matplotlib-users Mailing List for matplotlib

I made a little more progress, but i'm not sure i'm doing this the right way.
Suggestions?
from pylab import *
import numpy as np
#generate random temperature data
snp=[]
for i in range(0,65):
 snp.append(np.random.randint(35,122))
#hide the labels. I don't want them.
rc('xtick', labelsize=0)
rc('ytick', labelsize=0)
fig=figure(figsize=(8,8),facecolor='0.0')
ax = fig.add_subplot(111,polar=True,frameon=False)
tempTuple=array(snp)
r = tempTuple/10
theta = ((tempTuple*2.9508)*pi)/180
area = r**2*(tempTuple/5.4)
colors = theta
#this is the fancy green,yellow,red background
#it's actually a scatter plot that sits behind (zorder)
#of the rest of the scatter plots.
#radius
r1 = 0.7 # 20%
r2 = r1 + 0.2 # 40%
# define some sizes of the scatter marker
sizes = [55000]
x = [0] + np.cos(np.linspace(0, 2*math.pi*r1, 100)).tolist()
y = [0] + np.sin(np.linspace(0, 2*math.pi*r1, 100)).tolist()
xy1 = zip(x,y)
x = [0] + np.cos(np.linspace(2*math.pi*r1, 2*math.pi*r2, 100)).tolist()
y = [0] + np.sin(np.linspace(2*math.pi*r1, 2*math.pi*r2, 100)).tolist()
xy2 = zip(x,y)
x = [0] + np.cos(np.linspace(2*math.pi*r2, 2*math.pi, 100)).tolist()
y = [0] + np.sin(np.linspace(2*math.pi*r2, 2*math.pi, 100)).tolist()
xy3 = zip(x,y)
ax.scatter([0,0,0], [0,0,0], marker=(xy1,0), s=sizes,
facecolor='green',alpha=.25,zorder=1)
ax.scatter([0,0,0], [0,0,0], marker=(xy2,0), s=sizes, facecolor='yellow'
,alpha=.25,zorder=1)
ax.scatter([0,0,0], [0,0,0], marker=(xy3,0), s=sizes,
facecolor='red',alpha=.25,zorder=1)
ax.scatter(theta, r, c=colors, s=area,zorder=2)
ax.grid(False)
show()
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Haibao Tang <tan...@gm...> writes:
> Any ideas?
Yes, image clipping was unimplemented in the pdf backend. I added an
implementation (both on the trunk and on the 0.98.5 branch) that at
least gets this example and the dolphin right - please test it if you
have some other use case.
-- 
Jouni K. Seppänen
http://www.iki.fi/jks

On Thu, Feb 26, 2009 at 4:51 AM, Søren Nielsen
<sor...@gm...> wrote:
> I've tried placing a legend using the loc = (x,y) .. and the legend is moved
> where I want it. the problem is, when I add new lines to the plot.. the
> legend grows, but upwards.. so the lower left point of the legend box is
> constant.. but that's not the logical way for a legend box to grow..
> shouldn't it grow downwards, just like when I use the standard loc = 1
> (upper right position) .
Well, technically, legend never grows. Whenever you call legend(), a
new legend instance is created and the old one is just destroyed.
Anyhow, as far as I can tell, the (x,y) coordinates given to the *loc*
parameter has been the coordinate of the lower left corner of the
legend (but I don't think this is clearly specified in the
documentation). Therefore, I don't think it is a good idea to make the
legend grow(?) downward while you're supplying a fixed coordinate of
the lower left corner. This is hardly possible and it seems to make
little sense to me.
Anyhow, I just submitted a patch to the svn that add an optional
*bbox_to_anchor* argument for the legend class. This lets you specify
the bbox that the legend will be anchored (the default is the bbox of
the parent).
For example,
legend(loc="upper left", bbox_to_anchor=[0.0, 0.5])
will create an legend with its upper left corner at (0.0, 0.5), and it
will grow downward. Note that when len(bbox_to_anchor)==2, a bbox with
zero width and zero height is created.
I hope this suits your need.
-JJ

