Jacky Liu's Blog
用 Python / Matplotlib 画出来的股票 K线图 (三)
---- 前一篇在这: 用 Python / Matplotlib 画出来的股票 K线图 (二)
---- 后一篇在这: 用 Python / Matplotlib 画出来的股票 K线图 (四)
---- 就像上回说的，新内容加进来。除此之外，与上一版代码相比最大的改动就是内部重构过，子图全部定义成 class。图中一共包含 5 个子图，从上到下依次是: 基本信息（就是那些文字）、历史价格、历史换手率、价格、换手率。通过输入的绘图数据进行控制，任何一个子图都可以关闭，关闭子图可以节省绘图时间和存储空间。本来还有一个财务信息子图要加进去，但是现在想暂时告一段落，先弄点其它的。
---- 作为输入的 Python pickle file 在 这里。
---- 最后是脚本，仍然是 Python 2 的:
# -*- coding: utf-8 -*-
import os
import sys
import pickle
import math
import datetime
import itertools
import matplotlib
matplotlib.use("WXAgg", warn=True) # 这个要紧跟在 import matplotlib 之后，而且必须安装了 wxpython 2.8 才行。
import matplotlib.pyplot as pyplot
import matplotlib.font_manager as font_manager
import numpy
from matplotlib.ticker import NullLocator, FixedLocator, MultipleLocator, FuncFormatter, NullFormatter
from matplotlib.patches import Ellipse
__font_properties__= font_manager.FontProperties(fname='/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc')
__color_lightsalmon__= '#ffa07a'
__color_pink__= '#ffc0cb'
__color_navy__= '#000080'
__color_gold__= '#FDDB05'
__color_gray30__= '0.3'
__color_gray70__= '0.7'
__color_lightblue__= 'lightblue'
__shrink__= 1.0 / 4
__expbase__= 1.1
class SubPlot_BasicInfo:
'''
公司的基本信息
Note: this is not "real" subplot, no Axes object contained.
'''
def __init__(self, pdata, parent, name):
self._name= name
self._pdata= pdata
self._cominfo= self._pdata[u'公司信息']
self._parent= parent
self._Axes= None
self._xsize, \
self._ysize= self._compute_size()
def _compute_size(self):
return (300.0, 1.8)
def get_size(self):
return (self._xsize, self._ysize)
def build_axes(self, figobj, rect):
axes= figobj.add_axes(rect)
axes.set_frame_on(False)
self._Axes= axes
self.set_xticks()
self.set_yticks()
def set_xticks(self):
axes= self._Axes
xaxis= axes.get_xaxis()
# 设定 X 轴坐标的范围
#==================================================================================================================================================
axes.set_xlim(0, self._xsize)
xaxis.set_major_locator(NullLocator())
for mal in axes.get_xticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_xticklabels(minor=True):
mil.set_visible(False)
def set_yticks(self):
axes= self._Axes
yaxis= axes.get_yaxis()
# 设定 X 轴坐标的范围
#==================================================================================================================================================
axes.set_ylim(0, self._ysize)
yaxis.set_major_locator(NullLocator())
for mal in axes.get_yticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_yticklabels(minor=True):
mil.set_visible(False)
def plot(self):
self.plot_codesymbol(xbase=0.0, ybase=self._ysize)
self.plot_codesymbol_2(xbase=self._xsize, ybase=self._ysize)
self.plot_companyname(xbase=0.0, ybase=self._ysize-0.8)
self.plot_companylocation(xbase=48.0, ybase=self._ysize)
self.plot_mainbusiness(xbase=48.0, ybase=self._ysize)
self.plot_description(xbase=90.0, ybase=self._ysize)
self.plot_sortinginfo(xbase=165.0, ybase=self._ysize)
def plot_codesymbol(self, xbase, ybase):
'''
交易代码、公司简称
'''
txtstr= self._cominfo[u'代码'] + u' ' + self._cominfo[u'简称']
label= self._Axes.text(xbase, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left')
label.set_fontsize(16.0)
def plot_codesymbol_2(self, xbase, ybase):
txtstr= self._cominfo[u'简称二']
label= self._Axes.text(xbase, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='right')
label.set_fontsize(16.0)
def plot_companyname(self, xbase, ybase):
'''
曾用名、全名、英文名
'''
txtstr= self._cominfo[u'基本情况'][u'曾用名']
txtlist= txtstr.split('->')
if len(txtlist) > 15:
txtstr= ' -> '.join(txtlist[:5]) + ' ->\n' + ' -> '.join(txtlist[5:10]) + ' ->\n' + ' -> '.join(txtlist[10:15]) + ' ->\n' + ' -> '.join(txtlist[15:]) + '\n'
elif len(txtlist) > 10:
txtstr= ' -> '.join(txtlist[:5]) + ' ->\n' + ' -> '.join(txtlist[5:10]) + ' ->\n' + ' -> '.join(txtlist[10:]) + '\n'
elif len(txtlist) > 5:
txtstr= ' -> '.join(txtlist[:5]) + ' ->\n' + ' -> '.join(txtlist[5:]) + '\n'
else:
txtstr= ' -> '.join(txtlist) + '\n'
txtstr += self._cominfo[u'基本情况'][u'公司名称'] + '\n'
txtstr += self._cominfo[u'基本情况'][u'英文名称']
label= self._Axes.text(xbase, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left')
label.set_fontsize(4.5)
def plot_companylocation(self, xbase, ybase):
'''
地域、所属行业、上市日期
'''
txtstr= self._cominfo[u'公司概况'][u'区域'] + ' ' + self._cominfo[u'公司概况'][u'所属行业'] + ' ' + self._cominfo[u'发行相关'][u'上市日期']
label= self._Axes.text(xbase, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left')
label.set_fontsize(6.5)
def plot_mainbusiness(self, xbase, ybase):
'''
主营业务
'''
# 查找表: (<文字长度>, <每行字数>, <字体大小>, <Y轴偏移量>)
lookups= (
(20, 10, 12.0, 0.5),
(45, 15, 8.2, 0.5),
(80, 20, 6.2, 0.5),
(125, 25, 5.0, 0.5),
(180, 30, 4.1, 0.5),
(245, 35, 3.5, 0.4),
(999999, 37, 3.4, 0.4)
)
txtstr= self._cominfo[u'基本情况'][u'主营业务']
length= len(txtstr)
for sizelimit, linelimit, fontsize, yshift in lookups:
if length <= sizelimit:
txtstr= '\n'.join([txtstr[linelimit*idx : linelimit*(idx+1)] for idx in range(length//linelimit + 1)])
fsize= fontsize
ycoord= ybase - yshift
break
label= self._Axes.text(xbase, ycoord, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left', color='blue')
label.set_fontsize(fsize)
def plot_description(self, xbase, ybase):
'''
公司简介
'''
# 查找表: (<文字长度>, <每行字数>, <字体大小>)
lookups= (
(150, 30, 7.0),
(240, 40, 5.6),
(329, 47, 4.8),
(432, 54, 4.2),
(576, 64, 3.5),
(670, 67, 3.4),
(792, 72, 3.1),
(960, 80, 2.8),
(1222, 94, 2.4),
(1428, 102, 2.26),
(1620, 108, 2.12),
(1938, 114, 2.00),
(999999, 130, 1.75)
)
txtstr= self._cominfo[u'公司概况'][u'公司简介'] # 26 ~ 2600 字符
length= len(txtstr)
for sizelimit, linelimit, fontsize in lookups:
if length <= sizelimit:
txtstr= '\n'.join([txtstr[linelimit*idx : linelimit*(idx+1)] for idx in range(length//linelimit + 1)])
fsize= fontsize
break
label= self._Axes.text(xbase, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left')
label.set_fontsize(fsize)
def plot_sortinginfo(self, xbase, ybase):
'''
行业板块信息
'''
infolist= self._cominfo[u'行业板块']
for idx in range(len(infolist)//10 + 1):
txtstr= '\n'.join(infolist[10*idx : 10*(idx+1)])
if not txtstr:
break
xcoord= xbase + 25.0*idx
label= self._Axes.text(xcoord, ybase, txtstr, fontproperties=__font_properties__, verticalalignment='top', horizontalalignment='left', color='blue')
label.set_fontsize(3.4)
class SubPlot_Financial:
'''
换手率子图
'''
pass
class SubPlot_PriceBase:
'''
'''
def __init__(self, pdata, parent, xparams, name):
'''
'''
self._name= name # 派生类自己设置
self._pdata= pdata
self._parent= parent
self._expbase= __expbase__
self._xparams= xparams
self._shrink= __shrink__ if name == 'pricefs' else 1.0
# 绘图数据
quotes= pdata[u'行情']
if name == 'pricefs':
self._dates= quotes[u'日期']
self._open= quotes[u'开盘']
self._close= quotes[u'收盘']
self._high= quotes[u'最高']
self._low= quotes[u'最低']
if u'简化' in quotes: self._simple= quotes[u'简化']
# if u'换手率' in quotes: self._torate= quotes[u'换手率']
# if u'成交量' in quotes: self._volume= quotes[u'成交量']
# if u'成交额' in quotes: self._turnover= quotes[u'成交额']
if u'3日均' in quotes: self._average3= quotes[u'3日均']
if u'5日均' in quotes: self._average5= quotes[u'5日均']
if u'10日均' in quotes: self._average10= quotes[u'10日均']
if u'30日均' in quotes: self._average30= quotes[u'30日均']
if u'60日均' in quotes: self._average60= quotes[u'60日均']
if u'开盘二' in quotes:
self._open_2= quotes[u'开盘二']
self._close_2= quotes[u'收盘二']
self._high_2= quotes[u'最高二']
self._low_2= quotes[u'最低二']
if u'简化二' in quotes: self._simple_2= quotes[u'简化二']
