malaria_config

DoseFractionByAge

Pediatric dosing fraction for a specific age cutoff. Children below upper_age_in_years receive fraction_of_adult_dose of the adult dose.

Schema type: idmType:DoseFractionByAge

Parameters:

Name	Type	Description	Default
upper_age_in_years	float	Age in years below which children receive a reduced dose. Minimum value: 0 Maximum value: 125	required
fraction_of_adult_dose	float	Fraction of the adult dose given to children below the specified age. Minimum value: 0 Maximum value: 1	required

Source code in emodpy_malaria/drug_config.py

class DoseFractionByAge:
    """
    Pediatric dosing fraction for a specific age cutoff. Children below
    **upper_age_in_years** receive **fraction_of_adult_dose** of the adult dose.

    Schema type: ``idmType:DoseFractionByAge``

    Args:
        upper_age_in_years (float): Age in years below which children receive a
            reduced dose.
            Minimum value: 0
            Maximum value: 125
        fraction_of_adult_dose (float): Fraction of the adult dose given to children
            below the specified age.
            Minimum value: 0
            Maximum value: 1
    """

    def __init__(self, upper_age_in_years: float, fraction_of_adult_dose: float):
        self._upper_age = validate_value_range(
            upper_age_in_years, "upper_age_in_years", min_value=0, max_value=125)
        self._fraction = validate_value_range(
            fraction_of_adult_dose, "fraction_of_adult_dose", min_value=0, max_value=1)

    @property
    def upper_age_in_years(self) -> float:
        return self._upper_age

    @property
    def fraction_of_adult_dose(self) -> float:
        return self._fraction

    def to_schema_dict(self, manifest):
        obj = s2c.get_class_with_defaults("idmType:DoseFractionByAge", schema_path=manifest.schema_file)
        obj.Upper_Age_In_Years = self._upper_age
        obj.Fraction_Of_Adult_Dose = self._fraction
        return obj

DrugModifier

Drug resistance modifier applied when a parasite genome matches the specified resistant string. Multiple matching modifiers are multiplied together.

Schema type: idmType:DrugModifier

Parameters:

Name	Type	Description	Default
drug_resistant_string	str	Nucleotide base letters (A, C, G, T) defining resistance at specific genome locations.	required
pkpd_c50_modifier	float	Multiplier applied to the drug's Drug_PKPD_C50. Minimum value: 0 Maximum value: 1000 Default value: 1.0	1.0
max_irbc_kill_modifier	float	Multiplier applied to the drug's Max_Drug_IRBC_Kill. Minimum value: 0 Maximum value: 1000 Default value: 1.0	1.0

Source code in emodpy_malaria/drug_config.py

class DrugModifier:
    """
    Drug resistance modifier applied when a parasite genome matches the specified
    resistant string. Multiple matching modifiers are multiplied together.

    Schema type: ``idmType:DrugModifier``

    Args:
        drug_resistant_string (str): Nucleotide base letters (A, C, G, T) defining
            resistance at specific genome locations.
        pkpd_c50_modifier (float, optional): Multiplier applied to the drug's
            **Drug_PKPD_C50**.
            Minimum value: 0
            Maximum value: 1000
            Default value: 1.0
        max_irbc_kill_modifier (float, optional): Multiplier applied to the drug's
            **Max_Drug_IRBC_Kill**.
            Minimum value: 0
            Maximum value: 1000
            Default value: 1.0
    """

    def __init__(self, drug_resistant_string: str,
                 pkpd_c50_modifier: float = 1.0,
                 max_irbc_kill_modifier: float = 1.0):
        self._drug_resistant_string = drug_resistant_string
        self._pkpd_c50_modifier = validate_value_range(
            pkpd_c50_modifier, "pkpd_c50_modifier", min_value=0, max_value=1000)
        self._max_irbc_kill_modifier = validate_value_range(
            max_irbc_kill_modifier, "max_irbc_kill_modifier", min_value=0, max_value=1000)

    @property
    def drug_resistant_string(self) -> str:
        return self._drug_resistant_string

    @property
    def pkpd_c50_modifier(self) -> float:
        return self._pkpd_c50_modifier

    @property
    def max_irbc_kill_modifier(self) -> float:
        return self._max_irbc_kill_modifier

    def to_schema_dict(self, manifest):
        obj = s2c.get_class_with_defaults("idmType:DrugModifier", schema_path=manifest.schema_file)
        obj.Drug_Resistant_String = self._drug_resistant_string
        obj.PKPD_C50_Modifier = self._pkpd_c50_modifier
        obj.Max_IRBC_Kill_Modifier = self._max_irbc_kill_modifier
        return obj

MalariaDrugTypeParameters

Schema-backed malaria drug type configuration. Encapsulates all pharmacokinetic/ pharmacodynamic parameters for a single antimalarial drug.

Schema type: idmType:MalariaDrugTypeParameters

Parameters:

Name	Type	Description	Default
name	(str, required)	Drug name. Must be unique across all configured drugs.	required
pkpd_model	Union[PKPDModel, str]	PK/PD model type. Use PKPDModel.CONCENTRATION_VERSUS_TIME for full PK/PD modeling or PKPDModel.FIXED_DURATION_CONSTANT_EFFECT for simplified constant-effect modeling. Default value: FIXED_DURATION_CONSTANT_EFFECT	FIXED_DURATION_CONSTANT_EFFECT
drug_cmax	float	Maximum drug concentration after a treatment dose (mg/L). Only used when pkpd_model is CONCENTRATION_VERSUS_TIME. Minimum value: 0 Maximum value: 100000 Default value: 1000	1000
drug_decay_t1	float	First-phase exponential decay rate (days). Minimum value: 0 Maximum value: 100000 Default value: 1	1
drug_decay_t2	float	Second-phase exponential decay rate (days). Minimum value: 0 Maximum value: 100000 Default value: 1	1
drug_vd	float	Volume of distribution (L/kg). Only used when pkpd_model is CONCENTRATION_VERSUS_TIME. Minimum value: 0 Maximum value: 100000 Default value: 10	10
drug_pkpd_c50	float	Drug concentration at which killing rate is 50% of maximum (mg/L). Only used when pkpd_model is CONCENTRATION_VERSUS_TIME. Minimum value: 0 Maximum value: 100000 Default value: 100	100
drug_fulltreatment_doses	int	Number of doses in a full treatment course. Minimum value: 1 Maximum value: 100000 Default value: 3	3
drug_dose_interval	float	Days between doses. Minimum value: 0 Maximum value: 100000 Default value: 1	1
drug_gametocyte02_killrate	float	Kill rate for stage 0–2 gametocytes. Minimum value: 0 Maximum value: 100000 Default value: 0	0
drug_gametocyte34_killrate	float	Kill rate for stage 3–4 gametocytes. Minimum value: 0 Maximum value: 100000 Default value: 0	0
drug_gametocytem_killrate	float	Kill rate for mature gametocytes. Minimum value: 0 Maximum value: 100000 Default value: 0	0
drug_hepatocyte_killrate	float	Kill rate for hepatocytes (liver stage). Minimum value: 0 Maximum value: 100000 Default value: 0	0
max_drug_irbc_kill	float	Maximum kill rate for infected red blood cells. Minimum value: 0 Maximum value: 100000 Default value: 5	5
bodyweight_exponent	float	Exponent for body-weight-based dosing adjustment. Minimum value: 0 Maximum value: 100000 Default value: 0	0
fractional_dose_by_upper_age	list[DoseFractionByAge]	Pediatric dosing fractions by age. Default value: []	None
resistances	list[DrugModifier]	Drug resistance modifiers for parasite genetics simulations. Default value: []	None

Source code in emodpy_malaria/drug_config.py

class MalariaDrugTypeParameters:
    """
    Schema-backed malaria drug type configuration. Encapsulates all pharmacokinetic/
    pharmacodynamic parameters for a single antimalarial drug.

    Schema type: ``idmType:MalariaDrugTypeParameters``

    Args:
        name (str, required): Drug name. Must be unique across all configured drugs.
        pkpd_model (Union[PKPDModel, str], optional): PK/PD model type. Use
            ``PKPDModel.CONCENTRATION_VERSUS_TIME`` for full PK/PD modeling or
            ``PKPDModel.FIXED_DURATION_CONSTANT_EFFECT`` for simplified constant-effect
            modeling.
            Default value: ``FIXED_DURATION_CONSTANT_EFFECT``
        drug_cmax (float, optional): Maximum drug concentration after a treatment
            dose (mg/L). Only used when **pkpd_model** is
            ``CONCENTRATION_VERSUS_TIME``.
            Minimum value: 0
            Maximum value: 100000
            Default value: 1000
        drug_decay_t1 (float, optional): First-phase exponential decay rate (days).
            Minimum value: 0
            Maximum value: 100000
            Default value: 1
        drug_decay_t2 (float, optional): Second-phase exponential decay rate (days).
            Minimum value: 0
            Maximum value: 100000
            Default value: 1
        drug_vd (float, optional): Volume of distribution (L/kg). Only used when
            **pkpd_model** is ``CONCENTRATION_VERSUS_TIME``.
            Minimum value: 0
            Maximum value: 100000
            Default value: 10
        drug_pkpd_c50 (float, optional): Drug concentration at which killing rate is
            50% of maximum (mg/L). Only used when **pkpd_model** is
            ``CONCENTRATION_VERSUS_TIME``.
            Minimum value: 0
            Maximum value: 100000
            Default value: 100
        drug_fulltreatment_doses (int, optional): Number of doses in a full treatment
            course.
            Minimum value: 1
            Maximum value: 100000
            Default value: 3
        drug_dose_interval (float, optional): Days between doses.
            Minimum value: 0
            Maximum value: 100000
            Default value: 1
        drug_gametocyte02_killrate (float, optional): Kill rate for stage 0–2
            gametocytes.
            Minimum value: 0
            Maximum value: 100000
            Default value: 0
        drug_gametocyte34_killrate (float, optional): Kill rate for stage 3–4
            gametocytes.
            Minimum value: 0
            Maximum value: 100000
            Default value: 0
        drug_gametocytem_killrate (float, optional): Kill rate for mature gametocytes.
            Minimum value: 0
            Maximum value: 100000
            Default value: 0
        drug_hepatocyte_killrate (float, optional): Kill rate for hepatocytes
            (liver stage).
            Minimum value: 0
            Maximum value: 100000
            Default value: 0
        max_drug_irbc_kill (float, optional): Maximum kill rate for infected red
            blood cells.
            Minimum value: 0
            Maximum value: 100000
            Default value: 5
        bodyweight_exponent (float, optional): Exponent for body-weight-based dosing
            adjustment.
            Minimum value: 0
            Maximum value: 100000
            Default value: 0
        fractional_dose_by_upper_age (list[DoseFractionByAge], optional): Pediatric
            dosing fractions by age.
            Default value: []
        resistances (list[DrugModifier], optional): Drug resistance modifiers for
            parasite genetics simulations.
            Default value: []
    """

    def __init__(self,
                 name: str,
                 pkpd_model: Union[PKPDModel, str] = PKPDModel.FIXED_DURATION_CONSTANT_EFFECT,
                 drug_cmax: float = 1000,
                 drug_decay_t1: float = 1,
                 drug_decay_t2: float = 1,
                 drug_vd: float = 10,
                 drug_pkpd_c50: float = 100,
                 drug_fulltreatment_doses: int = 3,
                 drug_dose_interval: float = 1,
                 drug_gametocyte02_killrate: float = 0,
                 drug_gametocyte34_killrate: float = 0,
                 drug_gametocytem_killrate: float = 0,
                 drug_hepatocyte_killrate: float = 0,
                 max_drug_irbc_kill: float = 5,
                 bodyweight_exponent: float = 0,
                 fractional_dose_by_upper_age: list = None,
                 resistances: list = None):
        if not isinstance(pkpd_model, PKPDModel):
            try:
                pkpd_model = PKPDModel(pkpd_model)
            except ValueError:
                raise ValueError(
                    f"Invalid pkpd_model {pkpd_model!r}. "
                    f"Valid options: {list(PKPDModel)}")

        self._name = name
        self._pkpd_model = pkpd_model
        self._drug_cmax = validate_value_range(
            drug_cmax, "drug_cmax", min_value=0, max_value=100000)
        self._drug_decay_t1 = validate_value_range(
            drug_decay_t1, "drug_decay_t1", min_value=0, max_value=100000)
        self._drug_decay_t2 = validate_value_range(
            drug_decay_t2, "drug_decay_t2", min_value=0, max_value=100000)
        self._drug_vd = validate_value_range(
            drug_vd, "drug_vd", min_value=0, max_value=100000)
        self._drug_pkpd_c50 = validate_value_range(
            drug_pkpd_c50, "drug_pkpd_c50", min_value=0, max_value=100000)
        self._drug_fulltreatment_doses = validate_value_range(
            drug_fulltreatment_doses, "drug_fulltreatment_doses",
            min_value=1, max_value=100000, param_type=int)
        self._drug_dose_interval = validate_value_range(
            drug_dose_interval, "drug_dose_interval", min_value=0, max_value=100000)
        self._drug_gametocyte02_killrate = validate_value_range(
            drug_gametocyte02_killrate, "drug_gametocyte02_killrate",
            min_value=0, max_value=100000)
        self._drug_gametocyte34_killrate = validate_value_range(
            drug_gametocyte34_killrate, "drug_gametocyte34_killrate",
            min_value=0, max_value=100000)
        self._drug_gametocytem_killrate = validate_value_range(
            drug_gametocytem_killrate, "drug_gametocytem_killrate",
            min_value=0, max_value=100000)
        self._drug_hepatocyte_killrate = validate_value_range(
            drug_hepatocyte_killrate, "drug_hepatocyte_killrate",
            min_value=0, max_value=100000)
        self._max_drug_irbc_kill = validate_value_range(
            max_drug_irbc_kill, "max_drug_irbc_kill", min_value=0, max_value=100000)
        self._bodyweight_exponent = validate_value_range(
            bodyweight_exponent, "bodyweight_exponent", min_value=0, max_value=100000)
        self._fractional_dose_by_upper_age = fractional_dose_by_upper_age or []
        self._resistances = resistances or []

