Package `aivis_engine_v2_sd_sdk_python`

This document describes the syntax of aivis State Detection using the Python SDK. For getting started with aivis State Detection and for a high-level understanding of the concepts, please have a look at the State Detection User Guide.

JSON Structures

DtoAbstractSignalInterpreter

Interprets the signal values and derives aspects from them.

@abstract

Type: Object
Sub-Types: DtoDefaultSignalInterpreter, DtoNumericalSignalInterpreter, DtoCategoricalSignalInterpreter, DtoOscillatorySignalInterpreter, DtoCyclicSignalInterpreter
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoDefaultSignalInterpreter

Interprets float signals via DtoNumericalSignalInterpreter and string and boolean signals via DtoCategoricalSignalInterpreter.

Type: Object
Super-Types: DtoAbstractSignalInterpreter
Discriminator: _type
Discriminator-Value: Default

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoNumericalSignalInterpreter

Interprets the signal as being numerical. The natural order of the different values is taken into account.

Type: Object
Super-Types: DtoAbstractSignalInterpreter
Discriminator: _type
Discriminator-Value: Numerical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoCategoricalSignalInterpreter

Interprets the different signal values as categories, which have no order. For every category a categorical boolean aspect is derived, which yields true if the signal value equals that category. This is the only allowed interpreter for string and boolean signals.

Type: Object
Super-Types: DtoAbstractSignalInterpreter
Discriminator: _type
Discriminator-Value: Categorical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoOscillatorySignalInterpreter

Interprets the signal as an oscillatory wave. It is transformed from time- to frequency-domain.

Type: Object
Super-Types: DtoAbstractSignalInterpreter
Discriminator: _type
Discriminator-Value: Oscillatory

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`windowLength`	DtoPositiveDuration	-	Length of the time window the frequency spectra are calculated for. The underlying discrete Fourier transform is based on the data at "t", "t - mesh", "t - 2*mesh", … stopping before "t - windowLength".
`mesh`	DtoPositiveDuration	-	Time resolution of the source signal that is used in window for computing Fourier transform. Timestamps with gaps of more than 2*mesh in their Fourier window are skipped. Mesh must not be bigger than window_length.

DtoCyclicSignalInterpreter

Interprets the signal as a cyclic variable, based on their residue after division. An important example are angles with a cycle length of 360 degrees. The wrapping at the cycle length is continuous, e.g. 2 degree are considered close to 357 degrees.

Type: Object
Super-Types: DtoAbstractSignalInterpreter
Discriminator: _type
Discriminator-Value: Cyclic

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`cycleLength`	DtoPositiveFloat	-	Divisor used to calculate the residue. All signal values are mapped into the interval from 0 to cycle length.

DtoColumnConfig

Handling of a specific column.

Type: Object

Property	Type	Markers	Description
`column`	DtoColumnId	-	ID of the column.
`interpreter`	DtoAbstractColumnInterpreter	optional, default: `{"_type":"Default"}`	Controls how this column will be interpreted.

DtoAbstractColumnInterpreter

Interprets the column values and splits them into different categories

@abstract

Type: Object
Sub-Types: DtoNumericalColumnInterpreter, DtoCategoricalColumnInterpreter, DtoDefaultColumnInterpreter
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoNumericalColumnInterpreter

Interprets the column as being numerical. The natural order of the different values is taken into account. The engine will split the values of this column into ranges. This interpreter is only allowed for float columns.

Type: Object
Super-Types: DtoAbstractColumnInterpreter
Discriminator: _type
Discriminator-Value: Numerical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`quantileCount`	DtoPositiveInteger	optional, default: `20`	Split the value range into this many quantiles. Values in the same quantile will not be differntiated by the engine.

DtoCategoricalColumnInterpreter

Interprets the different column values as categories, which have no order. The engine will consider DtoCategorySetPredicates for this column. This is the only allowed interpreter for string and boolean column.

Type: Object
Super-Types: DtoAbstractColumnInterpreter
Discriminator: _type
Discriminator-Value: Categorical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoDefaultColumnInterpreter

Interprets float columns via DtoNumericalColumnInterpreter and string and boolean columns via DtoCategoricalColumnInterpreter.

Type: Object
Super-Types: DtoAbstractColumnInterpreter
Discriminator: _type
Discriminator-Value: Default

Property	Type	Markers	Description
`_type`	String	-	Type of this object.

DtoDataType

Specification of the type of data.

Type: String
Enum: BOOLEAN, FLOAT, STRING

DtoDataFilter

Limits the use of the data based on certain criteria.

Type: Object

Property	Type	Markers	Description
`includeSignals`	DtoDataFilterRange[]	optional	If present, restrict to these signal ranges.
`excludeSignals`	DtoDataFilterRange[]	optional	If present, exclude all these signal ranges.
`includeRanges`	DtoInterval[]	optional	If present, restrict to these ranges for all signals.
`excludeRanges`	DtoInterval[]	optional	If present, exclude these ranges for all signals.
`startTime`	DtoTime	optional	If present, exclude all data before this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, exclude all data at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoDataFilterRange

Time range of a specific signal.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	ID of the signal.
`startTime`	DtoTime	optional	If present, the range only includes times at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, the range only includes times before this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoInterval

Interval used to exclude/include data.

Type: Object

Property	Type	Markers	Description
`startTime`	DtoTime	optional	If present, the range only includes times at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, the range only includes times before this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoIntervalBeforeIncident

Interval used to exclude/include data with an annotation denoting an estimated origin for an incident. This interval type is used for storing intervals before events (or incidents) for the state detection engine.

Type: Object

Property	Type	Markers	Description
`startTime`	DtoTime	optional	If present, the range only includes times at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, the range only includes times before this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoIntervalWithoutIncident

Type: Object

Property	Type	Markers	Description
`startTime`	DtoTime	optional	If present, the range only includes times at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, the range only includes times before this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoDataReport

Information about the data.

Type: Object

Property	Type	Markers	Description
`signals`	DtoAbstractSignalDataReport[]	-	Information on all signals in the data.

DtoAbstractSignalDataReport

Information on a specific signal in the data.

@abstract

Type: Object
Sub-Types: DtoRawSignalDataReport, DtoSynthesizedSignalDataReport
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.

DtoRawSignalDataReport

Information on a specific signal in the data, whose values were added directly.

Type: Object
Super-Types: DtoAbstractSignalDataReport
Discriminator: _type
Discriminator-Value: Raw

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.

DtoSynthesizedSignalDataReport

Information on a specific signal in the data, whose values were calculated by an expression (synthesized).

Type: Object
Super-Types: DtoAbstractSignalDataReport
Discriminator: _type
Discriminator-Value: Synthesized

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.
`expression`	String	-	Expression by which this signal was synthesized.
`involvedSignals`	DtoSignalId[]	-	Source signals that were used in the expression to synthesize the signal.

DtoInferenceDataSpecification

Specification for the data needed at the inference.

Type: Object

Property	Type	Markers	Description
`signals`	DtoAbstractInferenceSignalSpecification[]	-	Specification for all signals needed at the inference.

DtoAbstractInferenceSignalSpecification

Specification for a specific signal needed at the inference.

@abstract

Type: Object
Sub-Types: DtoInferenceRawSignalSpecification, DtoInferenceSynthesizedSignalSpecification
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.

DtoInferenceRawSignalSpecification

Specification for a specific signal needed at the inference, whose values were added directly.

Type: Object
Super-Types: DtoAbstractInferenceSignalSpecification
Discriminator: _type
Discriminator-Value: Raw

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.
`startLag`	DtoNonNegativeDuration	-	Start of the time window measured as duration until the inference timestamp.
`endLag`	DtoNonNegativeDuration	-	End of the time window (inclusive), measured as duration until the inference timestamp.

DtoInferenceSynthesizedSignalSpecification

Specification for a specific signal needed at the inference, whose values were calculated by an expression (synthesized).

Type: Object
Super-Types: DtoAbstractInferenceSignalSpecification
Discriminator: _type
Discriminator-Value: Synthesized

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`signal`	DtoSignalId	-	ID of the signal.
`dataType`	DtoDataType	-	Data type of the signal.
`expression`	String	-	Expression by which this signal was synthesized.
`involvedSignals`	DtoSignalId[]	-	Source signals that were used in the expression to synthesize the signal.

