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new version compatible with python 2.6

Browse source 
numeric replaced by numpy
updated syntax of gnuplot calls
Warning: better implementation available at http://gnuplot-py.sourceforge.net/
tested on RHEL5 (using /usr/bin/python2.6), Ubuntu11, RHEL6, Fedora 13
See also
http://www.nwchem-sw.org/index.php/Special:AWCforum/st/id350/contrib/python/Gnuplot.py_incomp....html
This commit is contained in:
Edoardo Apra 2012-02-10 19:26:24 +00:00
parent f4d87c51fe
commit 6bd5d5e9f1
1 changed files with 42 additions and 42 deletions
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84
contrib/python/Gnuplot.py
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@ -88,7 +88,7 @@ Features:
Restrictions:
- Relies on the Numeric Python extension. This can be obtained
- Relies on the numpy Python extension. This can be obtained
from LLNL (See ftp://ftp-icf.llnl.gov/pub/python/README.html).
If you're interested in gnuplot, you would probably also want
NumPy anyway.
@ -98,7 +98,7 @@ Restrictions:
explicit method functions. However, you can give arbitrary
commands to gnuplot manually; for example:
'g = Gnuplot.Gnuplot()',
'g('set data style linespoints')',
'g('set style data linespoints')',
'g('set pointsize 5')',
etc. I might add a more organized way of setting arbitrary
options.
@ -125,7 +125,7 @@ Bugs:
__version__ = "1.1a"
__cvs_version__ = "CVS version $Revision: 1.1 $"
import sys, os, string, tempfile, Numeric
import sys, os, string, tempfile, numpy
# Set after first call of test_persist(). This will be set from None
@ -211,10 +211,10 @@ class PlotItem:
self.options.append('notitle')
else:
self.options.append('title "' + self.title + '"')
if keyw.has_key('with'):
self.with = keyw['with']
del keyw['with']
self.options.append('with ' + self.with)
if keyw.has_key('with_'):
self.with_ = keyw['with_']
del keyw['with_']
self.options.append('with ' + self.with_)
if keyw:
raise OptionException(keyw)
@ -248,7 +248,7 @@ class Func(PlotItem):
The argument to the contructor is a string which is a expression.
Example:
g.plot(Func("sin(x)", with="line 3"))
g.plot(Func("sin(x)", with_="line 3"))
or the shorthand example:
@ -345,7 +345,7 @@ class ArrayFile(AnyFile):
"""A file to which, upon creation, an array is written.
When an ArrayFile is constructed, it creates a file and fills it
with the contents of a 2-d or 3-d Numeric array in the format
with the contents of a 2-d or 3-d numpy array in the format
expected by gnuplot. Specifically, for 2-d, the file organization
is for example:
@ -451,8 +451,8 @@ class Data(File):
"""Construct a Data object from a numeric array.
Create a Data 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
or more Float Python numpy arrays (or objects that can be
converted to a Float numpy array). If the routine is passed
one array, the last index ranges over the values comprising a
single data point (e.g., [x, y, and sigma]) and the rest of
the indices select the data point. If the routine is passed
@ -480,15 +480,15 @@ class Data(File):
if len(set) == 1:
# set was passed as a single structure
set = Numeric.asarray(set, Numeric.Float)
set = numpy.asarray(set, dtype=numpy.float32)
else:
# set was passed column by column (for example, Data(x,y))
set = Numeric.asarray(set, Numeric.Float)
set = numpy.asarray(set, dtype=numpy.float32)
dims = len(set.shape)
# transpose so that the last index selects x vs. y:
set = Numeric.transpose(set, (dims-1,) + tuple(range(dims-1)))
set = numpy.transpose(set, (dims-1,) + tuple(range(dims-1)))
if keyw.has_key('cols') and keyw['cols'] is not None:
set = Numeric.take(set, keyw['cols'], -1)
set = numpy.take(set, keyw['cols'], -1)
del keyw['cols']
apply(File.__init__, (self, TempArrayFile(set)), keyw)
@ -527,28 +527,28 @@ class GridData(File):
"""
data = Numeric.asarray(data, Numeric.Float)
data = numpy.asarray(data, dtype=numpy.float32)
assert len(data.shape) == 2
(numx, numy) = data.shape
if xvals is None:
xvals = Numeric.arange(numx)
xvals = numpy.arange(numx)
else:
xvals = Numeric.asarray(xvals, Numeric.Float)
xvals = numpy.asarray(xvals, dtype=numpy.float32)
assert len(xvals.shape) == 1
assert xvals.shape[0] == numx
if yvals is None:
yvals = Numeric.arange(numy)
yvals = numpy.arange(numy)
else:
yvals = Numeric.asarray(yvals, Numeric.Float)
yvals = numpy.asarray(yvals, dtype=numpy.float32)
assert len(yvals.shape) == 1
assert yvals.shape[0] == numy
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))
apply(File.__init__, (self, TempArrayFile(set)), keyw)
@ -566,11 +566,11 @@ def grid_function(f, xvals, yvals):
Note that f is evaluated at each pair of points using a Python loop,
which can be slow if the number of points is large. If speed is an
issue, you are better off computing functions matrix-wise using
Numeric's built-in ufuncs.
