def write_map(filename, m, nest=False, dtype=npy.float32, fits_IDL=True):
"""Writes an healpix map into an healpix file.
Input:
- filename: the fits file name
- m: the map to write. Possibly a sequence of 3 maps of same size.
They will be considered as I, Q, U maps
- nest=False: ordering scheme
- fits_IDL = true reshapes columns in rows of 1024, otherwise all the data will
go in one column
"""
if not hasattr(m, "__len__"):
raise TypeError("The map must be a sequence")
# check the dtype and convert it
fitsformat = getformat(dtype)
# print 'format to use: "%s"'%fitsformat
if hasattr(m[0], "__len__"):
# we should have three maps
if len(m) != 3 or len(m[1]) != len(m[0]) or len(m[2]) != len(m[0]):
raise ValueError("You should give 3 maps of same size " "for polarisation...")
nside = pixelfunc.npix2nside(len(m[0]))
if nside < 0:
raise ValueError("Invalid healpix map : wrong number of pixel")
cols = []
colnames = ["I_STOKES", "Q_STOKES", "U_STOKES"]
for cn, mm in zip(colnames, m):
if len(mm) > 1024 and fits_IDL:
# I need an ndarray, for reshape:
mm2 = npy.asarray(mm)
cols.append(pyf.Column(name=cn, format="1024%s" % fitsformat, array=mm2.reshape(mm2.size / 1024, 1024)))
else:
cols.append(pyf.Column(name=cn, format="%s" % fitsformat, array=mm))
else: # we write only one map
nside = pixelfunc.npix2nside(len(m))
if nside < 0:
raise ValueError("Invalid healpix map : wrong number of pixel")
if m.size > 1024 and fits_IDL:
cols = [pyf.Column(name="I_STOKES", format="1024%s" % fitsformat, array=m.reshape(m.size / 1024, 1024))]
else:
cols = [pyf.Column(name="I_STOKES", format="%s" % fitsformat, array=m)]
coldefs = pyf.ColDefs(cols)
tbhdu = pyf.new_table(coldefs)
# add needed keywords
tbhdu.header.update("PIXTYPE", "HEALPIX", "HEALPIX pixelisation")
if nest:
ordering = "NESTED"
else:
ordering = "RING"
tbhdu.header.update("ORDERING", ordering, "Pixel ordering scheme, either RING or NESTED")
tbhdu.header.update("EXTNAME", "xtension", "name of this binary table extension")
tbhdu.header.update("NSIDE", nside, "Resolution parameter of HEALPIX")
tbhdu.header.update("FIRSTPIX", 0, "First pixel # (0 based)")
tbhdu.header.update("LASTPIX", pixelfunc.nside2npix(nside) - 1, "Last pixel # (0 based)")
tbhdu.header.update("INDXSCHM", "IMPLICIT", "Indexing: IMPLICIT or EXPLICIT")
tbhdu.writeto(filename, clobber=True)
def write_map(filename,m,nest=False,dtype=np.float32,fits_IDL=True,coord=None):
"""Writes an healpix map into an healpix file.
Parameters
----------
filename : str
the fits file name
m : array or sequence of 3 arrays
the map to write. Possibly a sequence of 3 maps of same size.
They will be considered as I, Q, U maps
nest : bool, optional
If False, ordering scheme is NESTED, otherwise, it is RING. Default: RING.
fits_IDL : bool, optional
If True, reshapes columns in rows of 1024, otherwise all the data will
go in one column. Default: True
coord : str
The coordinate system, typically 'E' for Ecliptic, 'G' for Galactic or 'Q' for Equatorial
"""
if not hasattr(m, '__len__'):
raise TypeError('The map must be a sequence')
# check the dtype and convert it
fitsformat = getformat(dtype)
#print 'format to use: "%s"'%fitsformat
if hasattr(m[0], '__len__'):
# we should have three maps
if len(m) != 3 or len(m[1]) != len(m[0]) or len(m[2]) != len(m[0]):
raise ValueError("You should give 3 maps of same size "
"for polarisation...")
