CLASS Power Spectrum¶

Calculate the matter power spectrum using CLASS

class spectrumclass.powerclass[source]¶

Bases: object

Uses CLASS to compute the matter power spectrum

class_compute(parameters: dict)[source]¶

Calculate the relevant quantities using CLASS

Param: parameters (dict) : dictionary of input parameters to CLASS
Returns: class_module : the whole CLASS module (which contains distances, age, temperature and others)

configurations() → None[source]¶: Calculate and store the basic configurations which will be used by CLASS. This requires setting up a dictionary for the quantities we want CLASS to take as default and also the quantity we want CLASS to output.

derivatives(params: dict, order: int = 1, eps: list = [0.001], **kwargs) → numpy.ndarray[source]¶

Calculates the gradient of the power spectrum at a point in parameter space

Param: params (dict) : a point within the prior box
Param: eps (float) : epsilon - using central finite difference method to calculate gradient
Returns: grad (list) : an array containing the gradient of each parameter (of size (nk x nz) x ndim), for example 800 x 7

pk_nonlinear(parameters: dict, **kwargs) → numpy.ndarray[source]¶

Calculate the 3D matter power spectrum based on the emulator setting file

pk_nonlinear_components(parameters: dict, zref: float = 0.0, **kwargs) → dict[source]¶

The non-linear 3D matter power spectrum can be decomposed into:

P_nonlinear (k,z) = A(z) [1 + q(k,z)] P_linear (k,z0)

Calculates the following quantities:

Param: parameters (dict) - inputs to calculate the matter power spectrum
Param: zref (float) - the reference redshift at which the linear matter power spectrum is calculated (DEFAULT: 0.0)
Returns: quantities (dictionary) - dictionary consisting of the nonlinear power spectrum, linear power spectrum, growth factor and the non-linear function q(k,z)

pk_nonlinear_timed(parameters: dict) → dict[source]¶

Calculate the non linear matter power spectrum but within an allocated period of time