Metadata-Version: 2.1
Name: cmip6_preprocessing
Version: 0.2.0
Summary: Analysis ready CMIP6 data the easy way
Home-page: https://github.com/jbusecke/cmip6_preprocessing
Author: cmip6_preprocessing developers
Author-email: jbusecke@princeton.edu
License: MIT
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        ![BLM](BLM.png)
        
        Science is not immune to racism. Academia is an elitist system with numerous gatekeepers that has mostly allowed a very limited spectrum of people to pursue a career. I believe we need to change that.
        
        Open source development and reproducible science are a great way to democratize the means for scientific analysis. **But you can't git clone software if you are being murdered by the police for being Black!**
        
        Free access to software and hollow diversity statements are hardly enough to crush the systemic and institutionalized racism in our society and academia.
        
        If you are using this package, I ask you to go beyond just speaking out and donate [here](https://secure.actblue.com/donate/cmip6_preprocessing) to [Data for Black Lives](http://d4bl.org/) and [Black Lives Matter Action](https://blacklivesmatter.com/global-actions/).
        
        I explicitly welcome suggestions regarding the wording of this statement and for additional organizations to support. Please raise an [issue](https://github.com/jbusecke/cmip6_preprocessing/issues) for suggestions.
        
        # cmip6_preprocessing
        
        Frustrated with how 'dirty' CMIP6 data still is? Do you just want to run a simple (or complicated) analysis on various models and end up having to write logic for each seperate case? Then this package is for you.
        
        Developed during the [cmip6-hackathon](https://cmip6hack.github.io/#/) this package provides utility functions that play nicely with [intake-esm](https://github.com/NCAR/intake-esm).
        
        We currently support the following functions
        
        1. Preprocessing CMIP6 data (Please check out the [tutorial](docs/tutorial.ipynb) for some examples using the [pangeo cloud](ocean.pangeo.io)). The preprocessig includes:
            a. Fix inconsistent naming of dimensions and coordinates
            b. Fix inconsistent values,shape and dataset location of coordinates
            c. Homogenize longitude conventions
            d. Fix inconsistent units
        2. [Creating large scale ocean basin masks for arbitrary model output](docs/regionmask.ipynb)
        
        The following issues are under development:
        1. Reconstruct/find grid metrics
        2. Arrange different variables on their respective staggered grid, so they can work seamlessly with [xgcm](https://xgcm.readthedocs.io/en/latest/)
        
        Check out this recent Earthcube [notebook](https://github.com/earthcube2020/ec20_busecke_etal) (cite via doi: [10.1002/essoar.10504241.1](https://www.essoar.org/doi/10.1002/essoar.10504241.1)) for a high level demo of `cmip6_preprocessing` and [xgcm](https://github.com/xgcm/xgcm).
        
        
        ## Installation
        
        Install `cmip6_preprocessing` via pip:
        
        `pip install cmip6_preprocessing`
        
        or conda:
        
        `conda install -c conda-forge cmip6_preprocessing`
        
        To install the newest master from github you can use pip aswell:
        
        `pip install git+pip install git+https://github.com/jbusecke/cmip6_preprocessing.git`
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
