def diagnostics(path, maskset):
'''
Compute the standard deviation in a speckle measurement
'''
mask = maskset.mask
rawrefpix = fdio.read(os.path.join(path, '0.rawframe'))
refcube = combine.separate_pixelated(rawrefpix)
rawpix = fdio.read(os.path.join(path, '1.rawframe'))
phasecube = combine.separate_pixelated(rawpix)
diffim = doit_speckle(os.path.join(path, '1.rawframe'),
maskset,
refcube,
0,
output=False)[0]
mdiffim = diffim[maskset.mask]
sat = (rawpix > 250).sum()
b0, b90, b180, b270 = refcube
m0, m90, m180, m270 = phasecube
Nm = m270 - m90
Dm = m0 - m180
Nb = b270 - b90
Db = b0 - b180
numerator = Nm * Db - Dm * Nb
denominator = Dm * Db + Nm * Nb
nmaskpoints = mask.astype(np.int32).sum()
average_intensity = (
(refcube + phasecube).sum(axis=0) * mask).sum() / (2 * nmaskpoints)
modulation = np.sqrt(numerator**2 + denominator**2) / 2
avg_mod = (modulation * mask).sum() / nmaskpoints
return mdiffim.std(), sat, avg_mod / average_intensity
def doit_speckle(inpath,
maskset,
refcube,
prevrefphase,
windowsize=5,
output=True):
'''
take a single raw image, compute wrapped phase, spatially unwrap,
temporally unwrap, fit zernikes, save unwrapped image, zernike results
and reference point value to disk.
'''
if output:
print("processing ", inpath, windowsize)
center = maskset.center
rawframe = fdio.read(inpath)
cube = combine.separate_pixelated(rawframe)
phase = calcPhaseDiff(refcube, cube, windowsize)
unwrapped = unwrap(phase) * maskset.mask
refphase = (unwrapped * maskset.mask).sum() / maskset.mask.astype(
np.int64).sum()
phasecorr = temporal_correction(prevrefphase, refphase)
unwrapped -= phasecorr
y, x = maskset.indices
radius = maskset.radius
zcoeff = zernike.fit_gzernike(x, y, unwrapped[maskset.indices], 10, center,
radius)
return unwrapped, zcoeff, unwrapped[center[1], center[0]]
def sdiff(maskset):
refcube = combine.separate_pixelated(
fdio.read(os.path.join('.', '0.rawframe')))
diffim = doit_speckle(os.path.join('.', '1.rawframe'),
maskset,
refcube,
0,
output=False)[0]
return diffim
def doall_speckle_rebaseline(inpath, maskfile, rebaseline=1000):
'''
Here inpath is the basic directory that contains all the associated data.
/raw is appended to it to get to the raw data. Results are stored in the
results subdirectory.
'''
globpat = os.path.join(inpath, '*.rawframe')
filelist = glob.glob(globpat)
# filelist = glob.glob(os.path.join(inpath, 'raw/frame_*.dat'))
# Given the variable number length, sorting is more complex
filenum = [int(os.path.split(item)[1].split('.')[0]) for item in filelist]
print(filenum)
zlist = list(zip(filenum, filelist))
zlist.sort()
filelist = [item[1] for item in zlist]
print(filelist)
mask = hsio.read(maskfile)[1]
maskset = MaskSet(mask, center=(240, 240), radius=180)
outdir = os.path.join(inpath, '000_results')
if not os.path.exists(outdir):
os.mkdir(outdir)
print(outdir)
zlist = []
niter = len(filelist) // rebaseline
print('niter:', niter)
tfilelist = filelist.copy()
tfilelist.append('bozo') # just to allow slicing to work on the last iter
for i in range(niter):
for j in range(5):
print(50 * '*')
rfilelist = tfilelist[i * rebaseline:(i + 1) * rebaseline + 1]
rawref = fdio.read(rfilelist[0])
refcube = combine.separate_pixelated(rawref)
prevrefphase = 0
zmatrix = np.zeros((rebaseline + 1, 10))
zresfile = open(outdir + '/zernikes.txt', 'w')
for i, rfile in enumerate(rfilelist):
if rfile == 'bozo':
break
print(i, rfile)
uim, zcoeff, rphase = doit_speckle(rfile, maskset, refcube,
prevrefphase)
zmatrix[i] = zcoeff
zlist.append(zmatrix)
# now splice segments together
szmatrix = np.zeros((len(filelist) + 1, 10))
szmatrix[0:rebaseline + 1, :] = zlist[0]
for i in range(niter - 1):
szmatrix[(i + 1) * rebaseline:(i + 2) * rebaseline +
1, :] = szmatrix[(i + 1) * rebaseline, :] + zlist[i + 1]
szresfile = open(outdir + '/szernikes.txt', 'w')
for i in range(len(filelist)):
szresfile.write(10 * '%e,' % tuple(szmatrix[i, :]) + '\n')
szresfile.close()
def doall_speckle(inpath, maskset, range=None, suffix=''):
'''
Here inpath is the basic directory that contains all the associated data.
