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I want to find all the maximums and their index in a numpy array.

I am looking for something simple. I started something like data[1:] < data[:-1] no idea how to get 20 and 30 and their index 2 and 7. 

import numpy as np data = np.array([0,1,20,1,0,1,2,30,2,1,0]) A = data[1:] < data[:-1]

EDIT: Argmax and findpeaks sound difficult (find peaks gives you min and max for instance). I did a np.diff and a loop and I have my index eventhough I try to avoid using loop

import numpy as np def maximum_index(data): data = np.diff(data) index_max = [] for index in range(len(data)-1): if data[index] > 0 and data[index+1] < 0: index_max.append(index+1) return np.asarray(index_max) data = np.array([0,1,9,1,0,1,2,9,2,1,0]) result_max = maximum_index(data)

Thank you

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You can use numpy.argsort as follows:

import numpy as np data = np.array([0,1,20,1,0,1,2,30,2,1,0]) N = 2 # number of maxima idx = np.argsort(data)[-N:] idx array([2, 7], dtype=int64) data[idx] array([20, 30])

If you don't know the number of maxima, you can use scipy.signal.find_peaks:

from scipy.signal import find_peaks idx = find_peaks(data)[0] idx array([2, 7], dtype=int64) data[idx] array([20, 30])
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you can try below code 

max_data_pos=np.argmax(data) #Find position of max elelemt max_data_val=data[max_data_pos] #Find Max Valuse second_max_data_pos=np.argmax(np.delete(data,max_data_pos)) #Find position of second max elelemt secondmax_data_val=data[second_max_data_pos] #Find Max Valuse

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