Metadata-Version: 2.1
Name: continuous-peak-fit
Version: 0.0.1.dev1
Summary: Fits azimuth/time dependency of peaks with Fourier Series descriptions
Home-page: https://github.com/ExperimentalMineralPhysics/Continuous-Peak-Fit
Author: Simon Hunt & Danielle Fenech
Author-email: simon.hunt@manchester.ac.uk
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: pycairo
Requires-Dist: lmfit
Requires-Dist: h5py
Requires-Dist: pillow
Requires-Dist: pyFAI

# Fourier-Peak-Fit

## Installation

Installation is available through git or via pip

From git use

`git clone https://github.com/ExperimentalMineralPhysics/Continuous-Peak-Fit.git`

To install the required dependencies use, in the Continuous-Peak-Fit directory use 

`pip install requirements.txt`

# 

For pip installation use

`pip install continuous-peak-fit`

this should automatically install the required dependencies.


## Usage

Continuous-Peak-Fit can be run in a number of ways but requires an inputs file containing information about where your 
data files are stored as well as information of the number of peak and appropriate ranges for the fit. Example data and 
inputs file are available in the Example1-Fe directory from the git repository. 

If using a pip install an example inputs file can be generated using the 'CPF_generate_inputs' executable or from within
 python using

`import cpf`

`cpf.generate_inputs()`

Fitting can then be performed using 

`CPF_XRD_FitPattern <inputs_file>` from the command line

or from within python

`import cpf`

`cpf.XRD_FitPattern.execute(settings_file=<inputs_file>)`



