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Field Level Inference Package: a python package to infer growth rate from density and velocity field

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corentinravoux/flip

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flip: Field Level Inference Package

flip is a Python package that uses the maximum likelihood method to fit the growth rate based on the velocity and density fields. The first part of the software is the computation of a covariance matrix from a model power spectrum and the considered coordinates. This part is generalized to work for any linear power spectrum models, both for velocities, densities, and cross-terms, and it is optimized with Hankel transform for any model. In the second part, the covariance is used to create a likelihood by multiplying it by velocities or densities. Finally, this package includes some integrated fitters such as Minuit and MCMC (with emcee) to fit the growth rate of structures.

Documentation Status

Quick install

git clone https://github.com/corentinravoux/flip.git
cd flip
pip install .

Required packages

Mandatory: numpy, scipy, matplotlib, cosmoprimo, iminuit, emcee, sympy

Optional: classy, pypower

Examples

For an example with velocity fit check out: Open In Colab

For density only: Open In Colab

For a joint fit: Open In Colab

Need help?

Documentation available on ReadTheDoc

How to cite

This package was started on the previous work of @bastiencarreres, for now, please cite this article.

A paper describing the concept of the code is in preparation.

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Field Level Inference Package: a python package to infer growth rate from density and velocity field

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