nside = pixelfunc.npix2nside(len(m[0]))
if nside < 0:
raise ValueError('Invalid healpix map : wrong number of pixel')
cols=[]
colnames=['I_STOKES','Q_STOKES','U_STOKES']
for cn,mm in zip(colnames,m):
if len(mm) > 1024 and fits_IDL:
# I need an ndarray, for reshape:
mm2 = np.asarray(mm)
cols.append(pf.Column(name=cn,
format='1024%s'%fitsformat,
array=mm2.reshape(mm2.size/1024,1024)))
else:
cols.append(pf.Column(name=cn,
format='%s'%fitsformat,
array=mm))
else: # we write only one map
nside = pixelfunc.npix2nside(len(m))
if nside < 0:
raise ValueError('Invalid healpix map : wrong number of pixel')
if m.size > 1024 and fits_IDL:
cols = [pf.Column(name='I_STOKES',
format='1024%s'%fitsformat,
array=m.reshape(m.size/1024,1024))]
else:
cols = [pf.Column(name='I_STOKES',
format='%s'%fitsformat,
array=m)]
tbhdu = pf.new_table(cols)
# add needed keywords
tbhdu.header.update('PIXTYPE','HEALPIX','HEALPIX pixelisation')
if nest: ordering = 'NESTED'
else: ordering = 'RING'
tbhdu.header.update('ORDERING',ordering,
'Pixel ordering scheme, either RING or NESTED')
if coord:
tbhdu.header.update('COORD',coord,
'Ecliptic, Galactic or eQuatorial')
tbhdu.header.update('EXTNAME','xtension',
'name of this binary table extension')
tbhdu.header.update('NSIDE',nside,'Resolution parameter of HEALPIX')
tbhdu.header.update('FIRSTPIX', 0, 'First pixel # (0 based)')
tbhdu.header.update('LASTPIX',pixelfunc.nside2npix(nside)-1,
'Last pixel # (0 based)')
tbhdu.header.update('INDXSCHM','IMPLICIT',
'Indexing: IMPLICIT or EXPLICIT')
tbhdu.writeto(filename,clobber=True)
def read_map(filename,field=0,dtype=np.float64,nest=False,hdu=1,h=False,
verbose=False):
"""Read an healpix map from a fits file.
Parameters
----------
filename : str
the fits file name
field : int or tuple of int, optional
The column to read. Default: 0.
By convention 0 is temperature, 1 is Q, 2 is U.
Field can be a tuple to read multiple columns (0,1,2)
dtype : data type, optional
Force the conversion to some type. Default: np.float64
nest : bool, optional
If True return the map in NEST ordering, otherwise in RING ordering;
use fits keyword ORDERING to decide whether conversion is needed or not
If None, no conversion is performed.
hdu : int, optional
the header number to look at (start at 0)
h : boo, optional
If True, return also the header. Default: False.
verbose : bool, optional
If True, print a number of diagnostic messages
Returns
-------
m | (m0, m1, ...) [, header] : array or a tuple of arrays, optionally with header appended
The map(s) read from the file, and the header if *h* is True.
"""
hdulist=pf.open(filename)
#print hdulist[1].header
nside = hdulist[hdu].header.get('NSIDE')
if nside is None:
warnings.warn("No NSIDE in the header file : will use length of array",
HealpixFitsWarning)
else:
nside = int(nside)
if verbose: print 'NSIDE = %d'%nside
if not pixelfunc.isnsideok(nside):
raise ValueError('Wrong nside parameter.')
ordering = hdulist[hdu].header.get('ORDERING','UNDEF').strip()
if ordering == 'UNDEF':
ordering = (nest and 'NESTED' or 'RING')
warnings.warn("No ORDERING keyword in header file : "
"assume %s"%ordering)
if verbose: print 'ORDERING = %s in fits file'%ordering
sz=pixelfunc.nside2npix(nside)
if not hasattr(field, '__len__'):
field = (field,)
ret = []
for ff in field:
m=hdulist[hdu].data.field(ff).astype(dtype).ravel()
if (not pixelfunc.isnpixok(m.size) or (sz>0 and sz != m.size)) and verbose:
print 'nside=%d, sz=%d, m.size=%d'%(nside,sz,m.size)
raise ValueError('Wrong nside parameter.')