DtoFeatureFilter

Limits the use of features based on certain criteria.

Type: Object

Property	Type	Markers	Description
`includeFeatures`	DtoFunctionId[]	optional	If present, restrict to these features.
`excludeFeatures`	DtoFunctionId[]	optional	If present, exclude all these features.
`includeSignals`	DtoSignalId[]	optional	If present, restrict to the features created by these signals.
`excludeSignals`	DtoSignalId[]	optional	If present, exclude all features created by these signals.

DtoTabularDataFilter

Limits the use of the data based on certain criteria.

Type: Object

Property	Type	Markers	Description
`includeColumns`	DtoColumnId[]	optional	If present, include only these columns.
`excludeColumns`	DtoColumnId[]	optional	If present, exclude all these columns.

DtoColumnDataReport

Information about the column data.

Type: Object

Property	Type	Markers	Description
`columns`	DtoAbstractColumnDataReport[]	-	Information on all columns in the data.

DtoAbstractColumnDataReport

Information on a specific column in the data.

@abstract

Type: Object
Sub-Types: DtoRawColumnDataReport, DtoSynthesizedColumnDataReport
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`column`	DtoColumnId	-	ID of the column.
`dataType`	DtoDataType	-	Data type of the column.

DtoRawColumnDataReport

Information on a specific column in the data, whose values were added directly.

Type: Object
Super-Types: DtoAbstractColumnDataReport
Discriminator: _type
Discriminator-Value: Raw

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`column`	DtoColumnId	-	ID of the column.
`dataType`	DtoDataType	-	Data type of the column.

DtoSynthesizedColumnDataReport

Information on a specific column in the data, with values calculated by an expression (synthesized).

Type: Object
Super-Types: DtoAbstractColumnDataReport
Discriminator: _type
Discriminator-Value: Synthesized

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`column`	DtoColumnId	-	ID of the column.
`dataType`	DtoDataType	-	Data type of the column.
`expression`	String	-	Expression by which this column was synthesized.
`involvedColumns`	DtoColumnId[]	-	Source columns that were used in the expression to synthesize the column.

DtoTimeseriesFilesReaderConfig

Type: Object

Property	Type	Markers	Description
`folder`	String	-	Path to the archive folder
`filesFilter`	DtoFilesFilter	optional	files to include and/or exclude from the folder
`dataFilter`	DtoAbstractTimeseriesDataFilter	optional	If present, the data to be read can be restricted.
`dataTypes`	DtoTimeseriesDataTypesConfig	optional	Needs to be set if there are any non-float signals or non-standard headers.
`ignoreSignalAvailabilities`	Boolean	optional, default: `false`	Whether or not the availability column of inference data should be ignored. If no availabilities are given, this configuration is irrelevant.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoAbstractTimeseriesDataFilter

@abstract

Type: Object
Sub-Types: DtoDefaultTimeseriesDataFilter, DtoInferenceTimeseriesDataFilter
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object

DtoDefaultTimeseriesDataFilter

Type: Object
Super-Types: DtoAbstractTimeseriesDataFilter
Discriminator: _type
Discriminator-Value: Default

Property	Type	Markers	Description
`_type`	String	-	Type of this object
`includeSignals`	DtoDataFilterRange[]	optional	If present, restrict to these signal ranges.
`excludeSignals`	DtoDataFilterRange[]	optional	If present, exclude all these signal ranges.
`includeRanges`	DtoInterval[]	optional	If present, restrict to these ranges for all signals.
`excludeRanges`	DtoInterval[]	optional	If present, exclude these ranges for all signals.
`startTime`	DtoTime	optional	If present, exclude all data before this time. If both startTime and endTime are present we require startTime ≤ endTime.
`endTime`	DtoTime	optional	If present, exclude all data at or after this time. If both startTime and endTime are present we require startTime ≤ endTime.

DtoInferenceTimeseriesDataFilter

Type: Object
Super-Types: DtoAbstractTimeseriesDataFilter
Discriminator: _type
Discriminator-Value: Inference

Property	Type	Markers	Description
`_type`	String	-	Type of this object
`dataSpecifications`	DtoInferenceDataSpecification[]	-	Signals that are part of a data specification are read. At least one data specification must be given.
`additionalSignals`	DtoSignalId[]	optional, default: `[]`	Additional signals to read that are not in the data specifications, e.g., the target signal. It is okay to specify those signals that are already in the data specifications.
`inferenceTimeRanges`	DtoInterval[]	optional	Specify inference time ranges. The files reader will only read those timestamps that are relevant for the specified time ranages, such that inferences can be done at the very first timestamp in each time range. This means the lag information of all signals are considered when reading the data points. When unspecified, it defaults to (-inf, inf), i.e., reading all timestamps.

DtoTimeseriesDataTypesConfig

Type: Object

Property	Type	Markers	Description
`defaultType`	DtoDataType	optional, default: `FLOAT`	Any signal that is not listed in either floatSignals, stringSignals, or booleanSignals is of defaultType.
`timestampSignal`	DtoSignalId	optional, default: `timestamp`	The header for timestamp
`availabilitySignal`	DtoSignalId	optional, default: `availability`	The header for availability
`floatSignals`	DtoSignalId[]	optional	List of float signal ids
`stringSignals`	DtoSignalId[]	optional	List of string signal ids
`booleanSignals`	DtoSignalId[]	optional	List of boolean signal ids

DtoTabularFilesReaderConfig

Type: Object

Property	Type	Markers	Description
`folder`	String	-	Path to the archive folder
`filesFilter`	DtoFilesFilter	optional	files to include and/or exclude from the folder
`dataFilter`	DtoTabularDataFilter	optional	If present, the data to be read can be restricted.
`dataTypes`	DtoTabularDataTypesConfig	optional	Needs to be set if there are any non-float columns or non-standard headers.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoTabularDataTypesConfig

Type: Object

Property	Type	Markers	Description
`defaultType`	DtoDataType	optional, default: `FLOAT`	Any column that is not listed in either floatColumns, stringColumns, or booleanColumns is of defaultType.
`idColumn`	DtoColumnId	optional, default: `id`	The header for id
`floatColumns`	DtoColumnId[]	optional	List of float column ids
`stringColumns`	DtoColumnId[]	optional	List of string column ids
`booleanColumns`	DtoColumnId[]	optional	List of boolean column ids

DtoFilesFilter

Type: Object

Property	Type	Markers	Description
`includeFiles`	String[]	optional	files to read from the folder and its sub-folders, perhaps regex
`excludeFiles`	String[]	optional	files to exclude from the folder and its sub-folders, perhaps regex.

DtoAbstractFunction

Parts of the formula describing the calculation while inference. Functions are succesively evaluated on signals and other functions to derive a final inference result.

@abstract

Type: Object
Sub-Types: DtoSignalFunction, DtoLagFunction, DtoLtiFilterFunction, DtoCategoryEqualsFunction, DtoFourierTransformFunction, DtoPowerSpectrumFunction, DtoPhaseSpectrumFunction, DtoSinFunction, DtoCosFunction, DtoScaleFunction, DtoPrincipalDirectionFunction, DtoLogisticFunction, DtoReluFunction, DtoIdentityFunction, DtoMollifierFunction, DtoIdCategoryMapFunction, DtoIdCategoryProbaMapFunction, DtoSumFunction, DtoLinearFunction, DtoLogSumExpFunction, DtoPNormFunction, DtoMaxFunction, DtoArgMaxFunction, DtoOrFunction, DtoProductFunction, DtoConstantFunction, DtoStepFunction, DtoLogarithmFunction, DtoExponentialFunction, DtoGaussCdfFunction, DtoAggregatedNumericalFunction, DtoAggregatedCategoricalFunction, DtoKernelModelFunction, DtoTreeModelFunction
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.

DtoSignalFunction

Wraps a signal into a function.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Signal

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`signal`	DtoSignalId	-	The ID of the signal to be used as function.

