PyFisher

PyFisher is a python package for calculating Fisher matrices and forecasting parameter uncertainties for CMB experiments.

Installation

You will need to install a dependency called orphics that is not available on pip, conda, etc. https://github.com/msyriac/orphics

The installation procedure for that dependency is the same as for this package. Repeat the following for each of orphics and pyfisher separately.

1. Git clone the repository
2. cd into the repository and run pip install -e . --user.

The latter step just copies symbolic links to the relevant modules into a directory (managed by pip) that is in your python path.

Once this is done, you should be able to do things like

import pyfisher.clFisher as clFish

from anywhere on your system.

Basic Usage

1. Edit input/params.ini. It is documented. You can include or exclude BAO by changing otherFishers, and the details of lensing reconstruction by changing the lensing section. There are a whole bunch of sections for different experiment configurations too.
2. See how tests/testFisher.py uses this ini file. Inside the root repo directory, run python tests/testFisher.py <experiment section name> <lensing section name> For example python tests/testFisher.py S4-5m lensing which will tell you what the mnu constraint and lensing S/N is. You can adapt this script to, for example, override one of the ini configurations and make plots of constraints and S/N varying that configuration.

Advanced Usage

Make derivatives

Edit input/makeDefaults.ini and specify a fiducial cosmology, derivative step sizes and a prefix under which to save the derivatives to output/. Run with

python bin/makeDerivs.py

Re-make Planck or BAO Fisher matrices.

Edit input/fisherDebug.ini and run

python bin/driver.py input/fisherDebug.ini

A tutorial

A very common forecasting scenario is combining a future CMB experiment with existing Planck data and BAO. Please read this tutorial for suggestions on how to do this with pyfisher.

https://github.com/msyriac/pyfisher/blob/master/forecasting.md