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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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20
freqtrade/freqai/data_drawer.py
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@@ -30,6 +30,7 @@ class FreqaiDataDrawer:
def __init__(self, full_path: Path, config: dict, follow_mode: bool = False):
self.config = config
self.freqai_info = config.get('freqai', {})
# dictionary holding all pair metadata necessary to load in from disk
self.pair_dict: Dict[str, Any] = {}
# dictionary holding all actively inferenced models in memory given a model filename
@@ -168,7 +169,8 @@ class FreqaiDataDrawer:
self.model_return_values[pair]['do_preds'] = dh.full_do_predict
self.model_return_values[pair]['target_mean'] = dh.full_target_mean
self.model_return_values[pair]['target_std'] = dh.full_target_std
self.model_return_values[pair]['DI_values'] = dh.full_DI_values
if self.freqai_info.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
self.model_return_values[pair]['DI_values'] = dh.full_DI_values
# if not self.follow_mode:
# self.save_model_return_values_to_disk()
@@ -189,8 +191,9 @@ class FreqaiDataDrawer:
self.model_return_values[pair]['predictions'] = np.append(
self.model_return_values[pair]['predictions'][i:], predictions[-1])
self.model_return_values[pair]['DI_values'] = np.append(
self.model_return_values[pair]['DI_values'][i:], dh.DI_values[-1])
if self.freqai_info.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
self.model_return_values[pair]['DI_values'] = np.append(
self.model_return_values[pair]['DI_values'][i:], dh.DI_values[-1])
self.model_return_values[pair]['do_preds'] = np.append(
self.model_return_values[pair]['do_preds'][i:], do_preds[-1])
self.model_return_values[pair]['target_mean'] = np.append(
@@ -202,8 +205,9 @@ class FreqaiDataDrawer:
prepend = np.zeros(abs(length_difference) - 1)
self.model_return_values[pair]['predictions'] = np.insert(
self.model_return_values[pair]['predictions'], 0, prepend)
self.model_return_values[pair]['DI_values'] = np.insert(
self.model_return_values[pair]['DI_values'], 0, prepend)
if self.freqai_info.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
self.model_return_values[pair]['DI_values'] = np.insert(
self.model_return_values[pair]['DI_values'], 0, prepend)
self.model_return_values[pair]['do_preds'] = np.insert(
self.model_return_values[pair]['do_preds'], 0, prepend)
self.model_return_values[pair]['target_mean'] = np.insert(
@@ -215,7 +219,8 @@ class FreqaiDataDrawer:
dh.full_do_predict = copy.deepcopy(self.model_return_values[pair]['do_preds'])
dh.full_target_mean = copy.deepcopy(self.model_return_values[pair]['target_mean'])
dh.full_target_std = copy.deepcopy(self.model_return_values[pair]['target_std'])
dh.full_DI_values = copy.deepcopy(self.model_return_values[pair]['DI_values'])
if self.freqai_info.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
dh.full_DI_values = copy.deepcopy(self.model_return_values[pair]['DI_values'])
# if not self.follow_mode:
# self.save_model_return_values_to_disk()
@@ -227,7 +232,8 @@ class FreqaiDataDrawer:
dh.full_do_predict = np.zeros(len_df)
dh.full_target_mean = np.zeros(len_df)
dh.full_target_std = np.zeros(len_df)
dh.full_DI_values = np.zeros(len_df)
if self.freqai_info.get('feature_parameters', {}).get('DI_threshold', 0) > 0:
dh.full_DI_values = np.zeros(len_df)
def purge_old_models(self) -> None: