def smoothing(m, fwhm, nest=True):
full_map = np.ones(npix)
full_map[total_mask] = m
if fwhm <= 0:
return m
if nest:
smoothed_map = hpf.reorder(hp.smoothing(hpf.reorder(full_map, n2r=True), fwhm=fwhm), r2n=True)
else:
smoothed_map = hp.smoothing(full_map, fwhm=fwhm)
return smoothed_map[total_mask]
def get_faces_par(im, nested=False, num_cores=None):
npix = np.shape(im)[0]
assert npix % 12 == 0
nside = npix2nside(npix)
if not nested:
new_im = reorder(im, r2n=True)
else:
new_im = im
# index = np.array([xyf2pix(nside, x, range(nside), 0, True)
# for x in range(nside-1, -1, -1)])
index = make_index_par(nside, num_cores)
CubeFace = sm.empty((12, nside, nside))
with sharedmem_pool(num_cores, numexpr=False) as pool:
# for face in range(12):
# CubeFace[face] = np.resize(new_im[index + nside**2 * face],
# (nside, nside))
def work(i):
CubeFace[i] = np.resize(new_im[index + nside**2 * i],
(nside, nside))
pool.map(work, range(12))
return np.array(CubeFace)
def set_faces_par(CubeFace, nested=False, num_cores=None):
npix = np.size(CubeFace)
assert npix % 12 == 0
nside = npix2nside(npix)
index = make_index_par(nside, num_cores)
# index = np.array([xyf2pix(nside, x, range(nside), 0, True)
# for x in range(nside-1, -1, -1)])
imag = sm.empty((npix))
with sharedmem_pool(num_cores, numexpr=False) as pool:
def work(i):
for face in range(12):
imag[index + nside**2 * face] = np.resize(
CubeFace[face], (nside, nside))
#imag[index + nside**2 * face] = np.resize(CubeFace[face],
# (nside,nside))
pool.map(work, range(12))
imag = np.array(imag)
if not nested:
new_im = reorder(imag, n2r=True)
else:
new_im = imag
return new_im
def get_faces(Imag, nested=False, num_cores=None):
npix = np.shape(Imag)[0]
assert npix % 12 == 0
nside = npix2nside(npix)
CubeFace = np.zeros((12, nside, nside))
if not nested:
NewIm = reorder(Imag, r2n=True)
else:
NewIm = Imag
# index = np.array([xyf2pix(nside, x, range(nside), 0, True)
# for x in range(nside-1, -1, -1)
# ])
index = make_index_par(nside, num_cores)
for face in range(12):
CubeFace[face] = np.resize(NewIm[index + nside**2 * face],
(nside, nside))
return CubeFace
def set_faces(CubeFace, nested=False):
npix = np.size(CubeFace)
assert npix % 12 == 0
nside = npix2nside(npix)
Imag = np.zeros((npix))
index = np.array([
xyf2pix(nside, x, range(nside), 0, True)
for x in range(nside - 1, -1, -1)
])
for face in range(12):
Imag[index + nside**2 * face] = np.resize(CubeFace[face],
(nside, nside))
if not nested:
NewIm = reorder(Imag, n2r=True)
else:
NewIm = Imag
return NewIm
if os.path.isfile(partial_psf_name):
partial_psfs = np.fromfile(partial_psf_name, dtype='float64')
partial_psfs.shape = (npix_nonzero, np.sum(low_sub_mask))
else:
print "Computing partial PSF, predicted %.1fmin."%(8. * np.sum(low_sub_mask) / 50), datetime.datetime.now()
sys.stdout.flush()
timer = time.time()
partial_psfs = AtNiAi.dot(AtNiA_sum[:, low_sub_mask])
print "%f minutes used" % (float(time.time() - timer) / 60.)
sys.stdout.flush()
partial_psfs.astype('float64').tofile(partial_psf_name)
map_resolution = np.zeros(low_npix) + np.pi / 10.
# map_resolution[low_sub_self_mask] = la.norm([fwhm(partial_psfs[:, c]) for c in range(partial_psfs.shape[1])], axis=-1)
map_resolution[low_sub_self_mask] = np.array([fwhm2(partial_psfs[:, c]) for c in range(partial_psfs.shape[1])])
smoothed_map_resolution = hpf.reorder(hp.smoothing(hpf.reorder(map_resolution, n2r=True), fwhm=2 * hpf.nside2resol(low_nside)), r2n=True)
map_resolution_full = hpf.get_interp_val(smoothed_map_resolution, thetas, phis, nest=True)
map_resolution_full[~total_mask] = np.nan
map_resolution_full.astype('float64').tofile(AtNiAi_filename + '_resolution_nside%i'%low_nside)
#########
####rescale using the rows of the PSF matrix, which I call point collect function (pcf) rather than psf
###########
partial_pcf_name = AtNiAi_filename + '_partialPCF_nside%i'%low_nside
if os.path.isfile(partial_pcf_name):
partial_pcfs = np.fromfile(partial_pcf_name, dtype='float64')
partial_pcfs.shape = (npix_nonzero, np.sum(low_sub_mask))
else:
print "Computing partial PCF, predicted %.1fmin."%(8. * np.sum(low_sub_mask) / 50), datetime.datetime.now()
sys.stdout.flush()
timer = time.time()