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fixes utils.detect2peaks not detecting peaks at borders #88

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Nov 13, 2024
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fixes utils.detect2peaks not detecting peaks at borders #88

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16 changes: 14 additions & 2 deletions amep/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -959,6 +959,11 @@ def detect2peaks(
Detects the two highest peaks in the given data after smoothing it
with a running average. Includes also global maxima at the boundaries.

Notes
-----
This method only produces correct results if there are at most two
peaks present! Please check the behavior in your individual case.

Parameters
----------
xdata : np.ndarray
Expand All @@ -983,7 +988,7 @@ def detect2peaks(
avydata : np.ndarray
Averaged y values.
avxdata : np.ndarray
Averaged x values (same shape as avxdata).
Averaged x values (same shape as avydata).

Examples
--------
Expand Down Expand Up @@ -1021,6 +1026,12 @@ def detect2peaks(
# smooth data with running mean
avxdata = runningmean(xdata, nav, mode='valid')
avydata = runningmean(ydata, nav, mode='valid')

# detecting maxima at the borders
# adding "virtual" points at the beginning and end of data
dx=avxdata[1]-avxdata[0]
avxdata=np.concatenate(([avxdata[0]-dx], avxdata, [avxdata[-1]+dx]))
avydata=np.concatenate(([np.min(avydata)], avydata, [np.min(avydata)]))

# determine peaks in averaged data
ind, other = signal.find_peaks(avydata, height=height, distance=distance, width=width)
Expand Down Expand Up @@ -1053,7 +1064,8 @@ def detect2peaks(
high = [np.max(avxdata[ind[largest]]),\
avydata[ind[largest]][np.argmax(avxdata[ind[largest]])]] # high x peak

return low, high, avydata, avxdata
# remove virtual points in avxdata and avydata
return low, high, avydata[1:-1], avxdata[1:-1]



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