---- 有句话怎么说来着，“只有趋势才是你的朋友”。

    ---- 对任意一点可以辨认它所处的趋势。算法保证如果 A 点和 B 点的趋势起点都在 O，那么 A、B 之间任意一点的趋势起点也在 O 点。

    ---- 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)

---- 最新的在这里： 用 Python / Matplotlib 画出来的股票 K线图 (四)

---- 下一篇在这里： 用 Python / Matplotlib 画出来的股票 K线图 (三)

---- 上一版的改进，双股同列 + 无数细小改进，如下图。dpi= 300。明的一条是个股走势，暗的是同期的指数走势。这大概是近期最强的一只。

---- 要想培养对走势的感觉，采用固定比例尺的图形是必须的。一般股票软件里的图形都为显示方便而做了变形处理，用处不大。

---- 图形感觉差不多了，告一段落。接下来的目标是 股本结构、历史分配、行业板块、股东研究 这些信息，还包括个股资讯。实时的数据仍然暂时不碰。

---- 源码贴出来。因为 Matplotlib 还不支持 Python3, 所以单写了一个 Python2 脚本。注意绘图数据是用 pickle file 传递的。

［补记：我决定放弃线性坐标了。这个脚本只支持对数坐标。］

# -*- coding: utf-8 -*-

import os
import sys
import pickle
import math
import datetime
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 FixedLocator, MultipleLocator, FuncFormatter, NullFormatter



__font_properties__=font_manager.FontProperties(fname='/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc')
__color_lightsalmon__= '#ffa07a'
__color_pink__= '#ffc0cb'
__color_navy__= '#000080'






def Plot(pfile, figpath):
	'''
	pfile 指明存放绘图数据的 pickle file，figpath 指定图片需存放的路径
	'''

	fileobj= open(name=pfile, mode='rb')
	pdata= pickle.load(fileobj)
	fileobj.close()
	os.remove(pfile)

	#	计算图片的尺寸（单位英寸）
	#	注意：Python2 里面， "1 / 10" 结果是 0, 必须写成 "1.0 / 10" 才会得到 0.1
	#==================================================================================================================================================
	length= len(pdata[u'日期'])		# 所有数据的长度，就是天数

	open_price_pri= pdata[u'开盘'][0]	# int 类型
	open_price_sec= pdata[u'开盘二'][0]	# 同上

	highest_price_pri= max( [phigh for phigh in pdata[u'最高'] if phigh != None] )		# 第一个行情的最高价
	highest_price_sec= max( [phigh for phigh in pdata[u'最高二'] if phigh != None] )	# 第二个行情的最高价
	highest_price= max(highest_price_pri, highest_price_sec*open_price_pri/open_price_sec)	# 以第一个行情为基准修正出的总最高价
	
	lowest_price_pri= min( [plow for plow in pdata[u'最低'] if plow != None] )	# 最低价
	lowest_price_sec= min( [plow for plow in pdata[u'最低二'] if plow != None] )	# 最低价
	lowest_price= min(lowest_price_pri, lowest_price_sec*open_price_pri/open_price_sec)	# 以第一个行情为基准修正出的总最低价



	yhighlim_price= int(highest_price * 1.1)	# K线子图 Y 轴最大坐标
	ylowlim_price=  int(lowest_price / 1.1)		# K线子图 Y 轴最小坐标



	xfactor= 10.0/230.0	# 一条 K 线的宽度在 X 轴上所占距离（英寸）
	yfactor= 0.3	# Y 轴上每一个距离单位的长度（英寸），这个单位距离是线性坐标和对数坐标通用的

	expbase= 1.1	# 底数，取得小一点，比较接近 1。股价 3 元到 4 元之间有大约 3 个单位距离
	
	# 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。
	ymulti_price= math.log(yhighlim_price, expbase)	- math.log(ylowlim_price, expbase)	
	
	ymulti_vol= 3.0		# 成交量部分在 Y 轴所占的 “份数”
	ymulti_top= 1.2		# 顶部空白区域在 Y 轴所占的 “份数”
	ymulti_bot= 1.2		# 底部空白区域在 Y 轴所占的 “份数”

