CODEWITHSUNDEEP
pythonnumpy
Shew
Shew

Reputation: 1596

numpy get column indices where all elements are greater than threshold

I want to find the column indices of a numpy array where all the elements of the column are greater than a threshold value.

For example,

 X = array([[ 0.16,  0.40,  0.61,  0.48,  0.20],
            [ 0.42,  0.79,  0.64,  0.54,  0.52],
            [ 0.64,  0.64,  0.24,  0.63,  0.43],
            [ 0.33,  0.54,  0.61,  0.43,  0.29],
            [ 0.25,  0.56,  0.42,  0.69,  0.62]])

In the above case, if the threshold is 0.4, my result should be 1,3.

Upvotes: 3

Views: 4523

Answers (3)

Tolgahan ÜZÜN
Tolgahan ÜZÜN

Reputation: 433

x = array([[ 0.16,  0.40,  0.61,  0.48,  0.20],
        [ 0.42,  0.79,  0.64,  0.54,  0.52],
        [ 0.64,  0.64,  0.24,  0.63,  0.43],
        [ 0.33,  0.54,  0.61,  0.43,  0.29],
        [ 0.25,  0.56,  0.42,  0.69,  0.62]])

threshold = 0.3
size = numpy.shape(x)[0]
for it in range(size):
    y = x[it] > threshold
    print(y.all())

Try pls.

Upvotes: 1

b1ch0u
b1ch0u

Reputation: 1326

a generic solution using list comprehension

threshold = 0.4
rows_nb, col_nb = shape(X)
rows_above_threshold = [col for col in range(col_nb) \
    if all([X[row][col] >= threshold for row in range(rows_nb)])]

Upvotes: 0

hilberts_drinking_problem
hilberts_drinking_problem

Reputation: 11602

You can compare against the min of each column using np.where:

large = np.where(X.min(0) >= 0.4)[0]

Upvotes: 10

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