def projmap(self,
map,
vec2pix_func,
vmin=None,
vmax=None,
badval=UNSEEN,
cmap=None,
norm=None,
rot=None,
coord=None,
**kwds):
"""Project a map.
Input:
- map: a map
- vec2pix_func: the function describing the pixelisation
- vmin, vmax: min and max value to use instead of min max of the map
- badval: the value of the bad pixels
- cmapname: the name of the color map to use (see cm.datad.keys())
- rot: =(a,b,c) map is centered on (a,b) and rotated by angle c, in deg.
- coord: the coordinate system of the map ('G','E' or 'C'), rotate
the map if different from the axes coord syst.
other keywords given to Axes.imshow
"""
img = self.proj.projmap(map, vec2pix_func, rot=rot, coord=coord)
w = ~(npy.isnan(img) | npy.isinf(img)
| pixelfunc.mask_bad(img, badval=badval))
try:
if vmin is None: vmin = img[w].min()
except ValueError:
vmin = 0.
try:
if vmax is None: vmax = img[w].max()
except ValueError:
vmax = 0.
if vmin > vmax:
vmin = vmax
if vmin == vmax:
vmin -= 1.
vmax += 1.
cm, nn = get_color_table(vmin, vmax, img[w], cmap=cmap, norm=norm)
ext = self.proj.get_extent()
img = npy.ma.masked_values(img, badval)
aximg = self.imshow(img,
extent=ext,
cmap=cm,
norm=nn,
interpolation='nearest',
origin='lower',
vmin=vmin,
vmax=vmax,
**kwds)
xmin, xmax, ymin, ymax = self.proj.get_extent()
self.set_xlim(xmin, xmax)
self.set_ylim(ymin, ymax)
def projmap(self,map,vec2pix_func,vmin=None,vmax=None,badval=UNSEEN,
cmap=None,norm=None,rot=None,coord=None,**kwds):
"""Project a map on the SphericalProjAxes.
Parameters
----------
map : array-like
The map to project.
vec2pix_func : function
The function describing the pixelisation.
vmin, vmax : float, scalars
min and max value to use instead of min max of the map
badval : float
The value of the bad pixels
cmap : a color map
The colormap to use (see matplotlib.cm)
rot : sequence
In the form (lon, lat, psi) (unit: degree):the center of the map is
at (lon, lat) and rotated by angle psi around that direction.
coord : {'G', 'E', 'C', None}
The coordinate system of the map ('G','E' or 'C'), rotate
the map if different from the axes coord syst.
Notes
-----
Other keywords are transmitted to :func:`matplotlib.Axes.imshow`
"""
img = self.proj.projmap(map,vec2pix_func,rot=rot,coord=coord)
w = ~( np.isnan(img) |
np.isinf(img) |
pixelfunc.mask_bad(img, badval = badval) )
try:
if vmin is None: vmin = img[w].min()
except ValueError:
vmin = 0.
try:
if vmax is None: vmax = img[w].max()
except ValueError:
vmax = 0.
if vmin > vmax:
vmin = vmax
if vmin == vmax:
vmin -= 1.
vmax += 1.
cm,nn = get_color_table(vmin,vmax,img[w],cmap=cmap,norm=norm)
ext = self.proj.get_extent()
img = np.ma.masked_values(img, badval)
aximg = self.imshow(img,extent = ext,cmap=cm,norm=nn,
interpolation='nearest',origin='lower',
vmin=vmin,vmax=vmax,**kwds)
xmin,xmax,ymin,ymax = self.proj.get_extent()
self.set_xlim(xmin,xmax)
self.set_ylim(ymin,ymax)
return img
def projmap(self,map,vec2pix_func,vmin=None,vmax=None,badval=UNSEEN,
cmap=None,norm=None,rot=None,coord=None,**kwds):
"""Project a map on the SphericalProjAxes.
Parameters
----------
map : array-like
The map to project.
vec2pix_func : function
The function describing the pixelisation.
vmin, vmax : float, scalars
min and max value to use instead of min max of the map
badval : float
The value of the bad pixels
cmap : a color map
The colormap to use (see matplotlib.cm)
rot : sequence
In the form (lon, lat, psi) (unit: degree):the center of the map is
at (lon, lat) and rotated by angle psi around that direction.
coord : {'G', 'E', 'C', None}
The coordinate system of the map ('G','E' or 'C'), rotate
the map if different from the axes coord syst.
Notes
-----
Other keywords are transmitted to :func:`matplotlib.Axes.imshow`
"""
img = self.proj.projmap(map,vec2pix_func,rot=rot,coord=coord)
w = ~( np.isnan(img) |
np.isinf(img) |
pixelfunc.mask_bad(img, badval = badval) )
try:
if vmin is None: vmin = img[w].min()
except ValueError:
vmin = 0.
try:
if vmax is None: vmax = img[w].max()
except ValueError:
vmax = 0.
if vmin > vmax:
vmin = vmax
if vmin == vmax:
vmin -= 1.
vmax += 1.
cm,nn = get_color_table(vmin,vmax,img[w],cmap=cmap,norm=norm)
ext = self.proj.get_extent()
img = np.ma.masked_values(img, badval)
aximg = self.imshow(img,extent = ext,cmap=cm,norm=nn,
interpolation='nearest',origin='lower',
vmin=vmin,vmax=vmax,**kwds)
xmin,xmax,ymin,ymax = self.proj.get_extent()
self.set_xlim(xmin,xmax)
self.set_ylim(ymin,ymax)
def projmap(self,map,vec2pix_func,vmin=None,vmax=None,badval=UNSEEN,
cmap=None,norm=None,rot=None,coord=None,**kwds):
"""Project a map.
Input:
- map: a map
- vec2pix_func: the function describing the pixelisation
- vmin, vmax: min and max value to use instead of min max of the map
- badval: the value of the bad pixels
- cmapname: the name of the color map to use (see cm.datad.keys())
- rot: =(a,b,c) map is centered on (a,b) and rotated by angle c, in deg.
- coord: the coordinate system of the map ('G','E' or 'C'), rotate
the map if different from the axes coord syst.
other keywords given to Axes.imshow
"""
img = self.proj.projmap(map,vec2pix_func,rot=rot,coord=coord)
w = ~( npy.isnan(img) |
npy.isinf(img) |
pixelfunc.mask_bad(img, badval = badval) )
try:
if vmin is None: vmin = img[w].min()
except ValueError:
vmin = 0.
try:
if vmax is None: vmax = img[w].max()
except ValueError:
vmax = 0.
if vmin > vmax:
vmin = vmax
if vmin == vmax:
vmin -= 1.
vmax += 1.
cm,nn = get_color_table(vmin,vmax,img[w],cmap=cmap,norm=norm)
ext = self.proj.get_extent()
img = npy.ma.masked_values(img, badval)
aximg = self.imshow(img,extent = ext,cmap=cm,norm=nn,
interpolation='nearest',origin='lower',
vmin=vmin,vmax=vmax,**kwds)
xmin,xmax,ymin,ymax = self.proj.get_extent()
self.set_xlim(xmin,xmax)
self.set_ylim(ymin,ymax)
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 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 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)