{
    "info": {
        "author": "Rick van Hattem",
        "author_email": "Wolph@Wol.ph",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 6 - Mature",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "numpy-stl\n==============================================================================\n\n\n.. image:: https://travis-ci.org/WoLpH/numpy-stl.svg?branch=master\n    :alt: numpy-stl test status \n    :target: https://travis-ci.org/WoLpH/numpy-stl\n\n.. image:: https://badge.fury.io/py/mt-940.svg\n    :alt: numpy-stl Pypi version \n    :target: https://pypi.python.org/pypi/mt-940\n\n.. image:: https://coveralls.io/repos/WoLpH/numpy-stl/badge.svg?branch=master\n    :alt: numpy-stl code coverage \n    :target: https://coveralls.io/r/WoLpH/numpy-stl?branch=master\n\n.. image:: https://img.shields.io/pypi/pyversions/mt-940.svg\n\nSimple library to make working with STL files (and 3D objects in general) fast\nand easy.\n\nDue to all operations heavily relying on `numpy` this is one of the fastest\nSTL editing libraries for Python available.\n\nLinks\n-----\n\n - The source: https://github.com/WoLpH/numpy-stl\n - Project page: https://pypi.python.org/pypi/numpy-stl\n - Reporting bugs: https://github.com/WoLpH/numpy-stl/issues\n - Documentation: http://numpy-stl.readthedocs.org/en/latest/\n - My blog: https://wol.ph/\n\nRequirements for installing:\n------------------------------------------------------------------------------\n\n - `numpy`_ any recent version\n - `python-utils`_ version 1.6 or greater\n\nInstallation:\n------------------------------------------------------------------------------\n\n`pip install numpy-stl`\n\nInitial usage:\n------------------------------------------------------------------------------\n\n - `stl2bin your_ascii_stl_file.stl new_binary_stl_file.stl`\n - `stl2ascii your_binary_stl_file.stl new_ascii_stl_file.stl`\n - `stl your_ascii_stl_file.stl new_binary_stl_file.stl`\n\nContributing:\n------------------------------------------------------------------------------\n\nContributions are always welcome. Please view the guidelines to get started:\nhttps://github.com/WoLpH/numpy-stl/blob/develop/CONTRIBUTING.rst\n\nQuickstart\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    import numpy\n    from stl import mesh\n\n    # Using an existing stl file:\n    your_mesh = mesh.Mesh.from_file('some_file.stl')\n\n    # Or creating a new mesh (make sure not to overwrite the `mesh` import by\n    # naming it `mesh`):\n    VERTICE_COUNT = 100\n    data = numpy.zeros(VERTICE_COUNT, dtype=mesh.Mesh.dtype)\n    your_mesh = mesh.Mesh(data, remove_empty_areas=False)\n\n    # The mesh normals (calculated automatically)\n    your_mesh.normals\n    # The mesh vectors\n    your_mesh.v0, your_mesh.v1, your_mesh.v2\n    # Accessing individual points (concatenation of v0, v1 and v2 in triplets)\n    assert (your_mesh.points[0][0:3] == your_mesh.v0[0]).all()\n    assert (your_mesh.points[0][3:6] == your_mesh.v1[0]).all()\n    assert (your_mesh.points[0][6:9] == your_mesh.v2[0]).all()\n    assert (your_mesh.points[1][0:3] == your_mesh.v0[1]).all()\n\n    your_mesh.save('new_stl_file.stl')\n\nPlotting using `matplotlib`_ is equally easy:\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    from stl import mesh\n    from mpl_toolkits import mplot3d\n    from matplotlib import pyplot\n\n    # Create a new plot\n    figure = pyplot.figure()\n    axes = mplot3d.Axes3D(figure)\n\n    # Load the STL files and add the vectors to the plot\n    your_mesh = mesh.Mesh.from_file('tests/stl_binary/HalfDonut.stl')\n    axes.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors))\n\n    # Auto scale to the mesh size\n    scale = your_mesh.points.flatten(-1)\n    axes.auto_scale_xyz(scale, scale, scale)\n\n    # Show the plot to the screen\n    pyplot.show()\n\n.. _numpy: http://numpy.org/\n.. _matplotlib: http://matplotlib.org/\n.. _python-utils: https://github.com/WoLpH/python-utils\n\nModifying Mesh objects\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    from stl import mesh\n    import math\n    import numpy\n\n    # Create 3 faces of a cube\n    data = numpy.zeros(6, dtype=mesh.Mesh.dtype)\n\n    # Top of the cube\n    data['vectors'][0] = numpy.array([[0, 1, 1],\n                                      [1, 0, 1],\n                                      [0, 0, 1]])\n    data['vectors'][1] = numpy.array([[1, 0, 