dem_pix#

demregpy.dem_pix( dnin, ednin, rmatrix, logt, dlogt, glc, reg_tweak=1.0, max_iter=10, rgt_fact=1.5, dem_norm0=None, nmu=42, warn=True, l_emd=False, )[source]#

Recover a DEM for one observation vector.

Parameters:

dnin (array_like) – Input counts for one observation.
ednin (array_like) – Uncertainties on dnin.
rmatrix (ndarray) – Temperature response of each channel.
logt (array_like) – Log temperature bins.
dlogt (array_like) – Size of temperature bins.
glc (array_like) – Length-nf 0/1 mask selecting the filters used for EM loci weighting.
reg_tweak (float, optional) – Initial Chisq target, by default 1.0
max_iter (int, optional) – Max number of iterations to reach target chisq before giving up, by default 10
rgt_fact (float, optional) – Factor to increase chisq by each iteration, by default 1.5
dem_norm0 (array_like, optional) – Initial guess at the dem shape, by default 0
nmu (int, optional) – number of reg param samples to use, by default 42
warn (bool, optional) – Print warnings, by default False
l_emd (bool, optional) – Remove sqrt from constraint matrix, by default False

Returns:

dem (ndarray) – Recovered DEM values.
edem (ndarray) – Vertical uncertainties on dem.
elogt (ndarray) – Horizontal temperature resolution estimates in log10(T).
chisq (array_like) – Reduced chi-squared value.
dn_reg (ndarray) – Reconstructed counts for each filter.