if not nest is None: # no conversion with None
if nest and ordering == 'RING':
idx = pixelfunc.nest2ring(nside,np.arange(m.size,dtype=np.int32))
m = m[idx]
if verbose: print 'Ordering converted to NEST'
elif (not nest) and ordering == 'NESTED':
idx = pixelfunc.ring2nest(nside,np.arange(m.size,dtype=np.int32))
m = m[idx]
if verbose: print 'Ordering converted to RING'
try:
m[pixelfunc.mask_bad(m)] = UNSEEN
except OverflowError, e:
pass
ret.append(m)
def in_ring(nside, iz, phi0, dphi, nest=False):
"""Compute the list of pixels in ring number iz in phi interval [phi0,phi0+dphi]
Input:
- nside: a power of 2
- iz: ring number
- phi0: the starting longitude
- dphi: interval of longitude
Keyword:
- nested: if True, return pixel number in nested scheme. Default: False (RING)
Return:
- list of pixel numbers
"""
from numpy import pi, arange, concatenate, hstack, fabs, round
from pixelfunc import nside2npix, ring2nest
npix = nside2npix(nside)
take_all = 0
to_top = 0
twopi = 2.0 * pi
ncap = 2 * nside * (nside - 1)
listir = -1
nir = 0
phi_low = (phi0 - dphi) % twopi
if (phi_low < 0): phi_low = phi_low + twopi
phi_hi = (phi0 + dphi) % twopi
if (phi_hi < 0): phi_hi = phi_hi + twopi
if (fabs(dphi - pi) < 1e-6): take_all = 1
# equatorial region
if ((iz >= nside) & (iz <= 3 * nside)):
ir = iz - nside + 1
ipix1 = ncap + 4 * nside * (ir - 1)
ipix2 = ipix1 + 4 * nside - 1
kshift = ir % 2
nr = nside * 4
else:
if (iz < nside):
ir = iz
ipix1 = 2 * ir * (ir - 1)
ipix2 = ipix1 + 4 * ir - 1
else:
ir = 4 * nside - iz
ipix1 = npix - 2 * ir * (ir + 1)
ipix2 = ipix1 + 4 * ir - 1
nr = ir * 4
kshift = 1
if (take_all == 1):
nir = ipix2 - ipix1 + 1
listir = arange(ipix1, ipix2 + 1, 1)
if (take_all == 0):
shift = kshift * .5
ip_low = int(round(nr * phi_low / twopi - shift))
ip_hi = int(round(nr * phi_hi / twopi - shift))
ip_low = ip_low % nr
ip_hi = ip_hi % nr
if (ip_low > ip_hi): to_top = 1
ip_low = ip_low + ipix1
ip_hi = ip_hi + ipix1
if (to_top == 1):
nir1 = ipix2 - ip_low + 1
nir2 = ip_hi - ipix1 + 1
nir = nir1 + nir2
if ((nir1 > 0) & (nir2 > 0)):
#listir = concatenate(arange(0,nir2,1)+ipix1, arange(0,nir1,1)+ip_low)
list1 = arange(0, nir1, 1) + ip_low
list2 = arange(0, nir2, 1) + ipix1
listir = concatenate((list1, list2))
else:
if (nir1 == 0): listir = arange(0, nir2, 1) + ipix1
if (nir2 == 0): listir = arange(0, nir1, 1) + ip_low
else:
nir = ip_hi - ip_low + 1
listir = arange(0, nir, 1) + ip_low
if (nest): listir = ring2nest(nside, listir)
return listir
def read_map(filename, field=0, dtype=npy.float64, nest=False, hdu=1, h=False, verbose=False):
"""Read an healpix map from a fits file.
