nbodykit.transform¶

Functions

`ConcatenateSources`(sources, *kwargs)	Concatenate CatalogSource objects together, optionally including only certain columns in the returned source.
`ConstantArray`(value, size[, chunks])	Return a dask array of the specified `size` holding a single value.
`HaloConcentration`(mass, cosmo, redshift[, mdef])	Return halo concentration from halo mass, based on the analytic fitting formulas presented in Dutton and Maccio 2014.
`HaloRadius`(mass, cosmo, redshift[, mdef])	Return halo radius from halo mass, based on the specified mass definition.
`SkyToCartesian`(ra, dec, redshift, cosmo[, …])	Convert sky coordinates (`ra`, `dec`, `redshift`) to a Cartesian `Position` column.
`SkyToUnitSphere`(ra, dec[, degrees])	Convert sky coordinates (`ra`, `dec`) to Cartesian coordinates on the unit sphere.
`StackColumns`(*cols)	Stack the input dask arrays vertically, column by column.

nbodykit.transform.ConcatenateSources(*sources, **kwargs)[source]¶

Concatenate CatalogSource objects together, optionally including only certain columns in the returned source.

Note

The returned catalog object carries the meta-data from only the first catalog supplied to this function (in the attrs dict).

Parameters:	sources (subclass of `CatalogSource`) – the catalog source objects to concatenate together columns* (str, list of str, optional) – the columns to include in the concatenated catalog
Returns:	the concatenated catalog source object
Return type:	CatalogSource

Examples

>>> from nbodykit.lab import *
>>> source1 = UniformCatalog(nbar=100, BoxSize=1.0)
>>> source2 = UniformCatalog(nbar=100, BoxSize=1.0)
>>> print(source1.csize, source2.csize)
>>> combined = transform.ConcatenateSources(source1, source2, columns=['Position', 'Velocity'])
>>> print(combined.csize)

nbodykit.transform.ConstantArray(value, size, chunks=100000)[source]¶

Return a dask array of the specified size holding a single value.

This uses numpy’s “stride tricks” to avoid replicating the data in memory for each element of the array.

Parameters:	value (float) – the scalar value to fill the array with size (int) – the length of the returned dask array chunks (int, optional) – the size of the dask array chunks

nbodykit.transform.HaloConcentration(mass, cosmo, redshift, mdef='vir')[source]¶

Return halo concentration from halo mass, based on the analytic fitting formulas presented in Dutton and Maccio 2014.

Note

The units of the input mass are assumed to be \(M_{\odot}/h\)

Parameters:	mass (array_like) – either a numpy or dask array specifying the halo mass; units assumed to be \(M_{\odot}/h\) cosmo (`Cosmology`) – the cosmology instance used in the analytic formula redshift (float) – compute the c(M) relation at this redshift mdef (str, optional) – string specifying the halo mass definition to use; should be ‘vir’ or ‘XXXc’ or ‘XXXm’ where ‘XXX’ is an int specifying the overdensity
Returns:	concen – a dask array holding the analytic concentration values
Return type:	`dask.array.Array`

References

Dutton and Maccio, “Cold dark matter haloes in the Planck era: evolution of structural parameters for Einasto and NFW profiles”, 2014, arxiv:1402.7073

nbodykit.transform.HaloRadius(mass, cosmo, redshift, mdef='vir')[source]¶

Return halo radius from halo mass, based on the specified mass definition. This is independent of halo profile, and simply returns

\[R = \left [ 3 M /(4\pi\Delta) \right]^{1/3}\]

where \(\Delta\) is the density threshold, which depends on cosmology, redshift, and mass definition

Note

The units of the input mass are assumed to be \(M_{\odot}/h\)

Parameters:	mass (array_like) – either a numpy or dask array specifying the halo mass; units assumed to be \(M_{\odot}/h\) cosmo (`Cosmology`) – the cosmology instance redshift (float) – compute the density threshold which determines the R(M) relation at this redshift mdef (str, optional) – string specifying the halo mass definition to use; should be ‘vir’ or ‘XXXc’ or ‘XXXm’ where ‘XXX’ is an int specifying the overdensity
Returns:	radius – a dask array holding the halo radius
Return type:	`dask.array.Array`

nbodykit.transform.SkyToCartesian(ra, dec, redshift, cosmo, degrees=True)[source]¶

Convert sky coordinates (ra, dec, redshift) to a Cartesian Position column.

Warning

The returned Cartesian position is in units of Mpc/h.

Parameters:	ra (`dask.array.Array`; shape: (N,)) – the right ascension angular coordinate dec (`dask.array.Array`; shape: (N,)) – the declination angular coordinate redshift (`dask.array.Array`; shape: (N,)) – the redshift coordinate cosmo (`Cosmology`) – the cosmology used to meausre the comoving distance from `redshift` degrees (bool, optional) – specifies whether `ra` and `dec` are in degrees
Returns:	pos – the cartesian position coordinates, where columns represent `x`, `y`, and `z` in units of Mpc/h
Return type:	`dask.array.Array`; shape: (N,3)
Raises:	`TypeError` – If the input columns are not dask arrays

nbodykit.transform.SkyToUnitSphere(ra, dec, degrees=True)[source]¶

Convert sky coordinates (ra, dec) to Cartesian coordinates on the unit sphere.

Parameters:	ra (`dask.array.Array`; shape: (N,)) – the right ascension angular coordinate dec (`dask.array.Array`; ; shape: (N,)) – the declination angular coordinate degrees (bool, optional) – specifies whether `ra` and `dec` are in degrees or radians
Returns:	pos – the cartesian position coordinates, where columns represent `x`, `y`, and `z`
Return type:	`dask.array.Array`; shape: (N,3)
Raises:	`TypeError` – If the input columns are not dask arrays

nbodykit.transform.StackColumns(*cols)[source]¶

Stack the input dask arrays vertically, column by column.

This uses dask.array.vstack().

Parameters:	*cols (`dask.array.Array`) – the dask arrays to stack vertically together
Returns:	the dask array where columns correspond to the input arrays
Return type:	`dask.array.Array`
Raises:	`TypeError` – If the input columns are not dask arrays