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Merged revisions 7428-7433 via svnmerge from
https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/v0_99_maint ........ r7428 | jdh2358 | 2009-08-08 02:21:29 -1000 (Sat, 08 Aug 2009) | 1 line clean up mplot3d examples: use pyplot noy pylab and numpy rather than list comps and python random module ........ r7429 | jdh2358 | 2009-08-08 03:53:24 -1000 (Sat, 08 Aug 2009) | 1 line two new examples using a compund path for a histogram; one animated ........ r7430 | jdh2358 | 2009-08-08 03:58:52 -1000 (Sat, 08 Aug 2009) | 1 line two new examples using a compund path for a histogram; one animated ........ r7431 | jdh2358 | 2009-08-08 05:10:08 -1000 (Sat, 08 Aug 2009) | 1 line use a class helper method to make the compound path from polys ........ r7432 | jdh2358 | 2009-08-08 05:16:57 -1000 (Sat, 08 Aug 2009) | 1 line simplify poly array in example ........ r7433 | efiring | 2009-08-08 08:16:01 -1000 (Sat, 08 Aug 2009) | 2 lines Fix excessive line length in annotations.rst ........ svn path=/trunk/matplotlib/; revision=7434
2 parents aa82808 + 52f7369 commit c6156ac

17 files changed

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‎doc/users/annotations.rst‎

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@@ -56,15 +56,18 @@ from the text to the annotated point by giving a dictionary of arrow
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properties in the optional keyword argument ``arrowprops``.
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==================== ===========================================================================
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==================== =====================================================
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``arrowprops`` key description
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==================== ===========================================================================
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==================== =====================================================
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width the width of the arrow in points
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frac the fraction of the arrow length occupied by the head
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headwidth the width of the base of the arrow head in points
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shrink move the tip and base some percent away from the annotated point and text
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\*\*kwargs any key for :class:`matplotlib.patches.Polygon`, eg ``facecolor``
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==================== ===========================================================================
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shrink move the tip and base some percent away from
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the annotated point and text
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\*\*kwargs any key for :class:`matplotlib.patches.Polygon`,
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e.g. ``facecolor``
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==================== =====================================================
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In the example below, the ``xy`` point is in native coordinates
@@ -78,4 +81,7 @@ keyword args like ``horizontalalignment``, ``verticalalignment`` and
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.. plot:: pyplots/annotation_polar.py
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:include-source:
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For more on all the wild and wonderful things you can do with annotations, including fancy arrows, see :ref:`plotting-guide-annotation` and :ref:`pylab_examples-annotation_demo`.
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For more on all the wild and wonderful things you can do with
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annotations, including fancy arrows, see :ref:`plotting-guide-annotation`
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and :ref:`pylab_examples-annotation_demo`.
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‎examples/animation/histogram_tkagg.py‎

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"""
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This example shows how to use a path patch to draw a bunch of
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rectangles for an animated histogram
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"""
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import time
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import numpy as np
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import matplotlib
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matplotlib.use('TkAgg') # do this before importing pylab
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import matplotlib.pyplot as plt
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import matplotlib.patches as patches
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import matplotlib.path as path
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fig = plt.figure()
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ax = fig.add_subplot(111)
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# histogram our data with numpy
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data = np.random.randn(1000)
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n, bins = np.histogram(data, 100)
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# get the corners of the rectangles for the histogram
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left = np.array(bins[:-1])
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right = np.array(bins[1:])
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bottom = np.zeros(len(left))
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top = bottom + n
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nrects = len(left)
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# here comes the tricky part -- we have to set up the vertex and path
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# codes arrays using moveto, lineto and closepoly
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# for each rect: 1 for the MOVETO, 3 for the LINETO, 1 for the
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# CLOSEPOLY; the vert for the closepoly is ignored but we still need
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# it to keep the codes aligned with the vertices
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nverts = nrects*(1+3+1)
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verts = np.zeros((nverts, 2))
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codes = np.ones(nverts, int) * path.Path.LINETO
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codes[0::5] = path.Path.MOVETO
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codes[4::5] = path.Path.CLOSEPOLY
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verts[0::5,0] = left
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verts[0::5,1] = bottom
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verts[1::5,0] = left
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verts[1::5,1] = top
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verts[2::5,0] = right
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verts[2::5,1] = top
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verts[3::5,0] = right
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verts[3::5,1] = bottom
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barpath = path.Path(verts, codes)
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patch = patches.PathPatch(barpath, facecolor='green', edgecolor='yellow', alpha=0.5)
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ax.add_patch(patch)
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ax.set_xlim(left[0], right[-1])
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ax.set_ylim(bottom.min(), top.max())
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def animate():
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if animate.cnt>=100:
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return
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animate.cnt += 1
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# simulate new data coming in
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data = np.random.randn(1000)
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n, bins = np.histogram(data, 100)
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top = bottom + n
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verts[1::5,1] = top
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verts[2::5,1] = top
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fig.canvas.draw()
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fig.canvas.manager.window.after(100, animate)
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animate.cnt = 0
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fig.canvas.manager.window.after(100, animate)
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plt.show()

