sp_validation.basic

BASIC.

Name:

basic.py

Description:

This file contains methods for calibration (metacalibration) and basic validation of a weak-lensing shape catalogue independent of cosmology.

Author:

Axel Guinot, Martin Kilbinger

class metacal(data, mask, masking_type='gal', step=0.01, prefix='NGMIX', snr_min=10, snr_max=500, rel_size_min=0.5, rel_size_max=3.0, size_corr_ell=True, global_R_weight=None, sigma_eps=0.34, col_2d=True, verbose=False)[source]

Bases: object

Metacal.

Metacalibration.

Parameters:

  • data – input galaxy catalogue

  • mask (array of bool) – mask according to galaxy selection, e.g. spread_model

  • masking_type (string, optional, default='gal') – masking type, one in ‘gal’, ‘gal_mom’, ‘star’

  • step (float, optional, default=0.01) – step h in finite differences

  • prefix (string, optional, default='NGMIX') – to specify columns in input catalogue

  • snr_min (float, optional, default=10) – signal-to-noise minimum

  • float (snr_max;) – signal-to-noise maximum

  • optional – signal-to-noise maximum

  • default=500 – signal-to-noise maximum

  • rel_size_min (float, optional, default=0.5) – relative size minimum

  • rel_size_max (float, optional, default=3.0) – relative size maximum

  • size_corr_ell (bool, optional, default=True)

  • global_R_weight (str, optional,) – weight column name for global response matrix; default is None (unweighted mean)

  • sigma_eps (float, optional) – ellipticity dispersion (one component) for computation of weights; default is 0.34

  • col_2d (bool, optional) – if True (default, ellipticity in one 2D column; if False, ellipticity in two columns ELL_0, ELL_1

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

_read_data(data, mask)[source]

Read Data.

Read relevant data columns.

_read_data_ngmix(masked_data, m1, p1, m2, p2, ns)[source]

Read Data Ngmix.

Read data from ngmix catalogue.

static get_variance_ivweights(data, sigma_eps, prefix='NGMIX', mask=None, col_2d=True)[source]

Get Variance IVWEIGHTS.

Compute variance and inverse-variance weights.

Parameters:

  • data (numpy.ndarray) – input data

  • sigma_eps (float) – ellipticity dispersion

  • prefix (str, optional) – shape measurement identifier; default is “NGMIX”

  • mask (list, optional) – indicates valid objects with True values; default is None = use all objects type has to be bool

  • col_2d (bool, optional) – if True (default), ellipticity is given in single 2D column; if False, ellipticity is expected in two 1D columns.

Returns:

  • float – variance first component

  • float – variance second component

  • float – weight

_read_data_galsim(masked_data, m1, p1, m2, p2, ns)[source]

Read Data Galsim.

Read data from galsim catalogue.

_compute_calibration()[source]

Compute Calibration.

Perform masking and compute calibration.

add_cuts(snr_min=10, snr_max=500, rel_size_min=0.5)[source]

Add Cuts.

Apply additional cuts to metacal galaxy catalogue.

_masking_gal()[source]

Masking Gal.

Mask metacal catalogue, i.e. apply cuts.

_masking_gal_mom()[source]

Add docstring.

…

_masking_star()[source]

Add docstring.

…

_shear_response()[source]

Shear Response.

Compute shear response matrix

_shear_response_std(stat_operator=<function metacal.<lambda>>)[source]

Shear Response Std.

Standard deviation of shear response

_selection_response()[source]

Add docstring.

…

_total_response()[source]

Add docstring.

…

_return()[source]

Add docstring.

…

jackknif_weighted_average2(data, weights, remove_size=0.1, n_realization=100)[source]

Add docstring.

…

mask_gal_size(T, Tpsf, rel_size_min, rel_size_max, size_corr_ell=False, g1=None, g2=None)[source]
mask_gal_SNR(SNR, snr_min, snr_max)[source]