def protection_levels(fares, demands, sigmas=None, cap=None, method='EMSRb'):
"""Calculate protection levels.
Parameters
----------
`fares`: array of fares (decreasing order)
`demands`: array of predicted demands for the fares in `fares`
`cap`: capacity of the resource (e.g. number of seats)
`sigmas`: array of standard deviations of the demand predictions
`method`: optimization method ('EMSRb', 'EMSRb_MR')
Returns
-------
array of protection levels for each fare class
"""
check_fares_decreasing(fares)
if method == 'EMSRb':
return calc_EMSRb(fares, demands, sigmas)
elif method == 'EMSRb_MR':
prot_levels = calc_EMSRb_MR(fares, demands, sigmas, cap)
return prot_levels
else:
raise ValueError('method "{}" not supported'.format(method))
def calc_EMSRb_MR(fares, demands, sigmas=None, cap=None):
return calc_EMSRb(fares, demands, sigmas)
def test_emsrb_partly_zero_demand(self):
demands = np.array([31.2, 0, 14.8, 19.9, 0, 36.3])
sigmas = np.zeros(demands.shape)
p = optimizers.calc_EMSRb(self.fares, demands, sigmas)
self.assertEqual([0.0, 31.0, 31.0, 46.0, 66.0, 66.0], p.tolist())
def test_emsrb_nan_demand(self):
demands = np.full(self.demands.shape, np.nan)
p = optimizers.calc_EMSRb(self.fares, demands, self.sigmas)
self.assertEqual(np.zeros(demands.shape).tolist(), p.tolist())
def test_emsrb_stochastic_demand(self):
# test example data from above mentioned paper
p = optimizers.calc_EMSRb(self.fares, self.demands, self.sigmas)
self.assertEqual([0., 20., 35., 54., 80., 117.], p.tolist())