def sample_damage_interval(self, dmg, damage_interval_keys, num_samples,
seed):
"""
Dylan Sanderson code to calculate the Monte Carlo simulations of damage state.
Args:
dmg (dict): Damage results that contains dmg interval values.
damage_interval_keys (list): Keys of the damage states.
num_samples (int): Number of simulation.
seed (int): Random number generator seed for reproducibility.
Returns:
dict: A dictionary of damage states.
"""
ds = {}
random_generator = np.random.RandomState(seed)
for i in range(num_samples):
# each sample should have a unique seed
rnd_num = random_generator.uniform(0, 1)
prob_val = 0
flag = True
for ds_name in damage_interval_keys:
if rnd_num < prob_val + AnalysisUtil.float_to_decimal(
dmg[ds_name]):
ds['sample_{}'.format(i)] = ds_name
flag = False
break
else:
prob_val += AnalysisUtil.float_to_decimal(dmg[ds_name])
if flag:
print("cannot determine MC damage state!")
return ds
def test_fragility_set_small_overlap():
fragility_set = get_fragility_set("fragility_curve.json")
# Test Case 1 - single overlap
limit_states = collections.OrderedDict([("LS_0", 0.9692754643),
("LS_1", 0.0001444974),
("LS_2", 0.0004277083)])
limit_states = AnalysisUtil.float_dict_to_decimal(limit_states)
damage_states = fragility_set._3ls_to_4ds(limit_states)
assert damage_states['DS_0'] == AnalysisUtil.float_to_decimal(0.0307245357) and \
damage_states['DS_1'] == AnalysisUtil.float_to_decimal(0.968847756) and \
damage_states['DS_2'] == AnalysisUtil.float_to_decimal(0.0) and \
damage_states['DS_3'] == AnalysisUtil.float_to_decimal(0.0004277083)
# Test Case 2 - double overlap
limit_states = collections.OrderedDict([("LS_0", 0.12), ("LS_1", 0.64),
("LS_2", 0.8)])
limit_states = AnalysisUtil.float_dict_to_decimal(limit_states)
damage_states = fragility_set._3ls_to_4ds(limit_states)
assert damage_states['DS_0'] == AnalysisUtil.float_to_decimal(0.2) and \
damage_states['DS_1'] == AnalysisUtil.float_to_decimal(0.0) and \
damage_states['DS_2'] == AnalysisUtil.float_to_decimal(0.0) and \
damage_states['DS_3'] == AnalysisUtil.float_to_decimal(0.8)