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default settings to trigger low, take stop

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creslinux 2018-07-17 21:33:11 +00:00
parent 8cea0517eb
commit 3184c85dca
1 changed files with 31 additions and 24 deletions
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51
freqtrade/optimize/backtesting.py
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@ -101,7 +101,7 @@ class Backtesting(object):
self.debug_vector = False # Debug vector calcs self.debug_vector = False # Debug vector calcs
self.debug_timing_main_loop = False # print overall timing per pair - works in Backtest and Backslap self.debug_timing_main_loop = False # print overall timing per pair - works in Backtest and Backslap
self.backslap_show_trades = True # prints trades in addition to summary report self.backslap_show_trades = False # prints trades in addition to summary report
self.backslap_save_trades = True # saves trades as a pretty table to backslap.txt self.backslap_save_trades = True # saves trades as a pretty table to backslap.txt
self.stop_stops: int = 9999 # stop back testing any pair with this many stops, set to 999999 to not hit self.stop_stops: int = 9999 # stop back testing any pair with this many stops, set to 999999 to not hit
@ -414,33 +414,35 @@ class Backtesting(object):
if debug: if debug:
from pandas import set_option from pandas import set_option
set_option('display.max_rows', 5000) set_option('display.max_rows', 5000)
set_option('display.max_columns', 10) set_option('display.max_columns', 20)
pd.set_option('display.width', 1000) pd.set_option('display.width', 1000)
pd.set_option('max_colwidth', 40) pd.set_option('max_colwidth', 40)
pd.set_option('precision', 12) pd.set_option('precision', 12)
bslap_results_df['trade_duration'] = bslap_results_df['close_time'] - bslap_results_df['open_time'] bslap_results_df['trade_duration'] = bslap_results_df['close_time'] - bslap_results_df['open_time']
# if debug:
# print(bslap_results_df[['open_time', 'close_time', 'trade_duration']])
## Spends, Takes, Profit, Absolute Profit ## Spends, Takes, Profit, Absolute Profit
print(bslap_results_df)
# Buy Price # Buy Price
bslap_results_df['buy_sum'] = stake * bslap_results_df['open_rate'] bslap_results_df['buy_vol'] = stake / bslap_results_df['open_rate'] # How many target are we buying
bslap_results_df['buy_fee'] = bslap_results_df['buy_sum'] * open_fee bslap_results_df['buy_fee'] = stake * open_fee
bslap_results_df['buy_spend'] = bslap_results_df['buy_sum'] + bslap_results_df['buy_fee'] bslap_results_df['buy_spend'] = stake + bslap_results_df['buy_fee'] # How much we're spending
# Sell price # Sell price
bslap_results_df['sell_sum'] = stake * bslap_results_df['close_rate'] bslap_results_df['sell_sum'] = bslap_results_df['buy_vol'] * bslap_results_df['close_rate']
bslap_results_df['sell_fee'] = bslap_results_df['sell_sum'] * close_fee bslap_results_df['sell_fee'] = bslap_results_df['sell_sum'] * close_fee
bslap_results_df['sell_take'] = bslap_results_df['sell_sum'] - bslap_results_df['sell_fee'] bslap_results_df['sell_take'] = bslap_results_df['sell_sum'] - bslap_results_df['sell_fee']
# profit_percent # profit_percent
bslap_results_df['profit_percent'] = bslap_results_df['sell_take'] / bslap_results_df['buy_spend'] - 1 bslap_results_df['profit_percent'] = (bslap_results_df['sell_take'] - bslap_results_df['buy_spend']) \
/ bslap_results_df['buy_spend']
# Absolute profit # Absolute profit
bslap_results_df['profit_abs'] = bslap_results_df['sell_take'] - bslap_results_df['buy_spend'] bslap_results_df['profit_abs'] = bslap_results_df['sell_take'] - bslap_results_df['buy_spend']
if debug: if debug:
print("\n") print("\n")
print(bslap_results_df[ print(bslap_results_df[
['buy_sum', 'buy_fee', 'buy_spend', 'sell_sum','sell_fee', 'sell_take', 'profit_percent', 'profit_abs', 'exit_type']]) ['buy_vol', 'buy_fee', 'buy_spend', 'sell_sum','sell_fee', 'sell_take', 'profit_percent', 'profit_abs', 'exit_type']])
return bslap_results_df return bslap_results_df
@ -458,6 +460,8 @@ class Backtesting(object):
stop_stops i stop_stops i
""" """
debug = self.debug
# Timers, to be called if in debug # Timers, to be called if in debug
def s(): def s():
st = timeit.default_timer() st = timeit.default_timer()
@ -486,6 +490,7 @@ class Backtesting(object):
if stop_stops_count >= stop_stops: # if maximum number of stops allowed in a pair is hit, exit loop if stop_stops_count >= stop_stops: # if maximum number of stops allowed in a pair is hit, exit loop
t_open_ind = -1 # -1 ends the loop t_open_ind = -1 # -1 ends the loop
if debug:
print("Max stop limit ", stop_stops, "reached. Moving to next pair") print("Max stop limit ", stop_stops, "reached. Moving to next pair")
return t_open_ind return t_open_ind
@ -1026,6 +1031,8 @@ class Backtesting(object):
timerange = Arguments.parse_timerange(None if self.config.get( timerange = Arguments.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange'))) 'timerange') is None else str(self.config.get('timerange')))
ld_files = self.s()
data = optimize.load_data( data = optimize.load_data(
self.config['datadir'], self.config['datadir'],
pairs=pairs, pairs=pairs,
@ -1046,6 +1053,8 @@ class Backtesting(object):
max_open_trades = 0 max_open_trades = 0
preprocessed = self.tickerdata_to_dataframe(data) preprocessed = self.tickerdata_to_dataframe(data)
t_t = self.f(ld_files)
print("Load from json to file to df in mem took", t_t)
# Print timeframe # Print timeframe
min_date, max_date = self.get_timeframe(preprocessed) min_date, max_date = self.get_timeframe(preprocessed)
@ -1110,18 +1119,16 @@ class Backtesting(object):
results results
) )
) )
logger.info(
## TODO. Catch open trades for this report. '\n=============================================== '
# logger.info( 'LEFT OPEN TRADES REPORT'
# '\n=============================================== ' ' ===============================================\n'
# 'LEFT OPEN TRADES REPORT' '%s',
# ' ===============================================\n' self._generate_text_table(
# '%s', data,
# self._generate_text_table( results.loc[results.open_at_end]
# data, )
# results.loc[results.open_at_end] )
# )
# )
def setup_configuration(args: Namespace) -> Dict[str, Any]: def setup_configuration(args: Namespace) -> Dict[str, Any]: