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Merge pull request #11191 from ImportanceOfBeingErnest/example-refs_imgscntrs
DOC: Adding example references for Images,contours,fields section
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‎examples/images_contours_and_fields/affine_image.py

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Affine transform of an image
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============================
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Prepending an affine transformation (:class:`~.transforms.Affine2D`)
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to the :ref:`data transform <data-coords>`
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of an image allows to manipulate the image's shape and orientation.
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This is an example of the concept of
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:ref:`transform chaining <transformation-pipeline>`.
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For the backends that support draw_image with optional affine
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transform (e.g., agg, ps backend), the image of the output should
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have its boundary match the dashed yellow rectangle.
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rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.imshow
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matplotlib.pyplot.imshow
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matplotlib.transforms.Affine2D

‎examples/images_contours_and_fields/barb_demo.py

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ax2.barbs(data['x'], data['y'], masked_u, data['v'], length=8, pivot='middle')
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.barbs
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matplotlib.pyplot.barbs
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‎examples/images_contours_and_fields/barcode_demo.py

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Barcode Demo
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============
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This demo shows how to produce a one-dimensional image, or "bar code".
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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fig = plt.figure()
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# a vertical barcode -- this is broken at present
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# a vertical barcode
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ax1 = fig.add_axes([0.1, 0.3, 0.1, 0.6], **axprops)
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ax1.imshow(x.reshape((-1, 1)), **barprops)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.imshow
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matplotlib.pyplot.imshow

‎examples/images_contours_and_fields/contour_corner_mask.py

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Contour Corner Mask
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===================
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Illustrate the difference between corner_mask=False and corner_mask=True
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for masked contour plots.
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Illustrate the difference between ``corner_mask=False`` and
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``corner_mask=True`` for masked contour plots.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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ax.plot(np.ma.array(x, mask=~mask), y, 'ro')
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions and methods is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.axes.Axes.contourf
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matplotlib.pyplot.contourf

‎examples/images_contours_and_fields/contour_demo.py

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Illustrate simple contour plotting, contours on an image with
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a colorbar for the contours, and labelled contours.
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See also contour_image.py.
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See also the
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:ref:`contour image example
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<sphx_glr_gallery_images_contours_and_fields_contour_image.py>`.
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"""
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import matplotlib
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import numpy as np
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import matplotlib.cm as cm
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import matplotlib.pyplot as plt
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matplotlib.rcParams['xtick.direction'] = 'out'
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matplotlib.rcParams['ytick.direction'] = 'out'
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delta = 0.025
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x = np.arange(-3.0, 3.0, delta)
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CB.ax.set_position([ll, b + 0.1*h, ww, h*0.8])
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions and methods is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.axes.Axes.clabel
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matplotlib.pyplot.clabel
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matplotlib.axes.Axes.set_position
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matplotlib.axes.Axes.get_position

‎examples/images_contours_and_fields/contour_image.py

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=============
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Test combinations of contouring, filled contouring, and image plotting.
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For contour labelling, see contour_demo.py.
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For contour labelling, see See also the
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:ref:`contour demo example
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<sphx_glr_gallery_images_contours_and_fields_contour_demo.py>`.
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The emphasis in this demo is on showing how to make contours register
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correctly on images, and on how to get both of them oriented as
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desired. In particular, note the usage of the "origin" and "extent"
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desired. In particular, note the usage of the
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:ref:`"origin" and "extent"
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<sphx_glr_tutorials_intermediate_imshow_extent.py>`
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keyword arguments to imshow and contour.
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"""
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import matplotlib.pyplot as plt
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fig.tight_layout()
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.axes.Axes.imshow
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matplotlib.pyplot.imshow
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.colors.Normalize

‎examples/images_contours_and_fields/contour_label_demo.py

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Illustrate some of the more advanced things that one can do with
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contour labels.
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See also contour_demo.py.
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See also the :ref:`contour demo example
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<sphx_glr_gallery_images_contours_and_fields_contour_demo.py>`.
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"""
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import matplotlib
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import matplotlib.ticker as ticker
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import matplotlib.pyplot as plt
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matplotlib.rcParams['xtick.direction'] = 'out'
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matplotlib.rcParams['ytick.direction'] = 'out'
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###############################################################################
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# Define our surface
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ax2.set_title("$100^Z$")
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.axes.Axes.clabel
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matplotlib.pyplot.clabel
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matplotlib.ticker.LogFormatterMathtext
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matplotlib.ticker.TickHelper.create_dummy_axis

‎examples/images_contours_and_fields/contourf_demo.py

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Contourf Demo
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=============
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How to use the ``contourf`` function to create filled contour plots.
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How to use the :meth:`.axes.Axes.contourf` method to create filled contour plots.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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ax.locator_params(nbins=4)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.axes.Axes.contourf
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matplotlib.pyplot.contourf
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matplotlib.axes.Axes.clabel
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matplotlib.pyplot.clabel
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.colors.Colormap
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matplotlib.colors.Colormap.set_bad
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matplotlib.colors.Colormap.set_under
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matplotlib.colors.Colormap.set_over

‎examples/images_contours_and_fields/contourf_hatching.py

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artists, labels = cs.legend_elements()
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ax2.legend(artists, labels, handleheight=2)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contour
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matplotlib.pyplot.contour
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matplotlib.axes.Axes.contourf
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matplotlib.pyplot.contourf
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.axes.Axes.legend
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matplotlib.pyplot.legend
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matplotlib.contour.ContourSet
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matplotlib.contour.ContourSet.legend_elements

‎examples/images_contours_and_fields/contourf_log.py

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cbar = fig.colorbar(cs)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.contourf
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matplotlib.pyplot.contourf
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.axes.Axes.legend
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matplotlib.pyplot.legend
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matplotlib.ticker.LogLocator

‎examples/images_contours_and_fields/custom_cmap.py

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Creating a colormap from a list of colors
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=========================================
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Creating a colormap from a list of colors can be done with the `from_list`
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method of `LinearSegmentedColormap`. You must pass a list of RGB tuples that
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define the mixture of colors from 0 to 1.
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Creating a :ref:`colormap <sphx_glr_tutorials_colors_colormaps.py>`
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from a list of colors can be done with the
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:meth:`~.colors.LinearSegmentedColormap.from_list` method of
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`LinearSegmentedColormap`. You must pass a list of RGB tuples that define the
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mixture of colors from 0 to 1.
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Creating custom colormaps
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fig.subplots_adjust(top=0.9)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods, classes and modules is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.imshow
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matplotlib.pyplot.imshow
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matplotlib.figure.Figure.colorbar
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matplotlib.pyplot.colorbar
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matplotlib.colors
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matplotlib.colors.LinearSegmentedColormap
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matplotlib.colors.LinearSegmentedColormap.from_list
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matplotlib.cm
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matplotlib.cm.ScalarMappable.set_cmap
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matplotlib.pyplot.register_cmap
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matplotlib.cm.register_cmap

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