Delete older ebuild.

(Portage version: 2.2_rc88_p40/cvs/Linux x86_64)

3 files changed, 5 insertions, 525 deletions

diff --git a/dev-python/gnuplot-py/ChangeLog b/dev-python/gnuplot-py/ChangeLog
index bd3ca7657148..d727a194406f 100644
--- a/dev-python/gnuplot-py/ChangeLog
+++ b/dev-python/gnuplot-py/ChangeLog
@@ -1,6 +1,10 @@
 # ChangeLog for dev-python/gnuplot-py
 # Copyright 1999-2010 Gentoo Foundation; Distributed under the GPL v2
-# $Header: /var/cvsroot/gentoo-x86/dev-python/gnuplot-py/ChangeLog,v 1.40 2010/04/30 17:21:04 grobian Exp $
+# $Header: /var/cvsroot/gentoo-x86/dev-python/gnuplot-py/ChangeLog,v 1.41 2010/09/29 21:39:26 arfrever Exp $
+
+  29 Sep 2010; Arfrever Frehtes Taifersar Arahesis <arfrever@gentoo.org>
+  -gnuplot-py-1.7-r2.ebuild, -files/gnuplot-py-1.7-numpy.patch:
+  Delete.
 
   30 Apr 2010; Fabian Groffen <grobian@gentoo.org>
   gnuplot-py-1.8.ebuild:
diff --git a/dev-python/gnuplot-py/files/gnuplot-py-1.7-numpy.patch b/dev-python/gnuplot-py/files/gnuplot-py-1.7-numpy.patch
deleted file mode 100644
index fb25a043d1ff..000000000000
--- a/dev-python/gnuplot-py/files/gnuplot-py-1.7-numpy.patch
+++ /dev/null
@@ -1,489 +0,0 @@
-diff -ur gnuplot-py-1.7/ANNOUNCE.txt gnuplot-py-1.7-numpy/ANNOUNCE.txt
---- gnuplot-py-1.7/ANNOUNCE.txt	2003-10-17 18:03:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/ANNOUNCE.txt	2007-11-20 22:17:29.000000000 +0200
-@@ -9,7 +9,7 @@
- 
- Prerequisites (see footnotes):
-     the Python interpreter [1]
--    the Python Numeric module [3]
-+    the Python numpy module [3]
-     the gnuplot program [2]
- 
- or, to use it under Java (experimental):
-@@ -20,7 +20,7 @@
- 
- Some ways this package can be used:
- 
--1. Interactive data processing: Use Python's excellent Numeric package
-+1. Interactive data processing: Use Python's excellent numpy package
-    to create and manipulate arrays of numbers, and use Gnuplot.py to
-    visualize the results.
- 2. Web graphics: write CGI scripts in Python that use gnuplot to
-diff -ur gnuplot-py-1.7/demo.py gnuplot-py-1.7-numpy/demo.py
---- gnuplot-py-1.7/demo.py	2003-10-17 17:28:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/demo.py	2007-11-20 22:36:59.000000000 +0200
-@@ -16,7 +16,7 @@
- __cvs_version__ = '$Revision: 1.1 $'
- 
- 
--from Numeric import *
-+from numpy import *
- 
- # If the package has been installed correctly, this should work:
- import Gnuplot, Gnuplot.funcutils
-@@ -31,7 +31,7 @@
-     g = Gnuplot.Gnuplot(debug=1)
-     g.title('A simple example') # (optional)
-     g('set data style linespoints') # give gnuplot an arbitrary command
--    # Plot a list of (x, y) pairs (tuples or a Numeric array would
-+    # Plot a list of (x, y) pairs (tuples or a numpy array would
-     # also be OK):
-     g.plot([[0,1.1], [1,5.8], [2,3.3], [3,4.2]])
-     raw_input('Please press return to continue...\n')
-@@ -39,7 +39,7 @@
-     g.reset()
-     # Plot one dataset from an array and one via a gnuplot function;
-     # also demonstrate the use of item-specific options:
--    x = arange(10, typecode=Float)
-+    x = arange(10, dtype='float_')
-     y1 = x**2
-     # Notice how this plotitem is created here but used later?  This
-     # is convenient if the same dataset has to be plotted multiple
-@@ -74,8 +74,8 @@
-     # Make a 2-d array containing a function of x and y.  First create
-     # xm and ym which contain the x and y values in a matrix form that
-     # can be `broadcast' into a matrix of the appropriate shape:
--    xm = x[:,NewAxis]
--    ym = y[NewAxis,:]
-+    xm = x[:,newaxis]
-+    ym = y[newaxis,:]
-     m = (sin(xm) + 0.1*xm) - ym**2
-     g('set parametric')
-     g('set data style lines')
-diff -ur gnuplot-py-1.7/FAQ.txt gnuplot-py-1.7-numpy/FAQ.txt
---- gnuplot-py-1.7/FAQ.txt	2003-10-17 17:28:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/FAQ.txt	2007-11-20 22:17:50.000000000 +0200
-@@ -17,7 +17,7 @@
