from bokeh.io import output_notebook, show
from bokeh.plotting import figure
output_notebook()
前面展示了一個畫布上展示多張圖。
其實這些圖片也可以有聯動關系假褪。
展示相同位置
from bokeh.layouts import gridplot
x = list(range(11))
y0, y1, y2 = x, [10-i for i in x], [abs(i-5) for i in x]
plot_options = dict(width=250, plot_height=250, tools='pan,wheel_zoom')
# create a new plot
s1 = figure(**plot_options)
s1.circle(x, y0, size=10, color="navy")
# create a new plot and share both ranges
s2 = figure(x_range=s1.x_range, y_range=s1.y_range, **plot_options)
s2.triangle(x, y1, size=10, color="firebrick")
# create a new plot and share only one range
s3 = figure(x_range=s1.x_range, **plot_options)
s3.square(x, y2, size=10, color="olive")
p = gridplot([[s1, s2, s3]])
# show the results
show(p)
link.PNG
如上代碼署咽， 它們的關聯關系為wheel_zoom， 這意味著其中幾張圖片擁有相同的坐標定位生音， 拉動其中一張圖宁否， 觀察它的上下左右不同方向時， 其他幾張圖也會跟著改變左邊的展示位置缀遍。
選擇相同區(qū)域
from bokeh.models import ColumnDataSource
x = list(range(-20, 21))
y0, y1 = [abs(xx) for xx in x], [xx**2 for xx in x]
# create a column data source for the plots to share
source = ColumnDataSource(data=dict(x=x, y0=y0, y1=y1))
TOOLS = "box_select,lasso_select,help"
# create a new plot and add a renderer
left = figure(tools=TOOLS, width=300, height=300)
left.circle('x', 'y0', source=source)
# create another new plot and add a renderer
right = figure(tools=TOOLS, width=300, height=300)
right.circle('x', 'y1', source=source)
p = gridplot([[left, right]])
show(p)
linked_1.PNG
上面樣例就是在多個圖中選擇相同區(qū)域的標記慕匠。
鼠標懸停展示更多信息
from bokeh.models import HoverTool
source = ColumnDataSource(
data=dict(
x=[1, 2, 3, 4, 5],
y=[2, 5, 8, 2, 7],
desc=['A', 'b', 'C', 'd', 'E'],
)
)
hover = HoverTool(
tooltips=[
("index", "$index"),
("(x,y)", "($x, $y)"),
("desc", "@desc"),
]
)
p = figure(plot_width=300, plot_height=300, tools=[hover], title="Mouse over the dots")
p.circle('x', 'y', size=20, source=source)
show(p)
hover_tools.PNG
了解更多信息，點擊這里
小工具
from bokeh.models.widgets import Slider
slider = Slider(start=0, end=10, value=1, step=.1, title="foo")
show(slider)
Bokeh支持直接加入小工具域醇， 了解更多台谊， 點擊這里
CustomJS 回調
為了讓小工具更有用， 我們需要讓它能執(zhí)行某些真是的動作譬挚。
下面舉例看看CustomJS如何通過JavaSript編碼實現行為的相應锅铅。
from bokeh.models import TapTool, CustomJS, ColumnDataSource
callback = CustomJS(code="alert('you tapped a circle!')")
tap = TapTool(callback=callback)
p = figure(plot_width=600, plot_height=300, tools=[tap])
p.circle(x=[1, 2, 3, 4, 5], y=[2, 5, 8, 2, 7], size=20)
show(p)
widgets_js.PNG
如上代碼可以實現點擊某個標記符號時， 將會出現彈窗信息减宣， 并選中該標記點盐须。
控制條的樣例
from bokeh.layouts import column
from bokeh.models import CustomJS, ColumnDataSource, Slider
x = [x*0.005 for x in range(0, 201)]
source = ColumnDataSource(data=dict(x=x, y=x))
plot = figure(plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
slider = Slider(start=0.1, end=6, value=1, step=.1, title="power")
update_curve = CustomJS(args=dict(source=source, slider=slider), code="""
var data = source.data;
var f = slider.value;
var x = data['x']
var y = data['y']
for (var i = 0; i < x.length; i++) {
y[i] = Math.pow(x[i], f)
}
// necessary becasue we mutated source.data in-place
source.change.emit();
""")
slider.js_on_change('value', update_curve)
show(column(slider, plot))
SliderWidget.PNG
通過拉動上面的控制條， 可以改變圖片中線條的曲線漆腌。
數據選擇樣例
from random import random
x = [random() for x in range(500)]
y = [random() for y in range(500)]
color = ["navy"] * len(x)
s1 = ColumnDataSource(data=dict(x=x, y=y, color=color))
p = figure(plot_width=400, plot_height=400, tools="lasso_select", title="Select Here")
p.circle('x', 'y', color='color', size=8, alpha=0.4, source=s1,
selection_color="firebrick", selection_alpha=0.4)
s2 = ColumnDataSource(data=dict(xm=[0,1],ym=[0.5, 0.5]))
p.line(x='xm', y='ym', color="orange", line_width=5, alpha=0.6, source=s2)
callback = CustomJS(args=dict(s1=s1, s2=s2), code="""
var inds = s1.selected.indices;
if (inds.length == 0)
return;
var ym = 0
for (var i = 0; i < inds.length; i++) {
ym += s1.data.y[inds[i]]
}
ym /= inds.length
s2.data.ym = [ym, ym]
// necessary becasue we mutated source.data in-place
s2.change.emit();
""")
s1.selected.js_on_change('indices', callback)
show(p)
DataSelection.PNG
CustomJS for UI Events
更多詳細的UI Events 點擊bokeh.events
from bokeh.plotting import figure
from bokeh import events
from bokeh.models import CustomJS, Div, Button
from bokeh.layouts import column, row
import numpy as np
x = np.random.random(size=2000) * 100
y = np.random.random(size=2000) * 100
p = figure(tools="box_select")
p.scatter(x, y, radius=1, fill_alpha=0.6, line_color=None)
div = Div(width=400)
button = Button(label="Button", width=300)
layout = column(button, row(p, div))
# Events with no attributes
button.js_on_event(events.ButtonClick, CustomJS(args=dict(div=div), code="""
div.text = "Button!";
"""))
p.js_on_event(events.SelectionGeometry, CustomJS(args=dict(div=div), code="""
div.text = "Selection! <p> <p>" + JSON.stringify(cb_obj.geometry, undefined, 2);
"""))
show(layout)
更多信息
其實有很多interactions和events可以與CustomJS的回調相連接贼邓。
- Widgets - Button, Toggle, Dropdown, TextInput, AutocompleteInput, Select, Multiselect, Slider, (DateRangeSlider), DatePicker,
- Tools - TapTool, BoxSelectTool, HoverTool,
- Selection - ColumnDataSource, AjaxDataSource, BlazeDataSource, ServerDataSource
- Ranges - Range1d, DataRange1d, FactorRange
更多詳細信息請見 JavaScript Interactions