	xmulti_left= 12.0	# 左侧空白区域所占的 “份数”
	xmulti_right= 12.0	# 右侧空白区域所占的 “份数”

	xmulti_all= length + xmulti_left + xmulti_right
	xlen_fig= xmulti_all * xfactor		# 整个 Figure 的宽度
	ymulti_all= ymulti_price + ymulti_vol + ymulti_top + ymulti_bot
	ylen_fig= ymulti_all * yfactor		# 整个 Figure 的高度
	
	rect_1= (xmulti_left/xmulti_all, (ymulti_bot+ymulti_vol)/ymulti_all, length/xmulti_all, ymulti_price/ymulti_all)	# K线图部分
	rect_2= (xmulti_left/xmulti_all, ymulti_bot/ymulti_all, length/xmulti_all, ymulti_vol/ymulti_all)	# 成交量部分



	#	建立 Figure 对象
	#==================================================================================================================================================
	figfacecolor= __color_pink__
	figedgecolor= __color_navy__
	figdpi= 300
	figlinewidth= 1.0

	figobj= pyplot.figure(figsize=(xlen_fig, ylen_fig), dpi=figdpi, facecolor=figfacecolor, edgecolor=figedgecolor, linewidth=figlinewidth)	# Figure 对象

	# 整个 figure 的标题
	title_pri= (pdata[u'代码'] + ' ' if u'代码' in pdata else '') + pdata[u'简称']
	title_sec= (pdata[u'代码二'] + '   ' if u'代码二' in pdata else '') + pdata[u'简称二']
	
	figobj.suptitle(title_pri + ' / ' + title_sec, fontsize=12, fontproperties=__font_properties__)



	#==================================================================================================================================================
	#==================================================================================================================================================
	#=======	
	#=======	XXX: 第一只：成交量部分
	#=======	
	#==================================================================================================================================================
	#==================================================================================================================================================

	#	第一只：添加 Axes 对象
	#==================================================================================================================================================
	axes_2= figobj.add_axes(rect_2, axis_bgcolor='black')
	axes_2.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_2.get_children():
		if isinstance(child, matplotlib.spines.Spine):
			child.set_color('lightblue')

	#	第一只：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()

	#	第一只：设置两个坐标轴上的 grid
	#==================================================================================================================================================
	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)



	#==================================================================================================================================================
	#=======	第一只：成交量绘图
	#==================================================================================================================================================
	xindex= numpy.arange(length)	# X 轴上的 index，一个辅助数据

	zipoc= zip(pdata[u'开盘'], pdata[u'收盘'])
	up=   numpy.array( [ True if po < pc and po != None else False for po, pc in zipoc] )		# 标示出该天股价日内上涨的一个序列
	down= numpy.array( [ True if po > pc and po != None else False for po, pc in zipoc] )		# 标示出该天股价日内下跌的一个序列
	side= numpy.array( [ True if po == pc and po != None else False for po, pc in zipoc] )		# 标示出该天股价日内走平的一个序列



	if u'成交额' in pdata:
		volume= pdata[u'成交额']
	else:
		volume= pdata[u'成交量']

	rarray_vol= numpy.array(volume)
	volzeros= numpy.zeros(length)	# 辅助数据

	# XXX: 如果 up/down/side 各项全部为 False，那么 vlines() 会报错。
	if True in up:
		axes_2.vlines(xindex[up], volzeros[up], rarray_vol[up], edgecolor='red', linewidth=3.0, label='_nolegend_')
	if True in down:
		axes_2.vlines(xindex[down], volzeros[down], rarray_vol[down], edgecolor='green', linewidth=3.0, label='_nolegend_')
	if True in side:
		axes_2.vlines(xindex[side], volzeros[side], rarray_vol[side], edgecolor='0.7', linewidth=3.0, label='_nolegend_')
	


	#	第一只：设定 X 轴坐标的范围 
	#==================================================================================================================================================
	axes_2.set_xlim(-1, length)