# if u'换手率二' in quotes: self._torate_2= quotes[u'换手率二']
# if u'成交量二' in quotes: self._volume_2= quotes[u'成交量二']
# if u'成交额二' in quotes: self._turnover_2= quotes[u'成交额二']
if u'3日均二' in quotes: self._average3_2= quotes[u'3日均二']
if u'5日均二' in quotes: self._average5_2= quotes[u'5日均二']
if u'10日均二' in quotes: self._average10_2= quotes[u'10日均二']
if u'30日均二' in quotes: self._average30_2= quotes[u'30日均二']
if u'60日均二' in quotes: self._average60_2= quotes[u'60日均二']
else:
sidx, eidx= pdata[u'任务描述'][u'起始偏移'], pdata[u'任务描述'][u'结束偏移']
self._dates= quotes[u'日期'][sidx:eidx]
self._open= quotes[u'开盘'][sidx:eidx]
self._close= quotes[u'收盘'][sidx:eidx]
self._high= quotes[u'最高'][sidx:eidx]
self._low= quotes[u'最低'][sidx:eidx]
if u'简化' in quotes: self._simple= quotes[u'简化'][sidx:eidx]
# if u'换手率' in quotes: self._torate= quotes[u'换手率'][sidx:eidx]
# if u'成交量' in quotes: self._volume= quotes[u'成交量'][sidx:eidx]
# if u'成交额' in quotes: self._turnover= quotes[u'成交额'][sidx:eidx]
if u'3日均' in quotes: self._average3= quotes[u'3日均'][sidx:eidx]
if u'5日均' in quotes: self._average5= quotes[u'5日均'][sidx:eidx]
if u'10日均' in quotes: self._average10= quotes[u'10日均'][sidx:eidx]
if u'30日均' in quotes: self._average30= quotes[u'30日均'][sidx:eidx]
if u'60日均' in quotes: self._average60= quotes[u'60日均'][sidx:eidx]
if u'开盘二' in quotes:
self._open_2= quotes[u'开盘二'][sidx:eidx]
self._close_2= quotes[u'收盘二'][sidx:eidx]
self._high_2= quotes[u'最高二'][sidx:eidx]
self._low_2= quotes[u'最低二'][sidx:eidx]
if u'简化二' in quotes: self._simple_2= quotes[u'简化二'][sidx:eidx]
# if u'换手率二' in quotes: self._torate_2= quotes[u'换手率二'][sidx:eidx]
# if u'成交量二' in quotes: self._volume_2= quotes[u'成交量二'][sidx:eidx]
# if u'成交额二' in quotes: self._turnover_2= quotes[u'成交额二'][sidx:eidx]
if u'3日均二' in quotes: self._average3_2= quotes[u'3日均二'][sidx:eidx]
if u'5日均二' in quotes: self._average5_2= quotes[u'5日均二'][sidx:eidx]
if u'10日均二' in quotes: self._average10_2= quotes[u'10日均二'][sidx:eidx]
if u'30日均二' in quotes: self._average30_2= quotes[u'30日均二'][sidx:eidx]
if u'60日均二' in quotes: self._average60_2= quotes[u'60日均二'][sidx:eidx]
self._length= len(self._dates) # XXX: 由派生类设定
# 衍生数据
#==============================================================================================================
self._xindex= numpy.arange(self._length) # X 轴上的 index，一个辅助数据
self._zipoc= zip(self._open, self._close)
self._up= numpy.array( [ True if po < pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内上涨的一个序列
self._down= numpy.array( [ True if po > pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内下跌的一个序列
self._side= numpy.array( [ True if po == pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内走平的一个序列
if u'开盘二' in quotes:
self._zipoc_2= zip(self._open_2, self._close_2)
self._up_2= numpy.array( [ True if po < pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内上涨的一个序列
self._down_2= numpy.array( [ True if po > pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内下跌的一个序列
self._side_2= numpy.array( [ True if po == pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内走平的一个序列
self._Axes= None
self._AxisX= None
self._AxisY= None
self._xsize= 0.0
self._ysize= 0.0
self._yhighlim= 0 # Y 轴最大坐标
self._ylowlim= 0 # Y 轴最小坐标
if u'开盘二' in self._pdata[u'行情']:
self._Axes_2= None # 如果有第二个行情数据，就建立另一个 Axes 对象
self._AxisX_2= None
self._AxisY_2= None
self._yhighlim_2= 0 # Y 轴最大坐标
self._ylowlim_2= 0 # Y 轴最小坐标
self._compute_size()
self._ytickset= self._compute_ytickset() # 需放在前一句后面
def _compute_size(self):
'''
根据绘图数据 pdata 计算出本子图的尺寸，修改数据成员
'''
quotes= self._pdata[u'行情']
popen= self._open[0] # int 类型
phigh= max( [ph for ph in self._high if ph is not None] ) # 最高价
plow= min( [pl for pl in self._low if pl is not None] ) # 最低价
# Y 轴范围
if self._name == 'pricefs':
yhighlim= phigh * 1.2 # K线子图 Y 轴最大坐标
ylowlim= plow / 1.2 # K线子图 Y 轴最小坐标
else:
yhighlim= phigh * 1.1 # K线子图 Y 轴最大坐标
ylowlim= plow / 1.1 # K线子图 Y 轴最小坐标
self._yhighlim= yhighlim
self._ylowlim= ylowlim
if u'开盘二' in quotes:
popen_2= self._open_2[0] # 同上
phigh_2= max( [ph for ph in self._high_2 if ph is not None] ) # 第二个行情的最高价
phigh= max(phigh, int(phigh_2 * popen / float(popen_2))) # 以第一个行情为基准修正出的总最高价
plow_2= min( [pl for pl in self._low_2 if pl is not None] ) # 最低价
plow= min(plow, int(plow_2 * popen / float(popen_2))) # 以第一个行情为基准修正出的总最低价
if self._name == 'pricefs':
yhighlim= phigh * 1.2 # K线子图 Y 轴最大坐标
ylowlim= plow / 1.2 # K线子图 Y 轴最小坐标
else:
yhighlim= phigh * 1.1 # K线子图 Y 轴最大坐标
ylowlim= plow / 1.1 # K线子图 Y 轴最小坐标
ylowlim_2= ylowlim * popen_2 / float(popen)
yhighlim_2= yhighlim * popen_2 / float(popen)
self._yhighlim= yhighlim
self._ylowlim= ylowlim
self._yhighlim_2= yhighlim_2
self._ylowlim_2= ylowlim_2
# XXX: 价格在 Y 轴上的 “份数”。注意，虽然最高与最低价是以第一个行情为基准修正出来的，但其中包含的倍数因子对结果无影响，即:
# log(base, num1) - log(base, num2) ==
# log(base, num1/num2) ==
# log(base, k*num1/k*num2) ==
# log(base, k*num1) - log(base, k*num2)
# ，这是对数运算的性质。
xmargin= self._xparams['xmargin']
self._xsize= (self._length + xmargin*2) * self._shrink # int, 所有数据的长度，就是天数
self._ysize= (math.log(yhighlim, self._expbase) - math.log(ylowlim, self._expbase)) * self._shrink # float
def get_size(self):
return (self._xsize, self._ysize)
def get_ylimits(self):
return (self._yhighlim, self._ylowlim)
def build_axes(self, figobj, rect):
'''
初始化 self._Axes 对象
'''
# 添加 Axes 对象
#==================================================================================================================================================
if self._name == 'price' and 'torate' in self._parent._subplots:
sharex= self._parent._subplots['torate'].get_axes()
axes= figobj.add_axes(rect, axis_bgcolor='black', sharex=sharex)
elif self._name == 'pricefs' and 'toratefs' in self._parent._subplots:
sharex= self._parent._subplots['toratefs'].get_axes()
axes= figobj.add_axes(rect, axis_bgcolor='black', sharex=sharex)
else:
axes= figobj.add_axes(rect, axis_bgcolor='black')
axes.set_axisbelow(True) # 网格线放在底层
# axes.set_zorder(1) # XXX: 不顶用
# axes.patch.set_visible(False) # hide the 'canvas'
axes.set_yscale('log', basey=self._expbase) # 使用对数坐标
# 改变坐标线的颜色
#==================================================================================================================================================
for child in axes.get_children():
if isinstance(child, matplotlib.spines.Spine):
child.set_color(__color_gold__)
# 得到 X 轴 和 Y 轴 的两个 Axis 对象
#==================================================================================================================================================
xaxis= axes.get_xaxis()
yaxis= axes.get_yaxis()
# 设置两个坐标轴上的网格线
#==================================================================================================================================================
xaxis.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
xaxis.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
if self._name == 'pricefs': # 如果是小图，就不设辅助网格线
yaxis.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.1)
else:
yaxis.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
yaxis.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
yaxis.set_label_position('left')
self._Axes= axes
self._AxisX= xaxis
self._AxisY= yaxis
if u'开盘二' in self._pdata[u'行情']:
# 添加 Axes 对象。注意，设置 axes_2 而不是 axes 的网格线，从而不会跑到 axes 边框上边的做法不顶用。
#==================================================================================================================================================
axes_2= axes.twinx() # twinx is problematic, no use no more.
