def get_neighbours(nside,theta,phi=None,nest=False):
"""Return the 4 nearest pixels and corresponding weights.
Parameters
----------
nside : int
the healpix nside
theta, phi : float, scalar or array-like
if phi is not given, theta is interpreted as pixel number,
otherwise theta[rad],phi[rad] are angular coordinates
nest : bool
if ``True``, NESTED ordering, otherwise RING ordering.
Returns
-------
res : tuple of length 2
contains pixel numbers in res[0] and weights in res[1].
Usual numpy broadcasting rules apply.
See Also
--------
get_interp_val, get_all_neighbours
Examples
--------
>>> import healpy as hp
>>> hp.get_neighbours(1, 0)
(array([0, 1, 4, 5]), array([ 1., 0., 0., 0.]))
>>> hp.get_neighbours(1, 0, 0)
(array([1, 2, 3, 0]), array([ 0.25, 0.25, 0.25, 0.25]))
>>> hp.get_neighbours(1, [0, np.pi/2], 0)
(array([[ 1, 4],
[ 2, 5],
[ 3, 11],
[ 0, 8]]), array([[ 0.25, 1. ],
[ 0.25, 0. ],
[ 0.25, 0. ],
[ 0.25, 0. ]]))
"""
if not isnsideok(nside):
raise ValueError('Wrong nside value. Must be a power of 2.')
if phi == None:
theta,phi = pix2ang(nside,theta,nest=nest)
if nest:
r=pixlib._get_interpol_nest(nside,theta,phi)
else:
r=pixlib._get_interpol_ring(nside,theta,phi)
p=np.array(r[0:4])
w=np.array(r[4:8])
return (p,w)
def get_neighbours(nside,theta,phi=None,nest=False):
"""Return the 4 nearest pixels and corresponding weights.
Parameters
----------
nside : int
the healpix nside
theta, phi : float, scalar or array-like
if phi is not given, theta is interpreted as pixel number,
otherwise theta[rad],phi[rad] are angular coordinates
nest : bool
if ``True``, NESTED ordering, otherwise RING ordering.
Returns
-------
res : tuple of length 2
contains pixel numbers in res[0] and weights in res[1].
Usual numpy broadcasting rules apply.
See Also
--------
get_interp_val, get_all_neighbours
Examples
--------
>>> import healpy as hpy
>>> hpy.get_neighbours(1, 0)
(array([0, 1, 4, 5]), array([ 1., 0., 0., 0.]))
>>> hpy.get_neighbours(1, 0, 0)
(array([1, 2, 3, 0]), array([ 0.25, 0.25, 0.25, 0.25]))
>>> hpy.get_neighbours(1, [0, npy.pi/2], 0)
(array([[ 1, 4],
[ 2, 5],
[ 3, 11],
[ 0, 8]]), array([[ 0.25, 1. ],
[ 0.25, 0. ],
[ 0.25, 0. ],
[ 0.25, 0. ]]))
"""
if not isnsideok(nside):
raise ValueError('Wrong nside value. Must be a power of 2.')
if phi == None:
theta,phi = pix2ang(nside,theta,nest=nest)
if nest:
r=pixlib._get_interpol_nest(nside,theta,phi)
else:
r=pixlib._get_interpol_ring(nside,theta,phi)
p=npy.array(r[0:4])
w=npy.array(r[4:8])
return (p,w)
def get_interp_val(m,theta,phi,nest=False):
"""Return the bi-linear interpolation value of a map at given direction.
Input:
- m: a map (an ndarray)
- theta, phi : the direction [rad] (either scalar or arrays of same size)
Parameters:
- nest: if True, the map is in NEST scheme. Default: False (ie RING)
Return:
- the interpolated value(s)
"""
m2=m.ravel()
nside=npix2nside(m2.size)
if nest:
r=pixlib._get_interpol_nest(nside,theta,phi)
else:
r=pixlib._get_interpol_ring(nside,theta,phi)
p=npy.array(r[0:4])
w=npy.array(r[4:8])
del r
return npy.sum(m2[p]*w,0)
def get_interp_val(m, theta, phi, nest=False):
"""Return the bi-linear interpolation value of a map at given direction.
