def prepare_map_field(map, args, crange=None, printer=noprint):
if crange is None:
with printer.time("ranges", 3):
crange = get_color_range(map, args)
if map.ndim == 2:
map = map[None]
if args.autocrop_each:
map = enmap.autocrop(map)
with printer.time("colorize", 3):
color = map_to_color(map, crange, args)
return map, color
L.info("Reading %s" % args.map)
map = enmap.read_map(args.map)
map = map.reshape((-1, ) + map.shape[-2:])[0][None]
L.info("Reading %s" % args.noise)
inoise = enmap.read_map(args.noise)
inoise = inoise.reshape((-1, ) + inoise.shape[-2:])[0][None, None]
print map.shape, inoise.shape
shape_orig = map.shape[-2:]
# Mask out too noisy areas
L.info("Masking")
mask = inoise[0, 0] < args.noise_max**-2
map[:, mask] = np.nan
if not args.nocrop:
L.info("Cropping")
map, info = enmap.autocrop(map, method="fft", return_info=True)
inoise = enmap.padcrop(inoise, info)
shape_crop = map.shape[-2:]
L.info("Cropped from %s to %s" % (str(shape_orig), str(shape_crop)))
map[np.isnan(map)] = 0
## Truncate to fft-friendly areas
#h = fft.fft_len(map.shape[-2],[2,3,5])
#w = fft.fft_len(map.shape[-1],[2,3,5])
#map = map[:,:h,:w]
#inoise = inoise[:,:,:h,:w]
#map[~np.isfinite(map)] = 0
# Kill extreme values
L.info("Removing extreme outliers above 1e6")
map = np.minimum(1e6, np.maximum(-1e6, map))
def get_map(ifile, args, return_info=False):
"""Read the specified map, and massage it according to the options
in args. Relevant ones are sub, autocrop, slice, op, downgrade, scale,
mask. Retuns with shape [:,ny,nx], where any extra dimensions have been
flattened into a single one."""
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
toks = ifile.split(":")
ifile, slice = toks[0], ":".join(toks[1:])
m0 = enmap.read_map(ifile)
if args.fix_wcs:
m0.wcs = enwcs.fix_wcs(m0.wcs)
# Save the original map, so we can compare its wcs later
m = m0
# Submap slicing currently has wrapping issues
if args.sub is not None:
default = [[-90,-180],[90,180]]
sub = np.array([[(default[j][i] if q == '' else float(q))*np.pi/180 for j,q in enumerate(w.split(":"))]for i,w in enumerate(args.sub.split(","))]).T
m = m.submap(sub)
# Perform a common autocrop across all fields
if args.autocrop:
m = enmap.autocrop(m)
# If necessary, split into stamps. If no stamp splitting occurs,
# a list containing only the original map is returned
mlist = extract_stamps(m, args)
# The stamp stuff is a bit of an ugly hack. This loop and wcslist
# are parts of that hack.
for i, m in enumerate(mlist):
# Downgrade
downgrade = [int(w) for w in args.downgrade.split(",")]
m = enmap.downgrade(m, downgrade)
# Slicing, either at the file name level or though the slice option
m = eval("m"+slice)
if args.slice is not None:
m = eval("m"+args.slice)
flip = (m.wcs.wcs.cdelt*m0.wcs.wcs.cdelt)[::-1]<0
assert m.ndim >= 2, "Image must have at least 2 dimensions"
# Apply arbitrary map operations
m1 = m
if args.op is not None:
m = eval(args.op, {"m":m},np.__dict__)
# Scale if requested
scale = [int(w) for w in args.scale.split(",")]
if np.any(np.array(scale)>1):
m = enmap.upgrade(m, scale)
# Flip such that pixels are in PIL or matplotlib convention,
# such that RA increases towards the left and dec upwards in
# the final image. Unless a slicing operation on the image
# overrrode this.
if m.wcs.wcs.cdelt[1] > 0: m = m[...,::-1,:]
if m.wcs.wcs.cdelt[0] > 0: m = m[...,:,::-1]
if flip[0]: m = m[...,::-1,:]
if flip[1]: m = m[...,:,::-1]
# Update stamp list
mlist[i] = m
wcslist = [m.wcs for m in mlist]
m = enmap.samewcs(np.asarray(mlist),mlist[0])
if args.stamps is None:
m, wcslist = m[0], None
# Flatten pre-dimensions
mf = m.reshape((-1,)+m.shape[-2:])
# Stack
if args.tile is not None:
toks = [int(i) for i in args.tile.split(",")]
nrow = toks[0] if len(toks) > 0 else -1
ncol = toks[1] if len(toks) > 1 else -1
mf = hwstack(hwexpand(mf, nrow, ncol, args.tile_transpose))[None]
# Mask bad data
if args.mask is not None:
if not np.isfinite(args.mask): mf[np.abs(mf)==args.mask] = np.nan
else: mf[np.abs(mf-args.mask)<=args.mask_tol] = np.nan
# Done
if not return_info: return mf
else:
info = bunch.Bunch(fname=ifile, ishape=m.shape, wcslist=wcslist)
return mf, info