def nanFilter(af, kernel=3):
"""
3D phase contrast filter often creates 'nan'
this filter removes nan by averaging surrounding pixels
return af
"""
af = af.copy()
shape = N.array(af.shape)
radius = N.subtract(kernel, 1) // 2
box = kernel * af.ndim
nan = N.isnan(af)
nids = N.array(N.nonzero(nan)).T
for nidx in nids:
slc = [slice(idx, idx + 1) for idx in nidx]
slices = []
for dim in range(af.ndim):
slc2 = slice(slc[dim].start - radius, slc[dim].stop + radius)
while slc2.start < 0:
slc2 = slice(slc2.start + 1, slc2.stop)
while slc2.stop > shape[dim]:
slc2 = slice(slc2.start, slc2.stop - 1)
slices.append(slc2)
val = af[slices]
nanlocal = N.isnan(val)
ss = N.sum(N.where(nanlocal, 0, val)) / float((box - N.sum(nanlocal)))
af[slc] = ss
return af
def nanFilter(af, kernel=3):
"""
3D phase contrast filter often creates 'nan'
this filter removes nan by averaging surrounding pixels
return af
"""
af = af.copy()
shape = N.array(af.shape)
radius = N.subtract(kernel, 1) // 2
box = kernel * af.ndim
nan = N.isnan(af)
nids = N.array(N.nonzero(nan)).T
for nidx in nids:
slc = [slice(idx,idx+1) for idx in nidx]
slices = []
for dim in range(af.ndim):
slc2 = slice(slc[dim].start - radius, slc[dim].stop + radius)
while slc2.start < 0:
slc2 = slice(slc2.start + 1, slc2.stop)
while slc2.stop > shape[dim]:
slc2 = slice(slc2.start, slc2.stop -1)
slices.append(slc2)
val = af[slices]
nanlocal = N.isnan(val)
ss = N.sum(N.where(nanlocal, 0, val)) / float((box - N.sum(nanlocal)))
af[slc] = ss
return af
def yGaussian2DR(param, shape, LD, rot=0):
"""
param: (mean, max - mean, y, x, sigma[y], [sigmax], [rot])
shape: (y,x)
rot: scaler (counter clockwise) if len(param) < 7
LD: left down coordinate (offset)
"""
if len(param) == 7:
rot = parm[-1]
sy = 2. * (param[4] * param[4])
sx = 2. * (param[5] * param[5])
# import imgFilters
yx = N.subtract(param[2:4], LD)
# ll.append(yx)
yyi, xxi = rotateIndices2D(shape, rot, yx) # return float64
dist = -(yyi) * (yyi) / sy - (xxi) * (xxi) / sx
return param[0] + param[1] * N.exp(dist)
def yGaussian2DR(param, shape, LD, rot=0):
"""
param: (mean, max - mean, y, x, sigma[y], [sigmax], [rot])
shape: (y,x)
rot: scaler (counter clockwise) if len(param) < 7
LD: left down coordinate (offset)
"""
if len(param) == 7:
rot = parm[-1]
sy = 2. * (param[4]*param[4])
sx = 2. * (param[5]*param[5])
# import imgFilters
yx = N.subtract(param[2:4], LD)
# ll.append(yx)
yyi, xxi = rotateIndices2D(shape, rot, yx) # return float64
dist = -(yyi)*(yyi)/sy -(xxi)*(xxi)/sx
return param[0] + param[1] * N.exp(dist)
def gaussianArr2D(shape=(256,256), sigma=[2.,2.], peakVal=None, orig=None, rot=0):
"""
>1.5x faster implemetation than gaussianArrND
shape: (y,x)
sigma: scaler or [sigmay, sigmax]
orig: (y,x)
rot: scaler anti-clockwise
return N.float32
"""
shape = N.asarray(shape, N.uint)
try:
if len(sigma) == len(shape):
sy = 2*(sigma[0]*sigma[0])
sx = 2*(sigma[1]*sigma[1])
elif len(sigma) == 1:
sx = sy = 2*(sigma[0]*sigma[0])
else:
raise ValueError('sigma must be scaler or [sigmay, sigmax]')
except TypeError: # sigma scaler
sx = sy = 2*(sigma*sigma)
# print y, x
if rot:
yyi, xxi = imgFit.rotateIndices2D(shape, rot, orig, N.float32)
else:
if orig is None:
y, x = shape / 2. - 0.5 # pixel center remove
else:
y, x = N.subtract(orig, 0.5) # pixel center remove
yi, xi = N.indices(shape, dtype=N.float32)
yyi = y-yi
xxi = x-xi
k1 = -(yyi)*(yyi)/(sy) - (xxi)*(xxi)/(sx)
if peakVal:
k0 = peakVal
else:
k0 = 1. / ((sx+sy)/2. * ((2*N.pi)**0.5))
return k0 * N.exp(k1)
def gaussianArr2D(
shape=(256, 256), sigma=[2., 2.], peakVal=None, orig=None, rot=0):
"""
>1.5x faster implemetation than gaussianArrND
shape: (y,x)
sigma: scaler or [sigmay, sigmax]
orig: (y,x)
rot: scaler anti-clockwise
return N.float32
"""
shape = N.asarray(shape, N.uint)
try:
if len(sigma) == len(shape):
sy = 2 * (sigma[0] * sigma[0])
sx = 2 * (sigma[1] * sigma[1])
elif len(sigma) == 1:
sx = sy = 2 * (sigma[0] * sigma[0])
else:
raise ValueError('sigma must be scaler or [sigmay, sigmax]')
except TypeError: # sigma scaler
sx = sy = 2 * (sigma * sigma)
# print y, x
if rot:
yyi, xxi = imgFit.rotateIndices2D(shape, rot, orig, N.float32)
else:
if orig is None:
y, x = shape / 2. - 0.5 # pixel center remove
else:
y, x = N.subtract(orig, 0.5) # pixel center remove
yi, xi = N.indices(shape, dtype=N.float32)
yyi = y - yi
xxi = x - xi
k1 = -(yyi) * (yyi) / (sy) - (xxi) * (xxi) / (sx)
if peakVal:
k0 = peakVal
else:
k0 = 1. / ((sx + sy) / 2. * ((2 * N.pi)**0.5))
return k0 * N.exp(k1)
