# 数据
x = [1, 2, 3, 4, 5]
y = [6, 7, 2, 4, 5]
# 画布：尺寸
p = figure(plot_width=400, plot_height=400)
# 画图
p.scatter(x, y,
size=20, # screen units 显示器像素单位
# radius=1, # data-space units 坐标轴单位
marker="circle", color="navy", alpha=0.5)
# p.circle(x, y, size=20, color="navy", alpha=0.5)
# 显示
show(p) # 数据
N = 4000
x = np.random.random(size=N) * 100 # 随机点x坐标
y = np.random.random(size=N) * 100 # 随机点y坐标
radii = np.random.random(size=N) * 1.5 # 随机半径
# 工具条
TOOLS="hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,save,box_select,poly_select,lasso_select"
# RGB颜色，画布1，绘图1
colors2 = ["#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30
+2*y)]
p1 = figure(width=300, height=300, tools=TOOLS)
p1.scatter(x,y, radius=radii, fill_color=colors2, fill_alpha=0.6, line_color=None)
# RGB颜色，画布2，绘图2
colors2 = ["#%02x%02x%02x" % (150, int(g), int(b)) for g, b in zip(50+2*x, 30+2*y)]
p2 = figure(width=300, height=300, tools=TOOLS)
p2.scatter(x,y, radius=radii, fill_color=colors2, fill_alpha=0.6, line_color=None)
# 直接显示
# show(p1)
# show(p2)
# 网格显示
from bokeh.layouts import gridplot
grid = gridplot([[p1, p2]])
show(grid)
from bokeh.layouts
import column, gridplot
from bokeh.models import BoxSelectTool, Div
# 数据
x = np.linspace(0, 4*np.pi, 100)
y = np.sin(x)
# 工具条
TOOLS = "wheel_zoom,save,box_select,lasso_select,reset"
# HTML代码
div = Div(text="""
Bokeh中的画布可通过多种布局方式进行显示；
通过配置参数BoxSelectTool，在图中用鼠标选择数据，采用不同方式进行交互。
""") # HTML代码直接作为一个图层显示，也可以作为整个HTML文档
# 视图属性
opts = dict(tools=TOOLS, plot_width=350, plot_height=350)
# 绘图1
p1 = figure(title="selection on mouseup", **opts)
p1.circle(x, y, color="navy", size=6, alpha=0.6)
# 绘图2
p2 = figure(title="selection on mousemove", **opts)
p2.square(x, y, color="olive", size=6, alpha=0.6)
p2.select_one(BoxSelectTool).select_every_mousemove = True
# 绘图3
p3 = figure(title="default highlight", **opts)
p3.circle(x, y, color="firebrick", alpha=0.5
, size=6)
# 绘图4
p4 = figure(title="custom highlight", **opts)
p4.square(x, y, color="navy", size=6, alpha=0.6,
nonselection_color="orange", nonselection_alpha=0.6)
# 布局
layout = column(div,
gridplot([[p1, p2], [p3, p4]], toolbar_location="right"),
sizing_mode="scale_width") # sizing_mode 根据窗口宽度缩放图像
# 绘图
show(layout)
from bokeh.models import (
ColumnDataSource,
Range1d, DataRange1d,
LinearAxis, SingleIntervalTicker, FixedTicker,
Label, Arrow, NormalHead,
HoverTool, TapTool, CustomJS)
from bokeh.sampledata.sprint import sprint
abbrev_to_country = {
"USA": "United States",
"GBR": "Britain",
"JAM": "Jamaica",
"CAN": "Canada",
"TRI": "Trinidad and Tobago",
"AUS": "Australia",
"GER": "Germany",
"CUB": "Cuba",
"NAM": "Namibia",
"URS": "Soviet Union",
"BAR": "Barbados",
"BUL": "Bulgaria",
"HUN": "Hungary",
"NED": "Netherlands",
"NZL": "New Zealand",
"PAN": "Panama",
"POR": "Portugal",
"RSA": "South Africa",
"EUA": "United Team of Germany",
}
gold_fill = "#efcf6d"
gold_line = "#c8a850"
silver_fill = "#cccccc"
silver_line = "#b0b0b1"
bronze_fill = "#c59e8a"
bronze_line = "#98715d"
fill_color = { "gold": gold_fill, "silver": silver_fill, "bronze": bronze_fill }
line_color = { "gold": gold_line, "silver": silver_line, "bronze": bronze_line }
def selected_name(name, medal, year):
