def blkwl(img):
"""Calculate wavelength given an image block"""
f=np.abs(fftshift(fft2(img)))
origin=np.where(f==np.max(f));f[origin]=0;mmax=np.where(f==np.max(f))
wl=2*img.shape[0]/(((origin[0]-mmax[0][0])*2)**2+((origin[1]-mmax[1][0])*2)**2)**0.5
return wl
python类fftshift()的实例源码
def test_definition(self):
x = [0, 1, 2, 3, 4, -4, -3, -2, -1]
y = [-4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
x = [0, 1, 2, 3, 4, -5, -4, -3, -2, -1]
y = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
def test_inverse(self):
for n in [1, 4, 9, 100, 211]:
x = np.random.random((n,))
assert_array_almost_equal(fft.ifftshift(fft.fftshift(x)), x)
def test_axes_keyword(self):
freqs = [[0, 1, 2], [3, 4, -4], [-3, -2, -1]]
shifted = [[-1, -3, -2], [2, 0, 1], [-4, 3, 4]]
assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shifted)
assert_array_almost_equal(fft.fftshift(freqs, axes=0),
fft.fftshift(freqs, axes=(0,)))
assert_array_almost_equal(fft.ifftshift(shifted, axes=(0, 1)), freqs)
assert_array_almost_equal(fft.ifftshift(shifted, axes=0),
fft.ifftshift(shifted, axes=(0,)))
def vecpot(arx,ary,arz, kf, lx=2*np.pi, ly=2*np.pi, lz=2*np.pi):
"""
Function to compute vector potential of a 3D array
"""
nx,ny,nz=arx.shape
# COMPUTE THE ARRAY SIZE
kx, ky, kz, km = create_kgrid(*arx.shape, lx=lx, ly=ly, lz=lz)
#kx, ky, kz, k2 = kx[:,nna,nna],ky[nna,:,nna],kz[nna,nna,:], km**2
k2=km**2
k2[nx/2,ny/2,nz/2]=1.
# FOURIER TRANSFORM THE ARRAY
farx = nf.fftshift(nf.fftn(arx))
fary = nf.fftshift(nf.fftn(ary))
farz = nf.fftshift(nf.fftn(arz))
# SET VALUES ABOVE kf AS 0+0i
farx = (np.sign(km - kf) - 1.)/(-2.)*farx
fary = (np.sign(km - kf) - 1.)/(-2.)*fary
farz = (np.sign(km - kf) - 1.)/(-2.)*farz
# FIND THE CORRESPONDING VECTOR POTENTIAL A = -ik x B /k^2
axf = -eye*(ky*farz-kz*fary)/k2
ayf = -eye*(kz*farx-kx*farz)/k2
azf = -eye*(kx*fary-ky*farx)/k2
# BACK TRANSFORM TO REAL SPACE
ax = np.real(nf.ifftn(nf.ifftshift(axf)))
ay = np.real(nf.ifftn(nf.ifftshift(ayf)))
az = np.real(nf.ifftn(nf.ifftshift(azf)))
return ax,ay,az
def Spec2D(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi):
"""
Spec2D(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi)
2D spectrum of ar perpendicular to axis ax
"""
if len(ar) == 0:
print 'No array provided! Exiting!'
return
ar=ar-np.mean(ar)
nx=np.shape(ar)[0];kx=nf.fftshift(nf.fftfreq(nx))*nx*(2*pi/lenx)
ny=np.shape(ar)[1];ky=nf.fftshift(nf.fftfreq(ny))*ny*(2*pi/leny)
nz=np.shape(ar)[2];kz=nf.fftshift(nf.fftfreq(nz))*nz*(2*pi/lenz)
if ax==0:
k1=ky; k2=kz
elif ax==1:
k1=kx; k2=kz
elif ax==2:
k1=kx; k2=ky
far = nf.fftshift(nf.fftn(ar))/(nx*ny*nz); fftea=0.5*np.abs(far)**2
ffteb=fftea.sum(axis=ax)
return k1,k2,ffteb
##
## 2D SPECTRUM OF A VECTOR
##
def ReducedSpec(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi):
"""
ReducedSpec(ar,ax=2,lenx=2*pi,leny=2*pi,lenz=2*pi)
Reduced spectrum of ar along axis ax
"""
if len(ar) == 0:
print 'No array provided! Exiting!'
