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pythonnumpymatrixcompare
mnekkach
mnekkach

Reputation: 343

Python - Extract matrix a into matrix b

I would like to extract matrix A (4,4) into matrix b (7,4).

Below matrix :

>>> Matrix_A = numpy.array([[[10,1.5,-3.8,8.0],[20,10.2,5.2,6.7],[30,0.5,-6.2,-7.1],[40,-0.7,-0.6,-0.5]]])
>>> Matrix_A
array([[[ 10. ,   1.5,  -3.8,   8. ],
        [ 20. ,  10.2,   5.2,   6.7],
        [ 30. ,   0.5,  -6.2,  -7.1],
        [ 40. ,  -0.7,  -0.6,  -0.5]]])

>>> Matrix_B = numpy.array([[[10,2.7,4.8,-5.8],[15,-1.4,-6.4,8.1],[20,12.4,-7.1,4.9],[25,-1.5,6.2,-4.8],[30,-6.8,0.47,3.8],[35,5.4,-4.8,10.5],[40,16.2,5.7,-8.3]]])
>>> Matrix_B
array([[[ 10.  ,   2.7 ,   4.8 ,  -5.8 ],
        [ 15.  ,  -1.4 ,  -6.4 ,   8.1 ],
        [ 20.  ,  12.4 ,  -7.1 ,   4.9 ],
        [ 25.  ,  -1.5 ,   6.2 ,  -4.8 ],
        [ 30.  ,  -6.8 ,   0.47,   3.8 ],
        [ 35.  ,   5.4 ,  -4.8 ,  10.5 ],
        [ 40.  ,  16.2 ,   5.7 ,  -8.3 ]]])

The result I would like is :

    >>> Matrix_A_extract_from_Matrix_B
array([[[ 10.  ,   2.7 ,   4.8 ,  -5.8 ],
        [ 20.  ,  12.4 ,  -7.1 ,   4.9 ],
        [ 30.  ,  -6.8 ,   0.47,   3.8 ],
        [ 40.  ,  16.2 ,   5.7 ,  -8.3 ]]])

And if it is possible I would like to get a matrix R containing the rest as you can see below :

    >>> Matrix_R
array([[[ 15. ,  -1.4,  -6.4,   8.1],
        [ 25. ,  -1.5,   6.2,  -4.8],
        [ 35. ,   5.4,  -4.8,  10.5]]])

The main goal is to compare Matrix_A and Matrix_A_extract_from_Matrix_B.

My real problem is to compare matrix with thousands of lines, Matrix_A et Matrix B it is just an example to simplify the problem.

Thanks a lot for your help.

Upvotes: 0

Views: 110

Answers (1)

Kasravnd
Kasravnd

Reputation: 107347

First off all since your arrays ar 3d arrays you should squeeze the size to convert them to 2d arrays for the ease of computation.

In [27]: Matrix_A = np.squeeze(Matrix_A)

In [28]: Matrix_B = np.squeeze(Matrix_B)

Then you can use np.in1d to find the indices of the common first columns and extract them with a simple indexing:

In [29]: Matrix_B[np.in1d(Matrix_B[:, 0],Matrix_A[:, 0])]
Out[29]: 
array([[ 10.  ,   2.7 ,   4.8 ,  -5.8 ],
       [ 20.  ,  12.4 ,  -7.1 ,   4.9 ],
       [ 30.  ,  -6.8 ,   0.47,   3.8 ],
       [ 40.  ,  16.2 ,   5.7 ,  -8.3 ]])

In [30]: Matrix_B[np.logical_not(np.in1d(Matrix_B[:, 0],Matrix_A[:, 0]))]
Out[30]: 
array([[ 15. ,  -1.4,  -6.4,   8.1],
       [ 25. ,  -1.5,   6.2,  -4.8],
       [ 35. ,   5.4,  -4.8,  10.5]])

Upvotes: 1

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