Hi,
If I have a figure:
h = pp.figure(num=14)
What is the best way to check to see if Figure 14 exists? I'm writing a 
function that adds plots to a figure window. I want the function to 
check if the figure exists, and if so, turn off autoscaling (using 
Eric's suggested axes.set_autoscale_on(False)) in case the user has zoomed.
-- 
Christopher Brown, Ph.D.
Department of Speech and Hearing Science
Arizona State University

Aaron R> wrote:
> I have an app which adds data to a plot. Everything is working, but
> when I add data to a plot that was zoomed in, it switches the display
> to a zoomed out view.
> 
> def addData(self, xdata, ydata):
> 	# Need to save off current zoom level before adding new plot data
> # But don't know how
Try this:
 self.axes.set_autoscale_on(False)
Eric
> 	self.axes.plot(xdata, ydata)
> 
> 	# Restore view here, then redraw
> 	self.canvas.draw()
> 

Just a follow-up: I managed to interpolate this problem away...
 interpolated = []
 iinds = []
 for i in range(len(stockData.rinds)-1):
 interpolated.append(s[stockData.rinds[i]])
 iinds.append(stockData.inds[i])
 interpolated.append((s[stockData.rinds[i]]*3. + s[stockData.rinds[i]+1])/4)
 iinds.append(stockData.inds[i] + 0.25)
 interpolated.append((s[stockData.rinds[i]] + s[stockData.rinds[i]+1])/2)
 iinds.append(stockData.inds[i] + 0.5)
 interpolated.append((s[stockData.rinds[i]] + 3.* s[stockData.rinds[i]+1])/4)
 iinds.append(stockData.inds[i] + 0.75)
 interpolated.append(s[stockData.rinds[len(stockData.rinds)-1]])
 iinds.append(stockData.inds[len(stockData.inds)-1])
 interpolated = array(interpolated)
 ax.fill_between(iinds, interpolated, 50-thresh, where=interpolated<50-thresh, color=color, alpha=0.3 )
It would be nice to see this taken care of intelligently inside the fill_between routine, but I wouldn't know how to do it for the general case. Maybe this post will allow future users with a similar problem to find their answer.
-Ryan
From: Ryan Wagner
Sent: Wednesday, February 25, 2009 5:06 PM
To: 'mat...@li...'
Subject: Bug in Fill_Between?
Is this a bug in fill_between, or is there a known workaround?
In the attached picture, I'm calling fill_between as follows, and I can't fill the entire area between the line (50+thresh) and the signal, s. I realize that the areas that aren't filled are boundary conditions, but there should be some sort of interpolation I can do to fix this I would think...
 ax.fill_between(stockData.inds, s[stockData.rinds], 50+thresh, where=s[stockData.rinds]>50+thresh, color=color, alpha=0.3 )
So for example: stockData.inds = range(6), s[stockData.rinds] = [20,30,70,80,40,20] and thresh = 0. I need the areas filled with color where stockData.rinds is greater than 50. It does fully fill in the xrange(2,3), but the border conditions xrange(1,2) and xrange(3,4) are not fully filled under the line.
I had the same problem with fill_over and was hoping it would be resolved with the move to fill_between. Any ideas?
-Ryan

