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An interactive visualizer to help explore the results of running MCMC posterior sampling on a cosmological model.

Project description

InViz

InViz (Interactive Visualizer) is a tool for exploratory analysis of high-dimensional datasets where data points from the parameter space are used to calculate to some set of real-world observables. This enables you to easily see how the derived observables change as you traverse the parameter space. If you have pre-computed observables, simply import them alongside the dataset containing the parameters to start visualizing. Or, write your own function that takes your parameters as inputs, and give it to InViz to compute on the fly!

Installation

InViz can be installed with pip:

python -m pip install inviz

Or, if you want to test the latest changes, you can clone the repository with

git clone https://github.com/wen-jams/inviz
cd inviz
python setup.py install

Dependencies

  • Python versions $\geq$ 3.8 and $<$ 3.11 are supported.
  • Holoviews $\leq$ 1.15.4 (this package and its dependencies will be installed automatically)

Getting Started

Test Installation

To verify that inviz and all the dependencies have been installed correctly, open a Jupyter Notebook and run:

from inviz import *
hv.extension('bokeh')
pn.extension()

If no errors appear, all the dependencies were installed correctly and we're ready to start visualizing!

Example

Download and run the tutorial notebook in the tutorials folder to see an example of how inviz can be used.

Here's an example of InViz in an astrophysics context! The parameters come from a specific dark matter model, and the observables are the matter power spectrum and CMB anisotropy power spectra. example output

Project details


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