[SciPy-User] Value that compare two
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
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