Metadata-Version: 2.1
Name: inviz
Version: 0.3.5
Summary: An interactive visualizer to help explore high-dimensional likelihoods and their observables.
Home-page: http://packages.python.org/inviz
Author: James Wen
Author-email: jswen@usc.edu
License: MIT
Keywords: interactive visualizer cosmology
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# 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 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

### 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)

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

## Getting Started

### Test Installation

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

    import inviz as nv

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

### Example

Download and run the `live_data_example` notebook in the [tutorials](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](images/example2.png)
