semvec/pypi-packages huggingface dataset:
sklearn-xarray-ext 0.5.0
xarray integration with sklearn (maintained fork)
Requires Python: >=3.9
Keywords: scikit-learn, xarray, machine-learning

.. -*- mode: rst -*-

|PyPI|_ |Black|_

.. |PyPI| image:: https://badge.fury.io/py/sklearn-xarray-ext.svg
.. _PyPI: https://badge.fury.io/py/sklearn-xarray-ext

.. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg
.. _Black: https://github.com/psf/black

sklearn-xarray-ext
==================

**sklearn-xarray-ext** is a maintained fork of `sklearn-xarray
<https://github.com/phausamann/sklearn-xarray>`_ by Peter Hausamann.

It is an open-source python package that combines the
n-dimensional labeled arrays of xarray_ with the machine learning and model
selection tools of scikit-learn_. The package contains wrappers that allow
the user to apply scikit-learn estimators to xarray types without losing their
labels.

.. _scikit-learn: http://scikit-learn.org/stable/
.. _xarray: http://xarray.pydata.org


Documentation
-------------

The original package documentation can be found at
https://phausamann.github.io/sklearn-xarray/


Features
----------

- Makes sklearn estimators compatible with xarray DataArrays and Datasets.
- Allows for estimators to change the number of samples.
- Adds a large number of pre-processing transformers.


Installation
-------------

The package can be installed with ``pip``::

    $ pip install sklearn-xarray-ext


Example
-------

The `activity recognition example`_ demonstrates how to use the
package for cross-validated grid search for an activity recognition task.
You can also download the example as a jupyter notebook.

.. _activity recognition example: https://phausamann.github.io/sklearn-xarray/auto_examples/plot_activity_recognition.html


Contributing
------------

Please read the `contribution guide <https://github.com/mmann1123/sklearn-xarray/blob/master/.github/CONTRIBUTING.rst>`_
if you want to contribute to this project.
inc 0.1.9
install new computer
Requires Python: >=3.7
Keywords: python

# Install new computer (inc) 0.1.9

Install basic software for different operating systems:

[See documentation](https://install-new-computer.readthedocs.io/en/latest/)

## Installation for users

First install [uv](https://docs.astral.sh/uv/):

```
curl -LsSf https://astral.sh/uv/install.sh | sh
```

Then install `inc`:

```
uv tool install inc
```

## Usage

```
inc --help
```

### List available scripts

```
inc ls
```

Example output:
```
Available bash scripts:
  conda_python311
  conda_python312
  dotfiles
  gmsh
  install_new_mac
```

### Run a script

```
inc run <script_name>
```

For example, to install gmsh:
```
inc run gmsh
```

To see what a script would do without running it:
```
inc run gmsh --dry-run
```

### View script contents

```
inc cat <script_name>
```
## Installation for developers

```
git clone https://github.com/joamatab/install_new_computer.git ~/install_new_computer
cd ~/install_new_computer
uv sync
```

For MacOs type this into a terminal first:

```
xcode-select --install
```

## References

- [my dotfiles wiki](https://github.com/joamatab/dotfiles/wiki)
- [my dotfiles](https://github.com/joamatab/dotfiles)
- [mac CLI](https://github.com/guarinogabriel/mac-cli)
- https://github.com/jaywcjlove/awesome-mac.git
- https://www.stuartellis.name/articles/mac-setup/
- https://dotfiles.github.io/
- https://github.com/atomantic/dotfiles
- https://sourabhbajaj.com/mac-setup/
- https://github.com/gotbletu
- https://lukesmith.xyz/
- http://www.openvim.com/tutorial.html