DtoLagFunction

Lags the values of the source function by some fixed delay.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Lag

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`source`	DtoFunctionId	-	ID of the function whose values are lagged.
`lag`	DtoNonNegativeDuration	-	The delay. The value of the resulting function at time "t" is given by "source(t - lag)".

DtoLtiFilterFunction

An LtiFilterFunction is the convolution of a moving time window of the input with some fixed function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: LtiFilter

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`source`	DtoFunctionId	-	FunctionId of the only input function.
`parameters`	DtoFloat[]	-	Parameters of the lti-filter function. The value of the resulting function at time t is given by "sum_i source(t - mesh * (parameters.size - i -1)) * parameters[i]".
`mesh`	DtoPositiveDuration	-	Time resolution of the source used in this function.

DtoCategoryEqualsFunction

A CategoricalEqualsFunction applied to a categorical function yields a 0/1-function for one of the function's categories. Numeric, string or boolean input and numeric output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: CategoryEquals

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`category`	DtoFunctionId	-	FunctionId of the only input function.
`testValue`	DtoAbstractCategory	-	The category (=value) of the categorical source for which this 0/1-function is created. The function is 1 when the source evaluates to this value. Otherwise, the function evaluates to 0.
`catCount`	DtoPositiveInteger	optional	The number of unique categories within the source signal.

DtoFourierTransformFunction

A DtoFourierTransformFunction performs a Fourier transform on the input. Numeric input and complex vector output.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: FourierTransform

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.
`windowLength`	DtoPositiveDuration	-	At time "t", frequency spectra are calculated for the time window from after "t - windowLength" to "t" using a step size given by mesh.
`mesh`	DtoPositiveDuration	-	Time resolution of the source used in creation of this function. Mesh must not be bigger than window_length.

DtoPowerSpectrumFunction

A DtoPowerSpectrumFunction returns the logarithm of the power in some frequency band. Complex vector input and numeric output.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: PowerSpectrum

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`spectrum`	DtoFunctionId	-	FunctionId of the only input function.
`minFrequency`	DtoNonNegativeInteger	-	The lowest frequency included in the frequency band. Frequencies are enumerated by successive integers starting with 0. Frequency k means a period of windowLength/k; (frequency 0 means mean over windowLenght); windowLength is given in the underlying DtoFourierTransformFunction.
`maxFrequency`	DtoNonNegativeInteger	-	Exclusive upper bound of the frequency band. Frequencies are enumerated by successive integers starting with 0. Frequency k means a period of windowLength/k; (frequency 0 means mean over windowLenght); windowLength is given in the underlying DtoFourierTransformFunction.

DtoPhaseSpectrumFunction

A DtoPhaseSpectrumFunction represents a phase of a complex frequency spectrum. Complex vector input and numeric output (cycle 2 pi).

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: PhaseSpectrum

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`spectrum`	DtoFunctionId	-	FunctionId of the only input function.
`frequency`	DtoNonNegativeInteger	-	The frequency to which the phase belongs. Frequencies are enumerated by successive integers starting with 0. Frequency k means a period of windowLength/k; (frequency 0 means mean over windowLenght); windowLength is given in the underlying DtoFourierTransformFunction.

DtoSinFunction

The sin function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Sin

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoCosFunction

The cos function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Cos

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoScaleFunction

Returns the input multiplied by the factor. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Scale

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.
`factor`	DtoFloat	-	-

DtoPrincipalDirectionFunction

A DtoPrincipalDirectionFunction is a linear combination of other functions. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: PrincipalDirection

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`coefficients`	DtoFeatureValue[]	-	The weights of the functions in the linear combination that form this function.

DtoLogisticFunction

The logistic function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Logistic

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoReluFunction

The rectified linear unit. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Relu

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoIdentityFunction

Identity function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Identity

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoMollifierFunction

A mollifier function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Mollifier

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoIdCategoryMapFunction

Assigns each input value a result based on a dictionary. DtoFunctionId input and float or string or boolean output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: IdCategoryMap

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function (whose return type is DtoFunctionId).
`entries`	DtoIdCategoryEntry[]	-	The key-value-pairs of this dictionary (all entries should have the same value type)

DtoIdCategoryProbaMapFunction

Assigns each input value a result based on a dictionary and its probability.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: IdCategoryProbaMap

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	FunctionIds of the only input functions.
`entries`	DtoIdCategoryEntry[]	-	The key-value-pairs of this dictionary (all entries should have the same value type)

DtoIdCategoryEntry

Type: Object

Property	Type	Markers	Description
`id`	DtoFunctionId	-	The key.
`category`	DtoAbstractCategory	-	The category the key is mapped to.

DtoSumFunction

Sum over all input functions. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Sum

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`summands`	DtoFunctionId[]	-	The values of these functions are used as input.

DtoLinearFunction

Weighted sum over all input functions plus intercept. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Linear

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	The values of these functions are used as input.
`coeffs`	DtoFloat[]	-	Coefficients of linear function. Order must be same as in sources.
`intercept`	DtoFloat	-	Intercept of linear function.

DtoLogSumExpFunction

Smooth max function. Approximates the maximum of the elements of the vector used as input.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: LogSumExp

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	The values of these functions are used as input.
`scale`	DtoFloat	-	Scales the inputs and makes the function sharper around the maximum.
`absArgument`	Boolean	-	Take the absolute values of the sources

DtoPNormFunction

Smooth max function. Approximates the maximum of the elements of the vector used as input.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: PNorm

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	The values of these functions are used as input.
`p`	DtoNonNegativeInteger	-	Scales the inputs and makes the function sharper around the maximum.
`absArgument`	Boolean	-	Take the absolute values of the sources

DtoMaxFunction

Returns the largest function value among the source functions at a given timestamp. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Max

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	The values of these functions are used as input.

DtoArgMaxFunction

Returns the id of the function with the largest result. Multiple numeric inputs and DtoFunctionId output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: ArgMax

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`arguments`	DtoFunctionId[]	-	The values of these functions are used as input.

DtoOrFunction

Returns true if any of the source functions returns true. Boolean input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Or

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`sources`	DtoFunctionId[]	-	The values of these functions are used as input.

DtoProductFunction

Product over all input functions. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Product

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`factors`	DtoFunctionId[]	-	The values of these functions are used as input.

DtoConstantFunction

Returns the constant value provided. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Constant

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`constant`	DtoFloat	-	-

DtoStepFunction

Step function. Returns 0 if argument value is negative else 1. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Step

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoLogarithmFunction

Natural logarithm function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Logarithm

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoExponentialFunction

Exponential function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: Exponential

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.

DtoGaussCdfFunction

Gaussian cummulative distribution function. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: GaussCdf

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`argument`	DtoFunctionId	-	FunctionId of the only input function.
`mean`	DtoFloat	-	Mean of Gaussian.
`std`	DtoFloat	-	Standard deviation of Gaussian.

DtoAggregatedNumericalFunction

Aggregating a numerical signal over the time window given by min and max lags. Numeric input and ouput.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: AggregatedNumerical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`source`	DtoFunctionId	-	FunctionId of the only input function.
`evalType`	DtoNumericalFunctionEvalType	-	Evalution type of aggregated numerical function
`maxLag`	DtoNonNegativeDuration	-	Start of the time window.
`minLag`	DtoNonNegativeDuration	-	End of the time window.
`mesh`	DtoPositiveDuration	-	Time resolution of the source used in this function.

DtoNumericalFunctionEvalType

Available evalution types.

@experimental: Might change in future releases.

Type: String
Enum: MIN, MAX, RANGE, MEAN, SLOPE

DtoAggregatedCategoricalFunction

Aggregating a categorical signal over the time window given by min and max lags. The source of the function is DtoCategoryEqualsFunction. Numeric input and ouput.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: AggregatedCategorical

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`source`	DtoFunctionId	-	FunctionId of the only input function.
`evalType`	DtoCategoricalFunctionEvalType	-	Evalution type of aggregated categorical function
`maxLag`	DtoNonNegativeDuration	-	Start of the time window.
`minLag`	DtoNonNegativeDuration	-	End of the time window.

DtoCategoricalFunctionEvalType

Available evalution types. Positive state is a state at which the source function (DtoCategoricalEqualsFunction) returns 1.0, i.e., true.

