Getting Started with Minterpy#
Have you installed Minterpy? Read on how to install it before moving on.
Installation#
The public release of Minterpy (i.e., the main branch) can be obtained directly from PyPI with pip:
pip install minterpy
The latest development branch of Minterpy can be obtained from its GitHub repository:
git clone -b dev https://github.com/minterpy-project/minterpy
After moving inside the cloned directory, the package can be installed
from source with pip:
pip install [-e] .
As a best practice, it is recommended to create a virtual environment to avoid installing external packages directly into your base Python environment. You can accomplish this using tools such as:
What’s next?#
If you’re brand new to Minterpy and simply want to approximate a function using polynomial interpolations, start with:
Quick Start Guide to Function Approximations with Minterpy
While function approximation using polynomials is a key feature of Minterpy, the package also provides a powerful implementation of multivariate polynomials in Python. These polynomials have a consistent interface that makes it easy to perform advanced manipulations like arithmetic and calculus operations.
To learn more about these features of Minterpy, follow the series of tutorials below. We recommend that you go through these tutorials in sequence.
If you want to… |
Go to… |
|---|---|
understand Minterpy polynomials by approximating a 1D function |
|
learn how to approximate multidimensional function using polynomial interpolation |
|
know more about the supported arithmetic operations with Minterpy polynomials |
|
know more more the supported calculus operations with Minterpy polynomials |
|
understand the available polynomial bases and how to transform between them |
|
learn how to construct a polynomial from scattered data |
Once you’ve become more familiar with Minterpy and need help to achieve a particular task, be sure to check out the How-to Guides!