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more replacements of ticker_interval

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Matthias 2019-11-02 20:34:39 +01:00
parent 334ac8b10c
commit 1c57a4ac35
3 changed files with 6 additions and 6 deletions
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4
freqtrade/constants.py
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@ -24,7 +24,7 @@ AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList']
DRY_RUN_WALLET = 999.9 DRY_RUN_WALLET = 999.9
MATH_CLOSE_PREC = 1e-14 # Precision used for float comparisons MATH_CLOSE_PREC = 1e-14 # Precision used for float comparisons
TICKER_INTERVALS = [ TIMEFRAMES = [
'1m', '3m', '5m', '15m', '30m', '1m', '3m', '5m', '15m', '30m',
'1h', '2h', '4h', '6h', '8h', '12h', '1h', '2h', '4h', '6h', '8h', '12h',
'1d', '3d', '1w', '1d', '3d', '1w',
@ -57,7 +57,7 @@ CONF_SCHEMA = {
'type': 'object', 'type': 'object',
'properties': { 'properties': {
'max_open_trades': {'type': 'integer', 'minimum': -1}, 'max_open_trades': {'type': 'integer', 'minimum': -1},
'ticker_interval': {'type': 'string', 'enum': TICKER_INTERVALS}, 'ticker_interval': {'type': 'string', 'enum': TIMEFRAMES},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'XBT', 'ETH', 'USDT', 'EUR', 'USD']}, 'stake_currency': {'type': 'string', 'enum': ['BTC', 'XBT', 'ETH', 'USDT', 'EUR', 'USD']},
'stake_amount': { 'stake_amount': {
"type": ["number", "string"], "type": ["number", "string"],

6
freqtrade/data/btanalysis.py
View File

@ -178,9 +178,9 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
:return: Returns df with one additional column, col_name, containing the cumulative profit. :return: Returns df with one additional column, col_name, containing the cumulative profit.
""" """
from freqtrade.exchange import timeframe_to_minutes from freqtrade.exchange import timeframe_to_minutes
ticker_minutes = timeframe_to_minutes(timeframe) timeframe_minutes = timeframe_to_minutes(timeframe)
# Resample to ticker_interval to make sure trades match candles # Resample to timeframe to make sure trades match candles
_trades_sum = trades.resample(f'{ticker_minutes}min', on='close_time')[['profitperc']].sum() _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_time')[['profitperc']].sum()
df.loc[:, col_name] = _trades_sum.cumsum() df.loc[:, col_name] = _trades_sum.cumsum()
# Set first value to 0 # Set first value to 0
df.loc[df.iloc[0].name, col_name] = 0 df.loc[df.iloc[0].name, col_name] = 0

2
freqtrade/optimize/backtesting.py
View File

@ -121,7 +121,7 @@ class Backtesting:
min_date.isoformat(), max_date.isoformat(), (max_date - min_date).days min_date.isoformat(), max_date.isoformat(), (max_date - min_date).days
) )
# Adjust startts forward if not enough data is available # Adjust startts forward if not enough data is available
timerange.adjust_start_if_necessary(timeframe_to_seconds(self.ticker_interval), timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
self.required_startup, min_date) self.required_startup, min_date)
return data, timerange return data, timerange