adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

First pass changes for cleaning up

Browse Source
This commit is contained in:
froggleston 2022-05-29 11:20:11 +01:00
parent 145faf9817
commit e7c5818d16
4 changed files with 75 additions and 96 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
freqtrade/commands/arguments.py
View File

@ -101,8 +101,8 @@ ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperop
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header", "print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
"disableparamexport", "backtest_breakdown"] "disableparamexport", "backtest_breakdown"]
ARGS_ANALYZE_ENTRIES_EXITS = ["analysis_groups", "enter_reason_list", ARGS_ANALYZE_ENTRIES_EXITS = ["analysis-groups", "enter-reason-list",
"exit_reason_list", "indicator_list"] "exit-reason-list", "indicator-list"]
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes", NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-data", "list-markets", "list-pairs", "list-strategies", "list-data",
@ -421,7 +421,7 @@ class Arguments:
self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd) self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)
# Add backtesting analysis subcommand # Add backtesting analysis subcommand
analysis_cmd = subparsers.add_parser('analysis', help='Analysis module.', analysis_cmd = subparsers.add_parser('analysis', help='Backtest Analysis module.',
parents=[_common_parser, _strategy_parser]) parents=[_common_parser, _strategy_parser])
analysis_cmd.set_defaults(func=start_analysis_entries_exits) analysis_cmd.set_defaults(func=start_analysis_entries_exits)
self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd) self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd)

8
freqtrade/commands/cli_options.py
View File

@ -615,7 +615,7 @@ AVAILABLE_CLI_OPTIONS = {
action="store_true", action="store_true",
), ),
"analysis_groups": Arg( "analysis_groups": Arg(
"--analysis_groups", "--analysis-groups",
help=("grouping output - ", help=("grouping output - ",
"0: simple wins/losses by enter tag, ", "0: simple wins/losses by enter tag, ",
"1: by enter_tag, ", "1: by enter_tag, ",
@ -626,21 +626,21 @@ AVAILABLE_CLI_OPTIONS = {
default="0,1,2", default="0,1,2",
), ),
"enter_reason_list": Arg( "enter_reason_list": Arg(
"--enter_reason_list", "--enter-reason-list",
help=("Comma separated list of entry signals to analyse. Default: all. ", help=("Comma separated list of entry signals to analyse. Default: all. ",
"e.g. 'entry_tag_a,entry_tag_b'"), "e.g. 'entry_tag_a,entry_tag_b'"),
nargs='?', nargs='?',
default='all', default='all',
), ),
"exit_reason_list": Arg( "exit_reason_list": Arg(
"--exit_reason_list", "--exit-reason-list",
help=("Comma separated list of exit signals to analyse. Default: all. ", help=("Comma separated list of exit signals to analyse. Default: all. ",
"e.g. 'exit_tag_a,roi,stop_loss,trailing_stop_loss'"), "e.g. 'exit_tag_a,roi,stop_loss,trailing_stop_loss'"),
nargs='?', nargs='?',
default='all', default='all',
), ),
"indicator_list": Arg( "indicator_list": Arg(
"--indicator_list", "--indicator-list",
help=("Comma separated list of indicators to analyse. ", help=("Comma separated list of indicators to analyse. ",
"e.g. 'close,rsi,bb_lowerband,profit_abs'"), "e.g. 'close,rsi,bb_lowerband,profit_abs'"),
nargs='?', nargs='?',

