def test_emsrbmr_protecion_levels_increasing(self):
demands = np.array([1, 0, 0, 1, 0, 17, 2, 6])
sigmas = np.array([4, 4, 4, 4, 4, 4, 4, 4])
fares = np.array([12.97, 9.07, 8.65, 7.92, 7.66, 6.25, 6.08, 5.91])
cap = 55
y = meta_optimizers.calc_EMSRb_MR(fares, demands, sigmas)
self.assertTrue(is_increasing(y[~np.isnan(y)]))
def protection_levels(fares, demands, sigmas=None, cap=None, method='EMSRb'):
"""Calculate protection levels.
Parameters
----------
fares: np array
fares provided in decreasing order
demands: np array
demands for the fares in `fares`
cap: int, capacity
sigmas: np array
standard deviations of demands
method: str
optimization method ('EMSRb'or 'EMSRb_MR')
Returns
-------
np 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 test_emsrbmr_stochastic_demand_with_cap(self):
cap = 50
# test example data from above mentioned paper
p = meta_optimizers.calc_EMSRb_MR(self.fares, self.demands,
self.sigmas, cap)
np.testing.assert_equal(
np.array([0.0, 35.0, np.nan, np.nan, np.nan, np.nan]), p)
def protection_levels(fares, demands, sigmas=None, cap=None, method='EMSRb'):
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 test_emsrbmr_zero_demand(self):
demands = np.zeros(self.fares.shape)
p = meta_optimizers.calc_EMSRb_MR(self.fares, demands, self.sigmas)
np.testing.assert_equal(
np.array([0, np.nan, np.nan, np.nan, np.nan, np.nan]), p)