Input:
- filename: the fits file name
Parameters:
- field: the column to read Default: 0
by convention 0 is temperature, 1 is Q, 2 is U
field can be a tuple to read multiple columns (0,1,2)
- dtype: force the conversion to some type. Default: npy.float64
- nest=False: if True return the map in NEST ordering, otherwise in RING ordering;
use fits keyword ORDERING to decide whether conversion is needed or not
if None, no conversion is performed
- hdu=1: the header number to look at (start at 0)
- h=False: if True, return also the header
- verbose=False: if True, print a number of diagnostic messages
Return:
- an array, a tuple of array, possibly with the header at the end if h
is True
"""
hdulist = pyf.open(filename)
# print hdulist[1].header
nside = int(hdulist[hdu].header.get("NSIDE"))
if nside is None:
warnings.warn("No NSIDE in the header file : will use length of array", HealpixFitsWarning)
if verbose:
print "NSIDE = %d" % nside
if not pixelfunc.isnsideok(nside):
raise ValueError("Wrong nside parameter.")
ordering = hdulist[hdu].header.get("ORDERING", "UNDEF").strip()
if ordering == "UNDEF":
ordering = nest and "NESTED" or "RING"
warnings.warn("No ORDERING keyword in header file : " "assume %s" % ordering)
if verbose:
print "ORDERING = %s in fits file" % ordering
sz = pixelfunc.nside2npix(nside)
if not hasattr(field, "__len__"):
field = (field,)
ret = []
for ff in field:
m = hdulist[hdu].data.field(ff).astype(dtype).ravel()
if (not pixelfunc.isnpixok(m.size) or (sz > 0 and sz != m.size)) and verbose:
print "nside=%d, sz=%d, m.size=%d" % (nside, sz, m.size)
raise ValueError("Wrong nside parameter.")
if nest != None: # no conversion with None
if nest and ordering == "RING":
idx = pixelfunc.nest2ring(nside, npy.arange(m.size, dtype=npy.int32))
m = m[idx]
if verbose:
print "Ordering converted to NEST"
elif (not nest) and ordering == "NESTED":
idx = pixelfunc.ring2nest(nside, npy.arange(m.size, dtype=npy.int32))
m = m[idx]
if verbose:
print "Ordering converted to RING"
try:
m[pixelfunc.mask_bad(m)] = UNSEEN
except OverflowError, e:
pass
ret.append(m)
def in_ring(nside,iz,phi0,dphi,nest=False):
"""Compute the list of pixels in ring number iz in phi interval [phi0,phi0+dphi]
Input:
- nside: a power of 2
- iz: ring number
- phi0: the starting longitude
- dphi: interval of longitude
Keyword:
- nested: if True, return pixel number in nested scheme. Default: False (RING)
Return:
- list of pixel numbers
"""
from numpy import pi,arange,concatenate,hstack,fabs,round
from pixelfunc import nside2npix,ring2nest
npix = nside2npix(nside)
take_all = 0
to_top = 0
twopi = 2.0 * pi
ncap = 2*nside*(nside-1)
listir = -1
nir = 0
phi_low = (phi0 - dphi) % twopi
if (phi_low < 0): phi_low = phi_low + twopi
phi_hi = (phi0 + dphi) % twopi
if (phi_hi < 0): phi_hi = phi_hi + twopi
if (fabs(dphi-pi) < 1e-6): take_all = 1
# equatorial region
if ((iz >= nside) & (iz <= 3*nside)):
ir = iz - nside + 1
ipix1 = ncap + 4*nside*(ir-1)
ipix2 = ipix1 + 4*nside - 1
kshift = ir % 2
nr = nside*4
else:
if (iz < nside):
ir = iz
ipix1 = 2*ir*(ir-1)
ipix2 = ipix1 + 4*ir - 1
else:
ir = 4*nside - iz
ipix1 = npix - 2*ir*(ir+1)
ipix2 = ipix1 + 4*ir - 1
nr = ir*4
kshift = 1
if (take_all == 1):
nir = ipix2 - ipix1 + 1
listir = arange(ipix1,ipix2+1,1)
if (take_all == 0):
shift = kshift * .5
ip_low = int(round (nr * phi_low / twopi - shift))
ip_hi = int(round(nr * phi_hi / twopi - shift))
ip_low = ip_low % nr
ip_hi = ip_hi % nr
if (ip_low > ip_hi): to_top = 1
ip_low = ip_low + ipix1
