def DrawClosesAndVolumes(pl, closes, volumes, zz=None, avg=None, trade_index=None,\
title=None, closes_dp=None, closes_bankuai=None):
"""画closes，非df模式，
closes_dp: 大盘
closes_bankuai: 板块
"""
legend = []
pl.figure
pl.subplot(211)
if title != None:
pl.title(title, fontproperties=getFont())
pl.plot(closes)
legend.append('close')
if zz is not None:
DrawZZ(pl, zz, c='r')
if avg is not None:
pl.plot(avg)
if not agl.IsNone(closes_dp):
pl.plot(closes_dp)
legend.append('dapan')
if not agl.IsNone(closes_bankuai):
pl.plot(closes_bankuai)
legend.append('bankuai')
if trade_index != None:
pl, index, ts = pl, trade_index, closes
_DrawVLine(pl, index, ts)
pl.legend(legend, loc='upper left')
pl.subplot(212)
pl.plot(volumes)
pl.show()
pl.close()
def drawKline(pl,
df_code,
df_dp=None,
df_bk=None,
title=None,
df_syl=None,
legend2=None):
"""画个股k线图
pl: 自定义pl
df_code: 个股pd.DataFrame, ['holcv']
df_dp: 大盘
df_bk: 板块
df_syl: 历史市盈率
legend2: 标识, 不支持中文
"""
if 0: pl = plt
pl.figure
pl.subplot(211)
if title != None:
pl.title(title, fontproperties=getFont())
#画个股数据
df = copy.deepcopy(df_code)
df['c'] = df['c'] / max(df['c'])
df['v'] = df['v'] / max(df['v'])
df['c'].plot()
df2 = df['v']
legend = ['close']
if not isinstance(df_dp, type(None)) and len(df_dp) > 0:
df = copy.deepcopy(df_dp)
if isinstance(df, pd.Series):
df.plot()
else:
df['c'] = df['c'] / max(df['c'])
#df['v'] = df['v'] / max(df['v'])
df['c'].plot()
legend.append('dapan')
#df['v'].plot()
if not agl.IsNone(df_bk):
df_bk.plot()
legend.append('bankuai')
pl.legend(legend, loc='upper left')
pl.subplot(212)
df2.plot()
legend = ['volumns']
if not isinstance(df_syl, type(None)) and len(df_syl) > 0:
df = copy.deepcopy(df_syl)
#df['市盈率'] = df['市盈率'] / max(df['市盈率'])
#df['每股收益'] = df['每股收益'] / max(df['每股收益'])
##df['市盈率'].plot()
#df['每股收益'].plot()
#legend.append('mgsy')
df.plot()
legend.append('jll')
if legend2 is not None:
legend = legend2
pl.legend(legend, loc='upper left')
pl.show()
pl.close()
def drawKline(df, df_trades=None):
"""画k线图, 异步模式
需要注意的是如果df比较大的话，那么速度是相当的慢, 一般5日线10天的数据较好
df : 日线或5分钟线, cols('ohlcv')
df_trades : 交易点, 需要包含字段cols('trade_bSell', ['trade_price']), 见enum, []意思为不是必须
"""
def df_to_matplotformat(df):
"""
return: list[turpl(t,o,h,l,c)]
"""
data_list = []
for dates,row in df.iterrows():
# 将时间转换为数字
#date_time = datetime.datetime.strptime(dates,'%Y-%m-%d')
t = date2num(dates)
open,high,low,close = row[:4]
datas = (t,open,high,low,close)
data_list.append(datas)
return data_list
quotes = df_to_matplotformat(df)
plt.cla()
# 创建一个子图
#fig, ax = plt.subplots(facecolor=(0.5, 0.5, 0.5))
#fig.subplots_adjust(bottom=0.2)
ax = plt.gca()
if 0: ax = matplotlib.axes.Axes(fig, rect)
plt.subplots_adjust(bottom=0.2)
## 设置X轴刻度为日期时间
#ax.xaxis_date()
## X轴刻度文字倾斜45度
#plt.xticks(rotation=45)
#plt.title("code")
#plt.xlabel("time")
#plt.ylabel("price")
#mpf.candlestick_ohlc(ax,quotes,width=.001,colorup='r',colordown='green')
#调整下面日期显示的密度
freq = len(quotes)/20
weekday_candlestick(quotes, ax, fmt='%b %d %H:%M', freq=freq, width=0.01, colorup='r',colordown='green')
#plt.grid(True)
#画交易点
if not agl.IsNone(df_trades):
if 0:df_trades = pd.DataFrame()
for index, row in df_trades.iterrows():
if AsynDrawKline.enum.trade_price in row.keys():
price = row[AsynDrawKline.enum.trade_price]
else:
price = row['c']
#交易点
trade_position = []
a = np.zeros(len(quotes))
a[:] = price
index = len(df[:index])
a[:index] =np.nan
bSell = int(row[AsynDrawKline.enum.trade_bSell])
clr = agl.where(bSell, 'g', 'r')
plt.plot(a, color=clr, linewidth=0.25)
plt.text(len(quotes),price, str(price), color=clr)
#左右两边都有坐标
#ax.yaxis.set_ticks_position('both')
#plt.tick_params(axis='y', which='both', labelleft='on', labelright='on')
plt.draw()
plt.pause(0.1)