rail.interactive.creation.degraders.desi_selector_phy module

rail.interactive.creation.degraders.desi_selector_phy.spec_selection_desi_phy(**kwargs)

DESI tracer selector based on pre-computed redshift-dependent thresholds.

Applies a selection to a simulation catalog by comparing a physical parameter column against a threshold that varies with redshift. The threshold table is provided externally (e.g. from abundance matching) and is not computed by this stage.

All supported DESI tracer types (bgs, lrg, elg) select objects whose physical parameter value is above the redshift-interpolated threshold.

Inputs

inputPqHandle

Simulation catalog containing the physical parameter column and a redshift column.

threshold_tableTableHandle

Table with two columns:

• z : redshift bin centers

• thresh: threshold values at those redshift centers

Output

outputPqHandle

Catalog after applying the DESI selection mask.

—

Apply the DESI physical selection to a catalog.

—

This function was generated from the function rail.creation.degraders.desi_selector_phy.SpecSelection_DESI_Phy.__call__

param sample:

Input simulation catalog.

type sample:

table-like or PqHandle, required

param drop_rows:

Drop selected rows from output table Default: True

type drop_rows:

bool, optional

param seed:

Set to an int to force reproducible results. Default: None

type seed:

unknown type, optional

param desi_type:

DESI tracer type: ‘bgs’, ‘lrg’, or ‘elg’ Default: lrg

type desi_type:

str, optional

param threshold_col:

Column in the input catalog used for threshold-based selection (e.g. ‘log_peak_sub_halo_mass’ for bgs/lrg, ‘log_sfr’ for elg) Default: None

type threshold_col:

str, optional

param redshift_col:

Column name for redshift in the input catalog Default: redshift

type redshift_col:

str, optional

param threshold_table:

Filename of the threshold file Default: None

type threshold_table:

str, optional

returns:

Handle to the output catalog containing only the selected objects (when drop_rows=True, the default) or the full catalog with a flag column (when drop_rows=False).

rtype:

pandas.core.frame.DataFrame

Return type:

Any