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- Until the conda install is stable again
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MilesCranmer committed Jun 12, 2023
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PySR searches for symbolic expressions which optimize a particular objective.

https://github.com/MilesCranmer/PySR/assets/7593028/c8511a49-b408-488f-8f18-b1749078268f

<https://github.com/MilesCranmer/PySR/assets/7593028/c8511a49-b408-488f-8f18-b1749078268f>

# PySR: High-Performance Symbolic Regression in Python and Julia

| **Docs** | **Forums** | **Paper** | **colab demo** |
|:---:|:---:|:---:|:---:|
|[![Documentation](https://github.com/MilesCranmer/PySR/actions/workflows/docs.yml/badge.svg)](https://astroautomata.com/PySR/)|[![Discussions](https://img.shields.io/badge/discussions-github-informational)](https://github.com/MilesCranmer/PySR/discussions)|[![Paper](https://img.shields.io/badge/arXiv-2305.01582-b31b1b)](https://arxiv.org/abs/2305.01582)|[![Colab](https://img.shields.io/badge/colab-notebook-yellow)](https://colab.research.google.com/github/MilesCranmer/PySR/blob/master/examples/pysr_demo.ipynb)|

| **pip** | **conda** | **Stats** |
| :---: | :---: | :---: |
|[![PyPI version](https://badge.fury.io/py/pysr.svg)](https://badge.fury.io/py/pysr)|[![Conda Version](https://img.shields.io/conda/vn/conda-forge/pysr.svg)](https://anaconda.org/conda-forge/pysr)|<div align="center">pip: [![Downloads](https://pepy.tech/badge/pysr)](https://badge.fury.io/py/pysr)<br>conda: [![Anaconda-Server Badge](https://anaconda.org/conda-forge/pysr/badges/downloads.svg)](https://anaconda.org/conda-forge/pysr)</div>|
| **Docs** | **pip** | **Forums** | **Paper** | **colab demo** |
|:---:|:---:|:---:|:---:|:---:|
|[![Documentation](https://github.com/MilesCranmer/PySR/actions/workflows/docs.yml/badge.svg)](https://astroautomata.com/PySR/)|[![PyPI version](https://badge.fury.io/py/pysr.svg)](https://badge.fury.io/py/pysr)|[![Discussions](https://img.shields.io/badge/discussions-github-informational)](https://github.com/MilesCranmer/PySR/discussions)|[![Paper](https://img.shields.io/badge/arXiv-2305.01582-b31b1b)](https://arxiv.org/abs/2305.01582)|[![Colab](https://img.shields.io/badge/colab-notebook-yellow)](https://colab.research.google.com/github/MilesCranmer/PySR/blob/master/examples/pysr_demo.ipynb)|

</div>

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## Installation

| [pip](#pip) | [conda](#conda) | [docker](#docker-build) |
|:---:|:---:|:---:|
| Everywhere (recommended) | Linux and Intel-based macOS | Everywhere (if all else fails) |

---

### pip

1. [Install Julia](https://julialang.org/downloads/)
- Alternatively, my personal preference is to use [juliaup](https://github.com/JuliaLang/juliaup#installation), which performs this automatically.
2. Then, run:

```bash
pip3 install -U pysr
```
3. Finally, to install Julia dependencies:
```bash
python3 -m pysr install
```
> (Alternatively, from within Python, you can call `import pysr; pysr.install()`)

---

### conda

The PySR build in conda includes all required dependencies, so you can install it by simply running:
3. Finally, to install Julia dependencies:

```bash
conda install -c conda-forge pysr
python3 -m pysr install
```

from within your target conda environment.

However, note that the conda install does not support precompilation of Julia libraries, so the
start time may be slightly slower as the JIT-compilation will be running.
(Once the compilation finishes, there will not be a performance difference though.)
> (Alternatively, from within Python, you can call `import pysr; pysr.install()`)
---

### docker build

1. Clone this repo.
2. In the repo, run the build command with:

```bash
docker build -t pysr .
```

3. You can then start the container with an IPython execution with:

```bash
docker run -it --rm pysr ipython
```
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```python
PySRRegressor.equations_ = [
pick score equation loss complexity
0 0.000000 4.4324794 42.354317 1
1 1.255691 (x0 * x0) 3.437307 3
2 0.011629 ((x0 * x0) + -0.28087974) 3.358285 5
3 0.897855 ((x0 * x0) + cos(x3)) 1.368308 6
4 0.857018 ((x0 * x0) + (cos(x3) * 2.4566472)) 0.246483 8
5 >>>> inf (((cos(x3) + -0.19699033) * 2.5382123) + (x0 *... 0.000000 10
pick score equation loss complexity
0 0.000000 4.4324794 42.354317 1
1 1.255691 (x0 * x0) 3.437307 3
2 0.011629 ((x0 * x0) + -0.28087974) 3.358285 5
3 0.897855 ((x0 * x0) + cos(x3)) 1.368308 6
4 0.857018 ((x0 * x0) + (cos(x3) * 2.4566472)) 0.246483 8
5 >>>> inf (((cos(x3) + -0.19699033) * 2.5382123) + (x0 *... 0.000000 10
]
```

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