作为概念验证的演示，我创建了一个由四个OHLC蜡烛图组成的Bokeh图。 我想扩展演示，使得当前蜡烛图可以动起来并根据其OHLC数据的变化更新。 重要的一点是只应更新最终蜡烛图的组件（雕刻？），而不是整个图表。 目的是展示一种计算轻量级且可扩展到具有许多蜡烛图和非常频繁更新“实时”蜡烛图的更大图表的方法。 请问是否有人能够概述或以代码形式演示如何实现此目标？ 谢谢。 Jupyter笔记本Python代码（包括39秒的合成Tick数据，以促进4 x 10秒蜡烛图动画）：
from ipywidgets import interact
import numpy as np
from bokeh.plotting import figure, output_notebook, show
import datetime as dt
import pandas as pd
from math import pi
datum = dt.datetime.now()
time_delta = dt.timedelta(seconds=1)
tick_data = [(datum + (time_delta*1), 20),
(datum + (time_delta*2), 19.67603177022472),
(datum + (time_delta*3), 20.431878609290592),
(datum + (time_delta*4), 20.20576131687243),
(datum + (time_delta*5), 20.715609070433032),
(datum + (time_delta*6), 20.722416975732024),
(datum + (time_delta*7), 20.722027468712426),
(datum + (time_delta*8), 20.728022489796615),
(datum + (time_delta*9), 20.70996968619282),
(datum + (time_delta*10), 20.70096021947874),
(datum + (time_delta*11), 20.729546647699372),
(datum + (time_delta*12), 20.759081440837274),
(datum + (time_delta*13), 20.823807346441097),
(datum + (time_delta*14), 20.610018797947472),
(datum + (time_delta*15), 20.591932124168064),
(datum + (time_delta*16), 20.584175853951805),
(datum + (time_delta*17), 20.563650527527987),
(datum + (time_delta*18), 20.617504106758794),
(datum + (time_delta*19), 20.42010872326373),
(datum + (time_delta*20), 20.391860996799267),
(datum + (time_delta*21), 20.3913190739894),
(datum + (time_delta*22), 20.34308794391099),
(datum + (time_delta*23), 20.2225778590662),
(datum + (time_delta*24), 20.47050754458162),
(datum + (time_delta*25), 20.83193618858914),
(datum + (time_delta*26), 20.80978509373571),
(datum + (time_delta*27), 20.80917543057461),
(datum + (time_delta*28), 20.859506511541262),
(datum + (time_delta*29), 20.596402987349492),
(datum + (time_delta*30), 20.644024454266795),
(datum + (time_delta*31), 20.58183881183424),
(datum + (time_delta*32), 20.59023861538722),
(datum + (time_delta*33), 20.454961133973477),
(datum + (time_delta*34), 20.495334383308776),
(datum + (time_delta*35), 20.483818523599044),
(datum + (time_delta*36), 20.593964334705078),
(datum + (time_delta*37), 20.91518908025538),
(datum + (time_delta*38), 20.87942217480398),
(datum + (time_delta*39), 20.772392419854697)]
#Prepare to convert fractal tick data into candlesticks
candle_delta = dt.timedelta(seconds=10)
candle_close_time = datum + candle_delta
candle_data = []
#Initialise
op, hi, lo, cl = 0, 0, 0, 0
#Convert ticks to candlesticks
for (dtval, val) in tick_data:
if candle_close_time < dtval:
#store the completed candle
candle_data.append((candle_close_time, op, hi, lo, cl))
#increment to the next candle
candle_close_time += candle_delta
#Reset
op, hi, lo, cl = 0, 0, 0, 0
if dtval <= candle_close_time and op==0:
#set initial values
op, hi, lo, cl = val, val, val, val
elif dtval <= candle_close_time and op!=0:
#update values as appropriate
hi = val if val > hi else hi
lo = val if val < lo else lo
cl = val
#final tick
if dtval == tick_data[-1][0]:
#store the completed candle
candle_data.append((candle_close_time, op, hi, lo, cl))
#print(str(candle_data))
df = pd.DataFrame(candle_data, columns=list('dohlc'))
#For rectangle positioning
mids = (df.o + df.c)/2
#Rectangle height
spans = abs(df.c-df.o)
#Detect up / down candle body
inc = df.c > df.o
dec = df.o > df.c
#Candle width
w = 10 * 500
TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
p = figure(x_axis_type="datetime", tools=TOOLS, plot_width=500, title = "Four Candles")
p.xaxis.major_label_orientation = pi/4
p.grid.grid_line_alpha=0.3
#Wick
p.segment(df.d, df.h, df.d, df.l, color="#000000")
#Up body
p.rect(df.d[inc], mids[inc], w, spans[inc], fill_color="#09ff00", line_color="#09ff00")
#Down body
p.rect(df.d[dec], mids[dec], w, spans[dec], fill_color="#ff0000", line_color="#ff0000")
output_notebook()
show(p)
