dsigma.surveys module

Module with functions specific to the CFHTLenS survey.

dsigma.surveys.cfhtls.default_column_keys(version=None)

Return a dictionary of default column keys.

Parameters:
versionoptional

Ignored.

Returns:
keysdict

Dictionary of default column keys.

Module with functions specific to the Dark Energy Survey.

dsigma.surveys.des.default_column_keys(version='Y3')

Return a dictionary of default column keys.

Parameters:
versionstring or None, optional

Version of the catalog.

Returns:
keysdict

Dictionary of default column keys.

Raises:
ValueError

If version does not correspond to a known catalog version.

dsigma.surveys.des.multiplicative_shear_bias(z_bin, version='Y3')

Return the multiplicative shear bias.

For DES Y3, we can define a blending-related multiplicative shear bias. This function returns the multiplicative bias \(m\) as a function of the bin. The values can be computed from the blending-corrected Y3 redshift distributions and are, as expected, very similar to the values in Table 4 in MacCrann et al. (2022) where they were calculated for mock catalogs.

Parameters:
z_binnumpy.ndarray

Tomographic redshift bin.

versionstring, optional

Which catalog version to use.

Returns:
mnumpy.ndarray

The multiplicative shear bias corresponding to each tomographic bin.

Raises:
ValueError

If the version does not correspond to a known catalog version or multiplicative shear biases cannot be defined for this version of the catalog.

dsigma.surveys.des.selection_response(table_s, version='Y3')

Calculate the DES selection response.

See Sheldon & Huff (2017) and McClintock et al. (2018) for details.

Parameters:
table_sastropy.table.Table

Catalog of sources.

versionstring, optional

Which catalog version to use.

Returns:
R_selnumpy.ndarray

2x2 matrix containing the selection response.

dsigma.surveys.des.tomographic_redshift_bin(z_s, version='Y3')

Return the photometric redshift bin.

Parameters:
z_snumpy.ndarray

Photometric redshifts.

versionstring, optional

Which catalog version to use.

Returns:
z_binnumpy.ndarray

The tomographic redshift bin corresponding to each photometric redshift. Returns -1 in case a redshift does not fall into any bin.

Raises:
ValueError

If the version does not correspond to a known catalog version or if tomographic bins were not assigned based on photometric redshifts for the given catalog version.

Module with functions specific to the Hyper-Suprime Cam survey.

dsigma.surveys.hsc.default_column_keys(version='Y3')

Return a dictionary of default column keys.

Parameters:
versionstring or None, optional

Version of the catalog.

Returns:
keysdict

Dictionary of default column keys.

Raises:
ValueError

If version does not correspond to a known catalog version.

dsigma.surveys.hsc.multiplicative_selection_bias(table_s, version='Y3')

Compute the multiplicative selection bias.

Parameters:
table_sastropy.table.Table

HSC weak lensing source catalog.

Returns:
m_selnumpy.ndarray

Per-object estimate of the HSC selection bias \(m_\mathrm{sel}\).

Module with functions specific to the Kilo Degree Survey.

dsigma.surveys.kids.default_column_keys(version='DR4')

Return a dictionary of default column keys.

Parameters:
versionstring or None, optional

Version of the catalog.

Returns:
keysdict

Dictionary of default column keys.

Raises:
ValueError

If version does not correspond to a known catalog version.

dsigma.surveys.kids.multiplicative_shear_bias(z_bin, version='DR4')

Return the multiplicative shear bias.

For many version of KiDS, the multiplicative shear bias is not estimated on the basis of individual sources but for broad photometric redshift bins. This function returns the multiplicative bias \(m\) as a function of the bin.

Parameters:
z_binnumpy.ndarray

Tomographic redshift bin.

versionstring

Which catalog version to use.

Returns:
mnumpy.ndarray

The multiplicative shear bias corresponding to each tomographic bin.

Raises:
ValueError

If the version does not correspond to a known catalog version or multiplicative shear biases cannot be defined for this version of the catalog.

dsigma.surveys.kids.tomographic_redshift_bin(z_s, version='DR4')

Return the photometric redshift bin.

Parameters:
z_snumpy.ndarray

Photometric redshifts.

versionstring, optional

Which catalog version to use. Currently ignored.

Returns:
z_binnumpy.ndarray

The tomographic redshift bin corresponding to each photometric redshift. Returns -1 in case a redshift does not fall into any bin.