    @property
    def name(self) -> str:
        return self._name

    @property
    def pkpd_model(self) -> PKPDModel:
        return self._pkpd_model

    def to_schema_dict(self, manifest):
        mdp = s2c.get_class_with_defaults("idmType:MalariaDrugTypeParameters", schema_path=manifest.schema_file)
        mdp.Name = self._name
        mdp.PKPD_Model = self._pkpd_model.value
        mdp.Drug_Cmax = self._drug_cmax
        mdp.Drug_Decay_T1 = self._drug_decay_t1
        mdp.Drug_Decay_T2 = self._drug_decay_t2
        mdp.Drug_Vd = self._drug_vd
        mdp.Drug_PKPD_C50 = self._drug_pkpd_c50
        mdp.Drug_Fulltreatment_Doses = self._drug_fulltreatment_doses
        mdp.Drug_Dose_Interval = self._drug_dose_interval
        mdp.Drug_Gametocyte02_Killrate = self._drug_gametocyte02_killrate
        mdp.Drug_Gametocyte34_Killrate = self._drug_gametocyte34_killrate
        mdp.Drug_GametocyteM_Killrate = self._drug_gametocytem_killrate
        mdp.Drug_Hepatocyte_Killrate = self._drug_hepatocyte_killrate
        mdp.Max_Drug_IRBC_Kill = self._max_drug_irbc_kill
        mdp.Bodyweight_Exponent = self._bodyweight_exponent

        for dose_frac in self._fractional_dose_by_upper_age:
            mdp.Fractional_Dose_By_Upper_Age.append(
                dose_frac.to_schema_dict(manifest))

        for resistance in self._resistances:
            mdp.Resistances.append(
                resistance.to_schema_dict(manifest))

        return mdp

VectorHabitat

Defines a vector larval habitat entry for a species' Habitats list. Each habitat has a type, a maximum larval capacity, and — for LINEAR_SPLINE habitats — a time-varying capacity distribution.

For non-spline habitat types (TEMPORARY_RAINFALL, WATER_VEGETATION, HUMAN_POPULATION, CONSTANT, BRACKISH_SWAMP), only habitat_type and max_larval_capacity are needed.

For LINEAR_SPLINE, capacity_distribution_over_time is required and capacity_distribution_number_of_years may optionally be set.

Parameters:

Name	Type	Description	Default
habitat_type	(Union[HabitatType, str], required)	The type of larval habitat. Use HabitatType enum values (e.g. HabitatType.LINEAR_SPLINE, HabitatType.TEMPORARY_RAINFALL).	required
max_larval_capacity	(float, required)	The maximum larval capacity for this habitat.	required
capacity_distribution_over_time	Union[ValueMap, dict]	Required when habitat_type is LINEAR_SPLINE. A ValueMap or a dictionary with "Times" and "Values" keys that scales the larval capacity over time. Times is in days and Values are a scale factor per degrees squared. Ideally, the last value should equal the first value if they are one day apart. Example:: {"Times": [0, 30, 60, 91, 122, 152, 182, 213, 243, 274, 304, 334, 365], "Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1, 2]}	None
capacity_distribution_number_of_years	int	Only used when habitat_type is LINEAR_SPLINE. The total length of time in years for the scaling pattern. If the simulation runs longer than this, the pattern repeats. Default value: 1	1

Example

Seasonal habitat with a linear spline::

from emodpy_malaria.vector_config import VectorHabitat
from emodpy_malaria.utils.emod_enum import HabitatType

habitat = VectorHabitat(
    habitat_type=HabitatType.LINEAR_SPLINE,
    max_larval_capacity=1e8,
    capacity_distribution_over_time={
        "Times":  [0, 30, 60, 91, 122, 152, 182, 213, 243, 274, 304, 334, 365],
        "Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1, 2]
    }
)

Example

Simple constant habitat::

habitat = VectorHabitat(
    habitat_type=HabitatType.CONSTANT,
    max_larval_capacity=1e7
)

Source code in emodpy_malaria/vector_config.py

class VectorHabitat:
    """
    Defines a vector larval habitat entry for a species' **Habitats** list.
    Each habitat has a type, a maximum larval capacity, and — for
    ``LINEAR_SPLINE`` habitats — a time-varying capacity distribution.

    For non-spline habitat types (``TEMPORARY_RAINFALL``, ``WATER_VEGETATION``,
    ``HUMAN_POPULATION``, ``CONSTANT``, ``BRACKISH_SWAMP``), only
    ``habitat_type`` and ``max_larval_capacity`` are needed.

    For ``LINEAR_SPLINE``, ``capacity_distribution_over_time`` is required
    and ``capacity_distribution_number_of_years`` may optionally be set.

    Args:
        habitat_type (Union[HabitatType, str], required):
            The type of larval habitat. Use [HabitatType](https://emod.idmod.org/emodpy-malaria/autoapi/emodpy_malaria/utils/emod_enum/)
            enum values (e.g. ``HabitatType.LINEAR_SPLINE``,
            ``HabitatType.TEMPORARY_RAINFALL``).

        max_larval_capacity (float, required):
            The maximum larval capacity for this habitat.

        capacity_distribution_over_time (Union[ValueMap, dict], optional):
            Required when ``habitat_type`` is ``LINEAR_SPLINE``. A
            [ValueMap](https://emod.idmod.org/emodpy/autoapi/emodpy/campaign/common/) or a dictionary with
            ``"Times"`` and ``"Values"`` keys that scales the larval capacity
            over time. Times is in days and Values are a scale factor per
            degrees squared. Ideally, the last value should equal the first
            value if they are one day apart.

            Example::

                {"Times": [0, 30, 60, 91, 122, 152, 182, 213, 243, 274, 304, 334, 365],
                 "Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1, 2]}

        capacity_distribution_number_of_years (int, optional):
            Only used when ``habitat_type`` is ``LINEAR_SPLINE``. The total
            length of time in years for the scaling pattern. If the simulation
            runs longer than this, the pattern repeats.
            Default value: 1

    Example:
        Seasonal habitat with a linear spline::

            from emodpy_malaria.vector_config import VectorHabitat
            from emodpy_malaria.utils.emod_enum import HabitatType

            habitat = VectorHabitat(
                habitat_type=HabitatType.LINEAR_SPLINE,
                max_larval_capacity=1e8,
                capacity_distribution_over_time={
                    "Times":  [0, 30, 60, 91, 122, 152, 182, 213, 243, 274, 304, 334, 365],
                    "Values": [3, 0.8, 1.25, 0.1, 2.7, 8, 4, 35, 6.8, 6.5, 2.6, 2.1, 2]
                }
            )

    Example:
        Simple constant habitat::

            habitat = VectorHabitat(
                habitat_type=HabitatType.CONSTANT,
                max_larval_capacity=1e7
            )
    """

    def __init__(self,
                 habitat_type: Union[HabitatType, str],
                 max_larval_capacity: float,
                 capacity_distribution_over_time: Union[ValueMap, dict] = None,
                 capacity_distribution_number_of_years: int = 1,
                 campaign=None):
        if not isinstance(habitat_type, HabitatType):
            try:
                habitat_type = HabitatType(habitat_type)
            except ValueError:
                raise ValueError(
                    f"habitat_type must be a HabitatType enum value, got {habitat_type!r}. "
                    f"Valid options: {list(HabitatType)}")

        if habitat_type == HabitatType.LINEAR_SPLINE:
            if capacity_distribution_over_time is None:
                raise ValueError(
                    "capacity_distribution_over_time is required when "
                    "habitat_type is LINEAR_SPLINE.")

            if isinstance(capacity_distribution_over_time, dict):
                if "Times" not in capacity_distribution_over_time or "Values" not in capacity_distribution_over_time:
                    raise ValueError(
                        "capacity_distribution_over_time must be a dictionary "
                        "with 'Times' and 'Values' keys.")
                capacity_distribution_over_time = ValueMap(
                    times=capacity_distribution_over_time["Times"],
                    values=capacity_distribution_over_time["Values"]
                )

            if not isinstance(capacity_distribution_over_time, ValueMap):
                raise ValueError(
                    "capacity_distribution_over_time must be a ValueMap or a dict "
                    "with 'Times' and 'Values' keys.")

        self._campaign = campaign
        self._habitat_type = habitat_type
        self._max_larval_capacity = max_larval_capacity
        self._capacity_distribution_over_time = capacity_distribution_over_time
        self._capacity_distribution_number_of_years = capacity_distribution_number_of_years

    def to_schema_dict(self) -> s2c.ReadOnlyDict:
        obj = s2c.get_class_with_defaults(
            "idmType:VectorHabitat",
            schema_json=self._campaign.get_schema())
        obj.Habitat_Type = self._habitat_type
        obj.Max_Larval_Capacity = self._max_larval_capacity
        if self._habitat_type == HabitatType.LINEAR_SPLINE:
            obj.Capacity_Distribution_Number_Of_Years = self._capacity_distribution_number_of_years
            obj.Capacity_Distribution_Over_Time = self._capacity_distribution_over_time.to_schema_dict(self._campaign)
        obj.pop("schema", None)
        obj.pop("explicits", None)
        return obj

VectorSpeciesParameters

Defines a vector species and its biological parameters for use in Vector_Species_Params. Each species entry controls mosquito behavior: feeding preferences, life expectancy, habitat, transmission efficiency, and temperature-dependent development rates.

Use the constructor to create a species from scratch, or use from_preset() to start from a built-in species template (gambiae, arabiensis, funestus, etc.) and override selected parameters.

Parameters:

Name	Type	Description	Default
name	(str, required)	Name of the vector species. Must be unique within the simulation's Vector_Species_Params list.	required
habitats	(list[VectorHabitat], required)	List of VectorHabitat objects defining the larval habitat types and capacities for this species.	required
anthropophily	float	Fraction of blood meals taken from humans vs. animals. Default value: 0.65	0.65
indoor_feeding_fraction	float	Fraction of human feeds that occur indoors. Default value: 0.95	0.95
adult_life_expectancy	float	Average female mosquito lifespan in days. Default value: 20	20
male_life_expectancy	float	Average male mosquito lifespan in days. Default value: 10	10
transmission_rate	float	Probability that a bite from an infectious mosquito infects a naive, uninfected individual. Default value: 0.9	0.9
acquire_modifier	float	Modifier of the probability that a mosquito becomes infected when feeding on an infectious human. Default value: 0.8	0.8
egg_batch_size	float	Number of eggs laid per successful blood meal. Default value: 100	100
days_between_feeds	float	Average number of days between blood-feeding attempts. Default value: 3	3
aquatic_mortality_rate	float	Base daily mortality rate for aquatic-stage larvae. Default value: 0.1	0.1
immature_duration	float	Days for larvae to develop into adults. Default value: 2	2
infected_egg_batch_factor	float	Multiplier on egg batch size for infected females. Default value: 0.8	0.8
infectious_human_feed_mortality_factor	float	Multiplier on feeding mortality for infected mosquitoes. Default value: 1.5	1.5
vector_sugar_feeding_frequency	str	Sugar-feeding behavior. One of "VECTOR_SUGAR_FEEDING_NONE", "VECTOR_SUGAR_FEEDING_ON_EMERGENCE_ONLY", "VECTOR_SUGAR_FEEDING_EVERY_FEED", "VECTOR_SUGAR_FEEDING_EVERY_DAY". Default value: "VECTOR_SUGAR_FEEDING_NONE"	'VECTOR_SUGAR_FEEDING_NONE'

Example

Create a custom species with a seasonal spline habitat::

habitat = VectorHabitat(HabitatType.LINEAR_SPLINE,
                        max_larval_capacity=1e8,
                        capacity_distribution_over_time={...})
species = VectorSpeciesParameters(name="gambiae",
                                  habitats=[habitat],
                                  anthropophily=0.65,
                                  indoor_feeding_fraction=0.95)
config.parameters.Vector_Species_Params.append(species.to_schema_dict())

Example

Load a built-in preset and override one parameter::

species = VectorSpeciesParameters.from_preset(campaign, manifest, "arabiensis")
species.indoor_feeding_fraction = 0.3
config.parameters.Vector_Species_Params.append(species.to_schema_dict())

Source code in emodpy_malaria/vector_config.py

class VectorSpeciesParameters:
    """
    Defines a vector species and its biological parameters for use in
    **Vector_Species_Params**. Each species entry controls mosquito
    behavior: feeding preferences, life expectancy, habitat, transmission
    efficiency, and temperature-dependent development rates.

    Use the constructor to create a species from scratch, or use
    `from_preset()` to start from a built-in species template
    (gambiae, arabiensis, funestus, etc.) and override selected parameters.

