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figureCanvas.py
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figureCanvas.py
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# This Python file uses the following encoding: utf-8
# if __name__ == "__main__":
# pass
#matplotlib.use('QtAgg') #指定渲染后端。QtAgg后端指用Agg二维图形库在Qt控件上绘图。
from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas
#使用matplotlib中的FigureCanvas(继承自QtWidgets.QWidget)绘制图形可以嵌入QT GUI
import mplfinance as mpf
import pandas as pd
import time
title_font = {'fontname': 'SimHei',
'size': '16',
'color': 'black',
'weight': 'bold',
'va': 'bottom',
'ha': 'center'}
large_red_font = {'fontname': 'Arial',
'size': '24',
'color': 'red',
'weight': 'bold',
'va': 'bottom'}
# 绿色数字格式（显示开盘收盘价）粗体绿色24号字
large_green_font = {'fontname': 'Arial',
'size': '24',
'color': 'green',
'weight': 'bold',
'va': 'bottom'}
# 小数字格式（显示其他价格信息）粗体红色12号字
small_red_font = {'fontname': 'Arial',
'size': '12',
'color': 'red',
'weight': 'bold',
'va': 'bottom'}
# 小数字格式（显示其他价格信息）粗体绿色12号字
small_green_font = {'fontname': 'Arial',
'size': '12',
'color': 'green',
'weight': 'bold',
'va': 'bottom'}
# 标签格式，可以显示中文，普通黑色12号字
normal_label_font = {'fontname': 'SimHei',
'size': '12',
'color': 'black',
'va': 'bottom',
'ha': 'right'}
# 普通文本格式，普通黑色12号字
normal_font = {'fontname': 'Arial',
'size': '12',
'color': 'black',
'va': 'bottom',
'ha': 'left'}
class Figure_Canvas(FigureCanvas):
def __init__(self,code,freq,data,name,industry,parent=None,width=17,height=9.7,dpi=100):
my_color=mpf.make_marketcolors(up='r',
down='g',
edge='inherit',
wick='inherit',
volume='inherit'
)
my_style=mpf.make_mpf_style(base_mpf_style='blueskies',
#marketcolors=my_color,
figcolor='(0.82, 0.83, 0.85)',
gridcolor='(0.82, 0.83, 0.85)')
self.style=my_style
self.fig=mpf.figure(style=my_style,figsize=(width,height),facecolor=(0.82, 0.83, 0.85))
fig=self.fig
#显示鼠标位置信息
# 添加三个图表，四个数字分别代表图表左下角在figure中的坐标，以及图表的宽（0.88）、高（0.60）
self.ax1 = fig.add_axes([0.06, 0.25, 0.88, 0.60])
#添加第二、三张图表时，使用sharex关键字指明与ax1在x轴上对齐，且共用x轴
self.ax2 = fig.add_axes([0.06, 0.15, 0.88, 0.10], sharex=self.ax1)
self.ax3 = fig.add_axes([0.06, 0.05, 0.88, 0.10], sharex=self.ax1)
# 设置三张图表的Y轴标签
#self.ax1.set_ylabel('Price')
#self.ax2.set_ylabel('Volume')
FigureCanvas.__init__(self,fig)
self.setParent(parent)
self.Title=self.fig.text(0.50, 0.94, code,title_font)
self.init(code,freq,data,name,industry)
self.detailed_data()
fig.text(0.12, 0.90, '开/收: ', normal_label_font)
fig.text(0.40, 0.90, '涨幅: ', normal_label_font)
fig.text(0.40, 0.86, '换手: ', normal_label_font)
fig.text(0.55, 0.90, '高: ', normal_label_font)
fig.text(0.55, 0.86, '低：', normal_label_font)
fig.text(0.70, 0.90, '量(万股): ', normal_label_font)
fig.text(0.70, 0.86, '额(千万元): ', normal_label_font)
fig.text(0.85, 0.90, 'PE(滚): ', normal_label_font)
fig.text(0.85, 0.86, '前收: ', normal_label_font)
self.Title.set_text(self.stock_code+' '+self.name+'('+self.interval+')'+self.industry)
#fig.canvas.mpl_connect('button_press_event',self.on_press)
#fig.canvas.mpl_connect('button_release_event',self.on_release)
fig.canvas.mpl_connect('motion_notify_event',self.on_motion)
