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constrain fit params to positive vals in CP

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Sander Roosendaal
2017-06-16 08:17:30 +02:00
parent b7487f1f77
commit 4b8d9d02f1
1 changed files with 2 additions and 1 deletions
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3
rowers/interactiveplots.py
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@@ -619,7 +619,7 @@ def interactive_otwcpchart(powerdf,promember=0):
# there is no Paul's law for OTW
# Fit the data to thee parameter CP model
fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3]))
fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/abs(pars[3])))
errfunc = lambda pars,x,y: fitfunc(pars,x)-y
p0 = [500,350,10,8000]
@@ -636,6 +636,7 @@ def interactive_otwcpchart(powerdf,promember=0):
p1 = [p0[0]/factor,p0[1]/factor,p0[2],p0[3]]
p1 = [abs(p) for p in p1]
fitt = pd.Series(10**(4*np.arange(100)/100.))
fitpower = fitfunc(p1,fitt)