    Args:
        name (str, required):
            Name of the vector species. Must be unique within the simulation's
            Vector_Species_Params list.

        habitats (list[VectorHabitat], required):
            List of [VectorHabitat](https://emod.idmod.org/emodpy-malaria/autoapi/emodpy_malaria/vector_config/) objects defining the larval habitat
            types and capacities for this species.

        anthropophily (float, optional):
            Fraction of blood meals taken from humans vs. animals.
            Default value: 0.65

        indoor_feeding_fraction (float, optional):
            Fraction of human feeds that occur indoors.
            Default value: 0.95

        adult_life_expectancy (float, optional):
            Average female mosquito lifespan in days.
            Default value: 20

        male_life_expectancy (float, optional):
            Average male mosquito lifespan in days.
            Default value: 10

        transmission_rate (float, optional):
            Probability that a bite from an infectious mosquito infects
            a naive, uninfected individual.
            Default value: 0.9

        acquire_modifier (float, optional):
            Modifier of the probability that a mosquito becomes infected
            when feeding on an infectious human.
            Default value: 0.8

        egg_batch_size (float, optional):
            Number of eggs laid per successful blood meal.
            Default value: 100

        days_between_feeds (float, optional):
            Average number of days between blood-feeding attempts.
            Default value: 3

        aquatic_mortality_rate (float, optional):
            Base daily mortality rate for aquatic-stage larvae.
            Default value: 0.1

        immature_duration (float, optional):
            Days for larvae to develop into adults.
            Default value: 2

        infected_egg_batch_factor (float, optional):
            Multiplier on egg batch size for infected females.
            Default value: 0.8

        infectious_human_feed_mortality_factor (float, optional):
            Multiplier on feeding mortality for infected mosquitoes.
            Default value: 1.5

        vector_sugar_feeding_frequency (str, optional):
            Sugar-feeding behavior. One of ``"VECTOR_SUGAR_FEEDING_NONE"``,
            ``"VECTOR_SUGAR_FEEDING_ON_EMERGENCE_ONLY"``,
            ``"VECTOR_SUGAR_FEEDING_EVERY_FEED"``,
            ``"VECTOR_SUGAR_FEEDING_EVERY_DAY"``.
            Default value: ``"VECTOR_SUGAR_FEEDING_NONE"``

    Example:
        Create a custom species with a seasonal spline habitat::

            habitat = VectorHabitat(HabitatType.LINEAR_SPLINE,
                                    max_larval_capacity=1e8,
                                    capacity_distribution_over_time={...})
            species = VectorSpeciesParameters(name="gambiae",
                                              habitats=[habitat],
                                              anthropophily=0.65,
                                              indoor_feeding_fraction=0.95)
            config.parameters.Vector_Species_Params.append(species.to_schema_dict())

    Example:
        Load a built-in preset and override one parameter::

            species = VectorSpeciesParameters.from_preset(campaign, manifest, "arabiensis")
            species.indoor_feeding_fraction = 0.3
            config.parameters.Vector_Species_Params.append(species.to_schema_dict())
    """

    def __init__(self,
                 name: str,
                 habitats: list,
                 anthropophily: float = 0.65,
                 indoor_feeding_fraction: float = 0.95,
                 adult_life_expectancy: float = 20,
                 male_life_expectancy: float = 10,
                 transmission_rate: float = 0.9,
                 acquire_modifier: float = 0.8,
                 egg_batch_size: float = 100,
                 days_between_feeds: float = 3,
                 aquatic_mortality_rate: float = 0.1,
                 immature_duration: float = 2,
                 infected_egg_batch_factor: float = 0.8,
                 infectious_human_feed_mortality_factor: float = 1.5,
                 aquatic_arrhenius_1: float = 84200000000,
                 aquatic_arrhenius_2: float = 8328,
                 infected_arrhenius_1: float = 117000000000,
                 infected_arrhenius_2: float = 8336,
                 cycle_arrhenius_1: float = 40900000000,
                 cycle_arrhenius_2: float = 7740,
                 cycle_arrhenius_reduction_factor: float = 1.0,
                 vector_sugar_feeding_frequency: str = "VECTOR_SUGAR_FEEDING_NONE",
                 temperature_dependent_feeding_cycle: str = "NO_TEMPERATURE_DEPENDENCE",
                 campaign=None):
        self._campaign = campaign
        self.name = name
        self.habitats = habitats
        self.anthropophily = anthropophily
        self.indoor_feeding_fraction = indoor_feeding_fraction
        self.adult_life_expectancy = adult_life_expectancy
        self.male_life_expectancy = male_life_expectancy
        self.transmission_rate = transmission_rate
        self.acquire_modifier = acquire_modifier
        self.egg_batch_size = egg_batch_size
        self.days_between_feeds = days_between_feeds
        self.aquatic_mortality_rate = aquatic_mortality_rate
        self.immature_duration = immature_duration
        self.infected_egg_batch_factor = infected_egg_batch_factor
        self.infectious_human_feed_mortality_factor = infectious_human_feed_mortality_factor
        self.aquatic_arrhenius_1 = aquatic_arrhenius_1
        self.aquatic_arrhenius_2 = aquatic_arrhenius_2
        self.infected_arrhenius_1 = infected_arrhenius_1
        self.infected_arrhenius_2 = infected_arrhenius_2
        self.cycle_arrhenius_1 = cycle_arrhenius_1
        self.cycle_arrhenius_2 = cycle_arrhenius_2
        self.cycle_arrhenius_reduction_factor = cycle_arrhenius_reduction_factor
        self.vector_sugar_feeding_frequency = vector_sugar_feeding_frequency
        self.temperature_dependent_feeding_cycle = temperature_dependent_feeding_cycle

    @classmethod
    def from_preset(cls, campaign: object, manifest: object, species_name: str) -> "VectorSpeciesParameters":
        """
        Create a VectorSpeciesParameters from a built-in species preset.

        Built-in species: gambiae, arabiensis, funestus, fpg_gambiae,
        minimus, dirus.

        Args:
            campaign (object): An instance of the emod_api.campaign module.
            manifest (object): Manifest module containing the schema path.
            species_name (str): Name of a built-in species.

        Returns:
            VectorSpeciesParameters: An instance with preset values that
            can be modified before calling ``to_schema_dict()``.
        """
        import copy
        from emodpy_malaria.malaria_vector_species_params import _SPECIES_DATA

        if species_name not in _SPECIES_DATA:
            available = list(_SPECIES_DATA.keys())
            raise ValueError(
                f"Species {species_name!r} not found. "
                f"Available presets: {available}")

        if not campaign.get_schema():
            campaign.set_schema(manifest.schema_file)

        species = copy.deepcopy(_SPECIES_DATA[species_name])
        species._campaign = campaign
        for h in species.habitats:
            h._campaign = campaign
        return species

    def to_schema_dict(self) -> s2c.ReadOnlyDict:
        obj = s2c.get_class_with_defaults(
            "idmType:VectorSpeciesParameters",
            schema_json=self._campaign.get_schema())
        obj.Name = self.name
        obj.Anthropophily = self.anthropophily
        obj.Indoor_Feeding_Fraction = self.indoor_feeding_fraction
        obj.Adult_Life_Expectancy = self.adult_life_expectancy
        obj.Male_Life_Expectancy = self.male_life_expectancy
        obj.Transmission_Rate = self.transmission_rate
        obj.Acquire_Modifier = self.acquire_modifier
        obj.Egg_Batch_Size = self.egg_batch_size
        obj.Days_Between_Feeds = self.days_between_feeds
        obj.Aquatic_Mortality_Rate = self.aquatic_mortality_rate
        obj.Immature_Duration = self.immature_duration
        obj.Infected_Egg_Batch_Factor = self.infected_egg_batch_factor
        obj.Infectious_Human_Feed_Mortality_Factor = self.infectious_human_feed_mortality_factor
        obj.Aquatic_Arrhenius_1 = self.aquatic_arrhenius_1
        obj.Aquatic_Arrhenius_2 = self.aquatic_arrhenius_2
        obj.Infected_Arrhenius_1 = self.infected_arrhenius_1
        obj.Infected_Arrhenius_2 = self.infected_arrhenius_2
        obj.Cycle_Arrhenius_1 = self.cycle_arrhenius_1
        obj.Cycle_Arrhenius_2 = self.cycle_arrhenius_2
        obj.Cycle_Arrhenius_Reduction_Factor = self.cycle_arrhenius_reduction_factor
        obj.Vector_Sugar_Feeding_Frequency = self.vector_sugar_feeding_frequency
        obj.Temperature_Dependent_Feeding_Cycle = self.temperature_dependent_feeding_cycle
        obj.Habitats = [h.to_schema_dict() if hasattr(h, 'to_schema_dict') else h
                        for h in self.habitats]
        obj.pop("schema", None)
        obj.pop("explicits", None)
        return obj

from_preset(campaign, manifest, species_name) classmethod

Create a VectorSpeciesParameters from a built-in species preset.

Built-in species: gambiae, arabiensis, funestus, fpg_gambiae, minimus, dirus.

Parameters:

Name	Type	Description	Default
campaign	object	An instance of the emod_api.campaign module.	required
manifest	object	Manifest module containing the schema path.	required
species_name	str	Name of a built-in species.	required

Returns:

Name	Type	Description
VectorSpeciesParameters	VectorSpeciesParameters	An instance with preset values that
	VectorSpeciesParameters	can be modified before calling to_schema_dict().

Source code in emodpy_malaria/vector_config.py

@classmethod
def from_preset(cls, campaign: object, manifest: object, species_name: str) -> "VectorSpeciesParameters":
    """
    Create a VectorSpeciesParameters from a built-in species preset.

    Built-in species: gambiae, arabiensis, funestus, fpg_gambiae,
    minimus, dirus.

    Args:
        campaign (object): An instance of the emod_api.campaign module.
        manifest (object): Manifest module containing the schema path.
        species_name (str): Name of a built-in species.

    Returns:
        VectorSpeciesParameters: An instance with preset values that
        can be modified before calling ``to_schema_dict()``.
    """
    import copy
    from emodpy_malaria.malaria_vector_species_params import _SPECIES_DATA

    if species_name not in _SPECIES_DATA:
        available = list(_SPECIES_DATA.keys())
        raise ValueError(
            f"Species {species_name!r} not found. "
            f"Available presets: {available}")

    if not campaign.get_schema():
        campaign.set_schema(manifest.schema_file)

    species = copy.deepcopy(_SPECIES_DATA[species_name])
    species._campaign = campaign
    for h in species.habitats:
        h._campaign = campaign
    return species

add_blood_meal_mortality(config, manifest, species, allele_combo, default_probability_of_death, probability_of_death_for_allele_combo)

Add a probability of death after a mosquito has a blood meal. There are some genetically modified mosquitoes that have a fitness cost associated with the digestion of a blood meal. This affects vectors whether this is a human or animal blood meal. This is a GeneticProbability such that the probability used can depend on the genetic makeup of the mosquito. The deaths from this are added to the "die after feeding" numbers for vectors that have fed on humans and "die before feeding on a human" for vectors that die after animal blood meal.

If you need to add multiple allele combos for the same species, call this method once for each allele combo and associated probability. If you do, please note that the default probability will be combined by OR'ing the different values together [1-((1-p1)*(1-p2))]. Also note that the default probabilities for each species will be OR'd together.

The probability selected for given genome will depend on the "complexity" of the allele combinations. If an entry has more genes/loci positions than another, the combination with more will be considered first. If they have the same number of genes and one has fewer possible genomes, the one with fewer possible genomes will be considered first. For example, if you add a1-a1 in one call and b1-b0 in a second call, EMOD will first check if the genome has a1-a1. If it has a1-a1, it will get that probability. If it does not, it will check if the genome has b1-b0 or b0-b1. The entered values are not combined in any way. It is up to the user to specify the probability for specific combinations.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest module containing the schema path	required
species	str	Name of the species of vectors to give the specific probability to.	required
allele_combo	list	The combination of alleles that a mosquito's genome must have in order to apply associated probability. You do not need to specify alleles for every locus. The ones not defined are not considered in the match This should be a two-dimensional array where each internal array has two strings representing two alleles of the same locus. Each separate internal array represents locus, and you can only have one entry per locus. You can use '' for an allele to say any allele. For example, [ ["a1", "a1"], ["b1, ""] ] says any mosquito with a1-a1 in the first locus and b1 in either chromosome of the second locus.	required
default_probability_of_death	float	The probability used if the genome of the mosquito does not match any of the defined allele combinations in Genetic_Probabilities.	required
probability_of_death_for_allele_combo	float	The probability to use if the genome of the mosquito has the matching Allele_Combinations. The default is zero.	required

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_blood_meal_mortality(config, manifest,
                             species: str,
                             allele_combo: list,
                             default_probability_of_death: float,
                             probability_of_death_for_allele_combo: float):
    """
    Add a probability of death after a mosquito has a blood meal.  There are some genetically
    modified mosquitoes that have a fitness cost associated with the digestion of a blood meal.
    This affects vectors whether this is a human or animal blood meal.
    This is a GeneticProbability such that the probability used can depend on the genetic makeup
    of the mosquito.  The deaths from this are added to the "die after feeding" numbers for
    vectors that have fed on humans and "die before feeding on a human" for vectors that
    die after animal blood meal.

    If you need to add multiple allele combos for the same species, call this method once for
    each allele combo and associated probability.  If you do, please note that the default
    probability will be combined by OR'ing the different values together [1-((1-p1)*(1-p2))].
    Also note that the default probabilities for each species will be OR'd together.

    The probability selected for given genome will depend on the "complexity" of the allele
    combinations.  If an entry has more genes/loci positions than another, the combination with
    more will be considered first.  If they have the same number of genes and one has fewer
    possible genomes, the one with fewer possible genomes will be considered first.  For example,
    if you add a1-a1 in one call and b1-b0 in a second call, EMOD will first check if the genome
    has a1-a1.  If it has a1-a1, it will get that probability.  If it does not, it will check
    if the genome has b1-b0 or b0-b1.  The entered values are not combined in any way.  It is up
    to the user to specify the probability for specific combinations.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest module containing the schema path
        species (str): Name of the species of vectors to give the specific probability to.
        allele_combo (list): The combination of alleles that a mosquito's genome must have in order to
            apply associated probability.  You do not need to specify alleles for every locus.
            The ones not defined are not considered in the match  This should be a two-dimensional
            array where each internal array has two strings representing two alleles of the same
            locus.  Each separate internal array represents locus, and you can only have one entry
            per locus.  You can use '*' for an allele to say any allele. For example,
            [ ["a1", "a1"], ["b1, "*"] ] says any mosquito with a1-a1 in the first locus and
            b1 in either chromosome of the second locus.
        default_probability_of_death (float): The probability used if the genome of the mosquito does not
            match any of the defined allele combinations in Genetic_Probabilities.
        probability_of_death_for_allele_combo (float): The probability to use if the genome of the mosquito
            has the matching Allele_Combinations.  The default is zero.

