find_cut

lstchain.mc.sensitivity.find_cut(events, rates, obstime, feature, low_cut, high_cut, gamma_efficiency)

Find cut in feature that corresponds to gamma efficiency. Bisection method is used to find the root of the function Number of events after cuts - gamma_efficiency*total number of events

Parameters:

events: `pd.dataframe` Dataframe of events

rates: `np.ndarray` gamma rates

obstime: `observation time`

feature: `string` feature for cut: gammaness or theta2

low_cut: `float` lower cut limit

high_cut: `float` higher cut limit

gamma_efficiency: `float` target gamma efficiency for the cut

Returns:

midpoint: float cut in feature