Metadata-Version: 2.1
Name: DINCAE
Version: 1.1.0
Summary: DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations
Home-page: https://github.com/gher-ulg/DINCAE
Author: Alexander Barth
License: UNKNOWN
Description: [![documentation latest](https://img.shields.io/badge/docs-latest-blue.svg)](https://gher-ulg.github.io/DINCAE/)
        [![DOI](https://zenodo.org/badge/193079989.svg)](https://zenodo.org/badge/latestdoi/193079989)
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        # DINCAE
        
        
        DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to
        reconstruct missing data in satellite observations. https://www.geosci-model-dev-discuss.net/gmd-2019-128/
        
        
        ## Installation
        
        Python 3.6 with the modules:
        * numpy (https://docs.scipy.org/doc/numpy/user/install.html)
        * netCDF4 (https://unidata.github.io/netcdf4-python/netCDF4/index.html)
        * TensorFlow 1.15 with GPU support (https://www.tensorflow.org/install)
        
        Tested versions:
        
        * Python 3.6.8
        * netcdf4 1.4.2
        * numpy 1.15.4
        * Tensorflow version 1.15
        
        You can install those packages either with `pip3` or with `conda`.
        
        ## Input format
        
        The input data should be in netCDF with the variables:
        * `lon`: longitude (degrees East)
        * `lat`: latitude (degrees North)
        * `time`: time (days since 1900-01-01 00:00:00)
        * `mask`: boolean mask where true means the data location is valid
        * `SST` (or any other varbiable name): the data
        
        
        ```
        netcdf avhrr_sub_add_clouds {
        dimensions:
        	time = UNLIMITED ; // (5266 currently)
        	lat = 112 ;
        	lon = 112 ;
        variables:
        	double lon(lon) ;
        	double lat(lat) ;
        	double time(time) ;
        		time:units = "days since 1900-01-01 00:00:00" ;
        	int mask(lat, lon) ;
        	float SST(time, lat, lon) ;
        		SST:_FillValue = -9999.f ;
        }
        ```
        
        ## Running DINCAE
        
        Copy the template file `run_DINCAE.py` and adapt the filename, variable name and the output directory and possibly optional arguments for the reconstruction method as mentioned in the [documentation](https://gher-ulg.github.io/DINCAE/).
        The code can be run as follows:
        
        ```bash
        export PYTHONPATH=/path/to/module
        python3 run_DINCAE.py
        ```
        
        `/path/to/module` should be replaced by the directory name containing the file `DINCAE.py`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