- #! /usr/bin/python2
- 
- import Gnuplot, Gnuplot.funcutils
--from Numeric import *
-+from numpy import *
- 
- g = Gnuplot.Gnuplot()
- g.plot([[0,1.1], [1,5.8], [2,3.3], [3,4.2]])
-diff -ur gnuplot-py-1.7/funcutils.py gnuplot-py-1.7-numpy/funcutils.py
---- gnuplot-py-1.7/funcutils.py	2003-10-17 17:28:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/funcutils.py	2007-11-20 22:25:24.000000000 +0200
-@@ -16,19 +16,19 @@
- 
- __cvs_version__ = '$Revision: 1.1 $'
- 
--import Numeric
-+import numpy
- 
- import Gnuplot, utils
- 
- 
--def tabulate_function(f, xvals, yvals=None, typecode=None, ufunc=0):
-+def tabulate_function(f, xvals, yvals=None, dtype=None, ufunc=0):
-     """Evaluate and tabulate a function on a 1- or 2-D grid of points.
- 
-     f should be a function taking one or two floating-point
-     parameters.
- 
-     If f takes one parameter, then xvals should be a 1-D array and
--    yvals should be None.  The return value is a Numeric array
-+    yvals should be None.  The return value is a numpy array
-     '[f(x[0]), f(x[1]), ..., f(x[-1])]'.
- 
-     If f takes two parameters, then 'xvals' and 'yvals' should each be
-@@ -39,7 +39,7 @@
- 
-     If 'ufunc=0', then 'f' is evaluated at each point using a Python
-     loop.  This can be slow if the number of points is large.  If
--    speed is an issue, you should write 'f' in terms of Numeric ufuncs
-+    speed is an issue, you should write 'f' in terms of numpy ufuncs
-     and use the 'ufunc=1' feature described next.
- 
-     If called with 'ufunc=1', then 'f' should be a function that is
-@@ -51,34 +51,33 @@
- 
-     if yvals is None:
-         # f is a function of only one variable:
--        xvals = Numeric.asarray(xvals, typecode)
-+        xvals = numpy.asarray(xvals, dtype)
- 
-         if ufunc:
-             return f(xvals)
-         else:
--            if typecode is None:
--                typecode = xvals.typecode()
-+            if dtype is None:
-+                dtype = xvals.dtype.char
- 
--            m = Numeric.zeros((len(xvals),), typecode)
-+            m = numpy.zeros((len(xvals),), dtype)
-             for xi in range(len(xvals)):
-                 x = xvals[xi]
-                 m[xi] = f(x)
-             return m
-     else:
-         # f is a function of two variables:
--        xvals = Numeric.asarray(xvals, typecode)
--        yvals = Numeric.asarray(yvals, typecode)
-+        xvals = numpy.asarray(xvals, dtype)
-+        yvals = numpy.asarray(yvals, dtype)
- 
-         if ufunc:
--            return f(xvals[:,Numeric.NewAxis], yvals[Numeric.NewAxis,:])
-+            return f(xvals[:,numpy.newaxis], yvals[numpy.newaxis,:])
-         else:
--            if typecode is None:
-+            if dtype is None:
-                 # choose a result typecode based on what '+' would return
-                 # (yecch!):
--                typecode = (Numeric.zeros((1,), xvals.typecode()) +
--                            Numeric.zeros((1,), yvals.typecode())).typecode()
--
--            m = Numeric.zeros((len(xvals), len(yvals)), typecode)
-+                dtype = (numpy.zeros((1,), xvals.dtype.char) +
-+                        numpy.zeros((1,), yvals.dtype.char)).dtype.char
-+            m = numpy.zeros((len(xvals), len(yvals)), dtype)
-             for xi in range(len(xvals)):
-                 x = xvals[xi]
-                 for yi in range(len(yvals)):
-diff -ur gnuplot-py-1.7/_Gnuplot.py gnuplot-py-1.7-numpy/_Gnuplot.py
---- gnuplot-py-1.7/_Gnuplot.py	2003-10-17 17:28:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/_Gnuplot.py	2007-11-20 22:37:26.000000000 +0200
-@@ -228,8 +228,8 @@
- 
-         'items' is a sequence of items, each of which should be a
-         'PlotItem' of some kind, a string (interpreted as a function
--        string for gnuplot to evaluate), or a Numeric array (or
--        something that can be converted to a Numeric array).
