Re: Vector division by a matrix different results when executed in Octave or Python

[Mike Miller]

On Fri, Oct 25, 2019 at 12:44:53 +0000, Denis Lessard wrote:
> import numpy as np
> a=np.array([10,10,10])
> b=np.array([[1,1,1],[2,2,2],[3,3,3]])
> print(a)
> print(b)
> c=np.divide(a,b)
> print("np.divide(a,b) = ")
> print (c)
> 
> the results:
> 
> a=[10 10 10]
> 
> 
> b=[[1 1 1]
>     [2 2 2]
>     [3 3 3]]
> 
> 
> np.divide(a,b) =
>  [[10.         10.         10.        ]
>  [ 5.          5.          5.        ]
>  [ 3.33333333  3.33333333  3.33333333]]

This is the same result as Octave's ./ operator, elementwise division.

> For octave I wrote the same small program (no numpy )
> and when I use c=a/b the results are:
> 0.71429 , 1.42847 , 2.14286

For the equivalent linear algebra in Python, use

    (np.linalg.pinv(b).T * np.matrix(a).T).T

-- 
mike

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