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- Found and fixed some bugs.
- Added a legend. - Added a label attribute to each plot for the legend. - Added some more tests. - Trying to clean up the mess that is all the internals. - Added cmaps. - Promoted some parameters to properties so they can be modified after inital plot. - Moved around some scalar stuff to try and make the API more consistent.
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‎docs/source/Extras.rst‎

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@@ -8,18 +8,24 @@ vtkplotlib.zip_axes
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.. autofunction:: vtkplotlib.nuts_and_bolts.zip_axes
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---------------------
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vtkplotlib.unzip_axes
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---------------------
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.. autofunction:: vtkplotlib.nuts_and_bolts.unzip_axes
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---------------------
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vtkplotlib.TextureMap
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---------------------
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.. autoclass:: vtkplotlib.colors.TextureMap
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--------------------------
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vtkplotlib.quick_test_plot
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--------------------------
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‎docs/source/Figures.rst‎

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shown figure is closed the current working figure is deleted.
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---------------
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vtkplotlib.show
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---------------
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.. autofunction:: vtkplotlib.figures.figure_manager.show
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-----------------
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vtkplotlib.figure
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-----------------
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.. autoclass:: vtkplotlib.figures.figure.Figure
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--------------
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vtkplotlib.gcf
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--------------
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.. autofunction:: vtkplotlib.figures.figure_manager.gcf
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--------------
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vtkplotlib.scf
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--------------
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.. autofunction:: vtkplotlib.figures.figure_manager.scf
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-----------------------
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vtkplotlib.reset_camera
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.. autofunction:: vtkplotlib.figures.figure_manager.reset_camera
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-------------------
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vtkplotlib.save_fig
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-------------------
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.. autofunction:: vtkplotlib.figures.figure_manager.save_fig
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---------------
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vtkplotlib.view
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---------------
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.. autofunction:: vtkplotlib.figures.figure_manager.view
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----------------
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vtkplotlib.close
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.. autofunction:: vtkplotlib.figures.figure_manager.close
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-------------------------
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vtkplotlib.figure_history
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.. autodata:: vtkplotlib._history.figure_history
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----------------------
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vtkplotlib.auto_figure
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----------------------
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.. autofunction:: vtkplotlib.figures.figure_manager.auto_figure
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-------------------
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vtkplotlib.QtFigure
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.. autoclass:: vtkplotlib.figures.QtFigure.QtFigure
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--------------------
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vtkplotlib.QtFigure2
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‎docs/source/Plots.rst‎

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================
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vtkplotlib.scatter
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------------------
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.. autofunction:: vtkplotlib.plots.Scatter.scatter
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---------------
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vtkplotlib.plot
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---------------
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.. autoclass:: vtkplotlib.plots.Lines.Lines
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--------------------
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vtkplotlib.mesh_plot
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.. autoclass:: vtkplotlib.plots.MeshPlot.MeshPlot
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--------------------------------------
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vtkplotlib.mesh_plot_with_edge_scalars
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--------------------------------------
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.. autofunction:: vtkplotlib.plots.MeshPlot.mesh_plot_with_edge_scalars
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------------------
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vtkplotlib.polygon
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.. autoclass:: vtkplotlib.plots.Polygon.Polygon
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---------------------
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vtkplotlib.scalar_bar
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.. autoclass:: vtkplotlib.plots.ScalarBar.ScalarBar
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----------------
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vtkplotlib.arrow
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.. autofunction:: vtkplotlib.plots.Arrow.arrow
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-----------------
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vtkplotlib.quiver
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---------------
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vtkplotlib.text
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.. autoclass:: vtkplotlib.plots.Text.Text
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-----------------
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vtkplotlib.text3d
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.. autoclass:: vtkplotlib.plots.Text3D.Text3D
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-------------------
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vtkplotlib.annotate
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.. autofunction:: vtkplotlib.plots.Text3D.annotate
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------------------
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vtkplotlib.surface
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.. autoclass:: vtkplotlib.plots.Surface.Surface
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-------------------
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vtkplotlib.PolyData
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vtkplotlib.legend
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.. autoclass:: vtkplotlib.plots.Legend.Legend

