when 'myArray * 'myObject' is not equal to 'myObject' * 'myArray'

[Duim]

Although I'm sure somewhere this issue is discussed in this (great)
group, I didn't know the proper search words for it (although I
tried).

I'm using python (2.6) scientifically mostly, and created a simple
class to store time series (my 'Signal' class).
I need this class to have a possibility to get multiplied by an array,
but pre and post multiplication have different mathematical outcomes
( basically A* B != B*A ) .

Post multiplication by an array works fine defining __mul__ in the
Signal class, but pre multiplication does not. It keeps trying to
multiply all elements separately instead to send this array to my
__rmul__ function.

How can I fix this without the need for a separate
'multiplysignal(A,B)' function?
To make things easy I've made a small example:

[code]
import numpy as np

class Signal(object):
    def __init__(self,data,dt):
        self.data=data
        self.dt=dt

    def Nch(self):
        return self.data.shape[0]

    def __mul__(self,other):
        print 'mul called! ',other

        if isinstance(other,type(np.array([1,2]))):
            #it's an array: use dot product:
            return Signal(np.dot(self.data,other),self.dt)


        if other.__class__.__name__=='Signal':
            # do something
            pass


    def __rmul__(self,other):
        print 'rmul called! ',other

        if isinstance(other,type(np.array([1,2]))):
            #it's an array: use dot product:
            return Signal(np.dot(other,self.data),self.dt)


        if other.__class__.__name__=='Signal':
            # do something
            pass

mySignal=Signal(np.array([[1.,2],[4,5]]),1.)
myArray=np.array([[1.,2.],[4.,3.]])

result_mul = mySignal*myArray
result_rmul = myArray*mySignal #called 4 times for all members once!

#result:
#mul called!  [[ 1.  2.]
# [ 4.  3.]]
#rmul called!  1.0
#rmul called!  2.0
#rmul called!  4.0
#rmul called!  3.0
[/code]