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External module "src/util"

Index

Type aliases

Functions

Object literals

Type aliases

Fake

Fake: {}

Type declaration

  • [index: string]: any

Functions

generateNumberRange

  • generateNumberRange(start: number, end: number): number[]

getData

  • getData(items: number): any[]

getDatum

  • getDatum(customDate?: Date, customTransation?: { amount?: number; late_payments?: boolean }): any

getMockClassification

  • getMockClassification(): { data: { animal: string; ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[]; dependent_variables: string[]; independent_variables: string[]; prediction_inputs: { ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[] }

  • Returns { data: { animal: string; ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[]; dependent_variables: string[]; independent_variables: string[]; prediction_inputs: { ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[] }

    • data: { animal: string; ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[]
    • dependent_variables: string[]
    • independent_variables: string[]
    • prediction_inputs: { ear_style: string; primary_sound: string; secondary_sound: string; walking_noise_level: number; weight: number }[]

getMockRegression

  • getMockRegression(): { data: { ignored_1: number; input_1: number; input_2: number; input_3: number; output_1: number; output_2: number }[]; dependent_variables: string[]; independent_variables: string[]; prediction_inputs: { ignored_1: number; input_1: number; input_2: number; input_3: number }[] }

  • Returns { data: { ignored_1: number; input_1: number; input_2: number; input_3: number; output_1: number; output_2: number }[]; dependent_variables: string[]; independent_variables: string[]; prediction_inputs: { ignored_1: number; input_1: number; input_2: number; input_3: number }[] }

    • data: { ignored_1: number; input_1: number; input_2: number; input_3: number; output_1: number; output_2: number }[]
    • dependent_variables: string[]
    • independent_variables: string[]
    • prediction_inputs: { ignored_1: number; input_1: number; input_2: number; input_3: number }[]

getMockTimeseries

  • getMockTimeseries(): { dependent_variables: string[]; independent_variables: string[]; input_independent_features: { feature_field_name: string; feature_field_type: AutoFeatureTypes }[]; prediction_inputs: any[]; timeseriesData: any[] }

  • Returns { dependent_variables: string[]; independent_variables: string[]; input_independent_features: { feature_field_name: string; feature_field_type: AutoFeatureTypes }[]; prediction_inputs: any[]; timeseriesData: any[] }

    • dependent_variables: string[]
    • independent_variables: string[]
    • input_independent_features: { feature_field_name: string; feature_field_type: AutoFeatureTypes }[]
    • prediction_inputs: any[]
    • timeseriesData: any[]

randomNumber

  • randomNumber(min: number, max: number): number

Const timeseriesSort

  • timeseriesSort(a: ModelXDataTypes.Datum, b: ModelXDataTypes.Datum): number

Object literals

Const Faker

Faker: object