ip_hi = ip_hi + ipix1
if (to_top == 1):
nir1 = ipix2 - ip_low + 1
nir2 = ip_hi - ipix1 + 1
nir = nir1 + nir2
if ((nir1 > 0) & (nir2 > 0)):
#listir = concatenate(arange(0,nir2,1)+ipix1, arange(0,nir1,1)+ip_low)
list1 = arange(0,nir1,1)+ip_low
list2 = arange(0,nir2,1)+ipix1
listir = concatenate((list1,list2))
else:
if (nir1 == 0) : listir = arange(0,nir2,1)+ipix1
if (nir2 == 0) : listir = arange(0,nir1,1)+ip_low
else:
nir = ip_hi - ip_low + 1
listir = arange(0,nir,1)+ip_low
if (nest): listir = ring2nest(nside,listir)
return listir
def query_disc(nside, v0, radius, nest=False, deg=True):
"""Return the list of pixels within angle 'radius' from vector direction 'v0'
Input:
- nside: a power of 2
- v0: the vector describing the direction of the center of the disc
- radius: the opening angle of the disc
Keywords:
- nest: if True, pixel returned in nested scheme. Default: False (RING)
- deg: if False, radius angle expected in radian. Default: True (DEGREE)
Return:
- list of pixel (as a numpy array)
"""
# assumes input in degrees
from numpy import sqrt, sin, cos, pi, array, fabs, arccos, arcsin, size, empty, concatenate, arctan2, asarray
from pixelfunc import vec2pix, nside2npix
npix = nside2npix(nside)
ang_conv = 1.0
if (deg): ang_conv = pi / 180.0
cosang = cos(radius * ang_conv)
# radius in radians
radius_eff = radius * ang_conv
v0 = asarray(v0)
v0 /= sqrt((v0**2).sum())
x0, y0, z0 = v0
a = x0 * x0 + y0 * y0
phi0 = 0.0
if ((x0 != 0.0) | (y0 != 0.0)): phi0 = arctan2(y0, x0)
cosphi0 = cos(phi0)
rlat0 = arcsin(z0)
rlat1 = rlat0 + radius_eff
rlat2 = rlat0 - radius_eff
if (rlat1 >= pi / 2.0): zmax = 1.0
else: zmax = sin(rlat1)
irmin = max(ring_num(nside, zmax) - 1, 1)
if (rlat2 <= -pi / 2.0): zmin = -1.0
else: zmin = sin(rlat2)
irmax = min(ring_num(nside, zmin) + 1, 4 * nside - 1)
#first = 1
work = [[]]
for iz in xrange(irmin, irmax + 1):
skip = 0
z = ring2z(nside, iz)
b = cosang - z * z0
c = 1.0 - z * z
cosdphi = b / sqrt(a * c)
if ((x0 == 0) & (y0 == 0)):
cosdphi = -1.0
dphi = pi
if (fabs(cosdphi) <= 1):
dphi = arccos(cosdphi)
else:
if (cosphi0 < cosdphi):
skip = 1
dphi = pi
if (skip == 0):
listir = in_ring(nside, iz, phi0, dphi, nest=nest)
nir = size(listir)
if (nir > 0):
work.append(listir)
if len(work) > 1:
work = concatenate(work[1:])
else:
work = asarray([], dtype=int)
return work
def query_disc(nside,v0,radius,nest=False,deg=True):
"""Return the list of pixels within angle 'radius' from vector direction 'v0'
Input:
- nside: a power of 2
- v0: the vector describing the direction of the center of the disc
- radius: the opening angle of the disc
Keywords:
- nest: if True, pixel returned in nested scheme. Default: False (RING)
- deg: if False, radius angle expected in radian. Default: True (DEGREE)
Return:
- list of pixel (as a numpy array)
"""
# assumes input in degrees
from numpy import sqrt,sin,cos,pi,array,fabs,arccos,arcsin,size,empty,concatenate,arctan2,asarray
from pixelfunc import vec2pix,nside2npix
npix = nside2npix(nside)
ang_conv = 1.0
if (deg): ang_conv = pi/180.0
cosang = cos(radius*ang_conv)
# radius in radians
radius_eff = radius * ang_conv
v0 = asarray(v0)
v0 /= sqrt((v0**2).sum())
x0,y0,z0 = v0
a = x0*x0 + y0*y0
phi0 = 0.0
if ((x0!= 0.0)|(y0!=0.0)): phi0 = arctan2(y0, x0)
cosphi0 = cos(phi0)
rlat0 = arcsin(z0)
rlat1 = rlat0 + radius_eff
rlat2 = rlat0 - radius_eff
if (rlat1 >= pi/2.0): zmax = 1.0
else : zmax = sin(rlat1)
irmin = max(ring_num(nside,zmax) - 1,1)
if (rlat2 <= -pi/2.0): zmin = -1.0
else : zmin = sin(rlat2)