Hi, i'm wondering if there is an easy way to fill the background in a polar
graph with a specific color. If I were making a pie graph, it'd be
something like: pie([70,20,10]), where the first 70% is green, the next 20,
yellow, and the last 10, red. I've been experimenting with polar graphs
using some random data and i've gotten close to what I want, but it'd be
neat to have a color in the background. Here's what I have now. it's a
polar scatter plot, much like what is found in the gallery, but with a few
changes.
from pylab import *
import numpy as np
snp=[]
for i in range(0,65):
 snp.append(np.random.randint(35,122))
tempTuple=array(snp)
r = tempTuple/10
theta = ((tempTuple*2.9508)*pi)/180
area = r**2*(tempTuple/5.4)
colors = theta
ax = subplot(111, polar=True)
c = scatter(theta, r, c=colors, s=area)
c.set_alpha(0.75)
show()
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I have an app which adds data to a plot. Everything is working, but
when I add data to a plot that was zoomed in, it switches the display
to a zoomed out view.
Here's a code snippet:
class MyPlotFrame(Frame):
 def __init__(self):
 Frame.__init__(self,None,-1,
 'My Super Frame',size=(550,350))
 self.SetBackgroundColour(NamedColor("WHITE"))
 self.figure = Figure()
 self.axes = self.figure.add_subplot(111)
	t = arange(0.0,3.0,0.01)
 s = sin(2*pi*t)
 self.axes.plot(t,s)
	self.axes.grid()
 self.canvas = FigureCanvas(self, -1, self.figure)
 self.sizer = BoxSizer(VERTICAL)
 self.sizer.Add(self.canvas, 1, LEFT | TOP | GROW)
 self.SetSizer(self.sizer)
 self.Fit()
 self.add_toolbar() # comment this out for no toolbar
 def addData(self, xdata, ydata):
	# Need to save off current zoom level before adding new plot data
 # But don't know how
	self.axes.plot(xdata, ydata)
	# Restore view here, then redraw
	self.canvas.draw()
 def add_toolbar(self):
 self.toolbar = NavigationToolbar2Wx(self.canvas)
 self.toolbar.Realize()
 # Snipped some stuff for checking if on a Mac or Windows
 self.toolbar.update()
 def OnPaint(self, event):
 self.canvas.draw()
I can't find any examples or docs on maintaining my zoom of the plot.
In matlab, I know how to do this, but I'm not sure what to do here.
Can someone please advise?
Thanks,
Aaron R>

See
http://matplotlib.sourceforge.net/examples/pylab_examples/image_clip_path.html
... and click on pdf
Any ideas?
Haibao

Hi,
I've tried placing a legend using the loc = (x,y) .. and the legend is moved
where I want it. the problem is, when I add new lines to the plot.. the
legend grows, but upwards.. so the lower left point of the legend box is
constant.. but that's not the logical way for a legend box to grow..
shouldn't it grow downwards, just like when I use the standard loc = 1
(upper right position) .
Is there a way to change this behaviour?

