# -*- 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>, ) 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)