	#	第一只：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 pdata[u'日期'] ] ]

	# 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
	years= set([d.year for d in datelist])	# 所有的交易年份

	for y in sorted(years):		
		months= set([d.month for d in datelist if d.year == y])		# 当年所有的交易月份
		for m in sorted(months):
			monthday= min([dt for dt in datelist if dt.year==y and dt.month==m])	# 当月的第一个交易日
			mdindex.append(datelist.index(monthday))

	xMajorLocator= FixedLocator(numpy.array(mdindex))

	# 第一只：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)

	xMinorLocator= FixedLocator(numpy.array( sorted(wdindex.values()) ))

	# 第一只：确定 X 轴的 MajorFormatter 和 MinorFormatter
	def x_major_formatter_2(idx, pos=None):
		return datelist[idx].strftime('%Y-%m-%d')

	def x_minor_formatter_2(idx, pos=None):
		return datelist[idx].strftime('%m-%d')

	xMajorFormatter= FuncFormatter(x_major_formatter_2)
	xMinorFormatter= FuncFormatter(x_minor_formatter_2)

	# 第一只：设定 X 轴的 Locator 和 Formatter
	xaxis_2.set_major_locator(xMajorLocator)
	xaxis_2.set_major_formatter(xMajorFormatter)

	xaxis_2.set_minor_locator(xMinorLocator)
	xaxis_2.set_minor_formatter(xMinorFormatter)

	# 第一只：设定 X 轴主要坐标点与辅助坐标点的样式
	for malabel in axes_2.get_xticklabels(minor=False):
		malabel.set_fontsize(4)
		malabel.set_horizontalalignment('right')
		malabel.set_rotation('45')

	for milabel in axes_2.get_xticklabels(minor=True):
		milabel.set_fontsize(4)
		milabel.set_color('blue')
		milabel.set_horizontalalignment('right')
		milabel.set_rotation('45')



	#	第一只：设定成交量 Y 轴坐标的范围 
	#==================================================================================================================================================
	maxvol= max(volume)	# 注意是 int 类型
	axes_2.set_ylim(0, maxvol)



	#	第一只：设定成交量 Y 轴上的坐标
	#==================================================================================================================================================
	vollen= len(str(maxvol))
	
	volstep_pri= int(round(maxvol/10.0+5000, -4))
	
	yMajorLocator_2= MultipleLocator(volstep_pri)



	# 第一只：确定 Y 轴的 MajorFormatter
	dimsuffix= u'元' if u'成交额' in pdata else u'股'
	def y_major_formatter_2(num, pos=None):
		if num >= 10**8:	# 大于 1 亿
			return (str(round(num/10.0**8, 2)) + u'亿' + dimsuffix) if num != 0 else '0'
		else:
			return (str(num/10.0**4) + u'万' + dimsuffix) if num != 0 else '0'

	#	def y_major_formatter_2(num, pos=None):
	#		return int(num)
	yMajorFormatter_2= FuncFormatter(y_major_formatter_2)

	# 确定 Y 轴的 MinorFormatter
	#	def y_minor_formatter_2(num, pos=None):
	#		return int(num)
	#	yMinorFormatter_2= FuncFormatter(y_minor_formatter_2)
	yMinorFormatter_2= NullFormatter()

	# 第一只：设定 X 轴的 Locator 和 Formatter
	yaxis_2.set_major_locator(yMajorLocator_2)
	yaxis_2.set_major_formatter(yMajorFormatter_2)

	#	yaxis_2.set_minor_locator(yMinorLocator_2)
	yaxis_2.set_minor_formatter(yMinorFormatter_2)

	# 第一只：设定 Y 轴主要坐标点与辅助坐标点的样式
	for malab in axes_2.get_yticklabels(minor=False):
		malab.set_font_properties(__font_properties__)
		malab.set_fontsize(4.5)	# 这个必须放在前一句后面，否则作用会被覆盖
	


	#	第一只：成交量数值在图中间的显示
	#==================================================================================================================================================
	for iy in range(volstep_pri, maxvol, volstep_pri):
		for ix in mdindex[1:-1:3]:
			newlab= axes_2.text(ix+8, iy, y_major_formatter_2(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')



