I have an array
[
-670.0790336045966,
-670.079352863881,
-664.7769001654013,
-662.655094599744,
-662.6557553135007,
-662.6551031804399,
-667.966652577584,
-670.0779722837389,
-670.0789732042002]
.
I want to detect the changes but only 1 time per edge and remove noise as picture black circle are noises
I expect [1, 3, 5, 7]. But it showed [1, 2, 3, 5, 6, 7].
I tried:
Python
differences = np.abs(np.diff(array_L))
threshold = 1
distance = 1
change_points = np.where((differences > threshold) & (np.arange(len(array_L)-1) % distance == 0))[0] + 1
change_points1 = np.where((differences > threshold) & (np.arange(len(array_L)-1) % distance == 0))[0]