{
    "info": {
        "author": "Jean-Michel Perraud, Juan Castilla",
        "author_email": "per202@csiro.au",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Build Tools"
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        "description": "ela\n===\n\nExploratory Lithology Analysis\n------------------------------\n\n|pypi|\\ |license| |Codacy Badge|\n\nmaster |build-master|\\ |codecov-master|\n\ntesting |build-testing|\\ |codecov-testing|\n\n|Getting started tutorial - Bungendore 3D lithology|\n\nAnalysing driller\u2019s logs is a tedious and repetitive task in many\ngroundwater modelling projects. Automating the process of extracting\nuseful information from driller\u2019s logs allows spending less time on\nmanual data wrangling, more time on its interpretation, and enhances the\nreproducibility of the analysis.\n\nThis package combines features to:\n\n-  perform natural language processing on lithology descriptions in the\n   logs, to detect primary and secondary lithologies\n-  apply supervised machine learning to interpolate lithologies across a\n   3D grid\n-  visualise interactively the 3D data\n\nAn introductory `sample\nworkflow <https://github.com/csiro-hydrogeology/pyela-doc/blob/master/tutorials/getting_started.ipynb>`__\ngives an overview of some of these capabilities.\n\nLicense\n-------\n\nMIT (see\n`License.txt <https://github.com/csiro-hydrogeology/pyela/blob/master/LICENSE.txt>`__)\n\nDocumentation\n-------------\n\nThe `documentation <https://pyela.readthedocs.io>`__ includes the API\ndocumentation.\n\nSome notebook tutorials are hosted `in a separate github repository\npyela-doc <https://github.com/csiro-hydrogeology/pyela-doc>`__.\npyela-doc includes quick setup instructions with conda.\n\nGet a quick tour of `some legacy\nvisualisations <https://github.com/csiro-hydrogeology/pyela/blob/master/docs/visual_tour.md>`__.\nVisualisation features are currently being reengineered.\n\nInstallation\n------------\n\nThe quickest way with conda. We recommend installing conda packages\nrather than pip packages whereever possible.\n\non Linux:\n\n.. code:: bash\n\n   wget https://raw.githubusercontent.com/csiro-hydrogeology/pyela/testing/configs/ela_environment.yml\n   my_env_name=ELA\n   # my_env_name=elauser\n   conda env create -n $my_env_name -f ./ela_environment.yml python=3.7\n   conda activate $my_env_name \n\nThis should be all to get a working environment. If you want to use\n\u2018ela\u2019 from jupyter lab:\n\n.. code:: bash\n\n   conda install --name ${my_env_name} jupyterlab ipywidgets jupyter\n   jupyter-labextension install @jupyter-widgets/jupyterlab-manager\n   python -m ipykernel install --user --name ${my_env_name} --display-name \"Py3 ELA\"\n\nWindows:\n\n.. code:: bat\n\n   call C:\\Users\\xxxyyy\\AppData\\Local\\Continuum\\anaconda3\\Scripts\\activate.bat\n   REM curl should come with anaconda3. Perhaps not with miniconda though.\n   where curl\n   cd c:\\tmp\n   curl -o ela_environment.yml https://raw.githubusercontent.com/csiro-hydrogeology/pyela/testing/configs/ela_environment.yml\n   set my_env_name=ELA\n   conda env create -n %my_env_name% -f ela_environment.yml python=3.7\n   conda activate %my_env_name% \n\n.. code:: bat\n\n   This should be all to get a working environment. If you want to use 'ela' from jupyter lab:\n\n.. code:: bat\n\n   conda install -c conda-forge --name %my_env_name% jupyterlab ipywidgets jupyter\n   jupyter-labextension install @jupyter-widgets/jupyterlab-manager\n   python -m ipykernel install --user --name %my_env_name% --display-name \"Py3 ELA\"\n\nTroubleshooting\n~~~~~~~~~~~~~~~\n\npip packages specified from the ``environment.yaml`` files may have not\ninstalled (under investigation). Check that pvgeo and \u201cour\u201d packages are\ninstalled e.g.\n\n.. code:: bat\n\n   conda activate %my_env_name%\n   conda list | grep pvgeo\n\nif not present:\n\n.. code:: bat\n\n   REM make sure you have git in the PATH e.g.\n   set PATH=C:\\Users\\per202\\AppData\\Local\\Atlassian\\SourceTree\\git_local\\mingw32\\bin\\;%PATH%\n   where git\n\n   conda activate %my_env_name%\n   pip install --no-deps pvgeo\n   pip install -e git+https://github.com/jmp75/striplog@master#egg=striplog\n   pip install --no-deps -e git+https://github.com/jmp75/pyela@master#egg=ela\n\nManual installation\n~~~~~~~~~~~~~~~~~~~\n\nAs of January 2019 `ela is on pypi <https://pypi.org/project/ela/>`__.