‎docs/source/quickstart.rst‎

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A simple library to make 3D graphics using easy. Built on top of VTK. Whilst
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VTK is a very versatile library, it still only has a rather low level API. Even the
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simplest examples require the construction and linking of a large number of
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complicated internal components. This and other factors make writing in it slow
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and painful. This library seeks to overcome that by wrapping the all ugliness
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into numpy friendly functions to create a 3D equivalent of matplotlib. All the
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VTK components/functionality are still accessible but by default are already
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setup for you.
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VTK is a very versatile library, the learning curve is steep and writing in it
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is slow and painful. This library seeks to overcome that by wrapping the all
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ugliness into numpy friendly functions to create a 3D equivalent of matplotlib.
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All the VTK components/functionality are still accessible but by default are
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already setup for you.
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Key features
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------------
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- `vtk`_
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- `future`_
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There is no VTK version for Windows users with python 2.7 on PyPi. But you can
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get a .whl from `here <https://www.lfd.uci.edu/~gohlke/pythonlibs/#vtk>`_.
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It can take VTK a few weeks to release to PyPi for a new Python version so
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using the absolute latest Python is not recomended. There is no VTK version for
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Windows users with python 2.7 on PyPi. But you can get a .whl from
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`here <https://www.lfd.uci.edu/~gohlke/pythonlibs/#vtk>`_.
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‎setup.py‎

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long_description = fh.read()
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setup(name='vtkplotlib',
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version='1.1.3',
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version='1.2.0',
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description='High level 3D graphics and plotting',
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long_description=long_description,
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long_description_content_type="text/markdown",
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# ('models', ['data/models/*'])],
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include_package_data=True,
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install_requires=[
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"vtk<8.2.0",
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"vtk",
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"numpy",
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"pathlib2",
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"matplotlib",

‎vtkplotlib/__init__.py‎

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from .plots.Surface import Surface as surface
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from .plots.Text import Text as text
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from .plots.Text3D import Text3D as text3d, annotate
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from .plots.Legend import Legend
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from .plots.Legend import Legend as legend
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from .plots import BasePlot
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‎vtkplotlib/colors.py‎

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converted_cmaps = {}
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temp = []
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def vtk_cmap(cmap):
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if isinstance(cmap, str):
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def as_vtk_cmap(cmap, cache=True):
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if cache and isinstance(cmap, str):
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if cmap in converted_cmaps:
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return converted_cmaps[cmap]
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cmap = cm.get_cmap(cmap)
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if isinstance(cmap, vtk.vtkLookupTable):
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return cmap
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if isinstance(cmap, (colors.ListedColormap, colors.LinearSegmentedColormap)):
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if cache and isinstance(cmap, (colors.ListedColormap, colors.LinearSegmentedColormap)):
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name = cmap.name
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table.SetTable(numpy_to_vtk(cmap))
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temp.append(cmap)
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# if name is not None:
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# converted_cmaps[name] = table
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if name is not None:
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converted_cmaps[name] = table
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else:
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raise ValueError()
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raise ValueError("`cmap` should have shape (n, 3) or (n, 4). Received {}.".format(cmap.shape))
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if __name__ == "__main__":
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import vtkplotlib as vpl
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for args in [((.3, .4, .6), .2),
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([5, 8, 10], None),
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("red", ),
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("orange red", .5),
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("Orange_Red", ),
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("or33ange_rEd", ),
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]:
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print("process_color", args, "->", process_color(*args), "\n")
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path = Path('C:/Users/Brénainn/Downloads/3dm/duck/Bird_v1_L2.123ca5dbb1bc-8ef6-44e4-b558-3e6e2bbc7dd7/12248_Bird_v1_diff.jpg')
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self = TextureMap(path)
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self.interpolate = True
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n = 1000
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t = np.linspace(0, 1, n)
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uv = vpl.nuts_and_bolts.zip_axes(*np.meshgrid(t, t))
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# plt.figure(figsize=(n // 72,) * 2)
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# plt.imshow(self(uv))
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# plt.show()
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from PIL import Image
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im = Image.fromarray((self(uv) * 255).astype(np.uint8))
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#if __name__ == "__main__":
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# import vtkplotlib as vpl
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# for args in [((.3, .4, .6), .2),
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# ([5, 8, 10], None),
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# ("red", ),
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# ("orange red", .5),
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# ("Orange_Red", ),
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# ("or33ange_rEd", ),
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# ]:
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# print("process_color", args, "->", process_color(*args), "\n")
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#
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# path = Path('C:/Users/Brénainn/Downloads/3dm/duck/Bird_v1_L2.123ca5dbb1bc-8ef6-44e4-b558-3e6e2bbc7dd7/12248_Bird_v1_diff.jpg')
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#
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# self = TextureMap(path)
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# self.interpolate = True
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#
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# n = 1000
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# t = np.linspace(0, 1, n)
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# uv = vpl.nuts_and_bolts.zip_axes(*np.meshgrid(t, t))
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#
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## plt.figure(figsize=(n // 72,) * 2)
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## plt.imshow(self(uv))
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## plt.show()
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#
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# from PIL import Image
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# im = Image.fromarray((self(uv) * 255).astype(np.uint8))
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# im.show()
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# cmap = plt.get_cmap("Blues")

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