# XXX: 下面这三行把第一个 axes 放在上面，这样不会被第二个 axes 的图形遮盖。用 zorder 不顶用。
axes.figure.axes[-2:]= [axes_2, axes] # XXX:
axes.set_frame_on(False) # 如果不做此设定，axes_2 的内容会看不见
axes_2.set_frame_on(True)
axes_2.set_axis_bgcolor('black')
axes_2.set_axisbelow(True) # 网格线放在底层
axes_2.set_yscale('log', basey=self._expbase) # 使用对数坐标
# 改变坐标线的颜色
#==================================================================================================================================================
for child in axes_2.get_children():
if isinstance(child, matplotlib.spines.Spine):
child.set_color(__color_gold__)
# 得到 X 轴 和 Y 轴 的两个 Axis 对象
#==================================================================================================================================================
xaxis_2= axes_2.get_xaxis()
yaxis_2= axes_2.get_yaxis()
# 设置两个坐标轴上的网格线
#==================================================================================================================================================
# xaxis_2.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
# xaxis_2.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
# if self._name == 'pricefs': # 如果是小图，就不设辅助网格线
# yaxis_2.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.1)
# else:
# yaxis_2.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
# yaxis_2.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
yaxis_2.set_label_position('right')
self._Axes_2= axes_2
self._AxisX_2= xaxis_2
self._AxisY_2= yaxis_2
def set_xticks(self):
xMajorLocator= self._xparams['xMajorLocator']
xMinorLocator= self._xparams['xMinorLocator']
axes= self._Axes
xaxis= self._AxisX
# 设定 X 轴坐标的范围
#==================================================================================================================================================
xmargin= self._xparams['xmargin']
axes.set_xlim(-xmargin, self._length + xmargin)
# 先设置 label 位置，再将 X 轴上的坐标设为不可见。因为与 成交量子图 共用 X 轴
#==================================================================================================================================================
# 设定 X 轴的 Locator 和 Formatter
xaxis.set_major_locator(xMajorLocator)
# xaxis.set_major_formatter(xMajorFormatter)
xaxis.set_minor_locator(xMinorLocator)
# xaxis.set_minor_formatter(xMinorFormatter)
# 将 X 轴上的坐标设为不可见。
for mal in axes.get_xticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_xticklabels(minor=True):
mil.set_visible(False)
def set_xticks_2(self):
quotes= self._pdata[u'行情']
axes= self._Axes_2
xaxis= self._AxisX_2
xMajorLocator= self._xparams['xMajorLocator']
xMinorLocator= self._xparams['xMinorLocator']
# 设定 X 轴坐标的范围
#==================================================================================================================================================
xmargin= self._xparams['xmargin']
axes.set_xlim(-xmargin, self._length + xmargin)
# 先设置 label 位置，再将 X 轴上的坐标设为不可见。因为与 成交量子图 共用 X 轴
#==================================================================================================================================================
# 设定 X 轴的 Locator 和 Formatter
xaxis.set_major_locator(xMajorLocator)
# xaxis.set_major_formatter(xMajorFormatter)
xaxis.set_minor_locator(xMinorLocator)
# xaxis.set_minor_formatter(xMinorFormatter)
# 将 X 轴上的坐标设为不可见。
for mal in axes.get_xticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_xticklabels(minor=True):
mil.set_visible(False)
def _compute_ytickset(self):
'''
计算 Y 轴坐标点的位置，包括第二个行情
'''
quotes= self._pdata[u'行情']
expbase= self._expbase
ytickset= {}
yhighlim= self._yhighlim
ylowlim= self._ylowlim
if u'开盘二' in quotes:
yhighlim_2= self._yhighlim_2
ylowlim_2= self._ylowlim_2
if self._name == 'price' and 'pricefs' in self._parent._subplots:
tsetfs= self._parent._subplots['pricefs'].get_ytickset()
majors= tsetfs['major']
while majors[-1] < yhighlim: majors.append(majors[-1] * expbase)
while majors[0] > ylowlim: majors.insert(0, majors[0] / expbase)
minors= tsetfs['minor']
while minors[-1] < yhighlim: minors.append(minors[-1] * expbase)
while minors[0] > ylowlim: minors.insert(0, minors[0] / expbase)
ytickset['major']= [loc for loc in majors if loc > ylowlim and loc < yhighlim]
ytickset['minor']= [loc for loc in minors if loc > ylowlim and loc < yhighlim]
else:
# 主要坐标点
#----------------------------------------------------------------------------
majors= [ylowlim]
while majors[-1] < yhighlim: majors.append(majors[-1] * 1.1)
# 辅助坐标点
#----------------------------------------------------------------------------
minors= [ylowlim * 1.1**0.5]
while minors[-1] < yhighlim: minors.append(minors[-1] * 1.1)
ytickset['major']= [loc for loc in majors if loc > ylowlim and loc < yhighlim] # 注意，第一项（ylowlim）被排除掉了
ytickset['minor']= [loc for loc in minors if loc > ylowlim and loc < yhighlim]
if u'开盘二' in quotes:
popen= self._open[0] # int 类型
popen_2= self._open_2[0] # 同上
ytickset['major_2']= [loc * popen_2 / popen for loc in ytickset['major']]
ytickset['minor_2']= [loc * popen_2 / popen for loc in ytickset['minor']]
return ytickset
def get_ytickset(self):
return self._ytickset
def set_yticks(self):
'''
设置第一只行情的 Y 轴坐标，包括坐标值在图中间的显示
'''
axes= self._Axes
ylowlim= self._ylowlim
yhighlim= self._yhighlim
yaxis= self._AxisY
majorticks= self._ytickset['major']
minorticks= self._ytickset['minor']
# 设定 Y 轴坐标的范围
#==================================================================================================================================================
axes.set_ylim(ylowlim, yhighlim)
# 设定 Y 轴上的坐标
#==================================================================================================================================================
# 主要坐标点
#----------------------------------------------------------------------------
yMajorLocator= FixedLocator(numpy.array(majorticks))
# 确定 Y 轴的 MajorFormatter
def y_major_formatter(num, pos=None):
return str(round(num/1000.0, 2))
yMajorFormatter= FuncFormatter(y_major_formatter)
# 设定 X 轴的 Locator 和 Formatter
yaxis.set_major_locator(yMajorLocator)
yaxis.set_major_formatter(yMajorFormatter)
# 设定 Y 轴主要坐标点与辅助坐标点的样式
fsize= 4 if self._name == 'pricefs' else 6
for mal in axes.get_yticklabels(minor=False):
mal.set_fontsize(fsize)
# 辅助坐标点
#----------------------------------------------------------------------------
yMinorLocator= FixedLocator(numpy.array(minorticks))
# 确定 Y 轴的 MinorFormatter
def y_minor_formatter(num, pos=None):
return str(round(num/1000.0, 2))
yMinorFormatter= FuncFormatter(y_minor_formatter)
# 设定 X 轴的 Locator 和 Formatter
yaxis.set_minor_locator(yMinorLocator)
yaxis.set_minor_formatter(yMinorFormatter)
# 设定 Y 轴辅助坐标点的样式
if self._name == 'pricefs':
for mil in axes.get_yticklabels(minor=True):
mil.set_visible(False)
else:
for mil in axes.get_yticklabels(minor=True):
mil.set_fontsize(5)
mil.set_color('blue')
def set_yticks_2(self):
'''
子图右侧的 Y 轴坐标
'''
axes= self._Axes_2
yaxis= self._AxisY_2
yhighlim_2= self._yhighlim_2
ylowlim_2= self._ylowlim_2
majorticks_2= self._ytickset['major_2']
minorticks_2= self._ytickset['minor_2']
# 设定 Y 轴坐标的范围
#==================================================================================================================================================
axes.set_ylim(ylowlim_2, yhighlim_2)
# 设定 Y 轴上的坐标
#==================================================================================================================================================
# 主要坐标点
#----------------------------------------------------------------------------
yMajorLocator= FixedLocator(numpy.array(majorticks_2))
# 确定 Y 轴的 MajorFormatter
def y_major_formatter(num, pos=None):
return str(round(num/1000.0, 2))
yMajorFormatter= FuncFormatter(y_major_formatter)
# 设定 X 轴的 Locator 和 Formatter
yaxis.set_major_locator(yMajorLocator)
yaxis.set_major_formatter(yMajorFormatter)
# 设定 Y 轴主要坐标点与辅助坐标点的样式
fsize= 4 if self._name == 'pricefs' else 6
for mal in axes.get_yticklabels(minor=False):
mal.set_fontsize(fsize)
# 辅助坐标点
#----------------------------------------------------------------------------
yMinorLocator= FixedLocator(numpy.array(minorticks_2)) # XXX minor ticks 已经在上面一并设置，这里不需要了。
# 确定 Y 轴的 MinorFormatter
def y_minor_formatter(num, pos=None):
return str(round(num/1000.0, 2))
yMinorFormatter= FuncFormatter(y_minor_formatter)
# 设定 X 轴的 Locator 和 Formatter
yaxis.set_minor_locator(yMinorLocator)
yaxis.set_minor_formatter(yMinorFormatter)
# 设定 Y 轴主要坐标点与辅助坐标点的样式
if self._name == 'pricefs':
for mil in axes.get_yticklabels(minor=True):
mil.set_visible(False)
else:
for mil in axes.get_yticklabels(minor=True):
mil.set_fontsize(5)
mil.set_color('blue')
def plot(self):
'''
由派生类自己定义
'''
pass
def plot_candlestick(self):
'''
绘制 K 线
'''
axes= self._Axes
xindex= self._xindex
up= self._up
down= self._down
side= self._side
# 绘制 K 线部分
#==================================================================================================================================================
# 对开收盘价进行视觉修正
for idx, poc in enumerate(self._zipoc):
if poc[0] == poc[1] and None not in poc:
variant= int(round((poc[1]+1000)/2000.0, 0))
