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I have a 2D numpy array:
x = [[ 1.92043482e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 2.41005634e-03 0.00000000e+00 7.19330120e-04 0.00000000e+00 0.00000000e+00 1.42886875e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 9.79279411e-05 7.88888657e-04 0.00000000e+00 0.00000000e+00 1.40425916e-01 0.00000000e+00 1.13955893e-02 7.36868947e-03 3.67091988e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.72037105e-03 1.72377961e-03 0.00000000e+00 0.00000000e+00 1.19532061e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 3.37249481e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.75111492e-03 0.00000000e+00 0.00000000e+00 1.12639313e-02] [ 0.00000000e+00 0.00000000e+00 1.10271735e-04 5.98736562e-04 6.77961628e-04 7.49569659e-04 0.00000000e+00 0.00000000e+00 2.91697850e-03 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 3.30257021e-04 2.46629275e-04 0.00000000e+00 1.87586441e-02 6.49103144e-04 0.00000000e+00 1.19046355e-04 0.00000000e+00 0.00000000e+00 2.69499898e-03 1.48525386e-02 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.18803119e-03 3.93100829e-04 0.00000000e+00 3.76245304e-04 2.79537738e-02 0.00000000e+00 1.20738457e-03 9.74669064e-06 7.18680093e-04 1.61546793e-02 3.49360861e-04 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] How do I get indices of the elements that are greater than 0.01?
Right now, I'm doing t = np.argmax(x, axis=1) to get the index of the maximum value from each and the result of it is: [21 35]. How do I achieve the above?
685
You can use argmax() to get the index of your maximum value.
In order to get the indices of N maximum values in a NumPy array, we can use the argsort() function.
Index of element in 2D array We can also use the np. where() function to find the position/index of occurrences of elements in a two-dimensional or multidimensional array. For a 2D array, the returned tuple will contain two numpy arrays one for the rows and the other for the columns.
To check if two NumPy arrays A and B are equal: Use a comparison operator (==) to form a comparison array. Check if all the elements in the comparison array are True.
You can use np.argwhere to return the indices of all the entries in an array matching a boolean condition:
>>> x = np.array([[0,0.2,0.5],[0.05,0.01,0]]) >>> np.argwhere(x > 0.01) array([[0, 1], [0, 2], [1, 0]]) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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