def catchment_ento(cb, catch):
arab_times, arab_spline = catch_3_yr_spline(catch, "arabiensis")
funest_times, funest_spline = catch_3_yr_spline(catch, "funestus")
# Arabiensis
set_species_param(
cb, 'arabiensis', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 3,
"Capacity_Distribution_Over_Time": {
"Times": arab_times,
"Values": arab_spline
},
"Max_Larval_Capacity": pow(10, 8.5)
}
})
# Funestus
set_species_param(
cb, 'funestus', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 3,
"Capacity_Distribution_Over_Time": {
"Times": funest_times,
"Values": funest_spline
},
"Max_Larval_Capacity": pow(10, 7.5)
}
})
def test_species_params(self):
self.assertEqual(
vs.get_species_param(self.cb, 'arabiensis', 'Immature_Duration'),
2)
vs.set_species_param(self.cb, 'arabiensis', 'Egg_Batch_Size', 123)
self.assertEqual(
vs.get_species_param(self.cb, 'arabiensis', 'Egg_Batch_Size'), 123)
vs.set_larval_habitat(
self.cb,
{'arabiensis': {
'TEMPORARY_RAINFALL': 123,
'CONSTANT': 456
}})
self.assertDictEqual(
vs.get_species_param(self.cb, 'arabiensis',
'Larval_Habitat_Types'), {
'TEMPORARY_RAINFALL': 123,
'CONSTANT': 456
})
vs.scale_all_habitats(self.cb, 2)
self.assertDictEqual(
vs.get_species_param(self.cb, 'arabiensis',
'Larval_Habitat_Types'), {
'TEMPORARY_RAINFALL': 246,
'CONSTANT': 912
})
funestus_habitat = vs.get_species_param(
self.cb, 'funestus', 'Larval_Habitat_Types')['WATER_VEGETATION']
self.assertEqual(funestus_habitat, 4e7)
def set_ento(cb):
cb.update_params({
"Climate_Model": "CLIMATE_CONSTANT",
"Base_Air_Temperature": 27,
"Base_Land_Temperature": 27,
})
cb.update_params({'Vector_Species_Names': ['funestus']})
set_species_param(
cb,
'funestus',
'Larval_Habitat_Types',
{
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5,
212.917, 243.333, 273.75, 304.167, 334.583
],
"Values": [
0.01,
0.01,
0.01,
0.01,
0.2,
0.5,
0.5,
0.5,
1.0, #oct
1.0, #sept
0.35,
0.01
]
# "Values": [
# 0.01,
# 0.01,
# 0.01,
# 0.2,
# 0.8,
# 1.0,
# 1.0,
# 1.0,
# 0.5,
# 0.2,
# 0.01,
# 0.01
# ]
},
"Max_Larval_Capacity": 10.**9
},
# "WATER_VEGETATION": 10.**9
})
def map_sample_to_model_input(cb, sample):
set_species_param(cb,
'arabiensis',
'Larval_Habitat_Types', {
# "CONSTANT": 10.**sample['arab_constant_scale'],
"CONSTANT": 10.**6.5,
"TEMPORARY_RAINFALL": 10.**sample['arab_rainfall_scale']
})
# Funestus
set_species_param(cb,
'funestus',
'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [
0.0,
30.417,
60.833,
91.25,
121.667,
152.083,
182.5,
212.917,
243.333,
273.75,
304.167,
334.583
],
"Values": [
0.0,
0.0,
0.0,
0.2,
0.8,
1.0,
1.0,
1.0,
0.5,
0.2,
0.0,
0.0
]
},
"Max_Larval_Capacity": 10.**(sample['arab_rainfall_scale']+sample['log_spline_rainfall_ratio'])
# "Max_Larval_Capacity": 10.**sample['arab_rainfall_scale'] * sample['spline_rainfall_ratio']
# "Max_Larval_Capacity": 10.**sample['funest_spline_scale']
},
# "WATER_VEGETATION": 10.**sample['funest_veg_scale']
"WATER_VEGETATION": 10.**5.5
})
return sample
def simulation_setup(cb,
species_details,
site_vector_props,
max_larval_capacity=4e8):
site_dir = os.path.join('sites', 'all')
# directories
cb.update_params({
"Demographics_Filenames": [
os.path.join(site_dir, "demographics.json"),
os.path.join(site_dir, "demographics_net_overlay.json")
],
"Air_Temperature_Filename":
os.path.join(site_dir, "air_temperature_daily.bin"),
"Land_Temperature_Filename":
os.path.join(site_dir, "air_temperature_daily.bin"),
"Rainfall_Filename":
os.path.join(site_dir, "rainfall_daily.bin"),
"Relative_Humidity_Filename":
os.path.join(site_dir, "relative_humidity_daily.bin")
})
# Find vector proportions for each vector
set_params_by_species(cb.params, [name for name in species_details.keys()])
larval_habs_per_site = {"NodeID": site_vector_props["node_id"]}
for species_name, species_modifications in species_details.items():
set_species_param(cb, species_name, "Adult_Life_Expectancy", 20)
set_species_param(cb, species_name, 'Vector_Sugar_Feeding_Frequency',
'VECTOR_SUGAR_FEEDING_EVERY_DAY')
for param, val in species_modifications.items():
if param == "habitat_split":
new_vals = {
hab: hab_prop * max_larval_capacity
for hab, hab_prop in val.items()
}
set_species_param(cb, species_name, "Larval_Habitat_Types",
new_vals)
larval_habs_per_site.update({
".".join([species_name, hab]):
site_vector_props[species_name]
for hab in val.keys()
})
else:
set_species_param(cb, species_name, param, val)
scale_larval_habitats(cb, pd.DataFrame(larval_habs_per_site))
def update_vector_params(cb):
cb.update_params({'Vector_Species_Names': ['gambiae']})
set_species(cb, ['gambiae'])
set_species_param(cb, "gambiae", "Anthropophily", 0.65)
