def padproj(sptmap, padding=(4000, 4000), squaremap=True, proj0=True):
sptmap = np.pad(np.asarray(sptmap), padding, mode='constant')
if squaremap == True:
sptmap = sptmap[:,
int((sptmap.shape[1] / 2) -
(sptmap.shape[0] / 2)):int((sptmap.shape[1] / 2) +
(sptmap.shape[0] / 2))]
sptmap = maps.FlatSkyMap(
sptmap.copy(order='C'),
0.25 * core.G3Units.arcmin,
weighted=False,
proj=maps.MapProjection.Proj5,
alpha_center=0 * core.G3Units.deg,
delta_center=-57.5 * core.G3Units.deg,
coord_ref=maps.MapCoordReference.Equatorial,
units=core.G3TimestreamUnits.Tcmb,
pol_type=maps.MapPolType.T,
)
if proj0 == True:
MapProj0 = map_3g.Clone(False)
MapProj0.proj = maps.MapProjection.Proj0
maps.reproj_map(map_3g, MapProj0, interp=True)
sptmap = MapProj0
return sptmap
good_wafers = []
for wafer in args.wafers_to_include:
if wafer not in [None, '']:
good_wafers.append(wafer.capitalize())
# Suppress warnings about timestream missing from scan frame
if args.split_left_right:
core.set_log_level(core.G3LogLevel.LOG_ERROR, 'MapBinner')
# -----------------------------------------------------------------------------
# Generate map stubs for use later in pipeline.
# -----------------------------------------------------------------------------
map_params = maps.FlatSkyMap(
x_len = x_len, y_len = y_len, res = res,
proj = proj, alpha_center = ra, delta_center = dec,
pol_type = maps.MapPolType.T,
coord_ref = maps.MapCoordReference.Equatorial)
# Set up an empty map for point source filtering
if args.mask_point_sources and args.point_source_file not in [None, '']:
ps_params = maps.FlatSkyMap(
x_len = x_len, y_len = y_len, res = res,
proj = proj, alpha_center = ra, delta_center = dec,
pol_type = maps.MapPolType.T,
coord_ref = maps.MapCoordReference.Equatorial)
# Fill map with the point source mask
sources.source_utils.make_point_source_map(
ps_params, args.point_source_file)
ps_map_id = 'PointSourceMask'
def healpix_to_flatsky(
map_in, nest=False, map_stub=None, rebin=1, interp=False, **kwargs
):
"""
Re-pixelize a map from Healpix to one of the flat sky projections.
Parameters:
-----------
map_in: numpy array or HealpixSkyMap
The array containing the input healpix map to reproject.
nest[False]: bool
Ordering of the healpix map, if the input is a numpy array. Ring
ordering is assumed by default.
map_stub[None]: FlatSkyMap
Stub output map object to be used to construct the output map. If not
supplied, one will be constructed using the remaining keyword arguments.
rebin[1]: int
If supplied and >1, account for sub-pixel structure by integrating
over a sub-grid on each pixel of the given dimension. This avoids
aliasing of power at angular scales beyond the map resolution.
interp[false]: bool
If True, use bilinear interpolation to extract values from the input
map. Otherwise, the nearest-neighbor value is used.
All additional keyword arguments are passed to FlatSkyMap to construct
the output map object. Required if `map_stub` is not supplied,
otherwise ignored.
Returns:
--------
output_map: FlatSkyMap
The reprojected map
"""
# Construct the output map
if map_stub is None:
if isinstance(map_in, maps.HealpixSkyMap):
kwargs.setdefault("coord_ref", map_in.coord_ref)
kwargs.setdefault("pol_type", map_in.pol_type)
kwargs.setdefault("pol_conv", map_in.pol_conv)
map_out = maps.FlatSkyMap(**kwargs)
else:
if not isinstance(map_stub, maps.FlatSkyMap):
raise TypeError("Output stub must be a FlatSkyMap")
map_out = map_stub.Clone(False)
# Populate output map pixels with interpolation and rebinning
if not isinstance(map_in, maps.HealpixSkyMap):
map_in = maps.HealpixSkyMap(
map_in,
nested=nest,
coord_ref=map_out.coord_ref,
weighted=map_out.weighted,
units=map_out.units,
pol_type=map_out.pol_type,
pol_conv=map_out.pol_conv,
)
maps.reproj_map(map_in, map_out, rebin=rebin, interp=interp)
return map_out
def healpix_to_flatsky(map_in,
nest=False,
map_stub=None,
rebin=1,
interp=False,
**kwargs):
"""
Re-pixelize a map from Healpix to one of the flat sky projections.