-+        string for gnuplot to evaluate), or a numpy array (or
-+        something that can be converted to a numpy array).
- 
-         """
- 
-diff -ur gnuplot-py-1.7/__init__.py gnuplot-py-1.7-numpy/__init__.py
---- gnuplot-py-1.7/__init__.py	2003-10-17 18:04:29.000000000 +0300
-+++ gnuplot-py-1.7-numpy/__init__.py	2007-11-20 22:19:00.000000000 +0200
-@@ -128,9 +128,9 @@
- 
- Restrictions:
- 
-- -  Relies on the Numeric Python extension.  This can be obtained from
--    "SourceForge", http://sourceforge.net/projects/numpy/.  If you're
--    interested in gnuplot, you would probably also want NumPy anyway.
-+ -  Relies on the numpy Python extension.  This can be obtained from
-+    the Scipy group at <http://www.scipy.org/Download>..  If you're
-+    interested in gnuplot, you would probably also want numpy anyway.
- 
-  -  Only a small fraction of gnuplot functionality is implemented as
-     explicit method functions.  However, you can give arbitrary
-diff -ur gnuplot-py-1.7/NEWS.txt gnuplot-py-1.7-numpy/NEWS.txt
---- gnuplot-py-1.7/NEWS.txt	2003-10-17 18:04:29.000000000 +0300
-+++ gnuplot-py-1.7-numpy/NEWS.txt	2007-11-20 22:22:08.000000000 +0200
-@@ -57,7 +57,7 @@
-   equivalent.)  If I find the time I might try to produce a version
-   that doesn't require Numeric at all, under either Python or Jython.
- 
--* Removed the oldplot.py module: (1) I doubt anybody is still using
-+ Removed the oldplot.py module: (1) I doubt anybody is still using
-   it. (2) It seems to be broken anyway. (3) I don't have the energy to
-   fix or maintain it.  Let me know if I'm wrong about point 1.
- 
-@@ -222,10 +222,10 @@
-   dataset; e.g., what used to be written as
- 
-       g = Gnuplot.Gnuplot()
--      x = Numeric.arange(100)/10.0
-+      x = numpy.arange(100)/10.0
-       y = x**2
-       # Create an array of (x,y) pairs:
--      g.plot(Gnuplot.Data(Numeric.transpose((x, y))))
-+      g.plot(Gnuplot.Data(numpy.transpose((x, y))))
- 
-   can now be shortened to
- 
-diff -ur gnuplot-py-1.7/PlotItems.py gnuplot-py-1.7-numpy/PlotItems.py
---- gnuplot-py-1.7/PlotItems.py	2003-10-17 17:39:03.000000000 +0300
-+++ gnuplot-py-1.7-numpy/PlotItems.py	2007-11-20 22:34:49.000000000 +0200
-@@ -23,7 +23,7 @@
- except ImportError:
-     from StringIO import StringIO
- 
--import Numeric
-+import numpy
- 
- import gp, utils, Errors
- 
-@@ -471,12 +471,12 @@
-     return apply(_FileItem, (filename,), keyw)
- 
- 
--def Data(*set, **keyw):
--    """Create and return a _FileItem representing the data from *set.
-+def Data(*data, **keyw):
-+    """Create and return a _FileItem representing the data from *data.