\nWhile ``pip install ela`` might work on some computers, it is *unlikely\nthat all python geospatial dependencies will install*. *We highly\nrecommend you set up a conda environment with all dependent packages*\nprior to installing ela with pip or from source.\n\n\u2018ela\u2019 relies on several external packages, and some can be fiddly to\ninstall depending on the version of Python and these external packages.\nThis section thus has fairly prescriptive instructions, given in the\nhope of limiting the risk of issues.\n\nDebian packages for spatial projections\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n``cartopy`` and possibly other python packages require ``proj4`` version\n4.9+ to be installed (libproj-dev). If your debian/ubuntu repo does not\nsuffice (older versions) you may try:\n\n.. code:: bash\n\n   sudo apt-get install -y libc6  \n   wget http://en.archive.ubuntu.com/ubuntu/pool/universe/p/proj/proj-data_4.9.3-2_all.deb\n   sudo dpkg -i proj-data_4.9.3-2_all.deb\n   wget http://en.archive.ubuntu.com/ubuntu/pool/universe/p/proj/libproj12_4.9.3-2_amd64.deb\n   sudo dpkg -i libproj12_4.9.3-2_amd64.deb\n   wget http://en.archive.ubuntu.com/ubuntu/pool/universe/p/proj/proj-bin_4.9.3-2_amd64.deb\n   sudo dpkg -i proj-bin_4.9.3-2_amd64.deb\n   wget http://en.archive.ubuntu.com/ubuntu/pool/universe/p/proj/libproj9_4.9.2-2_amd64.deb \n   sudo dpkg -i libproj9_4.9.2-2_amd64.deb\n   wget http://en.archive.ubuntu.com/ubuntu/pool/universe/p/proj/libproj-dev_4.9.3-2_amd64.deb\n   sudo dpkg -i libproj-dev_4.9.3-2_amd64.deb\n\nInstallation of python packages dependencies\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nWe recommend installing\n`Anaconda <http://docs.continuum.io/anaconda/install>`__ to install\ndependencies. Note that I recommend to **not** let anaconda change your\nstartup file and change the ``PATH`` environment. To activate Anaconda\nyou first need: ``source ~/anaconda3/bin/activate``. Then choose a conda\nenvironment name.\n\nOptionally, if your anaconda installation is a bit dated, you may want\nto do ``conda update -n base conda`` and\n``conda update -n base anaconda-navigator``\n\nTo create the conda environment for ela on Linux:\n\n.. code:: bash\n\n   # source ~/anaconda3/bin/activate\n   my_env_name=ELA\n   conda create --name ${my_env_name} python=3.7\n   conda install --name ${my_env_name} rasterio cartopy geopandas pandas nltk scikit-learn scikit-image matplotlib vtk\n   conda activate  ${my_env_name}\n\nOn Windows, using the DOS CMD prompt, assuming you installed Anaconda in\nuser mode.\n\n.. code:: bat\n\n   call %userprofile%\\AppData\\Local\\Continuum\\anaconda3\\Scripts\\activate.bat\n   set my_env_name=ELA\n   conda create --name %my_env_name% python=3.7\n   REM if using conda activate  %my_env_name%  I seem to loose conda from the command line, so:\n   conda install --name %my_env_name% conda \n   conda install --name %my_env_name% rasterio cartopy geopandas pandas nltk scikit-learn scikit-image matplotlib vtk\n   conda activate  %my_env_name%\n\nAt this point we have installed all the python dependencies ela needs\nthat are available via ``conda``.\n\nAs of writing (2019-08) conda does not have pyqt5, and no suitable\nversion of mayavi for python3. We resort to use ``pip``. You may want to\ndo first:\n\n.. code:: bash\n\n   pip install --upgrade pip\n\nFor Python 3.x one needs to install pyqt5 for mayavi, as per `these\ninstructions <https://docs.enthought.com/mayavi/mayavi/installation.html>`__.\nAs of Jan 2019 be aware that there is a `known issue in mayavi visual\nrendering with pyqt5 as a backend on\nLinux <https://github.com/enthought/mayavi/issues/656>`__ and \u2018ela\u2019 is\naffected by this. Nevertheless this is not a commplete blocker for most\n\u2018ela\u2019 features so installation instructions are kept here.\n\n.. code:: bash\n\n   pip search pyqt5 | sort -g\n   pip search mayavi\n\n.. code:: bash\n\n   pip install pyqt5\n   pip install mayavi\n\nFor users without admin rights\uff0c\n\n.. code:: bash\n\n   conda install pyqt5\n   pip install mayavi --user\n\nAt this point all mandatory dependencies for \u2018ela\u2019 are installed.