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Hi all, I've created a custom projection for drawing Lambert plots on two adjacent hemispheres, copied closely from the custom_projection_example [1], and attached here. The basics are working I think, but the axes objects have too much whitespace around them, and I can't immediately work out what approach to take to reduce it to something reasonable. Can anyone point me in the right direction? Ultimately I'm hoping to be able to put several of these plots together in a figure, which is currently not practical. (Also, pcolor doesn't work as I expect, but I need to play around with that a bit more before I know what question I need to ask of the list.) Thanks, Angus. [1] http://matplotlib.sourceforge.net/examples/api/custom_projection_example.html -- AJC McMorland Post-doctoral research fellow Neurobiology, University of Pittsburgh
2011年1月1日 OKB (not okblacke) <bre...@br...>: > I noticed that the boxplot function incorrectly calculates the > location of the median line in each box. As a simple example, plotting > the dataset [1, 2, 3, 4] incorrectly plots the median line at 3. It seems to work fine in matplotlib 1.0.0: user@host:~$ python Python 2.6.6 (r266:84292, Sep 15 2010, 16:22:56) [GCC 4.4.5] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import matplotlib as mpl >>> mpl.__version__ '1.0.0' >>> import matplotlib.pyplot as plt >>> import matplotlib.mlab as mlab >>> plt.ion() >>> plt.boxplot([1, 2, 3, 4]) {'medians': [<matplotlib.lines.Line2D object at 0x3ad6250>], 'fliers': [<matplotlib.lines.Line2D object at 0x3ad6610>, <matplotlib.lines.Line2D object at 0x3ad69d0>], 'whiskers': [<matplotlib.lines.Line2D object at 0x3acff50>, <matplotlib.lines.Line2D object at 0x3ad4310>], 'boxes': [<matplotlib.lines.Line2D object at 0x3ad4e50>], 'caps': [<matplotlib.lines.Line2D object at 0x3ad46d0>, <matplotlib.lines.Line2D object at 0x3ad4a90>]} >>> plt.grid() >>> plt.boxplot([1, 2, 3, 4]) {'medians': [<matplotlib.lines.Line2D object at 0x3dfbad0>], 'fliers': [<matplotlib.lines.Line2D object at 0x3dfbe90>, <matplotlib.lines.Line2D object at 0x3dff290>], 'whiskers': [<matplotlib.lines.Line2D object at 0x3df8810>, <matplotlib.lines.Line2D object at 0x3df8b90>], 'boxes': [<matplotlib.lines.Line2D object at 0x3dfb710>], 'caps': [<matplotlib.lines.Line2D object at 0x3df8f50>, <matplotlib.lines.Line2D object at 0x3dfb350>]} >>> plt.grid() >>> # See attached image. ... >>> mlab.prctile([1, 2, 3, 4]) array([ 1. , 1.75, 2.5 , 3.25, 4. ]) Goyo > > It also seems that the quartile calculations for the box are a > little peculiar. I have seen some discussion in old mailing list > postings about mlab.prctile and its ways of calculating percentiles, > which are different than those of some other software. > > I'm aware that there is legitimate disagreement about the "best" > way to calculate the quartiles. However, it seems to me that mlab's way > is still not any of these possibly-correct ways, because it uses int() > or nparray.astype(int) to coerce the percentile result to an integer > index. This TRUNCATES the floating-point result. No accepted quantile- > calculating method that I'm aware of does this; they all ROUND instead > of truncating (if they want to coerce to an integer index at all, in > order to produce a quantile value that is an element of the data set), > or in some cases they round uniformly up for the lower quartile and > down for the upper. You can see a summary of different methods at > http://www.amstat.org/publications/jse/v14n3/langford.html ; the method > used by mlab does not appear to agree with any of these. > > I would suggest that mlab.prctile be fixed to conform to some one > or other of these methods, rather than adding to the proliferation of > approaches to quantile-calculation. Is there any motivation for always > truncating to integer (other that "it's quicker to type" :-)? > > Also, regardless of these quartile issues, there is, as far as I'm > aware, no one who denies that the median of a (sorted) data set with an > even number of values is the mean of the middle two values. Since numpy > is already a dependency for matplotlib, boxplot shouldn't use > mlab.prctile at all to decide where to plot the median line -- just use > numpy.median. > > Thanks, > -- > --OKB (not okblacke) > Brendan Barnwell > "Do not follow where the path may lead. Go, instead, where there is > no path, and leave a trail." > --author unknown
On Mon, Jan 3, 2011 at 3:53 PM, Paul Ivanov <piv...@gm...> wrote: Hi, Paul. Thanks for the links! Gf B, on 2011年01月03日 15:23, wrote: > > Can such a "grid of grids" be done with matplotlib? If so, could someone > > show me how? > > You'll be able to group the inner grids visually by adjusting the > spacing. As far as getting the spines to only outline the outer > grid, and not the inner grid - I think you'll have to do it > manually by hiding the appropriate spines for the inner subplots. > This sort of ad-hoc manual tweaking is what I was hoping to avoid. What would it take to implement a "true" grid-of-grids function in matplotlib? What I mean by this is a function that can arrange in a grid not only plots but also other grids. (Is this a question for the devel group?) G.
Hi, the formlayout part in the latest matplotlib requires python >= 2.5 See http://www.mail-archive.com/mat...@li.../msg19219.html That causes troubles on very popular in RHEL 5 based distributions - they use an old python 2.4 still. Can this be fixed for the next release? Best regards, Marcin