    Returns:
        (dict): configured config
    """

    # checks if species name is valid
    species_params = get_species_params(config, species)

    if (default_probability_of_death < 0.0) or (1.0 < default_probability_of_death):
        raise ValueError(f"Invalid value for 'default_probability_of_death'={default_probability_of_death}.\n"
                         f"The value must be between 0 and 1.\n")

    validate_allele_combo(species_params=species_params, allele_combo=allele_combo)

    if (probability_of_death_for_allele_combo < 0.0) or (1.0 < probability_of_death_for_allele_combo):
        raise ValueError(f"Invalid value for 'probability_of_death_for_allele_combo'={probability_of_death_for_allele_combo}.\n"
                         f"The value must be between 0 and 1.\n")

    acp = s2c.get_class_with_defaults("idmType:AlleleComboProbabilityConfig", schema_path=manifest.schema_file)
    acp.Allele_Combinations = allele_combo
    acp.Probability = probability_of_death_for_allele_combo

    species_params.Blood_Meal_Mortality.Genetic_Probabilities.append(acp)

    default_prob = species_params.Blood_Meal_Mortality.Default_Probability
    default_prob = 1.0 - ((1.0 - default_prob) * (1.0 - default_probability_of_death))
    species_params.Blood_Meal_Mortality.Default_Probability = default_prob

    return config

add_drug_resistance(config, manifest, drugname, drug_resistant_string, pkpd_c50_modifier=1.0, max_irbc_kill_modifier=1.0)

Adds a drug resistance modifier to an existing drug in the simulation config.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
drugname	str	name of the drug for which to assign resistances	required
drug_resistant_string	str	Nucleotide base letters (A, C, G, T) representing resistance at specific genome locations.	required
pkpd_c50_modifier	float	Multiplier applied to the drug's Drug_PKPD_C50 when the parasite genome matches. Genomes with multiple markers have modifiers multiplied together. Default: 1.0.	1.0
max_irbc_kill_modifier	float	Multiplier applied to the drug's Max_Drug_IRBC_Kill when the parasite genome matches. Default: 1.0.	1.0

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/malaria_config.py

def add_drug_resistance(config, manifest, drugname: str, drug_resistant_string: str,
                        pkpd_c50_modifier: float = 1.0, max_irbc_kill_modifier: float = 1.0):
    """
    Adds a drug resistance modifier to an existing drug in the simulation config.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        drugname (str): name of the drug for which to assign resistances
        drug_resistant_string (str): Nucleotide base letters (A, C, G, T) representing
            resistance at specific genome locations.
        pkpd_c50_modifier (float): Multiplier applied to the drug's Drug_PKPD_C50
            when the parasite genome matches. Genomes with multiple markers have
            modifiers multiplied together. Default: 1.0.
        max_irbc_kill_modifier (float): Multiplier applied to the drug's
            Max_Drug_IRBC_Kill when the parasite genome matches. Default: 1.0.

    Returns:
        (dict): configured config
    """
    modifier = DrugModifier(
        drug_resistant_string=drug_resistant_string,
        pkpd_c50_modifier=pkpd_c50_modifier,
        max_irbc_kill_modifier=max_irbc_kill_modifier,
    )

    for drug_param in config.parameters.Malaria_Drug_Params:
        if drug_param.Name == drugname:
            drug_param.Resistances.append(modifier.to_schema_dict(manifest))
            return config

    raise ValueError(f"Drug name {drugname} not found.\n")

add_genes_and_alleles(config, manifest, species, alleles)

Adds alleles to a species

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
species	str	species to which to assign the alleles	required
alleles	list[tuple]	List of tuples of (Name, Initial_Allele_Frequency, Is_Y_Chromosome) for a set of alleles or (Name, Initial_Allele_Frequency), 1/0 or True/False can be used for Is_Y_Chromosome, third parameter is assumed False (0). If the third parameter is set to 1 in any of the tuples, we assume, this is a gender gene.	required

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_genes_and_alleles(config, manifest, species: str, alleles: list[tuple]):
    """
    Adds alleles to a species

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        species (str): species to which to assign the **alleles**
        alleles (list[tuple]): List of tuples of (Name, Initial_Allele_Frequency, Is_Y_Chromosome) for a set of alleles
            or (Name, Initial_Allele_Frequency), 1/0 or True/False can be used for Is_Y_Chromosome,
            third parameter is assumed False (0). If the third parameter is set to 1 in any of the tuples,
            we assume, this is a gender gene.

    Returns:
        (dict): configured config
    """

    if not species or not alleles or not config or not manifest:
        raise ValueError("Please set all parameters, 'alleles' needs to be a list of tuples.\n")

    gene = s2c.get_class_with_defaults("idmType:VectorGene", schema_path=manifest.schema_file)
    for allele in alleles:
        vector_allele = s2c.get_class_with_defaults("idmType:VectorAllele", schema_path=manifest.schema_file)
        vector_allele.Name = allele[0]
        vector_allele.Initial_Allele_Frequency = allele[1]
        if len(allele) == 3:
            if allele[2]:
                gene.Is_Gender_Gene = 1
                vector_allele.Is_Y_Chromosome = 1
        gene.Alleles.append(vector_allele)

    species_params = get_species_params(config, species)
    species_params.Genes.append(gene)

    return config

add_insecticide_resistance(config, manifest, insecticide_name, species, allele_combo, blocking=1.0, killing=1.0, repelling=1.0, larval_killing=1.0)

Use this function to add to the list of **Resistances** parameter for a specific insecticide
Add each resistance separately.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
insecticide_name	str	The name of the insecticide to which attach the resistance.	required
species	str	Name of the species of vectors. Must be one of the species defined for this simulation.	required
allele_combo	list[list[str]]	List of combination of alleles that vectors must have in order to be resistant. All the genes defined for the species must be present in the combo, but not all the alleles need to be defined. You can use * symbol for alleles to say any allele. For example, [[a1,a1],[b0,*]] matches any vector with a1-a1 in the first gene and b0 in the second gene regardless of the other b-gene allele.	required
blocking	float	The value used to modify (multiply) the blocking effectivity of an intervention. The intervention must have a blocking effect for this to have an effect. Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.	1.0
killing	float	The value used to modify (multiply) the killing effectivity of an intervention. The intervention must have a killing effect for this to have an effect. Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.	1.0
repelling	float	The value used to modify (multiply) the repelling effectivity of an intervention. The intervention must have a repelling effect for this to have an effect. Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.	1.0
larval_killing	float	The value used to modify (multiply) the larval killing effectivity of an intervention. The intervention must have a larval killing effect for this to have an effect (e.g. larvicides). Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.	1.0

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_insecticide_resistance(config, manifest, insecticide_name: str, species: str,
                               allele_combo: list[list[str]], blocking: float = 1.0, killing: float = 1.0,
                               repelling: float = 1.0, larval_killing: float = 1.0):
    """
        Use this function to add to the list of **Resistances** parameter for a specific insecticide
        Add each resistance separately.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        insecticide_name (str): The name of the insecticide to which attach the resistance.
        species (str): Name of the species of vectors. Must be one of the species defined for this simulation.
        allele_combo (list[list[str]]): List of combination of alleles that vectors must have in order to be resistant.
            All the genes defined for the **species** must be present in the combo, but not all the alleles need to be
            defined. You can use * symbol for alleles to say any allele. For example, [[a1,a1],[b0,*]] matches
            any vector with a1-a1 in the first gene and b0 in the second gene regardless of the other b-gene allele.
        blocking (float): The value used to modify (multiply) the blocking effectivity of an intervention. The intervention
            must have a blocking effect for this to have an effect.
            Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.
        killing (float): The value used to modify (multiply) the killing effectivity of an intervention. The intervention
            must have a killing effect for this to have an effect.
            Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.
        repelling (float): The value used to modify (multiply) the repelling effectivity of an intervention. The intervention
            must have a repelling effect for this to have an effect.
            Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.
        larval_killing (float): The value used to modify (multiply) the larval **killing** effectivity of an intervention.
            The intervention must have a larval **killing** effect for this to have an effect (e.g. larvicides).
            Default is 1, values less than 1 reduce the effectivity, and values greater than 1 increase the effectivity.

    Returns:
        (dict): configured config
    """

    # checks if species name is valid
    species_params = get_species_params(config, species)
    validate_allele_combo(species_params=species_params, allele_combo=allele_combo)

    resistance = s2c.get_class_with_defaults("idmType:ResistantAlleleComboProbabilityConfig", schema_path=manifest.schema_file)
    resistance.Blocking_Modifier = blocking
    resistance.Killing_Modifier = killing
    resistance.Repelling_Modifier = repelling
    resistance.Larval_Killing_Modifier = larval_killing
    resistance.Species = species
    resistance.Allele_Combinations = allele_combo

    insecticides = config.parameters.Insecticides
    for an_insecticide in insecticides:
        if an_insecticide.Name == insecticide_name:
            an_insecticide.Resistances.append(resistance)
            return config

    new_insecticide = s2c.get_class_with_defaults("idmType:Insecticide", schema_path=manifest.schema_file)
    new_insecticide.Name = insecticide_name
    new_insecticide.Resistances.append(resistance)
    config.parameters.Insecticides.append(new_insecticide)

    return config

add_maternal_deposition(config, manifest, species, cas9_grna_from, allele_to_cut, likelihood_list)

Adds a maternal deposition element for the specified species.
After meiosis and fertilization, maternal deposition of Cas9 and gRNA can form additional drive-resistant alleles
in the zygote or early embryo from wildtype alleles. These elements define the likelihoods of forming additional
drive-resistant alleles.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
species	str	Name of the species for which we're adding the maternal deposition element.	required
cas9_grna_from	str	This is an allele for presence of which in the mother we will be checking to see if additional resistance alleles will be formed. This is the allele must be one of the 'driving_alleles' from vector_config.add_species_drivers() function.	required
allele_to_cut	str	The allele from which resistance alleles might be formed due to maternal deposition. This must be one of the 'to_replace' alleles defined in the vector_config.add_species_drivers() function.	required
likelihood_list	list	A list of tuples in format: [(, ),(),()] which will be converted to an array of allele-to-likelihood dictionaries to be applied to the 'allele_to_cut' for each 'cas9_grna_from' present in the mother. The sum of likelihoods should be equal to 1.	required

Returns:

Type	Description
dict	Config object with maternal deposition parameters added for the specified species.

Source code in emodpy_malaria/vector_config.py

def add_maternal_deposition(config, manifest, species: str, cas9_grna_from: str,
                            allele_to_cut: str, likelihood_list: list):
    """
        Adds a maternal deposition element for the specified species.
        After meiosis and fertilization, maternal deposition of Cas9 and gRNA can form additional drive-resistant alleles
        in the zygote or early embryo from wildtype alleles. These elements define the likelihoods of forming additional
        drive-resistant alleles.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        species (str): Name of the species for which we're adding the maternal deposition element.
        cas9_grna_from (str): This is an allele for presence of which in the mother we will be checking to see if additional
            resistance alleles will be formed. This is the allele must be one of the 'driving_alleles' from
            vector_config.add_species_drivers() function.
        allele_to_cut (str): The allele from which resistance alleles might be formed due to maternal deposition. This must
            be one of the 'to_replace' alleles defined in the vector_config.add_species_drivers() function.
        likelihood_list (list): A list of tuples in format: [(<cut_to_allele>, <likelihood>),(),()] which will be converted
            to an array of allele-to-likelihood dictionaries to be applied to the '**allele_to_cut**' for each
            '**cas9_grna_from**' present in the mother. The sum of likelihoods should be equal to 1.

    Returns:
        (dict): Config object with maternal deposition parameters added for the specified species.
    """

    sp_params = get_species_params(config, species)
    found_driver = False
    found_allele_to_cut = False
    allele_to_copy = ""
    for driver in sp_params.Drivers:
        if cas9_grna_from == driver.Driving_Allele:
            found_driver = True
            for allele_driven in driver.Alleles_Driven:
                if allele_to_cut == allele_driven.Allele_To_Replace:
                    found_allele_to_cut = True
                    allele_to_copy = allele_driven.Allele_To_Copy
                    break
    if not found_driver:
        raise ValueError(f"Failed to find 'cas9_grna_from' = '{cas9_grna_from}' in the drivers for species '{species}'."
                         f"\n'cas9_grna_from' must be one of the 'driving_alleles' defined in the "
                         f"vector_config.add_species_drivers() function.\n Please make sure the drivers are added "
                         f"before the maternal deposition.\n")
    if not found_allele_to_cut:
        raise ValueError(f"Failed to find 'allele_to_cut' = '{allele_to_cut}' in the drivers for species '{species}'.\n"
                         f"'allele_to_cut' must be one of the 'to_replace' alleles defined for 'driving_allele'="
                         f"'{cas9_grna_from}' in the "
                         f"vector_config.add_species_drivers() function.\n Please make sure the drivers are added "
                         f"before the maternal deposition.\n")

    maternal_deposition = s2c.get_class_with_defaults("idmType:MaternalDeposition", schema_path=manifest.schema_file)
    maternal_deposition.Cas9_gRNA_From = cas9_grna_from
    maternal_deposition.Allele_To_Cut = allele_to_cut

    total = 0.0
    for index, likely in enumerate(likelihood_list):
        c2likelyhood = s2c.get_class_with_defaults("idmType:CutToAlleleLikelihood", schema_path=manifest.schema_file)
        if likely[0] == allele_to_copy:
            raise ValueError(f"Element at index '{index}' in the 'likelihood_list' has allele '{likely[0]}', but it "
                             f"is also an 'allele_to_copy' for the 'driving_allele' = '{cas9_grna_from}' and cannot be"
                             f" cut to in maternal deposition.\n")
        c2likelyhood.Cut_To_Allele = likely[0]
        total += likely[1]
        c2likelyhood.Likelihood = likely[1]
        maternal_deposition.Likelihood_Per_Cas9_gRNA_From.append(c2likelyhood)
    if not math.isclose(total, 1.0, rel_tol=1e-6):
        raise ValueError(f"The sum of likelihoods in the 'likelihood_list' must be equal to 1.0, but got {total}.\n")

    sp_params.Maternal_Deposition.append(maternal_deposition)

    return config

add_microsporidia(config, manifest, species_name=None, strain_name='Strain_A', female_to_male_probability=0, female_to_egg_probability=0, male_to_female_probability=0, male_to_egg_probability=0, duration_to_disease_acquisition_modification=None, duration_to_disease_transmission_modification=None, larval_growth_modifier=1, female_mortality_modifier=1, male_mortality_modifier=1)

