API Reference

Constructors

new()

DataPredictNucleus.new({instanceId: string, url: string, uuid: string, apiKey: string}): DataPredictNucleusInstance

Parameters:

• instanceId: The id for the instance. If the instance id already exists, it will return the instance containing that id.

• url: The target url that contains the backend code. [Default: nucleus-api.datapredict.online]

• uuid: The unique identifier that was given to you when you registered your account.

• apiKey: The API key that deter

• commandPayloadArrayKey: The key for retrieving cached command payload. [Default: default]

• syncTime: The duration between syncs in seconds. [Default: 3]

• maximumNumberOfSyncRetry: The maximum number of sync retries if the sync fails. [Default: 3]

• syncRetryDelay: The delay between sync retries in seconds. [Default: 2]

• commandPayloadArrayCacheDuration: How long should the cached command payload should persists in seconds. [Default: 30]

Returns:

• DataPredictNucleusInstance: The instance created/retrieved based on the instance id.

Functions

destroy()

DataPredictNucleus:destroy()

startSync()

DataPredictNucleus:startSync()

stopSync()

DataPredictNucleus:stopSync()

addModelData()

DataPredictNucleus:addModelData(modelName: string, modelDictionary: {}, modelParameterNameArray: {string}, modelParametersType: string, classNameArray: {string})

Parameters:

• modelName: The model name to be used by the front end.

• modelDictionary: The existing model dictionary (if any) to be added. [Default: {}]

• modelParameterNameArray: The model parameter names to be added. [Default: {}]

• modelParametersType: The type of model parameters for this model. Available options are:

  • nil (Default)

  • Gradient

  • Centroids

• classNameArray: An array containing all the classes based on the output of the model.

removeModelData()

DataPredictNucleus:removeModelData(modelName: string)

Parameters:

• modelName: The model name to be removed from the DataPredict Nucleus instance.

getModelData()

DataPredictNucleus:getModelData(modelName: string): {}

Parameters:

• modelName: The model name to be retrieved from the DataPredict Nucleus instance.

Returns:

• modelData: A dictionary containing all the data for that particular model.

addModelToModelData()

DataPredictNucleus:addModelToModelData(modelName: string, key: string, Model: Model)

Parameters:

• modelName: The model name for the model data.

• key: A unique key identifying the model.

• Model: The model to be added to the model data.

removeModelFromModelData()

DataPredictNucleus:removeModelFromModelData(modelName: string, key: string)

Parameters:

• modelName: The model name for the model data.

• key: A unique key identifying the model.

removeModelFromModelData()

DataPredictNucleus:applyFunctionToAllModelsInModelData(modelName: string, functionToApply: function)

Parameters:

• modelName: The model name for the model data.

• functionToApply: The function to apply to the model data based on the model name.

addCommand()

DataPredictNucleus:addCommand(commandName: string, functionToRun: function)

Parameters:

• commandName: The command name to be added.

• functionToRun: The function to run when the command name is called.

removeCommand()

DataPredictNucleus:removeCommand(commandName: string)

Parameters:

• commandName: The command name to be removed.

runCommand()

DataPredictNucleus:runCommand(valueDictionary: {})

Parameters:

• valueDictionary: A dictionary containing what command to run. It must contain “commandName” key.

addLog()

DataPredictNucleus:addLog(logType: string, logMessage: string)

Parameters:

• logType: The type of the log. Available options are:

  • Normal

  • Warning

  • Error

• logMessage: The log message to add.

removeLog()

DataPredictNucleus:removeLog(position: number)

• position: The position of the log message to be removed.

getLogArray()

DataPredictNucleus:getLogArray(): 

Returns:

• logArray: An array containing all the logs.

clearLogArray()

DataPredictNucleus:clearLogArray()