.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/plotting/color_scatter_plots.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_plotting_color_scatter_plots.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_plotting_color_scatter_plots.py:


===================
Color scatter plots
===================

This example shows different ways to color vectors and (mis)orientations in scatter
plots.

.. GENERATED FROM PYTHON SOURCE LINES 27-40

.. code-block:: Python


    import matplotlib as mpl
    import matplotlib.pyplot as plt
    import numpy as np

    from orix.plot import register_projections
    from orix.quaternion import Orientation
    from orix.quaternion.symmetry import Oh
    from orix.vector import Vector3d

    register_projections()  # Register our custom Matplotlib projections
    np.random.seed(2319)  # Create reproducible random data








.. GENERATED FROM PYTHON SOURCE LINES 41-47

Create some random vectors and plot them in the stereographic projection, coloring by:

- Scalar values mapped to a Matplotlib color map
- Pre-computed RGBA colormapping from a Matplotlib color map
- RGB values
- A single color

.. GENERATED FROM PYTHON SOURCE LINES 47-73

.. code-block:: Python

    v = Vector3d.random(50)

    c_scalar = np.linspace(0, 1, v.size)
    c_rgba = mpl.colormaps["viridis"](c_scalar)
    c_rgb = np.random.random(v.size * 3).reshape(v.size, 3)
    c_color = "xkcd:salmon"

    n = 4
    fig = plt.figure(figsize=(n * 3, n), layout="constrained")

    ax0 = fig.add_subplot(1, n, 1, projection="stereographic")
    ax0.scatter(v, c=c_scalar, cmap="inferno")
    ax0.set_title("Scalars mapped to colormap")

    ax1 = fig.add_subplot(1, n, 2, projection="stereographic")
    ax1.scatter(v, c=c_rgba)
    ax1.set_title("Pre-computed RGBA colormap")

    ax2 = fig.add_subplot(1, n, 3, projection="stereographic")
    ax2.scatter(v, c=c_rgb)
    ax2.set_title("Pre-computed RGB values")

    ax3 = fig.add_subplot(1, n, 4, projection="stereographic")
    ax3.scatter(v, c=c_color)
    _ = ax3.set_title("A single color")




.. image-sg:: /examples/plotting/images/sphx_glr_color_scatter_plots_001.png
   :alt: Scalars mapped to colormap, Pre-computed RGBA colormap, Pre-computed RGB values, A single color
   :srcset: /examples/plotting/images/sphx_glr_color_scatter_plots_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 74-75

This also works nicely when coloring (mis)orientations

.. GENERATED FROM PYTHON SOURCE LINES 75-95

.. code-block:: Python

    ori = Orientation.random(50)
    ori.symmetry = Oh

    n = 4
    fig = plt.figure(figsize=(n * 3, n), layout="tight")
    scatter_kwargs = {"projection": "axangle", "figure": fig}

    ori.scatter(c=c_scalar, cmap="inferno", position=(1, n, 1), **scatter_kwargs)
    fig.axes[0].set_title("Scalars mapped to colormap")

    ori.scatter(c=c_rgba, position=(1, n, 2), **scatter_kwargs)
    fig.axes[1].set_title("Pre-computed RGBA colormap")

    ori.scatter(c=c_rgb, position=(1, n, 3), **scatter_kwargs)
    fig.axes[2].set_title("Pre-computed RGB values")

    ori.scatter(c=c_color, position=(1, n, 4), **scatter_kwargs)
    _ = fig.axes[3].set_title("A single color")

    plt.show()



.. image-sg:: /examples/plotting/images/sphx_glr_color_scatter_plots_002.png
   :alt: Scalars mapped to colormap, Pre-computed RGBA colormap, Pre-computed RGB values, A single color
   :srcset: /examples/plotting/images/sphx_glr_color_scatter_plots_002.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 1.478 seconds)

**Estimated memory usage:**  583 MB


.. _sphx_glr_download_examples_plotting_color_scatter_plots.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: color_scatter_plots.ipynb <color_scatter_plots.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: color_scatter_plots.py <color_scatter_plots.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: color_scatter_plots.zip <color_scatter_plots.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_