@experimental: Might change in future releases.

Type: String
Enum: POSITIVE_STATE_WAS_PRESENT, DURATION_OF_POSITIVE_STATES, POSITIVE_STATE_CHANGE_COUNT, DURATION_OF_LAST_POSITIVE_STATE

DtoAggregationType

Specify aggregated features to add.

Type: String
Enum: ALL, MIN, MAX, RANGE, MEAN, SLOPE, POSITIVE_STATE_WAS_PRESENT, DURATION_OF_POSITIVE_STATES, POSITIVE_STATE_CHANGE_COUNT, DURATION_OF_LAST_POSITIVE_STATE

DtoKernelModelFunction

A KernelModel is a kernel regressor fine-tuned with the training data. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: KernelModel

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	ID of the function.
`kernelType`	DtoKernelType	-	Engine internal.
`category`	DtoAbstractCategory	-	Engine internal.
`scaleFactors`	DtoFeatureValue[]	-	Engine internal.
`components`	DtoKernelModelComponent[]	-	Engine internal.
`noise`	DtoFloat	-	Engine internal.

DtoKernelType

Engine internal.

Type: String
Enum: LAPLACE, GAUSSIAN, QUADRATIC, LINEAR, MATERN

DtoKernelModelComponent

Engine internal.

Type: Object

Property	Type	Markers	Description
`controlPoint`	DtoFeatureValue[]	-	Engine internal.
`coefficient`	DtoFloat	-	Engine internal.
`id`	DtoControlPointId	optional	Engine internal.
`isSobolPoint`	Boolean	optional	Engine internal.

DtoFeatureValue

Feature value with featureId and its value.

Type: Object

Property	Type	Markers	Description
`feature`	DtoFunctionId	-	Engine internal.
`value`	DtoFloat	-	Engine internal.

DtoFeature

Type: Object

Property	Type	Markers	Description
`feature`	DtoFeatureId	-	-
`mean`	DtoFloat	-	Mean of the feature values computed based on inducing points.
`std`	DtoFloat	-	Standard deviation of the feature values computed based on inducing points.
`min`	DtoFloat	optional	Min of the feature values computed based on inducing points.
`max`	DtoFloat	optional	Max of the feature values computed based on inducing points.

DtoTreeModelFunction

A TreeModel is a tree regressor fine-tuned with the training data. Numeric input and output.

Type: Object
Super-Types: DtoAbstractFunction
Discriminator: _type
Discriminator-Value: TreeModel

Property	Type	Markers	Description
`_type`	String	-	Type of this object.
`id`	DtoFunctionId	-	Engine internal.
`sources`	DtoFunctionId[]	-	Engine internal.
`tree`	DtoTreeNode[]	-	Engine internal.
`root`	DtoTreeNodeId	-	Engine internal.

DtoTreeNode

Engine internal.

Type: Object

Property	Type	Markers	Description
`id`	DtoTreeNodeId	-	Engine internal.
`parent`	DtoTreeNodeId	optional	Engine internal,
`children`	DtoTreeNodeId[]	-	Engine internal.
`predicate`	DtoPredicate	optional	Engine internal.
`labelMean`	DtoFloat	-	Engine internal.
`count`	DtoNonNegativeInteger	-	Engine internal.
`labelMeanInRoot`	DtoFloat	-	Engine internal.
`rating`	DtoFloat	-	Engine internal.
`pvalue`	DtoNonNegativeFloat	optional	Engine internal.

DtoPredicate

Engine internal.

Type: Object

Property	Type	Markers	Description
`sourceFunction`	DtoFunctionId	-	Engine internal.
`min`	DtoFloat	optional	Engine internal.
`max`	DtoFloat	optional	Engine internal.

DtoFeatureStatisticsReport

Store statistics of the feature, sampled from its recorded timestamps within the operative periods.

Type: Object

Property	Type	Markers	Description
`mean`	DtoFloat	-	Mean of the feature values
`std`	DtoFloat	-	Standard deviation of the feature values
`min`	DtoFloat	-	Minimum of the feature values
`max`	DtoFloat	-	Maximum of the feature values
`count`	DtoUnsignedLong	-	Number of the recorded timestamps

DtoProducer

Identifying information on the engine.

Type: Object

Property	Type	Markers	Description
`name`	String	-	Name of the engine.
`version`	String	-	Engine version.

DtoModelType

Specification of the type of data.

Type: String
Enum: SIGNAL_PREDICTION, ANOMALY_DETECTION, STATE_DETECTION

DtoAbstractError

Base error type, generated by the engine.

@abstract

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoErrorParam

Named parameters used in error messages.

Type: Object

Property	Type	Markers	Description
`key`	String	-	-
`value`	Any	-	-

DtoTargetSignalNotFoundError

Failed to find target signal with ID {id}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TargetSignalNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoTargetSignalLowQualityError

Signal with ID {id} cannot be used as target due to its low information quality. Error: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TargetSignalLowQuality

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoTargetSignalDataTypeUnexpectedError

Target signal with ID {id} is expected to be any data type of {expected} but was of data type {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TargetSignalDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoTargetSignalTooManyCategoriesError

Target signal with ID {id} of data type Float contains too many unique values: {numb_of_cats}. Categorical interpreter with target of data type Float allows maximally 42 unique values. If you want to use target nevertheless ingest with data type String.

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TargetSignalTooManyCategories

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalNotFoundError

Failed to find signal with ID {id}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalDataTypeUnexpectedError

Signal with ID {id} is expected to be any data type of {expected} but was of data type {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalInterpreterAmbiguousError

Signal with ID {id} has ambiguous interpreters

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalInterpreterAmbiguous

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoOscillatorySignalInterpretationFailure

Unable to resolve oscillatory interpretation of signal {id} at time t {timestamp} due to too sparse data

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: OscillatorySignalInterpretationFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoColumnNotFoundError

Failed to find column with ID {id}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ColumnNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoColumnDataTypeUnexpectedError

Column with ID {id} is expected to be any data type of {expected} but was of data type {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ColumnDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoColumnValueAmbiguousError

In column with ID {id} there is ambiguity in the values for rows {row_ids}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ColumnValueAmbiguous

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoColumnInterpreterAmbiguousError

Column with ID {id} has ambiguous interpreters

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ColumnInterpreterAmbiguous

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoWeightColumnNegativeValueError

Weight column with ID {id} has negative value in row with ID {row_id}. All weights must be >=0.

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: WeightColumnNegative

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalIdAlreadyInUseError

Signal ID {id} is already in use

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalIdAlreadyInUse

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoColumnIdAlreadyInUseError

Column ID {id} is already in use

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ColumnIdAlreadyInUse

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSegmentNotFoundError

Failed to find segment with ID {id}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SegmentNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInferenceOutputTypeUnexpectedError

Inference output specification is expected to be of data type {expected} but was of data type {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InferenceOutputTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInferenceDataTypeUnexpectedError

Inference data specification for signal with ID {id} is expected to be of data type {expected} but was of data type {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InferenceDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInferenceDataPredecessorMissingError

Inference data is expected to include information on signal {id} at or before timestamp {timestamp}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InferenceDataPredecessorMissing

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInferenceOutputTargetInterpreterTypeUnexpectedError

Inference output specification is expected to be of target interpreter type {expected} but was {actual}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InferenceOutputTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoDataConcurrentModificationError

Failed to modify data with handle '{handle}' due to concurrent usage

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: DataConcurrentModification

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoDataQuantityInsufficientError

Data with handle '{handle}' does not contain any training signals

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: DataQuantityInsufficient

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoDataQualityInsufficientError

Data with handle '{handle}' does not contain any training signals after data removal

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: DataQualityInsufficient

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoHandleDanglingError

Failed to dereference handle '{handle}'

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: HandleDangling

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoHandleTypeUnexpectedError

Handle '{handle}' is expected to be of type '{expected}' but was of type '{actual}'

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: HandleTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoPointerForeignError

Pointer was not created by this engine instance

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: PointerForeign

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoPointerTypeUnexpectedError

Pointer has unexpected type

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: PointerTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoStringEncodingInvalidError

