
.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/userdemo/colormap_normalizations.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.py>`
        to download the full example code

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

.. _sphx_glr_gallery_userdemo_colormap_normalizations.py:


=======================
Colormap Normalizations
=======================

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

.. GENERATED FROM PYTHON SOURCE LINES 8-13

.. code-block:: default


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








.. GENERATED FROM PYTHON SOURCE LINES 14-16

Lognorm: Instead of pcolor log10(Z1) you can have colorbars that have
the exponential labels using a norm.

.. GENERATED FROM PYTHON SOURCE LINES 16-39

.. code-block:: default


    N = 100
    X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]

    # A low hump with a spike coming out of the top.  Needs to have
    # z/colour axis on a log scale so we see both hump and spike.  linear
    # scale only shows the spike.

    Z1 = np.exp(-X**2 - Y**2)
    Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
    Z = Z1 + 50 * Z2

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

    pcm = ax[0].pcolor(X, Y, Z,
                       norm=colors.LogNorm(vmin=Z.min(), vmax=Z.max()),
                       cmap='PuBu_r')
    fig.colorbar(pcm, ax=ax[0], extend='max')

    pcm = ax[1].pcolor(X, Y, Z, cmap='PuBu_r')
    fig.colorbar(pcm, ax=ax[1], extend='max')





.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_001.png
    :alt: colormap normalizations
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.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].pcolor(X, Y, Z,
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:35: 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].pcolor(X, Y, Z, cmap='PuBu_r')

    <matplotlib.colorbar.Colorbar object at 0x7f73b4910d00>



.. GENERATED FROM PYTHON SOURCE LINES 40-42

PowerNorm: Here a power-law trend in X partially obscures a rectified
sine wave in Y. We can remove the power law using a PowerNorm.

.. GENERATED FROM PYTHON SOURCE LINES 42-55

.. code-block:: default


    X, Y = np.mgrid[0:3:complex(0, N), 0:2:complex(0, N)]
    Z1 = (1 + np.sin(Y * 10.)) * X**2

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

    pcm = ax[0].pcolormesh(X, Y, Z1, norm=colors.PowerNorm(gamma=1. / 2.),
                           cmap='PuBu_r')
    fig.colorbar(pcm, ax=ax[0], extend='max')

    pcm = ax[1].pcolormesh(X, Y, Z1, cmap='PuBu_r')
    fig.colorbar(pcm, ax=ax[1], extend='max')




.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_002.png
    :alt: colormap normalizations
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:48: 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, Z1, norm=colors.PowerNorm(gamma=1. / 2.),
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:52: 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, Z1, cmap='PuBu_r')

    <matplotlib.colorbar.Colorbar object at 0x7f73b6830490>



.. GENERATED FROM PYTHON SOURCE LINES 56-62

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.

.. GENERATED FROM PYTHON SOURCE LINES 62-80

.. code-block:: default


    X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
    Z1 = 5 * 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, Z1,
                           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, Z1, cmap='RdBu_r', vmin=-np.max(Z1))
    fig.colorbar(pcm, ax=ax[1], extend='both')





.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_003.png
    :alt: colormap normalizations
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:70: 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, Z1,
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:76: 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, Z1, cmap='RdBu_r', vmin=-np.max(Z1))

    <matplotlib.colorbar.Colorbar object at 0x7f73c0089190>



.. GENERATED FROM PYTHON SOURCE LINES 81-84

Custom Norm: An example with a customized normalization.  This one
uses the example above, and normalizes the negative data differently
from the positive.

.. GENERATED FROM PYTHON SOURCE LINES 84-117

.. code-block:: default


    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

    # Example of making your own norm.  Also see matplotlib.colors.
    # From Joe Kington: This one gives two different linear ramps:


    class MidpointNormalize(colors.Normalize):
        def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
            self.midpoint = midpoint
            colors.Normalize.__init__(self, vmin, vmax, clip)

        def __call__(self, value, clip=None):
            # I'm ignoring masked values and all kinds of edge cases to make a
            # simple example...
            x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
            return np.ma.masked_array(np.interp(value, x, y))


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

    pcm = ax[0].pcolormesh(X, Y, Z,
                           norm=MidpointNormalize(midpoint=0.),
                           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')




.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_004.png
    :alt: colormap normalizations
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:109: 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,
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:114: 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))

    <matplotlib.colorbar.Colorbar object at 0x7f73bff0bdc0>



.. GENERATED FROM PYTHON SOURCE LINES 118-121

BoundaryNorm: For this one you provide the boundaries for your colors,
and the Norm puts the first color in between the first pair, the
second color between the second pair, etc.

.. GENERATED FROM PYTHON SOURCE LINES 121-142

.. code-block:: default


    fig, ax = plt.subplots(3, 1, figsize=(8, 8))
    ax = ax.flatten()
    # even bounds gives a contour-like effect
    bounds = np.linspace(-1, 1, 10)
    norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
    pcm = ax[0].pcolormesh(X, Y, Z,
                           norm=norm,
                           cmap='RdBu_r')
    fig.colorbar(pcm, ax=ax[0], extend='both', orientation='vertical')

    # uneven bounds changes the colormapping:
    bounds = np.array([-0.25, -0.125, 0, 0.5, 1])
    norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
    pcm = ax[1].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r')
    fig.colorbar(pcm, ax=ax[1], extend='both', orientation='vertical')

    pcm = ax[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z1))
    fig.colorbar(pcm, ax=ax[2], extend='both', orientation='vertical')

    plt.show()



.. image:: /gallery/userdemo/images/sphx_glr_colormap_normalizations_005.png
    :alt: colormap normalizations
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:127: 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,
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:135: 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, norm=norm, cmap='RdBu_r')
    /build/matplotlib-eAPYn3/matplotlib-3.3.4/examples/userdemo/colormap_normalizations.py:138: 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[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z1))





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

   **Total running time of the script:** ( 0 minutes  5.568 seconds)


.. _sphx_glr_download_gallery_userdemo_colormap_normalizations.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.py <colormap_normalizations.py>`



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

     :download:`Download Jupyter notebook: colormap_normalizations.ipynb <colormap_normalizations.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>`_
