(fovpix*ccdpix))
# log.info('CCD format: %s'% fovpix)
r = np.roll(np.roll(ztools.dist(2*ngrid),
ngrid,
axis=0),
ngrid,
axis=1) #distance from grid center, pixs
# # log.debug('INIT: %s %s'%(Rpix,Rpix*eps))
inside = np.bitwise_and( r <= Rpix ,
r >= Rpix*eps )
pupil = np.zeros((2*ngrid,2*ngrid)) # zero array
pupil[inside] = 1
n = inside.size
# x = (findgen(2*ngrid) - ngrid) # replicate(1.,2*ngrid)
x = np.array([(np.arange(2*ngrid) - ngrid)]*2*ngrid) # replicate(1.,2*ngrid)
theta = np.arctan2(x.T,x)
# theta[ngrid]=0.
self.zgrid = np.zeros((2,r[inside].shape[0]))
# print self.zgrid.shape,r[inside].shape,inside.shape,n
flat_inside=[i for i in inside.flat]
# log.debug('flat_inside: %s %s'%(len(flat_inside),self.zgrid.shape))
self.zgrid[0] = r[inside]/Rpix
self.zgrid[1] = theta[inside]
self.inside = inside
self.fovpix = fovpix
self.asperpix = asperpix
self.ccdpix = ccdpix
self.npixperpix = npixperpix
self.Rpix = Rpix
def newimage(self, a, jzer):
'''
a is the amplitude change of aberration (micron), Jzer is the Zernike number
(1=seeing, 4=focus etc.)
:param a:
:param jzer:
:return:
'''
#COMMON imagedata, uampl, filter2, seeing
newampl = np.array(self.uampl, copy=True)
if (jzer > 1): # Change Zernike coefficient
newphase = 2. * np.pi / self.alambda * a * ztools.zernike_estim(
jzer, self.zgrid)
tmp = np.zeros_like(newphase, dtype=np.complex)
tmp += np.cos(newphase)
tmp += np.sin(newphase) * np.complex(0., 1.)
newampl[self.inside] *= tmp
filter = self.filter2
else: # new seeing
newseeing = self.seeing + a
if (self.sflag > 0):
filter = np.exp(
-2. * np.pi**2 *
(newseeing / 2.35 / self.asperpix / 2 / self.ngrid)**2 *
self.r**2) # unbinned image
else:
rr = ztools.shift(ztools.dist(self.fovpix), self.fovpix / 2,
self.fovpix / 2)
filter = np.exp(
-2. * np.pi**2 *
(newseeing / 2.35 / self.ccdpix / self.fovpix)**2 *
rr**2) # binned image
#--------- compute the image ----------------------
imh = np.abs(
ztools.shift(
np.fft.ifft2(ztools.shift(newampl, self.ngrid, self.ngrid)),
self.ngrid, self.ngrid))**2
# imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(newampl,self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2)),self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2))**2.
if (self.sflag > 0): # exact seing blur
imh = np.abs(
np.fft2(
ztools.shift(np.fft.fft2(imh), self.ngrid, self.ngrid) *
filter))
impix = ztools.rebin(
imh, [self.fovpix, self.fovpix]) # rebinning into CCD pixels
else:
impix = ztools.rebin(
imh, [self.fovpix, self.fovpix]) # rebinning into CCD pixels
impix = np.abs(
np.fft.fft2(
ztools.shift(np.fft.fft2(impix), self.fovpix / 2,
self.fovpix / 2) * filter)) # Seeing blur
return impix / np.sum(impix)
def getimage(self,z):
'''
:param z: the Zernike vector in microns, starting from Z=2 (tip)
z[0] is seeing in arcseconds
:return:
'''
#COMMON imagedata, uampl, filter2, seeing
fact = 2.*np.pi/self.alambda
nzer = len(z)
phase = np.zeros_like(self.zgrid[0]) # empty array for phase
for j in range(1, nzer):
phase += fact*z[j]*ztools.zernike_estim(j+1,self.zgrid)
# # log.debug('GETIMAGE: %s %s'%(phase[0],phase[-1]))
# exit(0)
uampl = np.zeros((self.ngrid*2,self.ngrid*2),dtype=np.complex)
#uampl = np.complex(tmp, tmp)
self.uampl = uampl
uampl[self.inside] += np.cos(phase) #,
uampl[self.inside] += (np.sin(phase)*np.complex(0,1))
#uampl[np.bitwise_not(self.inside)] = 0.
self.seeing = z[0]
#--------- compute the image ----------------------
# imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(uampl,self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2)),self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2))**2.
imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(uampl,self.ngrid,self.ngrid)),self.ngrid,self.ngrid))**2.
