Re: [Matplotlib-users] Memory leaks in a web application

[John H. <jd...@gm...>]

On Tue, Feb 10, 2009 at 7:55 AM, Gerry Steele <ger...@gm...> wrote:
> Thanks Michael ,
>
> I had somehow put myself under the impression i was using he OO
> version of the api but it is much more clear now. Memory issues now
> look better.

There is room for confusion.  A common usage pattern, one I often use
myself, is to use pyplot for figure creation, closing and showing
only, and to use the OO API for everything else.  To whit:

  import matplotlib.pyplot as plt
  fig = plt.figure()
  ax = fig.add_subplot(111)
  ax.plot([1,2,3])
  ax.set_xlabel('hi')
  plt.show()

this contrasts with the pure pyplot approach, which uses the pyplot
state machine for everything (figure/axes creation, current axes, etc)

  import matplotlib.pyplot as plt
  plt.plot([1,2,3])
  plt.xlabel('hi')
  plt.show()

and both are different from the pure OO approach in which you manually
create the figure canvas etc

  from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
  from matplotlib.figure import Figure

  fig = Figure()
  canvas = FigureCanvas(fig)
  ax = fig.add_subplot(111)
  ax.plot([1,2,3])
  ax.set_xlabel('hi')

Note that in the 3rd example, all the code is the same as the first
example, except the figure/canvas creation, which is why one might
call it "OO pyplot"

Eric has summarized some additional information about the different
usage modes here

  http://matplotlib.sourceforge.net/faq/usage_faq.html#matplotlib-pylab-and-pyplot-how-are-they-related

JDH