Hello Eric, Hello list, a year ago I also encountered the problem of "one file - one figure" of the plotfile function. I would like to propose an addional functionality of using one figure and several files in plotfile, because sometimes I don't want to read data myself. I added a patch including the following changes: - added a new keywordargument to plotfile 'use_cf': If use_cf isTrue plotfile uses fig = gcf() instead of fig = figure() to suppress opening of a new figure and therewith allowing to use the user preferred figure - added a further new keyword argument 'names' to set x/ylabels in the case there are no names in the csv-file
Furthermore I attached the modified plotfile_demo.py
(examples/pylab_examples/plotfile_demo.py) and some new data
(examples/data/data_x_x2_x3.csv).
Could this be useful?
Thanks in advance for any comments.
best regards
Matthias
On Wednesday 29 April 2009 09:20:17 Eric Firing wrote:
> Joseph Smidt wrote:
> > Okay, I am another gnuplot user trying to migrate over to matplotlib.
> > I like what I see, but there are a couple things that are very easy to
> > do in Gnuplot that I can't figure out how to do with matplotlib.
> >
> > I have a file with 3 columns of data called data.txt that looks like:
> >
> > 0.0000 1.0000 1.0
> > 0.0634 1.0655 1.1353
> > 0.1269 1.1353 1.28899916094
> > 0.1903 1.2097 1.46345358199
> > 0.2538 1.2889 1.6615188369
> > 0.3173 1.3734 1.88639043926
> > ...
> >
> > I can plot this data, 2 versus 1 and 3 versus 1, very easily on the
> > same plot, with a legend, with log y values, and only for the xrange
> > between 2 and 3 with gnuplot:
> >
> > set log y
> > set xrange[2:3]
> > plot 'data.txt' u 1:2 w l t 'apples', 'data.txt' u 1:3 w l t 'oranges'
> >
> > Now, how do I do that same thing with matplotlob? Ie:
> >
> > 1. Both graphs overlayed on the same plot.
> > 2. Semilogy. (log y values),
> > 3. Only ploy for x in the range 2-3.
> > 4. Legend for the two graphs on same plot.
>
> Something like this:
>
> import numpy as np
> import matplotlib.pyplot as plt
>
> x, apples, oranges = np.loadtxt('data.txt', unpack=True)
> plt.semilogy(x, apples, label='apples')
> plt.semilogy(x, oranges, label='oranges')
> plt.legend()
> plt.gca().set_xlim(2, 3)
> plt.show()
>
> There are many possible variations and styles. The basic point is to
> separate reading in the data from plotting it. Plotfile won't do what
> you want because it is designed to make separate subplots instead of
> plotting multiple lines on a single axes. Maybe doing the latter would
> be at least as useful, if not more, and could be enabled as an option
> with one more kwarg.
>
> Eric
>
> > I have spent time looking through the documentation but I can't find
> > anyway to do this is any straightforward way. plotfile() looks
> > promising, but I can't seem to make it do the above. Thanks in
> > advance.
> >
> > Joseph Smidt
>
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Index: lib/matplotlib/pyplot.py
===================================================================
--- lib/matplotlib/pyplot.py (revision 7068)
+++ lib/matplotlib/pyplot.py (working copy)
@@ -1447,8 +1447,8 @@
draw_if_interactive()
return ret
-def plotfile(fname, cols=(0,), plotfuncs=None,
- comments='#', skiprows=0, checkrows=5, delimiter=',',
+def plotfile(fname, cols=(0,), plotfuncs=None, use_cf=False,
+ comments='#', skiprows=0, checkrows=5, delimiter=',', names=None,
**kwargs):
"""
Plot the data in *fname*
@@ -1473,9 +1473,12 @@
vector as you use in the *plotfuncs* dictionary, eg., integer
column numbers in both or column names in both.
- *comments*, *skiprows*, *checkrows*, and *delimiter* are all passed on to
- :func:`matplotlib.pylab.csv2rec` to load the data into a record array.
+ *use_cf* : use current figure instead of a new figure for plotting
+ *comments*, *skiprows*, *checkrows*, *delimiter*, and *names* are all
+ passed on to :func:`matplotlib.pylab.csv2rec` to load the data into a
+ record array.
+
kwargs are passed on to plotting functions.
Example usage::
@@ -1484,17 +1487,21 @@
plotfile(fname, (0,1,3))
# plot using column names; specify an alternate plot type for volume
- plotfile(fname, ('date', 'volume', 'adj_close'), plotfuncs={'volume': 'semilogy'})
+ plotfile(fname, ('date', 'volume', 'adj_close'),
+ plotfuncs={'volume': 'semilogy'})
"""
+ if use_cf is False:
+ fig = figure()
+ else:
+ fig = gcf()
- fig = figure()
if len(cols)<1:
raise ValueError('must have at least one column of data')
if plotfuncs is None:
plotfuncs = dict()
- r = mlab.csv2rec(fname, comments=comments,
- skiprows=skiprows, checkrows=checkrows, delimiter=delimiter)
+ r = mlab.csv2rec(fname, comments=comments, skiprows=skiprows,
+ checkrows=checkrows, delimiter=delimiter, names=names)
def getname_val(identifier):
'return the name and column data for identifier'
plotfile_demo.py
Description: application/python
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