irmax = min(ring_num(nside,zmin) + 1,4*nside-1)
#first = 1
work = [[]]
for iz in xrange(irmin,irmax+1):
skip = 0
z = ring2z(nside,iz)
b = cosang - z*z0
c = 1.0 - z*z
cosdphi = b/sqrt(a*c)
if ((x0 == 0)&(y0==0)):
cosdphi = -1.0
dphi = pi
if (fabs(cosdphi) <= 1):
dphi = arccos(cosdphi)
else:
if (cosphi0 < cosdphi):
skip = 1
dphi = pi
if (skip == 0):
listir = in_ring(nside, iz, phi0, dphi,nest=nest)
nir = size(listir)
if (nir>0):
work.append(listir)
if len(work) > 1:
work = concatenate(work[1:])
else:
work = asarray([], dtype=int)
return work
def write_map(filename,m,nest=False,dtype=np.float32,fits_IDL=True,coord=None,column_names=None):
"""Writes an healpix map into an healpix file.
Parameters
----------
filename : str
the fits file name
m : array or sequence of 3 arrays
the map to write. Possibly a sequence of 3 maps of same size.
They will be considered as I, Q, U maps.
Supports masked maps, see the `ma` function.
nest : bool, optional
If True, ordering scheme is assumed to be NESTED, otherwise, RING. Default: RING.
The map ordering is not modified by this function, the input map array
should already be in the desired ordering (run `ud_grade` beforehand).
fits_IDL : bool, optional
If True, reshapes columns in rows of 1024, otherwise all the data will
go in one column. Default: True
coord : str
The coordinate system, typically 'E' for Ecliptic, 'G' for Galactic or 'C' for
Celestial (equatorial)
column_names : str or list
Column name or list of column names, if None we use:
I_STOKES for 1 component,
I/Q/U_STOKES for 3 components,
II, IQ, IU, QQ, QU, UU for 6 components,
COLUMN_0, COLUMN_1... otherwise
"""
if not hasattr(m, '__len__'):
raise TypeError('The map must be a sequence')
# check the dtype and convert it
fitsformat = getformat(dtype)
m = pixelfunc.ma_to_array(m)
if pixelfunc.maptype(m) == 0: # a single map is converted to a list
m = [m]
if column_names is None:
column_names = standard_column_names.get(len(m), ["COLUMN_%d" % n for n in range(len(m))])
else:
assert len(column_names) == len(m), "Length column_names != number of maps"
# maps must have same length
assert len(set(map(len, m))) == 1, "Maps must have same length"
nside = pixelfunc.npix2nside(len(m[0]))
if nside < 0:
raise ValueError('Invalid healpix map : wrong number of pixel')
cols=[]
for cn, mm in zip(column_names, m):
if len(mm) > 1024 and fits_IDL:
# I need an ndarray, for reshape:
mm2 = np.asarray(mm)
cols.append(pf.Column(name=cn,
format='1024%s' % fitsformat,
array=mm2.reshape(mm2.size/1024,1024)))
else:
cols.append(pf.Column(name=cn,
format='%s' % fitsformat,
array=mm))
tbhdu = pf.new_table(cols)
# add needed keywords
tbhdu.header.update('PIXTYPE','HEALPIX','HEALPIX pixelisation')
if nest: ordering = 'NESTED'
else: ordering = 'RING'
tbhdu.header.update('ORDERING',ordering,
'Pixel ordering scheme, either RING or NESTED')
if coord:
tbhdu.header.update('COORDSYS',coord,
'Ecliptic, Galactic or Celestial (equatorial)')
tbhdu.header.update('EXTNAME','xtension',
'name of this binary table extension')
tbhdu.header.update('NSIDE',nside,'Resolution parameter of HEALPIX')
tbhdu.header.update('FIRSTPIX', 0, 'First pixel # (0 based)')
tbhdu.header.update('LASTPIX',pixelfunc.nside2npix(nside)-1,
'Last pixel # (0 based)')
tbhdu.header.update('INDXSCHM','IMPLICIT',
'Indexing: IMPLICIT or EXPLICIT')
tbhdu.writeto(filename,clobber=True)
def read_map(filename,
field=0,
dtype=npy.float64,
nest=False,
hdu=1,
h=False,
verbose=False):
"""Read an healpix map from a fits file.
