The notebook tf_planck2018_lite.ipynb shows an example of how to run a complete inference pipeline with power spectra sourced from CosmoPower. The notebooks runs a version of the Planck 2018 lite likelihood rewritten to be fully implemented in TensorFlow: tf_planck2018_lite.py. The lite version of the Planck likelihood is pre-marginalised over a set of nuisance parameters. This TensorFlow version of the Planck lite likelihood, provided as part of CosmoPower, is an adaptation for TensorFlow of the planck-lite-py likelihood written by H. Prince and J. Dunkley.

If you use tf_planck2018_lite, in addition to the CosmoPower release paper please also cite Prince & Dunkley (2019) and Planck (2018).

The notebook tf_planck2018_lite.ipynb can also be run on Colab

tf_planck2018_lite instantiation

Her we will simply show how to instantiate the tf_planck2018_lite likelihood, referring to the tf_planck2018_lite.ipynb notebook for a more detailed example of how to run it for inference.

The tf_planck2018_lite likelihood requires emulators for the TT, TE, EE power spectra. In the tf_planck2018_lite.ipynb notebook we use the pre-trained models from the CosmoPower release paper, available in the CosmoPower repository.

To create an instance of tf_planck2018_lite, we import CosmoPower and remember to input:

• a path to the tf_planck2018_lite likelihood. It will be used to access the Planck data;

• parameters of the analysis, as well as their priors;

• the CosmoPower emulators.

import cosmopower as cp

# CosmoPower emulators
tt_emu_model = cp.cosmopower_NN(restore=True,
                                restore_filename='cmb_TT_NN')

te_emu_model = cp.cosmopower_PCAplusNN(restore=True,
                                       restore_filename='cmb_TE_PCAplusNN')

ee_emu_model = cp.cosmopower_NN(restore=True,
                                restore_filename='cmb_EE_NN')

# path to the tf_planck2018_lite likelihood
tf_planck2018_lite_path = '/path/to/cosmopower/likelihoods/tf_planck2018_lite/'

# parameters of the analysis, and their priors
parameters_and_priors = {'omega_b':      [0.001, 0.04, 'uniform'],
                         'omega_cdm':    [0.005, 0.99,  'uniform'],
                         'h':            [0.2,   1.0,   'uniform'],
                         'tau_reio':     [0.01,  0.8,   'uniform'],
                         'n_s':          [0.9,   1.1,   'uniform'],
                         'ln10^{10}A_s': [1.61,  3.91,  'uniform'],
                         'A_planck':     [1.0,   0.01,  'gaussian'],
                          }

# instantiation
tf_planck = cp.tf_planck2018_lite(parameters=parameters_and_priors, 
                                  tf_planck2018_lite_path=tf_planck2018_lite_path,
                                  tt_emu_model=tt_emu_model,
                                  te_emu_model=te_emu_model,
                                  ee_emu_model=ee_emu_model
                                  )