self._open[idx]= poc[0] - variant # 稍微偏离一点，使得在图线上不致于完全看不到
self._close[idx]= poc[1] + variant
rarray_open= numpy.array(self._open)
rarray_close= numpy.array(self._close)
rarray_high= numpy.array(self._high)
rarray_low= numpy.array(self._low)
# XXX: 如果 up, down, side 里有一个全部为 False 组成，那么 vlines() 会报错。
# XXX: 可以使用 alpha 参数调节透明度
if True in up:
axes.vlines(xindex[up], rarray_low[up], rarray_high[up], edgecolor='red', linewidth=0.6, label='_nolegend_', alpha=0.5)
axes.vlines(xindex[up], rarray_open[up], rarray_close[up], edgecolor='red', linewidth=3.0, label='_nolegend_', alpha=0.5)
if True in down:
axes.vlines(xindex[down], rarray_low[down], rarray_high[down], edgecolor='green', linewidth=0.6, label='_nolegend_', alpha=0.5)
axes.vlines(xindex[down], rarray_open[down], rarray_close[down], edgecolor='green', linewidth=3.0, label='_nolegend_', alpha=0.5)
if True in side:
axes.vlines(xindex[side], rarray_low[side], rarray_high[side], edgecolor='0.7', linewidth=0.6, label='_nolegend_', alpha=0.5)
axes.vlines(xindex[side], rarray_open[side], rarray_close[side], edgecolor='0.7', linewidth=3.0, label='_nolegend_', alpha=0.5)
def plot_simplified(self):
'''
绘制简化行情
'''
xindex= self._xindex
axes= self._Axes
rarray_simple= numpy.array(self._simple)
axes.plot(xindex, rarray_simple, 'o-', color='white', linewidth=0.3, label='simple', \
markersize=0.3, markeredgecolor='white', markeredgewidth=0.1, alpha=0.3) # 简化行情
def plot_average(self):
'''
绘制均线
'''
# 绘制均线部分
#==================================================================================================================================================
quotes= self._pdata[u'行情']
xindex= self._xindex
axes= self._Axes
if self._name == 'pricefs':
widthw= 0.1
widthn= 0.07
mksize= 0.07
mkwidth= 0.1
alpha= 1.0
else:
widthw= 0.2
widthn= 0.1
mksize= 0.3
mkwidth= 0.1
alpha= 1.0
if u'3日均' in quotes:
rarray_3dayave= numpy.array(self._average3)
axes.plot(xindex, rarray_3dayave, 'o-', color='white', linewidth=widthw, label='avg_3', \
markersize=mksize, markeredgecolor='white', markeredgewidth=mkwidth, alpha=alpha) # 3日均线
if u'5日均' in quotes:
rarray_5dayave= numpy.array(self._average5)
axes.plot(xindex, rarray_5dayave, 'o-', color='white', linewidth=widthn, label='avg_5', \
markersize=mksize, markeredgecolor='white', markeredgewidth=mkwidth, alpha=alpha) # 5日均线
if u'10日均' in quotes:
rarray_10dayave= numpy.array(self._average10)
axes.plot(xindex, rarray_10dayave, 'o-', color='yellow', linewidth=widthn, label='avg_10', \
markersize=mksize, markeredgecolor='yellow', markeredgewidth=mkwidth, alpha=alpha) # 10日均线
if u'30日均' in quotes:
rarray_30dayave= numpy.array(self._average30)
axes.plot(xindex, rarray_30dayave, 'o-', color='cyan', linewidth=widthn, label='avg_30', \
markersize=mksize, markeredgecolor='cyan', markeredgewidth=mkwidth, alpha=alpha) # 30日均线
if u'60日均' in quotes:
rarray_60dayave= numpy.array(self._average60)
axes.plot(xindex, rarray_60dayave, 'o-', color='magenta', linewidth=widthn, label='avg_60', \
markersize=mksize, markeredgecolor='magenta', markeredgewidth=mkwidth, alpha=alpha) # 60日均线
def plot_adjustnotes(self):
'''
绘制复权提示
'''
quotes= self._pdata[u'行情']
firstday= self._dates[0]
lastday= self._dates[-1]
ylowlim= self._ylowlim
yhighlim= self._yhighlim
axes= self._Axes
# 使用 annotate() 进行标注。不用了，留作纪念。
#===========================================================================================================================
# adjdict= dict(quotes[u'相对复权']) # key 是 date string，value 是相对复权因子（float 类型）
# el= Ellipse((2, -1), 0.5, 0.5)
# for idx, dstr in enumerate(self._dates):
# if dstr in adjdict:
# axes.plot([idx, idx], [ylowlim, yhighlim], '-', color='purple', linewidth=0.1)
# axes.annotate(u'复权\n' + str(adjdict[dstr]),
# fontproperties=__font_properties__,
# xy=(idx, yhighlim/1.1), xycoords='data',
# xytext=(10, 5), textcoords='offset points', size=5, verticalalignment="center",
# bbox=dict(boxstyle="round", facecolor='white', edgecolor='purple'),
# arrowprops=dict(arrowstyle="wedge,tail_width=1.",
# facecolor='white', edgecolor='purple',
# patchA=None,
# patchB=el,
# relpos=(0.2, 0.8),
# connectionstyle="arc3,rad=-0.1"),
# alpha=0.5
# )
adjrecs= [rec for rec in quotes[u'相对复权'] if rec[0] >= firstday and rec[0] <= lastday]
if self._name == 'pricefs':
fsize= 3.0
ycoord= yhighlim/1.3
alpha= 1.0
else:
fsize= 5.0
ycoord= yhighlim/1.12
alpha= 1.0
for dstr, afac in adjrecs:
idx= self._dates.index(dstr)
axes.plot([idx, idx], [ylowlim, yhighlim], '-', color='purple', linewidth=0.1)
label= axes.text( \
idx, ycoord, \
u'复权 ' + str(afac) + u'\n' + dstr, \
fontproperties=__font_properties__, \
horizontalalignment='left', \
verticalalignment='top', \
color='purple', \
alpha=alpha
)
label.set_fontsize(fsize)
def plot_capchangenotes(self):
'''
绘制流通股本变更提示
注意两个问题:
1. 流通股本变更提示中的日期可能不是交易日期
2. 流通股本变更提示涵盖个股的所有历史，有些内容可能在绘图目标区间以外
'''
pdata= self._pdata
axes= self._Axes
ylowlim= self._ylowlim
yhighlim= self._yhighlim
firstday= self._dates[0]
lastday= self._dates[-1]
# 把目标区间之外的记录滤掉
changerecs= [rec for rec in pdata[u'公司信息'][u'流通股变更'] if rec[u'变更日期'] >= firstday and rec[u'变更日期'] <= lastday]
# 使用 annotate() 进行标注。不用了，留作纪念。
#===========================================================================================================================
# el= Ellipse((2, -1), 0.5, 0.5)
# for datestr, chrate in changerecs:
# dstr= [ds for ds in self._dates if ds >= datestr][0]
# idx= self._dates.index(dstr)
# axes.plot([idx, idx], [ylowlim, yhighlim], '-', color='yellow', linewidth=0.1)
# axes.annotate(u'流通股\n' + str(chrate),
# fontproperties=__font_properties__,
# xy=(idx, yhighlim/1.1), xycoords='data',
# xytext=(10, 5), textcoords='offset points', size=5, verticalalignment="center",
# bbox=dict(boxstyle="round", facecolor='white', edgecolor='yellow'),
# arrowprops=dict(arrowstyle="wedge,tail_width=1.",
# facecolor='white', edgecolor='yellow',
# patchA=None,
# patchB=el,
# relpos=(0.2, 0.8),
# connectionstyle="arc3,rad=-0.1"),
# alpha=0.5
# )
if self._name == 'pricefs':
fsize= 3.0
ycoord= yhighlim/1.1
alpha= 1.0
else:
fsize= 5.0
ycoord= yhighlim/1.05
alpha= 0.8
for record in changerecs:
datestr= record[u'变更日期']
chrate= record[u'变更比']
dstr= [ds for ds in self._dates if ds >= datestr][0]
idx= self._dates.index(dstr)
axes.plot([idx, idx], [ylowlim, yhighlim], '-', color='yellow', linewidth=0.1)
label= axes.text( \
idx, ycoord, \
u'流通股 ' + str(chrate) + u'\n' + datestr, \
fontproperties=__font_properties__, \
horizontalalignment='left', \
verticalalignment='top', \
color='yellow', \
alpha=alpha
)
label.set_fontsize(fsize)
def plot_candlestick_2(self):
'''
绘制第二条 K 线
'''
xindex= self._xindex
axes= self._Axes_2
up= self._up_2
down= self._down_2
side= self._side_2
# 对开收盘价进行视觉修正
for idx, poc in enumerate( self._zipoc_2 ):
if poc[0] == poc[1] and None not in poc:
self._open_2[idx]= poc[0] - 5 # 稍微偏离一点，使得在图线上不致于完全看不到
self._close_2[idx]= poc[1] + 5
rarray_open= numpy.array(self._open_2)
rarray_close= numpy.array(self._close_2)
rarray_high= numpy.array(self._high_2)
rarray_low= numpy.array(self._low_2)
# XXX: 如果 up, down, side 里有一个全部为 False 组成，那么 vlines() 会报错。
# XXX: 可以使用 alpha 参数调节透明度
if True in up:
axes.vlines(xindex[up], rarray_low[up], rarray_high[up], edgecolor='0.7', linewidth=0.6, label='_nolegend_', alpha=0.5)
axes.vlines(xindex[up], rarray_open[up], rarray_close[up], edgecolor='0.7', linewidth=3.0, label='_nolegend_', alpha=0.5)
if True in down:
axes.vlines(xindex[down], rarray_low[down], rarray_high[down], edgecolor='0.3', linewidth=0.6, label='_nolegend_', alpha=0.5)
axes.vlines(xindex[down], rarray_open[down], rarray_close[down], edgecolor='0.3', linewidth=3.0, label='_nolegend_', alpha=0.5)
if True in side:
axes.vlines(xindex[side], rarray_low[side], rarray_high[side], edgecolor='1.0', linewidth=0.6, label='_nolegend_', alpha=1.0)
axes.vlines(xindex[side], rarray_open[side], rarray_close[side], edgecolor='1.0', linewidth=3.0, label='_nolegend_', alpha=1.0)
def plot_capitalinfo(self):
'''
绘制行情首日和尾日的股本信息
'''
def find_biggestblank(didx):
'''
找出 X 轴某个位置图中最大的空隙
'''
pstart= self._open[0]
ptarget= self._open[didx]
compseq= [yhighlim, ptarget, ylowlim]
if u'开盘二' in quotes:
pstart_2= self._open_2[0]
ptarget_2= self._open_2[didx]
padjust= int(ptarget_2 * pstart / float(pstart_2))
compseq.append(padjust)
compseq.sort(reverse=True) # 图中的三个或四个关键点，高到底排序
diff, hi, low= max([(math.log(compseq[idx]/float(compseq[idx+1]), expbase), compseq[idx], compseq[idx+1]) for idx in range(len(compseq)-1)])
# XXX: for debugging
# print(compseq)
# print([diff, hi, low])
return (hi*low)**0.5 # 相乘再开平方，在 log 坐标系里看起来就是在中间位置。
def repr_int(intnum):
'''
123456789 --> '1,2345,6789'
'''
if type(intnum) not in (int, long): return str(intnum)
if intnum == 0: return '0'
if intnum < 0:
intnum= -intnum
isminus= True
else:
isminus= False
intstr= str(intnum)
intstr= '0'*((4-len(intstr)%4)%4) + intstr
intlist= [intstr[i:i+4] for i in range(0, len(intstr), 4)]
intlist[0]= intlist[0].lstrip('0')