#fig.canvas.mpl_connect('scroll_event',self.on_scroll)
fig.canvas.mpl_connect('key_press_event', self.on_key_press)
def init(self,code,freq,data,name,industry):
self.freq=freq
self.stock_code=code
self.data=data
self.deal_with_data_candle()
self.name=name
self.industry=industry
self.idx_start=len(self.data_candle)
self.curInformation=len(self.data_candle)-1
self.idx_range=120
if self.idx_start<self.idx_range:
self.idx_range=self.idx_start
self.pressed = False
# 鼠标按下时的x坐标
self.xpress = None
if self.freq in ['5', '15', '30','60']:
self.interval=self.freq+'分钟均线'
else:
if self.freq=='daily':
self.interval='日线'
if self.freq=='weekly':
self.interval='周线'
if self.freq=='monthly':
self.interval='月线'
self.Title.set_text(self.stock_code+' '+self.name+'('+self.interval+')'+self.industry)
def deal_with_data_candle(self):
self.data_candle=self.data[['date','open','high','low','close','volume']]
self.data_candle.set_index('date',inplace=True)
self.data_candle = self.data_candle.rename(index=pd.Timestamp)
#data_price['date']=data_price['date'].apply(lambda x:mdates.date2num(datetime.datetime.strptime(x,'%Y-%m-%d')))
#self.data_candle = self.data_candle.astype(float)
self.data_candle['open']=pd.to_numeric(self.data_candle['open'],errors='ignore')
self.data_candle['high']=pd.to_numeric(self.data_candle['high'],errors='ignore')
self.data_candle['low']=pd.to_numeric(self.data_candle['low'],errors='ignore')
self.data_candle['close']=pd.to_numeric(self.data_candle['close'],errors='ignore')
self.data_candle['volume']=pd.to_numeric(self.data_candle['volume'],errors='ignore')
def detailed_data(self):
a=self.data.loc[self.curInformation]
a=a.apply(pd.to_numeric,errors='ignore')
if self.freq in ['5','15','30','60']:
a['date'] = pd.to_datetime(a['date'])
if a[1]<=a[2]:
self.tOpen=self.fig.text(0.14,0.89,f'{a[1]}/{a[2]}',large_red_font)
else:
self.tOpen=self.fig.text(0.14,0.89,f'{a[1]}/{a[2]}',large_green_font)
self.tTime=self.fig.text(0.14, 0.86,a[0],**normal_label_font)
if a[8]>=0:
self.tGain=self.fig.text(0.40,0.90,'%s%%'%(a[8]),small_red_font)
else:
self.tGain=self.fig.text(0.40,0.90,'%s%%'%(a[8]),small_green_font)
self.tHigh=self.fig.text(0.55,0.90,a[3],small_red_font)
self.tLow=self.fig.text(0.55,0.86,a[4],small_green_font)
self.tVolume=self.fig.text(0.70,0.90,a[5]/10000,normal_font)
self.tPreclose=self.fig.text(0.85,0.86,(a[2]/(1+a[8]/100)).round(2),normal_font)
self.tAmount=self.fig.text(0.70,0.86,(a[6]/10000000).round(4),normal_font)
self.tTurn=self.fig.text(0.40,0.86,'%s%%'%(a[10]),normal_font)
def refrash_detailed_data(self,curInformation):
a=self.data.loc[curInformation]
a=a.apply(pd.to_numeric,errors='ignore')
if self.freq in ['5','15','30','60']:
a['date'] = pd.to_datetime(a['date'])
self.Title.set_text(self.stock_code+' '+self.name+'('+self.interval+')'+self.industry)
self.tOpen.set_text(f'{a[1]}/{a[2]}')
if a[1]<=a[2]:
self.tOpen.set_color('r')
else:
self.tOpen.set_color('g')
self.tGain.set_text('%s%%'%(a[8]))
if a[8]>=0:
self.tGain.set_color('r')
else:
self.tGain.set_color('g')
self.tTime.set_text(a[0])
self.tHigh.set_text(a[3].round(2))
self.tLow.set_text(a[4].round(2))
