Metadata-Version: 2.1
Name: omfvtk
Version: 0.0.4
Summary: A VTK interface for the Open Mining Format package
Home-page: https://github.com/OpenGeoVis/omfvtk
Author: Bane Sullivan
Author-email: info@pvgeo.org
License: UNKNOWN
Description: OMF-VTK
        =======
        
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           :target: https://omfvtk.readthedocs.io/en/latest/
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           :target: https://pypi.org/project/omfvtk/
           :alt: PyPI
        
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           :target: https://travis-ci.org/OpenGeoVis/omfvtk
           :alt: Build Status
        
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           :alt: GitHub
        
        
        A VTK interface for the `Open Mining Format package`_ (``omf``).
        
        .. _Open Mining Format package: https://omf.readthedocs.io/en/latest/
        
        Example Use
        -----------
        
        Be sure to check out the `Example Notebook`_ that demos ``omfvtk``!
        Here's an example using the sample data hosted in the `OMF repository`_.
        
        .. _Example Notebook: https://github.com/OpenGeoVis/omfvtk/blob/master/Example.ipynb
        .. _OMF repository: https://github.com/gmggroup/omf/tree/master/assets
        
        .. code-block:: python
        
            >>> import vtki
            >>> import omfvtk
        
            >>> project = omfvtk.load_project('test_file.omf')
            >>> project
        
        .. raw:: html
        
            <embed>
            <table><tr><th>Information</th><th>Blocks</th></tr><tr><td>
            <table>
            <tr><th>vtkMultiBlockDataSet</th><th>Values</th></tr>
            <tr><td>N Blocks</td><td>9</td></tr>
            <tr><td>X Bounds</td><td>443941.105, 447059.611</td></tr>
            <tr><td>Y Bounds</td><td>491941.536, 495059.859</td></tr>
            <tr><td>Z Bounds</td><td>2330.000, 3555.942</td></tr>
            </table>
            </td><td>
            <table>
            <tr><th>Index</th><th>Name</th><th>Type</th></tr>
            <tr><th>0</th><th>collar</th><th>vtkPolyData</th></tr>
            <tr><th>1</th><th>wolfpass_WP_assay</th><th>vtkPolyData</th></tr>
            <tr><th>2</th><th>Topography</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>3</th><th>Basement</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>4</th><th>Early Diorite</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>5</th><th>Intermineral diorite</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>6</th><th>Dacite</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>7</th><th>Cover</th><th>vtkUnstructuredGrid</th></tr>
            <tr><th>8</th><th>Block Model</th><th>vtkRectilinearGrid</th></tr>
            </table>
            </td></tr> </table>
            </embed>
        
        
        Once the data is loaded as a `vtki.MultiBlock` dataset from ``omfvtk``, then
        that object can be directly used for interactive 3D visualization from ``vtki``:
        
        .. code-block:: python
        
            >>> project.plot(notebook=False)
        
        Or an interactive scene can be created and manipulated to create a compelling
        figure directly in a Jupyter notebook. First, grab the elements from the project:
        
        .. code-block:: python
        
            # Grab a few elements of interest and plot em up!
            >>> vol = project['Block Model']
            >>> assay = project['wolfpass_WP_assay']
            >>> topo = project['Topography']
            >>> dacite = project['Dacite']
        
        Then apply a filtering tool from `vtki` to the volumetric data:
        
        .. code-block:: python
        
            >>> thresher = vtki.Threshold(vol)
        
        .. figure:: https://github.com/OpenGeoVis/omfvtk/blob/master/threshold.gif
        
        Then you can put it all in one environment!
        
        .. code-block:: python
        
            >>> p = vtki.BackgroundPlotter()#Plotter(notebook=False)
        
        
            >>> p.add_mesh(topo, colormap='gist_earth', showedges=False, opacity=0.5)
            >>> p.add_mesh(assay, color='blue', linethick=3)
            >>> p.add_mesh(thresher.output_dataset, showedges=False, rng=vol.get_data_range(), colormap='jet')
            >>> p.add_mesh(dacite, showedges=False, color='yellow', opacity=0.6)
        
            >>> p.add_bounds_axes(topo)
        
        And once you like what the render view displays, you can save a screenshot:
        
        .. code-block:: python
        
            >>> p.screenshot('wolfpass.png')
        
        .. image:: https://github.com/OpenGeoVis/omfvtk/blob/master/wolfpass.png
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: English
Description-Content-Type: text/x-rst