return ('-' + ','.join(intlist)) if isminus else ','.join(intlist)
pdata= self._pdata
quotes= pdata[u'行情']
ylowlim= self._ylowlim
yhighlim= self._yhighlim
length= self._length
expbase= self._expbase
capinfo= pdata[u'公司信息'][u'股本变更记录']
axes= self._Axes
firstday, lastday= self._dates[0], self._dates[-1]
fsize= 5.0 if self._name == 'price' else 3.0
# 首日总股本与流通股信息
#====================================================================================================================================
chunk= [rec for rec in capinfo if rec[u'变更日期'] <= firstday]
if chunk:
allshares= repr_int(chunk[-1][u'总股本'])
circulating= repr_int(chunk[-1][u'流通股'])
else:
allshares= 'None'
circulating= 'None'
infostr= u'总股本: ' + allshares + '\n' + u'流通股: ' + circulating
label= axes.text(0, find_biggestblank(didx=0), infostr, fontproperties=__font_properties__, color='0.7')
label.set_fontsize(fsize)
# label.set_zorder(0) # XXX: 放在底层
# 尾日总股本与流通股信息
#====================================================================================================================================
chunk= [rec for rec in capinfo if rec[u'变更日期'] <= lastday]
if chunk:
allshares= repr_int(chunk[-1][u'总股本'])
circulating= repr_int(chunk[-1][u'流通股'])
else:
allshares= 'None'
circulating= 'None'
infostr= u'总股本: ' + allshares + '\n' + u'流通股: ' + circulating
label= axes.text(length-1, find_biggestblank(didx=length-1), infostr, fontproperties=__font_properties__, horizontalalignment='right', color='0.7')
label.set_fontsize(fsize)
# label.set_zorder(0) # XXX: 放在底层
def plot_usernotes(self):
'''
'''
pdata= self._pdata
quotes= pdata[u'行情']
sidx= self._pdata[u'任务描述'][u'起始偏移']
eidx= self._pdata[u'任务描述'][u'结束偏移']
axes= self._Axes
usernotes= pdata[u'用户标记']
alldates= quotes[u'日期'][sidx:eidx]
lowprices= quotes[u'最低'][sidx:eidx]
expbase= self._expbase
# 绘制短线买点标记
for note in usernotes:
if note[u'类型'] == u'筛选结果':
dstr= note[u'日期']
# 日期不在绘图区间范围内，忽略
if dstr not in alldates:
continue
# 决定箭头的颜色
result= note[u'结果']
color= 'magenta' if result == u'上涨' else 'cyan' if result == u'下跌' else 'white'
# 箭头的起始位置
idx= alldates.index(dstr)
xpos= idx
ypos= lowprices[idx] / expbase
# 箭头的长度
dx= 0.0
dy= ypos * (expbase-1) * 0.9
# 头端的长度
head_length= dy * 0.2
# 绘制箭头
arrow_params={'length_includes_head':True, 'shape':'full', 'head_starts_at_zero':False}
axes.arrow(xpos, ypos, dx, dy, facecolor=color, edgecolor=color, linewidth=0.7, head_width=0.6, head_length=head_length, **arrow_params)
def plot_vlines(self):
xindex= self._xindex
up= self._up
down= self._down
side= self._side
axes= self._Axes
lwidth= 2.4 * self._shrink
# 绘制 K 线部分
#==================================================================================================================================================
rarray_high= numpy.array(self._high)
rarray_low= numpy.array(self._low)
# XXX: 如果 up, down, side 里有一个全部为 False 组成，那么 vlines() 会报错。
# XXX: 可以使用 alpha 参数调节透明度
if True in up:
axes.vlines(xindex[up], rarray_low[up], rarray_high[up], edgecolor='red', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in down:
axes.vlines(xindex[down], rarray_low[down], rarray_high[down], edgecolor='green', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in side:
axes.vlines(xindex[side], rarray_low[side], rarray_high[side], edgecolor='0.7', linewidth=lwidth, label='_nolegend_', alpha=0.5)
def plot_vlines_2(self):
xindex= self._xindex
axes= self._Axes_2
up= self._up_2
down= self._down_2
side= self._side_2
lwidth= 2.4 * self._shrink
rarray_high= numpy.array(self._high_2)
rarray_low= numpy.array(self._low_2)
# XXX: 如果 up, down, side 里有一个全部为 False 组成，那么 vlines() 会报错。
# XXX: 可以使用 alpha 参数调节透明度
if True in up:
axes.vlines(xindex[up], rarray_low[up], rarray_high[up], edgecolor='0.7', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in down:
axes.vlines(xindex[down], rarray_low[down], rarray_high[down], edgecolor='0.3', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in side:
axes.vlines(xindex[side], rarray_low[side], rarray_high[side], edgecolor='1.0', linewidth=lwidth, label='_nolegend_', alpha=1.0)
def plot_datenotes(self):
'''
内部的日期注释，由派生类定义
'''
pass
def plot_pricenotes(self):
'''
内部的价格注释，由派生类定义
'''
pass
class SubPlot_PriceFullSpan(SubPlot_PriceBase):
'''
'''
def plot(self):
'''
绘图
'''
pdata= self._pdata
# if u'简化' in pdata:
# self.plot_simplified()
# else:
# self.plot_candlestick()
self.plot_vlines()
self.plot_average()
if u'相对复权' in pdata[u'行情']:
self.plot_adjustnotes()
if u'流通股变更' in pdata[u'公司信息']:
self.plot_capchangenotes()
if u'股本变更记录' in pdata[u'公司信息']:
self.plot_capitalinfo()
self.set_xticks()
self.set_yticks()
if u'开盘二' in pdata[u'行情']:
self.plot_vlines_2()
self.set_xticks_2()
self.set_yticks_2()
self.plot_datenotes()
if 'price' in self._parent._subplots:
self.plot_windowspan()
def plot_datenotes(self):
'''
日期在图中间的显示
'''
ylowlim= self._ylowlim
axes= self._Axes
sdindex= self._xparams['sdindex']
mdindex= self._xparams['mdindex']
# 每季度第一个交易日
for ix in sdindex:
newlab= axes.text(ix - (1/self._shrink), ylowlim*1.03, self._dates[ix])
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(4)
newlab.set_rotation('45')
# newlab.set_rotation('vertical')
# newlab.set_horizontalalignment('left')
# newlab.set_verticalalignment('bottom')
# newlab.set_verticalalignment('center')
newlab.set_zorder(0) # XXX: 放在底层
# 每月第一个交易日
for ix in mdindex:
newlab= axes.text(ix - (0.8/self._shrink), ylowlim * 1.03, self._dates[ix])
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(3)
newlab.set_rotation('45')
# newlab.set_rotation('vertical')
# newlab.set_horizontalalignment('left')
# newlab.set_verticalalignment('top') # 不行
# newlab.set_verticalalignment('center')
# newlab.set_verticalalignment('bottom')
newlab.set_zorder(0) # XXX: 放在底层
def plot_windowspan(self):
axes= self._Axes
jobstat= self._pdata[u'任务描述']
sindex, eindex= jobstat[u'起始偏移'], jobstat[u'结束偏移']
hibdry, lobdry= self._parent._subplots['price'].get_ylimits()
xcoord= sindex - 1
width= eindex - sindex + 1
ycoord= lobdry
height= hibdry - lobdry
window= matplotlib.patches.Rectangle((xcoord, ycoord), width, height, fill=False, edgecolor=__color_lightblue__, linewidth=0.3, alpha=0.7)
window.set_zorder(-1) # 放在底层
axes.add_patch(window)
class SubPlot_Price(SubPlot_PriceBase):
'''
'''
def plot(self):
'''
绘图
'''
pdata= self._pdata
# if u'简化' in pdata:
# self.plot_simplified()
# else:
# self.plot_candlestick()
self.plot_candlestick()
self.plot_average()
if u'相对复权' in pdata[u'行情']:
self.plot_adjustnotes()
if u'流通股变更' in pdata[u'公司信息']:
self.plot_capchangenotes()
if u'股本变更记录' in pdata[u'公司信息']:
self.plot_capitalinfo()
if u'用户标记' in pdata:
self.plot_usernotes()
self.set_xticks()
self.set_yticks()
if u'开盘二' in pdata[u'行情']:
self.plot_candlestick_2()
self.set_xticks_2()
self.set_yticks_2()
self.plot_pricenotes()
self.plot_datenotes()
def plot_datenotes(self):
'''
日期在图中间的显示
'''
ylowlim= self._ylowlim
yhighlim= self._yhighlim
axes= self._Axes
mdindex= self._xparams['mdindex']
wdindex= self._xparams['wdindex']
# 每月第一个交易日
for iy in [ylowlim*1.1, yhighlim/1.21]:
for ix in mdindex:
newlab= axes.text(ix-1, iy, self._dates[ix])
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(4)
newlab.set_rotation('vertical')
# newlab.set_horizontalalignment('left')
# newlab.set_verticalalignment('bottom')
# newlab.set_verticalalignment('center')
newlab.set_zorder(0) # XXX: 放在底层
# 每周第一个交易日，根据这个可以推算出全部确切的日期。
# for iy in minorticks[0:-1:6]:
for iy in [ylowlim*1.01, yhighlim/1.09]:
for ix in wdindex:
newlab= axes.text(ix-0.8, iy, self._dates[ix])
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(3)
newlab.set_rotation('vertical')
# newlab.set_horizontalalignment('left')
# newlab.set_verticalalignment('top') # 不行
# newlab.set_verticalalignment('center')
# newlab.set_verticalalignment('bottom')
newlab.set_zorder(0) # XXX: 放在底层
def plot_pricenotes(self):
# 价格数值在图中间的显示
#==================================================================================================================================================
quotes= self._pdata[u'行情']
axes= self._Axes
majorticks= self._ytickset['major']
minorticks= self._ytickset['minor']
mdindex= self._xparams['mdindex']
def price_note(num):
return str(round(num/1000.0, 2))
if u'开盘二' in quotes:
majorticks_2= self._ytickset['major_2']
minorticks_2= self._ytickset['minor_2']
for iy, iy2 in zip(sorted(majorticks[:-1] + minorticks[1:-1]), sorted(majorticks_2[:-1] + minorticks_2[1:-1])):
for ix in mdindex[1:-1:3]:
newlab= axes.text(ix+6, iy*1.001, price_note(iy) + ' / ' + price_note(iy2))
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(3)
newlab.set_zorder(0) # XXX: 放在底层
else:
for iy in sorted(majorticks[:-1] + minorticks[1:-1]):
for ix in mdindex[1:-1:3]:
newlab= axes.text(ix+9, iy*1.001, price_note(iy))
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(3)
newlab.set_zorder(0) # XXX: 放在底层
class SubPlot_TORateBase:
'''
换手率子图
'''
def __init__(self, pdata, parent, xparams, name):
self._name= name
self._pdata= pdata
self._parent= parent