1],\n                                      [0, 1, 1],\n                                      [1, 1, 1]])\n    # Front face\n    data['vectors'][2] = numpy.array([[1, 0, 0],\n                                      [1, 0, 1],\n                                      [1, 1, 0]])\n    data['vectors'][3] = numpy.array([[1, 1, 1],\n                                      [1, 0, 1],\n                                      [1, 1, 0]])\n    # Left face\n    data['vectors'][4] = numpy.array([[0, 0, 0],\n                                      [1, 0, 0],\n                                      [1, 0, 1]])\n    data['vectors'][5] = numpy.array([[0, 0, 0],\n                                      [0, 0, 1],\n                                      [1, 0, 1]])\n\n    # Since the cube faces are from 0 to 1 we can move it to the middle by\n    # substracting .5\n    data['vectors'] -= .5\n\n    # Generate 4 different meshes so we can rotate them later\n    meshes = [mesh.Mesh(data.copy()) for _ in range(4)]\n\n    # Rotate 90 degrees over the Y axis\n    meshes[0].rotate([0.0, 0.5, 0.0], math.radians(90))\n\n    # Translate 2 points over the X axis\n    meshes[1].x += 2\n\n    # Rotate 90 degrees over the X axis\n    meshes[2].rotate([0.5, 0.0, 0.0], math.radians(90))\n    # Translate 2 points over the X and Y points\n    meshes[2].x += 2\n    meshes[2].y += 2\n\n    # Rotate 90 degrees over the X and Y axis\n    meshes[3].rotate([0.5, 0.0, 0.0], math.radians(90))\n    meshes[3].rotate([0.0, 0.5, 0.0], math.radians(90))\n    # Translate 2 points over the Y axis\n    meshes[3].y += 2\n\n\n    # Optionally render the rotated cube faces\n    from matplotlib import pyplot\n    from mpl_toolkits import mplot3d\n\n    # Create a new plot\n    figure = pyplot.figure()\n    axes = mplot3d.Axes3D(figure)\n\n    # Render the cube faces\n    for m in meshes:\n        axes.add_collection3d(mplot3d.art3d.Poly3DCollection(m.vectors))\n\n    # Auto scale to the mesh size\n    scale = numpy.concatenate([m.points for m in meshes]).flatten(-1)\n    axes.auto_scale_xyz(scale, scale, scale)\n\n    # Show the plot to the screen\n    pyplot.show()\n\nExtending Mesh objects\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    from stl import mesh\n    import math\n    import numpy\n\n    # Create 3 faces of a cube\n    data = numpy.zeros(6, dtype=mesh.Mesh.dtype)\n\n    # Top of the cube\n    data['vectors'][0] = numpy.array([[0, 1, 1],\n                                      [1, 0, 1],\n                                      [0, 0, 1]])\n    data['vectors'][1] = numpy.array([[1, 0, 1],\n                                      [0, 1, 1],\n                                      [1, 1, 1]])\n    # Front face\n    data['vectors'][2] = numpy.array([[1, 0, 0],\n                                      [1, 0, 1],\n                                      [1, 1, 0]])\n    data['vectors'][3] = numpy.array([[1, 1, 1],\n                                      [1, 0, 1],\n                                      [1, 1, 0]])\n    # Left face\n    data['vectors'][4] = numpy.array([[0, 0, 0],\n                                      [1, 0, 0],\n                                      [1, 0, 1]])\n    data['vectors'][5] = numpy.array([[0, 0, 0],\n                                      [0, 0, 1],\n                                      [1, 0, 1]])\n\n    # Since the cube faces are from 0 to 1 we can move it to the middle by\n    # substracting .5\n    data['vectors'] -= .5\n\n    cube_back = mesh.Mesh(data.copy())\n    cube_front = mesh.Mesh(data.copy())\n\n    # Rotate 90 degrees over the X axis followed by the Y axis followed by the\n    # X axis\n    cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))\n    cube_back.rotate([0.0, 0.5, 0.0], math.radians(90))\n    cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))\n\n    cube = mesh.Mesh(numpy.concatenate([\n        cube_back.data.copy(),\n        cube_front.data.copy(),\n    ]))\n\n    # Optionally render the rotated cube faces\n    from matplotlib import pyplot\n    from mpl_toolkits import mplot3d\n\n    # Create a new plot\n    figure = pyplot.figure()\n    axes = mplot3d.Axes3D(figure)\n\n    # Render the cube\n    axes.add_collection3d(mplot3d.art3d.Poly3DCollection(cube.vectors))\n\n    # Auto scale to the mesh size\n    scale = cube_back.points.flatten(-1)\n    axes.auto_scale_xyz(scale, scale, scale)\n\n    # Show the plot to the screen\n    