def preprocess_T(imap, dust_removal=False, dust_template=None, box=None, auto_adj=False):
omap = enmap.submap(imap[0], box=box)
if dust_removal:
dust = enmap.submap(dust_template[0], box=box)
if auto_adj:
par, _ = leastsq(lambda x: np.ravel(omap-x*dust), x0=1)
factor = par[0]
else: factor = 1
print("factor:", factor)
omap -= dust * factor
return omap
def preprocess_P(imap, dust_removal=None, smooth=None, box=None):
omap = np.sum(imap[1:]**2, axis=0)**0.5
if dust_removal is not None:
omap -= np.sum(dust_removal[1:]**2, axis=0)**0.5
if smooth is not None:
omap = enmap.smooth_gauss(omap, smooth * u.fwhm * u.arcmin)
return enmap.submap(omap, box=box)
def getSubmaps_originalPixelization(theMap, ras_deg, decs_deg, semiWidth_deg):
'''From the original pixelization of the map, extract a list of submaps.
theMap_fname: map to extract submaps from
ra_deg, dec_deg: arrays of ra and decs in degrees
semiWidth_deg: half of the width of the submap to be extracted in degrees.
'''
boxes = gen_boxes(ras_deg, decs_deg, semiWidth_deg)
submaps = []
for box in boxes:
submaps.append(enmap.submap(theMap, box))
return submaps
def getSubmap_originalPixelization(theMap, ra_deg, dec_deg, semiWidth_deg):
'''Receives theMap and gets a submap centered in ra,dec with width
semiWidth_deg'''
box = gen_box(ra_deg, dec_deg, semiWidth_deg)
submap = enmap.submap(theMap, box)
return submap