一个新的自定义工具#
此示例展示了一个自定义的 GestureTool 子类,它可以通过拖动鼠标(或触摸设备上的手指)在绘图画布上进行素描。
from bokeh.core.properties import Instance
from bokeh.models import ColumnDataSource, Tool
from bokeh.plotting import figure, show
from bokeh.util.compiler import TypeScript
CODE = """
import {GestureTool, GestureToolView} from "models/tools/gestures/gesture_tool"
import {ColumnDataSource} from "models/sources/column_data_source"
import {PanEvent} from "core/ui_events"
import * as p from "core/properties"
export class DrawToolView extends GestureToolView {
declare model: DrawTool
// this is executed when the pan/drag event starts
_pan_start(_e: PanEvent): void {
this.model.source.data = {x: [], y: []}
}
// this is executed on subsequent mouse/touch moves
_pan(e: PanEvent): void {
const {frame} = this.plot_view
const {sx, sy} = e
if (!frame.bbox.contains(sx, sy))
return
const x = frame.x_scale.invert(sx)
const y = frame.y_scale.invert(sy)
const {source} = this.model
source.get_array("x").push(x)
source.get_array("y").push(y)
source.change.emit()
}
// this is executed then the pan/drag ends
_pan_end(_e: PanEvent): void {}
}
export namespace DrawTool {
export type Attrs = p.AttrsOf<Props>
export type Props = GestureTool.Props & {
source: p.Property<ColumnDataSource>
}
}
export interface DrawTool extends DrawTool.Attrs {}
export class DrawTool extends GestureTool {
declare properties: DrawTool.Props
declare __view_type__: DrawToolView
constructor(attrs?: Partial<DrawTool.Attrs>) {
super(attrs)
}
tool_name = "Draw Tool"
tool_icon = "bk-tool-icon-lasso-select"
event_type = "pan" as "pan"
default_order = 12
static {
this.prototype.default_view = DrawToolView
this.define<DrawTool.Props>(({Ref}) => ({
source: [ Ref(ColumnDataSource) ],
}))
}
}
"""
class DrawTool(Tool):
__implementation__ = TypeScript(CODE)
source = Instance(ColumnDataSource)
source = ColumnDataSource(data=dict(x=[], y=[]))
plot = figure(x_range=(0,10), y_range=(0,10), title="Click and drag to draw",
background_fill_color="#efefef", tools="")
plot.add_tools(DrawTool(source=source))
plot.line('x', 'y', line_width=3, source=source)
show(plot)