self.tVolume.set_text(a[5]/10000)
self.tAmount.set_text((a[6]/10000000).round(4))
self.tPreclose.set_text((a[2]/(1+a[8]/100)).round(2))
self.tTurn.set_text('%s%%'%(a[10]))
def on_key_press(self,event):
scale_factor=1.0
if event.key == 'up':
scale_factor=0.8
if event.key=='down':
scale_factor=1.2
if event.key=='left':
new_start=self.idx_start-self.idx_range//4
if new_start <= self.idx_range:
new_start = self.idx_range
self.idx_start=new_start
if event.key=='right':
new_start=self.idx_start+self.idx_range//4
if new_start >= len(self.data_candle):
new_start = len(self.data_candle)
self.idx_start=new_start
self.idx_range=int(self.idx_range*scale_factor)
if self.idx_range>=self.idx_start:
self.idx_range=self.idx_start
if self.idx_range<=100:
self.idx_range=100
self.ax1.clear()
self.ax2.clear()
self.ax3.clear()
self.refrash_plot()
self.fig.canvas.draw()
def on_scroll(self,event):
if event.inaxes!=self.ax1:
return
def on_press(self,event):
if not event.inaxes==self.ax1:
return
if event.button!=1:
return
self.pressed=True
self.xpress=event.xdata
def on_release(self,event):
self.pressed=False
#dx=int(event.xdata-self.xpress)
#self.idx_start-=dx
if self.idx_start <= self.idx_range:
self.idx_start = self.idx_range
if self.idx_start >= len(self.data_candle):
self.idx_start = len(self.data_candle)
def on_motion(self,event):
if event.inaxes!=self.ax1:
#if(event.inaxes!=self.ax2):
#if(event.inaxes!=self.ax3):
return
if not self.pressed:
x=event.xdata
time.sleep(0.2)
if event.xdata==x:
self.curInformation=self.idx_start-(self.idx_range-int(event.xdata+0.5))
self.refrash_detailed_data(self.curInformation)
self.fig.canvas.draw_idle()
return
def refrash_plot(self):
all_data=self.data_candle
all_data['MA5'] = all_data['close'].rolling(window=5).mean()
all_data['MA10'] = all_data['close'].rolling(window=10).mean()
all_data['MA20'] = all_data['close'].rolling(window=20).mean()
all_data['MA60'] = all_data['close'].rolling(window=60).mean()
plot_data=all_data.iloc[self.idx_start-self.idx_range:self.idx_start]
#计算移动平均线
#talib计算macd
#import talib
#plot_data['MACD'],plot_data['MACDsignal'],plot_data['MACDhist'] = talib.MACD(plot_data.Close, fastperiod=12, slowperiod=26, signalperiod=9)
#计算macd的方式
exp12 = plot_data['close'].ewm(span=12, adjust=False).mean()
exp26 = plot_data['close'].ewm(span=26, adjust=False).mean()
macd = exp12 - exp26
signal = macd.ewm(span=9, adjust=False).mean()
histogram = macd - signal
histogram[histogram < 0] = None
histogram_positive = histogram
histogram = macd - signal
histogram[histogram >= 0] = None
histogram_negative = histogram
# 添加子图
add_plot = [
mpf.make_addplot(plot_data[['MA5','MA10','MA20','MA60']], ax=self.ax1),
mpf.make_addplot(histogram_positive, type='bar', color='red',ax=self.ax3),
mpf.make_addplot(histogram_negative, type='bar', color='green',ax=self.ax3),
mpf.make_addplot(macd, ax=self.ax3),
mpf.make_addplot(signal, ax=self.ax3)
]
self.ax3.set_ylabel('Macd')
mpf.plot(plot_data,
ax=self.ax1,
type='candle',
addplot=add_plot,
ylabel='Price', ylabel_lower='Volume',
volume=self.ax2,
style=self.style,
datetime_format='%Y-%m-%d',
tight_layout=True,
#mav=(5,10,20,60)
)