I have data from experiments that I would like to differentiate into two zones. The data represents the time between events, so the two zones represent events that occur faster and the other events that occur slower, and I would like to find a separation between the two. The data comes from experiments, so some data can be easy to see visually where the separation approximately is, but in other experiments not so easy.
For example, the following example plotted with python:
import numpy as np
import matplotlib.pyplot as plt
data1 = [0.8253909999999998, 0.8804020000000001, 0.14202099999999973, 0.7727520000000005, 1.1040220000000005, 0.10714699999999944, 0.5750040000000016, 0.7876929999999973, 0.8980040000000002, 1.1478490000000008, 0.44635099999999994, 1.052067000000001, 0.4327469999999991, 0.3272960000000005, 0.26918099999999967, 0.3854459999999982, 0.1827140000000007, 0.8867760000000011, 0.7774879999999982, 0.21082900000000038, 0.6758939999999996, 0.4335760000000022, 0.6791699999999992, 0.7758439999999993, 0.15755200000000258, 0.1414289999999987, 0.36975599999999886, 0.8993549999999999, 0.6577640000000002, 1.043728999999999, 0.19952800000000082, 0.12645200000000045, 0.3454990000000002, 0.9054520000000004, 0.7165229999999987, 0.9425269999999983, 0.7159280000000052, 0.7413279999999958, 0.12669900000000212, 0.2822880000000012, 0.3690029999999993, 0.7246340000000018, 0.4718329999999966, 0.7580859999999987, 0.744059, 0.19344999999999857, 0.12031900000000206, 0.47543600000000197, 0.437542999999998, 0.44232000000000227, 0.5250109999999992, 0.17673200000000122, 0.2440649999999991, 0.31524799999999686, 0.7674680000000009, 0.7837700000000041, 1.1910290000000003, 0.14404899999999543, 0.21560399999999902, 0.19931500000000568, 0.27113699999999596, 0.728234999999998, 0.5061920000000057, 0.6459329999999994, 0.7817450000000008, 0.8265129999999985, 0.17931199999999592, 0.30208600000000274, 0.32583699999999993, 0.41771599999999864]
n, bins, patches = plt.hist(x=data1, bins='auto', color='#0504aa',
alpha=0.7, rwidth=0.9,)
plt.grid(axis='y', alpha=0.35)
plt.xlabel('time [s]')
plt.ylabel('Frequency')
plt.title('Hit interval')
The separation value could be approximately at time=0.6 but with another experiment, for example,
data2 = [0.2571259999999995, 1.5822640000000003, 0.1466390000000004, 0.32824299999999873, 0.32104400000000055, 2.369047, 0.2478510000000007, 0.2485389999999974, 0.303955000000002, 0.2653870000000005, 2.5117650000000005, 0.3355749999999986, 0.292663000000001, 1.1105540000000005, 0.2860239999999976, 0.33515799999999984, 1.562253000000002, 0.28992900000000077, 0.2852049999999977, 0.34392700000000076, 1.8210219999999993, 0.329422000000001, 0.28030199999999894, 2.359422000000002, 0.2672719999999984, 0.24663200000000174, 0.2700189999999978, 0.3540030000000023, 1.2573369999999997, 0.5001749999999987, 0.310769999999998, 0.3096180000000004, 1.9164280000000034, 0.2525890000000004, 0.34174199999999644, 2.2837689999999995, 0.24895200000000273, 0.2644960000000012, 1.0374629999999954, 0.24909000000000248, 0.2702510000000018, 1.7076319999999967, 0.21309300000000064, 0.3227109999999982, 1.1984310000000065, 0.27072999999999325, 0.2533940000000001, 1.6089630000000028, 0.2667160000000024, 0.25072399999999817, 1.0275359999999978, 0.3001330000000024, 0.22650500000000306, 0.30086399999999713, 0.3070420000000027]
Visually, in a histogram representation seems more difficult to find separation,
I would like to find a way to compute the separation in two zones.