cb.update_params({
"Default_Geography_Initial_Node_Population": 1000,
"Default_Geography_Torus_Size": 10,
"Enable_Vector_Migration_Human": 0,
"Enable_Vector_Migration_Wind": 0,
"Egg_Hatch_Density_Dependence": "NO_DENSITY_DEPENDENCE",
"Temperature_Dependent_Feeding_Cycle": "NO_TEMPERATURE_DEPENDENCE",
"Enable_Drought_Egg_Hatch_Delay": 0,
"Enable_Egg_Mortality": 0,
"Enable_Temperature_Dependent_Egg_Hatching": 0,
"Vector_Migration_Modifier_Equation": "LINEAR"
})
set_species_param(
cb, 'gambiae', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Over_Time": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5,
212.917, 243.333, 273.75, 304.167, 334.583
],
"Values":
[3, 0.8, 1.25, 0.1, 2.7, 10, 6, 35, 2.8, 1.5, 1.6, 2.1]
},
"Capacity_Distribution_Number_Of_Years": 1,
"Max_Larval_Capacity": pow(10, 9)
}
})
set_species_param(cb, "gambiae", "Adult_Life_Expectancy", 20)
set_species_param(cb, "gambiae", "Male_Life_Expectancy", 10)
set_species_param(cb, "gambiae", "Indoor_Feeding_Fraction", 0.9)
def update_vector_params(cb):
cb.update_params({"Vector_Species_Names": ['gambiae']})
set_species_param(cb, 'gambiae', 'Larval_Habitat_Types',
{"LINEAR_SPLINE": {
"Capacity_Distribution_Per_Year": {
"Times": [0.0, 30.417, 60.833, 91.25, 121.667, 152.083,
182.5, 212.917, 243.333, 273.75, 304.167, 334.583],
"Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1]
},
"Max_Larval_Capacity": 1e9
}})
set_species_param(cb, "gambiae", "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, "gambiae", "Adult_Life_Expectancy", 20)
sim_duration = 365 * 70
num_seeds = 50
SetupParser('HPC')
cb = DTKConfigBuilder.from_defaults('MALARIA_SIM')
builder = GenericSweepBuilder.from_dict({'Run_Number': range(num_seeds)})
set_climate_constant(cb)
set_species_param(cb, 'gambiae', 'Larval_Habitat_Types',
{"LINEAR_SPLINE": {
"Capacity_Distribution_Per_Year": {
"Times": [0.0, 30.417, 60.833, 91.25, 121.667, 152.083,
182.5, 212.917, 243.333, 273.75, 304.167, 334.583],
# "Values": [1, 0.25, 0.1, 1, 1, 0.5, 12, 5, 3, 2, 1.5, 1.5]
"Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1]
},
"Max_Larval_Capacity": 1e9
}})
set_species_param(cb, "gambiae", "Indoor_Feeding_Fraction", 0.9)
cb.update_params({"Demographics_Filenames": ['Calibration/single_node_demographics.json'],
'Antigen_Switch_Rate': pow(10, -9.116590124),
'Base_Gametocyte_Production_Rate': 0.06150582,
'Base_Gametocyte_Mosquito_Survival_Rate': 0.002011099,
'Base_Population_Scale_Factor': 1, # Change x_Temporary_Larval_Habitat by same factor if changing Base_Population_Scale_Factor
'Falciparum_MSP_Variants': 32,
'Falciparum_Nonspecific_Types': 76,
def change_adult_lifespan(cb, adult_life_expectacy):
set_species_param(cb, 'gambiae', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'gambiae', 'Adult_Life_Expectancy',
adult_life_expectacy)
set_species_param(cb, 'gambiae', 'Anthropophily', 0.85)
set_species_param(cb, 'gambiae', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy',
adult_life_expectacy)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
return {"adult_life_expectancy": adult_life_expectacy}
def set_ento(cb, archetype="Southern"):
if archetype == "Southern":
set_species(cb, ["arabiensis", "funestus"])
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif archetype == "Sahel":
set_species(cb, ["gambiae"])
set_species_param(cb, 'gambiae', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'gambiae', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'gambiae', 'Anthropophily', 0.65)
set_species_param(cb, 'gambiae', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif archetype == "Central":
set_species(cb, ["gambiae", "funestus"])
set_species_param(cb, 'gambiae', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'gambiae', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'gambiae', 'Anthropophily', 0.85)
set_species_param(cb, 'gambiae', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif archetype == "Eastern":
set_species(cb, ["gambiae", "funestus", "arabiensis"])
set_species_param(cb, 'gambiae', "Indoor_Feeding_Fraction", 0.85)
set_species_param(cb, 'gambiae', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'gambiae', 'Anthropophily', 0.85)
set_species_param(cb, 'gambiae', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'arabiensis', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction",
0.7) # Motivated by Uganda Vectorlink 2019
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif archetype == "Coastal Western":
set_species(cb, ["gambiae", "funestus", "arabiensis"])
set_species_param(cb, 'gambiae', "Indoor_Feeding_Fraction", 0.85)
