Check feasibility of PCRaster import alternatives

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PCRaster Info

Installing PCRaster

PCRaster is available on conda-forge and can be installed using conda. Supported platforms are Linux, macOS and Windows.

We recommend to download and install Miniconda. The user guide and short reference on conda can be found here. After install you can check which Python versions are supported by PCRaster:

conda search -c conda-forge pcraster

Afterwards you can create a new environment and install PCRaster, e.g. with the following steps:

conda create --name pcraster -c conda-forge python

conda activate pcraster

conda install -c conda-forge pcraster

• Conda package recipe

• PCRaster-feedstock conda (automated builds) & Github workflows

• Conda builds
  https://anaconda.org/conda-forge/pcraster

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Python packaging tools

• Python Wheels
  Tutorial https://hynek.me/articles/sharing-your-labor-of-love-pypi-quick-and-dirty/

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Solutions from other packages that use PCRaster

• wflow

  wflow consists of a set of Python programs that can be run on the command line and perform hydrological simulations. The models are based on the PCRaster Python framework. In wflow this framework is extended (the wf_DynamicFramework) so that models build using the framework can be controlled using the API. Links to BMI, OpenMI and OpenDAP have been made.

  A link to the latest version can always be found at https://github.com/openstreams/wflow

  Reference documentation

  • Installing pcraster

    • If you are using conda, pcraster will be installed automatically in the section below, otherwise:
    • Download pcraster from http://pcraster.geo.uu.nl/ website (version 4.2+)
    • Follow the installation instructions at https://pcraster.geo.uu.nl/pcraster/4.3.1/documentation/pcraster_project/install.html

  • Install as a conda environment

  • Install using pip

    [...]

    If you want to avoid using conda, an example of a PCRaster build and pip install on Ubuntu Linux can be found in issue #36 Installing wflow on Ubuntu 18.04

    [...]

    For my specific application, I want the Python distribution to be as lean as possible. Therefore, I was not going for the Anaconda environment solution.

    Compile PCRaster from source:

    sudo apt install cmake gcc g++ git qtbase5-dev libncurses5-dev libqwt-qt5-dev libxerces-c-dev libboost-all-dev libgdal-dev python3-numpy python3-docopt
    wget http://pcraster.geo.uu.nl/pcraster/4.2.1/pcraster-4.2.1.tar.bz2
    tar xf pcraster-4.2.1.tar.bz2 && cd pcraster-4.2.1
    mkdir build && cd build
    cmake -DFERN_BUILD_ALGORITHM:BOOL=TRUE -DCMAKE_INSTALL_PREFIX:PATH=$HOME/pcraster -DPYTHON_EXECUTABLE:FILEPATH=/usr/bin/python3 ..
    cmake --build .
    make install
    export PATH=$PATH:$HOME/pcraster/bin
    export PYTHONPATH=$PYTHONPATH:$HOME/pcraster/python

    Since the automatic installation of the required Python packages did not work for me, I installed them manually using pip

    sudo apt install python3-pip
    pip3 install numpy
    pip3 install scipy
    pip3 install GDAL==$(gdal-config --version | awk -F'[.]' '{print $1"."$2}') --global-option=build_ext --global-option="-I/usr/include/gdal"
    pip3 install netcdf4
    pip3 install pyproj
    sudo apt-get install libllvm-9-ocaml-dev libllvm9 llvm-9 llvm-9-dev llvm-9-doc llvm-9-examples llvm-9-runtime
    export LLVM_CONFIG='/usr/bin/llvm-config-9'
    pip3 install numba
    pip3 install python-dateutil

    Afterwards I was cloning the git repository to my $Home directory

    cd $HOME
    git clone https://github.com/openstreams/wflow.git

    I had to excluded the required packages in the setup.py file, which is located in $HOME/wflow/setup.py

    install_requires=[
    	#   "numpy",
    	#   "scipy",
        #   "gdal",
        #   "netCDF4",
        #   "xarray",
    	#   "cftime",
        #   "numba",
        #   "pyproj",
    	#   "python-dateutil",
    ], 

    At last wflow can be installed by using pip

    cd wflow
    pip3 install -e .

[soaressgabriel]

Python Wrapping

• exec-wrappers

  Wrappers for running commands that need some initial setup. exec-wrappers is useful whenever you need a single executable file, but have to do some setup before executing it.

  If you develop using some kind of environment isolation like conda, schroot, virtualenv you probably wanted to configure a GUI application like an IDE to use the executables available inside these environments.

  [...]

  Creating conda wrappers:

  $ create-wrappers  -t conda --bin-dir ~/miniconda/envs/test/bin --dest-dir /tmp/conda_wrappers --conda-env-dir ~/miniconda/envs/test

  This will create in /tmp/conda_wrappers a wrapper for each executable found in ~/miniconda/envs/test/bin. So if you run the python wrapper:

  $ /tmp/conda_wrappers/python -c "import sys; print(sys.executable)"
  /home/username/miniconda/envs/test/bin/python

  It will actually activate the conda environment and set necessary variables, and then execute the real python interpreter. So you can use the wrapper to configure you IDE, for example.

  Features

  • automatically detect executables in a given directory
  • wrappers written in plain shell and batch scripts
  • low overhead (as low as possible)
  • built-in wrappers for common tools

  Requirements

  python is the only dependency to create wrappers. To properly use the generated wrappers you need the tool used by the wrapper (conda, schroot, etc.).

[soaressgabriel]

O Hans van der Kwast anunciou o PCRaster Tools plugin para o QGIS mais recente e agora é possível instalar o PCRaster (somente Windows por enquanto) através do instalador OSGeo4W no ambiente Python do QGIS.