I recently thought about implementing more functions used by non-math
people (I'm an Electronic Engineering student).
I started by trying to make a Bode plot, but after a lot of digging to
find how to make subplots and how to use logarithmic scale in plot(), I
found that if applying that kind of scale can turn plot() unusable.
The first problem is that the adaptive choosing of points just considers
linear scale, so the points get too much spaced apart in the beginning
of the plot and too close in the end.
The second problem relates to the axis, which, for the same reason,
isn't located right.
to test it, one can try:
p=plot(x,marker='.')
f=pylab.figure()
f.gca().set_xscale('log')
p.save(figure=f)
So, I intend to implement the changes in plot() to support it.
For that, I ask YOU (uncle sam pointing finger) sage gurus how to better
implement that: would it be better to try check if the user used a
custom figure() with different axis or would it be better to add another
kwarg like log="xy" where "x" would make the x axis logarithmic and "y"
likewise for the y axis, avoiding the need for the user to deal with
matplotlib's figure()?
Ronan Paixão
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