pyplot.show()\n\nCreating Mesh objects from a list of vertices and faces\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    import numpy as np\n    from stl import mesh\n\n    # Define the 8 vertices of the cube\n    vertices = np.array([\\\n        [-1, -1, -1],\n        [+1, -1, -1],\n        [+1, +1, -1],\n        [-1, +1, -1],\n        [-1, -1, +1],\n        [+1, -1, +1],\n        [+1, +1, +1],\n        [-1, +1, +1]])\n    # Define the 12 triangles composing the cube\n    faces = np.array([\\\n        [0,3,1],\n        [1,3,2],\n        [0,4,7],\n        [0,7,3],\n        [4,5,6],\n        [4,6,7],\n        [5,1,2],\n        [5,2,6],\n        [2,3,6],\n        [3,7,6],\n        [0,1,5],\n        [0,5,4]])\n\n    # Create the mesh\n    cube = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))\n    for i, f in enumerate(faces):\n        for j in range(3):\n            cube.vectors[i][j] = vertices[f[j],:]\n\n    # Write the mesh to file \"cube.stl\"\n    cube.save('cube.stl')\n\n\nEvaluating Mesh properties (Volume, Center of gravity, Inertia)\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    import numpy as np\n    from stl import mesh\n\n    # Using an existing closed stl file:\n    your_mesh = mesh.Mesh.from_file('some_file.stl')\n\n    volume, cog, inertia = your_mesh.get_mass_properties()\n    print(\"Volume                                  = {0}\".format(volume))\n    print(\"Position of the center of gravity (COG) = {0}\".format(cog))\n    print(\"Inertia matrix at expressed at the COG  = {0}\".format(inertia[0,:]))\n    print(\"                                          {0}\".format(inertia[1,:]))\n    print(\"                                          {0}\".format(inertia[2,:]))\n\nCombining multiple STL files\n------------------------------------------------------------------------------\n\n.. code-block:: python\n\n    import math\n    import stl\n    from stl import mesh\n    import numpy\n\n\n    # find the max dimensions, so we can know the bounding box, getting the height,\n    # width, length (because these are the step size)...\n    def find_mins_maxs(obj):\n        minx = maxx = miny = maxy = minz = maxz = None\n        for p in obj.points:\n            # p contains (x, y, z)\n            if minx is None:\n                minx = p[stl.Dimension.X]\n                maxx = p[stl.Dimension.X]\n                miny = p[stl.Dimension.Y]\n                maxy = p[stl.Dimension.Y]\n                minz = p[stl.Dimension.Z]\n                maxz = p[stl.Dimension.Z]\n            else:\n                maxx = max(p[stl.Dimension.X], maxx)\n                minx = min(p[stl.Dimension.X], minx)\n                maxy = max(p[stl.Dimension.Y], maxy)\n                miny = min(p[stl.Dimension.Y], miny)\n                maxz = max(p[stl.Dimension.Z], maxz)\n                minz = min(p[stl.Dimension.Z], minz)\n        return minx, maxx, miny, maxy, minz, maxz\n\n\n    def translate(_solid, step, padding, multiplier, axis):\n        if 'x' == axis:\n            items = 0, 3, 6\n        elif 'y' == axis:\n            items = 1, 4, 7\n        elif 'z' == axis:\n            items = 2, 5, 8\n        else:\n            raise RuntimeError('Unknown axis %r, expected x, y or z' % axis)\n\n        # _solid.points.shape == [:, ((x, y, z), (x, y, z), (x, y, z))]\n        _solid.points[:, items] += (step * multiplier) + (padding * multiplier)\n\n\n    def copy_obj(obj, dims, num_rows, num_cols, num_layers):\n        w, l, h = dims\n        copies = []\n        for layer in range(num_layers):\n            for row in range(num_rows):\n                for col in range(num_cols):\n                    # skip the position where original being copied is\n                    if row == 0 and col == 0 and layer == 0:\n                        continue\n                    _copy = mesh.Mesh(obj.data.copy())\n                    # pad the space between objects by 10% of the dimension being\n                    # translated\n                    if col != 0:\n                        translate(_copy, w, w / 10., col, 'x')\n                    if row != 0:\n                        translate(_copy, l, l / 10., row, 'y')\n                    if layer != 0:\n                        translate(_copy, h, h / 10., layer, 'z')\n                    copies.append(_copy)\n        return copies\n\n    # 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