	#==================================================================================================================================================
	#==================================================================================================================================================
	#=======	
	#=======	XXX: 第二条成交量图线
	#=======	
	#==================================================================================================================================================
	#==================================================================================================================================================

	#	添加 Axes 对象
	#==================================================================================================================================================
	axes_2_sec= axes_2.twinx()
	#	axes_2_sec.set_axisbelow(True)	# 网格线放在底层
	
	axes_2_sec.set_axisbelow(True)	# 网格线放在底层

	#	改变坐标线的颜色
	#==================================================================================================================================================
	#	for child in axes_2_sec.get_children():
	#		if isinstance(child, matplotlib.spines.Spine):
	#			child.set_color('lightblue')

	#	得到 X 轴 和 Y 轴 的两个 Axis 对象
	#==================================================================================================================================================
	xaxis_2_sec= axes_2_sec.get_xaxis()
	yaxis_2_sec= axes_2_sec.get_yaxis()

	#	设置两个坐标轴上的 grid
	#==================================================================================================================================================
	#	xaxis_2_sec.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
	#	xaxis_2_sec.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)

	#	yaxis_2_sec.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
	#	yaxis_2_sec.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)



	#==================================================================================================================================================
	#=======	绘图
	#==================================================================================================================================================

	if u'成交额二' in pdata:
		volume_sec= pdata[u'成交额二']
	else:
		volume_sec= pdata[u'成交量二']

	zipoc_sec= zip(pdata[u'开盘二'], pdata[u'收盘二'])
	up_sec=   numpy.array( [ True if po < pc and po != None else False for po, pc in zipoc_sec] )		# 标示出该天股价日内上涨的一个序列
	down_sec= numpy.array( [ True if po > pc and po != None else False for po, pc in zipoc_sec] )		# 标示出该天股价日内下跌的一个序列
	side_sec= numpy.array( [ True if po == pc and po != None else False for po, pc in zipoc_sec] )		# 标示出该天股价日内走平的一个序列
	
	rarray_vol_sec= numpy.array(volume_sec)
	volzeros_sec= numpy.zeros(length)	# 辅助数据

	# XXX: 如果 up_sec/down_sec/side_sec 各项全部为 False，那么 vlines() 会报错。
	if True in up_sec:
		axes_2_sec.vlines(xindex[up_sec], volzeros_sec[up_sec], rarray_vol_sec[up_sec], edgecolor='pink', linewidth=1.0, label='_nolegend_', alpha=0.3)
	if True in down_sec:
		axes_2_sec.vlines(xindex[down_sec], volzeros_sec[down_sec], rarray_vol_sec[down_sec], edgecolor='lightgreen', linewidth=1.0, label='_nolegend_', alpha=0.3)
	if True in side_sec:
		axes_2_sec.vlines(xindex[side_sec], volzeros_sec[side_sec], rarray_vol_sec[side_sec], edgecolor='0.7', linewidth=1.0, label='_nolegend_', alpha=0.3)
	


	#	设定 X 轴坐标的范围 
	#==================================================================================================================================================
	#	XXX: 不用了，与 axes_2 共用。


	#	设定 Y 轴坐标的范围 
	#==================================================================================================================================================
	maxvol_sec= max(volume_sec)	# 注意是 int 类型
	axes_2_sec.set_ylim(0, maxvol_sec)



	#	设定 Y 轴上的坐标
	#==================================================================================================================================================
	
	volstep_sec= volstep_pri*maxvol_sec/float(maxvol)
	yMajorLocator_2_sec= MultipleLocator(volstep_sec)

	# 确定 Y 轴的 MajorFormatter
	dimsuffix_sec= u'元' if u'成交额二' in pdata else u'股'
	def y_major_formatter_2_sec(num, pos=None):
		if num >= 10**8:	# 大于 1 亿
			print(('num= ' + str(num) + ', result= ' + str(round(num/10.0**8, 3)) + u'亿' + dimsuffix_sec).encode('utf8'))
			
			return (str(round(num/10.0**8, 3)) + u'亿' + dimsuffix_sec) if num != 0 else '0'
		else:
			return (str(round(num/10.0**4, 2)) + u'万' + dimsuffix_sec) if num != 0 else '0'