self._xparams= xparams
self._shrink= __shrink__ if name == 'toratefs' else 1.0
self._tostep= 0 # 每一格代表的换手率数值
self._yrange= 0
self._xsize= 0 # int
self._ysize= 0 # int
self._Axes= None
self._AxisX= None
self._AxisY= None
if u'换手率二' in pdata[u'行情']:
self._Axes_2= None
self._AxisX_2= None
self._AxisY_2= None
self._tostep_2= 0
# 绘图数据
quotes= pdata[u'行情']
if name == 'toratefs':
self._dates= quotes[u'日期']
self._open= quotes[u'开盘']
self._close= quotes[u'收盘']
self._high= quotes[u'最高']
self._low= quotes[u'最低']
if u'简化' in quotes: self._simple= quotes[u'简化']
if u'换手率' in quotes: self._torate= quotes[u'换手率']
if u'成交量' in quotes: self._volume= quotes[u'成交量']
if u'成交额' in quotes: self._turnover= quotes[u'成交额']
if u'开盘二' in quotes:
self._open_2= quotes[u'开盘二']
self._close_2= quotes[u'收盘二']
self._high_2= quotes[u'最高二']
self._low_2= quotes[u'最低二']
if u'简化二' in quotes: self._simple_2= quotes[u'简化二']
if u'换手率二' in quotes: self._torate_2= quotes[u'换手率二']
if u'成交量二' in quotes: self._volume_2= quotes[u'成交量二']
if u'成交额二' in quotes: self._turnover_2= quotes[u'成交额二']
else:
sidx, eidx= pdata[u'任务描述'][u'起始偏移'], pdata[u'任务描述'][u'结束偏移']
self._dates= quotes[u'日期'][sidx:eidx]
self._open= quotes[u'开盘'][sidx:eidx]
self._close= quotes[u'收盘'][sidx:eidx]
self._high= quotes[u'最高'][sidx:eidx]
self._low= quotes[u'最低'][sidx:eidx]
if u'简化' in quotes: self._simple= quotes[u'简化'][sidx:eidx]
if u'换手率' in quotes: self._torate= quotes[u'换手率'][sidx:eidx]
if u'成交量' in quotes: self._volume= quotes[u'成交量'][sidx:eidx]
if u'成交额' in quotes: self._turnover= quotes[u'成交额'][sidx:eidx]
if u'开盘二' in quotes:
self._open_2= quotes[u'开盘二'][sidx:eidx]
self._close_2= quotes[u'收盘二'][sidx:eidx]
self._high_2= quotes[u'最高二'][sidx:eidx]
self._low_2= quotes[u'最低二'][sidx:eidx]
if u'简化二' in quotes: self._simple_2= quotes[u'简化二'][sidx:eidx]
if u'换手率二' in quotes: self._torate_2= quotes[u'换手率二'][sidx:eidx]
if u'成交量二' in quotes: self._volume_2= quotes[u'成交量二'][sidx:eidx]
if u'成交额二' in quotes: self._turnover_2= quotes[u'成交额二'][sidx:eidx]
# 衍生数据
#==============================================================================================================
self._length= len(self._dates)
self._xindex= numpy.arange(self._length) # X 轴上的 index，一个辅助数据
self._zipoc= zip(self._open, self._close)
self._up= numpy.array( [ True if po < pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内上涨的一个序列
self._down= numpy.array( [ True if po > pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内下跌的一个序列
self._side= numpy.array( [ True if po == pc and po is not None else False for po, pc in self._zipoc] ) # 标示出该天股价日内走平的一个序列
if u'开盘二' in quotes:
self._zipoc_2= zip(self._open_2, self._close_2)
self._up_2= numpy.array( [ True if po < pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内上涨的一个序列
self._down_2= numpy.array( [ True if po > pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内下跌的一个序列
self._side_2= numpy.array( [ True if po == pc and po is not None else False for po, pc in self._zipoc_2] ) # 标示出该天股价日内走平的一个序列
self._compute_size()
def _compute_size(self):
'''
根据 pdata 计算自身尺寸
'''
def _compute_step(maxto):
'''
maxto 是 换手率 最大值。返回每格单位（最小 500, 代表 0.5%）以及格数
'''
for i in range(9):
if maxto > (4 * 500 * (2**i)): # 换手率最大是 100000, 代表 100%
continue
else:
tostep= 500 * (2**i)
tosize= int(round((maxto + tostep/2.0 - 1) / float(tostep), 0))
break
return (tostep, tosize)
quotes= self._pdata[u'行情']
xmargin= self._xparams['xmargin']
self._xsize= (self._length + xmargin*2) * self._shrink
maxto= max(self._torate)
self._tostep, self._yrange= _compute_step(maxto=maxto)
if u'换手率二' in quotes:
maxto_2= max(self._torate_2)
self._tostep_2, yrange_2= _compute_step(maxto=maxto_2)
self._yrange= max(self._yrange, yrange_2) # 成交量部分在 Y 轴所占的 “份数”
self._ysize= self._yrange * self._shrink
def get_size(self):
return (self._xsize, self._ysize)
def build_axes(self, figobj, rect):
# 第一只：添加 Axes 对象
#==================================================================================================================================================
axes= figobj.add_axes(rect, axis_bgcolor='black')
axes.set_axis_bgcolor('black')
axes.set_axisbelow(True) # 网格线放在底层
# 第一只：改变坐标线的颜色
#==================================================================================================================================================
for child in axes.get_children():
if isinstance(child, matplotlib.spines.Spine):
child.set_color(__color_gold__)
# child.set_zorder(3) # XXX: 放在上层，好像没什么用。
# 得到 X 轴 和 Y 轴 的两个 Axis 对象
#==================================================================================================================================================
xaxis= axes.get_xaxis()
yaxis= axes.get_yaxis()
# 设置两个坐标轴上的 grid
#==================================================================================================================================================
xaxis.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
xaxis.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
yaxis.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
yaxis.grid(True, 'minor', color='0.3', linestyle='solid', linewidth=0.1)
self._Axes= axes
self._AxisX= xaxis
self._AxisY= yaxis
if u'换手率二' in self._pdata[u'行情']:
# 添加 Axes 对象
#==================================================================================================================================================
axes_2= axes.twinx()
# XXX: 下面这三行把第一个 axes 放在上面，这样不会被第二个 axes 的图形遮盖。用 zorder 不顶用。
axes.figure.axes[-2:]= [axes_2, axes] # XXX: 把第一个 axes 放在上面，用 zorder 不顶用。
axes.set_frame_on(False) # 如果不做此设定，axes_2 的内容会看不见
axes_2.set_frame_on(True)
axes_2.set_axis_bgcolor('black')
axes_2.set_axisbelow(True) # 网格线放在底层
# 改变坐标线的颜色
#==================================================================================================================================================
for child in axes_2.get_children():
if isinstance(child, matplotlib.spines.Spine):
child.set_color(__color_gold__)
# 得到 X 轴 和 Y 轴 的两个 Axis 对象
#==================================================================================================================================================
xaxis_2= axes_2.get_xaxis()
yaxis_2= axes_2.get_yaxis()
# 设置网格线
#==================================================================================================================================================
# xaxis_2.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
# xaxis_2.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
# yaxis_2.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
# yaxis_2.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)
self._Axes_2= axes_2
self._AxisX_2= xaxis_2
self._AxisY_2= yaxis_2
def get_axes(self):
return self._Axes
def plot(self):
'''
绘制换手率图形
'''
self.plot_torate()
self.set_xticks()
self.set_yticks()
if u'换手率二' in self._pdata[u'行情']:
self.plot_torate_2()
self.set_xticks_2()
self.set_yticks_2()
def plot_torate(self):
'''
绘制换手率
'''
xindex= self._xindex
stopset= self._xparams['mdindex'] if self._name == 'torate' else self._xparams['sdindex']
axes= self._Axes
up= self._up
down= self._down
side= self._side
rarray_to= numpy.array(self._torate)
tozeros= numpy.zeros(self._length) # 辅助数据
lwidth= 3.0 if self._name == 'torate' else 2.4 * self._shrink
# XXX: 如果 up/down/side 各项全部为 False，那么 vlines() 会报错。
if True in up:
axes.vlines(xindex[up], tozeros[up], rarray_to[up], edgecolor='red', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in down:
axes.vlines(xindex[down], tozeros[down], rarray_to[down], edgecolor='green', linewidth=lwidth, label='_nolegend_', alpha=0.5)
if True in side:
axes.vlines(xindex[side], tozeros[side], rarray_to[side], edgecolor='0.7', linewidth=lwidth, label='_nolegend_', alpha=0.5)
# 绘制平均换手率（直线）
toeffect= [num for num in self._torate if num is not None]
toaverage= sum(toeffect) / float(len(toeffect))
axes.plot([-1, self._length], [toaverage, toaverage], '-', color='yellow', linewidth=0.2, alpha=0.7)
# 换手率数值在图中间的显示
#==================================================================================================================================================
for ix in stopset[2:-1:3]:
newlab= axes.text(ix+8, toaverage, str(round(toaverage/1000.0, 2)) + '%')
newlab.set_font_properties(__font_properties__)
newlab.set_color('yellow')
newlab.set_fontsize(3)
# newlab.set_zorder(0) # XXX: 放在底层
# newlab.set_verticalalignment('center')
def plot_torate_2(self):
'''
绘制第二条换手率柱状图
'''
quotes= self._pdata[u'行情']
xindex= self._xindex
axes= self._Axes_2
up= self._up_2
down= self._down_2
side= self._side_2
rarray_to= numpy.array(self._torate_2)
tozeros= numpy.zeros(self._length) # 辅助数据
lwidth, alpha= (0.7, 0.5) if self._name == 'torate' else (0.3, 0.7)
# XXX: 如果 up/down/side 各项全部为 False，那么 vlines() 会报错。
if True in up:
axes.vlines(xindex[up], tozeros[up], rarray_to[up], edgecolor='0.7', linewidth=lwidth, label='_nolegend_', alpha=alpha)
if True in down:
axes.vlines(xindex[down], tozeros[down], rarray_to[down], edgecolor='0.3', linewidth=lwidth, label='_nolegend_', alpha=alpha)
