----- Original Message ----
From: Robert Kern
I ran across what seems to be a change in how numerics are handled in Python 2.6 or Numpy 1.3.0 or both, I'm not sure. I've recently switched from using Python 2.4 and Numpy 1.0.3 to using the Python 2.6 and Numpy 1.3.0 that comes with SAGE which is a large mathematical package. But the issue seems to be a Python one, not a SAGE one.
Here is a short example of code that gives the new behavior:
# ---- Return the angle between two vectors ------------ def get_angle(v1,v2): '''v1 and v2 are 1 dimensional numpy arrays''' # Make unit vectors out of v1 and v2 v1norm=sqrt(dot(v1,v1)) v2norm=sqrt(dot(v2,v2)) v1unit=v1/v1norm v2unit=v2/v2norm ang=acos(dot(v1unit,v2unit)) return ang
When using Python 2.6 with Numpy 1.3.0 and v1 and v2 are parallel the dot product of v1unit and v2unit sometimes gives 1.0+epsilon where epsilon is the smallest step in the floating point numbers around 1.0 as given in the sys module. This causes acos to throw a Domain Exception. This does not happen when I use Python 2.4 with Numpy 1.0.3.
acos() is not a numpy function. It comes from the stdlib math module. Python 2.6 tightened up many of the border cases for the math functions. That is probably where the behavior difference comes from. -- Robert Kern Thanks, Robert. I thought some math functions were replaced by numpy functions that can also operate on arrays when using from numpy import *. That's the reason I asked about numpy. I know I should change this. But your explanation sounds like it is indeed in Py 2.6 where they tightened things up. I'll just leave the check for exceptions in place and use it more often now. -- Lou Pecora, my views are my own. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion