def test_summary_file_written(self, data):
loc_size = data.draw(integers(10, 20))
# Create Mock keys_data
keys_data = data.draw(
keys(size=loc_size,
from_area_peril_ids=just(1),
from_vulnerability_ids=just(1),
from_messages=just('str')))
# Create Mock location_data
loc_data = data.draw(
min_source_exposure(
size=loc_size,
from_building_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_other_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_contents_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_bi_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000))))
# Prepare arguments for write_exposure_summary
with TemporaryDirectory() as tmp_dir:
keys_fp = os.path.join(tmp_dir, 'keys.csv')
successes = [k for k in keys_data if k['status'] in ['success']]
keys_errors_fp = os.path.join(tmp_dir, 'keys_errors.csv')
nonsuccesses = [
k for k in keys_data if k['status'] not in ['success']
]
write_keys_files(keys=successes,
keys_file_path=keys_fp,
keys_errors=nonsuccesses,
keys_errors_file_path=keys_errors_fp)
location_fp = os.path.join(tmp_dir, 'location.csv')
write_source_files(exposure=loc_data, exposure_fp=location_fp)
location_df = get_location_df(location_fp)
exposure_summary_fp = write_exposure_summary(
tmp_dir, location_df, keys_fp, keys_errors_fp,
get_default_exposure_profile())
self.assertTrue(os.path.isfile(exposure_summary_fp))
with open(exposure_summary_fp) as f:
data = json.load(f)
loc_df = pd.DataFrame.from_dict(loc_data)
loc_df['loc_id'] = get_ids(
loc_df, ['portnumber', 'accnumber', 'locnumber'])
keys_df = pd.DataFrame.from_dict(keys_data)
exp_summary = get_exposure_summary(loc_df, keys_df)
self.assertDictAlmostEqual(data, exp_summary)
def test_single_peril__totals_correct(self, data):
# Shared Values between Loc / keys
loc_size = data.draw(integers(10, 20))
supported_cov = data.draw(st.lists(integers(1,4), unique=True, min_size=1, max_size=4))
perils = 'WTC'
# Create Mock keys_df
keys_data = list()
for i in supported_cov:
keys_data += data.draw(keys(
size=loc_size,
from_peril_ids=just(perils),
from_coverage_type_ids=just(i),
from_area_peril_ids=just(1),
from_vulnerability_ids=just(1),
from_messages=just('str')))
keys_df = pd.DataFrame.from_dict(keys_data)
# Create Mock location_df
loc_df = pd.DataFrame.from_dict(data.draw(min_source_exposure(
size=loc_size,
from_location_perils_covered=just(perils),
from_location_perils=just(perils),
from_building_tivs=integers(1000, 1000000),
from_other_tivs=integers(100, 100000),
from_contents_tivs=integers(50, 50000),
from_bi_tivs=integers(20, 20000))))
loc_df['loc_id'] = get_ids(loc_df, ['portnumber', 'accnumber', 'locnumber'])
# Run exposure_summary
exp_summary = get_exposure_summary(
exposure_df=loc_df,
keys_df=keys_df,
)
# Run Gul Proccessing
gul_inputs = get_gul_input_items(loc_df, keys_df)
gul_inputs = gul_inputs[gul_inputs['status'].isin(OASIS_KEYS_STATUS_MODELLED)]
# Fetch expected TIVS
tiv_portfolio = loc_df[['buildingtiv', 'othertiv', 'bitiv', 'contentstiv']].sum(1).sum(0)
tiv_modelled = gul_inputs['tiv'].sum()
tiv_not_modelled = tiv_portfolio - tiv_modelled
# Check TIV values
self.assertEqual(tiv_portfolio, exp_summary['total']['portfolio']['tiv'])
self.assertEqual(tiv_modelled, exp_summary['total']['modelled']['tiv'])
self.assertEqual(tiv_not_modelled, exp_summary['total']['not-modelled']['tiv'])
# Check number of locs
self.assertEqual(len(loc_df), exp_summary['total']['portfolio']['number_of_locations'])
self.assertEqual(len(gul_inputs.loc_id.unique()), exp_summary['total']['modelled']['number_of_locations'])
def test_multi_perils__multi_covarage(self, data):
loc_size = data.draw(integers(10, 20))
supported_cov = data.draw(
st.lists(integers(1, 4), unique=True, min_size=1, max_size=4))
perils = data.draw(
st.lists(st.text(alphabet=(string.ascii_letters + string.digits),
min_size=2,
max_size=6),
min_size=2,
max_size=6,
unique=True))
# Create Mock keys_df
keys_data = list()
for c in supported_cov:
for p in perils:
keys_data += data.draw(
keys(size=loc_size,
from_peril_ids=just(p),
from_coverage_type_ids=just(c),
from_area_peril_ids=just(1),
from_vulnerability_ids=just(1),
from_messages=just('str')))
keys_df = pd.DataFrame.from_dict(keys_data)
perils_returned = keys_df.peril_id.unique().tolist()
# Create Mock location_df
loc_df = pd.DataFrame.from_dict(
data.draw(
min_source_exposure(
size=loc_size,
from_location_perils_covered=st.sampled_from(perils),
from_location_perils=st.sampled_from(perils),
from_building_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_other_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_contents_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)),
from_bi_tivs=st.one_of(st.floats(1.0, 1000.0),
st.integers(1, 1000)))))
loc_df['loc_id'] = get_ids(loc_df,
['portnumber', 'accnumber', 'locnumber'])
# Run Summary output check
exp_summary = get_exposure_summary(exposure_df=loc_df, keys_df=keys_df)
gul_inputs = get_gul_input_items(loc_df, keys_df)
self.assertSummaryIsValid(loc_df, gul_inputs, exp_summary,
perils_returned)
