Python finding local maxima minima with numpy in a 1d numpy array
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sure! in python, you can use the `numpy` library to find local maxima and minima in a 1d numpy array. local maxima are the peaks in the data where the value is greater than its neighbors, and local minima are the valleys where the value is smaller than its neighbors.
here's a step-by-step tutorial on how to find local maxima and minima using numpy in a 1d numpy array:
1. import the numpy library:
2. create a 1d numpy array:
3. find the local maxima using numpy:
4. find the local minima using numpy:
5. print the local maxima and minima:
in this example, `np.diff` calculates the difference between adjacent elements, `np.sign` returns the sign of each element (1 for positive, 0 for zero, -1 for negative), and `(np.diff(...) 0).nonzero()[0] + 1` finds the indices of local maxima. similarly, `(np.diff(...) 0).nonzero()[0] + 1` finds the indices of local minima.
here's the complete code example:
when you run this code, it will output the indices of local maxima and minima in the given 1d numpy array.
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