def execute(self, *options, **kwoptions):
self._fit = Fit(self._model, self.parent.x, self.parent.y)
self.result = self._fit.execute(*options, **kwoptions)
argument_dict['x'] = x
argument_dict['x0'] = x0
argument_dict['k'] = k
if hasattr(args, 'n'):
n = Parameter(value=args.n, min=0, max=args.n * 2, fixed=True)
argument_dict['n'] = n
model = harmonic_distribution(**argument_dict)
#fit = fitter.InteractiveFit2D(model, xs, ys)
guess = symfit.contrib.interactive_guess.interactive_guess.InteractiveGuess2D(
model, xs, ys)
#fit.visual_guess(1000)
#result = fit.execute(maxfev=1000)
result = guess.execute()
fit = Fit(model, xs, ys)
result = fit.execute()
print(result)
plt.scatter(xs, ys, color='b')
plt.plot(xs, model(x=xs, **result.params), color='r')
plt.show()
#
#angs = np.array(range(-180, 181), dtype=np.float64)
#probs = model(th=angs, **result.params)
#
#potentials = -kb*T*np.log(probs)
#print(potentials)
#
#potentials[potentials == np.inf] = 50
