[SciPy-User] Value that compare two

Florian Lindner mailinglists@xgm...
Tue Apr 2 09:15:21 CDT 2013


this is not exactly a scipy question... but I want to implement it with scipy. 

I have two datasets of shape: (n, 2), each row consists of a coordinate and a 
pressure value from experiments or simulations.

I want to compare these two sets and get some kind of integral distance value.

delta = abs(data2 - data1)
delta[:,0] = data1[:,0] # I don't want to delta the coordinates
sum_delta = np.trapz(delta[:,1], x = delta[:,0])

This works fine, but I also want to have a normalized delta value (aka 

Before I try to invent another wheel which at the end will look rather 

Is there some best practice way to compute such a value? 

If one could also give a quotable source of the algorithm it would be even 
more perfect!



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