Metadata-Version: 2.1
Name: pyvoronoi
Version: 1.1.3
Summary: Cython wrapper for the Boost Voronoi library (version 1.59.0)
Home-page: https://github.com/fabanc/pyvoronoi
Author: Fabien Ancelin / Andrii Sydorchuk, Voxel8
Author-email: 
License: UNKNOWN
Description: 
        # pyvoronoi
        
        A wrapper for Boost's Voronoi diagram library. The full documentation of the Boost Voronoi API is available [here](https://www.boost.org/doc/libs/1_75_0/libs/polygon/doc/voronoi_main.htm).
        
        ## Install
        
        The installation have been tested on Windows and Linux Ubuntu. If you notice any issue on Mac, reach out to us, we are interested in making sure it works for you.
        
        Windows users will need Microsoft Visual C++ installed on their machine. You can find information about the version needed on [this](https://wiki.python.org/moin/WindowsCompilers) link. Python version from 3.5 to 3.12 rely on Visual C++ 14.x.
        
        ### Dependencies
        
        Cython dependency is optional. Cpp sources generated with Cython are available in releases.
        
        Note on using the setup.py:
        
        setup.py operates in 2 modes that are based on the presence of the dev file in the root of the project.
        
        * When dev is **present**, Cython will be used to compile the .pyx sources. This is the development mode (as you get it in the git repository).
        
        * When dev is **absent**, C/C++ compiler will be used to compile the .cpp sources (that were prepared in in the development mode). This is the distribution mode (as you get it on PyPI).
        
        This way the package can be used without or with an incompatible version of Cython.
        
        The idea comes from Matt Shannon's bandmat library.
        
        ### From PyPI
        
        
        Cython not required.
        
        ``pip install pyvoronoi``
        
        ### From source
        
        
        Cython required.
        
        Clone the repository:
        
        ``git clone https://github.com/fabanc/pyvoronoi.git``
        
        Install:
        
        ``python setup.py install``
        
        After every modification of .pyx files compile with Cython:
        
        ``python setup.py build_ext --inplace``
        
        Note in order to build the wheels, you will need to also install ``wheel``
        
        ``pip install wheel``
        
        ### Using
        
        
        Create a new instance, passing the scaling factor into the constructor:
        ```
        import pyvoronoi
        pv = pyvoronoi.Pyvoronoi(10)
        ```
        
        Since the voronoi library uses integer representation for points, the scaling factor chosen must be high enough
        to avoid roundoff error when converting from point coordinates to integers.
        
        Add points and segments:
        
        ```python
        pv.AddPoint([0, 0])
        pv.AddSegment([[1,5],[2,2]])
        ```
        
        Call ``Construct()`` and get the edges and vertices:
        
        
        ```python
        pv.Construct()
        edges = pv.GetEdges()
        vertices = pv.GetVertices()
        cells = pv.GetCells()
        ```
        
        Note that vertices, edges, and cells, can be accessed individually. The methods above are just convenience wrappers around
        the following functions:
        
        * GetVertex
        
        * GetEdge
        
        * Get Cell
        
        ```python
        def GetVertices(self):
            count = self.CountVertices()
            output = []
            for index in  range(count):
                output.append(self.GetVertex(index))
            return output
        ```
        
        ```python
        def GetEdges(self):
            count = self.CountEdges()
            output = []
            for index in range(count):
                output.append(self.GetEdge(index))
            return output
        ```
        
        ```python
        def GetCells(self):
            count = self.CountCells()
            output = []
            for index in range(count):
                output.append(self.GetCell(index))
            return output
        ```
        
        If you are running python 2.x, you might want to write your own wrappers using xrange. This will be more efficient.
        
        Edges have the following properties:
        
        * ``start, end`` contain the indices of the start and end vertices or ``-1`` if the edge is infinite at that end.
        * ``is_primary`` is true if the edge is not coincident with any of the source inputs.
        * ``is_linear`` is true if the edge is linear (not curved).
        * ``cell`` is the identifier of the cell this segment is part of.
        * ``twin`` is the identifier of the twin segment as defined in the boost voronoi API.
        
