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]
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