Metadata-Version: 2.1
Name: ipart
Version: 2.0.2
Summary: IPART is a Python package for the detection and tracking of atmospheric rivers from gridded IVT data using image-processing techniques.
Home-page: https://github.com/ihesp/IPART
Author: Guangzhi XU
Author-email: xugzhi1987@gmail.com
License: GPL-3
Description: # Image-Processing based Atmospheric River Tracking (IPART) algorithms
        
        ## Dependencies
        
        * Python2.7 or Python3.7.
        * netCDF4 (tested 1.4.2, 1.5.3 in py2, tested 1.5.3 in py3)
        * numpy (developed in 1.16.5 in py2, tested 1.18.1, 1.19.0 in py3)
        * scipy (developed in 1.2.1 in py2, tested 1.4.1, 1.5.1 in py3)
        * matplotlib (2.2.3 for both py2 and py3, having [issues](https://github.com/matplotlib/matplotlib/issues/12820) with 3.1.3)
        * basemap (developed in 1.2.0, 1.3.0 in py2, tested 1.2.0 in py3)
        * pandas (developed in 0.23.4, 0.24.2 in py2, tested 1.0.3, 1.0.5 in py3)
        * networkx (developed in 1.11 and 2.2 in py2, tested 2.4 in py3)
        * scikit-image (developed in 0.14.2, 0.14.3 in py2, tested 0.16.2, 0.17.2 in py3)
        * OS: Linux or Mac, may work in Windows.
        
        ## Installation
        
        Recommend building the Python environment using [Anaconda](https://www.anaconda.com/distribution/).
        
        ### Create conda env using environment file
        
        After Anaconda installation, git clone this repository:
        
        ```
        git clone https://github.com/ihesp/IPART
        ```
        
        Then build a new conda environment using the environment file provided. For example:
        
        ```
        cd IPART
        conda env create -f environment_py3.yml
        ```
        
        This creates a new environment named `ipartpy3`. Activate the environment using
        
        ```
        conda activate ipartpy3
        ```
        
        After that, you can check the list of packages installed by
        
        ```
        conda list
        ```
        
        Similarly for Python 2.7, use
        
        ```
        conda env create -f environment_py2.yml
        ```
        
        Finally install IPART using:
        
        ```
        pip install -e .
        ```
        
        
        ## tests
        
        To validate installation, issue a new Python session and run
        
        ```
        import ipart
        ```
        
        If nothing prints out, installation is successful.
        
        The `tests` folder also contains a number of `unittest`s, to run them:
        
        ```
        python -m unittest discover -s tests
        ```
        
        ## Documentation
        
        Further documentation can be found at [https://ipart.readthedocs.io/en/latest/](https://ipart.readthedocs.io/en/latest/).
        
        
        ## Example use case
        
        
        | ![fig3](joss/fig3.png) |
        | :--: |
        |*(a) The IVT field in kg/m/s at 1984-01-26 00:00 UTC over the North Hemisphere. (b) the IVT reconstruction field (IVT_rec) at the same time point. (c) the IVT anomaly field (IVT_ano) from the THR process at the same time point.*|
        
        | ![](joss/ar_track_198424.png) |
        | :--: |
        |*Locations of a track labelled "198424" found in year 1984. Black to yellow color scheme indicates the evolution.*|
        
        
        
        ## Inventory
        
        * docs: readthedocs documentation.
        * ipart: core module functions.
        * notebooks: a series of jupyter notebooks illustrating the major functionalities of the package.
        * scripts: example computation scripts. Can be used as templates to quickly develop your own working scripts.
        
        
        ## Changelog
        
        ### v3.0
        
        Make algorithms zonally cyclic.
        
        ### v2.0
        
        * restructure into a module `ipart`, separate module from scripts.
        * add a `findARsGen()` generator function to yield results at each time point separately.
        
        ### v1.0
        
        * initial upload. Can perform AR detection and tracing through time.
        
        
        
        ## Contribution
        
        If you encounter problems or would like to help improve the code, please don't
        hesitate to fire up an issue or pull request.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Description-Content-Type: text/markdown
