Python matrix: need to show where values are equal to vector

Question

I have this vector: [-3,0,2,4,7,10,12]

and this matrix:

[[ 7.   7.   4. ]
 [12.  10.  10. ]
 [-3.   7.   2. ]
 [10.   8.  12. ]
 [ nan  7.   nan]
 [ 7.   7.  10. ]
 [ 4.5  nan  2. ]
 [ 2.  12.   4. ]]

I have to show where in the matrix the the values are equal to in the vector. So it would show me which row and column 8 and 4.5 are e.g.

Any quick way to do this?

Asked By: user11658272

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Source

Answer 1

You can use numpy broadcasting to compare each value with the whole 2d array, and then get indexes using numpy.argwhere:

import numpy as np

v = np.array([-3, 0, 2, 4, 7, 10, 12])

m = np.array([[ 7. ,  7. ,  4. ],
              [12. , 10. , 10. ],
              [-3. ,  7. ,  2. ],
              [10. ,  8. , 12. ],
              [ nan,  7. ,  nan],
              [ 7. ,  7. , 10. ],
              [ 4.5,  nan,  2. ],
              [ 2. , 12. ,  4. ]]))

t = m[None,...] == v[:,None,None]

np.argwhere(t)
array([[0, 2, 0],
       [2, 2, 2],
       [2, 6, 2],
       [2, 7, 0],
       [3, 0, 2],
       [3, 7, 2],
       [4, 0, 0],
       [4, 0, 1],
       [4, 2, 1],
       [4, 4, 1],
       [4, 5, 0],
       [4, 5, 1],
       [5, 1, 1],
       [5, 1, 2],
       [5, 3, 0],
       [5, 5, 2],
       [6, 1, 0],
       [6, 3, 2],
       [6, 7, 1]], dtype=int64)

Let’s use the first row [0, 2, 0] of the result to understand what represents:

The first column is the index of the value in v that we are looking at, i.e. v[0] = -3.
The second and third column are the indexes in which the value in m is equal to such value in v, i.e. m[2,0] = -3.

If in the first column a index doesn’t appear it means that such value is not present in m (e.g. 0 is not in m) while if a index appears multiple times it means that such value is present more than once in m (e.g. the value v[2] = 2).

Answered By: FBruzzesi

Answer 2

if it’s a small array like in your example, a simple iteration over the rows and columns would do… like so:

import numpy as np

v = np.array([-3, 0, 2, 4, 7, 10, 12])
m = np.array([[ 7. ,  7. ,  4. ],
              [12. , 10. , 10. ],
              [-3. ,  7. ,  2. ],
              [10. ,  8. , 12. ],
              [ np.NaN,  7. ,  np.NaN],
              [ 7. ,  7. , 10. ],
              [ 4.5,  np.NaN,  2. ],
              [ 2. , 12. ,  4. ]])

#Iterations starts here
index_list = []
for i in range(m.shape[0]):
    for j in range(m.shape[1]):
        if m[i][j] not in v:
            index_list.append((i,j))

The output of this code (if you print index_list) is:

[(3, 1), (4, 0), (4, 2), (6, 0), (6, 1)]

Answered By: Itai Ben Amram

Python matrix: need to show where values are equal to vector

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