if True in side:
axes.vlines(xindex[side], tozeros[side], rarray_to[side], edgecolor='0.7', linewidth=lwidth, label='_nolegend_', alpha=1.0)
def set_xticks(self):
'''
X 轴坐标
'''
length= self._length
xmargin= self._xparams['xmargin']
axes= self._Axes
xaxis= self._AxisX
# xaxis.set_tick_params(which='both', direction='out') # XXX: 坐标点设到外面去，也可以用 Axes.tick_params()，好像 matplotlib 1.0.1 才有
# 设定 X 轴坐标的范围
#==================================================================================================================================================
axes.set_xlim(-xmargin, length + xmargin)
xMajorLocator= self._xparams['xMajorLocator']
xMinorLocator= self._xparams['xMinorLocator']
xMajorFormatter= self._xparams['xMajorFormatter']
xMinorFormatter= self._xparams['xMinorFormatter']
# 设定 X 轴的 Locator 和 Formatter
xaxis.set_major_locator(xMajorLocator)
xaxis.set_minor_locator(xMinorLocator)
if self._name == 'torate':
xaxis.set_major_formatter(xMajorFormatter)
xaxis.set_minor_formatter(xMinorFormatter)
# 设定 X 轴主要坐标点与辅助坐标点的样式
for mal in axes.get_xticklabels(minor=False):
mal.set_fontsize(4)
mal.set_horizontalalignment('right')
mal.set_rotation('45')
for mil in axes.get_xticklabels(minor=True):
mil.set_fontsize(4)
mil.set_color('blue')
mil.set_horizontalalignment('right')
mil.set_rotation('45')
else:
# 设为不可见
for mal in axes.get_xticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_xticklabels(minor=True):
mil.set_visible(False)
def set_xticks_2(self):
length= self._length
xmargin= self._xparams['xmargin']
axes= self._Axes_2
xaxis= self._AxisX_2
# xaxis.set_tick_params(which='both', direction='out') # XXX: 坐标点设到外面去，也可以用 Axes.tick_params()，好像 matplotlib 1.0.1 才有
# 设定 X 轴坐标的范围
#==================================================================================================================================================
axes.set_xlim(-xmargin, length + xmargin)
xMajorLocator= self._xparams['xMajorLocator']
xMinorLocator= self._xparams['xMinorLocator']
# 设定 X 轴的 Locator 和 Formatter
xaxis.set_major_locator(xMajorLocator)
xaxis.set_minor_locator(xMinorLocator)
# 设为不可见
for mal in axes.get_xticklabels(minor=False):
mal.set_visible(False)
for mil in axes.get_xticklabels(minor=True):
mil.set_visible(False)
def set_yticks(self):
'''
设置 Y 轴坐标
'''
axes= self._Axes
yaxis= self._AxisY
tostep= self._tostep
yrange= self._yrange
stopset= self._xparams['mdindex'] if self._name == 'torate' else self._xparams['sdindex']
# 设定换手率 Y 轴坐标的范围
#==================================================================================================================================================
axes.set_ylim(0, tostep*yrange)
# 主要坐标点
#==================================================================================================================================================
majorticks= [tostep*i for i in range(yrange)]
yMajorLocator= FixedLocator(numpy.array(majorticks))
# 确定 Y 轴的 MajorFormatter
def y_major_formatter(num, pos=None):
return str(round(num/1000.0, 2)) + '%'
yMajorFormatter= FuncFormatter(y_major_formatter)
# 确定 Y 轴的 MinorFormatter
yMinorFormatter= NullFormatter()
# 第一只：设定 X 轴的 Locator 和 Formatter
yaxis.set_major_locator(yMajorLocator)
yaxis.set_major_formatter(yMajorFormatter)
# 设定 Y 轴主要坐标点的样式
for mal in axes.get_yticklabels(minor=False):
mal.set_font_properties(__font_properties__)
mal.set_fontsize(5) # 这个必须放在前一句后面，否则作用会被覆盖
# 辅助坐标点
#==================================================================================================================================================
if self._name == 'torate':
minorticks= list( itertools.chain.from_iterable( mi for mi in [[ma + (tostep/4.0)*i for i in range(1, 4)] for ma in majorticks] ) )
yMinorLocator= FixedLocator(numpy.array(minorticks))
yaxis.set_minor_locator(yMinorLocator)
def y_minor_formatter(num, pos=None):
return str(round(num/1000.0, 3)) + '%'
yMinorFormatter= FuncFormatter(y_minor_formatter)
yaxis.set_minor_formatter(yMinorFormatter)
# 设定 Y 轴主要坐标点的样式
for mil in axes.get_yticklabels(minor=True):
mil.set_font_properties(__font_properties__)
mil.set_fontsize(4) # 这个必须放在前一句后面，否则作用会被覆盖
else:
# minorticks= list( itertools.chain.from_iterable( mi for mi in [[ma + (tostep/4.0)*i for i in range(1, 4)] for ma in majorticks] ) )
minorticks= list( [ma + (tostep/2.0) for ma in majorticks] )
yMinorLocator= FixedLocator(numpy.array(minorticks))
yaxis.set_minor_locator(yMinorLocator)
# 设定 Y 轴主要坐标点的样式
for mil in axes.get_yticklabels(minor=True):
mil.set_visible(False)
# 换手率数值在图中间的显示
#==================================================================================================================================================
for iy in range(int(tostep/2.0), tostep*yrange, int(tostep/2.0)):
for ix in stopset[1:-1:3]:
newlab= axes.text(ix+8, iy, y_major_formatter(iy))
newlab.set_font_properties(__font_properties__)
newlab.set_color('0.3')
newlab.set_fontsize(3)
newlab.set_zorder(0) # XXX: 放在底层
# newlab.set_verticalalignment('center')
def set_yticks_2(self):
'''
设置 Y 轴坐标
'''
axes= self._Axes_2
yaxis= self._AxisY_2
tostep= self._tostep_2
yrange= self._yrange # 与 1 是一样的
# 设定换手率 Y 轴坐标的范围
#==================================================================================================================================================
axes.set_ylim(0, tostep*yrange)
# 主要坐标点
#==================================================================================================================================================
majorticks= [tostep*i for i in range(yrange)]
yMajorLocator= FixedLocator(numpy.array(majorticks))
# 确定 Y 轴的 MajorFormatter
def y_major_formatter(num, pos=None):
return str(round(num/1000.0, 2)) + '%'
yMajorFormatter= FuncFormatter(y_major_formatter)
# 确定 Y 轴的 MinorFormatter
yMinorFormatter= NullFormatter()
# 第一只：设定 X 轴的 Locator 和 Formatter
yaxis.set_major_locator(yMajorLocator)
yaxis.set_major_formatter(yMajorFormatter)
# 设定 Y 轴主要坐标点的样式
for mal in axes.get_yticklabels(minor=False):
mal.set_font_properties(__font_properties__)
mal.set_fontsize(5) # 这个必须放在前一句后面，否则作用会被覆盖
# 辅助坐标点
#==================================================================================================================================================
if self._name == 'torate':
minorticks= list( itertools.chain.from_iterable( mi for mi in [[ma + (tostep/4.0)*i for i in range(1, 4)] for ma in majorticks] ) )
yMinorLocator= FixedLocator(numpy.array(minorticks))
def y_minor_formatter(num, pos=None):
return str(round(num/1000.0, 3)) + '%'
yMinorFormatter= FuncFormatter(y_minor_formatter)
yaxis.set_minor_locator(yMinorLocator)
yaxis.set_minor_formatter(yMinorFormatter)
# 设定 Y 轴主要坐标点的样式
for mil in axes.get_yticklabels(minor=True):
mil.set_font_properties(__font_properties__)
mil.set_fontsize(4) # 这个必须放在前一句后面，否则作用会被覆盖
else:
minorticks= list( [ma + (tostep/2.0) for ma in majorticks] )
yMinorLocator= FixedLocator(numpy.array(minorticks))
yaxis.set_minor_locator(yMinorLocator)
# 设定 Y 轴主要坐标点的样式
for mil in axes.get_yticklabels(minor=True):
mil.set_visible(False)
class SubPlot_TORate(SubPlot_TORateBase):
pass
class SubPlot_TORateFullSpan(SubPlot_TORateBase):
pass
class MyFigure:
'''
'''
def __init__(self, pdata):
self._pdata= pdata # 绘图数据
self._figfacecolor= __color_pink__
self._figedgecolor= __color_navy__
self._figdpi= 300
self._figlinewidth= 1.0
self._xfactor= 10.0 / 230.0 # x size * x factor = x length
self._yfactor= 0.3 # y size * y factor = y length
jobstat= pdata[u'任务描述']
self._xsize_left= 12.0 # left blank
self._xsize_right= 12.0 # right blank
self._ysize_top= 0.3 # top blank
self._ysize_bottom= 1.2 # bottom blank
self._ysize_gap1= 0.2
self._ysize_gap2= 0.3 if (jobstat[u'历史价格子图'] or jobstat[u'历史换手率子图'] or jobstat[u'财务指标子图']) else 0.0
# 建立 X 轴参数
#===============================================================================================================
if jobstat[u'价格子图'] or jobstat[u'换手率子图']:
xparams= {'xmargin': 1}
xparams.update(self._compute_xparams()) # 与 X 轴坐标点相关的数据结构
if jobstat[u'历史价格子图'] or jobstat[u'历史换手率子图'] or jobstat[u'财务指标子图']:
xparams_fs= {'xmargin': 3}
xparams_fs.update(self._compute_xparams_fullspan())
# 建立子图对象
#===============================================================================================================
self._subplots= {}
if jobstat[u'公司信息子图']:
name= 'basic'
self._subplots[name]= SubPlot_BasicInfo(pdata=pdata, parent=self, name=name)
if jobstat[u'历史价格子图']: # XXX: 这个要放在 价格子图 前面，因为后者可能会用到它的 Y 轴坐标点位置
name= 'pricefs'
self._subplots[name]= SubPlot_PriceFullSpan(pdata=pdata, parent=self, xparams=xparams_fs, name=name)
if jobstat[u'价格子图']:
name= 'price'
self._subplots[name]= SubPlot_Price(pdata=pdata, parent=self, xparams=xparams, name=name)
if jobstat[u'财务指标子图']:
name= 'financial'
self._subplots[name]= SubPlot_Financial(pdata=pdata, parent=self, xparams=xparams_fs, name=name)
if jobstat[u'换手率子图']:
name= 'torate'
self._subplots[name]= SubPlot_TORate(pdata=pdata, parent=self, xparams=xparams, name=name)