set_species_param(cb, 'gambiae', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'gambiae', 'Anthropophily',
0.8) # Slightly tuned down - Nigeria Vectorlink 2019
set_species_param(cb, 'gambiae', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'arabiensis', "Indoor_Feeding_Fraction", 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.85)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif archetype == "Magude":
set_species(cb, ["arabiensis", "funestus"])
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.95)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.6)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
else:
raise NotImplementedError
set_ento_splines(cb, habitat_scale=1, archetype=archetype)
def set_ento_splines(cb, habitat_scale, archetype="Southern"):
if archetype == "Southern":
arab_scale = habitat_scale
funest_scale = arab_scale - 0.8
set_species_param(
cb, 'funestus', "Larval_Habitat_Types", {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.13, 0.33, 1., 0.67, 0.67, 0.67, 0.33, 0.33, 0.2,
0.13, 0.067, 0.067
]
},
"Max_Larval_Capacity": 10**funest_scale
}
})
set_species_param(
cb, 'arabiensis', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.6, 0.8, 1.0, 0.9, 0.1, 0.01, 0.01, 0.01, 0.01,
0.01, 0.02, 0.05
]
},
"Max_Larval_Capacity": 10**arab_scale
},
"CONSTANT": 10**4.9
})
return_dict = {"hab_scale": habitat_scale}
elif archetype == "Sahel":
set_species_param(
cb, 'gambiae', "Larval_Habitat_Types", {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
return_dict = {"hab_scale": habitat_scale}
elif archetype == "Central":
# Amelia's spline setup
# x_overall_amelia = 63.1
#
# set_species_param(cb,
# 'gambiae',
# "Larval_Habitat_Types",
# {"CONSTANT": 40000000*x_overall_amelia,
# "TEMPORARY_RAINFALL": 360000000*x_overall_amelia,
# "LINEAR_SPLINE": {
# "Capacity_Distribution_Number_Of_Years": 1,
# "Capacity_Distribution_Over_Time": {
# "Times": month_times,
# "Values": [0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1., 0.19, 0.19, 0.074, 0.06]
# },
# "Max_Larval_Capacity": 10**habitat_scale
# }}
# )
#
# set_species_param(cb,
# 'funestus',
# "Larval_Habitat_Types",
# {"WATER_VEGETATION": 400000000*x_overall_amelia,
# "LINEAR_SPLINE": {
# "Capacity_Distribution_Number_Of_Years": 1,
# "Capacity_Distribution_Over_Time": {
# "Times": month_times,
# "Values": [0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1., 0.19, 0.19, 0.074, 0.06]
# },
# "Max_Larval_Capacity": 10**habitat_scale
# }}
# )
gamb_scale = habitat_scale
funest_scale = gamb_scale - 1.03 # Calculated for funestus to be ~5% of all mosquitos
set_species_param(
cb, 'gambiae', "Larval_Habitat_Types", {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.51, 0.42, 0.52, 0.66, 0.86, 0.92, 0.82, 0.75,
0.84, 0.99, 1.0, 0.77
]
},
"Max_Larval_Capacity": 10**gamb_scale
}
})
set_species_param(
cb, 'funestus', "Larval_Habitat_Types", {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.87, 0.82, 0.85, 0.9, 0.95, 0.93, 0.89, 0.87,
0.87, 0.94, 1.0, 0.97
]
},
"Max_Larval_Capacity": 10**funest_scale
}
})
return_dict = {"hab_scale": habitat_scale}
elif archetype == "Eastern":
# Amelia's spline setup
x_overall_amelia = 63.1
set_species_param(
cb, 'arabiensis', "Larval_Habitat_Types", {
"CONSTANT": 40000000 * x_overall_amelia,
"TEMPORARY_RAINFALL": 360000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
set_species_param(
cb, 'gambiae', "Larval_Habitat_Types", {
"CONSTANT": 40000000 * x_overall_amelia,
"TEMPORARY_RAINFALL": 360000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
set_species_param(
cb, 'funestus', "Larval_Habitat_Types", {
"WATER_VEGETATION": 400000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
return_dict = {"hab_scale": habitat_scale}
elif archetype == "Coastal Western":
# Amelia's spline setup
x_overall_amelia = 63.1
set_species_param(
cb, 'arabiensis', "Larval_Habitat_Types", {
"CONSTANT": 40000000 * x_overall_amelia,
"TEMPORARY_RAINFALL": 360000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
set_species_param(
cb, 'gambiae', "Larval_Habitat_Types", {
"CONSTANT": 40000000 * x_overall_amelia,
"TEMPORARY_RAINFALL": 360000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
set_species_param(
cb, 'funestus', "Larval_Habitat_Types", {
"WATER_VEGETATION": 400000000 * x_overall_amelia,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.086, 0.023, 0.034, 0.0029, 0.077, 0.23, 0.11, 1.,
0.19, 0.19, 0.074, 0.06
]
},
"Max_Larval_Capacity": 10**habitat_scale
}
})
return_dict = {"hab_scale": habitat_scale}
elif archetype == "Magude":
arab_scale = habitat_scale
funest_scale = arab_scale - 0.56