Pointer failed to be decoded as string: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: StringEncodingInvalid

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoExpressionSyntaxFailureError

Failed to compile expression {expression}: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ExpressionSyntaxFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoExpressionRuntimeFailureError

Failed to evaluate expression {expression} at timestamp '{timestamp}': {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ExpressionRuntimeFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoExpressionResultDataTypeUnexpectedError

Result of expression {expression} is expected to be of data type {expected} but was of type {actual} at timestamp '{timestamp}'

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ExpressionResultDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoTabularExpressionRuntimeFailureError

Failed to evaluate expression {expression} at row '{row_id}': {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TabularExpressionRuntimeFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoTabularExpressionResultDataTypeUnexpectedError

Result of expression {expression} is expected to be of data type {expected} but was of type {actual} at row '{row_id}'

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: TabularExpressionResultDataTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoLicenseServerCommunicationFailureError

Failed to communicate with license server: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: LicenseServerCommunicationFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoLicenseApiKeyNotFoundError

Failed to find license api key

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: LicenseApiKeyNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoLicenseInsufficientError

License terms insufficient

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: LicenseInsufficient

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoIncrementalLearningModelCorruptedError

DtoIncremental data does not match remaining model data: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: IncrementalLearningModelCorrupted

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoIncrementalLearningDataQualityInsufficientError

Insufficient data quality of signals at label timestamps

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: IncrementalLearningDataQualityInsufficient

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalConstraintInterpreterUnexpectedError

Constraint on signal with not supported interpreter

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalConstraintInterpreterUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoModelConstraintNotFoundError

Model ID {id} not part of the hub model

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ModelConstraintNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoConstraintNavigatorHubModelUnsuitedError

Model with model ID {id} is not differentiable. Can't be used for constraint inference.

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ConstraintNavigatorHubModelUnsuited

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoConstraintsMissingError

Model constraints must be provided in the inference_config in order to call the endpoint infer_float_with_next_normal.

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ConstraintsMissing

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoModelConstraintInconsistentError

For model constraint {id} the lower threshold is above the upper threshold at timestamp {timestamp}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ModelConstraintInconsistent

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalConstraintInconsistentError

In the constraint for signal/feature {id} the lower threshold is above the upper threshold at timestamp {timestamp}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalConstraintInconsistent

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSignalConstraintTrainingConflictError

The user set thresholds [{min_user}, {max_user}] lie outside of the data range seen in training [{min}, {max}] of signal/feature {id} at timestamp {timestamp}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SignalConstraintTrainingConflict

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoModelTypeUnexpectedError

Model {id} is expected to be '{expected}' model but it is '{actual} model

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ModelTypeUnexpected

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoSubModelIncrementalInfoNotFoundError

SubModelIncrementalInfo for model {id} cannot be found from IncrementalInfo

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: SubModelIncrementalInfoNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoDependencyAnalysisConstraintConfigNotFoundError

At least one of inner_linear_constraint_config or outer_linear_constraint_config should be present

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: DependencyAnalysisConstraintConfigNotFound

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoJsonParseFailureError

Failed to parse json: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: JsonParseFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoJsonValidationFailureError

Failed to validate json: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: JsonValidationFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInferenceRawSignalSpecificationDataTypeAmbiguousError

Data type of signal {id} is ambiguous in inference data specification

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InferenceRawSignalSpecificationDataTypeAmbiguous

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoOperativeSignalMissingTrueValuesError

Failed to identify operative periods: the operative signal must contain at least one 'true' value.

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: OperativeSignalMissingTrueValues

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoInternalEngineFailureError

Internal engine failure: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: InternalEngineFailure

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoArgumentValidationError

Failed to validate argument: {error}

Type: Object
Super-Types: DtoAbstractError
Discriminator: _type
Discriminator-Value: ArgumentValidationError

Property	Type	Markers	Description
`_type`	String	-	Type discriminator.
`message`	String	-	Error message.
`details`	DtoErrorParam[]	-	List of named parameters used in this error's message.

DtoAbstractCategory

@abstract

Type: Object
Sub-Types: DtoStringCategory, DtoFloatCategory, DtoBooleanCategory
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type discriminator

DtoStringCategory

Type: Object
Super-Types: DtoAbstractCategory
Discriminator: _type
Discriminator-Value: String

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	String	-	-

DtoFloatCategory

Type: Object
Super-Types: DtoAbstractCategory
Discriminator: _type
Discriminator-Value: Float

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	DtoFloat	-	-

DtoBooleanCategory

Type: Object
Super-Types: DtoAbstractCategory
Discriminator: _type
Discriminator-Value: Boolean

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	Boolean	-	-

DtoAbstractColumnValue

@abstract

Type: Object
Sub-Types: DtoStringColumnValue, DtoFloatColumnValue, DtoBooleanColumnValue
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type discriminator

DtoStringColumnValue

Type: Object
Super-Types: DtoAbstractColumnValue
Discriminator: _type
Discriminator-Value: String

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	String	-	-

DtoFloatColumnValue

Type: Object
Super-Types: DtoAbstractColumnValue
Discriminator: _type
Discriminator-Value: Float

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	DtoFloat	-	-

DtoBooleanColumnValue

Type: Object
Super-Types: DtoAbstractColumnValue
Discriminator: _type
Discriminator-Value: Boolean

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`value`	Boolean	-	-

DtoMatrix

Type: Object

Property	Type	Markers	Description
`rows`	DtoPositiveInteger	-	-
`cols`	DtoPositiveInteger	-	-
`entries`	DtoFloat[]	-	-

DtoSymmetricMatrix

Type: Object

Property	Type	Markers	Description
`rows`	DtoPositiveInteger	-	-
`entries`	DtoFloat[]	-	-

DtoSymmetricBlockDiagonalMatrix

Type: Object

Property	Type	Markers	Description
`entries`	DtoSymmetricMatrix[]	-	-

DtoTime

Type: Number
Restrictions: int64, >= 0.0

DtoSegmentId

Type: Number
Restrictions: int64

DtoSignalId

Type: String
Restrictions: size >= 1

DtoModelId

Type: String
Restrictions: size >= 1

DtoColumnId

Type: String
Restrictions: size >= 1

DtoClusterId

Type: Number
Restrictions: int32, >= 0.0

DtoControlPointId

Type: Number
Restrictions: int32, >= 0.0

DtoExpression

Type: String
Restrictions: size >= 1

DtoPositiveDuration

Type: Number
Restrictions: int64, >= 1.0

DtoNonNegativeDuration

Type: Number
Restrictions: int64, >= 0.0

DtoPositiveInteger

Type: Number
Restrictions: int32, >= 1.0

DtoNonNegativeInteger

Type: Number
Restrictions: int32, >= 0.0

DtoFloat

Type: Number
Restrictions: double

DtoNonNegativeFloat

Type: Number
Restrictions: double, >= 0.0

DtoPositiveFloat

Type: Number
Restrictions: double, >= 0.0

DtoFunctionId

Type: Number
Restrictions: int64, >= 0.0

DtoFeatureId

Type: Number
Restrictions: int64, >= 0.0

DtoTreeNodeId

Type: Number
Restrictions: int64, >= 0.0

DtoCorrelation

Type: Number
Restrictions: double, >= 0.0, <= 1.0

DtoPercentage

Type: Number
Restrictions: double, >= 0.0, <= 1.0

DtoUuid

A version 4 Uuid.

Type: String
Restrictions: exp = [0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}

DtoUnsignedLong

Type: Number
Restrictions: int64, >= 0.0

DtoAnalysisConfig

Necessary input configuration for a state detection analysis (first step for a state detection model or stand-alone step). Includes information about which of the available information is to be used and how.

