Metadata-Version: 2.1
Name: ecubevis
Version: 1.0.1
Summary: Earth CUBE VISualization with Python
Home-page: https://github.com/carlgogo/ecubevis
Author: Carlos Alberto Gomez Gonzalez
Author-email: carlos.gomez@bsc.es
License: UNKNOWN
Description: # Welcome to the repository of ecubevis
        
        `ecubevis`: Earth CUBE VISualization with Python. Intended for the interactive exploration of n-dimensional (2D, 3D, 4D or 5D spatio-temporal) arrays on Jupyterlab. Supports both ``xarray.Dataset/DataArray`` (with metadata) or ``numpy.ndarray`` objects. 
        
        ## How to install
        
        Install ``ecubevis`` from pypi:
        
        ```
        pip install ecubevis
        ```
        
        ## How to use
        
        Import the library:
        
        ```python
        import ecubevis as ecv
        ```
        
        The main function in ``ecubevis`` is ``ecv.plot()``. In interactive mode, the plot comes with sliders (thanks to `hvplot`/`holoviews`) allowing easy exploration of multi-dimensional data as 2D arrays across the time and additional dimensions. Under the hood, ``ecv.plot()`` calls one of the following functions depending on the data type: 
        
        * ``ecv.plot_ndarray()``: For plotting an in-memory ``numpy.ndarray`` object with 2, 3, 4 or 5 dimensions (ndarrays do not carry metadata so the dimensions are given with the ``dimensions`` argument). The function can take a tuple of 2D ndarrays, even with different grid/image size.
        
        * ``ecv.plot_dataset()``: For plotting an in-memory ``xr.Dataset`` or ``xr.DataArray`` objects with 2, 3, or 4 dimensions. The dimensions expected are [lat, lon] for 2D arrays, [time, lat, lon] for 3D arrays or [time, level, lat, lon] for 4D arrays.  
        
        ### Examples
        
        ``ecubevis`` will allow you to create:
        
        | Interactive | Static |
        | ----------- | -------|
        | plots of in-memory 2D, 3D and 4D ``xr.Dataset`` or ``xr.DataArray`` objects: <img src="./screenshots/ecubevis_1.png" width="300"> | mosaics of in-memory 3D and 4D ``xr.Dataset`` or ``xr.DataArray`` objects: <img src="./screenshots/ecubevis_2.png" width="300"> |
        | plots of in-memory 2D, 3D and 4D ``numpy.ndarray`` objects (composition thanks to ``holoviews``): <img src="./screenshots/ecubevis_3.png" width="300"> | plots of in-memory 2D, 3D and 4D ``numpy.ndarray`` objects: <img src="./screenshots/ecubevis_4.png" width="300"> |
        | plots of in-memory ``xr.Dataset`` or ``xr.DataArray`` while sub-setting across dimensions: <img src="./screenshots/ecubevis_6.png" width="300"> | plots of a tuple of in-memory 2D ``numpy.ndarray`` objects: <img src="./screenshots/ecubevis_5.png" width="300"> |
        
Keywords: visualization,interactive,plotting,earth-data
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: POSIX :: Linux
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
