pybird.projection module

pybird.projection.cH(Om, a)

LCDM growth rate auxiliary function

pybird.projection.DgN(Om, a)

LCDM growth rate auxiliary function

pybird.projection.fN(Om, z)

LCDM growth rate

pybird.projection.Hubble(Om, z)

LCDM AP parameter auxiliary function

pybird.projection.DA(Om, z)

LCDM AP parameter auxiliary function

pybird.projection.W2D(x)

Fiber collision effective window method auxiliary function

pybird.projection.Hllp(l, lp, x)

Fiber collision effective window method auxiliary function

pybird.projection.fllp_IR(l, lp, k, q, Dfc)

Fiber collision effective window method auxiliary function

pybird.projection.fllp_UV(l, lp, k, q, Dfc)

Fiber collision effective window method auxiliary function

class pybird.projection.Projection(xout, with_ap=False, H_fid=None, D_fid=None, with_survey_mask=False, survey_mask_arr_p=None, survey_mask_mat_kp=None, with_binning=False, binsize=None, fibcol=False, with_wedge=0, wedge_mat_wl=None, with_redshift_bin=False, redshift_bin_zz=None, redshift_bin_nz=None, co=<pybird.common.Common object>)

Bases: object

A class for applying observational projection effects to power spectra and correlation functions.

The Projection class handles various observational effects that transform the theoretical prediction into a form that can be directly compared with survey data. These effects include:

• Alcock-Paczynski (AP) effect: Accounts for the distortion due to assuming an incorrect fiducial cosmology when converting redshifts to distances.

• Survey window functions: Convolves the power spectrum with the survey mask.

• k-binning or interpolation: Maps the model k-array to the data k-array.

• Fiber collision corrections: Applies corrections for missing galaxy pairs due to fiber collisions in spectroscopic surveys.

• Multipole to wedge conversion: Transforms multipole expansion to angular wedges.

• Redshift bin evolution: Accounts for evolution of clustering across the redshift bin.

co

Common parameters object with configuration settings.

Type:

Common

cf

Whether working with correlation function (True) or power spectrum (False).

Type:

bool

xout

Output k or s array matching the data.

Type:

ndarray

# AP effect attributes

H_fid

Fiducial Hubble parameter.

Type:

float

D_fid

Fiducial angular diameter distance.

Type:

float

muacc

Mu grid for AP integration.

Type:

ndarray

sgrid, musgrid

Meshgrid of s and mu for correlation function.

Type:

ndarray

kgrid, mukgrid

Meshgrid of k and mu for power spectrum.

Type:

ndarray

arrayLegendremusgrid

Legendre polynomials evaluated on musgrid.

Type:

ndarray

arrayLegendremukgrid

Legendre polynomials evaluated on mukgrid.

Type:

ndarray

# Survey window attributes

arr_p

Array of p values for window function.

Type:

ndarray

mat_kp

Window function matrix.

Type:

ndarray

# Binning attributes

binvol

Volume of each k-bin.

Type:

ndarray

points

List of k-values within each bin.

Type:

list

# Wedge attributes

wedge_mat_wl

Transformation matrix from multipoles to wedges.

Type:

ndarray

# Redshift bin attributes

zz

Array of redshift values across the bin.

Type:

ndarray

nz

Number density as function of redshift.

Type:

ndarray

s, z1, mu

Meshgrid of separation, redshift and angle.

Type:

ndarray

n1

Number density evaluated on the meshgrid.

Type:

ndarray

L

Legendre polynomials for 3D reconstruction.

Type:

ndarray

Lp

Legendre polynomials for multipole integration.

Type:

ndarray

ft

Fourier transform object for s-k conversions.

Type:

FourierTransform

get_AP_param()

Compute the AP parameters qperp and qpar.

integrAP()

Perform AP integration over mu.

AP()

Apply the AP effect to power spectrum or correlation function.

integrWindow()

Convolve window function with power spectrum.

Window()

Apply survey window function to power spectrum.

dPuncorr()

Compute uncorrelated fiber collision contribution.

dPcorr()

Compute correlated fiber collision contribution.

fibcolWindow()

Apply fiber collision corrections.

loadBinning()

Create bins for data k-array.

integrBinning()

Integrate over each k-bin.

xbinning()

Apply k-space binning for linear-spaced data.

xdata()

Interpolate to data k-array.

integrWedges()

Convert multipoles to wedges.

Wedges()

Apply multipole to wedge transformation.

Wedges_external()

Apply wedge transformation to external data.

mesheval1d()

Evaluate 1D function on mesh grid.

redshift()

Apply redshift evolution across the survey volume.

get_AP_param(bird=None, DA=None, H=None)

Compute the AP parameters

integrAP(k, Pk, kp, arrayLegendremup)

AP integration Credit: Jerome Gleyzes

AP(bird=None, q=None)

Apply the AP effect to the bird power spectrum or correlation function Credit: Jerome Gleyzes

integrWindow(P)

Convolve the window functions to a power spectrum P

Window(bird)

Apply the survey window function to the bird power spectrum

dPuncorr(xout, fs=0.6, Dfc=0.6344990408735429)

Compute the uncorrelated contribution of fiber collisions

kPS : a cbird wavenumber output, typically a (39,) np array fs : fraction of the survey affected by fiber collisions Dfc : angular distance of the fiber channel Dfc(z = 0.55) = 0.43Mpc

Credit: Thomas Colas

dPcorr(xout, kPS, PS, many=False, ktrust=0.25, fs=0.6, Dfc=0.6344990408735429)

Compute the correlated contribution of fiber collisions

kPS : a cbird wavenumber output, typically a (39,) np array PS : a cbird power spectrum output, typically a (3, 39) np array ktrust : a UV cutoff fs : fraction of the survey affected by fiber collisions Dfc : angular distance of the fiber channel Dfc(z = 0.55) = 0.43Mpc

Credit: Thomas Colas

fibcolWindow(bird)

Apply window effective method correction to fiber collisions to the bird power spectrum

loadBinning(xout, binsize)

Create the bins of the data k’s

integrBinning(P)

Integrate over each bin of the data k’s

xbinning(bird)

Apply binning in k-space for linear-spaced data k-array

xdata(bird)

Interpolate the bird power spectrum on the data k-array

integrWedges(P)

Wedges(bird)

Rotate multipoles to wedges

Wedges_external(P)

mesheval1d(z1d, zm, func)

redshift(bird, rz, Dz, fz, pk='Pk')