/raw is appended to it to get to the raw data. Results are stored in the
results subdirectory.
'''
globpat = os.path.join(inpath, '*.rawframe')
filelist = glob.glob(globpat)
# filelist = glob.glob(os.path.join(inpath, 'raw/frame_*.dat'))
# Given the variable number length, sorting is more complex
filenum = [int(os.path.split(item)[1].split('.')[0]) for item in filelist]
print(filenum)
zlist = list(zip(filenum, filelist))
zlist.sort()
filelist = [item[1] for item in zlist]
if range is not None:
filelist = filelist[range[0]:range[1]]
foffset = range[0]
else:
foffset = 0
reffile = filelist[0]
print(filelist)
mask = maskset.mask
#mask = hsio.read(maskfile)[1]
rawref = fdio.read(os.path.join(inpath, '0.rawframe'))
refcube = combine.separate_pixelated(rawref)
outdir = os.path.join(inpath, '000_results')
if not os.path.exists(outdir):
os.mkdir(outdir)
print(outdir)
# maskset = MaskSet(mask, center=(240, 240), radius=180)
prevrefphase = 0
zmatrix = np.zeros((len(filelist), 10))
refphase = np.zeros((len(filelist), ))
if range is None:
zresfile = open(outdir + '/zernikes{}.txt'.format(suffix), 'w')
presfile = open(outdir + '/phasetimeseries{}.txt'.format(suffix), 'w')
else:
zresfile = open(outdir + '/p_zernikes%s%03d.txt' % (suffix, foffset),
'w')
presfile = open(
outdir + '/p_phasetimeseries%s%03d.txt' % (suffix, foffset), 'w')
for i, rfile in enumerate(filelist):
print(i + foffset, rfile)
uim, zcoeff, rphase = doit_speckle(rfile, maskset, refcube,
prevrefphase)
zmatrix[i] = zcoeff
refphase[i] = rphase
zresfile.write(10 * '%e,' % tuple(zcoeff) + '\n')
presfile.write(str(rphase) + '\n')
zresfile.close()
presfile.close()
def doit_new(inpath, maskset, prevrefphase=None):
'''
take a single raw image, compute wrapped phase, spatially unwrap,
temporally unwrap, fit zernikes, save unwrapped image, zernike results
and reference point value to disk.
'''
print("processing ", inpath)
center = maskset.center
rawframe = fdio.read(inpath)
unwrapped = unwrap_raw_frame(rawframe, mask=maskset.mask)
refphase = unwrapped[center[1], center[0]]
phasecorr = temporal_correction(prevrefphase, refphase)
unwrapped -= phasecorr
y, x = maskset.indices
radius = maskset.radius
zcoeff = zernike.fit_gzernike(x, y, unwrapped[maskset.indices], 10, center,
radius)
return unwrapped, zcoeff, unwrapped[center[1], center[0]]