def data_frame(data, size, period1, period2):
df = pd.DataFrame(data)
df['date'], df['time'] = df['date'].dt.date, df['date'].dt.strftime('%H:%M:%S')
df = Renko(df)
df.brick_size = size
data = df.get_bricks()
data['MA4'] = data['close'].rolling(window=period1).mean()
data['MA10'] = data['close'].rolling(window=period2).mean()
return data
def GetRenko(DF, n):
df = DF.copy()
df.reset_index(inplace=True)
df = df.iloc[:, [0, 1, 2, 3, 5, 6]]
df.columns = ["date", "open", "high", "low", "close", "volume"]
renko_df = Renko(df)
renko_df.brick_size = round(ATR(DF, 120)['ATR'][-1], 0)
df2 = renko_df.get_bricks()
return df2
def renko_DF(DF):
"function to convert ohlc data into renko bricks"
df = DF.copy()
df.reset_index(inplace=True)
df = df.iloc[:, [0, 1, 2, 3, 5, 6]]
df.rename(columns={"Date": "date", "High": "high", "Low": "low",
"Open": "open", "Adj Close": "close", "Volume": "volume"}, inplace=True)
df2 = Renko(df)
df2.brick_size = round(ATR(DF, 120)["ATR"][-1], 0)
# if get_bricks() does not work try using get_ohlc_data() instead
renko_df = df2.get_bricks()
#renko_df = df2.get_ohlc_data()
return renko_df
def renko_DF(DF):
"function to convert ohlc data into renko bricks"
df = DF.copy()
df.reset_index(inplace=True)
df = df.iloc[:, [0, 1, 2, 3, 4, 5]]
df.columns = ["date", "open", "high", "low", "close", "volume"]
df2 = Renko(df)
df2.brick_size = max(0.5, round(ATR(DF, 120)["ATR"][-1], 0))
renko_df = df2.get_bricks()
renko_df["bar_num"] = np.where(renko_df["uptrend"] == True, 1, np.where(renko_df["uptrend"] == False, -1, 0))
for i in range(1, len(renko_df["bar_num"])):
if renko_df["bar_num"][i] > 0 and renko_df["bar_num"][i - 1] > 0:
renko_df["bar_num"][i] += renko_df["bar_num"][i - 1]
elif renko_df["bar_num"][i] < 0 and renko_df["bar_num"][i - 1] < 0:
renko_df["bar_num"][i] += renko_df["bar_num"][i - 1]
renko_df.drop_duplicates(subset="date", keep="last", inplace=True)
return renko_df
def renko_bars(self, DF, n, instrument):
df = DF.copy()
df2 = Renko(df)
real = talib.ATR(df["high"], df["low"], df["close"], timeperiod = n)
brick_sizing = round(real[len(real) - 1], 5)
print("BRICK_SIZE: ", brick_sizing)
df2.brick_size = brick_sizing
renko_df = df2.get_bricks()
renko_df["bar_num"] = np\
.where(renko_df["uptrend"]==True,1,np\
.where(renko_df["uptrend"]==False,-1,0))
for i in range(1,len(renko_df["bar_num"])):
if renko_df["bar_num"][i]>0 and renko_df["bar_num"][i-1]>0:
renko_df["bar_num"][i]+=renko_df["bar_num"][i-1]
elif renko_df["bar_num"][i]<0 and renko_df["bar_num"][i-1]<0:
renko_df["bar_num"][i]+=renko_df["bar_num"][i-1]
renko_df.drop_duplicates(subset="date",keep="last",inplace=True)
return renko_df, brick_sizing
def renko_DF(DF):
df = DF.copy()
df2 = Renko(df)
"Using ATR as renko brick size"
real = talib.ATR(df["high"], df["low"], df["close"], timeperiod=14)
brick_sizing = round(real[len(real) - 1], 6)
df2.brick_size = brick_sizing
renko_df = df2.get_bricks()
renko_df["bar_num"] = np\
.where(renko_df["uptrend"]==True,1,np\
.where(renko_df["uptrend"]==False,-1,0))
for i in range(1, len(renko_df["bar_num"])):
if renko_df["bar_num"][i] > 0 and renko_df["bar_num"][i - 1] > 0:
renko_df["bar_num"][i] += renko_df["bar_num"][i - 1]
elif renko_df["bar_num"][i] < 0 and renko_df["bar_num"][i - 1] < 0:
renko_df["bar_num"][i] += renko_df["bar_num"][i - 1]
renko_df.drop_duplicates(subset="date", keep="last", inplace=True)
return renko_df
def renko(o, h, l, c, v):
'''
Computes Ranko values for the given price series
Parameters
==========
o: pandas.Series(): Open price
h: pandas.Series(): High price
l: pandas.Series(): Low price
c: pandas.Series(): Closeprice
v: pandas.Series(): Volume
Returns
=======
renko_df: pandas.DataFrame()
'''
df = pd.concat([
copy.deepcopy(o),
copy.deepcopy(h),
copy.deepcopy(l),
copy.deepcopy(c),
copy.deepcopy(v)
],
axis=1)
df.reset_index(inplace=True)
df.columns = ['date', 'open', 'high', 'low', 'close', 'volume']
df2 = Renko(df)
renko_df = df2.get_bricks()
renko_df['bar_num'] = np.where(
renko_df['uptrend'] == True, 1,
np.where(renko_df['uptrend'] == False, -1, 0))
for i in range(1, len(renko_df['bar_num'])):
if renko_df['bar_num'][i] > 0 & renko_df['bar_num'][i - 1] > 0:
renko_df['bar_num'][i] += renko_df['bar_num'][i - 1]
elif renko_df['bar_num'][i] < 0 & renko_df['bar_num'][i - 1] < 0:
renko_df['bar_num'][i] += renko_df['bar_num'][i - 1]
renko_df.drop_duplicates(subset='Date', keep='last', inplace=True)
return renko_df
import numpy as np
import pandas as pd
import nsepy
from stocktrends import Renko
if len(sys.argv) > 1:
fname = sys.argv[1]
print('Reading local file {}'.format(fname))
df = pd.read_csv(sys.argv[1])
else:
symbol='SBIN'
print('Downloading {} data from nsepy'.format(symbol))
df = nsepy.get_history(
symbol=symbol,
start=dt.date(2017,1,1),
end=dt.date(2018,1,19)
)
if df.empty:
print('No data is received from nsepy.')
sys.exit()
debug = True
# print(df.tail(20))
renko = Renko(df)
renko.brick_size = 4
r = renko.get_bricks()
print(r.tail(33))
