def test_copy():
maps_file = remote_data_file('manga-8138-12704-MAPS-{0}.fits.gz'.format(dap_test_daptype))
kin = manga.MaNGAGasKinematics(maps_file)
_kin = kin.copy()
assert kin.vel is not _kin.vel, 'Velocity array points to the same object'
assert numpy.array_equal(kin.vel, _kin.vel), 'Velocity data should be identical'
assert kin.nbin == _kin.nbin, 'Number of bins is not the same'
def test_sbholes():
maps_file = remote_data_file('manga-8138-12704-MAPS-{0}.fits.gz'.format(dap_test_daptype))
kin = manga.MaNGAGasKinematics(maps_file, flux_bound=(0, 100))
sb = kin.remap('sb')
_sb = util.gaussian_fill(sb)
assert numpy.sum(_sb - sb.filled(0.0) > 0) > 250, 'Number of fixed spaxels changed.'
def test_inv_covar():
maps_file = remote_data_file('manga-8078-12703-MAPS-{0}.fits.gz'.format(dap_test_daptype))
kin = manga.MaNGAGasKinematics(maps_file, covar=True)
# Force the covariance matrix to be positive definite
cov = util.impose_positive_definite(kin.vel_covar)
# Invert it
icov = util.cinv(cov.toarray())
# Check that you get back the identity matrix
assert numpy.std(numpy.diag(numpy.dot(icov, cov.toarray())) - 1.) < 1e-4, \
'Multiplication by inverse matrix does not accurately produce identity matrix'
def test_manga_gas_kinematics():
maps_file = remote_data_file('manga-8138-12704-MAPS-{0}.fits.gz'.format(dap_test_daptype))
cube_file = remote_data_file('manga-8138-12704-LOGCUBE.fits.gz')
kin = manga.MaNGAGasKinematics(maps_file, cube_file=cube_file)
_vel = kin.remap('vel', masked=False)
with fits.open(maps_file) as hdu:
eml = manga.channel_dictionary(hdu, 'EMLINE_GVEL')
assert numpy.array_equal(_vel, hdu['EMLINE_GVEL'].data[eml['Ha-6564']]), 'Bad read'
# Check that the binning works. NOTE: This doesn't use
# numpy.array_equal because the matrix multiplication used by bin()
# leads to differences that are of order the numerical precision.
assert numpy.allclose(kin.bin(_vel), kin.vel), 'Rebinning is bad'