Hi,
This is a know fact, you should use Python default functions if you have
only one value.
If Numpy uses math.sqrt for floatting point number, it would have to use
cmath for complex values as well. Now, I don't know if an additionnal test
will slow down Numpy, if this is the case, then we should
On the VPython list Scott Daniels suggested using try/except to deal
with the problem of sqrt(5.5) being numpy.float64 and thereby making
sqrt(5.5)*(VPython vector) not a (VPython vector), which ends up as a
big performance hit on existing programs. I tried his suggestion and did
some timing us