- 
-     Create a '_FileItem' object (which is a type of 'PlotItem') out of
--    one or more Float Python Numeric arrays (or objects that can be
--    converted to a Float Numeric array).  If the routine is passed a
-+    one or more Float Python numpy arrays (or objects that can be
-+    converted to a float numpy array).  If the routine is passed a
-     single with multiple dimensions, then the last index ranges over
-     the values comprising a single data point (e.g., [<x>, <y>,
-     <sigma>]) and the rest of the indices select the data point.  If
-@@ -508,29 +508,29 @@
- 
-     """
- 
--    if len(set) == 1:
--        # set was passed as a single structure
--        set = utils.float_array(set[0])
-+    if len(data) == 1:
-+        # data was passed as a single structure
-+        data = utils.float_array(data[0])
- 
-         # As a special case, if passed a single 1-D array, then it is
-         # treated as one value per point (by default, plotted against
-         # its index):
--        if len(set.shape) == 1:
--            set = set[:,Numeric.NewAxis]
-+        if len(data.shape) == 1:
-+            data = data[:,numpy.newaxis]
-     else:
--        # set was passed column by column (for example,
-+        # data was passed column by column (for example,
-         # Data(x,y)); pack it into one big array (this will test
-         # that sizes are all the same):
--        set = utils.float_array(set)
--        dims = len(set.shape)
-+        data = utils.float_array(data)
-+        dims = len(data.shape)
-         # transpose so that the last index selects x vs. y:
--        set = Numeric.transpose(set, (dims-1,) + tuple(range(dims-1)))
-+        data = numpy.transpose(data, (dims-1,) + tuple(range(dims-1)))
-     if keyw.has_key('cols'):
-         cols = keyw['cols']
-         del keyw['cols']
--        if type(cols) is types.IntType:
-+        if isinstance(cols, types.IntType):
-             cols = (cols,)
--        set = Numeric.take(set, cols, -1)
-+        data = numpy.take(data, cols, -1)
- 
-     if keyw.has_key('inline'):
-         inline = keyw['inline']
-@@ -540,7 +540,7 @@
- 
-     # Output the content into a string:
-     f = StringIO()
--    utils.write_array(f, set)
-+    utils.write_array(f, data)
-     content = f.getvalue()
-     if inline:
-         return apply(_InlineFileItem, (content,), keyw)
-@@ -610,7 +610,7 @@
-         raise Errors.DataError('data array must be two-dimensional')
- 
-     if xvals is None:
--        xvals = Numeric.arange(numx)
-+        xvals = numpy.arange(numx)
-     else:
-         xvals = utils.float_array(xvals)
-         if xvals.shape != (numx,):
-@@ -619,7 +619,7 @@
-                 'the first dimension of the data array')
- 
-     if yvals is None:
--        yvals = Numeric.arange(numy)
-+        yvals = numpy.arange(numy)
-     else:
-         yvals = utils.float_array(yvals)
-         if yvals.shape != (numy,):
-@@ -647,17 +647,17 @@
-         # documentation has the roles of x and y exchanged.  We ignore
-         # the documentation and go with the code.
- 
--        mout = Numeric.zeros((numy + 1, numx + 1), Numeric.Float32)
-+        mout = numpy.zeros((numy + 1, numx + 1), numpy.float32)
-         mout[0,0] = numx
--        mout[0,1:] = xvals.astype(Numeric.Float32)
--        mout[1:,0] = yvals.astype(Numeric.Float32)
-+        mout[0,1:] = xvals.astype(numpy.float32)
-+        mout[1:,0] = yvals.astype(numpy.float32)
-         try:
-             # try copying without the additional copy implied by astype():
--            mout[1:,1:] = Numeric.transpose(data)
-+            mout[1:,1:] = numpy.transpose(data)
-         except:
-             # if that didn't work then downcasting from double
-             # must be necessary:
--            mout[1:,1:] = Numeric.transpose(data.astype(Numeric.Float32))
-+            mout[1:,1:] = numpy.transpose(data.astype(numpy.float32))
- 
-         content = mout.tostring()
-         if gp.GnuplotOpts.prefer_fifo_data:
-@@ -668,10 +668,10 @@
-         # output data to file as "x y f(x)" triplets.  This
-         # requires numy copies of each x value and numx copies of
-         # each y value.  First reformat the data:
--        set = Numeric.transpose(
--            Numeric.array(
--                (Numeric.transpose(Numeric.resize(xvals, (numy, numx))),
--                 Numeric.resize(yvals, (numx, numy)),
-+        set = numpy.transpose(
-+            numpy.array(
-+                (numpy.transpose(numpy.resize(xvals, (numy, numx))),
-+                 numpy.resize(yvals, (numx, numy)),
-                  data)), (1,2,0))
- 
-         # Now output the data with the usual routine.  This will
-diff -ur gnuplot-py-1.7/README.txt gnuplot-py-1.7-numpy/README.txt
---- gnuplot-py-1.7/README.txt	2003-10-19 17:52:35.000000000 +0300
-+++ gnuplot-py-1.7-numpy/README.txt	2007-11-20 22:35:30.000000000 +0200
-@@ -65,8 +65,8 @@
- 
- Obviously, you must have the gnuplot program if Gnuplot.py is to be of
- any use to you.  Gnuplot can be obtained via
--<http://www.gnuplot.info>.  You also need Python's Numerical
--extension, which is available from <http://numpy.sourceforge.net>.
