py21cmmc.likelihood.LikelihoodPlanck#

class py21cmmc.likelihood.LikelihoodPlanck(*args, tau_mean=0.0569, tau_sigma_u=0.0073, tau_sigma_l=0.0066, **kwargs)[source]#

A likelihood which utilises Planck optical depth data.

In practice, any optical depth measurement (or mock measurement) may be used, by defining the class variables tau_mean and tau_sigma.

This likelihood is vectorized i.e., it accepts an array of astro_params.

Parameters:

  • tau_mean (float) – Mean for the optical depth constraint. By default, it is 0.0569 from Planck 2018 (2006.16828)

  • tau_sigma_u (float) – One sigma errors for the optical depth constraint. By default, it is 0.0081 from Planck 2018 (2006.16828)

  • tau_sigma_l (float) – One sigma errors for the optical depth constraint. By default, it is 0.0066 from Planck 2018 (2006.16828)

Methods

__init__(*args[, tau_mean, tau_sigma_u, ...])

computeLikelihood(model)

Compute the likelihood.

get_fiducial_model()

Compute and return a model dictionary at the fiducial set of parameters.

reduce_data(ctx)

Reduce the data in the context to a model.

setup()

Perform post-init setup.

Attributes

chain

Reference to the LikelihoodComputationChain containing this core.

core_primary

The first core that appears in the requirements.

parameter_names

Names of the parameters of the full chain.

required_cores