Adds microsporidia parameters to the named species' parameters.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config dictionary, written to config.json	required
manifest	ModuleType	file that contains path to the schema file	required
species_name	str	Species to target, Name parameter	None
strain_name	str	Strain_Name The name/identifier of the collection of transmission parameters. Cannot be empty string	'Strain_A'
female_to_male_probability	float	Microsporidia_Female_to_Male_Transmission_Probability The probability an infected female will infect an uninfected male.	0
female_to_egg_probability	float	Microsporidia_Female_To_Egg_Transmission_Probability The probability an infected female will infect her eggs when laying them.	0
male_to_female_probability	float	Microsporidia_Male_To_Female_Transmission_Probability The probability an infected male will infect an uninfected female	0
male_to_egg_probability	float	Microsporidia_Male_To_Egg_Transmission_Probability The probability a female that mated with an infected male will infect her eggs when laying them, independent of her being infected and transmitting to her offspring.	0
duration_to_disease_acquisition_modification	Union[ValueMap, dict]	Microsporidia_Duration_To_Disease_Acquisition_Modification, a ValueMap or a dict with "Times" and "Values" keys as an age-based modification that the female will acquire malaria. Times is an array of days in ascending order since infection. Values are probabilities (0-1). Defaults to ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.5, 0.0]).	None
duration_to_disease_transmission_modification	Union[ValueMap, dict]	Microsporidia_Duration_To_Disease_Transmission_Modification, a ValueMap or a dict with "Times" and "Values" keys as an age-based modification that the female will transmit malaria. Times is an array of days in ascending order since infection. Values are probabilities (0-1). Defaults to ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.75, 0.5]).	None
larval_growth_modifier	float	Microsporidia_Larval_Growth_Modifier A multiplier modifier to the daily, temperature dependent, larval growth progress.	1
female_mortality_modifier	float	Microsporidia_Female_Mortality_Modifier A multiplier modifier on the death rate for female vectors due to general life expectancy, age, and dry heat	1
male_mortality_modifier	float	Microsporidia_Male_Mortality_Modifier A multiplier modifier on the death rate for male vectors due to general life expectancy, age, and dry heat	1

Source code in emodpy_malaria/vector_config.py

def add_microsporidia(config, manifest, species_name: str = None,
                      strain_name: str = "Strain_A",
                      female_to_male_probability: float = 0,
                      female_to_egg_probability: float = 0,
                      male_to_female_probability: float = 0,
                      male_to_egg_probability: float = 0,
                      duration_to_disease_acquisition_modification: Union[ValueMap, dict] = None,
                      duration_to_disease_transmission_modification: Union[ValueMap, dict] = None,
                      larval_growth_modifier: float = 1,
                      female_mortality_modifier: float = 1,
                      male_mortality_modifier: float = 1):
    """
        Adds microsporidia parameters to the named species' parameters.

    Args:
        config (dict): schema-backed config dictionary, written to config.json
        manifest (ModuleType): file that contains path to the schema file
        species_name (str): Species to target, Name parameter
        strain_name (str): Strain_Name The name/identifier of the collection of transmission parameters.
            Cannot be empty string
        female_to_male_probability (float): Microsporidia_Female_to_Male_Transmission_Probability The probability
            an infected female will infect an uninfected male.
        female_to_egg_probability (float): Microsporidia_Female_To_Egg_Transmission_Probability The probability
            an infected female will infect her eggs when laying them.
        male_to_female_probability (float): Microsporidia_Male_To_Female_Transmission_Probability The probability
            an infected male will infect an uninfected female
        male_to_egg_probability (float): Microsporidia_Male_To_Egg_Transmission_Probability The probability a female that
            mated with an infected male will infect her eggs when laying them, independent of her being infected and
            transmitting to her offspring.
        duration_to_disease_acquisition_modification (Union[ValueMap, dict]):
            Microsporidia_Duration_To_Disease_Acquisition_Modification,
            a [ValueMap](https://emod.idmod.org/emodpy/autoapi/emodpy/campaign/common/) or a dict with "Times" and "Values" keys
            as an age-based modification that the female will acquire malaria.
            Times is an array of days in ascending order since infection. Values are probabilities (0-1).
            Defaults to ``ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.5, 0.0])``.
        duration_to_disease_transmission_modification (Union[ValueMap, dict]):
            Microsporidia_Duration_To_Disease_Transmission_Modification,
            a [ValueMap](https://emod.idmod.org/emodpy/autoapi/emodpy/campaign/common/) or a dict with "Times" and "Values" keys
            as an age-based modification that the female will transmit malaria.
            Times is an array of days in ascending order since infection. Values are probabilities (0-1).
            Defaults to ``ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.75, 0.5])``.
        larval_growth_modifier (float): Microsporidia_Larval_Growth_Modifier A multiplier modifier to the daily, temperature
            dependent, larval growth progress.
        female_mortality_modifier (float): Microsporidia_Female_Mortality_Modifier A multiplier modifier on the death
            rate for female vectors due to general life expectancy, age, and dry heat
        male_mortality_modifier (float): Microsporidia_Male_Mortality_Modifier A multiplier modifier on the death rate for
            male vectors due to general life expectancy, age, and dry heat
    """
    if not strain_name:
        raise ValueError("Please define strain_name.\n")
    if duration_to_disease_acquisition_modification is None:
        duration_to_disease_acquisition_modification = ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.5, 0.0])
    elif isinstance(duration_to_disease_acquisition_modification, dict):
        duration_to_disease_acquisition_modification = ValueMap(
            times=duration_to_disease_acquisition_modification["Times"],
            values=duration_to_disease_acquisition_modification["Values"]
        )
    if duration_to_disease_transmission_modification is None:
        duration_to_disease_transmission_modification = ValueMap(times=[0, 3, 6, 9], values=[1.0, 1.0, 0.75, 0.5])
    elif isinstance(duration_to_disease_transmission_modification, dict):
        duration_to_disease_transmission_modification = ValueMap(
            times=duration_to_disease_transmission_modification["Times"],
            values=duration_to_disease_transmission_modification["Values"]
        )

    if not api_campaign.get_schema():
        api_campaign.set_schema(manifest.schema_file)

    species_parameters = get_species_params(config, species_name)
    microsporidia = s2c.get_class_with_defaults("idmType:MicrosporidiaParameters", schema_path=manifest.schema_file)
    microsporidia.Duration_To_Disease_Acquisition_Modification = duration_to_disease_acquisition_modification.to_schema_dict(api_campaign)
    microsporidia.Duration_To_Disease_Transmission_Modification = duration_to_disease_transmission_modification.to_schema_dict(api_campaign)
    microsporidia.Female_To_Male_Transmission_Probability = female_to_male_probability
    microsporidia.Male_To_Female_Transmission_Probability = male_to_female_probability
    microsporidia.Larval_Growth_Modifier = larval_growth_modifier
    microsporidia.Female_To_Egg_Transmission_Probability = female_to_egg_probability
    microsporidia.Female_Mortality_Modifier = female_mortality_modifier
    microsporidia.Male_Mortality_Modifier = male_mortality_modifier
    microsporidia.Male_To_Egg_Transmission_Probability = male_to_egg_probability
    microsporidia.Strain_Name = strain_name
    species_parameters.Microsporidia.append(microsporidia)

add_mutation(config, manifest, species, mutate_from, mutate_to, probability)

Adds to Mutations parameter in a Gene which has the matching Alleles

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
species	str	Name of vector species to which we're adding mutations	required
mutate_from	str	The allele in the gamete that could mutate	required
mutate_to	str	The allele that this locus will change to during gamete generation	required
probability	float	The probability that the allele will mutate from one allele to the other during the creation of the gametes	required

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_mutation(config, manifest, species, mutate_from, mutate_to, probability):
    """
    Adds to **Mutations** parameter in a Gene which has the matching **Alleles**

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        species (str): Name of vector species to which we're adding mutations
        mutate_from (str): The allele in the gamete that could mutate
        mutate_to (str): The allele that this locus will change to during gamete generation
        probability (float): The probability that the allele will mutate from one allele to the other during the
            creation of the gametes

    Returns:
        (dict): configured config
    """

    species_params = get_species_params(config, species)
    found = False
    for gene in species_params["Genes"]:
        allele_names = []
        for allele in gene["Alleles"]:
            allele_names.append(allele["Name"])
        if mutate_from in allele_names and mutate_to in allele_names:
            found = True
            mutations = s2c.get_class_with_defaults("idmType:VectorAlleleMutation", schema_path=manifest.schema_file)
            mutations.Mutate_From = mutate_from
            mutations.Mutate_To = mutate_to
            mutations.Probability_Of_Mutation = probability
            gene.Mutations.append(mutations)

    if not found:
        raise ValueError(f"Allele name(s) '{mutate_from}' and/or '{mutate_to}' were not found for {species}.\n")

    return config

add_new_drug(config, manifest, drug, overwrite=False)

Adds a new drug to the simulation's Malaria_Drug_Params list.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
drug	MalariaDrugTypeParameters	fully configured drug object	required
overwrite	bool	If True and a drug with the same name already exists, replace it. If False (default), raise ValueError on duplicate names.	False

Returns:

Type	Description
dict	configured config

Example::

drug = MalariaDrugTypeParameters(
    name="MyNewDrug",
    pkpd_model=PKPDModel.CONCENTRATION_VERSUS_TIME,
    drug_cmax=200,
    drug_decay_t1=0.5,
    max_drug_irbc_kill=6.0,
)
add_new_drug(config, manifest, drug)

Source code in emodpy_malaria/malaria_config.py

def add_new_drug(config, manifest, drug: MalariaDrugTypeParameters, overwrite: bool = False):
    """
    Adds a new drug to the simulation's **Malaria_Drug_Params** list.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        drug (MalariaDrugTypeParameters): fully configured drug object
        overwrite (bool): If ``True`` and a drug with the same name already exists,
            replace it. If ``False`` (default), raise ``ValueError`` on duplicate names.

    Returns:
        (dict): configured config

    **Example**::

        drug = MalariaDrugTypeParameters(
            name="MyNewDrug",
            pkpd_model=PKPDModel.CONCENTRATION_VERSUS_TIME,
            drug_cmax=200,
            drug_decay_t1=0.5,
            max_drug_irbc_kill=6.0,
        )
        add_new_drug(config, manifest, drug)
    """
    if not isinstance(drug, MalariaDrugTypeParameters):
        raise ValueError(
            f"'drug' must be a MalariaDrugTypeParameters instance, "
            f"got {type(drug).__name__}.")

    for idx, existing in enumerate(config.parameters.Malaria_Drug_Params):
        if existing.Name == drug.name:
            if overwrite:
                config.parameters.Malaria_Drug_Params[idx] = drug.to_schema_dict(manifest)
                return config
            raise ValueError(
                f"Drug '{drug.name}' already exists. "
                f"Set overwrite=True to replace it.")

    config.parameters.Malaria_Drug_Params.append(drug.to_schema_dict(manifest))
    return config

add_species(config, manifest, species_to_select)

Adds species with preset parameters from 'malaria_vector_species_params.py', if species name not found - "gambiae" parameters are added and the new species name assigned.

Also accepts VectorSpeciesParameters objects directly.

Parameters:

Name	Type	Description	Default
config	object	schema-backed config smart dict	required
manifest	object	manifest file containing the schema path	required
species_to_select	Union[str, list, VectorSpeciesParameters, list]	a list of species names, a single species name, or one or more VectorSpeciesParameters objects.	required

Returns:

Type	Description
object	configured config

Source code in emodpy_malaria/vector_config.py

def add_species(config: object,
                manifest: object,
                species_to_select: Union[str, list, "VectorSpeciesParameters", list]) -> object:
    """
    Adds species with preset parameters from 'malaria_vector_species_params.py', if species
    name not found - "gambiae" parameters are added and the new species name assigned.

    Also accepts [VectorSpeciesParameters](https://emod.idmod.org/emodpy-malaria/autoapi/emodpy_malaria/vector_config/) objects directly.

    Args:
        config (object): schema-backed config smart dict
        manifest (object): manifest file containing the schema path
        species_to_select (Union[str, list, 'VectorSpeciesParameters', list]): a list of species names, a single
            species name, or one or more VectorSpeciesParameters objects.