set_species_param(
cb, 'funestus', "Larval_Habitat_Types", {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.009, 0.438, 0.005, 0.088, 0.049, 1.000, 0.023,
0.170, 0.015, 0.008, 0.376, 0.193
]
},
"Max_Larval_Capacity": 10**funest_scale
}
})
set_species_param(
cb, 'arabiensis', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times":
month_times,
"Values": [
0.005, 0.119, 1.000, 0.069, 0.184, 0.203, 0.486,
0.157, 0.149, 0.185, 0.119, 0.011
]
},
"Max_Larval_Capacity": 10**arab_scale
},
"CONSTANT": 10**4.9
})
return_dict = {"hab_scale": habitat_scale}
else:
raise NotImplementedError
return return_dict
def add_zambia_ento_to_cb(self):
# Vector properties:
self.cb.update_params(
{'Vector_Species_Names': ['arabiensis', 'funestus']})
# Arabiensis
set_species_param(self.cb, 'arabiensis', 'Larval_Habitat_Types', {
"CONSTANT": 2000000.0,
"TEMPORARY_RAINFALL": 100000000.0
})
set_species_param(self.cb, 'arabiensis', 'Indoor_Feeding_Fraction',
0.5)
set_species_param(self.cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(self.cb, 'arabiensis',
'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
# Funestus
set_species_param(
self.cb, 'funestus', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083,
182.5, 212.917, 243.333, 273.75, 304.167, 334.583
],
"Values": [
0.0, 0.0, 0.0, 0.2, 0.8, 1.0, 1.0, 1.0, 0.5, 0.2,
0.0, 0.0
]
},
"Max_Larval_Capacity": 100000000.0
},
"WATER_VEGETATION": 2000000.0
})
set_species_param(self.cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(self.cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(self.cb, 'funestus',
'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
self.cb.params['Enable_Vector_Species_Report'] = 1
cb = DTKConfigBuilder.from_defaults('MALARIA_SIM')
builder = GenericSweepBuilder.from_dict({'Run_Number': range(num_seeds)})
set_climate_constant(cb)
set_species_param(
cb,
'gambiae',
'Larval_Habitat_Types',
{
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5,
212.917, 243.333, 273.75, 304.167, 334.583
],
"Values": [
3, 0.8, 1.25, 0.1, 2.7, 10, 6, 35, 2.8, 1.5, 1.6, 2.1
] # with 'x_Temporary_Larval_Habitat': 0.2 for EIR~10
},
"Max_Larval_Capacity": pow(10, 9)
}
})
set_species_param(cb, "gambiae", "Adult_Life_Expectancy", 20)
set_species_param(cb, "gambiae", "Indoor_Feeding_Fraction", 0.9)
cb.update_params({
'Age_Initialization_Distribution_Type':
'DISTRIBUTION_SIMPLE',
def setup_chiyabi_single_node_cbever(cb,
demo_file=None,
immun_file=None,
migrate=False):
# Spatial simulation + migration settings
cb.update_params({
'Birth_Rate_Dependence':
'FIXED_BIRTH_RATE', # Match demographics file for constant population size (with exponential age distribution)
'Enable_Nondisease_Mortality': 1,
'New_Diagnostic_Sensitivity': 0.025, # 40/uL
"Enable_Immunity_Initialization_Distribution": 1,
"Immunity_Initialization_Distribution_Type":
"DISTRIBUTION_COMPLEX", # [Not sure what this does]
'Air_Temperature_Filename':
"Climate/test/Zambia_30arcsec_air_temperature_daily.bin",
'Land_Temperature_Filename':
"Climate/test/Zambia_30arcsec_air_temperature_daily.bin",
'Rainfall_Filename': "Climate/test/Zambia_30arcsec_rainfall_daily.bin",
'Relative_Humidity_Filename':
"Climate/test/Zambia_30arcsec_relative_humidity_daily.bin",
'Vector_Species_Names': ['arabiensis', 'funestus']
})
set_species_param(cb, 'arabiensis', 'Larval_Habitat_Types', {
"CONSTANT": 2000000.0,
"TEMPORARY_RAINFALL": 100000000.0
})
set_species_param(
cb, 'funestus', 'Larval_Habitat_Types', {
"LINEAR_SPLINE": {
"Capacity_Distribution_Per_Year": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5,
212.917, 243.333, 273.75, 304.167, 334.583
],
"Values": [
0.0, 0.0, 0.0, 0.2, 0.8, 1.0, 1.0, 1.0, 0.5, 0.2, 0.0,
0.0
]
},
"Max_Larval_Capacity": 100000000.0
},
"WATER_VEGETATION": 2000000.0
})
if immun_file:
cb.update_params({'Demographics_Filenames': [demo_file, immun_file]})
else:
cb.update_params({'Demographics_Filenames': [demo_file]})
if migrate:
print "migration on!"
cb.update_params({
# 'Vector_Sampling_Type': 'SAMPLE_IND_VECTORS', # individual vector model (required for vector migration)
# 'Mosquito_Weight': 10,
# 'Enable_Vector_Migration': 1, # mosquito migration
# 'Enable_Vector_Migration_Local': 1, # migration rate hard-coded in NodeVector::processEmigratingVectors() such that 50% total leave a 1km x 1km square per day (evenly distributed among the eight adjacent grid cells).
'Migration_Model':
'FIXED_RATE_MIGRATION',
'Local_Migration_Filename':
os.path.join(
'Migration/', exp_name + '_migration.bin'
), # note that underscore prior 'migration.bin' is required for legacy reasons that need to be refactored...
