def get_stock_data(start_date, end_date):
ris = RIndexStock(ct.OUT_DB_INFO, redis_host='127.0.0.1')
return ris.get_k_data_in_range(start_date, end_date)
class MarauderMap():
def __init__(self):
self.ris = RIndexStock()
self.logger = getLogger(__name__)
def get_data(self, mdate):
return self.ris.get_data(mdate)
def plot(self, cdate, fdir, fname):
df = self.ris.get_data(cdate)
if df.empty: return
fig, ax = plt.subplots()
#get min profit day
min_pday = df.pday.values.min()
max_pday = df.pday.values.max()
#get max profit day
min_profit = df.profit.values.min()
max_profit = df.profit.values.max()
#set axis for map
xmax = max(abs(min_pday), max_pday)
ymax = max(abs(min_profit), max_profit)
ax.set_xlim(-xmax, xmax)
ax.set_ylim(-ymax, ymax)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
for code in df.code.tolist():
pday = df.loc[df.code == code, 'pday']
profit = df.loc[df.code == code, 'profit']
ax.scatter(pday, profit, s=5, alpha=1, linewidths=0.1)
plt.savefig('%s/%s.png' % (fdir, fname), dpi=1000)
def gen_animation(self, end_date, days):
import matplotlib.animation as animation
matplotlib.use('Agg')
start_date = get_day_nday_ago(end_date, num=days, dformat="%Y-%m-%d")
df = self.ris.get_k_data_in_range(start_date, end_date)
fig, ax = plt.subplots()
#get min profit day
min_pday = df.pday.values.min()
max_pday = df.pday.values.max()
#get max profit day
min_profit = df.profit.values.min()
max_profit = df.profit.values.max()
#set axis for map
xmax = max(abs(min_pday), max_pday)
ymax = max(abs(min_profit), max_profit)
groups = df.groupby(df.date)
dates = list(set(df.date.tolist()))
dates.sort()
Writer = animation.writers['ffmpeg']
writer = Writer(fps=2, metadata=dict(artist='biek'), bitrate=-1)
def init():
ax.clear()
ax.set_xlim(-xmax, xmax)
ax.set_ylim(-ymax, ymax)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data', 0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data', 0))
def animate(i):
cdate = dates[i]
df = groups.get_group(cdate)
init()
print(cdate, len(df))
bull_stock_num = len(df[df.profit >= 0])
for code in df.code.tolist():
pday = df.loc[df.code == code, 'pday']
profit = df.loc[df.code == code, 'profit']
ax.scatter(pday, profit, color='black', s=1)
ax.set_title("日期：%s 股票总数：%s 牛熊股比:%s" %
(cdate, len(df), 100 * bull_stock_num / len(df)),
fontproperties=get_chinese_font())
ani = animation.FuncAnimation(fig,
animate,
frames=len(dates),
init_func=init,
interval=1000,
repeat=False)
sfile = '/code/panimation.mp4'
ani.save(sfile, writer)
ax.set_title('Marauder Map for date')
ax.grid(True)
plt.close(fig)
class OverSell():
def __init__(self):
self.ris = RIndexStock(dbinfo=ct.OUT_DB_INFO, redis_host='127.0.0.1')
self.base_color = '#e6daa6'
self.fig = plt.figure(facecolor=self.base_color, figsize=(24, 24))
self.price_ax = plt.subplot2grid((12, 12), (0, 0),
rowspan=6,
colspan=12,
facecolor=self.base_color,
fig=self.fig)
self.ratio_ax = plt.subplot2grid((12, 12), (6, 0),
rowspan=6,
colspan=12,
facecolor=self.base_color,
sharex=self.price_ax,
fig=self.fig)
def get_data(self, start_date, end_date, index_code):
df = self.ris.get_k_data_in_range(start_date, end_date)
iobj = CIndex(index_code,
dbinfo=ct.OUT_DB_INFO,
redis_host='127.0.0.1')
i_data = iobj.get_k_data_in_range(start_date, end_date)
i_data['time'] = i_data.index.tolist()
i_data = i_data[[
'time', 'open', 'high', 'low', 'close', 'volume', 'amount', 'date'
]]
return df, i_data
def is_market_oversell(self, start_date, end_date, index_code):
df, index_data = self.get_data(start_date, end_date, index_code)
info = self.compute_stock_score(df)
def get_oversell_stocks(self, df):
