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rename cablab to esdl
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.gitignore

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# PyCharm / IDEA
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.idea
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# Ignored CAB-LAB (Data Cube) files
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# Ignored ESDL (Data Cube) files
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*.nc
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testcube
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cablab-config.py
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esdl-config.py
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.travis.yml

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- conda info -a
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- conda env create --file environment.yml
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- source activate esdc
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- source activate esdl
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- conda list
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- python setup.py install
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script:
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# For the unit-tests, disable Numba JIT, otherwise Coverage wont reach the actual Python code
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- export NUMBA_DISABLE_JIT=1
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- py.test -v --cov=cablab test --ignore=test/providers
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- py.test -v --cov=esdl test --ignore=test/providers
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after_success:
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- pip install codecov

CHANGES.md

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## version 0.3.0
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* Rename cablab to esdl
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## version 0.2.3
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* Using `chunk_sizes` and `comp_level` from configuration when generating cubes

README.rst

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.. image:: https://travis-ci.org/CAB-LAB/cablab-core.svg?branch=master
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:target: https://travis-ci.org/CAB-LAB/cablab-core
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.. image:: https://travis-ci.org/esa-esdl/esdl-core.svg?branch=master
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:target: https://travis-ci.org/esa-esdl/esdl-core
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.. image:: https://ci.appveyor.com/api/projects/status/qvtsx40uv7p0e1tn?svg=true
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:target: https://ci.appveyor.com/project/hans-permana/cablab-core
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.. image:: https://codecov.io/gh/CAB-LAB/cablab-core/branch/master/graph/badge.svg
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:target: https://codecov.io/gh/CAB-LAB/cablab-core
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:target: https://ci.appveyor.com/project/hans-permana/esdl-core
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.. image:: https://codecov.io/gh/esa-esdl/esdl-core/branch/master/graph/badge.svg
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:target: https://codecov.io/gh/esa-esdl/esdl-core
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============
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CAB-LAB Core
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============
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==========
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ESDL Core
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==========
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----------
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Components
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----------
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* ``cablab`` - Public CAB-LAB API
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* ``cablab.cube`` - Data Cube Generation and Access (protected, public parts expr)
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* ``cablab.cube_cli`` - Command-line interface (protected)
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* ``cablab.util`` - Common utility functions (protected)
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* ``esdl`` - Public ESDL API
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* ``esdl.cube`` - Data Cube Generation and Access (protected, public parts expr)
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* ``esdl.cube_cli`` - Command-line interface (protected)
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* ``esdl.util`` - Common utility functions (protected)
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-------------
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Documentation
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-------------
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Find the CAB-LAB documentation `here <http://cablab.readthedocs.io/en/latest/>`_.
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Find the ESDL documentation `here <http://cablab.readthedocs.io/en/latest/>`_.
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---------------
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Developer Guide
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Defined extension points
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------------------------
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* ``cablab.image_providers``: *key* = *class derived from* ``cablab.ImageProvider``
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* ``esdl.image_providers``: *key* = *class derived from* ``esdl.ImageProvider``
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Extensions
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----------
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* ``cablab.image_providers``:
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* ``'burnt_area = cablab.providers.burnt_area.BurntAreaProvider'``
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* ``esdl.image_providers``:
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* ``'burnt_area = esdl.providers.burnt_area.BurntAreaProvider'``
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* ``console_scripts``:
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* ``'cablab_cli = cablab.cli:main'``, see %PYTHON_HOME%/Scripts/cablab_cli (*.exe on Windows) after installation
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* ``'esdl_cli = esdl.cli:main'``, see %PYTHON_HOME%/Scripts/esdl_cli (*.exe on Windows) after installation
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------------
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How to generate a data cube
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---------------------------
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Create a file ``cablab-config.py`` in your project root directory or your current working directory and add the
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Create a file ``esdl-config.py`` in your project root directory or your current working directory and add the
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following entry::
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cube_sources_root = <your local cube source directory>