return
ar=ar-np.mean(ar)
nx=np.shape(ar)[0];kx=nf.fftshift(nf.fftfreq(nx))*nx*(2*pi/lenx)
ny=np.shape(ar)[1];ky=nf.fftshift(nf.fftfreq(ny))*ny*(2*pi/leny)
nz=np.shape(ar)[2];kz=nf.fftshift(nf.fftfreq(nz))*nz*(2*pi/lenz)
if ax==0:
# Both are one because after the first sum, the new array as dim=2
# First sum along y, then along z
ax1=1; ax2=1
kk=kx; nn=nx
elif ax==1:
# First sum along x (0), then along z (1 for the new configuration)
ax1=0; ax2=1
kk=ky; nn=ny
elif ax==2:
# First sum along x (0), then along y (0 for the new configuration)
ax1=0; ax2=0
kk=kz; nn=nz
far = nf.fftshift(nf.fftn(ar))/(nx*ny*nz); fftea=0.5*np.abs(far)**2
ffteb=fftea.sum(axis=ax1).sum(axis=ax2)
dk = kk[1]-kk[0]
return kk[nn/2:],ffteb[nn/2:]/dk
##
## REDUCED SPECTRUM OF A VECTOR
##
def test_definition(self):
x = [0, 1, 2, 3, 4, -4, -3, -2, -1]
y = [-4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
x = [0, 1, 2, 3, 4, -5, -4, -3, -2, -1]
y = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
def test_inverse(self):
for n in [1, 4, 9, 100, 211]:
x = np.random.random((n,))
assert_array_almost_equal(fft.ifftshift(fft.fftshift(x)), x)
def test_axes_keyword(self):
freqs = [[0, 1, 2], [3, 4, -4], [-3, -2, -1]]
shifted = [[-1, -3, -2], [2, 0, 1], [-4, 3, 4]]
assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shifted)
assert_array_almost_equal(fft.fftshift(freqs, axes=0),
fft.fftshift(freqs, axes=(0,)))
assert_array_almost_equal(fft.ifftshift(shifted, axes=(0, 1)), freqs)
assert_array_almost_equal(fft.ifftshift(shifted, axes=0),
fft.ifftshift(shifted, axes=(0,)))
def test_definition(self):
x = [0, 1, 2, 3, 4, -4, -3, -2, -1]
y = [-4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
x = [0, 1, 2, 3, 4, -5, -4, -3, -2, -1]
y = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
def test_inverse(self):
for n in [1, 4, 9, 100, 211]:
x = np.random.random((n,))
assert_array_almost_equal(fft.ifftshift(fft.fftshift(x)), x)
def test_axes_keyword(self):
freqs = [[0, 1, 2], [3, 4, -4], [-3, -2, -1]]
shifted = [[-1, -3, -2], [2, 0, 1], [-4, 3, 4]]
assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shifted)
assert_array_almost_equal(fft.fftshift(freqs, axes=0),
fft.fftshift(freqs, axes=(0,)))
assert_array_almost_equal(fft.ifftshift(shifted, axes=(0, 1)), freqs)
assert_array_almost_equal(fft.ifftshift(shifted, axes=0),
fft.ifftshift(shifted, axes=(0,)))
def ft2(g, delta):
return fftshift(fft2(fftshift(g))) * (delta ** 2)
test_3dgauss_and_3d_plotting.py 文件源码
项目：CoherentXrayImaging
作者: susannahammarberg
项目源码
文件源码
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def image():
image = misc.imread('star.bmp',flatten=True)
circle = misc.imread('circle.png',flatten=True)
low_values_indices = circle < 200 # Where values are low
circle[low_values_indices] = 0 # All low values set to 0
high_values_indices = circle > 0
circle[high_values_indices] = 1
#image = misc.imread('P.png',flatten=True)
#data = abs(fft.fftshift(fft.fft2(image)))
theta = 10*np.pi / 180 #rad
# nä detta stämmer väl inte
r3 = 1 + 1/np.cos(theta) #antal pixlar som motsvarar 1 pixel i xled i xz systemet
r1 = 1 + 1/ np.sin(theta)
return 0
def test_definition(self):
x = [0, 1, 2, 3, 4, -4, -3, -2, -1]
y = [-4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
x = [0, 1, 2, 3, 4, -5, -4, -3, -2, -1]
y = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
assert_array_almost_equal(fft.fftshift(x), y)
assert_array_almost_equal(fft.ifftshift(y), x)
def test_inverse(self):
for n in [1, 4, 9, 100, 211]:
x = np.random.random((n,))
assert_array_almost_equal(fft.ifftshift(fft.fftshift(x)), x)
def test_axes_keyword(self):
freqs = [[0, 1, 2], [3, 4, -4], [-3, -2, -1]]
shifted = [[-1, -3, -2], [2, 0, 1], [-4, 3, 4]]
assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shifted)
assert_array_almost_equal(fft.fftshift(freqs, axes=0),
fft.fftshift(freqs, axes=(0,)))
assert_array_almost_equal(fft.ifftshift(shifted, axes=(0, 1)), freqs)
assert_array_almost_equal(fft.ifftshift(shifted, axes=0),
fft.ifftshift(shifted, axes=(0,)))
