Metadata-Version: 2.1
Name: imktk
Version: 0.1.8rc2
Summary: Toolkit provided by IMK at KIT
Home-page: https://github.com/imk-toolkit/imk-toolkit
License: MIT
Author: Uğur Çayoğlu
Author-email: Ugur.Cayoglu@kit.edu
Requires-Python: >=3.7,<3.10
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Requires-Dist: netCDF4 (>=1.5.8,<2.0.0)
Requires-Dist: xarray (>=0.20.1,<0.21.0)
Project-URL: Documentation, https://github.com/imk-toolkit/imk-toolkit
Project-URL: Repository, https://github.com/imk-toolkit/imk-toolkit
Description-Content-Type: text/markdown

# IMK Toolkit

This toolkit provides post-processing scripts developed by members of the
[Institute of Meteorology and Climate Research (IMK)](https://dev.to/epassaro/keep-your-research-reproducible-with-conda-pack-and-github-actions-339n)
at the Karlsruhe Institute of Technology (KIT). The goal of this module is to
gather together python post-processing scripts for the analysis of netCDF data.

## Getting Started
The easiest method to test the module is to use an interactive session with docker.
In this environment you will have a Python 3 environment with all necessary dependencies already installed.

```bash
docker run -it imktk/imktk:latest bash
```

> For the brave: You can test the latest release candidate by changing `latest` to `testing`

## Install

Choose one of the following methods to install the package:

1. Install using `pip`
2. Install using `conda`
3. Install straight from this repository using `git clone`

This package supports `Python3` starting with version `3.7`. If you are using
an earlier version of `Python` please consider updating your system.

### `pip`

Releases are automatically uploaded to PyPI. Please execute following command
to install the package.

```
python3 -m pip install imktk
```

### `conda`

Currently the package does no support native installation using `conda`
respectively `conda-forge`. This feature is on the roadmap and you can follow
its process using issue [#34](https://github.com/imk-toolkit/imk-toolkit/issues/34).
The current workaround for `conda` installation is to use the following steps
for any given environment `<env>`.

1. Activate the environment
```bash
conda activate <env>
```
2. Install using `pip`
```bash
python3 -m pip install imktk
```

### `git clone`

It is also possible to install the package natively by cloning the repository.
If you are interested in using this method of installation please follow
these steps

1. Install build dependencies
```bash
python3 -m pip install build
```

2. Clone repository

```bash
git clone https://github.com/imk-toolkit/imk-toolkit.git
```

3. Generate the Python packages

```bash
python3 -m build
# or
make
# or
make build
```

4. Install packages

```bash
pip3 install dist/imktk-<current.version>-py3-none-any.whl
# or
make install
```

Please be aware that the package uses `HDF5` and `netCDF` c-library in the
backend. If you are installing using this method consider setting the
`HDF5_DIR` environment variable with the location of the HDF5 header files.


## Usage

```python
import imktk
import xarray as xr

t = xr.tutorial.open_dataset("rasm").load().Tair
anomaly_free_t = t.imktk.anomalies()
```

## Further reading
If you are interested in the inner workings of the package and details of the
implementation please refer to the embedded [README.md](/imktk/README.md).

