sp_validation.catalog_builders

CATALOG BUILDERS.

Catalogue construction pipeline — the runner classes that create, mask, and calibrate joint comprehensive catalogues, plus the run_* entry-point functions. Built on the catalogue data layer in catalog (imported here as sp_cat), which supplies the read/write/column-access/matching primitives.

Author:

Martin Kilbinger

class Mask(col_name, label, kind=None, value=0, col_name2=None, dat=None, verbose=False)

Bases: object

Mask.

Class to handle masking of catalogues.

Parameters:

• col_name (str) – name of column to use for mask

• label (str) – mask label

• kind (str) – operation type; see apply_condition() for the allowed values, plus “not_equal_2bands”, which keeps objects whose value differs from value in col_name or col_name2 (two-band OR)

• value (float or list) – value(s) to be used in mask operation

• col_name2 (str, optional) – name of second column; required for (and only used by) kind “not_equal_2bands”

• dat (numpy.ndarray, optional) – input data, default is None; apply mask if given

• verbose (bool, optional) – verbose output if True; default is False

classmethod from_list(masks, label='combined', verbose=False)

apply(dat)

to_bool(hsp_mask)

classmethod print_strings(coln, lab, num, fnum, f_out=None)

print_stats(num_obj, f_out=None)

get_sign(latex=False)

print_condition(f_out, latex=False)

print_summary(f_out)

create_descr()

Create Descr.

Create description of mask for later use in output file header.

Returns:

description

Return type:

str

add_summary_to_FITS_header(header)

get_masks_from_config(config, dat, masks_to_apply=None, verbose=False)

Get Masks From Config.

Return the masks of the config’s dat cut list (catalogue_cuts), evaluated on dat.

Parameters:

• config (dict) – config information

• dat (numpy.ndarray or grammar.V2View) – input catalogue, in the v2 column grammar (e.g. from CalibrateCat.read_cat)

• masks_to_apply (list, optional) – masks to apply exclusively; if None (default), use all masks

• verbose (bool, optional) – verbose output if True; default is False

Returns:

• list – list of masks

• dict – list of indices for given mask column name (label)

print_mask_stats(num_obj, masks, mask_combined)

Print Mask Stats.

Print mask statistics.

Parameters:

num_obj

correlation_matrix(masks, confidence_level=0.9)

confusion_matrix(prediction, observation)