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cleanup in InformativeSample

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This commit is contained in:
hroff-1902
2019-08-17 04:59:13 +03:00
committed by GitHub
parent 8ef81a0ba6
commit 5606e64a45
1 changed files with 6 additions and 11 deletions
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user_data/strategies/InformativeSample.py
+6 -11
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@@ -4,7 +4,6 @@ from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
from freqtrade.data.converter import parse_ticker_dataframe
# --------------------------------
import talib.abstract as ta
@@ -12,8 +11,8 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
class InformativeSample(IStrategy):
"""
Sample strategy implementing Informative Pairs - compares ETH/BTC with USDT.
Not performing very well - but should serve as an example to use a referential pair against USD.
Sample strategy implementing Informative Pairs - compares stake_currency with USDT.
Not performing very well - but should serve as an example how to use a referential pair against USDT.
author@: xmatthias
github@: https://github.com/freqtrade/freqtrade-strategies
@@ -72,8 +71,6 @@ class InformativeSample(IStrategy):
("BTC/USDT", "15m"),
]
"""
return [(f"{self.config['stake_currency']}/USDT", self.ticker_interval)]
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -90,23 +87,21 @@ class InformativeSample(IStrategy):
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
if self.dp:
if self.dp.runmode in('live', 'dry_run'):
# Compare stake-currency with USDT - using the defined ticker-interval
# Get live ohlcv data for the informative pair.
if (f"{self.stake_currency}/USDT", self.ticker_interval) in self.dp.available_pairs:
data = self.dp.ohlcv(pair='ETH/BTC',
data = self.dp.ohlcv(pair=f"{self.stake_currency}/USDT",
ticker_interval=self.ticker_interval)
else:
# Get historic ohlcv data (cached on disk).
# data = parse_ticker_dataframe(self.dp.historic_ohlcv(pair='ETH/BTC',
# ticker_interval=self.ticker_interval), "5m")
data = self.dp.historic_ohlcv(pair=f"{self.stake_currency}/USDT",
ticker_interval=self.ticker_interval)
if len(data) == 0:
logger.warning(f"No data found for {self.stake_currency}/USDT")
# Combine the 2 dataframes using close
# this will result in a column named closeETH or closeBTC - depnding on stake_currency.
# this will result in a column named 'closeETH' or 'closeBTC' - depending on stake_currency.
dataframe = dataframe.merge(data[["date", "close"]], on="date", how="left", suffixes=("", self.config['stake_currency']))
# Calculate SMA20 on stakecurrency. Resulting column = smaETH20
# Calculate SMA20 on 'close' data for stake_currency/USDT. Resulting column is named as 'smaETH20' (if stake_currency is ETH)
dataframe[f"sma{self.config['stake_currency']}20"] = dataframe[f'close{self.stake_currency}'].rolling(20).mean()
return dataframe