-+<http://www.gnuplot.info>.  You also need a copy of the numpy package, which
-+is available from the Scipy group at <http://www.scipy.org/Download>.
- 
- Gnuplot.py uses Python distutils
- <http://www.python.org/doc/current/inst/inst.html> and can be
-diff -ur gnuplot-py-1.7/setup.py gnuplot-py-1.7-numpy/setup.py
---- gnuplot-py-1.7/setup.py	2003-10-17 17:52:28.000000000 +0300
-+++ gnuplot-py-1.7-numpy/setup.py	2007-11-20 22:19:20.000000000 +0200
-@@ -31,7 +31,7 @@
-     author_email='mhagger@alum.mit.edu',
-     url='http://gnuplot-py.sourceforge.net',
-     license='LGPL',
--    licence='LGPL', # Spelling error in distutils
-+    #licence='LGPL', # Spelling error in distutils
- 
-     # Description of the package in the distribution
-     package_dir={'Gnuplot' : '.'},
-diff -ur gnuplot-py-1.7/test.py gnuplot-py-1.7-numpy/test.py
---- gnuplot-py-1.7/test.py	2003-10-17 17:28:10.000000000 +0300
-+++ gnuplot-py-1.7-numpy/test.py	2007-11-20 22:43:26.000000000 +0200
-@@ -17,8 +17,7 @@
- __cvs_version__ = '$Revision: 1.1 $'
- 
- import os, time, math, tempfile
--import Numeric
--from Numeric import NewAxis
-+import numpy
- 
- try:
-     import Gnuplot, Gnuplot.PlotItems, Gnuplot.funcutils
-@@ -55,7 +54,7 @@
-     filename1 = tempfile.mktemp()
-     f = open(filename1, 'w')
-     try:
--        for x in Numeric.arange(100)/5. - 10.:
-+        for x in numpy.arange(100.)/5. - 10.:
-             f.write('%s %s %s\n' % (x, math.cos(x), math.sin(x)))
-         f.close()
- 
-@@ -137,10 +136,10 @@
-         g.plot(f)
- 
-         print '############### test Data ###################################'
--        x = Numeric.arange(100)/5. - 10.
--        y1 = Numeric.cos(x)
--        y2 = Numeric.sin(x)
--        d = Numeric.transpose((x,y1,y2))
-+        x = numpy.arange(100)/5. - 10.
-+        y1 = numpy.cos(x)
-+        y2 = numpy.sin(x)
-+        d = numpy.transpose((x,y1,y2))
- 
-         wait('Plot Data against its index')
-         g.plot(Gnuplot.Data(y2, inline=0))
-@@ -173,7 +172,7 @@
-         g.plot(Gnuplot.Data(d, title='Cosine of x'))
- 
-         print '############### test compute_Data ###########################'
--        x = Numeric.arange(100)/5. - 10.
-+        x = numpy.arange(100)/5. - 10.
