Module `aivis_engine_v2_base_sdk_python.dto`

Classes

class DtoBooleanCategoryWithProbability (category: bool, probability: float)

Category-probability pair with boolean-valued category. DTO class for transferring data points from/to the engine.

Instance variables

var category: Float-valued category
var probability: Probability of category

class DtoBooleanCell (id: str, value: bool)

Single cell with row id and boolean value. DTO class for transferring cells to/from the engine.

Instance variables

var id: Row id for this data point
var value: Value of this data point

class DtoBooleanDataPoint (timestamp: int, value: bool)

Single data point with timestamp and boolean value. DTO class for transferring data points to/from the engine.

Instance variables

var timestamp: Timestamp for this data point
var value: Value of this data point

class DtoBooleanDataPointWithAvailability (timestamp: int, availability: int, value: bool)

Single data point with timestamp, availability and boolean value. DTO class for transferring data points to/from the engine.

Instance variables

var availability: Availability timestamp of this data point
var timestamp: Detection timestamp of this data point
var value: Value of this data point

class DtoBooleanDataPointWithCategoryProbabilities (timestamp: int, categories: List[DtoBooleanCategoryWithProbability])

Enhanced data point with timestamp and list of boolean-valued category-probability pairs. DTO class for transferring DtoBooleanDataPointWithCategoryProbabilities from/to the engine.

Instance variables

var categories: List of category-prediction pairs
var timestamp: Detection timestamp for this data point

class DtoExpressionInfo (involved_signal_ids: List[str])

Dependency information of synthesized signal. DTO class for transferring expression information from the engine.

Instance variables

var involved_signal_ids: List of signal IDs, that have been used to create a synthesized signal's data

class DtoFeatureValueWithNextNormal (feature: int, value: float, next_normal_value: float, rating: float)

Quadruple with id of feature, observed value of feature, next normal value of feature, rating. DTO class for transferring enhanced data points to/from the engine.

Instance variables

var feature: Feature id
var next_normal_value: Next normal feature value
var rating: Rating how much value differs from next_normal_value
var value: Observed feature value

class DtoFloatCategoryWithProbability (category: float, probability: float)

Category-probability pair with float-valued category. DTO class for transferring data points from/to the engine.

Instance variables

var category: Float-valued category
var probability: Probability of category

class DtoFloatCell (id: str, value: float)

Single cell with row id and boolean value. DTO class for transferring cells to/from the engine.

Instance variables

var id: Row id for this data point
var value: Value of this data point

class DtoFloatConstraintValue (model: str, value: float)

Tuple with id of model and value of the model function. DTO class for transferring DtoFloatConstraintValue from/to the engine.

Instance variables

var model: Model id
var value: Value of the model function of this data point

class DtoFloatConstraintValueWithNextNormal (model: str, value: float, next_normal_value: float)

Triplet with id of model, value of the model function, and corresponding next normal value. DTO class for transferring DtoFloatConstraintValueWithNextNormal from/to the engine.

Instance variables

var model: Model id
var next_normal_value: Next normal value of the model function with the next normal features
var value: Value of the model function of this data point

class DtoFloatConstraintValues (timestamp: int, cost: DtoFloatCostValue, constraints: List[DtoFloatConstraintValue])

Enhanced data point with timestamp, DtoFloatCostValue, list of DtoFloatConstraintValue. DTO class for transferring DtoFloatConstraintValues from/to the engine.

Instance variables

var constraints : DtoFloatConstraintValue: List of model function values
var cost : DtoFloatCostValue: Evaluation of cost function
var timestamp: Detection timestamp for this data point

class DtoFloatConstraintValuesWithNextNormal (timestamp: int, cost: DtoFloatCostValueWithNextNormal, constraints: List[DtoFloatConstraintValueWithNextNormal], features: List[DtoFeatureValueWithNextNormal])

Enhanced data point with timestamp, DtoFloatCostValueWithNextNormal, list of DtoFloatConstraintValueWithNextNormal and list of DtoFeatureValueWithNextNormal. DTO class for transferring DtoFloatConstraintValuesWithNextNormal from/to the engine.