'Enable_Local_Migration':
1,
'Migration_Pattern':
'SINGLE_ROUND_TRIPS', # human migration
'Local_Migration_Roundtrip_Duration':
2, # mean of exponential days-at-destination distribution
'Local_Migration_Roundtrip_Probability':
0.95, # fraction that return
})
else:
print "migration off!!!"
cb.update_params(
{'Migration_Model': 'NO_MIGRATION'}
) #'NO_MIGRATION' is actually default for MALARIA_SIM, but might as well make sure it's off
def __call__(self, cb):
return set_species_param(cb, self.species, self.param, self.value)
def basic_gridded_config_builder(immunity_params="prashanth"):
cb = DTKConfigBuilder.from_defaults('MALARIA_SIM')
# Reduce StdOut size and prevent DTK from spitting out too many messages
cb.update_params({
"logLevel_default": "WARNING",
"Enable_Log_Throttling": 1,
"Memory_Usage_Warning_Threshold_Working_Set_MB": 50000,
"Memory_Usage_Halting_Threshold_Working_Set_MB": 60000,
"logLevel_JsonConfigurable": "WARNING",
"Disable_IP_Whitelist": 1
})
cb.update_params(immunity.params)
cb.update_params(infection.params)
cb.update_params(symptoms.params)
if immunity_params == 'prashanth':
cb.update_params({
'Antigen_Switch_Rate': pow(10, -9.116590124),
'Base_Gametocyte_Production_Rate': 0.06150582,
'Base_Gametocyte_Mosquito_Survival_Rate': 0.002011099,
'Falciparum_MSP_Variants': 32,
'Falciparum_Nonspecific_Types': 76,
'Falciparum_PfEMP1_Variants': 1070,
'Gametocyte_Stage_Survival_Rate': 0.588569307,
'MSP1_Merozoite_Kill_Fraction': 0.511735322,
'Max_Individual_Infections': 3,
'Nonspecific_Antigenicity_Factor': 0.415111634
})
elif immunity_params == "jaline":
cb.update_params({
'Base_Gametocyte_Production_Rate': 0.044,
"Gametocyte_Stage_Survival_Rate": 0.82,
'Antigen_Switch_Rate': 2.96e-9,
'Falciparum_PfEMP1_Variants': 1112,
'Falciparum_MSP_Variants': 7,
'MSP1_Merozoite_Kill_Fraction': 0.43,
'Falciparum_Nonspecific_Types': 90,
'Nonspecific_Antigenicity_Factor': 0.42,
'Base_Gametocyte_Mosquito_Survival_Rate': 0.00088,
"Max_Individual_Infections": 5
})
cb.update_params({
"Climate_Model":
"CLIMATE_CONSTANT",
"Base_Air_Temperature":
27,
"Base_Land_Temperature":
27,
"Migration_Model":
"NO_MIGRATION",
"Enable_Immunity_Distribution":
0,
"Enable_Immunity_Initialization_Distribution":
0,
"Immunity_Initialization_Distribution_Type":
"DISTRIBUTION_OFF"
})
cb.update_params({
"Enable_Demographics_Other": 1,
"Enable_Demographics_Builtin": 0,
"Valid_Intervention_States": [],
"Report_Detection_Threshold_PfHRP2": 40.0,
"Report_Detection_Threshold_Blood_Smear_Parasites": 0,
"Parasite_Smear_Sensitivity": 0.025,
"Birth_Rate_Dependence":
"FIXED_BIRTH_RATE", # Match demographics file for constant population size (with exponential age distribution)
"Enable_Nondisease_Mortality": 1,
})
# Intervention events
intervene_events_list = [
"Bednet_Got_New_One", "Bednet_Using", "Bednet_Discarded"
]
cb.update_params({
"Report_Event_Recorder": 0,
"Report_Event_Recorder_Ignore_Events_In_List": 0,
"Listed_Events": intervene_events_list,
"Report_Event_Recorder_Events": intervene_events_list
})
# Basic entomology
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
return cb
def add_interventions_and_reports(cb,sim_time_dict):
sim_start_year = sim_time_dict["sim_start_year"]
sim_length_years = sim_time_dict["sim_length_years"]
sim_filter_start_time = sim_time_dict["sim_filter_start_time"]
sim_filter_duration = sim_time_dict["sim_filter_duration"]
mozamb_exp.start_year = sim_start_year
mozamb_exp.sim_length_years = sim_length_years
mozamb_exp.implement_baseline_healthseeking(cb)
mozamb_exp.implement_interventions(cb,True,True,False,True,True)
all_nodes = list(mozamb_exp.desired_cells)
cb.update_params({
'x_Regional_Migration': 0.03,
})
add_migration_event(cb,
nodeto=100000,
coverage=0.5,
repetitions=500,
tsteps_btwn=30,
duration_of_stay=3,
duration_before_leaving_distr_type='UNIFORM_DURATION',
duration_before_leaving=0,
duration_before_leaving_2=30,
nodesfrom={'class': 'NodeSetNodeList',
'Node_List': all_nodes},
ind_property_restrictions=[{'TravelerStatus': 'IsTraveler'}])
#new entomology:
