This script lives in /reg/g/psdm/tutorials/examplePython3/cfd.py and demonstrates how to run a constant-fraction-discriminator algorithm on a waveform (similar to a peak-finder for area-detectors).

from psana import *
from pypsalg import find_edges
ds = DataSource('exp=amotut13:run=206')
det = Detector('AmoETOF.0:Acqiris.0')
import matplotlib.pyplot as plt
for nevent,evt in enumerate(ds.events()):
    waveforms,times = det.raw(evt)
    # find edges for channel 0                                                  
    # parameters: baseline, threshold, fraction, deadtime, leading_edges        
    edges = find_edges(waveforms[0],0.0,-0.05,1.0,5.0,True)
    # pairs of (amplitude,sampleNumber)                                         
    print(edges)
    break


Sven Augustin suggested this code to get actual times instead of sample numbers for the edges:

import pypsalg

def CFD(x, y, baseline=0.0, threshold=0.1, fraction=1.0, deadtime=5.0, leading_edges=True):
    if x is None or y is None:
        return None
    edges = pypsalg.find_edges(y, baseline, threshold, fraction, deadtime, leading_edges)
    if not edges.size:
        return None
    amplitudes, sample_numbers = edges.T
    # test whether the last element was found to be a peak, if so ignore it
    if sample_numbers[-1] >= len(y) - 1:
        amplitudes = amplitudes[:-1]
        sample_numbers = sample_numbers[:-1]
    # separate integer index and linearly interpolated fraction in between
    indices = sample_numbers.astype(int)
    linterp = sample_numbers % 1
    # get x step size for each index and calculate interpolated x axis
    steps = x[1:][indices] - x[:-1][indices]
    times = x[indices] + steps * linterp
    return times, amplitudes
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