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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_gallery_userdemo_colormap_normalizations_symlognorm.py>`
        to download the full example code

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

.. _sphx_glr_gallery_userdemo_colormap_normalizations_symlognorm.py:


==================================
Colormap Normalizations Symlognorm
==================================

Demonstration of using norm to map colormaps onto data in non-linear ways.

.. GENERATED FROM PYTHON SOURCE LINES 8-40



.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_symlognorm_001.png
    :alt: colormap normalizations symlognorm
    :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    /root/matplotlib/examples/userdemo/colormap_normalizations_symlognorm.py:30: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.
      pcm = ax[0].pcolormesh(X, Y, Z,
    /root/matplotlib/examples/userdemo/colormap_normalizations_symlognorm.py:36: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.
      pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))






|

.. code-block:: default


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

    """
    SymLogNorm: two humps, one negative and one positive, The positive
    with 5-times the amplitude. Linearly, you cannot see detail in the
    negative hump.  Here we logarithmically scale the positive and
    negative data separately.

    Note that colorbar labels do not come out looking very good.
    """

    N = 100
    X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
    Z1 = np.exp(-X**2 - Y**2)
    Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
    Z = (Z1 - Z2) * 2

    fig, ax = plt.subplots(2, 1)

    pcm = ax[0].pcolormesh(X, Y, Z,
                           norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
                                                  vmin=-1.0, vmax=1.0, base=10),
                           cmap='RdBu_r')
    fig.colorbar(pcm, ax=ax[0], extend='both')

    pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z))
    fig.colorbar(pcm, ax=ax[1], extend='both')

    plt.show()


.. _sphx_glr_download_gallery_userdemo_colormap_normalizations_symlognorm.py:


.. only :: html

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



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

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



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

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


.. only:: html

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

    Keywords: matplotlib code example, codex, python plot, pyplot
    `Gallery generated by Sphinx-Gallery
    <https://sphinx-gallery.readthedocs.io>`_