def _smoothBorder(arr, start, stop, smooth, value):
"""
start, stop: [z,y,x]
"""
# prepare coordinates
shape = N.array(arr.shape)
start = N.ceil(start).astype(N.int16)
stop = N.ceil(stop).astype(N.int16)
smooth_start = start - smooth
smooth_stop = stop + smooth
smooth_start = N.where(smooth_start < 0, 0, smooth_start)
smooth_stop = N.where(smooth_stop > shape, shape, smooth_stop)
#print smooth_start, smooth_stop
import copy
sliceTemplate = [slice(None, None, None)] * arr.ndim
shapeTemplate = list(shape)
for d in range(arr.ndim):
smooth_shape = shapeTemplate[:d] + shapeTemplate[d + 1:]
# make an array containing the edge value
edges = N.empty([2] + smooth_shape, N.float32)
# start side
slc = copy.copy(sliceTemplate)
slc[d] = slice(start[d], start[d] + 1, None)
edges[0] = arr[slc].reshape(smooth_shape)
# stop side
slc = copy.copy(sliceTemplate)
slc[d] = slice(stop[d] - 1, stop[d], None)
edges[1] = arr[slc].reshape(smooth_shape)
edges = (edges - value) / float(
smooth + 1) # this value can be array??
# both side
for s, side in enumerate([start, stop]):
if s == 0:
rs = range(smooth_start[d], start[d])
rs.sort(reverse=True)
elif s == 1:
rs = range(stop[d], smooth_stop[d])
# smoothing
for f, i in enumerate(rs):
slc = copy.copy(sliceTemplate)
slc[d] = slice(i, i + 1, None)
edgeArr = edges[s].reshape(arr[slc].shape)
#arr[slc] += edgeArr * (smooth - f)
arr[slc] = arr[slc] + edgeArr * (smooth - f) # casting rule
arr = N.ascontiguousarray(arr)
return arr
def img2polar2D(img,
center,
final_radius=None,
initial_radius=None,
phase_width=360):
"""
img: array
center: coordinate y, x
final_radius: ending radius
initial_radius: starting radius
phase_width: npixles / circle
"""
if img.ndim > 2 or len(center) > 2:
raise ValueError, 'this function only support 2D, you entered %i-dim array and %i-dim center coordinate' % (
img.ndim, len(center))
if initial_radius is None:
initial_radius = 0
if final_radius is None:
rad0 = N.ceil(N.array(img.shape) - center)
final_radius = min((min(rad0), min(N.ceil(center))))
if phase_width is None:
phase_width = N.sum(img.shape[-2:]) * 2
theta, R = np.meshgrid(np.linspace(0, 2 * np.pi, phase_width),
np.arange(initial_radius, final_radius))
Ycart, Xcart = polar2cart2D(R, theta, center)
Ycart = N.where(Ycart >= img.shape[0], img.shape[0] - 1, Ycart)
Xcart = N.where(Xcart >= img.shape[1], img.shape[1] - 1, Xcart)
Ycart = Ycart.astype(int)
Xcart = Xcart.astype(int)
polar_img = img[Ycart, Xcart]
polar_img = np.reshape(polar_img,
(final_radius - initial_radius, phase_width))
return polar_img
def getSphericalAbbe(arr3D, kmin=2, kmax=60, plot=False):
"""
compare frequency above and below the focus
return amplitude var(above)/var(below)
"""
afz = getFourierZprofile(arr3D)
# get z profile around the reasonable frequency
aa = N.abs(N.average(afz[:, kmin:kmax], axis=1))
# previously it was N.average(N.abs(afz[:,kmin:kmax]), axis=1), but that seems wrong...
# findMax
inds = N.indices(aa.shape, dtype=N.float64)
v, _0, _1, z = U.findMax(aa)
parm, check = imgFit.fitGaussianND(aa, [z], window=len(aa))
if check == 5:
raise RuntimeError, 'Peak not found check=%i' % check
gg = imgFit.yGaussianND(parm, inds, 3)
amg = aa - gg
z0 = parm[2]
mask = (parm[-1] * 3) / 2. # sigma * 3 / 2
ms0 = N.ceil(z0 - mask)
ms1 = N.ceil(z0 + mask)
amg[ms0:ms1] = 0
below = N.var(amg[:ms0])
above = N.var(amg[ms1:])
if plot:
Y.ploty(N.array((aa, gg, amg)))
print 'below: ', below
print 'above: ', above
print ms0, ms1, z0
return above / (above + below) #above / below
def pointsCutOutND(arr,
posList,
windowSize=100,
sectWise=None,
interpolate=True):
"""
array: nd array
posList: ([(z,)y,x]...)
windowSize: scalar (in pixel or as percent < 1.) or ((z,)y,x)
if arr.ndim > 2, and len(windowSize) == 2, then
cut out section-wise (higher dimensions stay the same)
sectWise: conern only XY of windowSize (higher dimensions stay the same)
interpolate: shift array by subpixel interpolation to adjust center
return: list of array centered at each pos in posList
"""
shape = N.array(arr.shape)
center = shape / 2.
# prepare N-dimensional window size
try:
len(windowSize) # seq
if sectWise:
windowSize = windowSize[-2:]
if len(windowSize) != arr.ndim:
dim = len(windowSize)
windowSize = tuple(shape[:-dim]) + tuple(windowSize)
except TypeError: # scaler
if windowSize < 1 and windowSize > 0: # percentage
w = shape * windowSize
if sectWise:
w[:-2] = shape[:-2]
windowSize = w.astype(N.uint16)
else:
windowSize = N.where(shape >= windowSize, windowSize, shape)
if sectWise:
windowSize = arr.shape[:-2] + windowSize[-2:]
windowSize = N.asarray(windowSize)
# cutout individual position
arrList = []
for pos in posList:
# prepare N-dimensional coordinate
n = len(pos)
if n != len(windowSize):
temp = center.copy()
center[-n:] = pos
pos = center
# calculate idx
ori = pos - (windowSize / 2.) # float value
oidx = N.ceil(ori) # idx
subpxl = oidx - ori # subpixel mod
if interpolate and N.sometrue(subpxl): # comit to make shift
SHIFT = 1
else:
SHIFT = 0
# prepare slice
# when comitted to make shift, first cut out window+1,
# then make subpixle shift, and then cutout 1 edge
slc = [Ellipsis] # Ellipsis is unnecessary, just in case...
slc_edge = [slice(1, -1, None)] * arr.ndim
for d in range(arr.ndim):
start = oidx[d] - SHIFT
if start < 0:
start = 0
slc_edge[d] = slice(0, slc_edge[d].stop, None)
stop = oidx[d] + windowSize[d] + SHIFT
if stop > shape[d]:
stop = shape[d]
slc_edge[d] = slice(slc_edge[d].start, shape[d], None)
slc += [slice(int(start), int(stop), None)]
# cutout, shift and cutout
try:
canvas = arr[slc]
if SHIFT:
canvas = U.nd.shift(canvas, subpxl)
canvas = canvas[slc_edge]
check = 1
except IndexError:
print 'position ', pos, ' was skipped'
check = 0
raise
if check:
arrList += [N.ascontiguousarray(canvas)]
return arrList