I'm trying to make a big plot with smaller insets. I would like to specify the
new axis rectangle in terms of data coordinates from the original plot. This
page
mentions an .xy_tup() method of Transform objects:
http://www.scipy.org/Cookbook/Matplotlib/Transformations?highlight=%28xy_tup%29
...b
Jon Olav Vik writes:
> Antony Lee writes:
> It happens that this array has dtype=int16, and imshow's doc says that
> it only accepts float arrays
Having looked at the example you sent me, I think what you want is .astype():
a = np.array([[24695, 19052, 0],
[24565,
Pau writes:
> I am trying to generate a 3d-plot
> I have two functions that depend on two free parameters,
> T_g = (5./512.) * Light_c**5 * a**4 / (Grav_G**3 * m**3)
> T_d = 3.e4 * sqrt(a**3/ (Grav_G * m**2.))
> These are given in units of time, so that I would like axis y to be
> "time", runni
Antony Lee writes:
> I'm trying to plot a grayscale (nonzero) array as an image -- so it's
basically
plt.imshow(array). However, this pops up (after plt.show()) a completely black
image. It happens that this array has dtype=int16, and imshow's doc says that
it
only accepts float arrays, th
David Carmean writes:
> At what point is a line Collection useful?
More efficient for adding or manipulating many lines in one go. It saved my
life
(some hours of it, anyway) the other day:
http://article.gmane.org/gmane.comp.python.matplotlib.general/22149
--
Jae-Joon Lee writes:
> 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
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
