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change start_backtesting to handle backtest_live_models

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This commit is contained in:
Wagner Costa Santos
2022-09-25 10:35:55 -03:00
parent 7f116db95e
commit 0ed7b2bfc3
2 changed files with 82 additions and 123 deletions
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58
freqtrade/freqai/data_kitchen.py
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@@ -62,6 +62,7 @@ class FreqaiDataKitchen:
live: bool = False,
pair: str = "",
):
self.backtest_live_models = False # temp
self.data: Dict[str, Any] = {}
self.data_dictionary: Dict[str, DataFrame] = {}
self.config = config
@@ -88,11 +89,16 @@ class FreqaiDataKitchen:
self.config["timerange"], self.freqai_config.get("train_period_days", 0)
)
(self.training_timeranges, self.backtesting_timeranges) = self.split_timerange(
self.full_timerange,
config["freqai"]["train_period_days"],
config["freqai"]["backtest_period_days"],
)
if self.backtest_live_models:
self.get_timerange_from_ready_models()
(self.training_timeranges,
self.backtesting_timeranges) = self.split_timerange_live_models()
else:
(self.training_timeranges, self.backtesting_timeranges) = self.split_timerange(
self.full_timerange,
config["freqai"]["train_period_days"],
config["freqai"]["backtest_period_days"],
)
self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
self.thread_count = self.freqai_config.get("data_kitchen_thread_count", -1)
@@ -451,6 +457,26 @@ class FreqaiDataKitchen:
# print(tr_training_list, tr_backtesting_list)
return tr_training_list_timerange, tr_backtesting_list_timerange
def split_timerange_live_models(
self
) -> Tuple[list, list]:
tr_backtesting_list_timerange = []
pair = self.pair.split("/")[0].split(":")[0]
pair_data = self.backtest_live_models_data["pairs_end_dates"][pair]
model_end_dates = []
backtesting_timerange = self.backtest_live_models_data["backtesting_timerange"]
for data in pair_data:
model_end_dates.append(data["model_end_date"])
model_end_dates.append(backtesting_timerange.stopts)
model_end_dates.sort()
for index, item in enumerate(model_end_dates):
if len(model_end_dates) > (index + 1):
tr_to_add = TimeRange("date", "date", item, model_end_dates[index + 1])
tr_backtesting_list_timerange.append(tr_to_add)
return tr_backtesting_list_timerange, tr_backtesting_list_timerange
def slice_dataframe(self, timerange: TimeRange, df: DataFrame) -> DataFrame:
"""
Given a full dataframe, extract the user desired window
@@ -1093,15 +1119,15 @@ class FreqaiDataKitchen:
return retrain, trained_timerange, data_load_timerange
def set_new_model_names(self, pair: str, trained_timerange: TimeRange):
def set_new_model_names(self, pair: str, timestamp_id: int):
coin, _ = pair.split("/")
self.data_path = Path(
self.full_path
/ f"sub-train-{pair.split('/')[0]}_{int(trained_timerange.stopts)}"
/ f"sub-train-{pair.split('/')[0]}_{timestamp_id}"
)
self.model_filename = f"cb_{coin.lower()}_{int(trained_timerange.stopts)}"
self.model_filename = f"cb_{coin.lower()}_{timestamp_id}"
def set_all_pairs(self) -> None:
@@ -1278,7 +1304,7 @@ class FreqaiDataKitchen:
pairs_end_dates: Dict[str, Any] = {}
for model_dir in models_path.iterdir():
if str(model_dir.name).startswith("sub-train"):
model_end_date = model_dir.name.split("_")[1]
model_end_date = int(model_dir.name.split("_")[1])
pair = model_dir.name.split("_")[0].replace("sub-train-", "")
model_file_name = (f"cb_{str(model_dir.name).replace('sub-train-', '').lower()}")
model_file_name = f"{model_file_name}_model.joblib"
@@ -1289,14 +1315,24 @@ class FreqaiDataKitchen:
pairs_end_dates[pair] = []
pairs_end_dates[pair].append({
"model_end_date": int(model_end_date),
"model_end_date": model_end_date,
"model_path_file": model_path_file,
"model_dir": model_dir
})
if model_end_date not in all_models_end_dates:
all_models_end_dates.append(int(model_end_date))
all_models_end_dates.append(model_end_date)
finish_timestamp = int(datetime.now(tz=timezone.utc).timestamp())
if len(all_models_end_dates) > 1:
# After last model end date, use the same period from previous model
# to finish the backtest
all_models_end_dates.sort(reverse=True)
finish_timestamp = all_models_end_dates[0] + \
(all_models_end_dates[0] - all_models_end_dates[1])
all_models_end_dates.append(finish_timestamp)
all_models_end_dates.sort()
start = datetime.fromtimestamp(min(all_models_end_dates), tz=timezone.utc)
stop = datetime.fromtimestamp(max(all_models_end_dates), tz=timezone.utc)
backtesting_string_timerange = f"{start.strftime('%Y%m%d')}-{stop.strftime('%Y%m%d')}"