93
freqtrade/data/entryexitanalysis.py
View File

@ -7,7 +7,8 @@ import joblib
import pandas as pd import pandas as pd
from tabulate import tabulate from tabulate import tabulate
from freqtrade.data.btanalysis import get_latest_backtest_filename, load_backtest_data from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data,
load_backtest_stats)
from freqtrade.exceptions import OperationalException from freqtrade.exceptions import OperationalException
@ -49,8 +50,8 @@ def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_cand
pair, pair,
trades, trades,
signal_candles[strategy_name][pair]) signal_candles[strategy_name][pair])
except Exception: except Exception as e:
pass print(f"Cannot process entry/exit reasons for {strategy_name}: ", e)
return analysed_trades_dict return analysed_trades_dict
@ -82,25 +83,28 @@ def _analyze_candles_and_indicators(pair, trades, signal_candles):
try: try:
trades_red = pd.merge(trades_red, trades_inds, on='signal_date', how='outer') trades_red = pd.merge(trades_red, trades_inds, on='signal_date', how='outer')
except Exception as e: except Exception as e:
print(e) raise e
return trades_red return trades_red
else: else:
return pd.DataFrame() return pd.DataFrame()
def _do_group_table_output(bigdf, glist): def _do_group_table_output(bigdf, glist):
if "0" in glist: for g in glist:
# 0: summary wins/losses grouped by enter tag
if g == "0":
group_mask = ['enter_reason']
wins = bigdf.loc[bigdf['profit_abs'] >= 0] \ wins = bigdf.loc[bigdf['profit_abs'] >= 0] \
.groupby(['enter_reason']) \ .groupby(group_mask) \
.agg({'profit_abs': ['sum']}) .agg({'profit_abs': ['sum']})
wins.columns = ['profit_abs_wins'] wins.columns = ['profit_abs_wins']
loss = bigdf.loc[bigdf['profit_abs'] < 0] \ loss = bigdf.loc[bigdf['profit_abs'] < 0] \
.groupby(['enter_reason']) \ .groupby(group_mask) \
.agg({'profit_abs': ['sum']}) .agg({'profit_abs': ['sum']})
loss.columns = ['profit_abs_loss'] loss.columns = ['profit_abs_loss']
new = bigdf.groupby(['enter_reason']).agg({'profit_abs': [ new = bigdf.groupby(group_mask).agg({'profit_abs': [
'count', 'count',
lambda x: sum(x > 0), lambda x: sum(x > 0),
lambda x: sum(x <= 0)]}) lambda x: sum(x <= 0)]})
@ -117,61 +121,33 @@ def _do_group_table_output(bigdf, glist):
sortcols = ['total_num_buys'] sortcols = ['total_num_buys']
_print_table(new, sortcols, show_index=True) _print_table(new, sortcols, show_index=True)
if "1" in glist:
new = bigdf.groupby(['enter_reason']) \ else:
.agg({'profit_abs': ['count', 'sum', 'median', 'mean'], agg_mask = {'profit_abs': ['count', 'sum', 'median', 'mean'],
'profit_ratio': ['sum', 'median', 'mean']} 'profit_ratio': ['sum', 'median', 'mean']}
).reset_index() agg_cols = ['num_buys', 'profit_abs_sum', 'profit_abs_median',
new.columns = ['enter_reason', 'num_buys', 'profit_abs_sum', 'profit_abs_median',
'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct', 'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct',
'total_profit_pct'] 'total_profit_pct']
sortcols = ['profit_abs_sum', 'enter_reason'] sortcols = ['profit_abs_sum', 'enter_reason']
new['median_profit_pct'] = new['median_profit_pct'] * 100 # 1: profit summaries grouped by enter_tag
new['mean_profit_pct'] = new['mean_profit_pct'] * 100 if g == "1":
new['total_profit_pct'] = new['total_profit_pct'] * 100 group_mask = ['enter_reason']
_print_table(new, sortcols) # 2: profit summaries grouped by enter_tag and exit_tag
if "2" in glist: if g == "2":
new = bigdf.groupby(['enter_reason', 'exit_reason']) \ group_mask = ['enter_reason', 'exit_reason']
.agg({'profit_abs': ['count', 'sum', 'median', 'mean'],
'profit_ratio': ['sum', 'median', 'mean']}
).reset_index()
new.columns = ['enter_reason', 'exit_reason', 'num_buys', 'profit_abs_sum',
'profit_abs_median', 'profit_abs_mean', 'median_profit_pct',
'mean_profit_pct', 'total_profit_pct']
sortcols = ['profit_abs_sum', 'enter_reason']
new['median_profit_pct'] = new['median_profit_pct'] * 100 # 3: profit summaries grouped by pair and enter_tag
new['mean_profit_pct'] = new['mean_profit_pct'] * 100 if g == "3":
new['total_profit_pct'] = new['total_profit_pct'] * 100 group_mask = ['pair', 'enter_reason']
_print_table(new, sortcols) # 4: profit summaries grouped by pair, enter_ and exit_tag (this can get quite large)
if "3" in glist: if g == "4":
new = bigdf.groupby(['pair', 'enter_reason']) \ group_mask = ['pair', 'enter_reason', 'exit_reason']
.agg({'profit_abs': ['count', 'sum', 'median', 'mean'],
'profit_ratio': ['sum', 'median', 'mean']}
).reset_index()
new.columns = ['pair', 'enter_reason', 'num_buys', 'profit_abs_sum',
'profit_abs_median', 'profit_abs_mean', 'median_profit_pct',
'mean_profit_pct', 'total_profit_pct']
sortcols = ['profit_abs_sum', 'enter_reason']
new['median_profit_pct'] = new['median_profit_pct'] * 100
new['mean_profit_pct'] = new['mean_profit_pct'] * 100
new['total_profit_pct'] = new['total_profit_pct'] * 100
_print_table(new, sortcols)
if "4" in glist:
new = bigdf.groupby(['pair', 'enter_reason', 'exit_reason']) \
.agg({'profit_abs': ['count', 'sum', 'median', 'mean'],
'profit_ratio': ['sum', 'median', 'mean']}
).reset_index()
new.columns = ['pair', 'enter_reason', 'exit_reason', 'num_buys', 'profit_abs_sum',
'profit_abs_median', 'profit_abs_mean', 'median_profit_pct',
'mean_profit_pct', 'total_profit_pct']
sortcols = ['profit_abs_sum', 'enter_reason']
new = bigdf.groupby(group_mask).agg(agg_mask).reset_index()
new.columns = group_mask + agg_cols
new['median_profit_pct'] = new['median_profit_pct'] * 100 new['median_profit_pct'] = new['median_profit_pct'] * 100
new['mean_profit_pct'] = new['mean_profit_pct'] * 100 new['mean_profit_pct'] = new['mean_profit_pct'] * 100
new['total_profit_pct'] = new['total_profit_pct'] * 100 new['total_profit_pct'] = new['total_profit_pct'] * 100
@ -179,7 +155,7 @@ def _do_group_table_output(bigdf, glist):
_print_table(new, sortcols) _print_table(new, sortcols)
def _print_results(analysed_trades, stratname, group, def _print_results(analysed_trades, stratname, analysis_groups,
enter_reason_list, exit_reason_list, enter_reason_list, exit_reason_list,
indicator_list, columns=None): indicator_list, columns=None):
@ -191,8 +167,8 @@ def _print_results(analysed_trades, stratname, group,
bigdf = pd.concat([bigdf, trades], ignore_index=True) bigdf = pd.concat([bigdf, trades], ignore_index=True)
if bigdf.shape[0] > 0 and ('enter_reason' in bigdf.columns): if bigdf.shape[0] > 0 and ('enter_reason' in bigdf.columns):
if group is not None: if analysis_groups is not None:
glist = group.split(",") glist = analysis_groups.split(",")
_do_group_table_output(bigdf, glist) _do_group_table_output(bigdf, glist)
if enter_reason_list is not None and not enter_reason_list == "all": if enter_reason_list is not None and not enter_reason_list == "all":
@ -244,6 +220,9 @@ def process_entry_exit_reasons(backtest_dir: Path,
indicator_list: Optional[str] = None): indicator_list: Optional[str] = None):
try: try:
bt_stats = load_backtest_stats(backtest_dir)
logger.info(bt_stats)
# strategy_name = bt_stats['something']
trades = load_backtest_data(backtest_dir, strategy_name) trades = load_backtest_data(backtest_dir, strategy_name)
except ValueError as e: except ValueError as e:
raise OperationalException(e) from e raise OperationalException(e) from e

