NGGCorrelation: Lens-Shear-Shear Correlations

The NGGCorrelation class computes the correlation of one scalar field and two spin-2 fields.

Example

import orpheus

scat = orpheus.SpinTracerCatalog(
    spin=2, pos1=x, pos2=y, tracer_1=g1, tracer_2=g2)
lcat = orpheus.ScalarTracerCatalog(
    pos1=x, pos2=y, tracer=weight)
ngg = orpheus.NGGCorrelation(
    min_sep=1., max_sep=128., binsize=0.1, nthreads=nthreads)
ngg.process(scat,lcat)  # Compute 3PCF in multipole basis
ngg.multipoles2npcf()   # Transform to real-space basis
class orpheus.NGGCorrelation(min_sep, max_sep, **kwargs)[source]

Bases: BinnedNPCF

Class containing methods to measure and obtain statistics that are built from third-order lens-shear-shear correlation functions.

min_sep

The smallest distance of each vertex for which the NPCF is computed.

Type

float

max_sep

The largest distance of each vertex for which the NPCF is computed.

Type

float

Notes

Inherits all other parameters and attributes from BinnedNPCF. Additional child-specific parameters can be passed via kwargs. Either nbinsr or binsize has to be provided to fix the binning scheme.

Note that the different components of the NGG correlator are ordered as

\[\left[ \tilde{G}_-, \tilde{G}_+, \right] \ ,\]

which is different to the usual conventions, but matches orpheus’ conventions to always start with a correlator in which no polar field is complex conjugated.

__process_patches(cat_source, cat_lens, dotomo_source=True, dotomo_lens=True, rotsignflip=False, apply_edge_correction=False, save_patchres=False, save_filebase='', keep_patchres=False)
process(cat_source, cat_lens, dotomo_source=True, dotomo_lens=True, rotsignflip=False, apply_edge_correction=False, save_patchres=False, save_filebase='', keep_patchres=False)[source]

Compute a lens-shear-shear correlation provided a source and a lens catalog.

Parameters

  • cat_source (orpheus.SpinTracerCatalog) – The source catalog which is processed

  • cat_lens (orpheus.ScalarTracerCatalog) – The lens catalog which is processed

  • dotomo_source (bool) – Flag that decides whether the tomographic information in the source catalog should be used. Defaults to True.

  • dotomo_lens (bool) – Flag that decides whether the tomographic information in the lens catalog should be used. Defaults to True.

  • rotsignflip (bool) – If the shape catalog has been decomposed in patches, choose whether the rotation angle should be flipped. For simulated data this was always ok to set to False. Defaults to False.

  • apply_edge_correction (bool) – Flag that decides how the NPCF in the real space basis is computed. * If set to True the computation is done via edge-correcting the NGG-multipoles * If set to False both NGG and NNN are transformed separately and the ratio is done in the real-space basis Defaults to False.

  • save_patchres (bool or str) – If the shape catalog has been decomposed in patches, flag whether to save the NGG measurements on the individual patches. Note that the path needs to exist, otherwise a ValueError is raised. For a flat-sky catalog this parameter has no effect. Defaults to False.

  • save_filebase (str) – Base of the filenames in which the patches are saved. The full filename will be <save_patchres>/<save_filebase>_patchxx.npz. Only has an effect if the shape catalog consists of multiple patches and save_patchres is not False.

  • keep_patchres (bool) – If the catalog consists of multiple patches, returns all measurements on the patches. Defaults to False.

edge_correction(ret_matrices=False)[source]
multipoles2npcf(integrated=False)[source]

Notes

  • When dividing by the (weighted) counts N, all contributions for which N <= 0 are set to zero.

projectnpcf(projection)[source]
computeNMM(radii, do_multiscale=False, tofile=False, filtercache=None)[source]

Compute third-order aperture statistics

_NMM_filtergrid(R1, R2, R3)[source]
__NMM_filtergrid(R2, R3, edges, centers, phis)
_checkcats(cats, spins)
_initprojections(child)
_print_npcfprojections_avail(child)
_projectnpcf(child, projection)

Projects npcf to a new basis.

_updatetree(new_resos, include_shifts=True)
autoset_tree(cat, dpix_grid=2.0, nside_grid=2048)