Hi
I'm trying to draw something like
http://en.wikipedia.org/wiki/File:Cartesian-coordinate-system.svg
Below is my current attempt.
Four questions:
1. The y-axis label is vertical: how do I make it horizontal?
2. How can I move the axis numbering to be in the centre of the graph,
rather than around the outside?
3. Most of the mess below is to try to get the arrow heads not to be
stretched. Is there a better way to draw those in "screen space" rather than
"graph space"?
4. The axis label positioning is ugly too, is there a better way to align
that text's midpoint?
Answers to any of these will be greatfully received. :)
Or, if I'm going about this all wrong and I missed an easy helper function,
that'd be even better!
thanks,
scott
-------------
from __future__ import division
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
def cartesian(w,h):
 fig = plt.figure(figsize=(5,5))
 ax = plt.axes()
 arrowExtraW = w/6
 arrowExtraH = h/6
 box = dict(edgecolor='white', facecolor='white', pad=5)
 plt.xlabel("$x$", bbox=box)
 ax.xaxis.set_label_coords(1.03, 0.515)
 plt.ylabel("$y$", bbox=box)
 ax.yaxis.set_label_coords(0.515, 1.03)
 plt.axis([-w-arrowExtraW, w+arrowExtraW, -h-arrowExtraH, h+arrowExtraH])
 plt.arrow(-w, 0, w*2, 0, head_width=arrowExtraH/1.5,
head_length=arrowExtraW, edgecolor="black",
 facecolor="black", label="$x$")
 plt.arrow(w, 0, -w*2, 0, head_width=arrowExtraH/1.5,
head_length=arrowExtraW, edgecolor="black", facecolor="black")
 plt.arrow(0, -h, 0, h*2, head_width=arrowExtraW/1.5,
head_length=arrowExtraH, edgecolor="black",
 facecolor="black", label="$y$")
 plt.arrow(0, h, 0, -h*2, head_width=arrowExtraW/1.5,
head_length=arrowExtraH, edgecolor="black", facecolor="black")
 plt.grid(True)
 plt.savefig("a.png")
cartesian(20, 6)
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I don't use wx so i'm not sure if this could be helpful, but you may
check the figimage command.
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.figimage
Note that it draws the image directly into the figure, thus no axes is needed.
-JJ
On Wed, Feb 25, 2009 at 6:09 PM, lionel keene <lio...@gm...> wrote:
> Hello all, I've been trying for days but I can't seem to get the
> result I'm looking for. I have a 2d array of type "numpy.ndarray"
> which I'd like to plot as a simple color map. I'd like to plot it in
> the upper-lefthand corner of the client area in a wxPython frame. The
> plotting needs to be a very simple 1:1 ratio, for example if the numpy
> array has 400 rows and 500 columns, I would like to plot it so that it
> assumes 400x500 pixels in the wxPython frame. I do not need axis ticks
> and labels, just the colormap plot itself. I can get my figure to plot
> (with tick marks and labels since I haven't figured out how to turn
> those off) but I cannot size it properly. I've copied a tutorial
> example I found and modify it and through tedious trial and error have
> gotten half-way to where I need:
>
>
> # First attempt to render data to a window:
>
> import matplotlib
> matplotlib.use('WXAgg')
>
> from matplotlib import rcParams
> import numpy
>
> import matplotlib.cm as cm
>
> from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
>
>
> #from matplotlib.figure import Figure
>
> from wx import *
>
> import DataFileTypes as DFT
>
>
> class DataFrame(Frame):
>
>  def __init__(self):
>
>    Frame.__init__(self, None, -1, "Data filename here",
>            size=DisplaySize())
>
>  def displayData(self):
>
>    data = None
>
>    # Load data into "data" object using my custom IntData(...) class:
>    try:
>      data = DFT.INTData("C:\SAR Test files\Tibet2008.int")
>
>    except DFT.DataFileError:
>      print("Error opening data file")
>
>    except DFT.ResourceFileError:
>      print("Error opening resource file")
>
>
>    if data:
>
>      # Assume a screen dpi of 96...seems very flakey to me:
>      ScreenDPI = 96.0
>
>
>      # compute the width and height of figure using this dpi
>      # and the rows and columns of the data for a 1:1 display ratio:
>      FigureWidthInInches = (data.numcolumns / ScreenDPI)
>      FigureHeightInInches = (data.numrows / ScreenDPI)
>      print(FigureWidthInInches, FigureHeightInInches)
>
>      # Instantiate Figure based on these parameters:
>      self.fig =
> matplotlib.figure.Figur((FigureWidthInInches,FigureHeightInInches),
> dpi = ScreenDPI)
>      self.canvas = FigureCanvasWxAgg(self, -1, self.fig)
>
>      # Put everything into a sizer:
>      sizer = BoxSizer(VERTICAL)
>      #sizer.Add(self.canvas, 1, LEFT | TOP | GROW)
>      sizer.Add(self.canvas, 0, LEFT | TOP)
>      self.SetSizer(sizer)
>      # self.Fit()
>
>      a = self.fig.add_axes([0.075, 0.1, 0.75, 0.85])
>      self.im = a.imshow(data.getNumpyArray(),
> interpolation=None, cmap = data.getCustomColorMap())
>
>
>
>
> if __name__ == '__main__':
>
>  app = PySimpleApp()
>  frame = DataFrame()
>  frame.displayData()
>
>  frame.Show()
>  app.MainLoop()
>
>
> It displays but the plot is inside the figure i.e. the colormap of the
> data is within the figure that I've sized. matplotlib does this by
> design, of course, but I cannot figure out how to defeat it. For one
> thing, I don't think I'm sizing the figure correctly by setting
> (guessing at) the dpi and computing the inches...just seems wrong, but
> I can't find any tutorials or examples that show anything that sizes
> figures using pixels or screen coords.
>
> I always know the dimensions of my data a priori, so let's assume the
> following very simple situation:
>
> - I have a numpy.ndarray of data with 350 rows and 500 columns. How do
> I display it in the upper-left hand corner of the frame client with no
> tick marks/labels, etc...just the colormap at screen
> coords(0,0)->(349,499) (rows,columns)? Could someone post a few lines
> to do this? Thanks so much in advance!
>
> -L
>
> ------------------------------------------------------------------------------
> Open Source Business Conference (OSBC), March 24-25, 2009, San Francisco, CA
> -OSBC tackles the biggest issue in open source: Open Sourcing the Enterprise
> -Strategies to boost innovation and cut costs with open source participation
> -Receive a 600ドル discount off the registration fee with the source code: SFAD
> http://p.sf.net/sfu/XcvMzF8H
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

