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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_additional_cmap.py:


=================================
Get additional color palettes
=================================

I created a class called `CommunityPalette` for accessing those pretty color palettes that are widely seen in oceanography but not directly available in Python.
This can be from Ocean Data View (ODV), NCL, Ferret, etc.

In this example, I will show these available color palettes in the `CommunityPalette` class.
But the majority of them is from Ferret (Thank the Ferret community for making this open sourced), which
can be found in https://ferret.pmel.noaa.gov/Ferret/faq/ferret-color-palettes

.. GENERATED FROM PYTHON SOURCE LINES 13-45



.. image-sg:: /auto_examples/images/sphx_glr_plot_additional_cmap_001.png
   :alt: scientific_batlow, scientific_imola, my_rainbow2, kovesi_rainbow, cspace_BlRd, BlGrYeOrReVi, Section, WtBuGnYlRd, my_rainbow, colorcet_r_bgyr, scientific_vik, scientific_bam, ukiyoe, scientific_cork, BuGd, tol_rainbow, BuGr, r_terrain, Zissou1, parula, ODV, w5m4
   :srcset: /auto_examples/images/sphx_glr_plot_additional_cmap_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import numpy as np
    import matplotlib.pyplot as plt
    from cgeniepy.plot import CommunityPalette

    def plot_colormaps(cmaps):
        ncols = 4
        nrows = int(np.ceil(len(cmaps) / ncols))
        fig, axes = plt.subplots(nrows, ncols, figsize=(15, nrows))

        for i, cmap_name in enumerate(cmaps):
            row = i // ncols
            col = i % ncols
            ax = axes[row, col] if nrows > 1 else axes[col]

            # Create a gradient image using the colormap
            gradient = np.linspace(0, 1, 256).reshape(1, -1)
            ax.imshow(gradient, aspect='auto', cmap=CommunityPalette().get_palette(cmap_name))
            ax.set_title(cmap_name, fontsize=14, fontweight='bold')
            ax.axis('off')

        ## remove the unused axes
        for i in range(len(cmaps), ncols * nrows):
            row = i // ncols
            col = i % ncols
            fig.delaxes(axes[row, col])

        plt.tight_layout()

    # List of colormaps from cgeniepy
    cmaps_list = CommunityPalette().avail_palettes(show_ferret_data=False)
    plot_colormaps(cmaps_list)


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

   **Total running time of the script:** (0 minutes 0.446 seconds)


.. _sphx_glr_download_auto_examples_plot_additional_cmap.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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