Re: [Matplotlib-users] Alpha compositing of ~60000 line plots takes forever

[Jae-Joon L. <lee...@gm...>]

If you're plotting lots of lines, do not use plot but use
LineCollection instead.

http://matplotlib.sourceforge.net/examples/api/collections_demo.html

http://matplotlib.sourceforge.net/api/collections_api.html#matplotlib.collections.LineCollection

Here is slightly modified version of your code that uses
LineCollection (but I haven't check if the code is correct).
With my not so good macbook, it took me 3 sec for 6000 lines and it
seems like O(n) to me.

Regards,

-JJ



    ax = subplot(111)
    x = np.arange(200)
    yy = [np.array((x, np.sin(x / (2 * np.pi * x[-1] * i))))) for i in range(n)]
    yyt = [np.transpose(y1) for y1 in yy]
    from matplotlib.collections import LineCollection

    lc = LineCollection(yyt, colors=[(0, 0, 0, alpha)])
    ax.add_collection(lc)
    ax.autoscale_view()


On Tue, Mar 16, 2010 at 7:26 AM, Jon Olav Vik <jo...@gm...> wrote:
> I want to overlay many line plots using alpha transparency. However, plotting
> them in Matplotlib takes about O(n**2) time, and I think I may be running into
> memory limitations as well.
>
> As a simple benchmark, I used IPython to run alco.ipy (below), which runs
> alco.py for an increasing number of data series. Extrapolating from this,
> plotting 60000 series would take something like 200 minutes. This is similar to
> my actual use case, which takes about 3 hours to finish a plot. Zooming in and
> saving again is much faster, taking only about 30 seconds.
>
> I would appreciate suggestions on how to speed this up. For instance:
>
> Is there a memoryless "canvas" object that I could draw on, just accumulating
> the alpha in each pixel: new_alpha = old_alpha + (1 - old_alpha) * this_alpha.
>
> Failing that, I could do it manually by keeping a Numpy array of the pixels in
> the image. For each series, find the x values corresponding to each column
> index, then interpolate to find the row index corresponding to each y value.
> Finally, use imshow() or something to add axes and annotation.
>
> That you in advance for any help.
>
> Best regards,
> Jon Olav
>
> == Output of alco.ipy ==
>
> The columns are "number of series" and "seconds".
>
> In [8]: run alco.ipy
> 1000 9.07
> 2000 24.8
> 3000 44.73
> 4000 67.85
> 5000 95.67
> 6000 135.1
> 7000 177.82
> 8000 226.03
> 9000 278.32
> 10000 340.81
>
> == alco.ipy ==
>
> n, t = [], []
> for i in range(1000, 10001, 1000):
>    n.append(i)
>    ti = !python alco.py $i
>    t.append(float(ti.s))
>    print n[-1], t[-1]
>
> plot(n, t, '.-')
>
> == alco.py ==
>
> """Alpha compositing of line plots. Usage: python alco.py NSERIES ALPHA"""
> from sys import argv
> import numpy as np
> import matplotlib as mpl
> mpl.use("agg") # noninteractive plotting
> from pylab import *
>
> n = int(argv[1])
> try:
>    alpha = float(argv[2])
> except IndexError:
>    alpha = 0.02
>
> # generate some data
> x = np.arange(200)
> for i in range(n):
>    y = np.sin(x / (2 * np.pi * x[-1] * i))
>    plot(x, y, 'k-', alpha=alpha)
>
> savefig("test.png")
>
>
>
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