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add model expiration feature, fix bug in DI return values

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This commit is contained in:
robcaulk
2022-06-17 14:55:40 +02:00
parent 0b0688a91e
commit f631ae911b
5 changed files with 69 additions and 18 deletions
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12
freqtrade/freqai/data_kitchen.py
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@@ -673,7 +673,7 @@ class FreqaiDataKitchen:
self.full_predictions = np.append(self.full_predictions, predictions)
self.full_do_predict = np.append(self.full_do_predict, do_predict)
if self.freqai_config.get('feature_parameters', {}).get('DI-threshold', 0) > 0:
if self.freqai_config.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
self.full_DI_values = np.append(self.full_DI_values, self.DI_values)
self.full_target_mean = np.append(self.full_target_mean, target_mean)
self.full_target_std = np.append(self.full_target_std, target_std)
@@ -689,7 +689,7 @@ class FreqaiDataKitchen:
filler = np.zeros(len_dataframe - len(self.full_predictions)) # startup_candle_count
self.full_predictions = np.append(filler, self.full_predictions)
self.full_do_predict = np.append(filler, self.full_do_predict)
if self.freqai_config.get('feature_parameters', {}).get('DI-threshold', 0) > 0:
if self.freqai_config.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
self.full_DI_values = np.append(filler, self.full_DI_values)
self.full_target_mean = np.append(filler, self.full_target_mean)
self.full_target_std = np.append(filler, self.full_target_std)
@@ -725,6 +725,12 @@ class FreqaiDataKitchen:
return full_timerange
def check_if_model_expired(self, trained_timestamp: int) -> bool:
time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp()
elapsed_time = (time - trained_timestamp) / 3600 # hours
max_time = self.freqai_config.get('expiration_hours', 0)
return elapsed_time > max_time
def check_if_new_training_required(self, trained_timestamp: int) -> Tuple[bool,
TimeRange, TimeRange]:
@@ -873,6 +879,8 @@ class FreqaiDataKitchen:
# check if newest candle is already appended
df_dp = strategy.dp.get_pair_dataframe(pair, tf)
if len(df_dp.index) == 0:
continue
if (
str(history_data[pair][tf].iloc[-1]['date']) ==
str(df_dp.iloc[-1:]['date'].iloc[-1])