data = df[(np.log(df['close']) - np.log(df['mprice'])) /
np.log(0.9) > 1]
return data.code.tolist()
def compute_stock_score(self, data):
code_list = list()
date_list = list()
rate_list = list()
oversell_ratio = 0
for cdate, df in data.groupby(data.date):
total_num = len(df)
oversell_code_list = self.get_oversell_stocks(df)
oversold_num = len(oversell_code_list)
oversell_ratio = 100 * oversold_num / total_num
date_list.append(cdate)
rate_list.append(oversell_ratio)
code_list.append(oversell_code_list)
info = {'date': date_list, 'rate': rate_list, 'code': code_list}
df = pd.DataFrame(info)
return df
def plot(self, start_date, end_date, index_code):
df, index_data = self.get_data(start_date, end_date, index_code)
date_tickers = index_data.date.tolist()
def _format_date(x, pos=None):
if x < 0 or x > len(date_tickers) - 1: return ''
return date_tickers[int(x)]
info = self.compute_stock_score(df)
candlestick_ohlc(self.price_ax,
index_data.values,
width=1.0,
colorup='r',
colordown='g')
self.ratio_ax.plot(info['date'],
info['rate'],
'r',
label="超跌系数",
linewidth=1)
self.price_ax.xaxis.set_major_locator(mticker.MultipleLocator(20))
self.price_ax.xaxis.set_major_formatter(
mticker.FuncFormatter(_format_date))
plt.show()
class CReivew:
def __init__(self, dbinfo=ct.DB_INFO, redis_host=None):
self.dbinfo = dbinfo
self.logger = getLogger(__name__)
self.tu_client = get_tushare_client()
self.doc = CDoc()
self.redis = create_redis_obj(
) if redis_host is None else create_redis_obj(redis_host)
self.mysql_client = CMySQL(dbinfo, iredis=self.redis)
self.margin_client = Margin(dbinfo=dbinfo, redis_host=redis_host)
self.rstock_client = RIndexStock(dbinfo=dbinfo, redis_host=redis_host)
self.sh_market_client = StockExchange(ct.SH_MARKET_SYMBOL)
self.sz_market_client = StockExchange(ct.SZ_MARKET_SYMBOL)
self.emotion_client = Emotion()
def get_industry_data(self, cdate):
ri = RIndexIndustryInfo()
df = ri.get_k_data(cdate)
if df.empty: return df
df = df.reset_index(drop=True)
df = df.sort_values(by='amount', ascending=False)
df['money_change'] = (df['amount'] - df['preamount']) / 1e8
industry_info = IndustryInfo.get()
df = pd.merge(df, industry_info, how='left', on=['code'])
return df
def get_index_data(self, cdate):
df = pd.DataFrame()
for code, name in ct.TDX_INDEX_DICT.items():
data = CIndex(code).get_k_data(cdate)
data['name'] = name
data['code'] = code
df = df.append(data)
df = df.reset_index(drop=True)
return df
def get_market_data(self, market, start_date, end_date):
if market == ct.SH_MARKET_SYMBOL:
df = self.sh_market_client.get_k_data_in_range(
start_date, end_date)
df = df.loc[df.name == '上海市场']
else:
df = self.sz_market_client.get_k_data_in_range(
start_date, end_date)
df = df.loc[df.name == '深圳市场']
df = df.round(2)
df = df.drop_duplicates()
df = df.reset_index(drop=True)
df = df.sort_values(by='date', ascending=True)
df.negotiable_value = (df.negotiable_value / 2).astype(int)
return df
def get_rzrq_info(self, market, start_date, end_date):
df = self.margin_client.get_k_data_in_range(start_date, end_date)
if market == ct.SH_MARKET_SYMBOL:
df = df.loc[df.code == 'SSE']
df['code'] = '上海市场'
else:
df = df.loc[df.code == 'SZSE']
df['code'] = '深圳市场'
df = df.round(2)
df['rzye'] = df['rzye'] / 1e+8
df['rzmre'] = df['rzmre'] / 1e+8
df['rzche'] = df['rzche'] / 1e+8
df['rqye'] = df['rqye'] / 1e+8
df['rzrqye'] = df['rzrqye'] / 1e+8
df = df.drop_duplicates()
df = df.reset_index(drop=True)
df = df.sort_values(by='date', ascending=True)
return df
def get_index_df(self, code, start_date, end_date):
cindex_client = CIndex(code)
df = cindex_client.get_k_data_in_range(start_date, end_date)
