I'm trying to plot a subset of some data, but the y-axis limits are not updated properly after I set the x-axis limits. Is there a way to have matplotlib update the y-axis limits after setting the x-axis limits?
For example, consider the following plot:
import numpy
import pylab
pylab.plot(numpy.arange(100)**2.0)
which gives: 
which works fine. However if I want to only view the part from x=0 to x=10, the y-scaling is messed up:
pylab.plot(numpy.arange(100)**2.0)
pylab.xlim(0,10)
which gives: 
.
In the former case, the x- and y-axis are scaled properly, in the latter case, the y-axis is still scaled the same, even if the data is not plotted. How do I tell matplotlib to update the y-axis scaling?
Obvious workarounds would be to plot a subset of the data itself, or to reset the y-axis limits manually by inspecting the data, but those are both rather cumbersome.
Update:
The example above is simplified, in the more general case one has:
pylab.plot(xdata, ydata1)
pylab.plot(xdata, ydata2)
pylab.plot(xdata, ydata3)
pylab.xlim(xmin, xmax)
Setting the y-axis range manually is of course possible
subidx = N.argwhere((xdata >= xmin) & (xdata <= xmax))
ymin = N.min(ydata1[subidx], ydata2[subidx], ydata3[subidx])
ymax = N.max(ydata1[subidx], ydata2[subidx], ydata3[subidx])
pylab.xlim(xmin, xmax)
but this is cumbersome to say the least (imho). Is there a faster way to do this without manually calculating the plotranges? Thanks!
Update 2:
The function autoscale does some scaling and seems the right candidate for