8000 Merge branch 'plot_directive' of github.com:mdboom/matplotlib into mi… · kaufman/matplotlib@6926044 · GitHub
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Merge branch 'plot_directive' of github.com:mdboom/matplotlib into minor_doc_fixes
Conflicts: lib/matplotlib/sphinxext/plot_directive.py
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‎CHANGELOG

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2011-04-01 The plot directive Sphinx extension now supports all of the
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features in the Numpy fork of that extension. These
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include doctest formatting, an 'include-source' option, and
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a number of new configuration options. - MGD
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2011-03-10 Update pytz version to 2011c, thanks to Simon Cross. - JKS
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2011-03-06 Add standalone tests.py test runner script. - JKS

‎doc/devel/documenting_mpl.rst

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@@ -206,19 +206,6 @@ Figures can be automatically generated from scripts and included in
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the docs. It is not necessary to explicitly save the figure in the
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script, this will be done automatically at build time to ensure that
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the code that is included runs and produces the advertised figure.
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Several figures will be saved with the same basename as the filename
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when the documentation is generated (low and high res PNGs, a PDF).
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Matplotlib includes a Sphinx extension
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(:file:`sphinxext/plot_directive.py`) for generating the images from
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the python script and including either a png copy for html or a pdf
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for latex::
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.. plot:: pyplots/pyplot_simple.py
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:include-source:
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If the script produces multiple figures (through multiple calls to
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:func:`pyplot.figure`), each will be given a numbered file name and
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included.
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The path should be relative to the ``doc`` directory. Any plots
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specific to the documentation should be added to the ``doc/pyplots``
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The ``:scale:`` directive rescales the image to some percentage of the
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original size, though we don't recommend using this in most cases
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since it is probably better to choose the correct figure size and dpi
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in mpl and let it handle the scaling. ``:include-source:`` will
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present the contents of the file, marked up as source code.
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in mpl and let it handle the scaling.
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Plot directive documentation
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''''''''''''''''''''''''''''
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.. automodule:: matplotlib.sphinxext.plot_directive
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Static figures
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--------------

‎doc/users/image_tutorial.rst

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@@ -152,7 +152,7 @@ plot from the prompt.
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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imgplot = plt.imshow(img)
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You can also plot any numpy array - just remember that the datatype
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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plt.imshow(lum_img)
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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imgplot = plt.imshow(lum_img)
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imgplot.set_cmap('hot')
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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imgplot = plt.imshow(lum_img)
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imgplot.set_cmap('spectral')
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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imgplot = plt.imshow(lum_img)
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imgplot.set_cmap('spectral')
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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import numpy as np
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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plt.hist(lum_img.flatten(), 256, range=(0.0,1.0), fc='black', ec='black')
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import numpy as np
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fig = plt.figure()
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a=fig.add_subplot(1,2,1)
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img = mpimg.imread('_static/stinkbug.png')
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img = mpimg.imread('../_static/stinkbug.png')
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lum_img = img[:,:,0]
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imgplot = plt.imshow(lum_img)
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a.set_title('Before')
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import matplotlib.image as mpimg
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import numpy as np
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import Image
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img = Image.open('_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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img = Image.open('../_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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rsize = img.resize((img.size[0]/10,img.size[1]/10)) # resize the image
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rsizeArr = np.asarray(rsize)
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lum_img = rsizeArr[:,:,0]
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import matplotlib.image as mpimg
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import numpy as np
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import Image
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img = Image.open('_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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img = Image.open('../_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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rsize = img.resize((img.size[0]/10,img.size[1]/10)) # resize the image
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rsizeArr = np.asarray(rsize)
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lum_img = rsizeArr[:,:,0]
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import matplotlib.image as mpimg
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import numpy as np
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import Image
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img = Image.open('_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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img = Image.open('../_static/stinkbug.png') # opens the file using PIL - it's not an array yet
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rsize = img.resize((img.size[0]/10,img.size[1]/10)) # resize the image
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rsizeArr = np.asarray(rsize)
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lum_img = rsizeArr[:,:,0]

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