    Returns:
        configured config
    """

    if not isinstance(species_to_select, list):
        species_to_select = [species_to_select]

    for species in species_to_select:
        if isinstance(species, VectorSpeciesParameters):
            if species._campaign is None:
                if not api_campaign.get_schema():
                    api_campaign.set_schema(manifest.schema_file)
                species._campaign = api_campaign
                for h in species.habitats:
                    if getattr(h, '_campaign', None) is None:
                        h._campaign = api_campaign
            config.parameters.Vector_Species_Params.append(species.to_schema_dict())
        else:
            from emodpy_malaria.malaria_vector_species_params import species_params
            vector_species_parameters = species_params(manifest, species)
            if isinstance(vector_species_parameters, list):
                raise ValueError(
                    f"'{species}' species not found in list, available species are: {vector_species_parameters}. "
                    f"We suggest adding 'gambiae' species and changing "
                    f"the name and relevant parameters with set_species_params() or "
                    f"adding your species to malaria_vector_species_params.py.\n")
            else:
                config.parameters.Vector_Species_Params.append(vector_species_parameters)

    return config

add_species_drivers(config, manifest, species=None, driving_allele=None, driver_type='CLASSIC', to_copy=None, to_replace=None, likelihood_list=None, shredding_allele_required=None, allele_to_shred=None, allele_to_shred_to=None, allele_shredding_fraction=None, allele_to_shred_to_surviving_fraction=None)

Add a gene drive that propagates a particular set of alleles.
Adds one **Alleles_Driven** item to the **Alleles_Driven** list, using 'driving_allele' as key if matching one
already exists.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
species	str	Name of the species for which we're setting the drivers	None
driving_allele	str	This is the allele that is known as the driver	None
driver_type	str	This indicates the type of driver. CLASSIC - The driver can only drive if the one gamete has the driving allele and the other has a specific allele to be replaced INTEGRAL_AUTONOMOUS - At least one of the gametes must have the driver. Alleles can still be driven if the driving allele is in both gametes or even if the driving allele cannot replace the allele in the other gamete X_SHRED, Y_SHRED - cannot be used in the same species during one simulation/realization. The driving_allele must exist at least once in the genome for shredding to occur. If there is only one, it can exist in either half of the genome. DAISY_CHAIN - can be used for drives that do not drive themselves but can be driven by another allele.	'CLASSIC'
to_copy	str	The main allele to be copied Allele_To_Copy	None
to_replace	str	The allele that must exist and will be replaced by the copy Allele_To_Replace	None
likelihood_list	list	A list of tuples in format: [(Copy_To_Allele, Likelihood),(),()] to assign to Copy_To_Likelyhood list	None
shredding_allele_required	str	The genome must have this gender allele in order for shredding to occur. If the driver is X_SHRED, then the allele must be designated as a Y chromosome. If the driver is Y_SHRED, then the allele must NOT be designated as a Y chromosome	None
allele_to_shred	str	The genome must have this gender allele in order for shredding to occur. If the driver is X_SHRED, then the allele must NOT be designated as a Y chromosome. If the driver is Y_SHRED, then the allele must be designated as a Y chromosome	None
allele_to_shred_to	str	This is a gender allele that the 'shredding' will change the allele_to_shred into. It can be a temporary allele that never exists in the output or could be something that appears due to resistance/failures	None
allele_shredding_fraction	float	This is the fraction of the alleles_to_Shred that will be converted to allele_to_shred_to. Values 0 to 1. If this value is less than 1, then some of the allele_to_shred will remain and be part of the gametes.	None
allele_to_shred_to_surviving_fraction	float	A trait modifier will automatically generated for [ Allele_To_Shred_To, * ], the trait ADJUST_FERTILE_EGGS, and this value as its modifier. Values 0 to 1. A value of 0 implies perfect shredding such that no allele_to_Shred_To survive in the eggs. A value of 1 means all of the 'shredded' alleles survive.	None

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_species_drivers(config, manifest, species: str = None, driving_allele: str = None, driver_type: str = "CLASSIC",
                        to_copy: str = None, to_replace: str = None, likelihood_list: list = None,
                        shredding_allele_required: str = None, allele_to_shred: str = None,
                        allele_to_shred_to: str = None, allele_shredding_fraction: float = None,
                        allele_to_shred_to_surviving_fraction: float = None):
    """
        Add a gene drive that propagates a particular set of alleles.
        Adds one **Alleles_Driven** item to the **Alleles_Driven** list, using 'driving_allele' as key if matching one
        already exists.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        species (str): Name of the species for which we're setting the drivers
        driving_allele (str): This is the allele that is known as the driver
        driver_type (str): This indicates the type of driver.
            CLASSIC - The driver can only drive if the one gamete has the driving allele and the other has a specific
            allele to be replaced
            INTEGRAL_AUTONOMOUS - At least one of the gametes must have the driver.  Alleles can still be driven if the
            driving allele is in both gametes or even if the driving allele cannot replace the allele in the
            other gamete
            X_SHRED, Y_SHRED -  cannot be used in the same **species** during one simulation/realization. The **driving_allele**
            must exist at least once in the genome for shredding to occur. If there is only one, it can exist in either
            half of the genome.
            DAISY_CHAIN -  can be used for drives that do not drive themselves but can be driven by another allele.
        to_copy (str): The main allele to be copied Allele_To_Copy
        to_replace (str): The allele that must exist and will be replaced by the copy Allele_To_Replace
        likelihood_list (list): A list of tuples in format: [(Copy_To_Allele, Likelihood),(),()] to assign to
            Copy_To_Likelyhood list
        shredding_allele_required (str): The genome must have this gender allele in order for shredding to occur.
            If the driver is X_SHRED, then the allele must be designated as a Y chromosome. If the driver is Y_SHRED,
            then the allele must NOT be designated as a Y chromosome
        allele_to_shred (str): The genome must have this gender allele in order for shredding to occur. If the driver is
            X_SHRED, then the allele must NOT be designated as a Y chromosome. If the driver is Y_SHRED, then the allele
            must be designated as a Y chromosome
        allele_to_shred_to (str): This is a gender allele that the 'shredding' will change the **allele_to_shred** into. It can
            be a temporary allele that never exists in the output or could be something that appears due to
            resistance/failures
        allele_shredding_fraction (float): This is the fraction of the alleles_to_Shred that will be converted to
            **allele_to_shred_to**. Values 0 to 1.  If this value is less than 1, then some of the **allele_to_shred** will
            remain and be part of the gametes.
        allele_to_shred_to_surviving_fraction (float): A trait modifier will automatically generated for
            [ Allele_To_Shred_To, * ], the trait ADJUST_FERTILE_EGGS, and this value as its modifier.  Values 0 to 1.
            A value of 0 implies perfect shredding such that no allele_to_Shred_To survive in the eggs. A value of 1
            means all of the 'shredded' alleles survive.

    Returns:
        (dict): configured config
    """
    if not config or not manifest or not species or not driving_allele or not to_copy or not to_replace or not likelihood_list:
        raise ValueError("Please define all the parameters for this function (except shredding, unless you're using them).\n")

    if not isinstance(driver_type, DriverType):
        try:
            driver_type = DriverType(driver_type)
        except ValueError:
            valid_types = [d.value for d in DriverType]
            raise ValueError(f"Invalid driver_type '{driver_type}'. Must be one of: {valid_types}\n")

    shred_types = (DriverType.X_SHRED, DriverType.Y_SHRED)
    has_shred_params = (shredding_allele_required or allele_to_shred
                        or allele_to_shred_to or allele_shredding_fraction
                        or allele_to_shred_to_surviving_fraction)
    if driver_type not in shred_types and has_shred_params:
        raise ValueError("Please do not define any shredding parameters if you're not using 'driver_type' = X_SHRED or Y_SHRED.\n")
    elif driver_type == DriverType.DAISY_CHAIN:
        for (copy_to_allele, likelihood) in likelihood_list:
            if copy_to_allele == driving_allele:
                raise ValueError(f"For DAISY_CHAIN driver_type, you cannot have the Driving_Allele (driving_allele) "
                                 f"= '{driving_allele}' be the same as any of the Copy_To_Allele (in likelihood_list) = "
                                 f"'({copy_to_allele}, {likelihood})'.\n")

    species_params = get_species_params(config, species)
    gender_allele_required = False
    gender_allele_to_shred = False
    gender_allele_to_shred_to = False

    gene_driver = s2c.get_class_with_defaults("idmType:VectorGeneDriver", schema_path=manifest.schema_file)
    gene_driver.Driving_Allele = driving_allele
    gene_driver.Driver_Type = driver_type

    if driver_type == DriverType.X_SHRED or driver_type == DriverType.Y_SHRED:
        if not allele_to_shred or not allele_to_shred_to or not shredding_allele_required:
            raise ValueError("For 'driver_type'= X_SHRED or Y_SHRED, please define all the shredding parameters.\n")
        for gene in species_params.Genes:
            if gene["Is_Gender_Gene"] == 1:
                for allele in gene["Alleles"]:
                    if allele["Name"] == shredding_allele_required:
                        gender_allele_required = True
                        if driver_type == DriverType.X_SHRED and allele["Is_Y_Chromosome"] == 0:
                            raise ValueError("For 'driver_type' = X_SHRED, 'shredding_allele_required' should be a Y chromosome.\n")
                        elif driver_type == DriverType.Y_SHRED and allele["Is_Y_Chromosome"] == 1:
                            raise ValueError("For 'driver_type' = Y_SHRED, 'shredding_allele_required' should be an X chromosome.\n")
                    elif allele["Name"] == allele_to_shred:
                        gender_allele_to_shred = True
                        if driver_type == DriverType.X_SHRED and allele["Is_Y_Chromosome"] == 1:
                            raise ValueError("For 'driver_type'= X_SHRED, 'allele_to_shred' should be X chromosome.\n")
                        elif driver_type == DriverType.Y_SHRED and allele["Is_Y_Chromosome"] == 0:
                            raise ValueError("For 'driver_type'= Y_SHRED, 'allele_to_shred' should be Y chromosome.\n")
                    elif allele["Name"] == allele_to_shred_to:
                        gender_allele_to_shred_to = True
                        if driver_type == DriverType.X_SHRED and allele["Is_Y_Chromosome"] == 1:
                            raise ValueError("For 'driver_type'= X_SHRED, 'allele_to_shred' should be X chromosome.\n")
                        elif driver_type == DriverType.Y_SHRED and allele["Is_Y_Chromosome"] == 0:
                            raise ValueError("For 'driver_type'= Y_SHRED, 'allele_to_shred_to' should be Y chromosome.\n")

        if not (gender_allele_required and gender_allele_to_shred and gender_allele_to_shred_to):
            raise ValueError("Looks like shredding_allele_required or allele_to_shred or allele_to_shred_to are not "
                             "on a gender gene, but they all should be. Please verify your settings.\n")

        shredding_alleles = s2c.get_class_with_defaults("idmType:ShreddingAlleles", schema_path=manifest.schema_file)
        shredding_alleles.Allele_Required = shredding_allele_required
        shredding_alleles.Allele_Shredding_Fraction = allele_shredding_fraction
        shredding_alleles.Allele_To_Shred = allele_to_shred
        shredding_alleles.Allele_To_Shred_To = allele_to_shred_to
        shredding_alleles.Allele_To_Shred_To_Surviving_Fraction = allele_to_shred_to_surviving_fraction
        gene_driver.Shredding_Alleles = shredding_alleles

    allele_driven = s2c.get_class_with_defaults("idmType:AlleleDriven", schema_path=manifest.schema_file)
    allele_driven.Allele_To_Copy = to_copy
    allele_driven.Allele_To_Replace = to_replace
    for index, likely in enumerate(likelihood_list):
        c2likelyhood = s2c.get_class_with_defaults("idmType:CopyToAlleleLikelihood", schema_path=manifest.schema_file)
        c2likelyhood.Copy_To_Allele = likely[0]
        c2likelyhood.Likelihood = likely[1]
        allele_driven.Copy_To_Likelihood.append(c2likelyhood)

    # check if the Driving_Allele already exists
    if "Drivers" in species_params:
        for driver in species_params.Drivers:
            if driving_allele == driver["Driving_Allele"]:
                if driver_type == driver["Driver_Type"]:
                    driver["Alleles_Driven"].append(allele_driven)
                    return config
                else:
                    raise ValueError(f"The gene driver with 'driving_allele'={driving_allele} must have exactly one "
                                     f"entry in 'Alleles_Driven' for this allele and therefore cannot be used for "
                                     f"multiple 'driver_type's.\n")

    if driver_type == DriverType.X_SHRED or driver_type == DriverType.Y_SHRED:
        gene_driver.Driving_Allele_Params = allele_driven
    else:
        gene_driver.Alleles_Driven = [allele_driven]

    gene_driver.Driver_Type = driver_type  # to circumvent the implicit settings
    species_params.Drivers.append(gene_driver)
    return config

add_trait(config, manifest, species, allele_combo=None, trait_modifiers=None)

Use this function to add traits as part of vector genetics configuration, the trait is assigned to the species' Gene_To_Trait_Modifiers parameter

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required
species	str	Name of species for which to add this Gene_To_Trait_Modifiers	required
allele_combo	list	List of lists, This defines a possible subset of allele pairs that a vector could have. Each pair are alleles from one gene. If the vector has this subset, then the associated traits will be adjusted. Order does not matter. '*' is allowed when only the occurrence of one allele is important. Example:: [[ "X", "X" ], [ "a0", "a1" ]]	None
trait_modifiers	list	list of trait modifier parameters created with create_trait() function.	None

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/vector_config.py

def add_trait(config, manifest, species, allele_combo: list = None, trait_modifiers: list = None):
    """
    Use this function to add traits as part of vector genetics configuration, the trait is assigned to the
    species' **Gene_To_Trait_Modifiers** parameter

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path
        species (str): Name of species for which to add this  Gene_To_Trait_Modifiers
        allele_combo (list): List of lists, This defines a possible subset of allele pairs that a vector could have.
            Each pair are alleles from one gene.  If the vector has this subset, then the associated traits will
            be adjusted.  Order does not matter.  '*' is allowed when only the occurrence of one allele is important.
            Example::

            [[  "X",  "X" ], [ "a0", "a1" ]]

        trait_modifiers (list): list of trait modifier parameters created with create_trait() function.

    Returns:
        (dict): configured config
    """
    species_params = get_species_params(config, species)
    validate_allele_combo(species_params=species_params, allele_combo=allele_combo)

    if not trait_modifiers or not isinstance(trait_modifiers, list):
        raise ValueError("Please make sure to pass in a list of trait modifiers created by create_trait() function.\n")

    trait = s2c.get_class_with_defaults("idmType:GeneToTraitModifierConfig", schema_path=manifest.schema_file)
    trait.Allele_Combinations = allele_combo
    trait.Trait_Modifiers = trait_modifiers
    species_params.Gene_To_Trait_Modifiers.append(trait)

    return config

add_vector_migration(task, species=None, vector_migration_data=None, vector_migration_filename_path=None, x_vector_migration=1)

Adds vector migration parameters to the named species' parameters and adds the migration file to the common_assets in task.

