def readConicWFS(fn,interp=None):
"""
Load in data from WFS measurement of cylindrical mirror.
Assumes that data was processed using processHAS, and loaded into
a .fits file.
Scale to microns, remove misalignments,
strip NaNs.
If rotate is set to an array of angles, the rotation angle
which minimizes the number of NaNs in the image after
stripping perimeter nans is selected.
Distortion is bump positive looking at concave surface.
Imshow will present distortion in proper orientation as if
viewing the concave surface.
Returns the data with best fit conic removed, as well as the
coefficients in the conic fit.
"""
#Remove NaNs and rescale
d = pyfits.getdata(fn)
d = man.stripnans(d)
d = d - np.nanmean(d)
# Negate to make bump positive and rotate to be consistent with looking at the part beamside.
#d = -d
d = -np.fliplr(d) #np.rot90(d,k = 2)
#Remove cylindrical misalignment terms
conic_fit = fit.fitConic(d)
d = d - conic_fit[0]
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d,conic_fit[1]
def readFlat4D(fn,interp=None):
"""
Load in data from 4D measurement of flat mirror.
Scale to microns, remove misalignments,
strip NaNs.
Distortion is bump positive looking at surface from 4D.
Imshow will present distortion in proper orientation as if
viewing the surface.
"""
#Get xpix value in mm
l = getline(fn,9)
dx = float(l.split()[1])*1000.
#Remove NaNs and rescale
d = np.genfromtxt(fn,skip_header=12,delimiter=',')
d = man.stripnans(d)
d = d *.6328
d = d - np.nanmean(d)
d = np.fliplr(d)
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d,dx
def readCylWFS(fn, rotate=np.linspace(.75, 1.5, 50), interp=None):
"""
Load in data from WFS measurement of cylindrical mirror.
Assumes that data was processed using processHAS, and loaded into
a .fits file.
Scale to microns, remove misalignments,
strip NaNs.
If rotate is set to an array of angles, the rotation angle
which minimizes the number of NaNs in the image after
stripping perimeter nans is selected.
Distortion is bump positive looking at concave surface.
Imshow will present distortion in proper orientation as if
viewing the concave surface.
"""
#Remove NaNs and rescale
d = pyfits.getdata(fn)
d = man.stripnans(d)
d = d - np.nanmean(d)
#Remove cylindrical misalignment terms
d = d - fit.fitCylMisalign(d)[0]
# Negate to make bump positive.
d = -d
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d, method=interp)
return d
def readCylScript(fn,rotate=np.linspace(.75,1.5,50),interp=None):
"""
Load in data from 4D measurement of cylindrical mirror.
File is assumed to have been saved with Ryan's scripting function.
Scale to microns, remove misalignments,
strip NaNs.
If rotate is set to an array of angles, the rotation angle
which minimizes the number of NaNs in the image after
stripping perimeter nans is selected.
Distortion is bump positive looking at concave surface.
Imshow will present distortion in proper orientation as if
viewing the concave surface.
"""
#Read in values from header
f = open(fn+'.hdr','r')
l = f.readlines()
f.close()
#Wavelength should never change
wave = float(l[0].split()[0])*.001 #in microns
#Ensure wedge factor is 0.5
wedge = float(l[1])
if wedge!=0.5:
print 'Wedge factor is ' + str(wedge)
pdb.set_trace()
#Get pixel scale size
dx = float(l[-1])
#Remove NaNs and rescale
d = np.fromfile(fn+'.bin',dtype=np.float32)
try:
d = d.reshape((1002,981))
except:
d = d.reshape((1003,982))
d[d>1e10] = np.nan
d = man.stripnans(d)
d = d *wave
d = d - np.nanmean(d)
#Remove cylindrical misalignment terms
d = d - fit.fitCylMisalign(d)[0]
#Rotate out CGH roll misalignment?
if rotate is not None:
b = [np.sum(np.isnan(\
man.stripnans(\
nd.rotate(d,a,order=1,cval=np.nan)))) for a in rotate]
d = man.stripnans(\
nd.rotate(d,rotate[np.argmin(b)],order=1,cval=np.nan))
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d,dx
def readFlatScript(fn,interp=None):
"""
Load in data from 4D measurement of flat mirror.
File is assumed to have been saved with Ryan's scripting function.
Scale to microns, remove misalignments,
strip NaNs.
Distortion is bump positive looking at surface from 4D.
Imshow will present distortion in proper orientation as if
viewing the surface.
"""
#Read in values from header
f = open(fn+'.hdr','r')
l = f.readlines()
f.close()
#Wavelength should never change
wave = float(l[0].split()[0])*.001 #in microns
#Ensure wedge factor is 0.5
wedge = float(l[1])
if wedge!=0.5:
print 'Wedge factor is ' + str(wedge)
pdb.set_trace()
#Get pixel scale size
dx = float(l[-1])
#Remove NaNs and rescale
d = np.fromfile(fn+'.bin',dtype=np.float32)
try:
d = d.reshape((1002,981))
except:
d = d.reshape((1003,982))
d[d>1e10] = np.nan
d = man.stripnans(d)
d = d *.6328
d = d - np.nanmean(d)
d = np.fliplr(d)
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d,dx
def readConic4D(fn,rotate=None,interp=None):
"""
Load in data from 4D measurement of cylindrical mirror.
Scale to microns, remove misalignments,
strip NaNs.
If rotate is set to an array of angles, the rotation angle
which minimizes the number of NaNs in the image after
stripping perimeter nans is selected.
Distortion is bump positive looking at concave surface.
Imshow will present distortion in proper orientation as if
viewing the concave surface.
"""
#Get xpix value in mm
l = getline(fn,9)
dx = float(l.split()[1])*1000.
#Remove NaNs and rescale
d = np.genfromtxt(fn,skip_header=12,delimiter=',')
d = man.stripnans(d)
d = d *.6328
d = d - np.nanmean(d)
#d = np.rot90(d,k = 2)
#Remove cylindrical misalignment terms
conic_fit = fit.fitConic(d)
d = d - conic_fit[0]
#Rotate out CGH roll misalignment?
if rotate is not None:
b = [np.sum(np.isnan(\
man.stripnans(\
nd.rotate(d,a,order=1,cval=np.nan)))) for a in rotate]
d = man.stripnans(\
nd.rotate(d,rotate[np.argmin(b)],order=1,cval=np.nan))
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d,dx,conic_fit[1]
def readFlatWFS(fn,interp=None):
"""
Load in data from WFS measurement of flat mirror.
Assumes that data was processed using processHAS, and loaded into
a .fits file.
Scale to microns, strip NaNs.
If rotate is set to an array of angles, the rotation angle
which minimizes the number of NaNs in the image after
stripping perimeter nans is selected.
Distortion is bump positive looking at concave surface.
Imshow will present distortion in proper orientation as if
viewing the concave surface.
"""
#Remove NaNs and rescale
d = pyfits.getdata(fn)
d = man.stripnans(d)
d = -d
#Interpolate over NaNs
if interp is not None:
d = man.nearestNaN(d,method=interp)
return d
