Metadata-Version: 2.1
Name: quagmire
Version: 0.2.1
Summary: Python surface process framework on highly scalable unstructured meshes
Home-page: https://github.com/University-of-Melbourne-Geodynamics/quagmire
Author: Louis Moresi
Author-email: louis.moresi@unimelb.edu.au
License: UNKNOWN
Description: # Quagmire
        
        Quagmire is a Python surface process framework for building erosion and deposition models on highly parallel, decomposed structured and unstructured meshes.
        
        Quagmire is structured into three major classes that inherit methods and attributes from lower tiers.
        
        ![Quagmire hierarchy](docs/images/hierarchy_chart.png)
        
        The Surface Processes class inherits from the Topography class, which in turn inherits from TriMesh or PixMesh depending on the type of mesh.
        
        ## Installation
        
        Numpy and a fortran compiler, preferably [gfortran](https://gcc.gnu.org/wiki/GFortran), are required to install Quagmire.
        
        - ``python setup.py build``
           - If you change the fortran compiler, you may have to add the
        flags `config_fc --fcompiler=<compiler name>` when setup.py is run
        (see docs for [numpy.distutils](http://docs.scipy.org/doc/numpy-dev/f2py/distutils.html)).
        - ``python setup.py install``
        
        
        ## Dependencies
        
        Running this code requires the following packages to be installed:
        
        - Petsc 3.7.x and above
        - Numpy 1.9 and above
        - Scipy 0.15 and above
        - [mpi4py](http://pythonhosted.org/mpi4py/usrman/index.html)
        - [petsc4py](https://pythonhosted.org/petsc4py/usrman/install.html)
        - [stripy](https://github.com/University-of-Melbourne-Geodynamics/stripy)
        - [h5py](http://docs.h5py.org/en/latest/mpi.html#building-against-parallel-hdf5) (optional - for saving parallel data)
        - Matplotlib (optional - for visualisation)
        
        ### PETSc installation
        
        PETSc is used extensively via the Python frontend, petsc4py. It is required that PETSc be configured and installed on your local machine prior to using Quagmire. You can use pip to install petsc4py and its dependencies.
        
        ```
        [sudo] pip install numpy mpi4py
        [sudo] pip install petsc petsc4py
        ```
        
        If that fails you must compile these manually.
        
        ### HDF5 installation
        
        This is an optional installation, but it is very useful for saving data that is distributed across multiple processes. If you are compiling HDF5 from [source](https://support.hdfgroup.org/downloads/index.html) it should be configured with the `--enable-parallel` flag:
        
        ```
        CC=/usr/local/mpi/bin/mpicc ./configure --enable-parallel --enable-shared --prefix=<install-directory>
        make	# build the library
        make check	# verify the correctness
        make install
        ```
        
        You can then point to this install directory when you install [h5py](http://docs.h5py.org/en/latest/mpi.html#building-against-parallel-hdf5).
        
        ## Usage
        
        Quagmire is highly scalable. All of the python scripts in the *tests* subdirectory can be run in parallel, e.g.
        
        ```
        mpirun -np 4 python stream_power.py
        ```
        
        where the number after the `-np` flag specifies the number of processors.
        
        ## Tutorials
        
        Tutorials with worked examples can be found in the *Notebooks* subdirectory. These are Jupyter Notebooks that can be run locally. We recommend installing [FFmpeg](https://ffmpeg.org/) to create videos in some of the notebooks.
        
        The topics covered in the Notebooks include:
        
        **Meshing**
        
        - Square mesh
        - Elliptical mesh
        - Mesh refinement (e.g. Lloyd's mesh improvement)
        - Poisson disc sampling
        
        **Flow algorithms**
        
        - Single and multiple downhill pathways
        - Accumulating flow
        
        **Erosion and deposition**
        
        - Long-range stream flow models
        - Short-range diffusive evolution
        
        **Landscape evolution**
        
        - Explicit timestepping and numerical stability
        - Landscape equilibrium metrics
        - Basement uplift
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
