synthesize_counts#

demregpy.synthetic.synthesize_counts( dem, logt, tresp, *, error_fraction=0.1, noise_fraction=None, min_fraction=0.1, random_state=None, )[source]#

Fold a DEM through a temperature response matrix and build synthetic counts.

Parameters:

dem (array_like) – DEM values on the logt grid. The last axis must match logt. Leading dimensions are preserved in the output.
logt (array_like) – Log10 temperature grid corresponding to the first axis of tresp.
tresp (array_like) – Temperature response matrix with shape (nt, nf).
error_fraction (float or array_like, optional) – Relative uncertainty applied to the clean counts when building edn_in. Defaults to 0.1.
noise_fraction (float or array_like, optional) – Relative Gaussian noise applied to the clean counts. If omitted, the returned dn_in is noise-free.
min_fraction (float, optional) – Lower bound applied to noisy counts as a fraction of the clean counts.
random_state (int or numpy.random.Generator, optional) – Random seed or generator used when noise_fraction is provided.

Returns:

Synthetic DEM, clean counts, input counts, and uncertainties.

Return type:

SyntheticObservation