# Arabiensis
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
# Funestus
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
# Add specific reports that we want (have to do it here because we need to know what times to filter for):
# Add filter report that has same length for both burn-in and non-burn-in runs (2010-2020).
# This version is for grid-level prevalence comparison
add_filtered_spatial_report(cb,
start=sim_filter_start_time,
end=(sim_filter_start_time+sim_filter_duration),
# channels=['Population', 'New_Diagnostic_Prevalence'])
channels=['Population', 'True_Prevalence']) # 'New_Clinical_Cases','New_Infections'
# Add filter that has same length for both burn-in and non-burn-in runs (2010-2020)
# This version is for HF-level incidence comparison. Add a similar report for the migration node
add_filtered_report(cb,
start=sim_filter_start_time,
end=(sim_filter_start_time + sim_filter_duration),
nodes=all_nodes)
add_filtered_report(cb,
start=sim_filter_start_time,
end=(sim_filter_start_time + sim_filter_duration),
nodes=[EIR_node_label],
description='Work')
# # Add filter report for prevalence in each bairro
foo = bairro_df.groupby('bairro')
for (bairro_num,df) in foo:
add_filtered_report(cb,
start=sim_filter_start_time,
end=(sim_filter_start_time + sim_filter_duration),
nodes=[int(x) for x in df['grid_cell'].values],
description=str(int(bairro_num)))
# Add counter report for clinical incidence
add_event_counter_report(cb,
event_trigger_list=['Received_Treatment', 'Received_IRS', 'Received_Campaign_Drugs', 'Received_RCD_Drugs', 'Bednet_Got_New_One', 'Received_Test'],
start=sim_filter_start_time,
duration=sim_filter_duration)
def set_magude_ento_params(cb, old_or_new):
if old_or_new == "old":
# set_species(cb, ["arabiensis", "funestus"])
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif old_or_new == "new":
# set_species(cb, ["arabiensis", "funestus"])
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.95)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.6)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
else:
return NotImplementedError
return {"old_or_new_ento_params": old_or_new}
def add_magude_ento(cb):
cb.update_params({'Vector_Species_Names': ['arabiensis', 'funestus']})
# Arabiensis
set_species_param(cb,
'arabiensis',
'Larval_Habitat_Types',
{
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [0.0, 30.417, 60.833, 91.25,
121.667, 152.083, 182.5, 212.917,
243.333, 273.75, 304.167, 334.583],
"Values": [1] * 12
},
"Max_Larval_Capacity": pow(10, 8.5)
}
})
# Funestus
set_species_param(cb,
'funestus',
'Larval_Habitat_Types',
{
"WATER_VEGETATION": 2e3,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [0.0, 30.417, 60.833, 91.25,
121.667, 152.083, 182.5, 212.917,
243.333, 273.75, 304.167, 334.583],
"Values": [1] * 12
},
"Max_Larval_Capacity": pow(10, 7.5)
}
})
#
# def find_cells_for_this_catchment(catch, base='../../'):
# # Find which grid cells correspond to a given HFCA
# df = pd.read_csv(base + "data/mozambique/grid_lookup_with_neighborhood.csv")
#
# if catch == 'all':
# return np.array(df['grid_cell'])
# else:
# df_catch = df[df['catchment'] == catch]
# return np.array(df_catch['grid_cell'])
#
#
# def find_pops_for_catch(catch, base='../../'):
# cells = find_cells_for_this_catchment(catch, base=base)
#
# pop_df = pd.read_csv(base + "data/mozambique/grid_population")
#
# return np.array(pop_df[np.in1d(pop_df['node_label'] ,cells)]['pop'])
#
#
#
# def find_bairros_for_this_catchment(catch, base='../../'):
# bairro_csv = base + "data/mozambique/grid_lookup_with_neighborhood.csv"
# bairro_data = pd.read_csv(bairro_csv)
#
# return_data = bairro_data[bairro_data["catchment" ]== catch]
# return return_data
#
#
#
# def catch_3_yr_spline(catch, species, dropbox_base="C:/Users/jsuresh/Dropbox (IDM)/Malaria Team Folder/projects/Mozambique/entomology_calibration/"):
# # Read spline directly from mini-CSV files generated by Jaline/Caitlin
#
# def load_raw_spline(csv_df):
# spline = np.zeros(36)
# raw_spline = np.array(csv_df["Values"])
# spline[4:35] = raw_spline[1:-1] # Throw out first and last entry
# return spline
#
# def fill_out_spline(spline):
# spline[0:4] = 0.5 * (spline[12:16] + spline[24:28])
# spline[35] = 0.5 * (spline[11]+spline[23])
# return spline
# # def fill_out_spline(spline):
# # # Account for the fact that we only really trust the data from indices 4-35 (May 15 - Nov 17)
# # # Reconstruct shape and amplitude of missing data by inferring from other
# # year1_factor = spline[4:11].sum()
# # year2_factor = spline[16:23].sum()
# # year3_factor = spline[28:35].sum()
# #
# # spline_inferred = spline.copy()
# #
# # spline_inferred[0:4] = year1_factor * 0.5 * (spline[12:16] / year2_factor + spline[24:28] / year3_factor)
# # spline_inferred[35] = year3_factor * 0.5 * (spline[11] / year1_factor + spline[23] / year2_factor)
# #
# # return spline_inferred
#
#
# ento_base = dropbox_base + "Multi_year_calibration_by_HFCA_180404/best_180410/"
# # ento_base = dropbox_base + "Multi_year_calibration_by_HFCA_180404/best_180409/"
#
#
#
# if species == "arabiensis":
# species = "gambiae"
#
#
# if species == "funestus":
# df = pd.read_csv(ento_base + "funestus.csv")
# spline = fill_out_spline(load_raw_spline(df))
# elif species == "gambiae":
# if catch == "Panjane-Caputine":
# df = pd.read_csv(ento_base + "{}_{}.csv".format("Panjane", species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch == "Magude-Sede-Facazissa":
# df = pd.read_csv(ento_base + "{}_{}.csv".format("Magude-Sede", species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch != "Moine" and catch != "Mahel":
# df = pd.read_csv(ento_base + "{}_{}.csv".format(catch, species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch == "Moine" or catch == "Mahel":
