Metadata-Version: 2.1
Name: Sigmoidal
Version: 0.4.0
Summary: Sigmoidal is a small library to allow you to fit and evaluate sigmoid functions in a way that works like the Numpy Polynomial class.
Home-page: https://github.com/HelloSleuth/sigmoid
Author: Jade Glaze, Sleuth
Author-email: jade@hellosleuth.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy (>=1.24.3)
Requires-Dist: scipy (>=1.10.1)

# Sigmoidal 

Sigmoidal is intended to work like the [Numpy Polynomial](https://numpy.org/doc/stable/reference/generated/numpy.polynomial.polynomial.Polynomial.html) class where it makes sense. Specifically it supports:
* Using the sigmoid function in a very natural way like `y = sig(x)` including when x is a numpy array. (Once you've created a Sigmoid instance `sig = Sigmoid(...)`)
* Fitting a Sigmoid to data just like Polynomial with `Sigmoid.fit(x, y)`.
* Taking the first or second derivative with `deriv()`.
* Finding the roots of the sigmoid or it's first or second derivitive with `.roots()`.
* The convenience method `.linspace()` which can get you an array of dependent values with only the range of independent values.
* `.copy()`
* Operations `==`, `!=`, `str()`, `repr()`

## Running Tests
* `python -m unittest discover tests`

## Setup for Deployment
* `pip install twine`

## Building the Package
* `python setup.py sdist bdist_wheel`

## Deploying
* `twine upload --skip-existing --repository-url https://upload.pypi.org/legacy/ dist/*`
