Timeline for Finding local maxima/minima with Numpy in a 1D numpy array

8 events

when toggle format	what		by	license	comment
Mar 29, 2021 at 10:45	history	edited	desertnaut	CC BY-SA 4.0	deleted 44 characters in body
May 31, 2016 at 18:16	history	edited	Cleb	CC BY-SA 3.0	highltighting
Apr 25, 2011 at 15:05	comment	added	user723888		I needed something similar for a project I was working on and used the numpy.diff method mentioned above, I thought it may be helpful to mention that for my data the above code missed a few maxima and minima, by changing the middle term in both if statements to <= and >= respectively, I was able to catch all the points.
Jan 27, 2011 at 18:08	history	edited	Mike Vella	CC BY-SA 2.5	updated method to use numpy.diff instead of numpy.gradient
Jan 27, 2011 at 15:41	comment	added	Mike Vella		Yes I know, however noisy data is a different issue. For that I guess use convolve.
Jan 27, 2011 at 15:39	history	edited	Mike Vella	CC BY-SA 2.5	wrote the actual code
Jan 27, 2011 at 15:09	comment	added	Navi		Do you know how this gradient is calculated? If you have noisy data probably the gradient changes a lot, but that doesn't have to mean that there is a max/min.
Jan 27, 2011 at 13:20	history	answered	Mike Vella	CC BY-SA 2.5