# panjane_df = pd.read_csv(ento_base + "{}_{}.csv".format("Panjane", species))
# chichuco_df = pd.read_csv(ento_base + "{}_{}.csv".format("Chichuco", species))
# panjane_spline = fill_out_spline(load_raw_spline(panjane_df))
# chichuco_spline = fill_out_spline(load_raw_spline(chichuco_df))
#
# spline = (panjane_spline + chichuco_spline)/2.
#
# # Return associated times:
# times_1yr = np.array([0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5, 212.917, 243.333, 273.75, 304.167, 334.583])
# times = np.append(times_1yr, times_1yr + 365)
# times = np.append(times, times_1yr + 365 * 2)
# times = list(times)
#
# return [times, list(spline)]
#
#
#
#
#
# def catch_3_yr_spline_GatesReview(catch, species, dropbox_base="C:/Users/jsuresh/Dropbox (IDM)/Malaria Team Folder/projects/Mozambique/entomology_calibration/"):
# # Read spline directly from mini-CSV files generated by Jaline/Caitlin
#
# def load_raw_spline(csv_df):
# spline = np.zeros(36)
# raw_spline = np.array(csv_df["Values"])
# spline[4:35] = raw_spline[1:-1] # Throw out first and last entry
# return spline
#
# def fill_out_spline(spline):
# spline[0:4] = 0.5 * (spline[12:16] + spline[24:28])
# spline[35] = 0.5 * (spline[11]+spline[23])
# return spline
# # def fill_out_spline(spline):
# # # Account for the fact that we only really trust the data from indices 4-35 (May 15 - Nov 17)
# # # Reconstruct shape and amplitude of missing data by inferring from other
# # year1_factor = spline[4:11].sum()
# # year2_factor = spline[16:23].sum()
# # year3_factor = spline[28:35].sum()
# #
# # spline_inferred = spline.copy()
# #
# # spline_inferred[0:4] = year1_factor * 0.5 * (spline[12:16] / year2_factor + spline[24:28] / year3_factor)
# # spline_inferred[35] = year3_factor * 0.5 * (spline[11] / year1_factor + spline[23] / year2_factor)
# #
# # return spline_inferred
#
#
# ento_base = dropbox_base + "Multi_year_calibration_by_HFCA_180404/best_180410/"
# # ento_base = dropbox_base + "Multi_year_calibration_by_HFCA_180404/best_180409/"
#
#
#
# if species == "arabiensis":
# species = "gambiae"
#
#
# if species == "funestus":
# df = pd.read_csv(ento_base + "funestus.csv")
# spline = fill_out_spline(load_raw_spline(df))
# elif species == "gambiae":
# if catch == "Panjane-Caputine":
# df = pd.read_csv(ento_base + "{}_{}.csv".format("Panjane", species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch == "Magude-Sede-Facazissa":
# df = pd.read_csv(ento_base + "{}_{}.csv".format("Magude-Sede", species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch != "Moine" and catch != "Mahel":
