xpipe.xhandle.shearops.AutoCalibrateProfile

class xpipe.xhandle.shearops.AutoCalibrateProfile(fname, fname_jk, pzcat, weights=None, id_key='MEM_MATCH_ID', weight_key='WEIGHT', z_key='Z_LAMBDA', sbins=(2, 3), xlims=(0.2, 30), Rs_sbins=None, seed=None, mfactor_sbins=None, mfactor_stds=None)

WEIGHTS must be from the base input dataset for Random points!!!

Automaticall Reads and calibrates weak lensing profiles according to DES Y3 standards

Parameters

• fname (str) – file name

• fname_jk (list of lists) – file names to Jackknife patches

• pzcat (sompz_reader object) – SOMPZ dataset

• weights (DataFrame) – DataFrame of IDs and weights

• id_key (str) – column key for IDs

• weight_key (str) – column key for weights

• z_key (str) – column key for redshifts

• sbins (tuple) – source bins to use

• xlims (tuple) – radius min and max in the units of xshear

• Rs_sbins (list of lists) – selection responses for the source bins

• seed (int) – np.random seed to use when needed

• mfactor_sbins (list) – multiplicative correction to apply for each source bin

• mfactor_stds (int) – std of multiplicative correction to apply for each source bin

add_boost(sboost)

Boost uncertainty is added to the diagonal in quadrature of the covariance

Parameters

sboost (SOMBoost) – Fitted boost factors

add_boost_jk(sboost, mfactor_sbins=None)

Add boost factors by correcting each Jackknife patch

Parameters

sboost (SOMBoost) – Fitted boost factors

combine_sbins(mfactor_sbins=None, mfactor_stds=None, weight_scrit_exponent=1)

Combine source bins

Parameters

• mfactor_sbins (list) – multiplicative correction to apply for each source bin

• mfactor_stds (int) – std of multiplicative correction to apply for each source bin

composite(other, operation)

Add, Subtract, Multiply or Divide this object by an other object of the same class

Parameters

• other (AutoCalibrateProfile) – Object to composite with

• operation (str) – “+, -, *, /”

Return type

AutoCalibrateProfile

copy()

Returns a deep copy of the object

get_profiles(reload=True, scinvs=None, mfactor_sbins=None, mfactor_stds=None, Rs_sbins=None, weights=None, weight_key=None, id_key=None, z_key=None, **kwargs)

Loads and Calculates DeltaSigma profile from a combination of tomographic source bins

Parameters

• reload (bool) – If true, file leading is performed, if false re-processes the already loaded data

• scinvs (list) – list of Sigma Crit inverse values

• mfactor_sbins (list) – mean multiplicative shear bias and redshift bias for each tomographic bin

• Rs_sbins (list of lists) – selection responses for the source bins

• weights (DataFrame) – DataFrame of IDs and weights

• id_key (str) – column key for IDs

• weight_key (str) – column key for weights

• z_key (str) – column key for redshifts

get_scinvs(**kwargs)

Calculates the expected Sigma Crit Inverse from the redshift integral over Pz_src assuming a the mean z_lens

get_scinvs_bin(**kwargs)

Calculates the expected Sigma Crit Inverse from the double redshift integral over Pz_lens and Pz_src

load_profiles(ismeta=True, shear=True, **kwargs)

loads the lensing profiles from file (the xshear output)

Parameters

• ismeta (bool) – try to lead sheared metacal files from disk

• shear (bool) – shear or deltasigma profile as result

load_targets(**kwargs)

loads the lens catalog from file

scale_cut()

Applies radial scale cuts when needed

to_profile()

Extracts a light-weight version of the data container

The only attributes are ‘rr’, ‘dst’, ‘dst_err’ and ‘cov’