def zoomFourier(arr, factor, use_abs=False):
shape = N.array(arr.shape)
target = [int(s) for s in shape * factor]
#target[-1] //= 2
#target[-1] += 1
af = F.fft(arr)
ap = paddingFourier(af, target)
afp = F.ifft(ap)
factor = target / shape
if use_abs:
return N.abs(afp) * N.product(factor)
else:
return N.real(afp) * N.product(factor)
def zoomFourier(arr, factor, use_abs=False):
shape = N.array(arr.shape)
target = [int(s) for s in shape * factor]
#target[-1] //= 2
#target[-1] += 1
af = F.fft(arr)
ap = paddingFourier(af, target)
afp = F.ifft(ap)
factor = target / shape
if use_abs:
return N.abs(afp) * N.product(factor)
else:
return N.real(afp) * N.product(factor)
def rotateIndicesND(slicelist, dtype=N.float64, rot=0, mode=2):
"""
slicelist: even shape works much better than odd shape
rot: counter-clockwise, xy-plane
mode: testing different ways of doing, (1 or 2 and the same result)
return inds, LD
"""
global INDS_DIC
shape = []
LD = []
for sl in slicelist:
if isinstance(sl, slice):
shape.append(sl.stop - sl.start)
LD.append(sl.start)
shapeTuple = tuple(shape + [rot])
if shapeTuple in INDS_DIC:
inds = INDS_DIC[shapeTuple]
else:
shape = N.array(shape)
ndim = len(shape)
odd_even = shape % 2
s2 = N.ceil(shape * (2**0.5))
if mode == 1: # everything is even
s2 = N.where(s2 % 2, s2 + 1, s2)
elif mode == 2: # even & even or odd & odd
for d, s in enumerate(shape):
if (s % 2 and not s2[d] % 2) or (not s % 2 and s2[d] % 2):
s2[d] += 1
cent = s2 / 2.
dif = (s2 - shape) / 2.
dm = dif % 1
# print s2, cent, dif, dm
slc = [Ellipsis] + [
slice(int(d),
int(d) + shape[i]) for i, d in enumerate(dif)
]
# This slice is float which shift array when cutting out!!
s2 = tuple([int(ss)
for ss in s2]) # numpy array cannot use used for slice
inds = N.indices(s2, N.float32)
ind_shape = inds.shape
nz = N.product(ind_shape[:-2])
nsec = nz / float(ndim)
if ndim > 2:
inds = N.reshape(inds, (nz, ) + ind_shape[-2:])
irs = N.empty_like(inds)
for d, ind in enumerate(inds):
idx = int(d // nsec)
c = cent[idx]
if rot and inds.ndim > 2:
U.trans2d(ind - c, irs[d], (0, 0, rot, 1, 0, 1))
irs[d] += c - dif[idx]
else:
irs[d] = ind - dif[idx]
if len(ind_shape) > 2:
irs = N.reshape(irs, ind_shape)
irs = irs[slc]
if mode == 1 and N.sometrue(dm):
inds = N.empty_like(irs)
# print 'translate', dm
for d, ind in enumerate(irs):
U.trans2d(ind, inds[d], (-dm[1], -dm[0], 0, 1, 0, 1))
else:
inds = irs
INDS_DIC[shapeTuple] = inds
r_inds = N.empty_like(inds)
for d, ld in enumerate(LD):
r_inds[d] = inds[d] + ld
return r_inds, LD
def rotateIndicesND(slicelist, dtype=N.float64, rot=0, mode=2):
"""
slicelist: even shape works much better than odd shape
rot: counter-clockwise, xy-plane
mode: testing different ways of doing, (1 or 2 and the same result)
return inds, LD
"""
global INDS_DIC
shape = []
LD = []
for sl in slicelist:
if isinstance(sl, slice):
shape.append(sl.stop - sl.start)
LD.append(sl.start)
shapeTuple = tuple(shape+[rot])
if shapeTuple in INDS_DIC:
inds = INDS_DIC[shapeTuple]
else:
shape = N.array(shape)
ndim = len(shape)
odd_even = shape % 2
s2 = N.ceil(shape * (2**0.5))
if mode == 1: # everything is even
s2 = N.where(s2 % 2, s2 + 1, s2)
elif mode == 2: # even & even or odd & odd
for d, s in enumerate(shape):
if (s % 2 and not s2[d] % 2) or (not s % 2 and s2[d] % 2):
s2[d] += 1
cent = s2 / 2.
dif = (s2 - shape) / 2.
dm = dif % 1
# print s2, cent, dif, dm
slc = [Ellipsis] + [slice(int(d), int(d)+shape[i]) for i, d in enumerate(dif)]
# This slice is float which shift array when cutting out!!
s2 = tuple([int(ss) for ss in s2]) # numpy array cannot use used for slice
inds = N.indices(s2, N.float32)
ind_shape = inds.shape
nz = N.product(ind_shape[:-2])
nsec = nz / float(ndim)
if ndim > 2:
inds = N.reshape(inds, (nz,)+ind_shape[-2:])
irs = N.empty_like(inds)
for d, ind in enumerate(inds):
idx = int(d//nsec)
c = cent[idx]
if rot and inds.ndim > 2:
U.trans2d(ind - c, irs[d], (0,0,rot,1,0,1))
irs[d] += c - dif[idx]
else:
irs[d] = ind - dif[idx]
if len(ind_shape) > 2:
irs = N.reshape(irs, ind_shape)
irs = irs[slc]
if mode == 1 and N.sometrue(dm):
inds = N.empty_like(irs)
# print 'translate', dm
for d, ind in enumerate(irs):
U.trans2d(ind, inds[d], (-dm[1], -dm[0], 0, 1, 0, 1))
else:
inds = irs
INDS_DIC[shapeTuple] = inds
r_inds = N.empty_like(inds)
for d, ld in enumerate(LD):
r_inds[d] = inds[d] + ld
return r_inds, LD