# df = pd.read_csv(ento_base + "{}_{}.csv".format(catch, species))
# spline = fill_out_spline(load_raw_spline(df))
# elif catch == "Moine" or catch == "Mahel":
# panjane_df = pd.read_csv(ento_base + "{}_{}.csv".format("Panjane", species))
# chichuco_df = pd.read_csv(ento_base + "{}_{}.csv".format("Chichuco", species))
# panjane_spline = fill_out_spline(load_raw_spline(panjane_df))
# chichuco_spline = fill_out_spline(load_raw_spline(chichuco_df))
#
# spline = (panjane_spline + chichuco_spline)/2.
#
# # Return associated times:
# times_1yr = np.array([0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5, 212.917, 243.333, 273.75, 304.167, 334.583])
# times = np.append(times_1yr, times_1yr + 365)
# times = np.append(times, times_1yr + 365 * 2)
# times = list(times)
#
# return [times, list(spline)]
def add_ento_to_cb(self):
# Vector properties:
self.cb.update_params(
{'Vector_Species_Names': ['arabiensis', 'funestus']})
# Arabiensis
set_species_param(self.cb, 'arabiensis', 'Indoor_Feeding_Fraction',
0.5)
set_species_param(self.cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(
self.cb,
'arabiensis',
'Larval_Habitat_Types',
{
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
# "Capacity_Distribution_Per_Year": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083,
182.5, 212.917, 243.333, 273.75, 304.167, 334.583
],
"Values": [1] * 12
# "Values": [0.0429944166751962,
# 0.145106159922212,
# 0.220520011001099,
# 0.318489404300663,
# 0.0617610600835594,
# 0.0462380862878181,
# 0.0367590381502996,
# 0.02474944109524821,
# 0.0300445801767523,
# 0.021859890543704,
# 0.0261404367939001,
# 0.0253992634551118
# ]
},
"Max_Larval_Capacity":
pow(10, 8.42
) # Uncertain-- this exponent is what we calibrate for
}
})
# Funestus
set_species_param(self.cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(self.cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(
self.cb,
'funestus',
'Larval_Habitat_Types',
{
"WATER_VEGETATION": 2e3,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
# "Capacity_Distribution_Per_Year": {
"Times": [
0.0, 30.417, 60.833, 91.25, 121.667, 152.083,
182.5, 212.917, 243.333, 273.75, 304.167, 334.583
],
# Prashanth's new spline: stand-alone
"Values": [1] * 12
# "Values": [0.00100058388478598,
# 0.0555791772797765,
# 0.0136439353956828,
# 0.0819954534745384,
# 0.0987507679669904,
# 0.08541870494461,
# 0.126723162372031,
# 0.0847818298332663,
# 0.249125024283648,
# 0.105551476581602,
# 0.0564097715821499,
# 0.0423232369866486
# ]
},
"Max_Larval_Capacity": pow(
10, 7.44
) # Uncertain-- this exponent was what we calibrate for
}
})
return None
if __name__ == "__main__":
expname = 'vector_genetics_single_node_no_introgression'
sim_duration = 365 * 10
num_seeds = 50
SetupParser('HPC')
cb = DTKConfigBuilder.from_defaults('VECTOR_SIM')
set_climate_constant(cb)
set_species_param(cb, 'arabiensis', 'Larval_Habitat_Types',
{"CONSTANT": 11250000000})
set_species_param(cb, 'arabiensis', 'Male_Life_Expectancy', 5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 10)
set_species_param(cb, 'arabiensis', 'Transmission_Rate', 0.5)
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 1.0)
set_species_param(cb, 'funestus', 'Larval_Habitat_Types',
{"CONSTANT": 11250000000})
set_species_param(cb, 'funestus', 'Male_Life_Expectancy', 5)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 10)
set_species_param(cb, 'funestus', 'Transmission_Rate', 0.5)
set_species_param(cb, 'funestus', 'Indoor_Feeding_Fraction', 1.0)
########################## VECTOR GENETICS ####################################################
add_genes(cb)
from simtools.SetupParser import SetupParser
if __name__ == "__main__":
expname = 'vector_genetics_single_node'
sim_duration = 365 * 6
num_seeds = 50
cb = DTKConfigBuilder.from_defaults('VECTOR_SIM')
builder = GenericSweepBuilder.from_dict({'Run_Number': range(num_seeds)})
set_climate_constant(cb)
set_species(cb, ['arabiensis'])
set_species_param(cb, 'arabiensis', 'Larval_Habitat_Types',
{"TEMPORARY_RAINFALL": 11250000000})
set_species_param(cb, 'arabiensis', 'Male_Life_Expectancy', 5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 10)
set_species_param(cb, 'arabiensis', 'Transmission_Rate', 0.5)
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 1.0)
########################## VECTOR GENETICS ####################################################
# Add genes
genes = {
'arabiensis': [{
"Alleles": {
"a0": 1.0,
"a1": 0.0
},
"Mutations": {
"a0:a1": 0.01,
def add_ento_to_cb(self):
# Vector properties:
self.cb.update_params({'Vector_Species_Names': ['arabiensis', 'funestus']})
# Arabiensis
set_species_param(self.cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(self.cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(self.cb, 'arabiensis', 'Larval_Habitat_Types',
{
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5, 212.917,
243.333, 273.75, 304.167, 334.583],
"Values": [1] * 12
},
"Max_Larval_Capacity": pow(10, 9.88)
}
})
# Funestus
set_species_param(self.cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(self.cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(self.cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(self.cb, 'funestus', 'Larval_Habitat_Types', {
"WATER_VEGETATION": 2e3,
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": {
"Times": [0.0, 30.417, 60.833, 91.25, 121.667, 152.083, 182.5, 212.917, 243.333, 273.75,
304.167, 334.583],
"Values": [1] * 12
},
"Max_Larval_Capacity": pow(10, 10.60)
}
})
def burnin_draw(old_or_new):
cb.set_param("Serialized_Population_Filenames", ["state-18250.dtk"])
if old_or_new == "old":
cb.set_param(
"Serialized_Population_Path",
"\\\\internal.idm.ctr\\IDM\\Home\\jsuresh\\output\\magude_burnins_ento_comparison_no__20210511_023616\\c44\\69a\\820\\c4469a82-01b2-eb11-a2e3-c4346bcb7275\\output"
)
elif old_or_new == "new":
cb.set_param(
"Serialized_Population_Path",
"\\\\internal.idm.ctr\\IDM\\Home\\jsuresh\\output\\magude_burnins_ento_comparison_no__20210511_023616\\c64\\69a\\820\\c6469a82-01b2-eb11-a2e3-c4346bcb7275\\output"
)
# set ento
if old_or_new == "old":
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction', 0.5)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis',
'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.9)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
elif old_or_new == "new":
set_species_param(cb, 'arabiensis', 'Indoor_Feeding_Fraction',
0.95)
set_species_param(cb, 'arabiensis', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'arabiensis', 'Anthropophily', 0.65)
set_species_param(cb, 'arabiensis',
'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
set_species_param(cb, 'funestus', "Indoor_Feeding_Fraction", 0.6)
set_species_param(cb, 'funestus', 'Adult_Life_Expectancy', 20)
set_species_param(cb, 'funestus', 'Anthropophily', 0.65)
set_species_param(cb, 'funestus', 'Vector_Sugar_Feeding_Frequency',
"VECTOR_SUGAR_FEEDING_NONE")
