plima.models#

Intrinsic-alignment model families.

plima.models.nla_amplitude(z, *, a_ia)[source]#

Return a constant NLA amplitude on a redshift grid.

Parameters:

z (ArrayLike) – Redshift values where the amplitude should be evaluated.
a_ia (float) – Constant intrinsic alignment amplitude.

Returns:

Array with the same shape as z containing the constant amplitude.

Raises:

ValueError – If any redshift value is not finite.

Return type:

ndarray[tuple[Any, …], dtype[float64]]

plima.models.nla_mass_amplitude(*, a_ia, red_fraction, halo_mass, beta, pivot_halo_mass=31622776601683.793)[source]#

Return a galaxy type and halo mass dependent NLA amplitude.

Parameters:

a_ia (float) – Overall intrinsic alignment amplitude.
red_fraction (ArrayLike) – Red galaxy fraction for each sample, bin, or object.
halo_mass (ArrayLike) – Halo mass values.
beta (float) – Power law dependence of the IA amplitude on halo mass.
pivot_halo_mass (float) – Pivot halo mass used to normalize the mass scaling. Defaults to the pivot halo mass used in arXiv:2409.15416 and arXiv:2503.19441.

Returns:

NLA amplitude weighted by red fraction and halo mass.

Raises:

ValueError – If red_fraction is outside the interval from zero to one.
ValueError – If any halo mass value is not positive.
ValueError – If pivot_halo_mass is not positive.

Return type:

ndarray[tuple[Any, …], dtype[float64]]

plima.models.nla_z_amplitude(z, *, a_ia, b_ia, pivot_redshift=0.62)[source]#

Return the KiDS style redshift dependent NLA amplitude.

Parameters:

z (ArrayLike) – Redshift values where the amplitude should be evaluated. Values may be negative for future scale factors, but must be greater than -1.
a_ia (float) – Intrinsic alignment amplitude at the pivot redshift.
b_ia (float) – Linear scale factor dependence of the IA amplitude.
pivot_redshift (float) – Pivot redshift used to define the redshift dependence. This may be negative, but must be greater than -1.

Returns:

Redshift dependent NLA amplitude evaluated at z.

Raises:

ValueError – If any redshift value is less than or equal to -1.
ValueError – If pivot_redshift is less than or equal to -1.

Return type:

ndarray[tuple[Any, …], dtype[float64]]

plima.models.p_delta_i_nla(matter_power, growth_factor, omega_m, *, amplitude, c1_rho_critical=0.0134)[source]#

Return the NLA matter intrinsic power spectrum.

Parameters:

matter_power (ArrayLike) – Matter power spectrum values.
growth_factor (ArrayLike) – Linear growth factor evaluated consistently with matter_power.
omega_m (float) – Present day matter density fraction.
amplitude (ArrayLike | float) – NLA amplitude. This may be a scalar or an array matching matter_power.
c1_rho_critical (float) – Conventional NLA normalization C1 * rho_crit.

Returns:

Matter intrinsic power spectrum predicted by the NLA model.

Raises:

ValueError – If any matter power value is not finite.
ValueError – If any growth factor value is not positive.

Return type:

ndarray[tuple[Any, …], dtype[float64]]

plima.models.p_ii_nla(matter_power, growth_factor, omega_m, *, amplitude, c1_rho_critical=0.0134)[source]#

Return the NLA intrinsic-intrinsic power spectrum.

Parameters:

matter_power (ArrayLike) – Matter power spectrum values.
growth_factor (ArrayLike) – Linear growth factor evaluated consistently with matter_power.
omega_m (float) – Present day matter density fraction.
amplitude (ArrayLike | float) – NLA amplitude. This may be a scalar or an array matching matter_power.
c1_rho_critical (float) – Conventional NLA normalization C1 * rho_crit.

Returns:

Intrinsic intrinsic power spectrum predicted by the NLA model.

Raises:

ValueError – If any matter power value is not finite.
ValueError – If any growth factor value is not positive.

Return type:

ndarray[tuple[Any, …], dtype[float64]]

Modules

`halo_model`	Halo model intrinsic alignment parameter models.
`la`	Linear alignment intrinsic alignment models.
`model_registry`	Registry for PLIMA model functions.
`nla`	Nonlinear alignment intrinsic alignment models.
`tatt`	TATT intrinsic alignment amplitude models.