二十、将子图应用于我们的图表

在这个 Matplotlib 教程中，我们将处理我们以前教程的代码，并实现上一个教程中的子图配置。 我们的起始代码是这样：

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
from matplotlib.finance import candlestick_ohlc
from matplotlib import style
import numpy as np
import urllib
import datetime as dt
style.use('fivethirtyeight')
print(plt.style.available)
print(plt.__file__)
def bytespdate2num(fmt, encoding='utf-8'):
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter
def graph_data(stock):
    fig = plt.figure()
    ax1 = plt.subplot2grid((1,1), (0,0))
    stock_price_url = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+stock+'/chartdata;type=quote;range=1m/csv'
    source_code = urllib.request.urlopen(stock_price_url).read().decode()
    stock_data = []
    split_source = source_code.split('\n')
    for line in split_source:
        split_line = line.split(',')
        if len(split_line) == 6:
            if 'values' not in line and 'labels' not in line:
                stock_data.append(line)
    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
                                                          delimiter=',',
                                                          unpack=True,
                                                          converters={0: bytespdate2num('%Y%m%d')})
    x = 0
    y = len(date)
    ohlc = []
    while x < y:
        append_me = date[x], openp[x], highp[x], lowp[x], closep[x], volume[x]
        ohlc.append(append_me)
        x+=1
    candlestick_ohlc(ax1, ohlc, width=0.4, colorup='#77d879', colordown='#db3f3f')
    for label in ax1.xaxis.get_ticklabels():
        label.set_rotation(45)
    ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
    ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
    ax1.grid(True)
    bbox_props = dict(boxstyle='round',fc='w', ec='k',lw=1)
    ax1.annotate(str(closep[-1]), (date[-1], closep[-1]),
                 xytext = (date[-1]+4, closep[-1]), bbox=bbox_props)
##    # Annotation example with arrow
##    ax1.annotate('Bad News!',(date[11],highp[11]),
##                 xytext=(0.8, 0.9), textcoords='axes fraction',
##                 arrowprops = dict(facecolor='grey',color='grey'))
##
##    
##    # Font dict example
##    font_dict = {'family':'serif',
##                 'color':'darkred',
##                 'size':15}
##    # Hard coded text
##    ax1.text(date[10], closep[1],'Text Example', fontdict=font_dict)
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.title(stock)
    #plt.legend()
    plt.subplots_adjust(left=0.11, bottom=0.24, right=0.90, top=0.90, wspace=0.2, hspace=0)
    plt.show()
graph_data('EBAY')

一个主要的改动是修改轴域的定义：

ax1 = plt.subplot2grid((6,1), (0,0), rowspan=1, colspan=1)
plt.title(stock)
ax2 = plt.subplot2grid((6,1), (1,0), rowspan=4, colspan=1)
plt.xlabel('Date')
plt.ylabel('Price')
ax3 = plt.subplot2grid((6,1), (5,0), rowspan=1, colspan=1)

现在，ax2是我们实际上在绘制的股票价格数据。 顶部和底部图表将作为指标信息。

在我们绘制数据的代码中，我们需要将ax1更改为ax2：

candlestick_ohlc(ax2, ohlc, width=0.4, colorup='#77d879', colordown='#db3f3f')
for label in ax2.xaxis.get_ticklabels():
    label.set_rotation(45)
ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax2.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax2.grid(True)
bbox_props = dict(boxstyle='round',fc='w', ec='k',lw=1)
ax2.annotate(str(closep[-1]), (date[-1], closep[-1]),
             xytext = (date[-1]+4, closep[-1]), bbox=bbox_props)

更改之后，代码为：

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
from matplotlib.finance import candlestick_ohlc
from matplotlib import style
import numpy as np
import urllib
import datetime as dt
style.use('fivethirtyeight')
print(plt.style.available)
print(plt.__file__)
def bytespdate2num(fmt, encoding='utf-8'):
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter
def graph_data(stock):
    fig = plt.figure()
    ax1 = plt.subplot2grid((6,1), (0,0), rowspan=1, colspan=1)
    plt.title(stock)
    ax2 = plt.subplot2grid((6,1), (1,0), rowspan=4, colspan=1)
    plt.xlabel('Date')
    plt.ylabel('Price')
    ax3 = plt.subplot2grid((6,1), (5,0), rowspan=1, colspan=1)
    stock_price_url = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+stock+'/chartdata;type=quote;range=1m/csv'
    source_code = urllib.request.urlopen(stock_price_url).read().decode()
    stock_data = []
    split_source = source_code.split('\n')
    for line in split_source:
        split_line = line.split(',')
        if len(split_line) == 6:
            if 'values' not in line and 'labels' not in line:
                stock_data.append(line)
    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
                                                          delimiter=',',
                                                          unpack=True,
                                                          converters={0: bytespdate2num('%Y%m%d')})
    x = 0
    y = len(date)
    ohlc = []
    while x < y:
        append_me = date[x], openp[x], highp[x], lowp[x], closep[x], volume[x]
        ohlc.append(append_me)
        x+=1
    candlestick_ohlc(ax2, ohlc, width=0.4, colorup='#77d879', colordown='#db3f3f')
    for label in ax2.xaxis.get_ticklabels():
        label.set_rotation(45)
    ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
    ax2.xaxis.set_major_locator(mticker.MaxNLocator(10))
    ax2.grid(True)
    bbox_props = dict(boxstyle='round',fc='w', ec='k',lw=1)
    ax2.annotate(str(closep[-1]), (date[-1], closep[-1]),
                 xytext = (date[-1]+4, closep[-1]), bbox=bbox_props)
##    # Annotation example with arrow
##    ax1.annotate('Bad News!',(date[11],highp[11]),
##                 xytext=(0.8, 0.9), textcoords='axes fraction',
##                 arrowprops = dict(facecolor='grey',color='grey'))
##
##    
##    # Font dict example
##    font_dict = {'family':'serif',
##                 'color':'darkred',
##                 'size':15}
##    # Hard coded text
##    ax1.text(date[10], closep[1],'Text Example', fontdict=font_dict)
    #
    #plt.legend()
    plt.subplots_adjust(left=0.11, bottom=0.24, right=0.90, top=0.90, wspace=0.2, hspace=0)
    plt.show()
graph_data('EBAY')

结果为：