Type: Object

Property	Type	Markers	Description
`dataFilter`	DtoDataFilter	optional, default: `{}`	Restrictions on the data used. Determines which signals to use and for which time ranges.
`target`	DtoTargetConfig	-	Configuration of the boolean target signal, the signal to be used to detect different states. Should be an incident signal.
`selfLabeling`	DtoSelfLabelingConfig	-	This determines how early before an incident the engine looks for the incident's origin.
`sampling`	DtoAnalysisSamplingConfig	-	Configures how the data is sampled for analysis.
`operativePeriods`	DtoOperativePeriodsConfig	optional	Configuration of a booelan signal in the data that says if the production environment was operative at a time. Target data from non-operative times is not used for analysis and subsequent training. By default, all times are assumed to be operative.
`signals`	DtoSignalConfig[]	optional, default: `[]`	Configures the interpretation of the input signals. Any signal without configuration defaults to a standard configuration depending on its data type. Multiple entries for a single signal are not allowed.
`lagging`	DtoLaggingConfig	optional	Configures which time points in the past to consider to make a prediction. If this is not set, only the most current signal values are used.
`segmenting`	DtoSegmentingConfig	optional, default: `{}`	Configures how incidents are grouped into segments.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoTargetConfig

Information on the target signal.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	Boolean signal in the data that describes occurences of an incident which should be predicted.

DtoSelfLabelingConfig

Adjust how the engine determines the start of the state leading to an incident.

Type: Object

Property	Type	Markers	Description
`coherencePeriod`	DtoPositiveDuration	-	The duration of the time period before each incident that could reasonably be expected to contain the beginning of the problematic state leading to the incident.
`mesh`	DtoPositiveDuration	-	Time resolution to be used inside the coherence period. Must not be bigger than coherencePeriod.

DtoAnalysisSamplingConfig

Adjusts the time points where the data is evaluated, called the sample time points. In general, data is evaluated at all time points before and at incidents.

Type: Object

Property	Type	Markers	Description
`additionalSampleMesh`	DtoPositiveDuration	optional	Time increment after which sample time points are added within existing gaps (their value will be the last known value). If this is not set, no additional sample time points are generated. If your target signal only registers value changes, it is important to set this property.
`maximalSampleCount`	DtoPositiveInteger	optional, default: `70000`	Maximal number of samples to be used. Exclusion is based on the expected relevance.
`removeOutliers`	Boolean	optional, default: `false`	Flag indicating whether outliers should be removed from training samples or considered part of normal behaviour.

DtoTrainingSamplingConfig

Adjusts the time points where the data is evaluated, called the sample time points. In general, data is evaluated at all time points before and at transitions.

Type: Object

Property	Type	Markers	Description
`maximalSampleCount`	DtoPositiveInteger	optional, default: `70000`	Maximal size of subset of samples from analysis, to be used for training. Exclusion is based on the expected relevance.

DtoOperativePeriodsConfig

Configures which time periods to be regarded as operative and whether different operative time periods are to be interpreted as batches.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	Boolean signal in the data that says if the production environment was operative at a time. Data from non-operative times is not used for training.
`batches`	Boolean	-	Set this to true if each continuous interval of operative times should be considered to be its own process (that either contained an incident or did not). If false, all times are considered part of one continuous process.

DtoSignalConfig

Handling of a specific signal.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	ID of the signal.
`interpreter`	DtoAbstractSignalInterpreter	optional, default: `{"_type":"Default"}`	Controls how aspects are derived from the signal values.
`preference`	DtoNonNegativeFloat	optional, default: `0.0` @experimental	The higher the preference, the more likely the signal will be used in the model. A considerable preference is obtained for a value of 1.0. @experimental: Might change in future releases.
`forceRetain`	Boolean	optional, default: `false`	Prevents the removal of the signal and forces inclusion of all signal aspects and of derived features. This flag has no effect on the target signal, on empty and on constant signals.
`lagging`	DtoSignalLaggingConfig	optional	Configures which time points in the past to consider to make a prediction. If set, this signal specific lagging configuration supersedes the global lagging configuration.

DtoSignalLaggingConfig

Signal specific confguration how to consider past signal values.

Type: Object

Property	Type	Markers	Description
`maximalLag`	DtoNonNegativeDuration	-	Upper bound on the considered delay (lag) of the influence of signals. A delayed influence means that a signal value evaluated for time "t - delay" is relevant for inference at "t".
`minimalLag`	DtoNonNegativeDuration	optional, default: `0`	Lower bound on the considered delay (lag) of the influence of signals. A delayed influence means that a signal value evaluated for time "t - delay" is relevant for inference at "t". May not be bigger than maximalLag.
`mesh`	DtoPositiveDuration	-	Time resolution of the delays (lags) to be considered (ignored if maximal lag = minimal lag).

DtoLaggingConfig

Consideration of signal values in the past while inference.

Type: Object

Property	Type	Markers	Description
`maximalLag`	DtoNonNegativeDuration	-	Upper bound on the considered delay (lag) of the influence of signals. A delayed influence means that a signal value evaluated for time "t - delay" is relevant for inference at "t".
`minimalLag`	DtoNonNegativeDuration	optional, default: `0`	Lower bound on the considered delay (lag) of the influence of signals. A delayed influence means that a signal value evaluated for time "t - delay" is relevant for inference at "t". Must not be bigger than maximalLag.
`mesh`	DtoPositiveDuration	-	Time resolution of the delays (lags) to be considered; (maximalLag - minimalLag) must not be smaller than mesh except if maximalLag = minimalLag.

DtoSegmentingConfig

Configures how incidents are grouped into segments in (different) zoom levels.

Type: Object

Property	Type	Markers	Description
`minimalSegmentSize`	DtoPositiveInteger	optional, default: `1`	Minimal number of incidents to be considered a segment; remaining incidents will be added to the segmentationResidue-segment (whose size is smaller than minimalSegmentSize).
`outputMultipleZoomLevels`	Boolean	optional, default: `false`	If set to true, multiple zoomLevels will be calculated and included in the output. If set to false, the only zoomLevel to be returned will be the one with the highest rating.

DtoAnalysisReport

Information about the process and the result of a state detection analysis. Includes informations about different segmentations to help you choose segments for a potential subsequent training.

Type: Object

Property	Type	Markers	Description
`producer`	DtoProducer	-	Information on the engine this object was built with.
`config`	DtoAnalysisConfig	-	Input configuration that resulted in this object.
`aivis_engine_v2_sd_sdk_python.data`	DtoDataReport	-	Information on the data this object was based on.
`dataUsage`	DtoDataUsageReport	-	Information on the selection of data that was used to analyze incidents and will be used in training of a model based on this analysis.
`incidents`	DtoIncidentReport[]	-	The incidents found in the data that were analyzed and will be considered for training.
`zoomLevels`	DtoZoomLevelReport[]	-	Analyses, each at a specific zoom factor.

DtoDataUsageReport

Information about data selected for analysis and model training.

Type: Object

Property	Type	Markers	Description
`trainingStartTime`	DtoTime	-	The start of the observed timerange.
`trainingEndTime`	DtoTime	-	The end of the observed timerange (inclusive).
`totalIncidentCount`	DtoPositiveInteger	-	Total number of incidents in the observed timerange of target signal.
`removedIncidents`	DtoIncidentRemoval[]	-	Incidents that will not be analyzed or used in model training, and the respective reasons.
`removedSignals`	DtoSignalRemoval[]	-	Signals that will not be analyzed or used in model training, and the respective reasons.

DtoIncidentRemoval

Information about an incident not selected for further analysis and model training

Type: Object

Property	Type	Markers	Description
`incidentStartTime`	DtoTime	-	The time when label switched from false to true (marking the start of this incident).
`reason`	DtoIncidentRemovalReason	-	The reason why the incident was removed.

DtoIncidentRemovalReason

Reasons for an incident to be removed analysis and model training
NOT_OPERATIVE - Start of incident not in the range specified by DtoOperativePeriodsConfig
RAPID_SUCCESSION - Incident too soon after the previous incident

Type: String
Enum: NOT_OPERATIVE, RAPID_SUCCESSION

DtoSignalRemoval

Information about a signal not selected for further analysis and model training.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	ID of the removed signal.
`reason`	DtoSignalRemovalReason	-	The reason why the signal was removed.