Input:
- filename: the fits file name
Parameters:
- field: the column to read Default: 0
by convention 0 is temperature, 1 is Q, 2 is U
field can be a tuple to read multiple columns (0,1,2)
- dtype: force the conversion to some type. Default: npy.float64
- nest=False: if True return the map in NEST ordering, otherwise in RING ordering;
use fits keyword ORDERING to decide whether conversion is needed or not
if None, no conversion is performed
- hdu=1: the header number to look at (start at 0)
- h=False: if True, return also the header
- verbose=False: if True, print a number of diagnostic messages
Return:
- an array, a tuple of array, possibly with the header at the end if h
is True
"""
hdulist = pyf.open(filename)
#print hdulist[1].header
nside = int(hdulist[hdu].header.get('NSIDE'))
if nside is None:
warnings.warn("No NSIDE in the header file : will use length of array",
HealpixFitsWarning)
if verbose: print 'NSIDE = %d' % nside
if not pixelfunc.isnsideok(nside):
raise ValueError('Wrong nside parameter.')
ordering = hdulist[hdu].header.get('ORDERING', 'UNDEF').strip()
if ordering == 'UNDEF':
ordering = (nest and 'NESTED' or 'RING')
warnings.warn("No ORDERING keyword in header file : "
"assume %s" % ordering)
if verbose: print 'ORDERING = %s in fits file' % ordering
sz = pixelfunc.nside2npix(nside)
if not hasattr(field, '__len__'):
field = (field, )
ret = []
for ff in field:
m = hdulist[hdu].data.field(ff).astype(dtype).ravel()
if (not pixelfunc.isnpixok(m.size) or
(sz > 0 and sz != m.size)) and verbose:
print 'nside=%d, sz=%d, m.size=%d' % (nside, sz, m.size)
raise ValueError('Wrong nside parameter.')
if nest != None: # no conversion with None
if nest and ordering == 'RING':
idx = pixelfunc.nest2ring(nside,
npy.arange(m.size, dtype=npy.int32))
m = m[idx]
if verbose: print 'Ordering converted to NEST'
elif (not nest) and ordering == 'NESTED':
idx = pixelfunc.ring2nest(nside,
npy.arange(m.size, dtype=npy.int32))
m = m[idx]
if verbose: print 'Ordering converted to RING'
try:
m[pixelfunc.mask_bad(m)] = UNSEEN
except OverflowError, e:
pass
ret.append(m)
def write_map(filename,m,nest=False,dtype=npy.float32):
"""Writes an healpix map into an healpix file.
Input:
- filename: the fits file name
- m: the map to write. Possibly a sequence of 3 maps of same size.
They will be considered as I, Q, U maps
- nest=False: ordering scheme
"""
if not hasattr(m, '__len__'):
raise TypeError('The map must be a sequence')
# check the dtype and convert it
fitsformat = getformat(dtype)
#print 'format to use: "%s"'%fitsformat
if hasattr(m[0], '__len__'):
# we should have three maps
if len(m) != 3 or len(m[1]) != len(m[0]) or len(m[2]) != len(m[0]):
raise ValueError("You should give 3 maps of same size "
"for polarisation...")
