def test_covdict_apply_mask(self):
msk = np.random.randint(0, 2, 2 * mpisize).reshape(1, -1)
mskdict = Masks()
comm.Bcast(msk, root=0)
mskdict.append(('test', 'nan', str(2 * mpisize), 'nan'), msk, True)
cov = np.random.rand(2, 2 * mpisize)
covdict = Covariances()
covdict.append(('test', 'nan', str(2 * mpisize), 'nan'), cov, True)
covdict.apply_mask(mskdict)
pix_num = msk.sum()
self.assertTrue(('test', 'nan', str(pix_num), 'nan') in covdict.keys())
def test_covdict_apply_mask(self):
msk = np.array([0, 1, 0, 1, 1]).reshape(1, 5)
mskdict = Masks()
mskdict.append(('test', 'nan', '5', 'nan'), msk, True)
cov_field = Field.from_global_data(RGSpace(shape=(5, 5)),
np.random.rand(5, 5))
arr = cov_field.local_data
covdict = Covariances()
covdict.append(('test', 'nan', '5', 'nan'), arr, True)
covdict.apply_mask(mskdict)
arr = np.delete(cov_field.to_global_data(), [0, 2], 0)
arr = np.delete(arr, [0, 2], 1)
for i in range(arr.shape[0]):
self.assertListEqual(
list((covdict[('test', 'nan', '3',
'nan')].to_global_data())[i]), list(arr[i]))
def test_maskdict_append_array(self):
msk = np.random.randint(0, 2, 48).reshape(1, -1)
comm.Bcast(msk, root=0)
mskdict = Masks()
mskdict.append(('test', 'nan', '2', 'nan'), msk)
local_msk = mskdict[('test', 'nan', '2', 'nan')].data
self.assertListEqual(list(local_msk[0]), list(msk[0]))
mskdict.append(('test', 'nan', '48', 'nan'), msk, True)
local_msk = mskdict[('test', 'nan', '48', 'nan')].data
self.assertListEqual(list(local_msk[0]), list(msk[0]))
def test_maskdict_append_array(self):
msk = np.random.randint(0, 2, 48).reshape(1, 48)
mskdict = Masks()
mskdict.append(('test', 'nan', '2', 'nan'), msk)
raw_msk = mskdict[('test', 'nan', '2', 'nan')].to_global_data()
if mpirank == 0:
self.assertListEqual(list(raw_msk[0]), list(msk[0]))
mskdict.append(('test', 'nan', '48', 'nan'), msk, True)
raw_msk = mskdict[('test', 'nan', '48', 'nan')].to_global_data()
if mpirank == 0:
self.assertListEqual(list(raw_msk[0]), list(msk[0]))
def mask_map(_nside, _freq):
"""
return mask map dictionary for synchrotron Q, U
at given nside and frequency
"""
msk_map = np.zeros(hp.nside2npix(_nside))
for _ipix in range(hp.nside2npix(_nside)):
l, b = hp.pix2ang(_nside, _ipix, lonlat=True)
R = np.pi / 180.
msk_map[_ipix] = 1
L = [329, 100, 124, 315]
B = [17.5, -32.5, 15.5, 48.5]
D = [116, 91, 65, 39.5]
#LOOP I
if (np.arccos(
np.sin(b * R) * np.sin(B[0] * R) +
np.cos(b * R) * np.cos(B[0] * R) * np.cos(l * R - L[0] * R)) <
0.5 * D[0] * R):
msk_map[_ipix] = 0
#LOOP II
elif (np.arccos(
np.sin(b * R) * np.sin(B[1] * R) +
np.cos(b * R) * np.cos(B[1] * R) * np.cos(l * R - L[1] * R)) <
0.5 * D[1] * R):
msk_map[_ipix] = 0
#LOOP III
elif (np.arccos(
np.sin(b * R) * np.sin(B[2] * R) +
np.cos(b * R) * np.cos(B[2] * R) * np.cos(l * R - L[2] * R)) <
0.5 * D[2] * R):
msk_map[_ipix] = 0
#LOOP IV
elif (np.arccos(
np.sin(b * R) * np.sin(B[3] * R) +
np.cos(b * R) * np.cos(B[3] * R) * np.cos(l * R - L[3] * R)) <
0.5 * D[3] * R):
msk_map[_ipix] = 0
#STRIPE
elif (abs(b) < 60.):
msk_map[_ipix] = 0
msk_dict = Masks()
msk_dict.append(('sync', str(_freq), str(_nside), 'Q'),
np.vstack([msk_map]))
msk_dict.append(('sync', str(_freq), str(_nside), 'U'),
np.vstack([msk_map]))
return msk_dict
def test_meadict_apply_mask(self):
msk = np.array([0, 1, 0, 1, 1]).reshape(1, 5)
mskdict = Masks()
comm.Bcast(msk, root=0)
mskdict.append(('test', 'nan', '5', 'nan'), msk, True)
arr = np.array([0., 1., 2., 3., 4.]).reshape(1, 5)
meadict = Measurements()
meadict.append(('test', 'nan', '5', 'nan'), arr, True)
meadict.apply_mask(mskdict)
self.assertListEqual(
list((meadict[('test', 'nan', '3', 'nan')].data)[0]), [1., 3., 4.])
# HEALPix map
msk = np.random.randint(0, 2, 48).reshape(1, 48)
comm.Bcast(msk, root=0)
mskdict.append(('test', 'nan', '2', 'nan'), msk)
arr = np.random.rand(1, 48)
meadict.append(('test', 'nan', '2', 'nan'), arr)
pix_num = msk.sum()
meadict.apply_mask(mskdict)
self.assertTrue(('test', 'nan', str(pix_num), 'nan') in meadict.keys())