import numpy as np

from bokeh.core.properties import Instance, String
from bokeh.io import show
from bokeh.models import ColumnDataSource, LayoutDOM
from bokeh.util.compiler import TypeScript

CODE = """
// This custom model wraps one part of the third-party vis.js library:
//     http://visjs.org/index.html
// Making it easy to hook up python data analytics tools (NumPy, SciPy,
// Pandas, etc.) to web presentations using the Bokeh server.

import {LayoutDOM, LayoutDOMView} from "models/layouts/layout_dom"
import {ColumnDataSource} from "models/sources/column_data_source"
import * as p from "core/properties"

declare namespace vis {
  class Graph3d {
    constructor(el: HTMLElement | DocumentFragment, data: object, OPTIONS: object)
    setData(data: vis.DataSet): void

  class DataSet {
    add(data: unknown): void

// This defines some default options for the Graph3d feature of vis.js
// See: http://visjs.org/graph3d_examples.html for more details.
const OPTIONS = {
  width: '600px',
  height: '600px',
  style: 'surface',
  showPerspective: true,
  showGrid: true,
  keepAspectRatio: true,
  verticalRatio: 1.0,
  legendLabel: 'stuff',
  cameraPosition: {
    horizontal: -0.35,
    vertical: 0.22,
    distance: 1.8,
// To create custom model extensions that will render on to the HTML canvas
// or into the DOM, we must create a View subclass for the model.
// In this case we will subclass from the existing BokehJS ``LayoutDOMView``
export class Surface3dView extends LayoutDOMView {
  declare model: Surface3d

  private _graph: vis.Graph3d

  initialize(): void {

    const url = "https://cdnjs.cloudflare.com/ajax/libs/vis/4.16.1/vis.min.js"
    const script = document.createElement("script")
    script.onload = () => this._init()
    script.async = false
    script.src = url

  private _init(): void {
    // Create a new Graph3s using the vis.js API. This assumes the vis.js has
    // already been loaded (e.g. in a custom app template). In the future Bokeh
    // models will be able to specify and load external scripts automatically.
    // BokehJS Views create <div> elements by default, accessible as this.el.
    // Many Bokeh views ignore this default <div>, and instead do things like
    // draw to the HTML canvas. In this case though, we use the <div> to attach
    // a Graph3d to the DOM.
    this._graph = new vis.Graph3d(this.shadow_el, this.get_data(), OPTIONS)

    // Set a listener so that when the Bokeh data source has a change
    // event, we can process the new data
    this.connect(this.model.data_source.change, () => {

  // This is the callback executed when the Bokeh data has an change. Its basic
  // function is to adapt the Bokeh data source to the vis.js DataSet format.
  get_data(): vis.DataSet {
    const data = new vis.DataSet()
    const source = this.model.data_source
    for (let i = 0; i < source.get_length()!; i++) {
        x: source.get(this.model.x)[i],
        y: source.get(this.model.y)[i],
        z: source.get(this.model.z)[i],
    return data

  get child_models(): LayoutDOM[] {
    return []

// We must also create a corresponding JavaScript BokehJS model subclass to
// correspond to the python Bokeh model subclass. In this case, since we want
// an element that can position itself in the DOM according to a Bokeh layout,
// we subclass from ``LayoutDOM``
export namespace Surface3d {
  export type Attrs = p.AttrsOf<Props>

  export type Props = LayoutDOM.Props & {
    x: p.Property<string>
    y: p.Property<string>
    z: p.Property<string>
    data_source: p.Property<ColumnDataSource>

export interface Surface3d extends Surface3d.Attrs {}

export class Surface3d extends LayoutDOM {
  declare properties: Surface3d.Props
  declare __view_type__: Surface3dView

  constructor(attrs?: Partial<Surface3d.Attrs>) {

  // The ``__name__`` class attribute should generally match exactly the name
  // of the corresponding Python class. Note that if using TypeScript, this
  // will be automatically filled in during compilation, so except in some
  // special cases, this shouldn't be generally included manually, to avoid
  // typos, which would prohibit serialization/deserialization of this model.
  static __name__ = "Surface3d"

  static {
    // This is usually boilerplate. In some cases there may not be a view.
    this.prototype.default_view = Surface3dView

    // The @define block adds corresponding "properties" to the JS model. These
    // should basically line up 1-1 with the Python model class. Most property
    // types have counterparts, e.g. ``bokeh.core.properties.String`` will be
    // ``String`` in the JS implementatin. Where the JS type system is not yet
    // as rich, you can use ``p.Any`` as a "wildcard" property type.
    this.define<Surface3d.Props>(({Str, Ref}) => ({
      x:            [ Str ],
      y:            [ Str ],
      z:            [ Str ],
      data_source:  [ Ref(ColumnDataSource) ],

# This custom extension model will have a DOM view that should layout-able in
# Bokeh layouts, so use ``LayoutDOM`` as the base class. If you wanted to create
# a custom tool, you could inherit from ``Tool``, or from ``Glyph`` if you
# wanted to create a custom glyph, etc.
class Surface3d(LayoutDOM):

    # The special class attribute ``__implementation__`` should contain a string
    # of JavaScript code that implements the browser side of the extension model.
    __implementation__ = TypeScript(CODE)

    # Below are all the "properties" for this model. Bokeh properties are
    # class attributes that define the fields (and their types) that can be
    # communicated automatically between Python and the browser. Properties
    # also support type validation. More information about properties in
    # can be found here:
    #    https://docs.bokeh.org/en/latest/docs/reference/core/properties.html#bokeh-core-properties

    # This is a Bokeh ColumnDataSource that can be updated in the Bokeh
    # server by Python code
    data_source = Instance(ColumnDataSource)

    # The vis.js library that we are wrapping expects data for x, y, and z.
    # The data will actually be stored in the ColumnDataSource, but these
    # properties let us specify the *name* of the column that should be
    # used for each field.
    x = String()

    y = String()

    z = String()

x = np.arange(0, 300, 10)
y = np.arange(0, 300, 10)
xx, yy = np.meshgrid(x, y)
xx = xx.ravel()
yy = yy.ravel()
value = np.sin(xx / 50) * np.cos(yy / 50) * 50 + 50

source = ColumnDataSource(data=dict(x=xx, y=yy, z=value))

surface = Surface3d(x="x", y="y", z="z", data_source=source, width=600, height=600)