‎examples/api/histogram_path_demo.py‎

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"""
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This example shows how to use a path patch to draw a bunch of
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rectangles. The technique of using lots of Rectangle instances, or
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the faster method of using PolyCollections, were implemented before we
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had proper paths with moveto/lineto, closepoly etc in mpl. Now that
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we have them, we can draw collections of regularly shaped objects with
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homogeous properties more efficiently with a PathCollection. This
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example makes a histogram -- its more work to set up the vertex arrays
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at the outset, but it should be much faster for large numbers of
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objects
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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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import matplotlib.patches as patches
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import matplotlib.path as path
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fig = plt.figure()
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ax = fig.add_subplot(111)
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# histogram our data with numpy
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data = np.random.randn(1000)
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n, bins = np.histogram(data, 50)
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# get the corners of the rectangles for the histogram
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left = np.array(bins[:-1])
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right = np.array(bins[1:])
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bottom = np.zeros(len(left))
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top = bottom + n
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# we need a (numrects x numsides x 2) numpy array for the path helper
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# function to build a compound path
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XY = np.array([[left,left,right,right], [bottom,top,top,bottom]]).T
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# get the Path object
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barpath = path.Path.make_compound_path_from_polys(XY)
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# make a patch out of it
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patch = patches.PathPatch(barpath, facecolor='blue', edgecolor='gray', alpha=0.8)
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ax.add_patch(patch)
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# update the view limits
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ax.set_xlim(left[0], right[-1])
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ax.set_ylim(bottom.min(), top.max())
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plt.show()

‎examples/mplot3d/2dcollections3d_demo.py‎

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from mpl_toolkits.mplot3d import Axes3D
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import numpy as np
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import pylab
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import matplotlib.pyplot as plt
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fig = pylab.figure()
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fig = plt.figure()
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ax = Axes3D(fig)
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x = np.linspace(0, 1, 100)
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ax.set_ylim3d(0, 1)
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ax.set_zlim3d(0, 1)
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pylab.show()
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plt.show()
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‎examples/mplot3d/bars3d_demo.py‎

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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib.collections import PolyCollection
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from matplotlib.colors import colorConverter
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import pylab
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import random
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import matplotlib.pyplot as plt
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import numpy as np
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fig = pylab.figure()
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fig = plt.figure()
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ax = Axes3D(fig)
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for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):
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xs = np.arange(20)
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ys = [random.random() for x in xs]
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ys = np.random.rand(20)
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ax.bar(xs, ys, zs=z, zdir='y', color=c, alpha=0.8)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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pylab.show()
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plt.show()
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‎examples/mplot3d/contour3d_demo.py‎

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from mpl_toolkits.mplot3d import axes3d
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import pylab
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import random
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import matplotlib.pyplot as plt
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fig = pylab.figure()
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fig = plt.figure()
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ax = axes3d.Axes3D(fig)
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X, Y, Z = axes3d.get_test_data(0.05)
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cset = ax.contour(X, Y, Z)
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ax.clabel(cset, fontsize=9, inline=1)
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pylab.show()
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plt.show()
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‎examples/mplot3d/contour3d_demo2.py‎

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from mpl_toolkits.mplot3d import axes3d
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import pylab
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import random
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import matplotlib.pyplot as plt
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fig = pylab.figure()
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fig = plt.figure()
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ax = axes3d.Axes3D(fig)
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X, Y, Z = axes3d.get_test_data(0.05)
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cset = ax.contour(X, Y, Z, 16, extend3d=True)
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ax.clabel(cset, fontsize=9, inline=1)
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pylab.show()
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plt.show()
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‎examples/mplot3d/contourf3d_demo.py‎

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from mpl_toolkits.mplot3d import axes3d
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import pylab
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import random
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import matplotlib.pyplot as plt
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fig = pylab.figure()
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fig = plt.figure()
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ax = axes3d.Axes3D(fig)
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X, Y, Z = axes3d.get_test_data(0.05)
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cset = ax.contourf(X, Y, Z)
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ax.clabel(cset, fontsize=9, inline=1)
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pylab.show()
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plt.show()
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‎examples/mplot3d/hist3d_demo.py‎

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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib.collections import PolyCollection
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from matplotlib.colors import colorConverter
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import pylab
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import random
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import matplotlib.pyplot as plt
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import numpy as np
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fig = pylab.figure()
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fig = plt.figure()
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ax = Axes3D(fig)
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x = np.random.rand(100) * 4
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y = np.random.rand(100) * 4
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x, y = np.random.rand(2, 100) * 4
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hist, xedges, yedges = np.histogram2d(x, y, bins=4)
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elements = (len(xedges) - 1) * (len(yedges) - 1)
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xpos, ypos = np.meshgrid(
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[xedges[i] + 0.25 for i in range(len(xedges) - 1)],
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[yedges[i] + 0.25 for i in range(len(yedges) - 1)])
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xpos, ypos = np.meshgrid(xedges[:-1]+0.25, yedges[:-1]+0.25)
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xpos = xpos.flatten()
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ypos = ypos.flatten()
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zpos = [0] * elements
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dx = [0.5] * elements
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dy = [0.5] * elements
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zpos = np.zeros(elements)
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dx = 0.5 * np.ones_like(zpos)
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dy = dx.copy()
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dz = hist.flatten()
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ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b')
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pylab.show()
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plt.show()
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‎examples/mplot3d/lines3d_demo.py‎

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import matplotlib as mpl
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from mpl_toolkits.mplot3d import Axes3D
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import numpy as np
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import pylab
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import matplotlib.pyplot as plt
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mpl.rcParams['legend.fontsize'] = 10
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fig = pylab.figure()
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fig = plt.figure()
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ax = Axes3D(fig)
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theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
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z = np.linspace(-2, 2, 100)
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ax.plot(x, y, z, label='parametric curve')
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ax.legend()
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pylab.show()
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plt.show()
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