Bitbybit Docs
    Preparing search index...

    Class GoodCoffeeTableDto (Things.Furniture.Tables.GoodCoffeeTable)

    The parameter set for the Good Coffee Table, a low table with a shelf. Generic in its value types so the same list can be expressed for a plain script, where every value is a number, and for a driven model, where a value can be an expression or a bound input. Concrete DTOs fill those type parameters in; read this class for what the model is actually shaped by.

    Implements

    Index

    Constructors

    • Parameters

      • Optionalheight: number
      • Optionalwidth: number
      • Optionallength: number
      • Optionalchamfer: number
      • OptionaltopThickness: number
      • OptionaltopGlassOffset: number
      • OptionalglassThickness: number
      • OptionalglassHolderLength: number
      • OptionalshelfTopOffset: number
      • OptionalshelfThickness: number
      • OptionallegWidth: number
      • OptionallegDepth: number
      • Optionalprecision: number
      • OptionaldrawEdges: boolean
      • Optionalrotation: number
      • Optionalscale: number
      • Optionalorigin: Point3
      • Optionaldirection: Vector3

      Returns GoodCoffeeTableDto

    Properties

    height: number

    桌子的高度

    0.4
    

    0.1

    Infinity

    0.01

    width: number

    桌子的宽度

    1
    

    0

    Infinity

    0.1

    length: number

    桌子的长度

    1.2
    

    0

    Infinity

    0.1

    chamfer: number

    对角进行倒角

    0.01
    

    0

    Infinity

    0.001

    topThickness: number

    桌子的桌面厚度

    0.05
    

    0.001

    Infinity

    0.001

    topGlassOffset: number

    桌面从桌子边缘到玻璃的偏移

    0.2
    

    0

    Infinity

    0.01

    glassThickness: number

    桌子的玻璃厚度

    0.005
    

    0.001

    Infinity

    0.001

    glassHolderLength: number

    桌子的玻璃托长度

    0.02
    

    0.001

    Infinity

    0.001

    shelfTopOffset: number

    搁板相对桌面底部的偏移 - 0 表示不制作搁板,因为这样的搁板没有用处。

    0.15
    

    0

    Infinity

    0.01

    shelfThickness: number

    搁板厚度

    0.03
    

    0.001

    Infinity

    0.001

    legWidth: number

    桌腿的宽度

    0.1
    

    0.01

    Infinity

    0.01

    legDepth: number

    桌腿的深度

    0.05
    

    0.01

    Infinity

    0.01

    precision: number

    所绘制模型的网格化精度。数值越小,绘制的模型越精确。请注意,该算法的输出还包含纯 occt 形状,可以在 draw any async 命令中单独网格化

    0.001
    

    0.000001

    5

    0.001

    drawEdges: boolean

    定义是否应绘制模型的边

    true
    
    rotation: number

    桌子的旋转,以度为单位

    0
    

    0

    Infinity

    10

    scale: number

    桌子的缩放

    1
    

    0

    Infinity

    origin: Point3

    奖牌的原点

    [0, 0, 0]
    
    direction: Vector3

    模型的方向

    [0, 1, 0]