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# $Id: demo.py,v 2.7 2001/01/07 21:35:12 mhagger Exp $
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# Copyright (C) 1999-2001 Michael Haggerty <mhagger@alum.mit.edu>
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version. This program is distributed in
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# the hope that it will be useful, but WITHOUT ANY WARRANTY; without
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# even the implied warranty of MERCHANTABILITY or FITNESS FOR A
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# PARTICULAR PURPOSE. See the GNU General Public License for more
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# details; it is available at <http://www.fsf.org/copyleft/gpl.html>,
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# or by writing to the Free Software Foundation, Inc., 59 Temple Place
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# - Suite 330, Boston, MA 02111-1307, USA.
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"""demo.py -- Demonstrate the Gnuplot python module.
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Run this demo by typing 'python demo.py'. For a more complete test of
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the Gnuplot package, see test.py.
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__cvs_version__ = '$Revision: 2.7 $'
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# If the package has been installed correctly, this should work:
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import Gnuplot, Gnuplot.funcutils
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# It may be that the user is just testing out the package by
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# running 'python demo.py' it the package's directory. If that is
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# the case, the following should work:
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Gnuplot.funcutils = funcutils
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"""Demonstrate the Gnuplot package."""
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# A straightforward use of gnuplot. The `debug=1' switch is used
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# in these examples so that the commands that are sent to gnuplot
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# are also output on stderr.
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g = Gnuplot.Gnuplot(debug=1)
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g.title('A simple example') # (optional)
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g('set data style linespoints') # give gnuplot an arbitrary command
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# Plot a list of (x, y) pairs (tuples or a Numeric array would
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g.plot([[0,1.1], [1,5.8], [2,3.3], [3,4.2]])
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raw_input('Please press return to continue...\n')
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# Plot one dataset from an array and one via a gnuplot function;
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# also demonstrate the use of item-specific options:
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x = arange(10, typecode=Float)
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# Notice how this plotitem is created here but used later? This
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# is convenient if the same dataset has to be plotted multiple
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# times. It is also more efficient because the data need only be
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# written to a temporary file once.
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d = Gnuplot.Data(x, y1,
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title='calculated by python',
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g.title('Data can be computed by python or gnuplot')
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# Plot a function alongside the Data PlotItem defined above:
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g.plot(Gnuplot.Func('x**2', title='calculated by gnuplot'), d)
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raw_input('Please press return to continue...\n')
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# Save what we just plotted as a color postscript file.
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# With the enhanced postscript option, it is possible to show `x
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# squared' with a superscript (plus much, much more; see `help set
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# term postscript' in the gnuplot docs). If your gnuplot doesn't
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# support enhanced mode, set `enhanced=0' below.
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g.ylabel('x^2') # take advantage of enhanced postscript mode
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g.hardcopy('gp_test.ps', enhanced=1, color=1)
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print ('\n******** Saved plot to postscript file "gp_test.ps" ********\n')
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raw_input('Please press return to continue...\n')
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# Demonstrate a 3-d plot:
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# set up x and y values at which the function will be tabulated:
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y = arange(30)/10.0 - 1.5
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# Make a 2-d array containing a function of x and y. First create
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# xm and ym which contain the x and y values in a matrix form that
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# can be `broadcast' into a matrix of the appropriate shape:
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m = (sin(xm) + 0.1*xm) - ym**2
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g('set data style lines')
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g('set contour base')
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g.title('An example of a surface plot')
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# The `binary=1' option would cause communication with gnuplot to
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# be in binary format, which is considerably faster and uses less
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# disk space. (This only works with the splot command due to
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# limitations of gnuplot.) `binary=1' is the default, but here we
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# disable binary because older versions of gnuplot don't allow
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# binary data. Change this to `binary=1' (or omit the binary
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# option) to get the advantage of binary format.
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g.splot(Gnuplot.GridData(m,x,y, binary=0))
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raw_input('Please press return to continue...\n')
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# plot another function, but letting GridFunc tabulate its values
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# automatically. f could also be a lambda or a global function:
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return 1.0 / (1 + 0.01 * x**2 + 0.5 * y**2)
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g.splot(Gnuplot.funcutils.compute_GridData(x,y, f, binary=0))
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raw_input('Please press return to continue...\n')
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# Explicit delete shouldn't be necessary, but if you are having
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# trouble with temporary files being left behind, try uncommenting
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# when executed, just run demo():
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if __name__ == '__main__':
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build/lib/Gnuplot/demo.py