DtoSignalRemovalReason

Reasons to not include a signal in the model. Can be overruled by forceRetain flag.
TARGET_SIGNAL - Target signal
TARGET_INVOLVED_SIGNAL - Signal used to build the target signal by the expression language
NO_INFORMATION - Signal empty or constant
INDEPENDENT - Signal independent to target signal

Type: String
Enum: TARGET_SIGNAL, TARGET_INVOLVED_SIGNAL, NO_INFORMATION, INDEPENDENT, COLLINEAR, LOW_IMPORTANCE

DtoIncidentReport

Information about incidents, i.e. periods of time where the target signal has value true.

Type: Object

Property	Type	Markers	Description
`id`	DtoIncidentId	-	Unique identifier among all incidents.
`startTime`	DtoTime	-	The time the incident started (transition of the target signal's value from false to true).
`endTime`	DtoTime	-	The end of the incident (target signal changes back from true to false).
`originTime`	DtoTime	-	The start of the state causing this incident; found within the temperature-maximalLag before the start.

DtoZoomLevelReport

A clustering (of some granularity) of the observed incidents into segments.

Type: Object

Property	Type	Markers	Description
`segments`	DtoSegmentReport[]	-	Segments of this specific zoom level. Incidents in one segment probably are caused by similar states.
`segmentationResidue`	DtoSegmentReport	optional	The remaining incidents that do not belong to any of the segments.
`rating`	DtoNonNegativeFloat	-	Some rating reflecting how "good" this zoom level is; bigger is potentially better.

DtoSegmentReport

Information pertaining to a subset of all incidents / states leading to incidents.

Type: Object

Property	Type	Markers	Description
`id`	DtoSegmentId	-	Unique identifier among all segments of all zoom levels.
`incidents`	DtoIncidentId[]	-	The incidents that are caused by states of this segment.
`signals`	DtoSignalReport[]	-	Includes information about the strength of interdependency between (aspects of) signals and the label in the context of this segment.
`features`	DtoAbstractFeatureReport[]	optional	Features used in the model. Features are auto-engineered from signal aspects.

DtoSignalReport

Wrapper for metrics measuring e.g. the strength of interdependency between the label signal and (lagged variants of) a signal aspects.

Type: Object

Property	Type	Markers	Description
`signal`	DtoSignalId	-	Signal this belongs to.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal and the label signal.
`aspects`	DtoAbstractSignalAspectReport[]	-	Relevant aspects of the signal and associated metrics.

DtoAbstractSignalAspectReport

Abstract base class of aspect report classes

@abstract

Type: Object
Sub-Types: DtoNumericalSignalAspectReport, DtoCategoricalSignalAspectReport, DtoOscillatoryPowerSignalAspectReport, DtoOscillatoryPhaseSignalAspectReport, DtoCyclicSignalAspectReport
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.

DtoNumericalSignalAspectReport

information about a numerical signal

Type: Object
Super-Types: DtoAbstractSignalAspectReport
Discriminator: _type
Discriminator-Value: Numerical

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.

DtoCategoricalSignalAspectReport

information about the occurence-signal of one category of a categorical signal

Type: Object
Super-Types: DtoAbstractSignalAspectReport
Discriminator: _type
Discriminator-Value: Categorical

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.
`category`	DtoAbstractCategory	-	-

DtoOscillatoryPowerSignalAspectReport

information about the energy in a frequencySpectrum of an oscillatory signal

Type: Object
Super-Types: DtoAbstractSignalAspectReport
Discriminator: _type
Discriminator-Value: OscillatoryPower

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.
`minFrequency`	DtoNonNegativeFloat	-	The lowest frequency included in the frequency band.
`maxFrequency`	DtoNonNegativeFloat	-	Exclusive upper bound of the frequency band.

DtoOscillatoryPhaseSignalAspectReport

information about the phase of a frequency of an oscillatory signal

Type: Object
Super-Types: DtoAbstractSignalAspectReport
Discriminator: _type
Discriminator-Value: OscillatoryPhase

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.
`frequency`	DtoNonNegativeFloat	-	The frequency to which the phase belongs.

DtoCyclicSignalAspectReport

information about a cyclic signal

Type: Object
Super-Types: DtoAbstractSignalAspectReport
Discriminator: _type
Discriminator-Value: Cyclic

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`aspect`	DtoFunctionId	optional	Id of this aspect.
`correlation`	DtoCorrelation	-	Overall strength of interdependency between this signal aspect and the label signal.
`laggedCorrelations`	DtoCorrelation[]	@experimental	Overall strength of interdependency between lagged variants of this signal aspect (sorted chronological, i.e. [0] is maximal lag) and the label signal. @experimental: Might change in future releases.

DtoAbstractFeatureReport

Information about a feature.

@abstract

Type: Object
Sub-Types: DtoLagFeatureReport, DtoLtiFilterFeatureReport, DtoAggregatedNumericalFeatureReport, DtoAggregatedCategoricalFeatureReport
Discriminator: _type

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`feature`	DtoFunctionId	-	Id of this feature.
`statistics`	DtoFeatureStatisticsReport	optional	Statistics of the feature, sampled from its recorded timestamps within the operative periods.

DtoLagFeatureReport

A feature created from a source aspect by delaying it by some lag.

Type: Object
Super-Types: DtoAbstractFeatureReport
Discriminator: _type
Discriminator-Value: Lag

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`feature`	DtoFunctionId	-	Id of this feature.
`statistics`	DtoFeatureStatisticsReport	optional	Statistics of the feature, sampled from its recorded timestamps within the operative periods.
`source`	DtoFunctionId	-	Id of the source aspect of this feature.
`lag`	DtoNonNegativeDuration	-	Lag applied to source aspect to create feature.

DtoLtiFilterFeatureReport

A feature created from a source aspect by applying an Lti filter to it.

Type: Object
Super-Types: DtoAbstractFeatureReport
Discriminator: _type
Discriminator-Value: LtiFilter

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`feature`	DtoFunctionId	-	Id of this feature.
`statistics`	DtoFeatureStatisticsReport	optional	Statistics of the feature, sampled from its recorded timestamps within the operative periods.
`source`	DtoFunctionId	-	Id of the source aspect of this feature.

DtoAggregatedNumericalFeatureReport

A feature created from a source aspect by applying a numerical aggregated function to it.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFeatureReport
Discriminator: _type
Discriminator-Value: AggregatedNumerical

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`feature`	DtoFunctionId	-	Id of this feature.
`statistics`	DtoFeatureStatisticsReport	optional	Statistics of the feature, sampled from its recorded timestamps within the operative periods.
`source`	DtoFunctionId	-	Id of the source aspect of this feature.
`evalType`	DtoNumericalFunctionEvalType	-	Evaluation type applied to source aspect to create the aggregated feature.

DtoAggregatedCategoricalFeatureReport

A feature created from a source aspect by applying a categorical aggregated function to it.

@experimental: Might change in future releases.

Type: Object
Super-Types: DtoAbstractFeatureReport
Discriminator: _type
Discriminator-Value: AggregatedCategorical

Property	Type	Markers	Description
`_type`	String	-	Type discriminator
`feature`	DtoFunctionId	-	Id of this feature.
`statistics`	DtoFeatureStatisticsReport	optional	Statistics of the feature, sampled from its recorded timestamps within the operative periods.
`source`	DtoFunctionId	-	Id of the source aspect of this feature.
`evalType`	DtoCategoricalFunctionEvalType	-	Evaluation type applied to source aspect to create the aggregated feature.

DtoTrainingPreparation

Information from the state detection analysis needed for a potential subsequent training step

Type: Object

Property	Type	Markers	Description
`producer`	DtoProducer	-	Information on the engine this object was built with.
`info`	DtoTrainingPreparationInfo	optional @experimental	Information about this training preparation and its creation; not needed for training @experimental: Might change in future releases.
`functions`	DtoAbstractFunction[]	-	All considered features. A feature is an adapted form of a source signal to increase its correlation with the target signal.
`commonLabelHistory`	DtoLabelDataPoint[]	-	The labelHistory that should be used for training in all segments (additional to the segment specific history)
`zoomLevels`	DtoTrainingPreparationZoomLevel[]	-	Segmentations, each at a specific zoom factor. You may choose segments from one or more zoomLevels for subsequent training.
`incidentContext`	DtoIncidentContext	optional @experimental	The incident context is used only for tree model training for which it must be set. @experimental: Might change in future releases.