Instance variables

var constraints: List of model function values and its next normal values
var cost : DtoFloatCostValueWithNextNormal: Evaluation of cost function before and after optimization
var features: Next normal feature values and rating of underlying features
var timestamp: Detection timestamp for this data point

class DtoFloatCostValue (cost_type: str, value: float)

Tuple with cost_type and value of the cost function. DTO class for transferring DtoFloatCostValue from/to the engine.

Instance variables

var cost_type: Type of cost function
var value: Evaluation of cost function

class DtoFloatCostValueWithNextNormal (cost_type: str, value: float, next_normal_value: float)

Triplet with cost_type, value of the cost function before and after optimization. DTO class for transferring DtoFloatCostValueWithNextNormal from/to the engine.

Instance variables

var cost_type: Type of cost function
var next_normal_value: Evaluation of cost function after optimization
var value: Evaluation of cost function before optimization

class DtoFloatDataPoint (timestamp: int, value: float)

Single data point with timestamp and floating point value. DTO class for transferring data points to/from the engine.

Instance variables

var timestamp: Detection timestamp for this data point
var value: Value of this data point

class DtoFloatDataPointWithAvailability (timestamp: int, availability: int, value: float)

Single data point with timestamp, availability and floating point value. DTO class for transferring data points to/from the engine.

Instance variables

var availability: Availability timestamp of this data point
var timestamp: Detection timestamp of this data point
var value: Value of this data point

class DtoFloatDataPointWithCategoryProbabilities (timestamp: int, categories: List[DtoFloatCategoryWithProbability])

Enhanced data point with timestamp and list of float-valued category-probability pairs. DTO class for transferring DtoFloatDataPointWithCategoryProbabilities from/to the engine.

Instance variables

var categories: List of category-prediction pairs
var timestamp: Detection timestamp for this data point

class DtoFloatDataPointWithNextNormal (timestamp: int, value: float, next_normal_value: float, features: List[DtoFeatureValueWithNextNormal])

Enhanced data point with timestamp, floating point value, List[DtoFeatureValueWithNextNormal]. DTO class for transferring enhanced data points to/from the engine.

Instance variables

var features: Next normal feature values and rating of underlying features
var next_normal_value: Prediction value of the next normal feature values
var timestamp: Detection timestamp for this data point
var value: Prediction value of this data point

class DtoStringCategoryWithProbability (category: str, probability: float)

Category-probability pair with string-valued category. DTO class for transferring data points from/to the engine.

Instance variables

var category: Float-valued category
var probability: Probability of category

class DtoStringCell (id: str, value: str)

Single cell with row id and string value. DTO class for transferring cells to/from the engine.

Instance variables

var id: Row id for this cell
var value: Value of this cell

class DtoStringDataPoint (timestamp: int, value: str)

Single data point with timestamp and string value. DTO class for transferring data points to/from the engine.

Instance variables

var timestamp: Timestamp for this data point
var value: Value of this data point

class DtoStringDataPointWithAvailability (timestamp: int, availability: int, value: str)

Single data point with timestamp, availability and string value. DTO class for transferring data points to/from the engine.

Instance variables

var availability: Availability timestamp of this data point
var timestamp: Detection timestamp of this data point
var value: Value of this data point

class DtoStringDataPointWithCategoryProbabilities (timestamp: int, categories: List[DtoStringCategoryWithProbability])

Enhanced data point with timestamp and list of string-valued category-probability pairs. DTO class for transferring DtoStringDataPointWithCategoryProbabilities from/to the engine.

Instance variables

var categories: List of category-prediction pairs
var timestamp: Detection timestamp for this data point

class DtoTabularExpressionInfo (involved_column_ids: List[str])

Dependency information of a synthesized column. DTO class for transferring expression information from the engine.

Instance variables

var involved_column_ids: List of column IDs, that have been used to create a synthesized column's data