LKeene wrote:
> 
> 
> - I have a numpy.ndarray of data with 350 rows and 500 columns. How do
> I display it in the upper-left hand corner of the frame client with no
> tick marks/labels, etc...just the colormap at screen
> coords(0,0)->(349,499) (rows,columns)? Could someone post a few lines
> to do this? Thanks so much in advance!
> 
> -L
> 
Hmm... interesting problem...
Here's a simple example where the image fills the frame - note the
properties such as xticks, yticks = [], position=[0,0,1,1], and the size of
the Frame itself... on my platform (Mac OS X) the height of the frame should
be 22 pixels more than the image (discovered by trial and error). 
The border of the axes is still visible in black - obscuring the outer
pixels of the image - does anyone know how to shut that off?
import matplotlib
matplotlib.interactive(False)
matplotlib.use('WXAgg')
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
from matplotlib.figure import Figure
from matplotlib.pyplot import setp
import numpy as np
import wx
class MatplotlibFrame(wx.Frame):
 def __init__(self, *args, **kwargs):
 wx.Frame.__init__(self, *args, **kwargs)
 self.figure = Figure()
 print self.figure
 self.canvas = FigureCanvasWxAgg(self, -1, self.figure)
 self.subplot = self.figure.add_subplot(111)
 #cdata = np.random.rand(351, 501)
 cdata = np.zeros((351, 501))
 cdata[::50, ::50] = 1
 self.subplot.imshow(cdata, aspect='equal', interpolation='nearest')
 setp(self.subplot, xticks=[], yticks=[], position=[0,0,1,1])
 def repaint(self):
 self.canvas.draw()
class App(wx.App):
 def OnInit(self):
 frame = MatplotlibFrame(parent=None, title="an image", size=(501,
351+22))
 frame.Show()
 return True
app = App()
app.MainLoop()
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Hello,
My first message in the list. I would like to mention a few things about the
matplotlib PDF document.
Firstly, the download link for the pdf document (@
http://matplotlib.sourceforge.net/contents.html) is for release 0.98.5.1,
compiled on December 17, instead of 0.98.5.2, on Dec-18.
Next, is there a way to get functions separately listed under each bookmark
listing in the pdf file? For example if I go IV Matplotlib API section from
the bookmarks menu and click the matplotlib.pyplot seb-menu I would like to
see the function names listed. In addition to module indexing (where
keywords highlighted back to original names) this would be a nice feature to
add the pdf documentation.
If this needs a manual configuration, I am volunteering to spend time to add
this functionality.
Regards,
Gökhan SEVER

does anyone know how to upgrade the matplotlib package that ships with 
the enthought python distribution? the current enthought release 
matplotlib is 0.98.3 and i'd like to upgrade to 0.98.5. i'm on an os 
x intel platform running leopard.
thank you,
daniel soto