	#	def y_major_formatter_2_sec(num, pos=None):
	#		return int(num)
	yMajorFormatter_2_sec= FuncFormatter(y_major_formatter_2_sec)

	# 确定 Y 轴的 MinorFormatter
	#	def y_minor_formatter_2(num, pos=None):
	#		return int(num)
	#	yMinorFormatter_2_sec= FuncFormatter(y_minor_formatter_2)
	yMinorFormatter_2_sec= NullFormatter()

	# 设定 X 轴的 Locator 和 Formatter
	yaxis_2_sec.set_major_locator(yMajorLocator_2_sec)
	yaxis_2_sec.set_major_formatter(yMajorFormatter_2_sec)

	#	yaxis_2_sec.set_minor_locator(yMinorLocator_2_sec)
	yaxis_2_sec.set_minor_formatter(yMinorFormatter_2_sec)

	# 设定 Y 轴主要坐标点与辅助坐标点的样式
	for malab in axes_2_sec.get_yticklabels(minor=False):
		malab.set_font_properties(__font_properties__)
		malab.set_fontsize(4.5)	# 这个必须放在前一句后面，否则作用会被覆盖
	




	#==================================================================================================================================================
	#==================================================================================================================================================
	#=======	
	#=======	XXX: K 线图部分
	#=======	
	#==================================================================================================================================================
	#==================================================================================================================================================

	#	添加 Axes 对象
	#==================================================================================================================================================
	axes_1= figobj.add_axes(rect_1, axis_bgcolor='black', sharex=axes_2)
	axes_1.set_axisbelow(True)	# 网格线放在底层
	
	axes_1.set_yscale('log', basey=expbase)		# 使用对数坐标
	
	#	改变坐标线的颜色
	#==================================================================================================================================================
	for child in axes_1.get_children():
		if isinstance(child, matplotlib.spines.Spine):
			child.set_color('lightblue')

	#	得到 X 轴 和 Y 轴 的两个 Axis 对象
	#==================================================================================================================================================
	xaxis_1= axes_1.get_xaxis()
	yaxis_1= axes_1.get_yaxis()

	#	设置两个坐标轴上的 grid
	#==================================================================================================================================================
	xaxis_1.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
	xaxis_1.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)

	yaxis_1.grid(True, 'major', color='0.3', linestyle='solid', linewidth=0.2)
	yaxis_1.grid(True, 'minor', color='0.3', linestyle='dotted', linewidth=0.1)



	#==================================================================================================================================================
	#=======	绘图
	#==================================================================================================================================================

	#	绘制 K 线部分
	#==================================================================================================================================================
	
	#	对开收盘价进行视觉修正
	for idx, poc in enumerate( zip(pdata[u'开盘'], pdata[u'收盘']) ):
		if poc[0] == poc[1] and None not in poc:
			variant= round((poc[1]+1000)/2000, 0)
			pdata[u'开盘'][idx]= poc[0] - variant		# 稍微偏离一点，使得在图线上不致于完全看不到
			pdata[u'收盘'][idx]= poc[1] + variant

	rarray_open= numpy.array(pdata[u'开盘'])
	rarray_close= numpy.array(pdata[u'收盘'])
	rarray_high= numpy.array(pdata[u'最高'])
	rarray_low= numpy.array(pdata[u'最低'])

	# 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_1.vlines(xindex[up], rarray_low[up], rarray_high[up], edgecolor='red', linewidth=0.6, label='_nolegend_')		
		axes_1.vlines(xindex[up], rarray_open[up], rarray_close[up], edgecolor='red', linewidth=3.0, label='_nolegend_')

	if True in down:
		axes_1.vlines(xindex[down], rarray_low[down], rarray_high[down], edgecolor='green', linewidth=0.6, label='_nolegend_')
		axes_1.vlines(xindex[down], rarray_open[down], rarray_close[down], edgecolor='green', linewidth=3.0, label='_nolegend_')

	if True in side:
		axes_1.vlines(xindex[side], rarray_low[side], rarray_high[side], edgecolor='0.7', linewidth=0.6, label='_nolegend_')
		axes_1.vlines(xindex[side], rarray_open[side], rarray_close[side], edgecolor='0.7', linewidth=3.0, label='_nolegend_')

