[SciPy-User] Use of numpy functions instead builtins

[Paul Anton Letnes]

On 3. apr. 2010, at 03.02, Florian Lindner wrote:

> Hello,
> I've code that have a lot longer formulas like this on:
> 
> tan_theta = ( 2 * (1/tan(sa))*(Ma**2*sin(sa)**2-1)) / ( 2+Ma**2 * (self.f_prop.kappa+1 - 2 * sin(sa)**2) )
> 
> all variables are scalars so it works fine with the stuff I get from the math package. Since I"m using scipy anyway in my app I wonder if there is any advantage using the numpy math functions (sin, cos, ..., exp, power). Is there any advantage using them over the python bultins?
> 

Hi,

I'm guessing this is not usually a problem, but I've also come across bugs in the python cmath library, so I don't trust it anymore. I'm not sure how often it is a problem, but it's damn annoying if you keep debugging and it's the library functions that are wrong.

Oh, and yes, the corresponding numpy functions were right.

cheers,
Paul.