actableai.causal.exposure.model package

Submodules

actableai.causal.exposure.model.confidence_interval_models module

class actableai.causal.exposure.model.confidence_interval_models.ConfidenceIntervalParams(*, estimate: actableai.causal.exposure.model.estimate_effect_models.EstimateResult)

Bases: pydantic.main.BaseModel

estimate: actableai.causal.exposure.model.estimate_effect_models.EstimateResult

class actableai.causal.exposure.model.confidence_interval_models.ConfidenceIntervalResult(*, estimate_id: str, lower_bound: float, upper_bound: float)

Bases: pydantic.main.BaseModel

estimate_id: str

lower_bound: float

to_dict()

upper_bound: float

actableai.causal.exposure.model.estimate_effect_models module

class actableai.causal.exposure.model.estimate_effect_models.CausalGraphModelSpec(*, type: str, label: str, confounders: List[str], effect_modifiers: List[str], treatment: str, outcome: str, causal_graph: str)

Bases: actableai.causal.exposure.model.estimate_effect_models.ModelSpec

causal_graph: str

outcome: str

treatment: str

class actableai.causal.exposure.model.estimate_effect_models.EstimateEffectRequestBody(*, population_specs: List[actableai.causal.exposure.model.estimate_effect_models.PopulationSpec], treatment_specs: List[actableai.causal.exposure.model.estimate_effect_models.TreatmentSpec], outcome_specs: List[actableai.causal.exposure.model.estimate_effect_models.OutcomeSpec], model_specs: List[actableai.causal.exposure.model.estimate_effect_models.ModelSpec], estimator_specs: List[actableai.causal.exposure.model.estimate_effect_models.EstimatorSpec])

Bases: pydantic.main.BaseModel

estimator_specs: List[actableai.causal.exposure.model.estimate_effect_models.EstimatorSpec]

model_specs: List[actableai.causal.exposure.model.estimate_effect_models.ModelSpec]

outcome_specs: List[actableai.causal.exposure.model.estimate_effect_models.OutcomeSpec]

population_specs: List[actableai.causal.exposure.model.estimate_effect_models.PopulationSpec]

treatment_specs: List[actableai.causal.exposure.model.estimate_effect_models.TreatmentSpec]

class actableai.causal.exposure.model.estimate_effect_models.EstimateResult(*, id: str, population_type: str, population_name: str, population_size: int, treatment_type: str, treatment: str, outcome_type: str, outcome: str, causal_model: str, estimator: str, causal_model_graph: dowhy.causal_model.CausalModel, identified_estimand: dowhy.causal_identifier.IdentifiedEstimand, estimate: dowhy.causal_estimator.CausalEstimate, covariate_balance: Optional[Dict[str, Any]] = None)

Bases: pydantic.main.BaseModel

class Config

Bases: object

arbitrary_types_allowed = True

causal_model: str

causal_model_graph: dowhy.causal_model.CausalModel

covariate_balance: Optional[Dict[str, Any]]

estimate: dowhy.causal_estimator.CausalEstimate

estimator: str

id: str

identified_estimand: dowhy.causal_identifier.IdentifiedEstimand

outcome: str

outcome_type: str

population_name: str

population_size: int

population_type: str

to_dict()

treatment: str

treatment_type: str

class actableai.causal.exposure.model.estimate_effect_models.EstimatorSpec(*, type: str, label: str, require_propensity_score: bool, method_name: str, method_params: Optional[Dict[str, Any]] = None)

Bases: pydantic.main.BaseModel

label: str

method_name: str

method_params: Optional[Dict[str, Any]]

require_propensity_score: bool

type: str

class actableai.causal.exposure.model.estimate_effect_models.ModelSpec(*, type: str, label: str, confounders: List[str], effect_modifiers: List[str])

Bases: pydantic.main.BaseModel

confounders: List[str]

effect_modifiers: List[str]

label: str

type: str

class actableai.causal.exposure.model.estimate_effect_models.OutcomeSpec(*, type: str, label: str, variable: str)

Bases: pydantic.main.BaseModel

label: str

type: str

variable: str

class actableai.causal.exposure.model.estimate_effect_models.PopulationSpec(*, type: str, label: str, dataframe: str, variable: Optional[str] = None)

Bases: pydantic.main.BaseModel

dataframe: str

label: str

type: str

variable: Optional[str]

class actableai.causal.exposure.model.estimate_effect_models.PopulationSpecDataFrame(*, type: str, label: str, dataframe: pandas.core.frame.DataFrame, variable: Optional[str] = None)

Bases: actableai.causal.exposure.model.estimate_effect_models.PopulationSpec

class Config

Bases: object

arbitrary_types_allowed = True

dataframe: pandas.core.frame.DataFrame

class actableai.causal.exposure.model.estimate_effect_models.Specification(*, population: actableai.causal.exposure.model.estimate_effect_models.PopulationSpecDataFrame, treatment: actableai.causal.exposure.model.estimate_effect_models.TreatmentSpec, outcome: actableai.causal.exposure.model.estimate_effect_models.OutcomeSpec, model: actableai.causal.exposure.model.estimate_effect_models.CausalGraphModelSpec, estimator: actableai.causal.exposure.model.estimate_effect_models.EstimatorSpec)

Bases: pydantic.main.BaseModel

estimator: actableai.causal.exposure.model.estimate_effect_models.EstimatorSpec

is_valid() → bool

model: actableai.causal.exposure.model.estimate_effect_models.CausalGraphModelSpec

outcome: actableai.causal.exposure.model.estimate_effect_models.OutcomeSpec

population: actableai.causal.exposure.model.estimate_effect_models.PopulationSpecDataFrame

treatment: actableai.causal.exposure.model.estimate_effect_models.TreatmentSpec

class actableai.causal.exposure.model.estimate_effect_models.TreatmentSpec(*, type: str, label: str, variable: str)