12
tests/data/test_entryexitanalysis.py
View File

@ -24,10 +24,10 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp
"exit_profit_only": False, "exit_profit_only": False,
"exit_profit_offset": 0.0, "exit_profit_offset": 0.0,
"ignore_roi_if_entry_signal": False, "ignore_roi_if_entry_signal": False,
'analysis_groups': "0", 'analysis-groups': "0",
'enter_reason_list': "all", 'enter-reason-list': "all",
'exit_reason_list': "all", 'exit-reason-list': "all",
'indicator_list': "rsi" 'indicator-list': "rsi"
}) })
patch_exchange(mocker) patch_exchange(mocker)
result1 = pd.DataFrame({'pair': ['ETH/BTC', 'LTC/BTC'], result1 = pd.DataFrame({'pair': ['ETH/BTC', 'LTC/BTC'],
@ -94,8 +94,8 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp
'--config', 'config.json', '--config', 'config.json',
'--datadir', str(testdatadir), '--datadir', str(testdatadir),
'--user-data-dir', str(tmpdir), '--user-data-dir', str(tmpdir),
'--analysis_groups', '0', '--analysis-groups', '0',
'--indicator_list', 'rsi', '--indicator-list', 'rsi',
'--strategy', '--strategy',
'StrategyTestV3Analysis', 'StrategyTestV3Analysis',
] ]