def test_manual_calcs():
# where is this script?
homedir = os.path.dirname(os.path.abspath(__file__))
popfile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_gpw.flt')
urbfile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_urban.bil')
isofile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_isogrid.bil')
ccode = 'ID'
timeofday = 'day'
density = URBAN
pop = 100000
mmi = 8.5
popyear = 2016
semi = SemiEmpiricalFatality.fromDefault()
semi.setGlobalFiles(popfile, popyear, urbfile, isofile)
# let's do the calculations "manually" by getting all of the data and doing our own multiplications
workforce = semi.getWorkforce(ccode)
res, nonres, outside = pop_dist(pop, workforce, timeofday, density)
resinv, nonresinv = semi.getInventories(ccode, density)
res_collapse = semi.getCollapse(ccode, mmi, resinv)
nonres_collapse = semi.getCollapse(ccode, mmi, nonresinv)
res_fat_rates = semi.getFatalityRates(ccode, timeofday, resinv)
nonres_fat_rates = semi.getFatalityRates(ccode, timeofday, nonresinv)
res_fats = res * resinv * res_collapse * res_fat_rates
nonres_fats = nonres * nonresinv * nonres_collapse * nonres_fat_rates
# print(res_fats)
# print(nonres_fats)
fatsum = int(res_fats.sum() + nonres_fats.sum())
print('Testing that "manual" calculations achieve tested result...')
assert fatsum == 383
print('Passed.')
def test_work():
popi = 2000
wforce = pd.Series({'WorkForceTotal': 0.5,
'WorkForceAgricultural': 0.5,
'WorkForceIndustrial': 0.25,
'WorkForceServices': 0.25})
timeofday = 'day'
dclass = URBAN
res, nonres, outdoor = pop_dist(popi, wforce, timeofday, dclass)
np.testing.assert_almost_equal(res, 410)
np.testing.assert_almost_equal(nonres, 865)
np.testing.assert_almost_equal(outdoor, 725)
def work_tests():
popi = 2000
fwf = 0.5
f_ind = 0.25
fser = 0.25
fagr = 0.5
timeofday = 'day'
dclass = URBAN
res, nonres, outdoor = pop_dist(popi, fwf, f_ind, fser, fagr, timeofday,
dclass)
np.testing.assert_almost_equal(res, 410)
np.testing.assert_almost_equal(nonres, 865)
np.testing.assert_almost_equal(outdoor, 725)
def model_test_single():
homedir = os.path.dirname(
os.path.abspath(__file__)) #where is this script?
invfile = os.path.join(homedir, '..', 'data', 'semi_inventory.hdf')
colfile = os.path.join(homedir, '..', 'data', 'semi_collapse_mmi.hdf')
fatfile = os.path.join(homedir, '..', 'data', 'semi_casualty.hdf')
workfile = os.path.join(homedir, '..', 'data', 'semi_workforce.hdf')
growthfile = os.path.join(homedir, '..', 'data',
'WPP2015_POP_F02_POPULATION_GROWTH_RATE.xls')
popfile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_gpw.flt')
urbfile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_urban.bil')
isofile = os.path.join(homedir, '..', 'data', 'eventdata', 'northridge',
'northridge_isogrid.bil')
ccode = 'ID'
timeofday = 'day'
density = URBAN
pop = 100000
mmi = 8.5
popyear = 2016
semi = SemiEmpiricalFatality.fromDefault()
semi.setGlobalFiles(popfile, popyear, urbfile, isofile)
#let's do the calculations "manually" by getting all of the data and doing our own multiplications
workforce = semi.getWorkforce(ccode)
res, nonres, outside = pop_dist(pop, workforce, timeofday, density)
resinv, nonresinv = semi.getInventories(ccode, density)
res_collapse = semi.getCollapse(ccode, mmi, resinv)
nonres_collapse = semi.getCollapse(ccode, mmi, nonresinv)
res_fat_rates = semi.getFatalityRates(ccode, timeofday, resinv)
nonres_fat_rates = semi.getFatalityRates(ccode, timeofday, nonresinv)
res_fats = res * resinv * res_collapse * res_fat_rates
nonres_fats = nonres * nonresinv * nonres_collapse * nonres_fat_rates
#print(res_fats)
#print(nonres_fats)
fatsum = int(res_fats.sum() + nonres_fats.sum())
print('Testing that "manual" calculations achieve tested result...')
assert fatsum == 383
print('Passed.')
loss, resfat, nresfat = make_test_semi_model(ccode, timeofday, density,
pop, mmi)
print(
'Testing that "manual" calculations achieve same results as grid calculations...'
)
assert fatsum == loss
print('Passed.')