appveyor.yml

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version: '0.2.2.{build}'
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version: '0.3.0.{build}'
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environment:
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global:
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build_script:
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- conda env create --file environment.yml
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- call %PYTHON_LOC%\Scripts\activate.bat esdc
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- call %PYTHON_LOC%\Scripts\activate.bat esdl
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- python setup.py install
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- conda list
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# For the unit-tests, disable Numba JIT, otherwise Coverage wont reach the actual Python code

cablab/version.py

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doc/README.txt

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'doc' is the CAB-LAB documentation folder. Documentation is build from *.rst files using Sphinx.
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'doc' is the ESDL documentation folder. Documentation is build from *.rst files using Sphinx.
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index.rst is the main documentation page.
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To install Sphinx run:
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> pip install Sphinx
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To build the CAB-LAB documentation run:
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To build the ESDL documentation run:
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> cd cablab-core/doc
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> cd esdl-core/doc
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> make html
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or to force regeneration of docs, run:
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> cd cablab-core
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> cd esdl-core
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> sphinx-build -E -a -b html doc doc/_build/html
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Then find the html documentation in cablab-core/doc/_build/html
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Then find the html documentation in esdl-core/doc/_build/html
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More info:
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* Sphinx Tutorial: http://sphinx-doc.org/tutorial.html

doc/collaboration.rst

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Collaboration is at the heart of science!
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The CAB-LAB project explicitly aims at enabling more scientists from various disciplines to not only interact
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The ESDL project explicitly aims at enabling more scientists from various disciplines to not only interact
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with Earth System data, but also with each other.
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The CAB-LAB team seeks active exchange with users of any background, data owners willing to add their data to the ESDC,
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The ESDL team seeks active exchange with users of any background, data owners willing to add their data to the ESDC,
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and developers who are interested in improving the ESDC.
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There are several ways to get in contact with the CAB-LAB team and other users of the ESDC:
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There are several ways to get in contact with the ESDL team and other users of the ESDC:
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Code Repository
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===============
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The source code is currently and will be for the foreseeable future under continuous development. Since the CAB-LAB team
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takes collaboration, transparency, and reproducibility seriously, the project is open source and public from the very beginning.
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Visit `CAB-LAB's github repository <https://github.com/CAB-LAB>`_ and check out the current status of the project or even
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Visit `ESDL's github repository <https://github.com/esa-esdl>`_ and check out the current status of the project or even
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contribute!
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Website & Forum

doc/conf.py

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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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# Include 'cablab'
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sys.path.append(os.path.abspath('..'))
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# packages thare are difficult to import, becuase the collide with pillow==3.0.0 requirement by rtd

doc/dat_julia.rst

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Overview
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========
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The Data Analytics Toolkit (DAT) for Julia is hosted in `CABLAB's github repository <https://github.com/CAB-LAB/CABLAB.jl>`_
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The Data Analytics Toolkit (DAT) for Julia is hosted in `ESDL's github repository <https://github.com/esa-esdl/CABLAB.jl>`_
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and is developed in close interaction with the scientific community. Here we give a short overview on the capabilities
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of the Julia DAT, but we would refer to the `official documentation`_ for
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a more detailed and frequently updated software description.
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Use Cases and Examples
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======================
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Example notebooks that explore the ESDC using the Julia DAT can be found in the `cablab-shared`_ repository.
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Example notebooks that explore the ESDC using the Julia DAT can be found in the `esdl-shared`_ repository.
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.. _`CABLAB's github repository`: https://github.com/CAB-LAB/CABLAB.jl
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.. _`official documentation`: http://cab-lab.github.io/CABLAB.jl/latest/
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.. _Analysis: http://cab-lab.github.io/CABLAB.jl/latest/analysis.html
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.. _Plotting: http://cab-lab.github.io/CABLAB.jl/latest/plotting.html
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.. _`adding_new`: http://cab-lab.github.io/CABLAB.jl/latest/adding_new.html
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.. _`cablab-shared`: https://github.com/CAB-LAB/cablab-shared/tree/master/notebooks/Julia
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.. _`ESDL's github repository`: https://github.com/esa-esdl/CABLAB.jl
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.. _`official documentation`: http://esa-esdl.github.io/CABLAB.jl/latest/
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.. _Analysis: http://esa-esdl.github.io/CABLAB.jl/latest/analysis.html
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.. _Plotting: http://esa-esdl.github.io/CABLAB.jl/latest/plotting.html
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.. _`adding_new`: http://esa-esdl.github.io/CABLAB.jl/latest/adding_new.html
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.. _`esdl-shared`: https://github.com/esa-esdl/esdl-shared/tree/master/notebooks/Julia

