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GAS trades verified from candle data to excel by hand
All pass 3 sells 1 stop loss
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@ -95,10 +95,10 @@ class Backtesting(object):
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self.np_sco: int = self.np_close # stops_calculated_on - Should be stop, FT uses close
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self.use_backslap = True # Enable backslap
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self.debug = False # Main debug enable, very print heavy, enable 2 loops recommended
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self.debug = True # Main debug enable, very print heavy, enable 2 loops recommended
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self.debug_timing = False # Stages within Backslap
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self.debug_2loops = False # Limit each pair to two loops, useful when debugging
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self.debug_vector = False # Debug vector calcs
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self.debug_vector = True # Debug vector calcs
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self.debug_timing_main_loop = False # print overall timing per pair
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@ -255,6 +255,7 @@ class Backtesting(object):
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use_backslap = self.use_backslap
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debug_timing = self.debug_timing_main_loop
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if use_backslap: # Use Back Slap code
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########################### Call out BSlap Loop instead of Original BT code
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bslap_results: list = []
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@ -395,7 +396,7 @@ class Backtesting(object):
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if debug:
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from pandas import set_option
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set_option('display.max_rows', 5000)
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set_option('display.max_columns', 8)
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set_option('display.max_columns', 10)
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pd.set_option('display.width', 1000)
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pd.set_option('max_colwidth', 40)
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pd.set_option('precision', 12)
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@ -422,8 +423,7 @@ class Backtesting(object):
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if debug:
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print("\n")
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print(bslap_results_df[
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['buy_sum', 'buy_fee', 'buy_spend', 'sell_sum', 'sell_take', 'profit_percent', 'profit_abs',
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'exit_type']])
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['buy_sum', 'buy_fee', 'buy_spend', 'sell_sum','sell_fee', 'sell_take', 'profit_percent', 'profit_abs', 'exit_type']])
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return bslap_results_df
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@ -708,8 +708,8 @@ class Backtesting(object):
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if debug:
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print("\n(4) numpy debug\nNext view index with sell = 1 is ", np_t_sell_ind)
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print("If 0 or less is returned there is no sell found to end of view, then next lines garbage")
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print("Row", np_t_sell_ind, np_t_open_v[np_t_stop_ind])
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print("Row", np_t_sell_ind + 1, np_t_open_v[np_t_stop_ind + 1])
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print("Row", np_t_sell_ind, np_t_open_v[np_t_sell_ind])
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print("Row", np_t_sell_ind + 1, np_t_open_v[np_t_sell_ind + 1])
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if debug_timing:
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t_t = f(st)
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print("4-numpy", str.format('{0:.17f}', t_t))
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