df['time'] = df.index.tolist()
df = df[[
'time', 'open', 'high', 'low', 'close', 'volume', 'amount', 'date'
]]
return df
def update(self, cdate=datetime.now().strftime('%Y-%m-%d')):
start_date = get_day_nday_ago(cdate, 100, dformat="%Y-%m-%d")
end_date = cdate
try:
#market info
sh_df = self.get_market_data(ct.SH_MARKET_SYMBOL, start_date,
end_date)
sz_df = self.get_market_data(ct.SZ_MARKET_SYMBOL, start_date,
end_date)
date_list = list(
set(sh_df.date.tolist()).intersection(set(
sz_df.date.tolist())))
sh_df = sh_df[sh_df.date.isin(date_list)]
sh_df = sh_df.reset_index(drop=True)
sz_df = sz_df[sz_df.date.isin(date_list)]
sz_df = sz_df.reset_index(drop=True)
#rzrq info
sh_rzrq_df = self.get_rzrq_info(ct.SH_MARKET_SYMBOL, start_date,
end_date)
sz_rzrq_df = self.get_rzrq_info(ct.SZ_MARKET_SYMBOL, start_date,
end_date)
date_list = list(
set(sh_rzrq_df.date.tolist()).intersection(
set(sz_rzrq_df.date.tolist())))
sh_rzrq_df = sh_rzrq_df[sh_rzrq_df.date.isin(date_list)]
sh_rzrq_df = sh_rzrq_df.reset_index(drop=True)
sz_rzrq_df = sz_rzrq_df[sz_rzrq_df.date.isin(date_list)]
sz_rzrq_df = sz_rzrq_df.reset_index(drop=True)
#average price info
av_df = self.get_index_df('880003', start_date, end_date)
#limit up and down info
limit_info = CLimit(self.dbinfo).get_data(cdate)
stock_info = self.rstock_client.get_data(cdate)
stock_info = stock_info[stock_info.volume >
0] #get volume > 0 stock list
stock_info = stock_info.reset_index(drop=True)
#index info
index_info = self.get_index_data(end_date)
#industry analysis
industry_info = self.get_industry_data(cdate)
#all stock info
all_stock_info = self.rstock_client.get_k_data_in_range(
start_date, end_date)
#gen review file and make dir for new data
self.doc.generate(cdate, sh_df, sz_df, sh_rzrq_df, sz_rzrq_df,
av_df, limit_info, stock_info, industry_info,
index_info, all_stock_info)
##gen review animation
#self.gen_animation()
except Exception as e:
self.logger.error(e)
traceback.print_exc()
def gen_animation(self, sfile=None):
style.use('fivethirtyeight')
Writer = animation.writers['ffmpeg']
writer = Writer(fps=1, metadata=dict(artist='biek'), bitrate=1800)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
_today = datetime.now().strftime('%Y-%m-%d')
cdata = self.mysql_client.get('select * from %s where date = "%s"' %
(ct.ANIMATION_INFO, _today))
if cdata is None: return None
cdata = cdata.reset_index(drop=True)
ctime_list = cdata.time.unique()
name_list = cdata.name.unique()
ctime_list = [
datetime.strptime(ctime, '%H:%M:%S') for ctime in ctime_list
]
frame_num = len(ctime_list)
if 0 == frame_num: return None
def animate(i):
ax.clear()
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
ax.xaxis.set_major_locator(mdates.DayLocator())
ax.set_title('盯盘', fontproperties=get_chinese_font())
ax.set_xlabel('时间', fontproperties=get_chinese_font())
ax.set_ylabel('增长', fontproperties=get_chinese_font())
ax.set_ylim((-6, 6))
fig.autofmt_xdate()
for name in name_list:
pchange_list = list()
price_list = cdata[cdata.name == name]['price'].tolist()
pchange_list.append(0)
for _index in range(1, len(price_list)):
pchange_list.append(
10 * (price_list[_index] - price_list[_index - 1]) /
price_list[0])
ax.plot(ctime_list[0:i],
pchange_list[0:i],
label=name,
linewidth=1.5)
if pchange_list[i - 1] > 1 or pchange_list[i - 1] < -1:
ax.text(ctime_list[i - 1],
pchange_list[i - 1],
name,
font_properties=get_chinese_font())
ani = animation.FuncAnimation(fig,
animate,
frame_num,
interval=60000,
repeat=False)
sfile = '/data/animation/%s_animation.mp4' % _today if sfile is None else sfile
ani.save(sfile, writer)
plt.close(fig)