if jobstat[u'历史换手率子图']:
name= 'toratefs'
self._subplots[name]= SubPlot_TORateFullSpan(pdata=pdata, parent=self, xparams=xparams_fs, name=name)
# 根据子图对象的尺寸计算自身的尺寸
#===============================================================================================================
self._xsize, \
self._ysize= self._compute_size()
self._xlength= self._xsize * self._xfactor
self._ylength= self._ysize * self._yfactor
# 根据计算出的尺寸建立 Figure 对象
#===============================================================================================================
self._Fig= pyplot.figure(figsize=(self._xlength, self._ylength), dpi=self._figdpi, facecolor=self._figfacecolor, \
edgecolor=self._figedgecolor, linewidth=self._figlinewidth) # Figure 对象
# 用新建立的 Figure 对象交给子图对象，完成子图对象的初始化
#===============================================================================================================
rects= self._compute_rect()
if 'basic' in self._subplots:
self._subplots['basic'].build_axes(figobj=self._Fig, rect=rects['basic'])
# XXX: 这个要放在 price 前面，因为后者要用到它的 Axes 对象
if 'torate' in self._subplots:
self._subplots['torate'].build_axes(figobj=self._Fig, rect=rects['torate'])
if 'price' in self._subplots:
self._subplots['price'].build_axes(figobj=self._Fig, rect=rects['price'])
# XXX: 这个要放在 pricefs 前面
if 'toratefs' in self._subplots:
self._subplots['toratefs'].build_axes(figobj=self._Fig, rect=rects['toratefs'])
if 'pricefs' in self._subplots:
self._subplots['pricefs'].build_axes(figobj=self._Fig, rect=rects['pricefs'])
def _compute_size(self):
'''
根据子图的尺寸计算自身尺寸
'''
pdata= self._pdata
jobstat= pdata[u'任务描述']
x_left, x_right= self._xsize_left, self._xsize_right
y_top, y_bottom= self._ysize_top, self._ysize_bottom
y_gap1= self._ysize_gap1
y_gap2= self._ysize_gap2
x_basic, y_basic= self._subplots['basic'].get_size() if 'basic' in self._subplots else (0.0, 0.0)
x_price, y_price= self._subplots['price'].get_size() if 'price' in self._subplots else (0.0, 0.0)
x_pricefs, y_pricefs= self._subplots['pricefs'].get_size() if 'pricefs' in self._subplots else (0.0, 0.0)
x_torate, y_torate= self._subplots['torate'].get_size() if 'torate' in self._subplots else (0.0, 0.0)
x_toratefs, y_toratefs= self._subplots['toratefs'].get_size() if 'toratefs' in self._subplots else (0.0, 0.0)
x_financial, y_financial= self._subplots['financial'].get_size() if 'financial' in self._subplots else (0.0, 0.0)
x_all= x_left + max(x_price, x_basic, x_pricefs) + x_right
y_all= y_top + y_basic + y_gap1 + y_pricefs + y_toratefs + y_financial + y_gap2 + y_price + y_torate + y_bottom
return (x_all, y_all)
def get_sizeset(self):
sizeset= {
'x': self._xsize,
'y': self._ysize,
'top': self._ysize_top,
'bottom': self._ysize_bottom,
'left': self._xsize_left,
'right': self._xsize_right
}
return sizeset
def _compute_rect(self):
'''
'''
pdata= self._pdata
jobstat= pdata[u'任务描述']
x_left= self._xsize_left
x_right= self._xsize_right
y_top= self._ysize_top
y_bottom= self._ysize_bottom
x_all= self._xsize
y_all= self._ysize
y_gap1= self._ysize_gap1 # basic 与 financial 之间的空隙
y_gap2= self._ysize_gap2 # toratefs 与 price 之间的空隙
x_basic, y_basic= self._subplots['basic'].get_size() if 'basic' in self._subplots else (0.0, 0.0)
x_price, y_price= self._subplots['price'].get_size() if 'price' in self._subplots else (0.0, 0.0)
x_pricefs, y_pricefs= self._subplots['pricefs'].get_size() if 'pricefs' in self._subplots else (0.0, 0.0)
x_torate, y_torate= self._subplots['torate'].get_size() if 'torate' in self._subplots else (0.0, 0.0)
x_toratefs, y_toratefs= self._subplots['toratefs'].get_size() if 'toratefs' in self._subplots else (0.0, 0.0)
x_financial, y_financial= self._subplots['financial'].get_size() if 'financial' in self._subplots else (0.0, 0.0)
rects= {}
if 'basic' in self._subplots:
rect= ((x_left + (x_all-x_left-x_right-x_basic)/2) / x_all, (y_all - y_top - y_basic)/y_all, x_basic/x_all, y_basic/y_all) # K线图部分
rects['basic']= rect
if 'price' in self._subplots:
rect= ((x_left + (x_all-x_left-x_right-x_price)/2) / x_all, (y_bottom + y_torate)/y_all, x_price/x_all, y_price/y_all) # K线图部分
rects['price']= rect
if 'torate' in self._subplots:
rect= ((x_left + (x_all-x_left-x_right-x_torate)/2)/x_all, y_bottom/y_all, x_torate/x_all, y_torate/y_all) # 成交量部分
rects['torate']= rect
if 'pricefs' in self._subplots:
rect= ((x_left + (x_all-x_left-x_right-x_pricefs)/2)/x_all, (y_all - y_top - y_basic - y_gap1 - y_pricefs)/y_all, x_pricefs/x_all, y_pricefs/y_all)
rects['pricefs']= rect
if 'toratefs' in self._subplots:
rect= ((x_left + (x_all-x_left-x_right-x_toratefs)/2)/x_all, (y_bottom + y_torate + y_price + y_gap2)/y_all, x_toratefs/x_all, y_toratefs/y_all)
rects['toratefs']= rect
return rects
def _compute_xparams(self):
'''
主要坐标点是每月第一个交易日，辅助坐标点是每周第一个交易日
'''
quotes= self._pdata[u'行情']
sidx= self._pdata[u'任务描述'][u'起始偏移']
eidx= self._pdata[u'任务描述'][u'结束偏移']
# 设定 X 轴上的坐标
#==================================================================================================================================================
datelist= [ datetime.date(int(ys), int(ms), int(ds)) for ys, ms, ds in [ dstr.split('-') for dstr in quotes[u'日期'][sidx:eidx] ] ]
# 确定 X 轴的 MajorLocator
mdindex= [] # 每个月第一个交易日在所有日期列表中的 index
allyears= set([d.year for d in datelist]) # 所有的交易年份
for yr in sorted(allyears):
allmonths= set([d.month for d in datelist if d.year == yr]) # 当年所有的交易月份
for mon in sorted(allmonths):
monthday= min([dt for dt in datelist if dt.year==yr and dt.month==mon]) # 当月的第一个交易日
mdindex.append(datelist.index(monthday))
xMajorLocator= FixedLocator(numpy.array(mdindex))
# 确定 X 轴的 MinorLocator
wdindex= {} # value: 每周第一个交易日在所有日期列表中的 index; key: 当周的序号 week number（当周是第几周）
for d in datelist:
isoyear, weekno= d.isocalendar()[0:2]
dmark= isoyear*100 + weekno
if dmark not in wdindex:
wdindex[dmark]= datelist.index(d)
wdindex= sorted(wdindex.values())
xMinorLocator= FixedLocator(numpy.array(wdindex))
# 确定 X 轴的 MajorFormatter 和 MinorFormatter
def x_major_formatter(idx, pos=None):
return datelist[idx].strftime('%Y-%m-%d')
def x_minor_formatter(idx, pos=None):
return datelist[idx].strftime('%m-%d')
xMajorFormatter= FuncFormatter(x_major_formatter)
xMinorFormatter= FuncFormatter(x_minor_formatter)
return {'xMajorLocator': xMajorLocator,
'xMinorLocator': xMinorLocator,
'xMajorFormatter': xMajorFormatter,
'xMinorFormatter': xMinorFormatter,
'mdindex': mdindex,
'wdindex': wdindex
}
def _compute_xparams_fullspan(self):
'''
主要坐标点是每季第一个交易日，辅助坐标点是每月第一个交易日。是给宏观子图用的。
'''
quotes= self._pdata[u'行情']
datelist= [ datetime.date(int(ys), int(ms), int(ds)) for ys, ms, ds in [ dstr.split('-') for dstr in quotes[u'日期'] ] ]
# 确定 X 轴的 MinorLocator
mdindex= [] # 每个月第一个交易日在所有日期列表中的 index
sdindex= [] # 每季度第一个交易日在所有日期列表中的 index
ydindex= [] # 每年第一个交易日在所有日期列表中的 index
allyears= set([d.year for d in datelist]) # 所有的交易年份
for yr in sorted(allyears):
allmonths= set([d.month for d in datelist if d.year == yr]) # 当年所有的交易月份
for mon in sorted(allmonths):
monthday= min([dt for dt in datelist if dt.year==yr and dt.month==mon]) # 当月的第一个交易日
idx= datelist.index(monthday)
if mon in (1, 4, 7, 10):
sdindex.append(idx)
if mon == 1:
ydindex.append(idx)
else:
mdindex.append(idx)
xMajorLocator= FixedLocator(numpy.array(sdindex))
xMinorLocator= FixedLocator(numpy.array(mdindex))
# 确定 X 轴的 MajorFormatter 和 MinorFormatter
def x_major_formatter(idx, pos=None):
return datelist[idx].strftime('%Y-%m-%d')
def x_minor_formatter(idx, pos=None):
return datelist[idx].strftime('%m-%d')
xMajorFormatter= FuncFormatter(x_major_formatter)
xMinorFormatter= FuncFormatter(x_minor_formatter)
return {'xMajorLocator': xMajorLocator,
'xMinorLocator': xMinorLocator,
'xMajorFormatter': xMajorFormatter,
'xMinorFormatter': xMinorFormatter,
'sdindex': sdindex,
'mdindex': mdindex,
'ydindex': ydindex
}
def plot(self):
'''
'''
# self.plot_title()
# 调用子图对象的绘图函数
if 'basic' in self._subplots:
self._subplots['basic'].plot()
if 'price' in self._subplots:
self._subplots['price'].plot()
if 'torate' in self._subplots:
self._subplots['torate'].plot()
if 'pricefs' in self._subplots:
self._subplots['pricefs'].plot()
if 'toratefs' in self._subplots:
self._subplots['toratefs'].plot()
def plot_title(self):
'''
绘制整个 Figure 的标题
'''
info= self._pdata[u'公司信息']
figobj= self._Fig
# 整个 figure 的标题
subtitle= (info[u'代码'] + ' ' if u'代码' in info else '') + info[u'简称']
subtitle_2= (info[u'代码二'] + ' ' if u'代码二' in info else '') + info[u'简称二']
figobj.suptitle(subtitle + ' / ' + subtitle_2, fontsize=12, fontproperties=__font_properties__)
def savefig(self, figpath):
'''
保存图片
'''
self._Fig.savefig(figpath, dpi=self._figdpi, facecolor=self._figfacecolor, edgecolor=self._figedgecolor, linewidth=self._figlinewidth)
if __name__ == '__main__':
# pfile 指明存放绘图数据的 pickle file，figpath 指定图片需存放的路径
pfile= sys.argv[1]
figpath= sys.argv[2]
# 绘图数据 pdata
fileobj= open(name=pfile, mode='rb')
pdata= pickle.load(fileobj)
fileobj.close()
os.remove(pfile)
myfig= MyFigure(pdata=pdata)
myfig.plot()
myfig.savefig(figpath=figpath)