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Merge pull request #1454 from freqtrade/feat/interpolate_missing

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interpolate missing candles
This commit is contained in:
Misagh
2019-01-04 22:33:53 +01:00
committed by GitHub
parent 55235ce20d 672d115eca
commit 26a77e193e
13 changed files with 157 additions and 40 deletions
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44
freqtrade/data/converter.py
View File

@@ -5,13 +5,19 @@ import logging
import pandas as pd
from pandas import DataFrame, to_datetime
from freqtrade.constants import TICKER_INTERVAL_MINUTES
logger = logging.getLogger(__name__)
def parse_ticker_dataframe(ticker: list) -> DataFrame:
def parse_ticker_dataframe(ticker: list, ticker_interval: str,
fill_missing: bool = True) -> DataFrame:
"""
Converts a ticker-list (format ccxt.fetch_ohlcv) to a Dataframe
:param ticker: ticker list, as returned by exchange.async_get_candle_history
:param ticker_interval: ticker_interval (e.g. 5m). Used to fill up eventual missing data
:param fill_missing: fill up missing candles with 0 candles
(see ohlcv_fill_up_missing_data for details)
:return: DataFrame
"""
logger.debug("Parsing tickerlist to dataframe")
@@ -33,7 +39,41 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
})
frame.drop(frame.tail(1).index, inplace=True) # eliminate partial candle
logger.debug('Dropping last candle')
return frame
if fill_missing:
return ohlcv_fill_up_missing_data(frame, ticker_interval)
else:
return frame
def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str) -> DataFrame:
"""
Fills up missing data with 0 volume rows,
using the previous close as price for "open", "high" "low" and "close", volume is set to 0
"""
ohlc_dict = {
'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'
}
tick_mins = TICKER_INTERVAL_MINUTES[ticker_interval]
# Resample to create "NAN" values
df = dataframe.resample(f'{tick_mins}min', on='date').agg(ohlc_dict)
# Forwardfill close for missing columns
df['close'] = df['close'].fillna(method='ffill')
# Use close for "open, high, low"
df.loc[:, ['open', 'high', 'low']] = df[['open', 'high', 'low']].fillna(
value={'open': df['close'],
'high': df['close'],
'low': df['close'],
})
df.reset_index(inplace=True)
logger.debug(f"Missing data fillup: before: {len(dataframe)} - after: {len(df)}")
return df
def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:

9
freqtrade/data/history.py
View File

@@ -82,6 +82,7 @@ def load_pair_history(pair: str,
timerange: TimeRange = TimeRange(None, None, 0, 0),
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
fill_up_missing: bool = True
) -> DataFrame:
"""
Loads cached ticker history for the given pair.
@@ -111,7 +112,7 @@ def load_pair_history(pair: str,
logger.warning('Missing data at end for pair %s, data ends at %s',
pair,
arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
return parse_ticker_dataframe(pairdata)
return parse_ticker_dataframe(pairdata, ticker_interval, fill_up_missing)
else:
logger.warning('No data for pair: "%s", Interval: %s. '
'Use --refresh-pairs-cached to download the data',
@@ -124,7 +125,8 @@ def load_data(datadir: Optional[Path],
pairs: List[str],
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, DataFrame]:
timerange: TimeRange = TimeRange(None, None, 0, 0),
fill_up_missing: bool = True) -> Dict[str, DataFrame]:
"""
Loads ticker history data for a list of pairs the given parameters
:return: dict(<pair>:<tickerlist>)
@@ -135,7 +137,8 @@ def load_data(datadir: Optional[Path],
hist = load_pair_history(pair=pair, ticker_interval=ticker_interval,
datadir=datadir, timerange=timerange,
refresh_pairs=refresh_pairs,
exchange=exchange)
exchange=exchange,
fill_up_missing=fill_up_missing)
if hist is not None:
result[pair] = hist
return result