cara/caimira/store/data_registry.py

468 lines
16 KiB
Python

from caimira.enums import ViralLoads
class DataRegistry:
"""Registry to hold data values."""
version = None
expiration_particle = {
"long_range_expiration_distributions": {
"minimum_diameter": 0.1,
"maximum_diameter": 30,
},
"short_range_expiration_distributions": {
"minimum_diameter": 0.1,
"maximum_diameter": 100,
},
"BLOmodel": {
"cn": {"B": 0.06, "L": 0.2, "O": 0.0010008},
"mu": {"B": 0.989541, "L": 1.38629, "O": 4.97673},
"sigma": {"B": 0.262364, "L": 0.506818, "O": 0.585005},
},
"expiration_BLO_factors": {
"Breathing": {"B": 1., "L": 0., "O": 0., },
"Speaking": {"B": 1., "L": 1., "O": 1., },
"Singing": {"B": 1., "L": 5., "O": 5., },
"Shouting": {"B": 1., "L": 5., "O": 5., },
},
"particle": {
"evaporation_factor": 0.3,
}
}
activity_distributions = {
"Seated": {
"inhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": -0.6872121723362303,
"lognormal_standard_deviation_gaussian": 0.10498338229297108,
},
},
"exhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": -0.6872121723362303,
"lognormal_standard_deviation_gaussian": 0.10498338229297108,
},
},
},
"Standing": {
"inhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": -0.5742377578494785,
"lognormal_standard_deviation_gaussian": 0.09373162411398223,
},
},
"exhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": -0.5742377578494785,
"lognormal_standard_deviation_gaussian": 0.09373162411398223,
},
},
},
"Light activity": {
"inhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 0.21380242785625422,
"lognormal_standard_deviation_gaussian": 0.09435378091059601,
},
},
"exhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 0.21380242785625422,
"lognormal_standard_deviation_gaussian": 0.09435378091059601,
},
},
},
"Moderate activity": {
"inhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 0.551771330362601,
"lognormal_standard_deviation_gaussian": 0.1894616357138137,
},
},
"exhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 0.551771330362601,
"lognormal_standard_deviation_gaussian": 0.1894616357138137,
},
},
},
"Heavy exercise": {
"inhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 1.1644665696723049,
"lognormal_standard_deviation_gaussian": 0.21744554768657565,
},
},
"exhalation_rate": {
"associated_value": "Log-normal distribution",
"parameters": {
"lognormal_mean_gaussian": 1.1644665696723049,
"lognormal_standard_deviation_gaussian": 0.21744554768657565,
},
},
},
}
virological_data = {
"symptomatic_vl_frequencies": {
"log_variable": [
2.46032,
2.67431,
2.85434,
3.06155,
3.25856,
3.47256,
3.66957,
3.85979,
4.09927,
4.27081,
4.47631,
4.66653,
4.87204,
5.10302,
5.27456,
5.46478,
5.6533,
5.88428,
6.07281,
6.30549,
6.48552,
6.64856,
6.85407,
7.10373,
7.30075,
7.47229,
7.66081,
7.85782,
8.05653,
8.27053,
8.48453,
8.65607,
8.90573,
9.06878,
9.27429,
9.473,
9.66152,
9.87552,
],
"frequencies": [
0.001206885,
0.007851618,
0.008078144,
0.01502491,
0.013258014,
0.018528495,
0.020053765,
0.021896167,
0.022047184,
0.018604005,
0.01547796,
0.018075445,
0.021503523,
0.022349217,
0.025097721,
0.032875078,
0.030594727,
0.032573045,
0.034717482,
0.034792991,
0.033267721,
0.042887485,
0.036846816,
0.03876473,
0.045016819,
0.040063473,
0.04883754,
0.043944602,
0.048142864,
0.041588741,
0.048762031,
0.027921732,
0.033871788,
0.022122693,
0.016927718,
0.008833228,
0.00478598,
0.002807662,
],
"kernel_bandwidth": 0.1,
},
'covid_overal_vl_data': {
"shape_factor": 3.47,
"scale_factor": 7.01,
"start": 0.01,
"stop": 0.99,
"num": 30.0,
"min_bound": 2,
"max_bound": 10,
"interpolation_fp_left": 0,
"interpolation_fp_right": 0,
"max_function": 0.2,
},
"virus_distributions": {
"SARS_CoV_2": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 1,
"infectiousness_days": 14,
},
"SARS_CoV_2_ALPHA": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 0.78,
"infectiousness_days": 14,
},
"SARS_CoV_2_BETA": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 0.8,
"infectiousness_days": 14,
},
"SARS_CoV_2_GAMMA": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 0.72,
"infectiousness_days": 14,
},
"SARS_CoV_2_DELTA": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 0.51,
"infectiousness_days": 14,
},
"SARS_CoV_2_OMICRON": {
"viral_load_in_sputum": ViralLoads.COVID_OVERALL.value,
"infectious_dose": {
"associated_value": "Uniform distribution",