DtoTrainingPreparationInfo

Information about this training preparation and its creation

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`config`	DtoAnalysisConfig	-	Input configuration that resulted in this object.

DtoLabelDataPoint

data point of a float signal

Type: Object

Property	Type	Markers	Description
`timestamp`	DtoTime	-	Detection timestamp of this data point
`value`	DtoFloat	-	Float value of this data point

DtoTrainingPreparationZoomLevel

A clustering (of some granularity) of the observed incidents into segments. Only includes information needed for subsequent training.

Type: Object

Property	Type	Markers	Description
`segments`	DtoTrainingPreparationSegment[]	-	Segments of this specific zoom level. Incidents in one segment probably are caused by similar states.
`segmentationResidue`	DtoTrainingPreparationSegment	optional	Segment of the remaining incidents that do not belong in any of the segments.
`rating`	DtoFloat	-	Some rating reflecting how "good" this zoom level is (in the engine's opinion)… bigger is potentially better.

DtoTrainingPreparationSegment

All information pertaining to a subset of all events / states leading to events.

Type: Object

Property	Type	Markers	Description
`id`	DtoSegmentId	-	Unique identifier among all segments of all zoom levels.
`labelHistory`	DtoLabelDataPoint[]	-	The labelHistory that should be used for training (additionally in this segment)
`features`	DtoFunctionId[]	-	Considered features for this segment.

DtoIncidentContext

Information about incidents, indicating time intervals before incidents and time intervals without incidents happened at the end. It is only relevant for tree model.

Type: Object

Property	Type	Markers	Description
`intervalsBeforeIncidents`	DtoIntervalBeforeIncident[]	-	time intervals that are followed by an incident (the target signal of state detection).
`intervalsWithoutIncidents`	DtoIntervalWithoutIncident[]	-	time intervals that are not followed by an incident.

DtoTrainingConfig

Necessary input configuration for a state detection training. Can be created from a DtoTrainingPreparation and a DtoPreparationBasedTrainingConfig.

Type: Object

Property	Type	Markers	Description
`dataFilter`	DtoDataFilter	optional, default: `{}`	Restrictions on the data used. Determines which signals to use and for which time ranges.
`sampling`	DtoTrainingSamplingConfig	optional, default: `{}`	Configures how the data is sampled for training.
`functions`	DtoAbstractFunction[]	-	All considered features, including features only needed by other features. A feature is an adapted form of a source signal to increase its correlation with the target signal.
`commonLabelHistory`	DtoLabelDataPoint[]	-	The labelHistory that should be used for training in all segments (additional to the segment specific history)
`segments`	DtoTrainingPreparationSegment[]	-	Segments of this specific zoom level.
`modeling`	DtoModelingConfig	optional, default: `{}`	Configuration of the prediction model.
`incidentContext`	DtoIncidentContext	optional @experimental	The incident context is used only for tree model training for which it must be set. @experimental: Might change in future releases.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoPreparationBasedTrainingConfig

To start a training from a DtoTrainingPreparation this additional config is necessary.

Type: Object

Property	Type	Markers	Description
`dataFilter`	DtoDataFilter	optional, default: `{}`	Restrictions on the data used. Determines which signals to use and for which time ranges.
`sampling`	DtoTrainingSamplingConfig	optional, default: `{}`	Configures how the data is sampled for training.
`segments`	DtoSegmentId[]	optional	Segments from the DtoTrainingPreparation that should be used for model building. If this is not set, all segments of the zoomLevel with highest rating are used.
`modeling`	DtoModelingConfig	optional, default: `{}`	Configuration of the prediction model.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoModelingConfig

Configuration of a kernel model.

Type: Object

Property	Type	Markers	Description
`controlPointCount`	DtoPositiveInteger	optional, default: `5000`	Granularity of the model. Increase generally leads to better quality but longer runtime.

DtoTrainingReport

Information from state detection training (irrelevant for inference)

Type: Object

Property	Type	Markers	Description
`producer`	DtoProducer	-	Information on the engine this object was built with.
`config`	DtoTrainingConfig	-	Input configuration that resulted in this object.
`aivis_engine_v2_sd_sdk_python.data`	DtoDataReport	-	Information on the data this object was based on.

DtoModel

The output of a request to make a state detection model. Includes all information necessary to make predictions of incidents (apart from data itself).

Type: Object

Property	Type	Markers	Description
`producer`	DtoProducer	-	Information on the engine this object was built with.
`info`	DtoModelInfo	optional @experimental	Information about this Model and its creation; not needed for inference @experimental: Might change in future releases.
`inferenceDataSpecification`	DtoInferenceDataSpecification	-	Specification of the data that is needed for a subsequent inference with this model.
`functions`	DtoAbstractFunction[]	-	All functions needed across all segments.
`segments`	DtoModelSegment[]	-	Segments of this model. Different segments differ in the relationship between signals and the target.

DtoModelInfo

Information about this Model and its creation

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`config`	DtoTrainingConfig	-	Input configuration that resulted in this object.

DtoModelSegment

All information that pertains to a single segment, a subset of samples.

Type: Object

Property	Type	Markers	Description
`id`	DtoSegmentId	-	ID of this segment (=ID of the trainingPreparation-segment this is based on)
`resultFunction`	DtoFunctionId	-	The final function that provides the prediction of this segment.

DtoInferenceConfig

Necessary input configuration to use a state detection model to predict transitions.

Type: Object

Property	Type	Markers	Description
`dataFilter`	DtoDataFilter	optional, default: `{}`	Restrictions on the data used. Determines which signals to use and for which time ranges.
`skipOnInsufficientData`	Boolean	-	This flag controls the behaviour for missing data at inference. Inference is only possible if the data adheres the inference data specification. If the flag is set to true, timestamps for which data are insufficient are skipped. If set to false, an error is thrown if data is not sufficient for some timestamp.
`dev`	Any	optional	Unstable and undocumented configuration options. Developers only.

DtoNextNormalConfig

Input configuration to set a normal threshold for each segment. Scores below the threshold are considered normal.

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`globalNormalThreshold`	DtoPercentage	-	Normal threshold used for those segments for which no segment specific DtoSegmentNormalThreshold is provided under segmentNormalThresholds.
`segmentNormalThresholds`	DtoSegmentNormalThreshold[]	optional, default: `[]`	Segment specific normal thresholds.
`featureFilter`	DtoFeatureFilter	optional, default: `[]`	Features to be included or excluded for finding the next normal point. If this is not set, the next normal point is seeked for in the full feature space.

DtoSegmentNormalThreshold

Segment specific normal threshold. A segment score below the threshold is considered normal.

Type: Object

Property	Type	Markers	Description
`segment`	DtoSegmentId	-	ID of the segment.
`value`	DtoPercentage	-	The normal threshold.

DtoIncidentId

Type: Number
Restrictions: int64

DtoLongString

Type: String
Restrictions: size <= 4096

DtoSignalTemperaturesConfig

Necessary input configuration for a request to calculate signal temperatures

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`signalFilter`	DtoTemperaturesSignalFilter	optional, default: `{}`	Restrictions on the signals for which temperatures should be computed.
`temperatures`	DtoTemperatureConfig	-	How temperatures are computed

DtoTemperaturesSignalFilter

Identify a subset of the signals in a data context

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`includeSignals`	DtoSignalId[]	optional	If present, include only these signals
`excludeSignals`	DtoSignalId[]	optional	If present, exclude all these signals

DtoTemperatureConfig

@experimental: Might change in future releases.

Type: Object

Property	Type	Markers	Description
`coherencePeriod`	DtoPositiveDuration	-	-
`mesh`	DtoPositiveDuration	-	Time resolution of the considered delay.

Sub-modules

aivis_engine_v2_sd_sdk_python.analysis
aivis_engine_v2_sd_sdk_python.data
aivis_engine_v2_sd_sdk_python.dto
aivis_engine_v2_sd_sdk_python.inference
aivis_engine_v2_sd_sdk_python.setup
aivis_engine_v2_sd_sdk_python.signal_temperatures
aivis_engine_v2_sd_sdk_python.training