imktk 0.1.7

Toolkit provided by IMK at KIT

IMK Toolkit

This toolkit provides post-processing scripts developed by members of the Institute of Meteorology and Climate Research (IMK) 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.

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. The current workaround for conda installation is to use the following steps for any given environment <env>.

1. Activate the environment

conda activate <env>

2. Install using pip

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. Clone repository

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

2. Enter the imktk directory and build Python packages for installation. The installation files will be saved in imk-toolkit/dist

cd imk-toolkit/imktk && python3 -m build

3. Enter the dist directory and install packages

cd dist && pip3 install imktk-<current.version>-py3-none-any.whl

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

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.