Parameters:
-----------
map_in: numpy array or HealpixSkyMap
The array containing the input healpix map to reproject.
nest[False]: bool
Ordering of the healpix map, if the input is a numpy array. Ring
ordering is assumed by default.
map_stub[None]: FlatSkyMap
Stub output map object to be used to construct the output map. If not
supplied, one will be constructed using the remaining keyword arguments.
rebin[1]: int
If supplied and >1, subdivide the output pixel by n x n with each
sub-pixel taking on the input map values at pixel center (with interp
or nearest neighbor). The output pixel takes on the average of the sub-pixel
values.
In the case that the input map has higher resolution than the output
map (and that the input map is not low-pass filtered to remove
information above the Nyquist freq. of the output map pixel), this
reduces aliasing compared with direct sampling. But there would still be
aliased power from the input map from freq above the ouput map pixel's
Nyquist.
interp[false]: bool
If True, use bilinear interpolation to extract values from the input
map. Otherwise, the nearest-neighbor value is used.
All additional keyword arguments are passed to FlatSkyMap to construct the
output map object. Required if `map_stub` is not supplied, otherwise
ignored.
Maps can be rotated between Equatorial and Galactic coordinates, and/or
change polarization convention between COSMO and IAU, by setting the
appropriate attributes of the input and output maps. Note that if the input
map is a numpy array representation of a healpix map, the coordinate system
and polarization convention are assumed to be that of the output map.
Conversely, attributes not defined in the output map are assumed to be
that of the input map.
Returns:
--------
output_map: FlatSkyMap
The reprojected map
"""
# Construct the output map
if map_stub is None:
if len(kwargs) == 0:
raise ValueError(
"Need to provide either a stub map or map parameters (projection, center, etc.)"
)
if isinstance(map_in, maps.HealpixSkyMap):
kwargs.setdefault("coord_ref", map_in.coord_ref)
kwargs.setdefault("pol_type", map_in.pol_type)
kwargs.setdefault("pol_conv", map_in.pol_conv)
map_out = maps.FlatSkyMap(**kwargs)
else:
if not isinstance(map_stub, maps.FlatSkyMap):
raise TypeError("Output stub must be a FlatSkyMap")
map_out = map_stub.clone(False)
# Populate output map pixels with interpolation and rebinning
if not isinstance(map_in, maps.HealpixSkyMap):
map_in = maps.HealpixSkyMap(
map_in,
nested=nest,
coord_ref=map_out.coord_ref,
weighted=map_out.weighted,
units=map_out.units,
pol_type=map_out.pol_type,
pol_conv=map_out.pol_conv,
)
maps.reproj_map(map_in, map_out, rebin=rebin, interp=interp)
return map_out
arr = np.arange(dim * dim).reshape(dim, dim)
res = core.G3Units.arcmin
deg = core.G3Units.deg
a0 = 20 * deg
d0 = -50 * deg
x0 = 120
y0 = 180
verbose = False
error = ''
fm0 = maps.FlatSkyMap(dim,
dim,
res,
proj=maps.MapProjection.ProjZEA,
alpha_center=a0,
delta_center=d0,
x_center=x0,
y_center=y0)
print('Checking projections for dim {}'.format(dim))
if verbose:
print('-' * 80)
for p in [0, 1, 2, 3, 4, 5, 6, 7, 9]:
if verbose:
print('Checking Proj{}'.format(p))
proj = getattr(maps.MapProjection, 'Proj{}'.format(p))
fm1 = maps.FlatSkyMap(arr,
res,
proj=proj,
from spt3g import core, maps
import numpy as np
pipe = core.G3Pipeline()
m = maps.FlatSkyMap(300,
300,
core.G3Units.arcmin,
proj=maps.MapProjection.ProjZEA)
pipe.Add(core.G3InfiniteSource, type=core.G3FrameType.Observation, n=1)
pipe.Add(maps.InjectMapStub,
map_id="test_map",
map_stub=m,
polarized=False,
weighted=True)
def RandomMap(frame):
if frame.type != core.G3FrameType.Map:
return
tmap = frame.pop("T")
tmap[:] = np.random.randn(*m.shape)
frame["T"] = tmap
wmap = frame.pop("Wunpol")
wmap.TT[:] = 10 * np.ones(m.shape)
frame["Wunpol"] = wmap
