# g(x)
def fit_exp(x,C,a):
    return C*1-np.exp(-2*x)

select = hist_hitmiss_y > 0

chi2_object = Chi2Regression(fit_exp, hist_hitmiss_x[select], hist_hitmiss_y[select], hist_hitmiss_sy[select])
minuit_hitmiss = Minuit(chi2_object, pedantic=False,print_level=2, C = 2., a=2.)
minuit_hitmiss.migrad();
chi2_hitmiss = minuit_hitmiss.fval
ndof_hitmiss = len(hist_hitmiss_x) - len(minuit_hitmiss.args)
prob_hitmiss = stats.chi2.sf(chi2_hitmiss, ndof_hitmiss)
C,a = minuit_hitmiss.args

C_error = minuit_hitmiss.values['C'], minuit_hitmiss.errors['C']
a_error = minuit_hitmiss.values['a'], minuit_hitmiss.errors['a']
# plot g(x)
x_axis2 = np.linspace(xmin, xmax, 500)
y_axis2 = fit_exp(x_axis2, *minuit_hitmiss.args)
#y_axis2 = fit_exp(x_axis2,C, a)
ax2.plot(x_axis2, y_axis2, 'g-', label='Fit')

# define the figure text
d_hitmiss = {'Entries': len(x_hitmiss),
           'Mean': x_hitmiss.mean(),
           'Std': x_hitmiss.std(ddof=1),
           'Chi2': chi2_hitmiss,
           'ndof': ndof_hitmiss,
           'Prob': prob_hitmiss,
           'aa': [minuit_hitmiss.values['a'], minuit_hitmiss.errors['a']],
            'C': [abs(minuit_hitmiss.values['C']), minuit_hitmiss.errors['C']]
           }
# add figure text
text2 = nice_string_output(d_hitmiss, extra_spacing=2, decimals=3)
add_text_to_ax(0.02, 0.97, text2, ax2, fontsize=14)

# add legend
ax2.legend(loc='best')
fig2.tight_layout()

# save figure
if save_plots:
    fig.savefig("Hist_fit_exp.pdf", dpi=600)

# show the figure
fig2