doc/dat_python.rst

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.. _pandas: http://pandas.pydata.org/
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.. _datetime: https://docs.python.org/3/library/datetime.html
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.. _Numpy ndarrays: http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html
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.. _cablab.dat: https://github.com/CAB-LAB/cablab-core/blob/master/cablab/dat.py
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.. _E-Lab: https://cablab.earthsystemdatacube.net
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.. _Jupyter notebook: https://github.com/CAB-LAB/cablab-shared/blob/master/notebooks/Python/Python_DAT.ipynb
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.. _esdl.dat: https://github.com/esa-esdl/esdl-core/blob/master/esdl/dat.py
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.. _E-Lab: https://jupyterhub.earthsystemdatalab.net
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.. _Jupyter notebook: https://github.com/esa-esdl/esdl-shared/blob/master/notebooks/Python/Python_DAT.ipynb
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.. _Indexing and selecting data: http://xarray.pydata.org/en/stable/indexing.html
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from cablab import Cube
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cube = Cube.open("/home/doe/esdc/cablab-datacube-0.2.4/low-res")
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from esdl import Cube
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cube = Cube.open("/home/doe/esdc/esdc-31d-1deg-1x180x360-1.0.1_1")
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dataset = cube.data.dataset(["precipitation", "evaporation", "ozone", "soil_moisture","air_temperature_2m"])
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Any geo-physical variable in the ESDC is represented by a `xarray.DataArray`_, which are Numpy_-like data arrays
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* `Time series data`_
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Building on top of the xarray_ API the DAT offers high-level functions for ESDC-specific workflows
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in the `cablab.dat`_ module. These functions are addressing specific user requirements and
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in the `esdl.dat`_ module. These functions are addressing specific user requirements and
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the scope of the module will increase with the users of the DAT. In the following, typical use cases and examples
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.. automodule:: cablab.dat
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.. automodule:: esdl.dat
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:members:
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doc/esdc_access.rst

