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#!/usr/bin/env python
"""
Bevington & Robinson's model of dual exponential decay
References::
[5] Bevington & Robinson (1992).
Data Reduction and Error Analysis for the Physical Sciences,
Second Edition, McGraw-Hill, Inc., New York.
"""
from numpy import exp, sqrt, vstack, array, asarray
def dual_exponential(t, A, B, C, tauA, tauB):
"""
Computes dual exponential decay.
y = A exp(-t/tauA) + B exp(-t/tauB) + C
"""
t = asarray(t)
return C + A * exp(-t / tauA) + B * exp(-t / tauB)
# data from Chapter 8 of [5].
data = array(
[
[15, 775],
[30, 479],
[45, 380],
[60, 302],
[75, 185],
[90, 157],
[105, 137],
[120, 119],
[135, 110],
[150, 89],
[165, 74],
[180, 61],
[195, 66],
[210, 68],
[225, 48],
[240, 54],
[255, 51],
[270, 46],
[285, 55],
[300, 29],
[315, 28],
[330, 37],
[345, 49],
[360, 26],
[375, 35],
[390, 29],
[405, 31],
[420, 24],
[435, 25],
[450, 35],
[465, 24],
[480, 30],
[495, 26],
[510, 28],
[525, 21],
[540, 18],
[555, 20],
[570, 27],
[585, 17],
[600, 17],
[615, 14],
[630, 17],
[645, 24],
[660, 11],
[675, 22],
[690, 17],
[705, 12],
[720, 10],
[735, 13],
[750, 16],
[765, 9],
[780, 9],
[795, 14],
[810, 21],
[825, 17],
[840, 13],
[855, 12],
[870, 18],
[885, 10],
]
)
# Set uncertainty to sqrt(counts)
data = {"x": data[0], "y": data[1], "dy": sqrt(data[1])}
# coeff = {'A': 1, 'B': 1, 'C': 1, 'tauA': 1, 'tauB': 1}
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