.. deprecated:: Use MalariaDemographics.add_vector_migration() instead, which follows the deferred implicit pattern and does not require a task object upfront.

Provide either vector_migration_data (a VectorMigrationData object) or vector_migration_filename_path (path to an existing binary file), not both.

Parameters:

Name	Type	Description	Default
task	EMODTask	contains config to edit and assets to add migration file to	required
species	str	Species to target, Name parameter	None
vector_migration_data	object	VectorMigrationData object. If provided, writes the binary file and registers it with the task.	None
vector_migration_filename_path	str	Path with the filename of the migration file to use to avoid importing and writing the file from a VectorMigrationData object. If provided, registers the file with the task.	None
x_vector_migration	float	Scale factor for the rate of vector migration to other nodes.	1

Source code in emodpy_malaria/vector_config.py

def add_vector_migration(task: object,
                         species: str = None,
                         vector_migration_data: object = None,
                         vector_migration_filename_path: str = None,
                         x_vector_migration: float = 1):
    """Adds vector migration parameters to the named species' parameters and adds the migration file to the
    common_assets in task.

    .. deprecated::
        Use `MalariaDemographics.add_vector_migration()` instead, which follows the
        deferred implicit pattern and does not require a task object upfront.

    Provide either ``vector_migration_data`` (a VectorMigrationData object) or
    ``vector_migration_filename_path`` (path to an existing binary file), not both.

    Args:
        task (emodpy.emod_task.EMODTask): contains config to edit and assets to add migration file to
        species (str): Species to target, Name parameter
        vector_migration_data (object): VectorMigrationData object. If provided, writes the binary file
            and registers it with the task.
        vector_migration_filename_path (str): Path with the filename of the migration file to use to avoid importing
            and writing the file from a VectorMigrationData object. If provided, registers the file with the task.
        x_vector_migration (float): Scale factor for the rate of vector migration to other nodes.
    """
    warnings.warn(
        "add_vector_migration(task, ...) is deprecated. "
        "Use MalariaDemographics.add_vector_migration(data, species, ...) instead.",
        DeprecationWarning,
        stacklevel=2,
    )
    if vector_migration_data is not None and vector_migration_filename_path is not None:
        raise ValueError("Provide either vector_migration_data or vector_migration_filename_path, not both.")
    if vector_migration_data is None and not vector_migration_filename_path:
        raise ValueError("Provide either vector_migration_data (VectorMigrationData object) "
                         "or vector_migration_filename_path (path to existing binary file).")

    if vector_migration_data is not None:
        filename = f"vector_migration_{species}.bin" if species else "vector_migration.bin"
        path = vector_migration_data.to_migration_file(filename)
        vector_migration_filename_path = str(path)

    head, tail = os.path.split(vector_migration_filename_path)

    params = get_species_params(task.config, species)
    params.Vector_Migration_Filename = tail
    params.x_Vector_Migration = x_vector_migration
    params.Vector_Migration_Modifier_Equation = ModifierEquationType.LINEAR.value
    params.Vector_Migration_Habitat_Modifier = 0
    params.Vector_Migration_Food_Modifier = 0
    params.Vector_Migration_Stay_Put_Modifier = 0
    if not task.common_assets.has_asset(vector_migration_filename_path):
        task.common_assets.add_asset(vector_migration_filename_path)
    if not task.common_assets.has_asset(vector_migration_filename_path + ".json"):
        task.common_assets.add_asset(vector_migration_filename_path + ".json")

create_trait(manifest, trait=None, modifier=None, sporozoite_barcode_string=None, gametocyte_a_barcode_string=None, gametocyte_b_barcode_string=None)

Configures and returns a modifier trait.

Parameters:

Name	Type	Description	Default
manifest	ModuleType	manifest file containing the schema path	required
trait	str	The trait to be modified of vectors with the given allele combination. Available traits are: "INFECTED_BY_HUMAN", "FECUNDITY", "FEMALE_EGG_RATIO", "STERILITY", "TRANSMISSION_TO_HUMAN", "ADJUST_FERTILE_EGGS", "MORTALITY", "INFECTED_PROGRESS", "OOCYST_PROGRESSION", "SPOROZOITE_MORTALITY"	None
modifier	float	The multiplier to use to modify the given trait for vectors with the given allele combination.	None
sporozoite_barcode_string	str	TBD	None
gametocyte_a_barcode_string	str	TBD	None
gametocyte_b_barcode_string	str	TBD	None

Returns:

Type	Description
dict	trait parameters that can be added to a list and passed to add_trait() function

Source code in emodpy_malaria/vector_config.py

def create_trait(manifest, trait: str = None, modifier: float = None,
                 sporozoite_barcode_string: str = None, gametocyte_a_barcode_string: str = None,
                 gametocyte_b_barcode_string: str = None):
    """
    Configures and returns a modifier trait.

    Args:
        manifest (ModuleType): manifest file containing the schema path
        trait (str): The trait to be modified of vectors with the given allele combination.
            Available traits are: "INFECTED_BY_HUMAN", "FECUNDITY", "FEMALE_EGG_RATIO", "STERILITY",
            "TRANSMISSION_TO_HUMAN", "ADJUST_FERTILE_EGGS", "MORTALITY", "INFECTED_PROGRESS", "OOCYST_PROGRESSION",
            "SPOROZOITE_MORTALITY"
        modifier (float): The multiplier to use to modify the given **trait** for vectors with the given allele combination.
        sporozoite_barcode_string (str): TBD
        gametocyte_a_barcode_string (str): TBD
        gametocyte_b_barcode_string (str): TBD

    Returns:
        (dict): trait parameters that can be added to a list and passed to add_trait() function
    """
    traits_available = [t.value for t in VectorTrait]
    if not trait or modifier is None:
        raise ValueError(f'Please define both trait and modifier. Available traits are: {traits_available}.\n')

    if not isinstance(trait, VectorTrait):
        try:
            trait = VectorTrait(trait)
        except ValueError:
            raise ValueError(f"Can't find trait '{trait}' in available traits. Traits available for use "
                             f"are {traits_available}")

    if trait == VectorTrait.OOCYST_PROGRESSION and not (gametocyte_a_barcode_string and gametocyte_b_barcode_string):
        raise ValueError("With trait = 'OOCYST_PROGRESSION', you need to define gametocyte_a_barcode_string and "
                         "gametocyte_b_barcode_string. \n")
    if trait == VectorTrait.SPOROZOITE_MORTALITY and not sporozoite_barcode_string:
        raise ValueError("With trait = 'SPOROZOITE_MORTALITY', you need to define sporozoite_barcode_string.\n")

    trait_modifier = s2c.get_class_with_defaults("idmType:TraitModifier", schema_path=manifest.schema_file)
    trait_modifier.Trait = trait
    trait_modifier.Modifier = modifier
    if trait == VectorTrait.SPOROZOITE_MORTALITY:
        trait_modifier.Sporozoite_Barcode_String = sporozoite_barcode_string
    if trait == VectorTrait.OOCYST_PROGRESSION:
        trait_modifier.Gametocyte_A_Barcode_String = gametocyte_a_barcode_string
        trait_modifier.Gametocyte_B_Barcode_String = gametocyte_b_barcode_string

    return trait_modifier

get_species_params(config, species=None)

Returns the species parameters dictionary with the matching species Name

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
species	str	Species to look up	None

Returns:

Type	Description
dict	Dictionary of species parameters with the matching name

Source code in emodpy_malaria/vector_config.py

def get_species_params(config, species: str = None):
    """
    Returns the species parameters dictionary with the matching species **Name**

    Args:
        config (dict): schema-backed config smart dict
        species (str): Species to look up

    Returns:
        (dict): Dictionary of species parameters with the matching name
    """
    if not species:
        raise ValueError("Please define a species.")
    for vector_species in config.parameters.Vector_Species_Params:
        if vector_species.Name == species:
            return vector_species
    raise ValueError(f"Species {species} not found.")

set_drug_param(config, drug_name=None, parameter=None, value=None)

Set a drug parameter, by passing in drug name, parameter and the parameter value. Added to facilitate adding drug Resistances, Example::

 artemether_drug_resistance = [{
    "Drug_Resistant_String": "A",
    "PKPD_C50_Modifier": 2.0,
    "Max_IRBC_Kill_Modifier": 0.9}]
 set_drug_param(cb, drug_name='Artemether', parameter="Resistances", value=artemether_drug_resistance)

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
drug_name	str	The drug that has a parameter to set	None
parameter	str	The parameter to set	None
value	any	The new value to set	None

Source code in emodpy_malaria/malaria_config.py

def set_drug_param(config, drug_name: str = None, parameter: str = None, value: any = None):
    """
     Set a drug parameter, by passing in drug name, parameter and the parameter value.
     Added to facilitate adding drug Resistances,
     **Example**::

         artemether_drug_resistance = [{
            "Drug_Resistant_String": "A",
            "PKPD_C50_Modifier": 2.0,
            "Max_IRBC_Kill_Modifier": 0.9}]
         set_drug_param(cb, drug_name='Artemether', parameter="Resistances", value=artemether_drug_resistance)

    Args:
        config (dict): schema-backed config smart dict
        drug_name (str): The drug that has a **parameter** to set
        parameter (str): The parameter to set
        value (any): The new value to set
    """

    if not drug_name or not parameter or value is None:
        raise Exception("Please pass in all: drug_name, parameter, and value.\n")
    for drug in config.parameters.Malaria_Drug_Params:
        if drug.Name == drug_name:
            if parameter not in drug:
                warnings.warn(f"Parameter '{parameter}' not found in drug '{drug_name}' parameters. "
                              f"It will be added — verify the spelling is correct.")
            drug[parameter] = value
            return  # should I return anything here?
    raise ValueError(f"{drug_name} not found.\n")

set_max_larval_capacity(config, species_name, habitat_type, max_larval_capacity)

Set the Max_Larval_Capacity for a given species and habitat. The habitat must already exist in the species' Habitats list (added via add_species()).

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
species_name	str	Name of the vector species to target.	required
habitat_type	HabitatType	The HabitatType of the habitat to update (e.g. HabitatType.TEMPORARY_RAINFALL).	required
max_larval_capacity	float	New value of Max_Larval_Capacity for the habitat.	required

Raises:

Type	Description
ValueError	If the species or habitat type is not found.

Source code in emodpy_malaria/vector_config.py

def set_max_larval_capacity(config, species_name: str, habitat_type: HabitatType, max_larval_capacity: float):
    """
    Set the **Max_Larval_Capacity** for a given species and habitat. The habitat must already
    exist in the species' **Habitats** list (added via `add_species()`).

    Args:
        config (dict): schema-backed config smart dict
        species_name (str): Name of the vector species to target.
        habitat_type (HabitatType): The [HabitatType](https://emod.idmod.org/emodpy-malaria/autoapi/emodpy_malaria/utils/emod_enum/) of
            the habitat to update (e.g. ``HabitatType.TEMPORARY_RAINFALL``).
        max_larval_capacity (float): New value of Max_Larval_Capacity for the habitat.

    Raises:
        ValueError: If the species or habitat type is not found.
    """
    if not isinstance(habitat_type, HabitatType):
        try:
            habitat_type = HabitatType(habitat_type)
        except ValueError:
            valid_types = [h.value for h in HabitatType]
            raise ValueError(f"Invalid habitat_type '{habitat_type}'. Must be one of: {valid_types}")

    habitats = get_species_params(config, species_name).Habitats
    for hab in habitats:
        if hab['Habitat_Type'] == habitat_type:
            hab['Max_Larval_Capacity'] = max_larval_capacity
            return

    raise ValueError(f"Failed to find habitat_type '{habitat_type}' for species '{species_name}'.")

set_parasite_genetics_params(config, manifest, var_gene_randomness_type=VarGeneRandomnessType.ALL_RANDOM, sporozoites_per_oocyst=None)

Sets up the default parameters for parasite genetics simulations Malaria_Model = "MALARIA_MECHANISTIC_MODEL_WITH_PARASITE_GENETICS"

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	schema path container	required
var_gene_randomness_type	VarGeneRandomnessType	Controls randomness of var genes in new infections. Defaults to VarGeneRandomnessType.ALL_RANDOM.	ALL_RANDOM
sporozoites_per_oocyst	BaseDistribution	A BaseDistribution that sets the Sporozoites_Per_Oocyst distribution parameters. Defaults to GaussianDistribution(mean=10000, std_dev=1000).	None

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/malaria_config.py

def set_parasite_genetics_params(config, manifest,
                                 var_gene_randomness_type: VarGeneRandomnessType = VarGeneRandomnessType.ALL_RANDOM,
                                 sporozoites_per_oocyst: BaseDistribution = None):
    """
    Sets up the default parameters for parasite genetics simulations
    Malaria_Model = "MALARIA_MECHANISTIC_MODEL_WITH_PARASITE_GENETICS"

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): schema path container
        var_gene_randomness_type (VarGeneRandomnessType): Controls randomness of var genes in new
            infections. Defaults to ``VarGeneRandomnessType.ALL_RANDOM``.
        sporozoites_per_oocyst (BaseDistribution): A [BaseDistribution](https://emod.idmod.org/emodpy-malaria/autoapi/emodpy_malaria/utils/distributions/) that
            sets the Sporozoites_Per_Oocyst distribution parameters. Defaults to
            ``GaussianDistribution(mean=10000, std_dev=1000)``.

