def test_table_near_vent_proc(self):
v = white_island(elc=0,
du=4,
volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020',
filename='../config_whiteIsland.JSON')
response = v.table_near_vent_proc()
df_nvp = {
'Eruption size': ["Small", "Moderate", "Large"],
'P(hourly)': [0.000477563, 0.0000477563, 0.00000530625],
'P(given eruption, exposure to near vent processes)': [0, 0.1, 1],
'P(given exposure, death from near vent processes)': [0.9, 0.9, 1],
'P(given eruption, death from near vent processes)': [0, 0.09, 1],
'P(death from near vent processes in hr)':
[0, 0.00000429807, 0.00000530625]
}
nvp_test = pd.DataFrame(data=df_nvp)
assert_frame_equal(response, nvp_test, check_dtype=False)
# no need to test table_ballis as ballis_hit is already tested
# def test_table_ballis(self):
# v = volcano(elc=0, du=4, volcano='WHAKAARI / WHITE ISLAND',
# eldate='21 January 2020', filename='../config_whiteIsland.JSON')
#
# response = v.table_stat_vpt()
def test_ballis_cal(self):
v = volcano(elc=0, du=4, volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020', filename='../config_whiteIsland.JSON')
# P of death from one ballistics: tables & calculations
df1 = v.table_phit()
p_hit = PcalsVepat(self.dr)
p_hit.load_dfs(df1, df2=None)
phit_tbl = p_hit.phit_cal()
# print(phit_tbl)
cng = white_island(elc=0, du=4, volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020', filename='../config_whiteIsland.JSON')
# generate ballistics dfs with initial input parameters
df100, df350, df750 = cng.table_ballis()
p_hit.load_dfs(phit_tbl, df100)
response = p_hit.ballis_cal(phit_tbl)
df_balls = {'Eruption size': ["Small", "Moderate", "Large"],
'P(hourly)': [0.000477563, 0.0000477563, 0.00000530625],
'Ballistic diameter (m)': [0.3, 0.3, 0.3],
'Given eruption, # ballistics in reference area': [5, 50, 200],
'P(given eruption, death from ballistics)': [0.0774268, 0.553308, 0.960186],
'P(death from ballistics in hr)': [0.00003697616873199321, 0.000026423931461547936,
0.000005094988026460348]}
ball_test = pd.DataFrame(data=df_balls)
assert_frame_equal(response, ball_test, check_dtype=False)
def test_table_phit(self):
v = white_island(elc=0,
du=4,
volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020',
filename='../config_whiteIsland.JSON')
ball_dia = [0.2, 0.3, 0.4]
person_dia = [1, 1, 1]
sq_lng = [30, 30, 30]
d1 = {
'boulder diameter': ball_dia,
'person diameter': person_dia,
'square length': sq_lng
}
d_test = pd.DataFrame(data=d1)
response = v.table_phit()
assert_frame_equal(response, d_test, check_dtype=False)
def test_table_surge(self):
cng = white_island(elc=0,
du=4,
volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020',
filename='../config_whiteIsland.JSON')
df_srg100strd, df_srg350strd, df_srg750strd, df_srg100adjc, df_srg350adjc, \
df_srg750adjc, df_srg100adjh, df_srg350adjh, df_srg750adjh = cng.table_surge()
response = df_srg100strd
df_surge = {
'Eruption size': ["Small", "Moderate", "Large"],
'P(hourly)': [0.000477563, 0.0000477563, 0.00000530625],
'P(given eruption, exposure to surge)': [0.01, 0.3, 0.4],
'P(given exposure, death from surge)': [0.95, 1, 1],
'P(given eruption, death from surge)': [0.0095, 0.3, 0.4],
'P(death from surge in hr)':
[0.00000453685, 0.0000143269, 0.0000021225]
}
surge_test = pd.DataFrame(data=df_surge)
assert_frame_equal(response, surge_test, check_dtype=False)
def test_cal_vpt(self):
v = white_island(elc=0,
du=4,
volcano='WHAKAARI / WHITE ISLAND',
eldate='21 January 2020',
filename='../config_whiteIsland.JSON')
response = v.cal_vpt()
self.assertEqual(first=response["P(eruption in period)"],
second=0.300),
self.assertEqual(first=response["P(no erupt. in period)"],
second=0.700),
self.assertEqual(first=response["P(no eruption in hr)"],
second=0.999469),
self.assertEqual(first=response["P(eruption in hr)"],
second=0.000530625),
self.assertEqual(first=response["P(small eruption in hr)"],
second=0.000477563),
self.assertEqual(first=response["P(moderate eruption in hr)"],
second=0.0000477563),
self.assertEqual(first=response["P(large eruption in hr)"],
second=0.00000530625)
site3 = base_para['Site location'][2]
#create table based on the inputs
df0 = get_inps.table_vpt()
#df0000 = get_inps.table_vpt_last()
#calculate stats based on the table
df00 = get_inps.table_stat_vpt()
#df000 = get_inps.table_stat_vpt_last()
#do calculations based on thee volcano from here onwards
if confg == "config_whiteIsland.JSON":
white = white_island(du=du,
elc=elc,
eldate=eldate,
filename=confg,
volcano=volcano)
white.doCalculationsPlots(pcals, get_inps, base_para, distance1, distance2,
distance3, site1, site2, site3, cal_type1,
cal_type2, cal_type3)
if confg == "config_ruapehu.JSON":
ruapehu = ruapehu(du=du,
elc=elc,
eldate=eldate,
filename=confg,
volcano=volcano)
ruapehu.doCalculationsPlots(pcals, get_inps, base_para, distance1,
distance2, distance3, site1, site2, site3,