8000 Fix lots of warnings in docs. · matplotlib/matplotlib@2da0657 · GitHub
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Fix lots of warnings in docs.
Fix some examples that crash.
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‎doc/api/api_changes.rst

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@@ -18,7 +18,7 @@ Code changes
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------------
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* A major refactoring of the axes module was made. The axes module has been
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split into smaller modules:
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split into smaller modules:
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- the `_base` module, which contains a new private _AxesBase class. This
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class contains all methods except plotting and labelling methods.
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* As part of the refactoring to enable Qt5 support, the module
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`matplotlib.backends.qt4_compat` was renamed to
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`matplotlib.qt_compat`. `qt4_compat` is deprecated in 1.4 and
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will be removed in 1.5.
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will be removed in 1.5.
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* The :func:`~matplotlib.pyplot.errorbar` method has been changed such that
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the upper and lower limits (*lolims*, *uplims*, *xlolims*, *xuplims*) now
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point to `IPython.sphinxext.ipython_directive` instead of
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`matplotlib.sphinxext.ipython_directive`.
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* In :module:`~matplotlib.finance`, almost all functions have been deprecated and
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replaced with a pair of functions name `*_ochl` and `*_ohlc`. The former is
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'open-close-high-low' order of quotes, and what the module used and the later
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is 'open-high-low-close' order of quotes, which is the standard in finance.
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* In `~matplotlib.finance`, almost all functions have been deprecated
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and replaced with a pair of functions name `*_ochl` and `*_ohlc`.
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The former is 'open-close-high-low' order of quotes, and what the
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module used and the later is 'open-high-low-close' order of quotes,
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which is the standard in finance.
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* For consistency the ``face_alpha`` keyword to
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:class:`matplotlib.patheffects.SimplePatchShadow` has been deprecated in

‎doc/users/whats_new.rst

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@@ -160,7 +160,7 @@ specifically the Skew-T used in meteorology.
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.. plot:: mpl_examples/api/skewt.py
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Support for specifying properties of wedge and text in pie charts.
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``````````````````````````````````````````````````````````````
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``````````````````````````````````````````````````````````````````
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Added the `kwargs` 'wedgeprops' and 'textprops' to :func:`~matplotlib.Axes.pie`
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to accept properties for wedge and text objects in a pie. For example, one can
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specify wedgeprops = {'linewidth':3} to specify the width of the borders of
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Fixed the mouse coordinates giving the wrong theta value in Polar graph
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```````````````````````````````````````````````````````````````````````
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Added code to
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:funct:`~matplotlib.InvertedPolarTransform.transform_non_affine`
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:func:`~matplotlib.InvertedPolarTransform.transform_non_affine`
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to ensure that the calculated theta value was between the range of 0 and 2 * pi
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since the problem was that the value can become negative after applying the
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direction and rotation to the theta calculation.

‎examples/color/named_colors.py

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ncols = 3
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nrows = int(np.ceil(1. * n / ncols))
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fig = plt.figure(figsize=(ncols*5, nrows*4))
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fig = plt.figure(figsize=(ncols*2.5, nrows*2))
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for i, (name, color) in enumerate(sorted_colors):
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ax = fig.add_subplot(nrows, ncols, i + 1)
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ax.text(0.55, 0.5, name, fontsize=12,

‎examples/images_contours_and_fields/interpolation_none_vs_nearest.py

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"""
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Displays the difference between interpolation = 'none' and
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Displays the difference between interpolation = 'none' and
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interpolation = 'nearest'.
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Interpolation = 'none' and interpolation = 'nearest' are equivalent when
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converting a figure to an image file, such as a PNG.
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Interpolation = 'none' and interpolation = 'nearest' behave quite
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differently, however, when converting a figure to a vector graphics file,
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such as a PDF. As shown, Interpolation = 'none' works well when a big
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image is scaled down, while interpolation = 'nearest' works well when a
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Interpolation = 'none' and interpolation = 'nearest' are equivalent when
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converting a figure to an image file, such as a PNG.
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Interpolation = 'none' and interpolation = 'nearest' behave quite
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differently, however, when converting a figure to a vector graphics file,
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such as a PDF. As shown, Interpolation = 'none' works well when a big
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image is scaled down, while interpolation = 'nearest' works well when a
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small image is blown up.
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"""
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fig.text(0.383, 0.90, "Interpolation = 'none'", ha = 'center')
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fig.text(0.75, 0.90, "Interpolation = 'nearest'", ha = 'center')
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#If you were going to run this example on your local machine, you
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#would save the figure as a PNG, save the same figure as a PDF, and
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#If you were going to run this example on your local machine, you
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#would save the figure as a PNG, save the same figure as a PDF, and
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#then compare them. The following code would suffice.
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txt = fig1.text(0.452, 0.95, 'Saved as a PNG', fontsize = 18)
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txt = fig.text(0.452, 0.95, 'Saved as a PNG', fontsize = 18)
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# plt.savefig('None_vs_nearest-png.png')
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# txt.set_text('Saved as a PDF')
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# plt.savefig('None_vs_nearest-pdf.pdf')
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#Here, however, we need to display the PDF on a webpage, which means
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#the PDF must be converted into an image. For the purposes of this
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#example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into
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#the PDF must be converted into an image. For the purposes of this
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#example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into
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#'Nearest_vs_none-pdf.png' at 80 dpi. We simply need to load and
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#display it.
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pdf_im_path = cbook.get_sample_data('None_vs_nearest-pdf.png')

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