On 10/31/11 8:56 PM, Dan Drake wrote:
This doesn't work:
sage: list_plot([[0, 0.7886751345948214], [0.01, 0.788675134595], [0.02,
0.788675134595], [0.03, 0.788675134595], [0.04, 0.788675134595], [0.05,
0.788675134595], [0.06, 0.788675134595], [0.07, 0.788675134595], [0.08,
0.788675134595], [0.09, 0.788675134595], [0.1, 0.788675134595]])
The y-values are (almost) all the same, but matplotlib gets stuck trying
to decide on the ticks:
/opt/sage/local/lib/python2.6/site-packages/matplotlib/axis.pyc in
get_minorticklabels(self)
1076 def get_minorticklabels(self):
1077 'Return a list of Text instances for the minor ticklabels'
-> 1078 ticks = self.get_minor_ticks()
1079 labels1 = [tick.label1 for tick in ticks if tick.label1On]
1080 labels2 = [tick.label2 for tick in ticks if tick.label2On]
/opt/sage/local/lib/python2.6/site-packages/matplotlib/axis.pyc in
get_minor_ticks(self, numticks)
1190 'get the minor tick instances; grow as necessary'
1191 if numticks is None:
-> 1192 numticks = len(self.get_minor_locator()())
1193
1194 if len(self.minorTicks)< numticks:
/opt/sage/local/lib/python2.6/site-packages/matplotlib/ticker.pyc in
__call__(self)
1424
1425 # don't create minor ticks on top of existing major ticks
-> 1426 diff = 0.5 * abs(locs[1] - locs[0])
1427 locs = [l for l in locs if (np.abs(l - majorlocs)>
diff).all()]
1428
IndexError: index out of bounds
It seems like list_plot should return something in this case. What
matplotlib magic do we need to get some kind of plot? If I plot a
constant function with plot(), it works fine.
Add a ymin and ymax as a workaround:
list_plot([[0, 0.7886751345948214], [0.01, 0.788675134595], [0.02,
0.788675134595], [0.03, 0.788675134595], [0.04, 0.788675134595], [0.05,
0.788675134595], [0.06, 0.788675134595], [0.07, 0.788675134595], [0.08,
0.788675134595], [0.09, 0.788675134595], [0.1,
0.788675134595]],ymin=0,ymax=1)
I agree that we should detect this problem when we draw a graphic with
ybounds too close to each other and turn off minor ticks or increase the
ybounds or something. Or maybe it's a bug in matplotlib we should track
down. If we offload it to the matplotlib guys, we should get a purely
matplotlib example of the problem first.
Thanks,
Jason
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