	#	绘制均线部分
	#==================================================================================================================================================
	if u'5日均' in pdata:
		rarray_5dayave= numpy.array(pdata[u'5日均'])
		axes_1.plot(xindex, rarray_5dayave, 'o-', color='white', linewidth=0.1, label='ave_5', \
			markersize=0.7, markeredgecolor='white', markeredgewidth=0.1)	# 5日均线
	
	if u'10日均' in pdata:
		rarray_10dayave= numpy.array(pdata[u'10日均'])
		axes_1.plot(xindex, rarray_10dayave, 'o-', color='yellow', linewidth=0.1, label='ave_10', \
			markersize=0.7, markeredgecolor='yellow', markeredgewidth=0.1)	# 10日均线
	
	if u'30日均' in pdata:
		rarray_30dayave= numpy.array(pdata[u'30日均'])
		axes_1.plot(xindex, rarray_30dayave, 'o-', color='cyan', linewidth=0.1, label='ave_30', \
			markersize=0.7, markeredgecolor='cyan', markeredgewidth=0.1)	# 30日均线



	#	绘制 复权提示
	#==================================================================================================================================================
	if u'复权' in pdata:
		adjdict= dict(pdata[u'复权'])
		
		for idx, dstr in enumerate(pdata[u'日期']):
			if dstr in adjdict:
				axes_1.plot([idx, idx], [ylowlim_price, yhighlim_price], '-', color='purple', linewidth=0.3)
	




	#	设定 X 轴坐标的范围 
	#==================================================================================================================================================
	axes_1.set_xlim(-1, length)



	#	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_1.set_major_locator(xMajorLocator)
	xaxis_1.set_major_formatter(xMajorFormatter)

	xaxis_1.set_minor_locator(xMinorLocator)
	xaxis_1.set_minor_formatter(xMinorFormatter)

	# 将 X 轴上的坐标设为不可见。
	for malab in axes_1.get_xticklabels(minor=False):
		malab.set_visible(False)

	for milab in axes_1.get_xticklabels(minor=True):
		milab.set_visible(False)

	# 用这一段效果也一样
	#	pyplot.setp(axes_1.get_xticklabels(minor=False), visible=False)
	#	pyplot.setp(axes_1.get_xticklabels(minor=True), visible=False)



	#	设定 Y 轴坐标的范围 
	#==================================================================================================================================================
	axes_1.set_ylim(ylowlim_price, yhighlim_price)



	#	设定 Y 轴上的坐标
	#==================================================================================================================================================
	
	# XXX: 不用 LogLocator 了，因为不能控制坐标点的位置。

	#	主要坐标点
	#----------------------------------------------------------------------------
	yticks_major_pri= []
	for i in range(1, 999):
		newloc= ylowlim_price * (expbase**i)
		if newloc <= yhighlim_price:
			yticks_major_pri.append(newloc)
		else:
			break

	yMajorLocator_1= FixedLocator(numpy.array(yticks_major_pri))

	# 确定 Y 轴的 MajorFormatter
	def y_major_formatter_1(num, pos=None):
		return str(round(num/1000.0, 2))
	
	yMajorFormatter_1= FuncFormatter(y_major_formatter_1)

	# 设定 X 轴的 Locator 和 Formatter
	yaxis_1.set_major_locator(yMajorLocator_1)
	yaxis_1.set_major_formatter(yMajorFormatter_1)

	# 设定 Y 轴主要坐标点与辅助坐标点的样式
	for mal in axes_1.get_yticklabels(minor=False):
		mal.set_fontsize(6)
	
	

