[Numpy-discussion] Is this a bug in numpy.ma.reduce?
David Goldsmith
d.l.goldsmith at gmail.com
Mon Mar 8 14:57:03 EST 2010
How embarrassing! :O Well, as they say, 'nother set of eyes...
Thanks!
DG
On Mon, Mar 8, 2010 at 11:25 AM, Friedrich Romstedt <
friedrichromstedt at gmail.com> wrote:
> It's pretty simple, but I was stunned myself how simple. Have a look
> at line 65 of your script you provided:
>
> W = W.T
>
> This means, x <-> y. But in the for loops, you still act as if W
> wasn't transposed. I added some prints, the positions should be clear
> for you:
>
> argW.shape = (320, 200)
> i, j = (0, 0)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (0, 50, 0, 80)
> part2plot.shape = (50, 80)
> i, j = (0, 1)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (50, 100, 0, 80)
> part2plot.shape = (50, 80)
> i, j = (0, 2)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (100, 150, 0, 80)
> part2plot.shape = (50, 80)
> i, j = (0, 3)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (150, 200, 0, 80)
> part2plot.shape = (50, 80)
> i, j = (1, 0)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (0, 50, 80, 160)
> part2plot.shape = (50, 80)
> i, j = (1, 1)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (50, 100, 80, 160)
> part2plot.shape = (50, 80)
> i, j = (1, 2)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (100, 150, 80, 160)
> part2plot.shape = (50, 80)
> i, j = (1, 3)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (150, 200, 80, 160)
> part2plot.shape = (50, 80)
> i, j = (2, 0)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (0, 50, 160, 240)
> part2plot.shape = (50, 40)
> i, j = (2, 1)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (50, 100, 160, 240)
> part2plot.shape = (50, 40)
> i, j = (2, 2)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (100, 150, 160, 240)
> part2plot.shape = (50, 40)
> i, j = (2, 3)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (150, 200, 160, 240)
> part2plot.shape = (50, 40)
> i, j = (3, 0)
> j*ny/4, (j+1)*ny/4, i*nx/4, (i+1)*nx/4 = (0, 50, 240, 320)
> part2plot.shape = (50, 0)
> Traceback (most recent call last):
> File "D:\Home\Friedrich\Entwicklung\2010\David\aquarius.py", line 91, in
> ?
> ax.imshow(part2plot, extent = extent)
> File
> "D:\Programme\Programmierung\python-2.4.1\lib\site-packages\matplotlib\ax
> es.py", line 5471, in imshow
> im.autoscale_None()
> File
> "D:\Programme\Programmierung\python-2.4.1\lib\site-packages\matplotlib\cm
> .py", line 148, in autoscale_None
> self.norm.autoscale_None(self._A)
> File
> "D:\Programme\Programmierung\python-2.4.1\lib\site-packages\matplotlib\co
> lors.py", line 682, in autoscale_None
> if self.vmin is None: self.vmin = ma.minimum(A)
> File
> "D:\Programme\Programmierung\python-2.4.1\lib\site-packages\numpy\ma\core
> .py", line 3042, in __call__
> return self.reduce(a)
> File
> "D:\Programme\Programmierung\python-2.4.1\lib\site-packages\numpy\ma\core
> .py", line 3057, in reduce
> t = self.ufunc.reduce(target, **kargs)
> ValueError: zero-size array to ufunc.reduce without identity
>
> So you simply have to exchange the role of x and y in your slice
> indicing expression, and everything will work out fine, I suspect :-)
>
> Or simpy leave out the transposition? Note that in the other case,
> you also may have to consider to change to extent's axes to get it
> properly reflected.
>
> NB: With my version of matplotlib, it didn't accept the colormap, but
> when yours does, it doesn't matter.
>
> Friedrich
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>
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