Metadata-Version: 2.1
Name: regressionpack
Version: 0.0.6
Summary: Library for making regression with errorbars a walk in the park. 
Home-page: https://pypi.org/project/regressionpack/
Author: FusedSilica
Author-email: caronmartin3@gmail.com
License: UNKNOWN
Description: # regressionpack
        
        A library of higher level regression functions that also include errorbars computed using a provided confidence interval. 
        Available regressions so far include  
        * [Linear](https://en.wikipedia.org/wiki/Linear_regression)
            * [Polynomial](https://en.wikipedia.org/wiki/Polynomial_regression)
            * Exponential (TODO)
            * Logarithmic (TODO)
        * GenericCurveFit
            * CosineFit
            * Logistic (TODO)
            * Michaelis-Menten (TODO)
        * Gaussian (TODO)
        * ErrorFunction (TODO)
        
        ## Getting Started
        
        These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
        
        ### Prerequisites
        
        This package was developped using:  
        * python 3.8.3
        * numpy 1.18.1
        * scipy 1.4.1
        
        While it may still work with older versions, I did not take the time to verify. 
        
        ### Installing
        
        ``
        pip install regressionpack
        ``
        
        Note that this will also install numpy 1.18.1 and scipy 1.4.1 if they are not already present. 
        Once installation is done, you may use the package by importing it this way:  
        ``
        import regressionpack
        ``
        
        ## Example applications
        
        For examples on how to use this package, look at the following [jupyter notebook](tests/test_regressionpack.ipynb). You will need [matplotlib](https://pypi.org/project/matplotlib/).  
        
        ## Built With
        * [Python](https://www.python.org/) - The language
        * [numpy](https://numpy.org/) - the numeric library
        * [scipy](https://docs.scipy.org/) - the scientific library
        
        ## Contributing
        Contact me and discuss your ideas and ambitions. 
        
        ## Authors
        
        * **FusedSilica** - *Initial work*
        
        ## License
        
        This project is licensed under the GNU LGPLv3 License - see the [LICENSE.md](LICENSE.md) file for details
        
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
