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updated goals and what's new
svn path=/trunk/matplotlib/; revision=303
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-10
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-10
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API_CHANGES

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@@ -45,6 +45,8 @@ Using sizes in data coords caused several problems. So you will need
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to adjust your size arguments accordingly or use scatter_classic.
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Object interface - Application programmers
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==========================================
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Makefile

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@@ -2,6 +2,9 @@
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# Copyright (C) 2003 <jdhunter@ace.bsd.uchicago.edu>
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# $Header$
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# $Log$
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# Revision 1.32 2004/05/17 15:08:44 jdh2358
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# updated goals and what's new
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#
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# Revision 1.31 2004/05/04 20:39:16 jdh2358
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# fixed makefile and some text bugs
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#
@@ -123,7 +126,7 @@ pyback:
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htmldocs:
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cp examples/*.py htdocs/examples;\
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cp .matplotlibrc NUMARRAY_ISSUES API_CHANGES htdocs/;\
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cp .matplotlibrc CHANGELOG NUMARRAY_ISSUES API_CHANGES htdocs/;\
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${PYTHON} license.py ${VERSION} htdocs/license.html.template;\
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cd htdocs;\
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${PYTHON} process_docs.py;\

TODO

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@@ -366,4 +366,6 @@
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-- DONE clipping for collections
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-- Todd's nx stuff
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-- Todd's nx stuff
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-- fix object picker and eeg demo

examples/backend_driver.py

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@@ -26,7 +26,7 @@
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'histogram_demo.py',
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'image_demo.py',
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'image_demo2.py',
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# 'image_demo_na.py',
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'image_demo_na.py',
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'invert_axes.py',
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'legend_demo.py',
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'legend_demo2.py',
@@ -77,10 +77,10 @@ def drive(backend):
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os.system('python %s' % tmpfile)
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times = {}
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#backends = ['PS', 'GD', 'Paint', 'Agg', 'Template']
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backends = ['PS', 'GD', 'Paint', 'Agg', 'Template']
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#backends.extend([ 'GTK', 'WX', 'TkAgg'])
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#backends = [ 'PS']
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backends = [ 'Agg', 'PS', 'Template']
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#backends = [ 'Agg']
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#backends = [ 'Agg', 'PS', 'Template']
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for backend in backends:
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print 'testing %s' % backend

examples/finance_demo.py

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@@ -31,8 +31,8 @@
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ax.xaxis.set_major_formatter(weekFormatter)
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#ax.xaxis.set_minor_formatter(dayFormatter)
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plot_day_summary(ax, quotes, ticksize=3, converter=converter)
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#candlestick(ax, quotes, width=0.6, converter=converter)
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#plot_day_summary(ax, quotes, ticksize=3, converter=converter)
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candlestick(ax, quotes, width=0.6, converter=converter)
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show()
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examples/image_demo_na.py

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@@ -16,8 +16,8 @@ def bivariate_normal(X, Y, sigmax=1.0, sigmay=1.0,
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Ymu = Y-muy
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rho = sigmaxy/(sigmax*sigmay)
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z = Xmu**2/sigmax**2 + Ymu**2/sigmay - 2*rho*Xmu*Ymu/(sigmax*sigmay)
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return 1.0/(2*pi*sigmax*sigmay*(1-rho**2)) * exp( -z/(2*(1-rho**2)))
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z = (1.0/sigmax**2)*Xmu**2 + (1.0/sigmay)*Ymu**2 - (2*rho/(sigmax*sigmay))*Xmu*Ymu
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return 1.0/(2*pi*sigmax*sigmay*(1-rho**2)) * exp( -1/(2*(1-rho**2))*z)
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delta = 0.025

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