numpy's built-in ufuncs.
"""
m = Numeric.zeros((len(xvals), len(yvals)), Numeric.Float)
m = numpy.zeros((len(xvals), len(yvals)), dtype=numpy.float32)
for xi in range(len(xvals)):
x = xvals[xi]
for yi in range(len(yvals)):
@ -718,8 +718,8 @@ class Gnuplot:
'items' is a list or tuple 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).
"""
@ -887,7 +887,7 @@ class Gnuplot:
filename = _default_lpr
setterm = ['set', 'term', 'postscript']
if eps: setterm.append('eps')
else: setterm.append('default')
else: setterm.append(' ')
if enhanced: setterm.append('enhanced')
if color: setterm.append('color')
self(string.join(setterm))
@ -912,7 +912,7 @@ def plot(*items, **keyw):
interface only. It is recommended that you use the new
object-oriented Gnuplot interface, which is much more flexible.
It can only plot Numeric array data. In this routine an NxM array
It can only plot numpy array data. In this routine an NxM array
is plotted as M-1 separate datasets, using columns 1:2, 1:3, ...,
1:M.
@ -926,19 +926,19 @@ def plot(*items, **keyw):
newitems = []
for item in items:
# assume data is an array:
item = Numeric.asarray(item, Numeric.Float)
item = numpy.asarray(item, dtype=numpy.float32)
dim = len(item.shape)
if dim == 1:
newitems.append(Data(item[:, Numeric.NewAxis], with='lines'))
newitems.append(Data(item[:, numpy.newaxis], with_='lines'))
elif dim == 2:
if item.shape[1] == 1:
# one column; just store one item for tempfile:
newitems.append(Data(item, with='lines'))
newitems.append(Data(item, with_='lines'))
else:
# more than one column; store item for each 1:2, 1:3, etc.
tempf = TempArrayFile(item)
for col in range(1, item.shape[1]):
newitems.append(File(tempf, using=(1,col+1), with='lines'))
newitems.append(File(tempf, using=(1,col+1), with_='lines'))
else:
raise DataException("Data array must be 1 or 2 dimensional")
items = tuple(newitems)
@ -964,7 +964,7 @@ def plot(*items, **keyw):
# Demo code
if __name__ == '__main__':
from Numeric import *
from numpy import *
import sys
# A straightforward use of gnuplot. The `debug=1' switch is used
@ -972,15 +972,15 @@ if __name__ == '__main__':
# are also output on stderr.
g1 = Gnuplot(debug=1)
g1.title('A simple example') # (optional)
g1('set data style linespoints') # give gnuplot an arbitrary command
# Plot a list of (x, y) pairs (tuples or a Numeric array would
g1('set style data linespoints') # give gnuplot an arbitrary command
# Plot a list of (x, y) pairs (tuples or a numpy array would
# also be OK):
g1.plot([[0.,1.1], [1.,5.8], [2.,3.3], [3.,4.2]])
# Plot one dataset from an array and one via a gnuplot function;
# also demonstrate the use of item-specific options:
g2 = Gnuplot(debug=1)
x = arange(10, typecode=Float)
x = arange(10, dtype=numpy.float32)
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
@ -988,7 +988,7 @@ if __name__ == '__main__':
# once.
d = Data(x, y1,
title="calculated by python",
with="points 3 3")
with_="points pointsize 3 pointtype 3")
g2.title('Data can be computed by python or gnuplot')
g2.xlabel('x')
g2.ylabel('x squared')
@ -1007,10 +1007,10 @@ if __name__ == '__main__':
# 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
g3('set data style lines')
g3('set style data lines')
g3('set hidden')
g3('set contour base')
g3.xlabel('x')