Bases: pydantic.main.BaseModel

label: str

type: str

variable: str

actableai.causal.exposure.model.identify_estimand_models module

class actableai.causal.exposure.model.identify_estimand_models.IdentifyEstimandResult(*, estimate_possibility: bool, backdoor_variables: List[str], frontdoor_variables: List[str], instrumental_variables: List[str], causal_model: dowhy.causal_model.CausalModel)

Bases: pydantic.main.BaseModel

class Config

Bases: object

arbitrary_types_allowed = True

backdoor_variables: List[str]

causal_model: dowhy.causal_model.CausalModel

estimate_possibility: bool

frontdoor_variables: List[str]

instrumental_variables: List[str]

to_dict()

actableai.causal.exposure.model.refute_estimate_models module

class actableai.causal.exposure.model.refute_estimate_models.RefuterResult(*, estimate_id: str, refuter: str, result: int)

Bases: pydantic.main.BaseModel

estimate_id: str

refuter: str

result: int

to_dict()

class actableai.causal.exposure.model.refute_estimate_models.RefuterSpec(*, num_simulations: int, method_name: str, estimate: actableai.causal.exposure.model.estimate_effect_models.EstimateResult)

Bases: pydantic.main.BaseModel

estimate: actableai.causal.exposure.model.estimate_effect_models.EstimateResult

method_name: str

num_simulations: int

actableai.causal.exposure.model.response module

class actableai.causal.exposure.model.response.NumberOfExecutionsResult(*, count: int)

Bases: pydantic.main.BaseModel

count: int

class actableai.causal.exposure.model.response.StatusModel(*, status: str, completed: int, pending: int, failed: int, results: Optional[Union[List[Union[actableai.causal.exposure.model.refute_estimate_models.RefuterResult, actableai.causal.exposure.model.estimate_effect_models.EstimateResult, actableai.causal.exposure.model.confidence_interval_models.ConfidenceIntervalResult, actableai.causal.exposure.model.shap_interpreter_models.ListShapInterpreterResult]], actableai.causal.exposure.model.significance_test_models.SignificanceTestResult]] = None)

Bases: pydantic.main.BaseModel

completed: int

failed: int

pending: int

results: Optional[Union[List[Union[actableai.causal.exposure.model.refute_estimate_models.RefuterResult, actableai.causal.exposure.model.estimate_effect_models.EstimateResult, actableai.causal.exposure.model.confidence_interval_models.ConfidenceIntervalResult, actableai.causal.exposure.model.shap_interpreter_models.ListShapInterpreterResult]], actableai.causal.exposure.model.significance_test_models.SignificanceTestResult]]

status: str

to_dict()

actableai.causal.exposure.model.shap_interpreter_models module

class actableai.causal.exposure.model.shap_interpreter_models.ListShapInterpreterResult(*, results: List[actableai.causal.exposure.model.shap_interpreter_models.ShapInterpreterResult])

Bases: pydantic.main.BaseModel

results: List[actableai.causal.exposure.model.shap_interpreter_models.ShapInterpreterResult]

to_dict()

class actableai.causal.exposure.model.shap_interpreter_models.ShapInterpreterResult(*, estimate_id: str, shap_population_name: int, shap_treatment: float, shap_outcome: int, shap_causal_model: float, shap_estimator: float)

Bases: pydantic.main.BaseModel

estimate_id: str

shap_causal_model: float

shap_estimator: float

shap_outcome: int

shap_population_name: int

shap_treatment: float

to_dict()

class actableai.causal.exposure.model.shap_interpreter_models.ShapInterpreterSpec(*, outcome_result: pandas.core.frame.DataFrame)

Bases: pydantic.main.BaseModel

class Config

Bases: object

arbitrary_types_allowed = True

outcome_result: pandas.core.frame.DataFrame

actableai.causal.exposure.model.significance_test_models module

class actableai.causal.exposure.model.significance_test_models.ComputeNullEffectSpec(*, estimate: dowhy.causal_estimator.CausalEstimate, identified_estimand: dowhy.causal_identifier.IdentifiedEstimand, causal_model: dowhy.causal_model.CausalModel, original_effect: float)

Bases: pydantic.main.BaseModel

class Config

Bases: object

arbitrary_types_allowed = True

causal_model: dowhy.causal_model.CausalModel

estimate: dowhy.causal_estimator.CausalEstimate

identified_estimand: dowhy.causal_identifier.IdentifiedEstimand

original_effect: float

class actableai.causal.exposure.model.significance_test_models.PropensityScoreSpec(*, estimate_id: str, identified_estimand: dowhy.causal_identifier.IdentifiedEstimand, causal_model: dowhy.causal_model.CausalModel, estimate: dowhy.causal_estimator.CausalEstimate)

Bases: pydantic.main.BaseModel

class Config

Bases: object

arbitrary_types_allowed = True

causal_model: dowhy.causal_model.CausalModel

estimate: dowhy.causal_estimator.CausalEstimate

estimate_id: str

identified_estimand: dowhy.causal_identifier.IdentifiedEstimand

class actableai.causal.exposure.model.significance_test_models.SignificanceTestResult(*, p_value: str, significance: bool)

Bases: pydantic.main.BaseModel

p_value: str

significance: bool

to_dict()

Module contents