	#	辅助坐标点
	#----------------------------------------------------------------------------
	yticks_minor_pri= []
	mtstart= ylowlim_price * (1.0+(expbase-1.0)/2)
	for i in range(999):
		newloc= mtstart * (expbase**i)
		if newloc <= yhighlim_price:
			yticks_minor_pri.append(newloc)
		else:
			break

	yMinorLocator_1= FixedLocator(numpy.array(yticks_minor_pri))		# 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_1(num, pos=None):
		return str(round(num/1000.0, 2))
		
	yMinorFormatter_1= FuncFormatter(y_minor_formatter_1)
	
	# 设定 X 轴的 Locator 和 Formatter
	yaxis_1.set_minor_locator(yMinorLocator_1)
	yaxis_1.set_minor_formatter(yMinorFormatter_1)
	# 设定 Y 轴主要坐标点与辅助坐标点的样式
	for mal in axes_1.get_yticklabels(minor=True):
		mal.set_fontsize(5)
		mal.set_color('blue')



	#	第一只：价格数值在图中间的显示
	#==================================================================================================================================================
	for iy in yticks_major_pri:
		for ix in mdindex[1:-1:3]:
			newlab= axes_1.text(ix+8, iy*1.001, y_major_formatter_1(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')



	#	第一只：日期在图中间的显示
	#==================================================================================================================================================
	for iy in yticks_minor_pri[1:-1:5]:
		for ix in mdindex:
			newlab= axes_1.text(ix-1, iy, pdata[u'日期'][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_zorder(0)		# XXX: 放在底层
			#	newlab.set_verticalalignment('center')



	#==================================================================================================================================================
	#==================================================================================================================================================
	#=======	
	#=======	XXX: 第二条 K 线图
	#=======	
	#==================================================================================================================================================
	#==================================================================================================================================================

	#	添加 Axes 对象
	#==================================================================================================================================================
	axes_1_sec= axes_1.twinx()
	#	axes_1_sec.set_axisbelow(True)	# 网格线放在底层
	
	axes_1_sec.set_yscale('log', basey=expbase)	# 使用对数坐标


	#	得到 X 轴 和 Y 轴 的两个 Axis 对象
	#==================================================================================================================================================
	xaxis_1_sec= axes_1_sec.get_xaxis()
	yaxis_1_sec= axes_1_sec.get_yaxis()



	#==================================================================================================================================================
	#=======	绘图
	#==================================================================================================================================================

	#	绘制 K 线部分
	#==================================================================================================================================================
	
	#	对开收盘价进行视觉修正
	for idx, poc in enumerate( zipoc_sec ):
		if poc[0] == poc[1] and None not in poc:
			pdata[u'开盘二'][idx]= poc[0] - 5		# 稍微偏离一点，使得在图线上不致于完全看不到
			pdata[u'收盘二'][idx]= poc[1] + 5		
	
	rarray_open= numpy.array(pdata[u'开盘二'])
	rarray_close= numpy.array(pdata[u'收盘二'])
	rarray_high= numpy.array(pdata[u'最高二'])
	rarray_low= numpy.array(pdata[u'最低二'])

	# XXX: 如果 up_sec, down_sec, side_sec 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_sec:
		axes_1_sec.vlines(xindex[up_sec], rarray_low[up_sec], rarray_high[up_sec], edgecolor='red', linewidth=0.6, label='_nolegend_', alpha=0.3)
		axes_1_sec.vlines(xindex[up_sec], rarray_open[up_sec], rarray_close[up_sec], edgecolor='red', linewidth=3.0, label='_nolegend_', alpha=0.3)

	if True in down_sec:
		axes_1_sec.vlines(xindex[down_sec], rarray_low[down_sec], rarray_high[down_sec], edgecolor='green', linewidth=0.6, label='_nolegend_', alpha=0.3)
		axes_1_sec.vlines(xindex[down_sec], rarray_open[down_sec], rarray_close[down_sec], edgecolor='green', linewidth=3.0, label='_nolegend_', alpha=0.3)

	if True in side_sec:
		axes_1_sec.vlines(xindex[side_sec], rarray_low[side_sec], rarray_high[side_sec], edgecolor='0.7', linewidth=0.6, label='_nolegend_', alpha=0.3)
		axes_1_sec.vlines(xindex[side_sec], rarray_open[side_sec], rarray_close[side_sec], edgecolor='0.7', linewidth=3.0, label='_nolegend_', alpha=0.3)



