https://github.com/cdeil/python-model-fit-tutorial
Python modeling and fitting tutorial
https://github.com/cdeil/python-model-fit-tutorial
Last synced: 5 months ago
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Python modeling and fitting tutorial
- Host: GitHub
- URL: https://github.com/cdeil/python-model-fit-tutorial
- Owner: cdeil
- License: mit
- Created: 2024-07-18T09:55:10.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-20T07:53:06.000Z (almost 2 years ago)
- Last Synced: 2025-03-22T16:45:42.076Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 323 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Python modeling and fitting tutorial
## Introduction
A hands-on introduction to Python tools and techniques to fit non-linear models to data.
* Use least squares examples, but any other models or cost functions would work very similar.
* Focus on finding optimal parameters (the best fit), not on parameter error estimation or statistical topics.
* Focus on code and tools and how to use it, not the underlying math and theory.
## Setup
To follow along and be able to edit and execute the examples you can do this:
```
git clone https://github.com/cdeil/python-modeling-fitting-tutorial.git
cd python-model-fit-tutorial
conde env create -y -f environment.yml
conda activate py-model-fit
```
Then open up [VSCode](https://code.visualstudio.com/) or [JupyterLab](https://jupyterlab.readthedocs.io/) or whatever you like.
## Tutorials
* 01 - Meet the tools - [01_meet_the_tools.ipynb](01_meet_the_tools.ipynb)
* 02 - Failing fits - [02_failing_fits.ipynb](02_failing_fits.ipynb)
* 03 - Understand the tools - [03_understand_the_tools.ipynb](03_understand_the_tools.ipynb)
* 04 - Complex model example - [04_complex_model_example.ipynb](04_complex_model_example.ipynb)
* 05 - Roll your own - [05_roll_your_own.ipynb](05_roll_your_own.ipynb)
* 06 - Hybrid models - [06_hybrid_models.ipynb](06_hybrid_models.ipynb)