def test_polar_vectors_numexpr():
""" Check that the the version with numexpr generates the same output """
for nn in range(5):
for mm in range(-1*nn,nn+1):
if (nn%2==0 and abs(mm)%2==0) or (nn%2==1 and abs(mm)%2==1):
res0 = fsh.polar_basis_L(r,nn,mm, beta)*np.exp(-1j*th*mm)
res1 = sh.polarDimBasis(nn,mm, beta)(r,th)
yield assert_allclose, res0, res1, 1e-7, 1e-9
def genPolarBasisFuncs(beta,nmax,phi,fourier=False):
"""Generate a list of basis functions
beta: characteristic size of the shapelets (b_major, b_minor)
nmax: maximum decomposition order
phi: rotation angle
fourier: return a FOurer transformed version of the basis functions
"""
bfs=[]
if type(nmax) is int: nmax=[nmax,nmax]
for nn in range(nmax[0]):
for mm in np.arange(-1*nn,nn+1):
if (nn%2==0 and mm%2==0) or (nn%2==1 and mm%2==1):
bfs.append(shapelet.polarDimBasis(nn,mm,beta=beta,phi=phi,fourier=fourier))
return bfs
def genPolarBasisMatrix(beta,nmax,r,th):
"""Generate the n x k matrix of basis functions(k) for each pixel(n)
beta: characteristic size of the shaeplets
nmax: maximum decomposition order
r: radius matrix of n pixels
th: theta matrix of n pixels
"""
bvals=[]
for nn in range(nmax):
for mm in np.arange(-1*nn,nn+1):
if (nn%2==0 and mm%2==0) or (nn%2==1 and mm%2==1):
bf=shapelet.polarDimBasis(nn,mm,beta=beta)
bvals.append(shapelet.computeBasisPolar(bf,r,th).flatten())
bm=np.array(bvals)
return bm.transpose()
def genPolarBasisMatrix(beta,nmax,phi,r,th,fourier=False):
"""Generate the n x k matrix of basis functions(k) for each pixel(n)
beta: characteristic size of the shapelets (b_major, b_minor)
nmax: maximum decomposition order
phi: rotation angle
r: radius matrix of n pixels
th: theta matrix of n pixels
fourier: return a FOurer transformed version of the basis functions
"""
bvals=[]
if type(nmax) is int: nmax=[nmax,nmax]
for nn in range(nmax[0]):
for mm in np.arange(-1*nn,nn+1):
if (nn%2==0 and mm%2==0) or (nn%2==1 and mm%2==1):
bf=shapelet.polarDimBasis(nn,mm,beta=beta,phi=phi,fourier=fourier)
bvals.append(shapelet.computeBasisPolar(bf,r,th).flatten())
bm=np.array(bvals)
return bm.transpose()
def genPolarBasisFuncs(beta, nmax, phi, fourier=False):
"""Generate a list of basis functions
beta: characteristic size of the shapelets (b_major, b_minor)
nmax: maximum decomposition order
phi: rotation angle
fourier: return a FOurer transformed version of the basis functions
"""
bfs = []
if type(nmax) is int: nmax = [nmax, nmax]
for nn in range(nmax[0]):
for mm in np.arange(-1 * nn, nn + 1):
if (nn % 2 == 0 and mm % 2 == 0) or (nn % 2 == 1 and mm % 2 == 1):
bfs.append(
shapelet.polarDimBasis(nn,
mm,
beta=beta,
phi=phi,
fourier=fourier))
return bfs
def genPolarBasisMatrix(beta, nmax, phi, r, th, fourier=False):
"""Generate the n x k matrix of basis functions(k) for each pixel(n)
beta: characteristic size of the shapelets (b_major, b_minor)
nmax: maximum decomposition order
phi: rotation angle
r: radius matrix of n pixels
th: theta matrix of n pixels
fourier: return a FOurer transformed version of the basis functions
"""
bvals = []
if type(nmax) is int: nmax = [nmax, nmax]
for nn in range(nmax[0]):
for mm in np.arange(-1 * nn, nn + 1):
if (nn % 2 == 0 and mm % 2 == 0) or (nn % 2 == 1 and mm % 2 == 1):
bf = shapelet.polarDimBasis(nn,
mm,
beta=beta,
phi=phi,
fourier=fourier)
bvals.append(shapelet.computeBasisPolar(bf, r, th).flatten())
bm = np.array(bvals)
return bm.transpose()