Input:
- m: a map (an ndarray)
- theta, phi : the direction [rad] (either scalar or arrays of same size)
Parameters:
- nest: if True, the map is in NEST scheme. Default: False (ie RING)
Return:
- the interpolated value(s)
"""
m2 = m.ravel()
nside = npix2nside(m2.size)
if nest:
r = pixlib._get_interpol_nest(nside, theta, phi)
else:
r = pixlib._get_interpol_ring(nside, theta, phi)
p = npy.array(r[0:4])
w = npy.array(r[4:8])
del r
return npy.sum(m2[p] * w, 0)
def get_interp_val(m, theta, phi, nest=False):
"""Return the bi-linear interpolation value of a map using 4 nearest neighbours.
Parameters
----------
m : array-like
an healpix map, accepts masked arrays
theta, phi : float, scalar or array-like
angular coordinates of point at which to interpolate the map
nest : bool
if True, the is assumed to be in NESTED ordering.
Returns
-------
val : float, scalar or arry-like
the interpolated value(s), usual numpy broadcasting rules apply.
See Also
--------
get_neighbours, get_all_neighbours
Examples
--------
>>> import healpy as hp
>>> hp.get_interp_val(np.arange(12.), np.pi/2, 0)
4.0
>>> hp.get_interp_val(np.arange(12.), np.linspace(0, np.pi, 10), 0)
array([ 1.5 , 1.5 , 1.5 , 2.20618428, 3.40206143,
5.31546486, 7.94639458, 9.5 , 9.5 , 9.5 ])
"""
m2 = m.ravel()
nside = npix2nside(m2.size)
if nest:
r = pixlib._get_interpol_nest(nside, theta, phi)
else:
r = pixlib._get_interpol_ring(nside, theta, phi)
p = np.array(r[0:4])
w = np.array(r[4:8])
del r
return np.sum(m2[p] * w, 0)
def get_interp_val(m,theta,phi,nest=False):
"""Return the bi-linear interpolation value of a map using 4 nearest neighbours.
Parameters
----------
m : array-like
an healpix map
theta, phi : float, scalar or array-like
angular coordinates of point at which to interpolate the map
nest : bool
if True, the is assumed to be in NESTED ordering.
Returns
-------
val : float, scalar or arry-like
the interpolated value(s), usual numpy broadcasting rules apply.
See Also
--------
get_neighbours, get_all_neighbours
Examples
--------
>>> import healpy as hpy
>>> hpy.get_interp_val(npy.arange(12.), npy.pi/2, 0)
4.0
>>> hpy.get_interp_val(npy.arange(12.), npy.linspace(0, npy.pi, 10), 0)
array([ 1.5 , 1.5 , 1.5 , 2.20618428, 3.40206143,
5.31546486, 7.94639458, 9.5 , 9.5 , 9.5 ])
"""
m2=m.ravel()
nside=npix2nside(m2.size)
if nest:
r=pixlib._get_interpol_nest(nside,theta,phi)
else:
r=pixlib._get_interpol_ring(nside,theta,phi)
p=npy.array(r[0:4])
w=npy.array(r[4:8])
del r
return npy.sum(m2[p]*w,0)
def get_neighbours(nside,theta,phi=None,nest=False):
"""Return the 4 nearest pixels and the corresponding weights for
bi-linear interpolation for the given direction.
Input:
- nside: the nside to work with
- theta, phi: if phi is not given, theta is actually a pixel number
if phi is given, theta[rad],phi[rad] is a direction
Parameters:
- nest: if True, NEST scheme. Default: False (RING)
Return:
- tuple of pixels and weights
"""
if not isnsideok(nside):
raise ValueError('Wrong nside value. Must be a power of 2.')
if phi == None:
theta,phi = pix2ang(nside,theta,nest=nest)
if nest:
r=pixlib._get_interpol_nest(nside,theta,phi)
else:
r=pixlib._get_interpol_ring(nside,theta,phi)
p=npy.array(r[0:4])
w=npy.array(r[4:8])
return (p,w)
def get_neighbours(nside, theta, phi=None, nest=False):
"""Return the 4 nearest pixels and the corresponding weights for
bi-linear interpolation for the given direction.
Input:
- nside: the nside to work with
- theta, phi: if phi is not given, theta is actually a pixel number
if phi is given, theta[rad],phi[rad] is a direction
Parameters:
- nest: if True, NEST scheme. Default: False (RING)
Return:
- tuple of pixels and weights
"""
if not isnsideok(nside):
raise ValueError('Wrong nside value. Must be a power of 2.')
if phi == None:
theta, phi = pix2ang(nside, theta, nest=nest)
if nest:
r = pixlib._get_interpol_nest(nside, theta, phi)
else:
r = pixlib._get_interpol_ring(nside, theta, phi)
p = npy.array(r[0:4])
w = npy.array(r[4:8])
return (p, w)