	#	设定 X 轴坐标的范围 
	#==================================================================================================================================================
	axes_1_sec.set_xlim(-1, length)



	#	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_1_sec.set_major_locator(xMajorLocator)
	xaxis_1_sec.set_major_formatter(xMajorFormatter)

	xaxis_1_sec.set_minor_locator(xMinorLocator)
	xaxis_1_sec.set_minor_formatter(xMinorFormatter)

	# 将 X 轴上的坐标设为不可见。
	for malab in axes_1_sec.get_xticklabels(minor=False):
		malab.set_visible(False)

	for milab in axes_1_sec.get_xticklabels(minor=True):
		milab.set_visible(False)



	#	设定 Y 轴坐标的范围 
	#==================================================================================================================================================
	axes_1_sec.set_ylim(ylowlim_price*open_price_sec/open_price_pri, yhighlim_price*open_price_sec/open_price_pri)



	#	设定 Y 轴上的坐标
	#==================================================================================================================================================
	
	#	主要坐标点
	#----------------------------------------------------------------------------
	yticks_major_sec= []
	ylowlim_price_sec=  ylowlim_price*open_price_sec/open_price_pri
	yhighlim_price_sec= yhighlim_price*open_price_sec/open_price_pri
	
	for i in range(1, 999):
		newloc= ylowlim_price_sec * (expbase**i)
		if newloc <= yhighlim_price_sec:
			yticks_major_sec.append(newloc)
		else:
			break

	yMajorLocator_1_sec= FixedLocator(numpy.array(yticks_major_sec))

	# 确定 Y 轴的 MajorFormatter
	def y_major_formatter_1_sec(num, pos=None):
		return str(round(num/1000.0, 2))
	
	yMajorFormatter_1_sec= FuncFormatter(y_major_formatter_1_sec)

	# 设定 X 轴的 Locator 和 Formatter
	yaxis_1_sec.set_major_locator(yMajorLocator_1_sec)
	yaxis_1_sec.set_major_formatter(yMajorFormatter_1_sec)

	# 设定 Y 轴主要坐标点与辅助坐标点的样式
	for mal in axes_1_sec.get_yticklabels(minor=False):
		mal.set_fontsize(6)
	
	

	#	辅助坐标点
	#----------------------------------------------------------------------------
	yticks_minor_sec= []
	mtstart_sec= ylowlim_price_sec * (1.0+(expbase-1.0)/2)
	for i in range(999):
		newloc= mtstart_sec * (expbase**i)
		if newloc <= yhighlim_price_sec:
			yticks_minor_sec.append(newloc)
		else:
			break

	yMinorLocator_1_sec= FixedLocator(numpy.array(yticks_minor_sec))		# 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_1_sec(num, pos=None):
		return str(round(num/1000.0, 2))
		
	yMinorFormatter_1_sec= FuncFormatter(y_minor_formatter_1_sec)
	
	# 设定 X 轴的 Locator 和 Formatter
	yaxis_1_sec.set_minor_locator(yMinorLocator_1_sec)
	yaxis_1_sec.set_minor_formatter(yMinorFormatter_1_sec)
	# 设定 Y 轴主要坐标点与辅助坐标点的样式
	for mal in axes_1_sec.get_yticklabels(minor=True):
		mal.set_fontsize(5)
		mal.set_color('blue')



	#	显示图片
	#==================================================================================================================================================
	#	pyplot.show()

	#	保存图片
	#==================================================================================================================================================
	figobj.savefig(figpath, dpi=figdpi, facecolor=figfacecolor, edgecolor=figedgecolor, linewidth=figlinewidth)



if __name__ == '__main__':
	Plot(pfile=sys.argv[1], figpath=sys.argv[2])