A special detection mode which models a form of darkvision (night vision). This mode is the default case which is tested first when evaluating visibility of objects.

Hierarchy (view full)

Properties

_source: any

The source data object for this DataModel instance. Once constructed, the source object is sealed such that no keys may be added nor removed.

parent: DataModel

An immutable reverse-reference to a parent DataModel to which this model belongs.

_detectionFilter: any

An optional filter to apply on the target when it is detected with this mode.

LOCALIZATION_PREFIXES: string[] = []

A set of localization prefix paths which are used by this DataModel.

Accessors

  • get schema(): SchemaField
  • Define the data schema for this document instance.

    Returns SchemaField

  • get invalid(): boolean
  • Is the current state of this DataModel invalid? The model is invalid if there is any unresolved failure.

    Returns boolean

  • get schema(): SchemaField
  • The Data Schema for all instances of this DataModel.

    Returns SchemaField

Methods

  • Parameters

    • visionSource: any
    • target: any

    Returns boolean

  • Test visibility of a target object or array of points for a specific vision source.

    Parameters

    • visionSource: VisionSource

      The vision source being tested

    • mode: TokenDetectionMode

      The detection mode configuration

    • config: CanvasVisibilityTestConfig = {}

      The visibility test configuration

    Returns boolean

    Is the test target visible?

  • Reset the state of this data instance back to mirror the contained source data, erasing any changes.

    Returns void

  • Clone a model, creating a new data model by combining current data with provided overrides.

    Parameters

    • Optional data: any = {}

      Additional data which overrides current document data at the time of creation

    • Optional context: any = {}

      Context options passed to the data model constructor

    Returns Document | Promise<Document>

    The cloned Document instance

  • Validate the data contained in the document to check for type and content This function throws an error if data within the document is not valid

    Parameters

    • options: {
          changes: any;
          clean: boolean;
          fallback: boolean;
          dropInvalidEmbedded: boolean;
          strict: boolean;
          fields: boolean;
          joint: boolean;
      } = {}

      Optional parameters which customize how validation occurs.

      • changes: any

        A specific set of proposed changes to validate, rather than the full source data of the model.

      • clean: boolean

        If changes are provided, attempt to clean the changes before validating them?

      • fallback: boolean

        Allow replacement of invalid values with valid defaults?

      • dropInvalidEmbedded: boolean

        If true, invalid embedded documents will emit a warning and be placed in the invalidDocuments collection rather than causing the parent to be considered invalid.

      • strict: boolean

        Throw if an invalid value is encountered, otherwise log a warning?

      • fields: boolean

        Perform validation on individual fields?

      • joint: boolean

        Perform joint validation on the full data model? Joint validation will be performed by default if no changes are passed. Joint validation will be disabled by default if changes are passed. Joint validation can be performed on a complete set of changes (for example testing a complete data model) by explicitly passing true.

    Returns boolean

    An indicator for whether the document contains valid data

  • Update the DataModel locally by applying an object of changes to its source data. The provided changes are cleaned, validated, and stored to the source data object for this model. The source data is then re-initialized to apply those changes to the prepared data. The method returns an object of differential changes which modified the original data.

    Parameters

    • changes: any = {}

      New values which should be applied to the data model

    • Optional options: any = {}

      Options which determine how the new data is merged

    Returns any

    An object containing the changed keys and values

  • Copy and transform the DataModel into a plain object. Draw the values of the extracted object from the data source (by default) otherwise from its transformed values.

    Parameters

    • Optional source: boolean = true

      Draw values from the underlying data source rather than transformed values

    Returns any

    The extracted primitive object

  • Extract the source data for the DataModel into a simple object format that can be serialized.

    Returns any

    The document source data expressed as a plain object

  • Protected

    Evaluate a single test point to confirm whether it is visible. Standard detection rules require that the test point be both within LOS and within range.