        Cells have the following properties:
        
        * ``cell_identifier`` is the index of the cell.
        * ``site`` is the index of the site which generated this cell (same as site1, site2 on the edges).
        * ``contains_point`` is true if the site was generated by a point.
        * ``contains_segment`` is true if the site was generated by a segment.
        * ``is_open`` is true if any of the cell's edges is infinite.
        * ``is_degenerate`` is true if the cell doesn't have an incident edge. Can happen if a few input segments share a common endpoint.
        * ``vertices`` contains indices into the vertex array.
        * ``edges`` contains indices into the edge array.
        
        ```python
        pv = pyvoronoi.Pyvoronoi(100)
        pv.AddSegment([[0.1,0.8],[0.3,0.6]])
        pv.AddSegment([[0.3,0.6],[0.4,0.6]])
        pv.AddSegment([[0.4,0.6],[0.4,0.5]])
        pv.AddSegment([[0.4,0.6],[0.4,0.7]])
        pv.AddSegment([[0.4,0.7],[0.5,0.8]])
        pv.AddSegment([[0.4,0.7],[0.5,0.6]])
        pv.AddSegment([[0.5,0.6],[0.7,0.7]])
        
        pv.Construct()
        edges = pv.GetEdges()
        vertices = pv.GetVertices()
        cells = pv.GetCells()
        print("Cell Count: {0}".format(len(cells)))
        for c in cells:
            print("Cell contains point: {0}. Contains segment: {1}. Is open: {2}, Site Index: {3}".format(c.contains_point, c.contains_segment, c.is_open, c.site))
            print(",".join(map(str,c.vertices)))
            for sIndex in c.edges:
                print("Start Index: {0}, End Index = {1}".format(edges[sIndex].start, edges[sIndex].end))
        ```
        
        Some output edges returned by the boost voronoi API are suposed to be curved. In the C++ API, it is up to you to code it. Luckily, you can do it in python using the following the function DiscretizeCurvedEdge.
        The sample below shows you how to do that:
        
        ```python
        for cIndex in range(len(cells)):
            cell = cells[cIndex]
            if cell.is_open == False:
                for i in range(len(cell.edges)):
                    e = edges[cell.edges[i]]
                    startVertex = vertices[e.start]
                    endVertex = vertices[e.end]
        
                    max_distance  = distance([startVertex.X, startVertex.Y], [endVertex.X, endVertex.Y]) / 10
                    if startVertex != -1 and endVertex != -1:
                        if(e.is_linear == True):
                            array = [[startVertex.X, startVertex.Y],[endVertex.X, endVertex.Y]]
                        else:
                            points = pv.DiscretizeCurvedEdge(i, max_distance)
                            for p in points:
                                print "{0},{1}".format(p[0], p[1])
        ```
        
        The curve interpolation code can return 2 exceptions.
        
        * FocusOnDirectixException: this happens when the input point is on the segment side. In that cases, it makes no sense to interpolate a parabola between those two geometries since a parabola equation is supposed to find an equidistant point between the two geometries.
        
        * UnsolvableParabolaEquation: there are cases where the point returned by boost does not fit with the parabola equation (for a same position on the x-axis, we get 2 different points, both equidistant). Understanding this issue is still under investigation. It is possible to mitigate this issue by setting an optional 3rd parameter of the function DiscretizeCurvedEdge). A higher value means more tolerance to this exception. The recommended value would be 1 / Scaling Factor.
        
        # License
        
        -  Pyvoronoi is available under `MIT
           license <http://opensource.org/licenses/MIT>`__.
        -  The core Voronoi library is available under `Boost Software
           License <http://www.boost.org/LICENSE_1_0.txt>`__. Freeware for both
           open source and commercial applications.
        
        
        # Development
        
        ## Build tools
        
        This project uses [cibuildwheel](https://github.com/pypa/cibuildwheel) to build wheels on multiple platforms.
Keywords: voronoi,Boost,polygon
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Cython
Classifier: Programming Language :: C++
Classifier: Environment :: Other Environment
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Multimedia :: Graphics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
