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I'm seeing a memory leak with calls to subplot.clear() and canvas.draw() 
on MacOS. The same code shows no leakage on unix.
Here is a simple script that demonstrates the problem.
#!/usr/bin/env python
from __future__ import division
"""Demonstrate a memory leak in matplotlib on MacOS with TkAgg
Variants:
- Comment out subplot.clear(): this reduces the leak by about 4/5
- Comment out canvas.draw(): this reduces the leak by about 1/5
- Comment out both: there should be essentially no leakage
The leak rate seems to be affected by the update rate
(larger update interval causes lower leakage),
which suggests it's not a simple "x amount of leakage per call".
"""
import resource
import time
import Tkinter
import matplotlib
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
class MemoryLeaker(Tkinter.Frame):
 """Demonstrate a memory leak in matplotlib
 """
 def __init__(self, master, updateInterval=0.1, updatesPerReport=25):
 """Construct a MemoryLeaker
 Inputs:
 - master: master widget
 - updateInterval: interval at which subplot.clear and 
canvas.draw are called
 - updatesPerReport: number of updates between memory reports
 """
 Tkinter.Frame.__init__(self, master)
 self._updateInterval = float(updateInterval)
 self._updatesPerReport = int(updatesPerReport)
 self.figure = matplotlib.figure.Figure(figsize=(8, 2), 
frameon=True)
 self.canvas = FigureCanvasTkAgg(self.figure, self)
 self.canvas.get_tk_widget().grid(row=0, column=0, sticky="news")
 self.subplot = self.figure.add_subplot(1, 1, 1)
 print "time max RSS leak rate"
 print "(sec) (kb) (kb/sec)"
 self._prevTime = time.time()
 self._prevMem = float("nan")
 self._reportCount = 0
 self.updatePlot()
 def updatePlot(self):
 """Update the plot; calls itself at the update interval
 """
 if self._reportCount == 0:
 self.reportMem()
 self._reportCount = (self._reportCount + 1) % 
self._updatesPerReport
 self.subplot.clear()
 self.canvas.draw()
 self.after(int(self._updateInterval * 1000), self.updatePlot)
 def reportMem(self):
 currTime = time.time()
 dTime = currTime - self._prevTime
 res = resource.getrusage(resource.RUSAGE_SELF)
 currMem = res.ru_maxrss / 1024 # maximum resident set size 
utilized (in kb)
 leakRate = (currMem - self._prevMem) / dTime
 self._prevTime = currTime
 self._prevMem = currMem
 print "%6.1f %6d %6.1f" % (dTime, currMem, leakRate)
if __name__ == "__main__":
 root = Tkinter.Tk()
 wdg = MemoryLeaker(root, updateInterval=0.1, updatesPerReport=25)
 wdg.pack(expand=True, fill="both")
 root.mainloop()
P.S. my current setup is:
- MacOS 10.9
- python.org python 2.7.8
- matploblib 1.3.1
- a pre-release of Tcl/Tk 8.5.17
but I've seen this on many earlier versions, as well
I have not tried it with matplotlib 1.4.1 yet (due to problems packaging 
that with py2app).

I was able to solve my two problems by doing label="" and numpoints=1.
Thank you very much for your help.
I found my solution here:
http://stackoverflow.com/questions/19385639/duplicate-items-in-legend-in-matplotlib
There is also another cleaner solution here:
http://stackoverflow.com/questions/13588920/stop-matplotlib-repeating-labels-in-legend
import matplotlib
matplotlib.use('Agg')
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
map = Basemap()
map.plot(label="")
plt.legend(numpoints=1)
On Mon, Oct 20, 2014 at 8:11 AM, Benjamin Root <ben...@ou...> wrote:
> Legends entries are blindly constructed. Each plotting call that has a
> legend keyword argument will produce a legend entry if you are automatically
> building the legend. You can pass a label value of "__nolabel__" to prevent
> an entry if you know you are about to do something that would duplicate the
> entries. Another approach is to manually collect unique artists and manually
> build the legend (I think there is an example of that in the gallary).
>
> As for configuring the legend, there are a bunch of parameters that can be
> set for sizing the font. I think the sizing of the marker is determined by
> their size in the plot, though.
>
> Cheers!
> Ben Root
>
>
> On Mon, Oct 20, 2014 at 10:46 AM, Hearne, Mike <mh...@us...> wrote:
>>
>> For your first question: Use the legend "numpoints" keyword. I think
>> if you set it to 1, it should solve that problem.
>>
>> For your second question, I'm not sure, but I'll bet if you poke
>> around in the Legend object returned by the function, you'll find
>> something.
>>
>> On Mon, Oct 20, 2014 at 8:04 AM, Tommy Carstensen
>> <tom...@gm...> wrote:
>> > How does one avoid duplicate legends?
>> >
>> > www.tommycarstensen.com/python2_matplotlib_basemap_merc_bluemarble_hresolution.jpg
>> >
>> > Can I make the legend size smaller than the marker size?
>> >
>> >
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>

I seem to recall that the MaxNLocator and some carefully chosen axes limits
suffices for me in the past.
On Tue, Oct 21, 2014 at 11:44 AM, Adam Hughes <hug...@gm...>
wrote:
> I wrote a program that draws grids manually on mpl plots a while back. If
> you can't find a solution can you write back here and I'll try to get that
> dusted off?
> On Oct 21, 2014 2:39 PM, "Benjamin Root" <ben...@ou...> wrote:
>
>> Well, the first part is easy... it is called twinx(). If you look up axis
>> twinning in the documentation, you will find a lot of examples of this.
>>
>> As for the grids part... that would be tricky. I would first just see if
>> matplotlib "just does the right thing". Doubtful, but who knows? Then I
>> would likely go the route of lining up the major ticks on both axes so that
>> the grid lines for one axes match up with the ticks for the other.
>>
>> Let us know what you find out. Maybe it might be a useful feature to add
>> for twinning.
>>
>> Cheers!
>> Ben Root
>>
>>
>> On Tue, Oct 21, 2014 at 2:29 PM, Neal Becker <ndb...@gm...> wrote:
>>
>>> I need to overlay 2 different plots. They will share an x-axis, but
>>> will have 2
>>> different y axis with 2 different sets of units. I want one y-axis on
>>> left and
>>> one on right.
>>>
>>> But to make it harder, I want a grid. That means, there are either 2
>>> different
>>> grids, which is ugly, or one plot has to be scaled vertically so that
>>> the same y
>>> grid can be shared between them.
>>>
>>> Anyone know how to do this?
>>>
>>> --
>>> -- Those who don't understand recursion are doomed to repeat it
>>>
>>>
>>>
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>>
>>
>>
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>>
>
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