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Updated the importation of numpy.ma; numerix.npyma is obsolete.
svn path=/trunk/matplotlib/; revision=5008
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‎CHANGELOG‎

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2008-03-14 Removed an apparently unnecessary call to
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FigureCanvasAgg.draw in backend_qt*agg. Thanks to Ted
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Drain - DSD
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2008-03-19 Changed ma import statements to "from numpy import ma";
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this should work with past and future versions of
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numpy, whereas "import numpy.ma as ma" will work only
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with numpy >= 1.05, and "import numerix.npyma as ma"
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is obsolete now that maskedarray is replacing the
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earlier implementation, as of numpy 1.05.
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2008-03-14 Removed an apparently unnecessary call to
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FigureCanvasAgg.draw in backend_qt*agg. Thanks to Ted
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Drain - DSD
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2008-03-10 Workaround a bug in backend_qt4agg's blitting due to a
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buffer width/bbox width mismatch in _backend_agg's

‎CODING_GUIDE‎

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# checking out the main src
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svn co https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/trunk/matplotlib matplotlib --username=youruser --password=yourpass
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# branch checkouts, eg the transforms branch
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# branch checkouts, eg the transforms branch
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svn co https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/transforms transbranch
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== Committing changes ==
@@ -47,15 +47,18 @@ For numpy, use:
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import numpy as npy
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a = npy.array([1,2,3])
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For masked arrays, use:
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import matplotlib.numerix.npyma as ma
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from numpy import ma
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(This is needed to support the maskedarray module as an
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alternative to the original numpy ma module; eventually,
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the maskedarray implementation is likely to replace the
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ma implementation.)
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(The earlier recommendation, 'import matplotlib.numerix.npyma as ma',
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was needed temporarily during the development of the maskedarray
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implementation as a separate package. As of numpy 1.05, it
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replaces the old implementation.
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Note: "from numpy import ma" works with numpy < 1.05 *and* with
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numpy >= 1.05. "import numpy.ma as ma" works *only* with
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numpy >= 1.05, so for now we must not use it.)
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For matplotlib main module, use:
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For matplotlib modules (or any other modules), use:
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import matplotlib.cbook as cbook
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import matplotlib.cbook as cbook
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if cbook.iterable(z):
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pass
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(add-hook 'python-mode-hook
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(lambda ()
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(add-hook 'local-write-file-hooks 'delete-trailing-whitespace)))
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(add-hook 'local-write-file-hooks 'delete-trailing-whitespace)))
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‎examples/color_by_yvalue.py‎

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# use masked arrays to plot a line with different colors by y-value
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import matplotlib.numerix.npyma as ma
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from numpy import logical_or, arange, sin, pi
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from numpy import ma
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from matplotlib.pyplot import plot, show
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t = arange(0.0, 2.0, 0.01)

‎examples/contourf_demo.py‎

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#!/usr/bin/env python
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from pylab import *
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import matplotlib.numerix.npyma as ma
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origin = 'lower'
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#origin = 'upper'
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‎examples/dynamic_collection.py‎

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facecolors = [cm.jet(0.5)]
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collection = RegularPolyCollection(
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fig.dpi,
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numsides=5, # a pentagon
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#fig.dpi,
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5, # a pentagon
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rotation=0,
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sizes=(50,),
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facecolors = facecolors,

‎examples/image_masked.py‎

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'''
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from pylab import *
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import matplotlib.numerix.npyma as ma
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from numpy import ma
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import matplotlib.colors as colors
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delta = 0.025

‎examples/masked_demo.py‎

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break the line at the data gaps.
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'''
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import matplotlib.numerix.npyma as ma
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from pylab import *
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x = ma.arange(0, 2*pi, 0.02)

‎examples/quadmesh_demo.py‎

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import numpy as npy
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from matplotlib.pyplot import figure, show, savefig
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from matplotlib import cm, colors
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from matplotlib.numerix import npyma as ma
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from numpy import ma
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n = 56
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x = npy.linspace(-1.5,1.5,n)

‎examples/scatter_masked.py‎

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#!/usr/bin/env python
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from pylab import *
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import matplotlib.numerix.npyma as ma
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N = 100
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r0 = 0.6

‎examples/step_demo.py‎

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import numpy as npy
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from matplotlib.numerix import npyma as ma
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from numpy import ma
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from matplotlib.pyplot import step, legend, xlim, ylim, show
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x = npy.arange(1, 7, 0.4)

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