return name if medal == "gold" and year in [1988, 1968, 1936, 1896] else ""
t0 = sprint.Time[0]
sprint["Abbrev"] = sprint.Country
sprint["Country"] = sprint.Abbrev.map(lambda abbr: abbrev_to_country[abbr])
sprint["Medal"
] = sprint.Medal.map(lambda medal: medal.lower())
sprint["Speed"] = 100.0/sprint.Time
sprint["MetersBack"] = 100.0*(1.0 - t0/sprint.Time)
sprint["MedalFill"] = sprint.Medal.map(lambda medal: fill_color[medal])
sprint["MedalLine"] = sprint.Medal.map(lambda medal: line_color[medal])
sprint["SelectedName"] = sprint[["Name", "Medal", "Year"]].apply(tuple, axis=1).map(lambda args: selected_name(*args))
source = ColumnDataSource(sprint)
xdr = Range1d(start=sprint.MetersBack.max()+2, end=0) # XXX: +2 is poor-man's padding (otherwise misses last tick)
ydr = DataRange1d(range_padding=4, range_padding_units="absolute")
plot = figure(
x_range=xdr, y_range=ydr,
plot_width=1000, plot_height=600,
toolbar_location=None,
outline_line_color=None, y_axis_type=None)
plot.title.text = "Usain Bolt vs. 116 years of Olympic sprinters"
plot.title.text_font_size = "14pt"
plot.xaxis.ticker = SingleIntervalTicker(interval=5, num_minor_ticks=0)
plot.xaxis.axis_line_color = None
plot.xaxis.major_tick_line_color = None
plot.xgrid.grid_line_dash = "dashed"
yticker = FixedTicker(ticks=[1900, 1912, 1924, 1936, 1952, 1964, 1976, 1988, 2000, 2012])
yaxis = LinearAxis(ticker=yticker, major_tick_in=-5, major_tick_out=10)
plot.add_layout(yaxis, "right")
medal = plot.circle(x="MetersBack", y="Year", radius=dict(value=5, units="screen"),
fill_color="MedalFill", line_color="MedalLine", fill_alpha=0.5, source=source, level="overlay")
plot.text(x="MetersBack", y="Year", x_offset=10, y_offset=-5, text="SelectedName",
text_align="left", text_baseline="middle", text_font_size="9pt", source=source)
no_olympics_label = Label(
x=7.5, y=1942,
text="No Olympics in 1940 or 1944",
text_align="center", text_baseline="middle",
text_font_size="9pt", text_font_style="italic", text_color="silver")
no_olympics = plot.add_layout(no_olympics_label)
x = sprint[sprint.Year == 1900].MetersBack.min() - 0.5
arrow = Arrow(x_start=x, x_end=5, y_start=1900, y_end=1900, start=NormalHead(fill_color="black", size=6), end=None, line_width=1.5)
plot.add_layout(arrow)
meters_back = Label(
x=5, x_offset=10, y=1900,
text="Meters behind 2012 Bolt",
text_align="left", text_baseline="middle",
text_font_size="10pt", text_font_style="bold")
plot.add_layout(meters_back)
disclaimer = Label(
x=0, y=0, x_units="screen", y_units="screen",
text="This chart includes medals for the United States and Australia in the \"Intermediary\" Games of 1906, which the I.O.C. does not formally recognize.",
text_font_size="8pt", text_color="silver")
plot.add_layout(disclaimer, "below")
tooltips = """
@Name
(@Abbrev)
@Time{0.00}
@Year
@{MetersBack}{0.00} meters behind
"""
plot.add_tools(HoverTool(tooltips=tooltips, renderers=[medal]))
open_url = CustomJS(args=dict(source=source), code="""
source.inspected._1d.indices.forEach(function(index) {
var name = source.data["Name"][index];
var url = "http://en.wikipedia.org/wiki/" + encodeURIComponent(name);
window.open(url);
});
""")
plot.add_tools(TapTool(callback=open_url, renderers=[medal], behavior="inspect"))
show(plot)
