py21cmmc.likelihood.LikelihoodForest#

class py21cmmc.likelihood.LikelihoodForest(name='', observation='bosman_optimistic', *args, **kwargs)[source]#

A likelihood based on chi^2 comparison to measured CDF of Lyman-alpha forest effective optical depth.

This is the likelihood arising from Bosman et al. (2018), which reports new constraints on Lyman-alpha opacity with a sample of 62 quasars at z>5.7, or D’Odorico et al. in prep., which includes new samples from the XQR-30 survey.

Parameters:

name (str) – The name used to match the core
observation (str) – The observation that is used to construct the tau_eff statisctic.

Methods

`__init__`([name, observation])
`computeLikelihood`(model)	Compute the likelihood, given the lightcone output from 21cmFAST.
`get_fiducial_model`()	Compute and return a model dictionary at the fiducial set of parameters.
`reduce_data`(ctx)	Reduce data to model.
`setup`()	Setup instance.

Attributes

`chain`	Reference to the `LikelihoodComputationChain` containing this core.
`core_primary`	The first core that appears in the requirements.
`paired_core`	The forest core that is paired with this likelihood.
`parameter_names`	Names of the parameters of the full chain.
`redshifts`	Redshifts at which forest is defined.
`required_cores`