nside = pixelfunc.npix2nside(len(m[0]))
if nside < 0:
raise ValueError('Invalid healpix map : wrong number of pixel')
cols=[]
colnames=['I_STOKES','Q_STOKES','U_STOKES']
for cn,mm in zip(colnames,m):
if len(mm) > 1024:
# I need an ndarray, for reshape:
mm2 = npy.asarray(mm)
cols.append(pyf.Column(name=cn,
format='1024%s'%fitsformat,
array=mm2.reshape(mm2.size/1024,1024)))
else:
cols.append(pyf.Column(name=cn,
format='%s'%fitsformat,
array=mm))
else: # we write only one map
nside = pixelfunc.npix2nside(len(m))
if nside < 0:
raise ValueError('Invalid healpix map : wrong number of pixel')
if m.size > 1024:
cols = [pyf.Column(name='I_STOKES',
format='1024%s'%fitsformat,
array=m.reshape(m.size/1024,1024))]
else:
cols = [pyf.Column(name='I_STOKES',
format='%s'%fitsformat,
array=m)]
coldefs=pyf.ColDefs(cols)
tbhdu = pyf.new_table(coldefs)
# add needed keywords
tbhdu.header.update('PIXTYPE','HEALPIX','HEALPIX pixelisation')
if nest: ordering = 'NESTED'
else: ordering = 'RING'
tbhdu.header.update('ORDERING',ordering,
'Pixel ordering scheme, either RING or NESTED')
tbhdu.header.update('EXTNAME','xtension',
'name of this binary table extension')
tbhdu.header.update('NSIDE',nside,'Resolution parameter of HEALPIX')
tbhdu.header.update('FIRSTPIX', 0, 'First pixel # (0 based)')
tbhdu.header.update('LASTPIX',pixelfunc.nside2npix(nside)-1,
'Last pixel # (0 based)')
tbhdu.header.update('INDXSCHM','IMPLICIT',
'Indexing: IMPLICIT or EXPLICIT')
tbhdu.writeto(filename,clobber=True)
def read_map(filename,field=0,dtype=npy.float64,nest=False,hdu=1,h=False):
"""Read an healpix map from a fits file.
Input:
- filename: the fits file name
Parameters:
- field: the column to read Default: 0
by convention 0 is temperature, 1 is Q, 2 is U
field can be a tuple to read multiple columns (0,1,2)
- dtype: force the conversion to some type. Default: npy.float64
- nest=False: if True return the map in NEST ordering, otherwise in RING ordering;
use fits keyword ORDERING to decide whether conversion is needed or not
if None, no conversion is performed
- hdu=1: the header number to look at (start at 0)
- h=False: if True, return also the header
Return:
- an array, a tuple of array, possibly with the header at the end if h
is True
"""
hdulist=pyf.open(filename)
#print hdulist[1].header
nside = int(hdulist[hdu].header.get('NSIDE'))
if nside is None:
warnings.warn("No NSIDE in the header file : will use length of array",
HealpixFitsWarning)
print 'NSIDE = %d'%nside
if not pixelfunc.isnsideok(nside):
raise ValueError('Wrong nside parameter.')
ordering = hdulist[hdu].header.get('ORDERING','UNDEF').strip()
if ordering == 'UNDEF':
ordering = (nest and 'NESTED' or 'RING')
warnings.warn("No ORDERING keyword in header file : "
"assume %s"%ordering)
print 'ORDERING = %s in fits file'%ordering
sz=pixelfunc.nside2npix(nside)
if not hasattr(field, '__len__'):
field = (field,)
ret = []
for ff in field:
m=hdulist[hdu].data.field(ff).astype(dtype).ravel()
if not pixelfunc.isnpixok(m.size) or (sz>0 and sz != m.size):
print 'nside=%d, sz=%d, m.size=%d'%(nside,sz,m.size)
raise ValueError('Wrong nside parameter.')
if nest != None: # no conversion with None
if nest and ordering == 'RING':
idx = pixelfunc.nest2ring(nside,npy.arange(m.size,dtype=npy.int32))
m = m[idx]
print 'Ordering converted to NEST'
elif (not nest) and ordering == 'NESTED':
idx = pixelfunc.ring2nest(nside,npy.arange(m.size,dtype=npy.int32))
m = m[idx]
print 'Ordering converted to RING'
m[m<-1.637e30] = UNSEEN
ret.append(m)
if len(ret) == 1:
if h:
return ret[0],hdulist[hdu].header.items()
else:
return ret[0]
else:
if h:
ret.append(hdulist[hdu].header.items())
return tuple(ret)
else:
return tuple(ret)