[Scipy-svn] r3703 - trunk/scipy/interpolate/tests

[scipy-svn at scipy.org]

Author: jarrod.millman
Date: 2007-12-24 03:19:59 -0600 (Mon, 24 Dec 2007)
New Revision: 3703

Removed:
   trunk/scipy/interpolate/tests/demos_xplt.py
Log:
removing code depending on xplt


Deleted: trunk/scipy/interpolate/tests/demos_xplt.py
===================================================================
--- trunk/scipy/interpolate/tests/demos_xplt.py	2007-12-24 06:41:28 UTC (rev 3702)
+++ trunk/scipy/interpolate/tests/demos_xplt.py	2007-12-24 09:19:59 UTC (rev 3703)
@@ -1,54 +0,0 @@
-#!/usr/bin/env python
-# Created by Pearu Peterson, Aug 2003
-""" Test xplt based demos for interpolate.fitpack2 module
-"""
-__usage__ = """
-Build interpolate:
-  python setup_interpolate.py build
-Run demos (assumes that scipy is installed):
-  python -i tests/demos_xplt.py
-"""
-
-import sys
-from numpy.test.testing import set_package_path
-set_package_path()
-from interpolate.fitpack2 import UnivariateSpline,LSQUnivariateSpline,\
-     InterpolatedUnivariateSpline
-from interpolate.fitpack2 import LSQBivariateSpline, SmoothBivariateSpline
-del sys.path[0]
-
-from scipy import *
-
-def demo1():
-    x = arange(0,2*pi+pi/4,2*pi/8)
-    xnew = arange(-pi/10,2*pi+pi/4+pi/10,pi/50)
-    y = sin(x)
-
-
-    def make_plot():
-        xplt.plot(x,y,'x',xnew,spline(xnew),x,y,'b',xnew,sin(xnew),
-                  spline.get_knots(),spline(spline.get_knots()),'o')
-
-    spline = UnivariateSpline(x,y,k=1)
-    assert isinstance(spline,LSQUnivariateSpline)
-    print 'Linear LSQ approximation of sin(x):',spline.__class__.__name__
-    make_plot()
-    print 'Residual=',spline.get_residual()
-    raw_input('Press any key to continue..')
-
-    spline.set_smoothing_factor(0)
-    assert isinstance(spline,InterpolatedUnivariateSpline)
-    print 'Linear interpolation of sin(x):',spline.__class__.__name__
-    make_plot()
-    print 'Residual=',spline.get_residual()
-    raw_input('Press any key to continue..')
-
-    spline = UnivariateSpline(x,y,k=1,s=0.1)
-    print 'Linear smooth approximation of sin(x):',spline.__class__.__name__
-    assert isinstance(spline,UnivariateSpline)
-    make_plot()
-    print 'Residual=',spline.get_residual()
-    raw_input('Press any key to continue..')
-
-if __name__ == "__main__":
-    demo1()