if (self.sflag > 0): # exact seeing blur
filter2 = np.exp(-2.*np.pi**2*(self.seeing/2.35/self.asperpix/2/self.ngrid)**2*self.r**2) # unbinned image
imh = np.abs(np.fft2(ztools.shift(np.fft2(imh),self.ngrid,self.ngrid)*filter2))
impix = ztools.rebin(imh,(self.fovpix,self.fovpix)) # rebinning into CCD pixels
else:
rr = ztools.shift(ztools.dist(self.fovpix),self.fovpix/2,self.fovpix/2)
filter2 = np.exp(-2.*np.pi**2*(self.seeing/2.35/self.ccdpix/self.fovpix)**2*rr**2) # binned image
impix = ztools.rebin(imh,[self.fovpix,self.fovpix]) # rebinning into CCD pixels
impix = np.abs(np.fft.fft2(ztools.shift(np.fft.fft2(impix),self.fovpix/2,self.fovpix/2)*filter2)) # Seeing blur
self.filter2 = filter2
return impix/np.sum(impix)
def getimage(self,z):
'''
:param z: the Zernike vector in microns, starting from Z=2 (tip)
z[0] is seeing in arcseconds
:return:
'''
#COMMON imagedata, uampl, filter2, seeing
fact = 2.*np.pi/self.alambda
nzer = len(z)
phase = np.zeros_like(self.zgrid[0]) # empty array for phase
for j in range(1, nzer):
phase += fact*z[j]*ztools.zernike_estim(j+1,self.zgrid)
# # log.debug('GETIMAGE: %s %s'%(phase[0],phase[-1]))
# exit(0)
uampl = np.zeros((self.ngrid*2,self.ngrid*2),dtype=np.complex)
#uampl = np.complex(tmp, tmp)
self.uampl = uampl
uampl[self.inside] += np.cos(phase) #,
uampl[self.inside] += (np.sin(phase)*np.complex(0,1))
#uampl[np.bitwise_not(self.inside)] = 0.
self.seeing = z[0]
#--------- compute the image ----------------------
# imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(uampl,self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2)),self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2))**2.
imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(uampl,self.ngrid,self.ngrid)),self.ngrid,self.ngrid))**2.
if (self.sflag > 0): # exact seeing blur
filter2 = np.exp(-2.*np.pi**2*(self.seeing/2.35/self.asperpix/2/self.ngrid)**2*self.r**2) # unbinned image
imh = np.abs(np.fft2(ztools.shift(np.fft2(imh),self.ngrid,self.ngrid)*filter2))
impix = ztools.rebin(imh,(self.fovpix,self.fovpix)) # rebinning into CCD pixels
else:
rr = ztools.shift(ztools.dist(self.fovpix),self.fovpix/2,self.fovpix/2)
filter2 = np.exp(-2.*np.pi**2*(self.seeing/2.35/self.ccdpix/self.fovpix)**2*rr**2) # binned image
impix = ztools.rebin(imh,[self.fovpix,self.fovpix]) # rebinning into CCD pixels
impix = np.abs(np.fft.fft2(ztools.shift(np.fft.fft2(impix),self.fovpix/2,self.fovpix/2)*filter2)) # Seeing blur
self.filter2 = filter2
return impix/np.sum(impix)
def newimage(self, a, jzer):
'''
a is the amplitude change of aberration (micron), Jzer is the Zernike number
(1=seeing, 4=focus etc.)
:param a:
:param jzer:
:return:
'''
#COMMON imagedata, uampl, filter2, seeing
newampl = np.array(self.uampl,copy=True)
if (jzer > 1): # Change Zernike coefficient
newphase = 2.*np.pi/self.alambda*a*ztools.zernike_estim(jzer,self.zgrid)
tmp = np.zeros_like(newphase,dtype=np.complex)
tmp += np.cos(newphase)
tmp += np.sin(newphase)*np.complex(0.,1.)
newampl[self.inside] *= tmp
filter = self.filter2
else: # new seeing
newseeing = self.seeing + a
if (self.sflag > 0):
filter = np.exp(-2.*np.pi**2*(newseeing/2.35/self.asperpix/2/self.ngrid)**2*self.r**2) # unbinned image
else:
rr = ztools.shift(ztools.dist(self.fovpix),self.fovpix/2,self.fovpix/2)
filter = np.exp(-2.*np.pi**2*(newseeing/2.35/self.ccdpix/self.fovpix)**2*rr**2) # binned image
#--------- compute the image ----------------------
imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(newampl,self.ngrid,self.ngrid)),self.ngrid,self.ngrid))**2
# imh = np.abs(ztools.shift(np.fft.ifft2(ztools.shift(newampl,self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2)),self.ngrid+self.fovpix/2,self.ngrid+self.fovpix/2))**2.
if (self.sflag > 0): # exact seing blur
imh = np.abs(np.fft2(ztools.shift(np.fft.fft2(imh),self.ngrid,self.ngrid)*filter))
impix = ztools.rebin(imh,[self.fovpix,self.fovpix]) # rebinning into CCD pixels
else:
impix = ztools.rebin(imh,[self.fovpix,self.fovpix]) # rebinning into CCD pixels
impix = np.abs(np.fft.fft2(ztools.shift(np.fft.fft2(impix),self.fovpix/2,self.fovpix/2)*filter)) # Seeing blur
return impix/np.sum(impix)