Metadata-Version: 2.1
Name: pysprint
Version: 0.14.0
Summary: Spectrally refined interferometry for Python
Home-page: https://github.com/Ptrskay3/PySprint
Author: Péter Leéh
Author-email: leeh123peter@gmail.com
License: UNKNOWN
Description: # PySprint
        ### Spectrally Refined Interferometry for Python 
        
        [![Build Status](https://travis-ci.org/Ptrskay3/PySprint.svg?branch=master)](https://travis-ci.org/Ptrskay3/pysprint)
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        | | |
        |-|-|
        |__Name__| PySprint|
        |__PyPI package__| [![PyPI version](https://badge.fury.io/py/pysprint.svg)](https://badge.fury.io/py/pysprint) |
        |__Anaconda package__| [![Anaconda-Server Badge](https://anaconda.org/ptrskay/pysprint/badges/version.svg)](https://anaconda.org/ptrskay/pysprint) |
        |__Development status__ | Pre-Alpha |
        |__License__| [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) |
        
        
        ## Description
        PySprint provides an interface for Spectrally resolved interferometry in Python. 
        PySprint implements all the evaluation methods described in the literature, however
        the API and the software itself might change over time. Documentation is sparse
        and not complete yet and the testing is in *very early stage*. We have a currently
        pointless Rust extension module, which might turn into something useful later.
        
        * âś“ Minimum-maximum method
        * âś“ Phase modulated cosine function fit method
        * âś“ Fourier method
        * âś“ Windowed Fourier transform method
        * âś“ Stationary phase point method
        
        ### Installation
        
        PySprint requires at least [Python 3.6](https://www.python.org/downloads/) to run.
        
        Install with
        
        ```sh
        pip install pysprint
        ```
        
        or install on Anaconda with:
        ```sh
        (CURRENTLY NOT AVAILABLE) conda install -c ptrskay pysprint -c conda-forge
        ```
        
        Requirements: 
        * numpy
        * scipy
        * matplotlib 
        * pandas
        * Jinja2
        * scikit-learn
        
        Optional packages: 
        * lmfit - for detailed curve fitting results
        * numba - to speed up non uniform FFT calculation
        * dask - for parallel WFT run
        
        
        ## Documentation
        
        The documentation is hosted on readthedocs.io.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Rust
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Description-Content-Type: text/markdown
Provides-Extra: optional