\n\nInstalling ELA\n~~~~~~~~~~~~~~\n\nThere are three options to access ela:\n\n-  use the latest available on pip,\n-  clone and install with ``setup.py``\n-  direct import of the package directory (this is done at runtime from\n   e.g.\u00a0a notebook)\n\n.. code:: bash\n\n   pip search ela\n   pip install ela\n\nAlternatively, from source with ``setup.py``\n\n.. code:: bash\n\n   pip install -r requirements.txt\n   python setup.py install\n\nOptional dependencies\n^^^^^^^^^^^^^^^^^^^^^\n\nAs of 2019-05 you can find new features using deep learning for\nclassification in the submodule ``ela.experiment``. You will need the\nadditional dependencies:\n\n.. code:: bash\n\n   conda install --name ${my_env_name} gensim tensorflow keras\n   pip install wordcloud\n\nIf reading xls files using pandas, need pkg ``xlrd`` with e.g.\n``conda install xlrd``\n\nusing Jupyter-lab\n~~~~~~~~~~~~~~~~~\n\nYou may use ela as you prefer; we recomment using \u201cJupyter Lab\u201d to write\nnotebooks. See the `Jupyter lab\ndoc <https://jupyterlab.readthedocs.io/en/stable/>`__ for official\ninformation.\n\nThe following should be enough otherwise to use \u2018ela\u2019\n\nLinux:\n\n.. code:: bash\n\n   my_env_name=ELA\n   conda install --name ${my_env_name} jupyterlab ipywidgets jupyter\n   jupyter-labextension install @jupyter-widgets/jupyterlab-manager\n   python -m ipykernel install --user --name ${my_env_name} --display-name \"Py3 ELA\"\n\nWindows:\n\n.. code:: bat\n\n   set my_env_name=ELA\n   conda install --name %my_env_name% jupyterlab ipywidgets jupyter\n   jupyter-labextension install @jupyter-widgets/jupyterlab-manager\n   python -m ipykernel install --user --name %my_env_name% --display-name \"Py3 ELA\"\n\nRelated Geoscience packages\n---------------------------\n\n\u2018ela\u2019 aims to complement other Python packages for geoscience, in\nparticular for handling bore data . It already depends on the package\n`\u2018striplog\u2019 <https://github.com/agile-geoscience/striplog>`__ and is\nlikely to depend on `\u2018lasio\u2019 <https://github.com/kinverarity1/lasio>`__\nin the future.\n\nYou should also check the repository\n`hydrogeol_utils <https://github.com/Neil-Symington/hydrogeol_utils>`__\n\nKnown issues\n------------\n\n3D interactive visualisation - Using mayavi 4.6+ on python 3.6+ may be\n`visually buggy <https://github.com/enthought/mayavi/issues/656>`__ on\nLinux. This appears to be a low level issue running on laptop with dual\nIntel/NVIDIA Graphic cards.\n\n.. _troubleshooting-1:\n\nTroubleshooting\n---------------\n\nIf in a conda environment trying to use ``pip`` you get:\n\n.. code:: text\n\n   ModuleNotFoundError: No module named 'pip._internal'\n\nconsider:\n\n.. code:: bash\n\n   curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py\n   python3 get-pip.py --force-reinstall\n\n.. |pypi| image:: https://img.shields.io/pypi/v/ela.svg?logo=python&logoColor=white\n   :target: https://pypi.org/project/ela/\n.. |license| image:: http://img.shields.io/badge/license-MIT-blue.svg\n   :target: https://github.com/csiro-hydrogeology/pyela/blob/master/LICENSE.txt\n.. |Codacy Badge| image:: https://api.codacy.com/project/badge/Grade/40f01ca659f04fe5832bbfe7f939bf8b\n   :target: https://www.codacy.com/app/jmp75/pyela?utm_source=github.com&utm_medium=referral&utm_content=csiro-hydrogeology/pyela&utm_campaign=Badge_Grade\n.. |build-master| image:: https://img.shields.io/travis/csiro-hydrogeology/pyela.svg?branch=master\n   :target: https://travis-ci.org/csiro-hydrogeology/pyela/branches\n.. |codecov-master| image:: https://codecov.io/gh/csiro-hydrogeology/pyela/branch/master/graph/badge.svg\n   :target: https://codecov.io/gh/csiro-hydrogeology/pyela/branch/master\n.. |build-testing| image:: https://img.shields.io/travis/csiro-hydrogeology/pyela.svg?branch=testing\n   :target: https://travis-ci.org/csiro-hydrogeology/pyela/branches\n.. |codecov-testing| image:: https://codecov.io/gh/csiro-hydrogeology/pyela/branch/testing/graph/badge.svg\n   :target: https://codecov.io/gh/csiro-hydrogeology/pyela/branch/testing\n.. |Getting started tutorial - Bungendore 3D lithology| image:: https://raw.githubusercontent.com/csiro-hydrogeology/pyela-doc/master/tutorials/img/3d_overlay_bungendore_clay_lithology_small.png\n   :target: https://github.com/csiro-hydrogeology/pyela-doc/blob/master/tutorials/getting_started.ipynb\n\n\n",
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