lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

start frequi with historical data if available

Browse Source
This commit is contained in:
Robert Caulk 2022-08-05 18:27:05 +02:00
parent 29b7b014e5
commit a3799c4d5d
1 changed files with 25 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
freqtrade/freqai/data_drawer.py
View File

@ -229,20 +229,34 @@ class FreqaiDataDrawer:
# dynamic df returned to strategy and plotted in frequi
mrv_df = self.model_return_values[pair] = pd.DataFrame()
for label in dk.label_list:
mrv_df[label] = pred_df[label]
mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
# if user reused `idenfitier` in config and has historical predictions collected, loadthem
# so that frequi remains uninterrupted after a crash
hist_df = self.historic_predictions
if pair in hist_df:
len_diff = len(hist_df[pair].index) - len(pred_df.index)
if len_diff < 0:
df_concat = pd.concat([pred_df.iloc[:abs(len_diff)], hist_df[pair]],
ignore_index=True, keys=hist_df[pair].keys())
else:
df_concat = hist_df[pair].tail(len(pred_df.index))
df_concat = df_concat.fillna(0)
self.model_return_values[pair] = df_concat
if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
mrv_df["DI_values"] = dk.DI_values
else:
for label in dk.label_list:
mrv_df[label] = pred_df[label]
mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
mrv_df["do_predict"] = do_preds
if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
mrv_df["DI_values"] = dk.DI_values
if dk.data['extra_returns_per_train']:
rets = dk.data['extra_returns_per_train']
for return_str in rets:
mrv_df[return_str] = rets[return_str]
mrv_df["do_predict"] = do_preds
if dk.data['extra_returns_per_train']:
rets = dk.data['extra_returns_per_train']
for return_str in rets:
mrv_df[return_str] = rets[return_str]
# for keras type models, the conv_window needs to be prepended so
# viewing is correct in frequi