    Returns:
        (dict): configured config
    """
    if sporozoites_per_oocyst is None:
        sporozoites_per_oocyst = GaussianDistribution(mean=10000, std_dev=1000)
    if not isinstance(var_gene_randomness_type, VarGeneRandomnessType):
        try:
            var_gene_randomness_type = VarGeneRandomnessType(var_gene_randomness_type)
        except ValueError:
            valid_types = [v.value for v in VarGeneRandomnessType]
            raise ValueError(f"Invalid var_gene_randomness_type '{var_gene_randomness_type}'. "
                             f"Must be one of: {valid_types}")

    set_team_defaults(config, manifest)
    config.parameters.pop("Malaria_Strain_Model")  # removing incompatible Malaria_Strain_Model parameter
    # config.parameters.pop("Enable_Initial_Prevalence") # popping it here doesn't work
    config.parameters.Malaria_Model = "MALARIA_MECHANISTIC_MODEL_WITH_PARASITE_GENETICS"
    config.parameters.Falciparum_MSP_Variants = 100
    config.parameters.Falciparum_Nonspecific_Types = 20
    config.parameters.Falciparum_PfEMP1_Variants = 1000
    config.parameters.Vector_Sampling_Type = VectorSamplingType.TRACK_ALL_VECTORS
    config.parameters.Max_Individual_Infections = 10
    # setting up Parasite_Genetics parameters
    fpg = s2c.get_class_with_defaults("idmType:ParasiteGenetics", schema_path=manifest.schema_file)
    fpg.Var_Gene_Randomness_Type = var_gene_randomness_type
    fpg.Sporozoite_Life_Expectancy = 25
    fpg.Num_Sporozoites_In_Bite_Fail = 12
    fpg.Probability_Sporozoite_In_Bite_Fails = 0.5
    fpg.Num_Oocyst_From_Bite_Fail = 3
    fpg.Probability_Oocyst_From_Bite_Fails = 0.5
    sporozoites_per_oocyst.set_intervention_distribution(fpg, "Sporozoites_Per_Oocyst")
    fpg.Crossover_Gamma_K = 2
    fpg.Crossover_Gamma_Theta = 0.38
    fpg.Drug_Resistant_Genome_Locations = []
    fpg.Barcode_Genome_Locations = [
        311500,
        1116500,
        2140000,
        3290000,
        4323333,
        4756667,
        5656667,
        6123333,
        7056667,
        7523333,
        8423333,
        8856667,
        9790000,
        10290000,
        11356667,
        11923333,
        13156667,
        13823333,
        15256667,
        16023333,
        17690000,
        18590000,
        20590000,
        21690000
    ]
    if var_gene_randomness_type == VarGeneRandomnessType.FIXED_NEIGHBORHOOD or var_gene_randomness_type == VarGeneRandomnessType.FIXED_MSP:
        fpg.MSP_Genome_Location = 200000
        fpg.Neighborhood_Size_MSP = 4
        if var_gene_randomness_type == VarGeneRandomnessType.FIXED_NEIGHBORHOOD:
            fpg.PfEMP1_Variants_Genome_Locations = [
                214333,
                428667,
                958667,
                1274333,
                1864900,
                2139900,
                2414900,
                2989900,
                3289900,
                3589900,
                4150000,
                4410000,
                4670000,
                4930000,
                5470000,
                5750000,
                6030000,
                6310000,
                6870000,
                7150000,
                7430000,
                7710000,
                8250000,
                8510000,
                8770000,
                9030000,
                9590000,
                9890000,
                10190000,
                10490000,
                11130000,
                11470000,
                11810000,
                12150000,
                12890000,
                13290000,
                13690000,
                14090000,
                14950000,
                15410000,
                15870000,
                16330000,
                17330000,
                17870000,
                18410000,
                18950000,
                20150000,
                20810000,
                21470000,
                22130000
            ]
            fpg.Neighborhood_Size_PfEMP1 = 10
    config.parameters.Parasite_Genetics = fpg
    # setting up gambiae parameters for parasite genetics
    fpg_gambiae_params = species_params(manifest, "fpg_gambiae")
    config.parameters.Vector_Species_Params = [fpg_gambiae_params]
    # end vector species
    return config

set_species_param(config, species, parameter, value, overwrite=False)

Sets a parameter value for a specific species.
Raises value error if species not found

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
species	str	name of species for which to set the parameter	required
parameter	str	parameter to set	required
value	Union[Any, list[Any]]	value to set the parameter to	required
overwrite	bool	if set to True and parameter is a list, overwrites the parameter with value, appends by default	False

Source code in emodpy_malaria/vector_config.py

def set_species_param(config, species, parameter, value, overwrite=False):
    """
        Sets a parameter value for a specific species.
        Raises value error if species not found

    Args:
        config (dict): schema-backed config smart dict
        species (str): name of species for which to set the parameter
        parameter (str): parameter to set
        value (Union[Any, list[Any]]): value to set the parameter to
        overwrite (bool): if set to True and parameter is a list, overwrites the parameter with value, appends by default
    """

    vector_species = get_species_params(config, species)

    if hasattr(value, 'to_schema_dict'):
        if getattr(value, '_campaign', None) is None:
            value._campaign = api_campaign
            for h in getattr(value, 'habitats', []):
                if getattr(h, '_campaign', None) is None:
                    h._campaign = api_campaign
        value = value.to_schema_dict()
    elif isinstance(value, list):
        for v in value:
            if hasattr(v, 'to_schema_dict') and getattr(v, '_campaign', None) is None:
                v._campaign = api_campaign
        value = [v.to_schema_dict() if hasattr(v, 'to_schema_dict') else v for v in value]

    if parameter in vector_species:
        if isinstance(vector_species[parameter], list):
            if overwrite:
                if isinstance(value, list):
                    vector_species[parameter] = value
                else:
                    vector_species[parameter] = [value]
            else:
                if isinstance(value, list):
                    for val in value:
                        vector_species[parameter].append(val)
                else:
                    vector_species[parameter].append(value)
        else:
            vector_species[parameter] = value
    else:
        vector_species[parameter] = value

set_team_defaults(config, manifest)

Set configuration defaults using team-wide values, including drugs and vector species.

Source code in emodpy_malaria/malaria_config.py

def set_team_defaults(config, manifest):
    """
        Set configuration defaults using team-wide values, including drugs and vector species.
    """
    vector_config.set_team_defaults(config, manifest)
    config.parameters.Simulation_Type = "MALARIA_SIM"
    # removing Infectious_Period parameters because not allowed in MALARIA_SIM, but need in VECTOR SIM
    config.parameters.pop("Infectious_Period_Constant")
    config.parameters.pop("Infectious_Period_Distribution")
    config.parameters.Malaria_Strain_Model = MalariaStrainModel.FALCIPARUM_RANDOM_STRAIN
    config.parameters.Enable_Disease_Mortality = 0
    # config.parameters.Enable_Malaria_CoTransmission = 0

    # INFECTION
    config.parameters.Infection_Updates_Per_Timestep = 8
    config.parameters.Enable_Superinfection = 1
    config.parameters.Incubation_Period_Distribution = "CONSTANT_DISTRIBUTION"
    config.parameters.Incubation_Period_Constant = 7
    config.parameters.Antibody_IRBC_Kill_Rate = 1.596
    config.parameters.RBC_Destruction_Multiplier = 3.29
    config.parameters.Parasite_Switch_Type = ParasiteSwitchType.RATE_PER_PARASITE_7VARS

    # IMMUNITY; these are NOT schema defaults
    config.parameters.Antibody_CSP_Killing_Threshold = 20
    config.parameters.Antigen_Switch_Rate = math.pow(10, -9.116590124)
    config.parameters.Base_Gametocyte_Production_Rate = 0.06150582
    config.parameters.Base_Gametocyte_Mosquito_Survival_Rate = 0.002011099
    config.parameters.Innate_Immune_Variation_Type = InnateImmuneVariationType.NONE
    config.parameters.Pyrogenic_Threshold = 1.5e4
    config.parameters.Falciparum_MSP_Variants = 32
    config.parameters.Falciparum_Nonspecific_Types = 76
    config.parameters.Falciparum_PfEMP1_Variants = 1070
    config.parameters.Fever_IRBC_Kill_Rate = 1.4
    config.parameters.Gametocyte_Stage_Survival_Rate = 0.588569307
    config.parameters.Max_MSP1_Antibody_Growthrate = 0.045
    config.parameters.MSP1_Merozoite_Kill_Fraction = 0.511735322
    config.parameters.Max_Individual_Infections = 3
    config.parameters.Nonspecific_Antigenicity_Factor = 0.415111634
    config.parameters.Antibody_Capacity_Growth_Rate = 0.09
    config.parameters.Antibody_Stimulation_C50 = 30
    config.parameters.Antibody_Memory_Level = 0.34
    config.parameters.Min_Adapted_Response = 0.05
    config.parameters.Cytokine_Gametocyte_Inactivation = 0.01667
    config.parameters.Enable_Maternal_Antibodies_Transmission = 1
    config.parameters.Maternal_Antibodies_Type = "SIMPLE_WANING"
    config.parameters.Maternal_Antibody_Protection = 0.1327

    # SYMPTOMATICITY
    config.parameters.Anemia_Mortality_Inverse_Width = 1
    config.parameters.Anemia_Mortality_Threshold = 0.654726662830038
    config.parameters.Anemia_Severe_Inverse_Width = 10
    config.parameters.Anemia_Severe_Threshold = 4.50775824973078

    config.parameters.Fever_Mortality_Inverse_Width = 1895.51971624351
    config.parameters.Fever_Mortality_Threshold = 3.4005008555391
    config.parameters.Fever_Severe_Inverse_Width = 27.5653580403806
    config.parameters.Fever_Severe_Threshold = 3.98354299722192

    config.parameters.Parasite_Mortality_Inverse_Width = 327.51594505874
    config.parameters.Parasite_Mortality_Threshold = 10 ** 5.93
    config.parameters.Parasite_Severe_Inverse_Width = 56.5754896048744
    config.parameters.Parasite_Severe_Threshold = 10 ** 5.929945527

    config.parameters.Clinical_Fever_Threshold_High = 1.5
    config.parameters.Clinical_Fever_Threshold_Low = 0.5
    config.parameters.Min_Days_Between_Clinical_Incidents = 14

    # updated from mambrose Oct 11 2019, personal communication with M Plucinski
    config.parameters.PfHRP2_Boost_Rate = 0.018  # original value: 0.07
    config.parameters.PfHRP2_Decay_Rate = 0.167  # original value: 0.172

    config.parameters.Report_Detection_Threshold_Blood_Smear_Gametocytes = 20
    config.parameters.Report_Detection_Threshold_Blood_Smear_Parasites = 20
    config.parameters.Report_Detection_Threshold_Fever = 1.0
    config.parameters.Report_Detection_Threshold_PCR_Gametocytes = 0.05
    config.parameters.Report_Detection_Threshold_PCR_Parasites = 0.05
    config.parameters.Report_Detection_Threshold_PfHRP2 = 5.0
    config.parameters.Report_Detection_Threshold_True_Parasite_Density = 0.0

    config.parameters.Report_Gametocyte_Smear_Sensitivity = 0.1
    config.parameters.Report_Parasite_Smear_Sensitivity = 0.1  # 10/uL

    config = set_team_drug_params(config, manifest)

    return config

set_team_drug_params(config, manifest)

Loads antimalarial drug parameters from the bundled CSV and appends them to the simulation config.

Parameters:

Name	Type	Description	Default
config	dict	schema-backed config smart dict	required
manifest	ModuleType	manifest file containing the schema path	required

Returns:

Type	Description
dict	configured config

Source code in emodpy_malaria/malaria_config.py

def set_team_drug_params(config, manifest):
    """
    Loads antimalarial drug parameters from the bundled CSV and appends them to
    the simulation config.

    Args:
        config (dict): schema-backed config smart dict
        manifest (ModuleType): manifest file containing the schema path

    Returns:
        (dict): configured config
    """
    csv_path = os.path.join(os.path.dirname(__file__), 'malaria_drug_params.csv')
    with open(csv_path, newline='') as csvfile:
        for row in csv.DictReader(csvfile):
            try:
                ages_str = row["Upper_Age_In_Years"].strip('[]').replace(' ', '')
                values_str = row["Fraction_Of_Adult_Dose"].strip('[]').replace(' ', '')
                if ages_str:
                    ages = [float(x) for x in ages_str.split(",")]
                    fractions = [float(x) for x in values_str.split(",")]
                    dose_fractions = [
                        DoseFractionByAge(age, frac)
                        for age, frac in zip(ages, fractions)
                    ]
                else:
                    dose_fractions = []
            except Exception as ex:
                warnings.warn(f"For drug {row['Name']}: {ex}. Defaulting to empty dose fractions.")
                dose_fractions = []

            drug = MalariaDrugTypeParameters(
                name=row["Name"],
                pkpd_model=row["PKPD_Model"],
                drug_cmax=float(row["Drug_Cmax"]),
                drug_decay_t1=float(row["Drug_Decay_T1"]),
                drug_decay_t2=float(row["Drug_Decay_T2"]),
                drug_vd=float(row["Drug_Vd"]),
                drug_pkpd_c50=float(row["Drug_PKPD_C50"]),
                drug_fulltreatment_doses=int(row["Drug_Fulltreatment_Doses"]),
                drug_dose_interval=float(row["Drug_Dose_Interval"]),
                drug_gametocyte02_killrate=float(row["Drug_Gametocyte02_Killrate"]),
                drug_gametocyte34_killrate=float(row["Drug_Gametocyte34_Killrate"]),
                drug_gametocytem_killrate=float(row["Drug_GametocyteM_Killrate"]),
                drug_hepatocyte_killrate=float(row["Drug_Hepatocyte_Killrate"]),
                max_drug_irbc_kill=float(row["Max_Drug_IRBC_Kill"]),
                bodyweight_exponent=float(row["Bodyweight_Exponent"]),
                fractional_dose_by_upper_age=dose_fractions,
            )
            config.parameters.Malaria_Drug_Params.append(drug.to_schema_dict(manifest))

    return config