- 
-         wait('Plot Data, computed by Gnuplot.py')
-         g.plot(Gnuplot.funcutils.compute_Data(x, lambda x: math.cos(x), inline=0))
-@@ -235,14 +234,14 @@
- 
-         print '############### test GridData and compute_GridData ##########'
-         # set up x and y values at which the function will be tabulated:
--        x = Numeric.arange(35)/2.0
--        y = Numeric.arange(30)/10.0 - 1.5
-+        x = numpy.arange(35)/2.0
-+        y = numpy.arange(30)/10.0 - 1.5
-         # Make a 2-d array containing a function of x and y.  First create
-         # xm and ym which contain the x and y values in a matrix form that
-         # can be `broadcast' into a matrix of the appropriate shape:
--        xm = x[:,NewAxis]
--        ym = y[NewAxis,:]
--        m = (Numeric.sin(xm) + 0.1*xm) - ym**2
-+        xm = x[:,numpy.newaxis]
-+        ym = y[numpy.newaxis,:]
-+        m = (numpy.sin(xm) + 0.1*xm) - ym**2
-         wait('a function of two variables from a GridData file')
-         g('set parametric')
-         g('set data style lines')
-@@ -264,7 +263,7 @@
- 
-         wait('Use compute_GridData in ufunc and binary mode')
-         g.splot(Gnuplot.funcutils.compute_GridData(
--            x,y, lambda x,y: Numeric.sin(x) + 0.1*x - y**2,
-+            x,y, lambda x,y: numpy.sin(x) + 0.1*x - y**2,
-             ufunc=1, binary=1,
-             ))
- 
-diff -ur gnuplot-py-1.7/utils.py gnuplot-py-1.7-numpy/utils.py
---- gnuplot-py-1.7/utils.py	2003-10-17 17:38:44.000000000 +0300
-+++ gnuplot-py-1.7-numpy/utils.py	2007-11-20 22:21:24.000000000 +0200
-@@ -17,28 +17,32 @@
- __cvs_version__ = '$Revision: 1.1 $'
- 
- import string
--import Numeric
-+import numpy
- 
- 
- def float_array(m):
--    """Return the argument as a Numeric array of type at least 'Float32'.
-+    """Return the argument as a numpy array of type at least 'Float32'.
- 
-     Leave 'Float64' unchanged, but upcast all other types to
-     'Float32'.  Allow also for the possibility that the argument is a
--    python native type that can be converted to a Numeric array using
--    'Numeric.asarray()', but in that case don't worry about
-+    python native type that can be converted to a numpy array using
-+    'numpy.asarray()', but in that case don't worry about
-     downcasting to single-precision float.
- 
-     """
- 
-     try:
-         # Try Float32 (this will refuse to downcast)
--        return Numeric.asarray(m, Numeric.Float32)
-+        return numpy.asarray(m, numpy.float32)
-     except TypeError:
-         # That failure might have been because the input array was
--        # of a wider data type than Float32; try to convert to the
-+        # of a wider data type than float32; try to convert to the
-         # largest floating-point type available:
--        return Numeric.asarray(m, Numeric.Float)
-+        try:
-+            return numpy.asarray(m, numpy.float_)
-+        except TypeError:
-+            print "Fatal: array dimensions not equal!"
-+            return None
- 
- 
- def write_array(f, set,
diff --git a/dev-python/gnuplot-py/gnuplot-py-1.7-r2.ebuild b/dev-python/gnuplot-py/gnuplot-py-1.7-r2.ebuild
deleted file mode 100644
index ac7a43b0d517..000000000000
--- a/dev-python/gnuplot-py/gnuplot-py-1.7-r2.ebuild
+++ /dev/null
@@ -1,35 +0,0 @@
-# Copyright 1999-2009 Gentoo Foundation
-# Distributed under the terms of the GNU General Public License v2
-# $Header: /var/cvsroot/gentoo-x86/dev-python/gnuplot-py/gnuplot-py-1.7-r2.ebuild,v 1.11 2009/02/26 10:17:50 bicatali Exp $
-
-inherit distutils eutils
-
-DESCRIPTION="A python wrapper for Gnuplot"
-HOMEPAGE="http://gnuplot-py.sourceforge.net/"
-SRC_URI="mirror://sourceforge/${PN}/${P}.tar.gz"
-
-LICENSE="LGPL-2.1"
-SLOT="0"
-KEYWORDS="amd64 ~ia64 ppc ~ppc64 s390 sparc x86 ~x86-fbsd"
-IUSE=""
-
-DEPEND="virtual/python
-	sci-visualization/gnuplot
-	dev-python/numpy"
-RDEPEND="${DEPEND}"
-
-PYTHON_MODNAME="Gnuplot"
-
-src_unpack() {
-	unpack ${A}
-	cd "${S}"
-	epatch "${FILESDIR}/${P}-numpy.patch"
-	epatch "${FILESDIR}/${P}-mousesupport.patch"
-}
-
-src_install() {
-	distutils_src_install
-	dohtml doc/Gnuplot/*
-	insinto /usr/share/doc/${PF}
-	doins demo.py
-}