Numpy array how to get index of row minimum

Question

I have a numpy array like this one

# [[0.64809866 1.4297429  1.76778859]
#  [0.98994126 0.60583935 1.07312068]
#  [0.47607127 0.58659789 1.52184562]
#  [0.6905903  0.33424117 1.50113122]
#  [0.66848235 1.5608329  2.02750987]

I'd like to find the min of each row, but knowing by index. Like this

# [[0]
#  [1]
#  [0]
#  [1]
#  [0]]

i used np.min(dist, axis=1).reshape(-1, 1) in order to generate a matrix with the min of results, but no idea how to follow from here.

BENY · Accepted Answer · 2020-05-31 02:21:11Z

2

Try with argmin

a.argmin(axis=1).reshape(-1,1)
array([[0],
       [1],
       [0],
       [1],
       [0]])

edited May 31, 2020 at 2:21

answered May 31, 2020 at 1:47

BENY

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2 Comments

Sharki Over a year ago

I think I wasn't clear, sorry. I wanted to find the index which is the min value from X1, X2, X3 (my matrix X) so I can create a new one matrix witch every index of every minium value of every row and then concatenate to the original matrix. Sorry for my english

BENY Over a year ago

@Sharki check the update , the you need np.hstack([a,a.argmin(axis=1).reshape(-1,1)])

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