matplotlib-users Mailing List for matplotlib

Hi john,

 After the refactoring you did for version 0.5 I am having a funny 
behavior in a plot embedded in wx:

the frame appers with the size of the toolbar, but if I resize the frame 
the plot is there and is not resizable, it justs stays the same no 
matter the size of the canvas(frame?).

I've made the changes to my original module  acording to the revised 
'embedding_in_wx.py' example, which runs fine.

Here is my ploting module:

===============================================

import matplotlib
matplotlib.use('WX')
   
from matplotlib.backends.backend_wx import Toolbar, FigureManager, 
FigureCanvasWx
from matplotlib.figure import Figure
from matplotlib.axes import Subplot
import Numeric as numpy
from RandomArray import *
from MLab import *

from wxPython.wx import *

def create(parent):
    return PlotFigure(parent)

class PlotFigure(wxFrame):


    def __init__(self,parent):
        wxFrame.__init__(self,None,-1,"Results")
        self.fig = Figure((5,4), 75)
        self.canvas = FigureCanvasWx(self,-1,self.fig)
        self.toolbar = Toolbar(self.canvas)
        self.toolbar.Realize()

        # On Windows, default frame size behaviour is incorrect
        # you don't need this under Linux
        tw, th = self.toolbar.GetSizeTuple()
        fw, fh = self.canvas.GetSizeTuple()
        self.toolbar.SetSize(wxSize(fw, th))
       
        # Create a figure manager to manage things
        self.figmgr = FigureManager(self.canvas, 1, self)
       
        # Now put all into a sizer
        sizer = wxBoxSizer(wxVERTICAL)
        # This way of adding to sizer prevents resizing
        #sizer.Add(self.fig, 0, wxLEFT|wxTOP)
       
        # This way of adding to sizer allows resizing
        sizer.Add(self.toolbar, 1, wxLEFT|wxTOP|wxGROW)
       
        # Best to allow the toolbar to resize!
        sizer.Add(self.toolbar, 0, wxGROW)
        self.SetSizer(sizer)
        self.Fit()
       
    def plotLine(self,y, leg, tit='Time Series'):
        """
        Generate line plots
        """
        # Use ths line if using a toolbar
        a = self.figmgr.add_subplot(211)
       
        # Or this one if there is no toolbar
        #a = Subplot(self.fig, 211)
        styles = ('-', '--', ':', '.', 'o', '^', 'v', '<', '>', 's', '+')
        colors = ('b', 'g', 'r', 'c', 'm', 'y', 'k')
        s = 0
        c = 0
        for i in range(numpy.shape(y)[0]):
            if s > len(styles)-1:
                s = 0
            if c > len(colors)-1:
                c = 0
            style = styles[s]
            color = colors[c]
            a.plot(y[i,:],style+color) # plot each line with a different 
combination of color and style
            if c == len(colors)-1:
                s += 1
            c += 1
        a.set_title(tit)
        a.legend(leg)
        self.toolbar.update()

===============================================

which I call like this: (I import the plotting module as PF)

self.fig = PF.create(None)
        leg = self.modict["slabels"]
        tit = 'Time Series and Final State'
        self.fig.plotLine(results, leg, tit)
       
        self.fig.plotBar(results, leg)
       
        self.fig.Show()

>>>>> "Engelsma," == Engelsma, Dave <D.E...@La...> writes:

Hi David, please post questions directly to the matplotlib-users list.

    Engelsma> Hello -- Is it possible to save figures (I'm using the
    Engelsma> .eps feature) without having to show the plots/charts
    Engelsma> on the user's screen? I'd like to be able to save the
    Engelsma> figures to disk without showing them on the
    Engelsma> screen. Currently, it seems that the figures will not
    Engelsma> save to disk, unless I issue the show() command after
    Engelsma> the savefig. I'd like to eliminate having to call
    Engelsma> show().

From your email, it sounds like you are using the GTK backend and
saving figures with the ps backend.  If you just want to save the
figures as PS and not show them to the screen, use the ps backend
directly as described on
http://matplotlib.sourceforge.net/backends.html

  > python myscript.py -dPS

or

    import matplotlib
    matplotlib.use('PS')
    from matplotlib.matlab import *

    t = arange(0.0, 3.0, 0.01)
    for i in range(1,10):
        figure(1)
        s = sin(2*pi*i*t)
        plot(t,s)
        savefig('plot%02d' % i)
        close(1)

In either case, there is no need to call 'show'.  If you want to make
multiple figures, you need to clear them between each save, as I did
here by closing the figure.

If you really want to use the GTK backend to make PS figures without
showing the figure, there are some things that will enable this, but I
don't see any reasons to go this route.  Let me know.

JDH

Hi,

I am happily using matplotlib-0.50e. I tried eps output and it worked very 
nicely. The problem with plot lines not being clipped by a manual axis in 
the PS backend also seems to have been fixed.

...

I have some feedback on the default tick behaviour. matplotlib seems to
pick a number of ticks, and then divides through to get the tick values.
This results in some ugly long tick labels, making it hard to quickly
gauge the range between two points on a graph.

E.g. if the y range of a plot is 1.927 to 1.948, then matplotlib puts
ticks at (1.927, 1.931, 1.935, ..., 1.948)

I think it would be better (and closer to the plotting behaviour of 
other software) if matplotlib picked ticks that were "round", even if that 
means the endpoints of the axes are slightly outside the range of the 
data.

So the ticks for the example above would become:
(1.925, 1.930, 1.935, ..., 1.950)

I guess this would be more complicated to implement than the current 
algorithm, but it would make life easier when interpreting graphs from 
matplotlib!

...

Another slight niggle. If I set the axis range manually, then if a data
point is exactly equal to the end of the axis range then it won't be 
plotted. Making the axis range slightly longer is clumsy. This also 
violates the principle of least surprise, because automatic axis ranges do 
not have this behaviour. A simple way to see the problem is to compare the 
output of the two plots below:

>>> xvals = arange(0.0, 1.0, 0.1)
>>> plot(xvals, [sin(x) for x in xvals])
[<matplotlib.lines.Line2D instance at 0x93fa844>]
>>> show()
>>> plot(xvals, [sin(x) for x in xvals])
[<matplotlib.lines.Line2D instance at 0x9249d2c>]
>>> autoaxis = axis()
>>> autoaxis
[0.0, 0.90000000000000002, 0.0, 0.80000000000000004]
>>> axis(autoaxis)
>>> show()

Presumably the logic for picking the datapoints to plot should use <= not
<.

Cheers,
Matthew.