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.. _xarray.DataArray: http://xarray.pydata.org/en/stable/data-structures.html#dataarray
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.. _Numpy ndarray: http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html
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.. _ESDC E-Laboratory: http://cablab.earthsystemdatacube.net/cablab-jupyterhub/
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.. _ESDC THREDDS server: http://www.brockmann-consult.de/cablab-thredds/catalog.html
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.. _ESDC FTP server: ftp://ftp.brockmann-consult.de/cablab02/cablab-datacube-0.2.4/
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.. _ESDC community repository: https://github.com/CAB-LAB/cablab-shared
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.. _ESDC community notebooks: https://github.com/CAB-LAB/cablab-shared/tree/master/notebooks
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.. _ESDL E-Laboratory: http://jupyterhub.earthsystemdatalab.net/
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.. _ESDL THREDDS server: http://www.brockmann-consult.de/cablab-thredds/catalog.html
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.. _ESDL FTP server: ftp://ftp.brockmann-consult.de/cablab02/esdc-31d-1deg-1x180x360-1.0.1_1/
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.. _ESDL community repository: https://github.com/esa-esdl/esdl-shared
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.. _ESDL community notebooks: https://github.com/esa-esdl/esdl-shared/tree/master/notebooks
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===========
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Download ESDC Data
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==================
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The simplest approach to access the ESDC data is downloading it to you computer using the `ESDC FTP server`_.
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The simplest approach to access the ESDC data is downloading it to you computer using the `ESDL FTP server`_.
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Since the ESDC is basically a directory of NetCDF_ files, you can use a variety of software packages and programming
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languages to access the data. In each cube directory, you find a text file ``cube.config`` which describes the overall
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OPeNDAP and WCS Services
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========================
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The ESDC' data variables can also be accessed via a dedicated `ESDC THREDDS server`_.
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The ESDC' data variables can also be accessed via a dedicated `ESDL THREDDS server`_.
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The server supports the `OPeNDAP`_ and OGC-compliant `Web Coverage Service (WCS)`_ data access protocols.
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You can use it for accessing subsets of the ESDC's data variables and also for visual exploration of the data,
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E-Laboratory
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============
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A dedicated `ESDC E-Laboratory`_ has been developed to access the ESDC data via distributed
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A dedicated `ESDL E-Laboratory`_ has been developed to access the ESDC data via distributed
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`Jupyter`_ `Notebooks`_ for Julia and Python. This is the most resource efficient and convenient
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way of exploring the ESDC.
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These notebooks have direct access to the ESDC data so there is no need to download it.
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In addition they provide the ESDC Python and Julia APIs comprising
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the Data Access API and the Data Analytics Toolkit.
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The E-Laboratory provides some example notebooks in the shared `ESDC community repository`_.
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The E-Laboratory provides some example notebooks in the shared `ESDL community repository`_.
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The E-Laboratory is based on the JupyterHub_ platform and currently comprises three 16-core computers
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running in a Cloud environment.
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The ESDC Python package has been developed against latest Anaconda_ / Miniconda_ distributions and uses their
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Conda_ package manager.
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To get started on your local computer with Python, clone the `cablab-core`
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repository from `<https://github.com/CAB-LAB>`_:
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To get started on your local computer with Python, clone the `esdl-core`
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repository from `<https://github.com/esa-esdl>`_:
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.. code-block:: bash
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git clone https://github.com/CAB-LAB/cablab-core
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git clone https://github.com/esa-esdl/esdl-core
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The following command will create a new Python 3.5 environment named ``esdc`` with all required dependencies, namely
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The following command will create a new Python 3.5 environment named ``esdl`` with all required dependencies, namely
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* dask >= 0.14
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* gridtools >= 0.1 (from Conda channel ``forman``)
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* gridtools >= 0.1 (from Conda channel ``cablab``)
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* h5netcdf >= 0.3
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* h5py >= 2.7
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* netcdf4 >= 1.2
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> activate esdc
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Now change into new folder ``cablab-core`` and install the ``cablab`` Python package using the ``develop`` target:
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Now change into new folder ``esdl-core`` and install the ``esdl`` Python package using the ``develop`` target:
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.. code-block:: bash
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$ cd cablab-core
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$ cd esdl-core
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$ python setup.py develop
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You can now easily change source code in ``cablab-core`` without reinstalling it.
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You can now easily change source code in ``esdl-core`` without reinstalling it.
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When you do not plan to add or modify any code (e.g. add a new source data provider), you can also permanently
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.. code:: python
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from cablab import Cube
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from esdl import Cube
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from datetime import datetime
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import numpy as np
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cube.close()
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Some more demonstrations are included in the `ESDC community notebooks`_.
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Some more demonstrations are included in the `ESDL community notebooks`_.
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Using Julia
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===========

doc/esdc_descr.rst

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Format and Structure
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====================
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The binary data format for the Earth System Data Cube (ESDC) in the CAB-LAB project is **netCDF 4 classic**, where the term classic stands for an
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The binary data format for the Earth System Data Cube (ESDC) in the ESDL project is **netCDF 4 classic**, where the term classic stands for an
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underlying HDF-5 format accessed by a netCDF 4 API.
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The netCDF file's content and structure follows the `CF-conventions <http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html>`_.
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--------------------
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The current version (version 0.1, Feb 2016) of the ESDC does not explicitly fill gaps. However, some
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gap-filling occurs during temporal aggregation as described below. The CAB-LAB team may provide
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gap-filling occurs during temporal aggregation as described below. The ESDL team may provide
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gap-filled ESDC versions at a later point in time of the project. Gap-filling is part of the *Data Analytics
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Toolkit* and is thus not tackled during Data Cube generation to retain the information on the original data coverage
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as much as possible.

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