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#!/usr/bin/env python
"""
Created on Sun Apr 15 19:47:45 2012
@author: Tillsten
"""
from numpy import exp, linspace, pi, random, sign, sin
from lmfit import Minimizer, Parameters, conf_interval, report_ci, report_fit
try:
import matplotlib.pyplot as plt
HASPYLAB = True
except ImportError:
HASPYLAB = False
p_true = Parameters()
p_true.add('amp', value=14.0)
p_true.add('period', value=5.33)
p_true.add('shift', value=0.123)
p_true.add('decay', value=0.010)
def residual(pars, x, data=None):
argu = (x*pars['decay'])**2
shift = pars['shift']
if abs(shift) > pi/2:
shift = shift - sign(shift)*pi
model = pars['amp']*sin(shift + x/pars['period']) * exp(-argu)
if data is None:
return model
return model - data
n = 2500
xmin = 0.
xmax = 250.0
noise = random.normal(scale=0.7215, size=n)
x = linspace(xmin, xmax, n)
data = residual(p_true, x) + noise
fit_params = Parameters()
fit_params.add('amp', value=13.0)
fit_params.add('period', value=2)
fit_params.add('shift', value=0.0)
fit_params.add('decay', value=0.02)
mini = Minimizer(residual, fit_params, fcn_args=(x,),
fcn_kws={'data': data})
out = mini.leastsq()
fit = residual(out.params, x)
report_fit(out)
ci, tr = conf_interval(mini, out, trace=True)
report_ci(ci)
if HASPYLAB:
names = out.params.keys()
i = 0
gs = plt.GridSpec(4, 4)
sx = {}
sy = {}
for fixed in names:
j = 0
for free in names:
if j in sx and i in sy:
ax = plt.subplot(gs[i, j], sharex=sx[j], sharey=sy[i])
elif i in sy:
ax = plt.subplot(gs[i, j], sharey=sy[i])
sx[j] = ax
elif j in sx:
ax = plt.subplot(gs[i, j], sharex=sx[j])
sy[i] = ax
else:
ax = plt.subplot(gs[i, j])
sy[i] = ax
sx[j] = ax
if i < 3:
plt.setp(ax.get_xticklabels(), visible=False)
else:
ax.set_xlabel(free)
if j > 0:
plt.setp(ax.get_yticklabels(), visible=False)
else:
ax.set_ylabel(fixed)
res = tr[fixed]
prob = res['prob']
f = prob < 0.96
x, y = res[free], res[fixed]
ax.scatter(x[f], y[f], c=1-prob[f], s=200*(1-prob[f]+0.5))
ax.autoscale(1, 1)
j += 1
i += 1
plt.show()
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