    Parameters

    • visionSource: VisionSource

      The vision source being tested

    • mode: TokenDetectionMode

      The detection mode configuration

    • target: PlaceableObject

      The target object being tested

    • test: CanvasVisibilityTest

      The test case being evaluated

    Returns boolean

  • Protected

    Test whether the line-of-sight requirement for detection is satisfied. Always true if the detection mode bypasses walls, otherwise the test point must be contained by the LOS polygon. The result of is cached for the vision source so that later checks for other detection modes do not repeat it.

    Parameters

    • visionSource: VisionSource

      The vision source being tested

    • mode: TokenDetectionMode

      The detection mode configuration

    • target: PlaceableObject

      The target object being tested

    • test: CanvasVisibilityTest

      The test case being evaluated

    Returns boolean

    Is the LOS requirement satisfied for this test?

  • Protected

    Test whether the target is within the vision angle.

    Parameters

    • visionSource: VisionSource

      The vision source being tested

    • mode: TokenDetectionMode

      The detection mode configuration

    • target: PlaceableObject

      The target object being tested

    • test: CanvasVisibilityTest

      The test case being evaluated

    Returns boolean

    Is the point within the vision angle?

  • Protected

    Verify that a target is in range of a source.

    Parameters

    • visionSource: VisionSource

      The vision source being tested

    • mode: TokenDetectionMode

      The detection mode configuration

    • target: PlaceableObject

      The target object being tested

    • test: CanvasVisibilityTest

      The test case being evaluated

    Returns boolean

    Is the target within range?

  • Protected

    Configure the data model instance before validation and initialization workflows are performed.

    Parameters

    • options: {} = {}

      Returns void

    • Protected

      Initialize the source data for a new DataModel instance. One-time migrations and initial cleaning operations are applied to the source data.

      Parameters

      • data: any

        The candidate source data from which the model will be constructed

      • Optional options: any = {}

        Options provided to the model constructor

      Returns any

      Migrated and cleaned source data which will be stored to the model instance

    • Protected

      Initialize the instance by copying data from the source object to instance attributes. This mirrors the workflow of SchemaField#initialize but with some added functionality.

      Parameters

      • Optional options: any = {}

        Options provided to the model constructor

      Returns void

    • Clean a data source object to conform to a specific provided schema.

      Parameters

      • Optional source: any = {}

        The source data object

      • Optional options: any = {}

        Additional options which are passed to field cleaning methods

      Returns any

      The cleaned source data

    • Evaluate joint validation rules which apply validation conditions across multiple fields of the model. Field-specific validation rules should be defined as part of the DataSchema for the model. This method allows for testing aggregate rules which impose requirements on the overall model.

      Parameters

      • data: any

        Candidate data for the model

      Returns any

      Throws

      An error if a validation failure is detected

    • Create a new instance of this DataModel from a source record. The source is presumed to be trustworthy and is not strictly validated.

      Parameters

      • source: any

        Initial document data which comes from a trusted source.

      • Optional context: any = {}

        Model construction context

      Returns DataModel

    • Create a DataModel instance using a provided serialized JSON string.

      Parameters

      • json: string

        Serialized document data in string format

      Returns DataModel

      A constructed data model instance

    • Migrate candidate source data for this DataModel which may require initial cleaning or transformations.

      Parameters

      • source: any

        The candidate source data from which the model will be constructed

      Returns any

      Migrated source data, if necessary

    • Wrap data migration in a try/catch which attempts it safely

      Parameters

      • source: any

        The candidate source data from which the model will be constructed

      Returns any

      Migrated source data, if necessary

    • Take data which conforms to the current data schema and add backwards-compatible accessors to it in order to support older code which uses this data.

      Parameters

      • data: any

        Data which matches the current schema

      • Optional options: {
            embedded: boolean;
        } = {}

        Additional shimming options

        • embedded: boolean

          Apply shims to embedded models?

      Returns any

      Data with added backwards-compatible properties

    • Protected

      A generator that orders the DataFields in the DataSchema into an expected initialization order.

      Returns Generator<[string, DataField], any, any>