mdl.c1.thaw()
mdl.c2 = 0
mdl.c2.freeze()
dump("f.fit()")
report("mdl")
stat1 = f.calc_stat()
print("Statistic: order 1 = {:.3f} order 2 = {:.3f}".format(stat1, stat2))
mplot2 = ModelPlot()
mplot2.prepare(d, mdl)
mplot.plot()
mplot2.overplot()
savefig("model_comparison.png")
xgrid = np.linspace(0, 20, 21)
y1 = mdl(xgrid)
mdl.c0 = res.parvals[0]
mdl.c1 = 0
mdl.c2 = res.parvals[1]
y2 = mdl(xgrid)
plt.clf()
plt.plot(xgrid, y2, label='order=2')
plt.plot(xgrid, y1, label='order=1')
plt.legend();
plt.title("Manual evaluation of the models")
savefig("model_comparison_manual.png")
report("mdl([-100])")
report("mdl([234.56])")
mdl.c1.thaw()
mdl.c2 = 0
mdl.c2.freeze()
dump("f.fit()")
report("mdl")
stat1 = f.calc_stat()
print("Statistic: order 1 = {:.3f} order 2 = {:.3f}".format(stat1, stat2))
mplot2 = ModelPlot()
mplot2.prepare(d, mdl)
mplot.plot()
mplot2.overplot()
savefig("model_comparison.png")
xgrid = np.linspace(0, 20, 21)
y1 = mdl(xgrid)
mdl.c0 = res.parvals[0]
mdl.c1 = 0
mdl.c2 = res.parvals[1]
y2 = mdl(xgrid)
plt.clf()
plt.plot(xgrid, y2, label='order=2')
plt.plot(xgrid, y1, label='order=1')
plt.legend()
plt.title("Manual evaluation of the models")
savefig("model_comparison_manual.png")
dplot.prepare(d)
from sherpa.models.basic import Const1D, Exp
plateau = Const1D('plateau')
rise = Exp('rise')
mdl = plateau / (1 + rise)
report("mdl")
rise.ampl.freeze()
report("mdl")
from sherpa.plot import ModelPlot
mplot = ModelPlot()
mplot.prepare(d, mdl)
plt.subplot(2, 1, 1)
mplot.plot(clearwindow=False)
plt.subplot(2, 1, 2)
dplot.plot(clearwindow=False)
plt.title('')
savefig("model_data_before_fit.png")
from sherpa.stats import Chi2
from sherpa.fit import Fit
f = Fit(d, mdl, stat=Chi2())
report("f")
print("Starting statistic: {}".format(f.calc_stat()))
fitres = f.fit()
report("fitres.format()")