"parameters": {"low": 10, "high": 100},
},
"viable_to_RNA_ratio": {
'associated_value': 'Uniform distribution',
'parameters': {'low': 0.01, 'high': 0.6},
},
"transmissibility_factor": 0.2,
"infectiousness_days": 14,
},
},
}
mask_distributions = {
"Type I": {
"η_inhale": {
"associated_value": "Uniform distribution",
"parameters": {
"low": 0.25,
"high": 0.80,
},
},
"factor_exhale": 1,
},
"FFP2": {
"η_inhale": {
"associated_value": "Uniform distribution",
"parameters": {
"low": 0.83,
"high": 0.91,
},
},
"factor_exhale": 1,
},
"Cloth": {
"η_inhale": {
"associated_value": "Uniform distribution",
"parameters": {
"low": 0.05,
"high": 0.40,
},
},
"η_exhale": {
"associated_value": "Uniform distribution",
"parameters": {
"low": 0.20,
"high": 0.50,
},
},
"factor_exhale": 1,
},
}
####################################
room = {
"inside_temp": 293,
"humidity_with_heating": 0.3,
"humidity_without_heating": 0.5,
}
ventilation = {
"natural": {
"discharge_factor": {
"sliding": 0.6,
},
},
"infiltration_ventilation": 0.25,
}
concentration_model = {
"virus_concentration_model": {
"min_background_concentration": 0.0,
},
"CO2_concentration_model": {
"CO2_atmosphere_concentration": 440.44,
"CO2_fraction_exhaled": 0.042,
},
}
short_range_model = {
"dilution_factor": {
"mouth_diameter": 0.02,
"exhalation_coefficient": 2,
"breathing_cycle": 4,
"penetration_coefficients": {
"𝛽r1": 0.18,
"𝛽r2": 0.2,
"𝛽x1": 2.4,
},
},
"conversational_distance": {
"minimum_distance": 0.5,
"maximum_distance": 2.0,
},
}
monte_carlo = {
"sample_size": 250000,
}
population_scenario_activity = {
"office": {"placeholder": "Office", "activity": "Seated", "expiration": {"Speaking": 1, "Breathing": 2}},
"smallmeeting": {
"placeholder": "Small meeting (<10 occ.)",
"activity": "Seated",
"expiration": {"Speaking": 1},
},
"largemeeting": {
"placeholder": "Large meeting (>= 10 occ.)",
"activity": "Standing",
"expiration": {"Speaking": 1, "Breathing": 2},
},
"callcenter": {"placeholder": "Call Center", "activity": "Seated", "expiration": {"Speaking": 1}},
"controlroom-day": {
"placeholder": "Control Room - Day shift",
"activity": "Seated",
"expiration": {"Speaking": 1, "Breathing": 1},
},
"controlroom-night": {
"placeholder": "Control Room - Night shift",
"activity": "Seated",
"expiration": {"Speaking": 1, "Breathing": 9},
},
"library": {"placeholder": "Library", "activity": "Seated", "expiration": {"Breathing": 1}},
"lab": {
"placeholder": "Lab",
"activity": "Light activity",
"expiration": {"Speaking": 1, "Breathing": 1},
},
"workshop": {
"placeholder": "Workshop",
"activity": "Moderate activity",
"expiration": {"Speaking": 1, "Breathing": 1},
},
"training": {"placeholder": "Conference/Training (speaker infected)", "activity": "Standing", "expiration": {"Speaking": 1}},
"training_attendee": {"placeholder": "Conference/Training (attendee infected)", "activity": "Seated", "expiration": {"Breathing": 1}},
"gym": {"placeholder": "Gym", "activity": "Heavy exercise", "expiration": {"Breathing": 1}},
"household-day": {
"placeholder": "Household (day time)",
"activity": "Light activity",
"expiration": {"Breathing": 5, "Speaking": 5},
},
"household-night": {
"placeholder": "Household (evening and night time)",
"activity": "Seated",
"expiration": {"Breathing": 7, "Speaking": 3},
},
"primary-school": {
"placeholder": "Primary school",
"activity": "Light activity",
"expiration": {"Breathing": 5, "Speaking": 5},
},
"secondary-school": {
"placeholder": "Secondary school",
"activity": "Light activity",
"expiration": {"Breathing": 7, "Speaking": 3},
},
"university": {
"placeholder": "University",
"activity": "Seated",
"expiration": {"Breathing": 9, "Speaking": 1},
},
"restaurant": {
"placeholder": "Restaurant",
"activity": "Seated",
"expiration": {"Breathing": 1, "Speaking": 9},
},
"precise": {"placeholder": "Precise", "activity": "", "expiration": {}},
}
def to_dict(self):
# Filter out methods, special attributes, and non-serializable objects
data_dict = {
key: value
for key, value in self.__class__.__dict__.items()
if not key.startswith("__") and not callable(value) and not isinstance(value, (type, classmethod, staticmethod))
}
return data_dict
def update(self, data, version=None):
"""Update local cache with data provided as argument."""
for attr_name, value in data.items():
setattr(self, attr_name, value)
if version:
self.version = version