def save_settings(self, emitter=None):
"""
Dump camera settings to YAML file
"""
camera_config = self.camera_widget.get_settings()
email_settings = self.email_notifier_widget.get_settings()
Config.dump_config({
"camera_settings": camera_config,
"email_notification_settings": email_settings,
})
print((
f'Model training has completed.\nMean validation correlation:'
f' {np.array(corrs).mean():.3f}.\nMean validation sharpe: {np.array(sharpes).mean():.3f}'
))
if cfg.EVAL.SAVE_PREDS:
print(f'Generating and Saving Predictions')
save_preds(model=mod,
chunksize=cfg.EVAL.CHUNK_SIZE,
pred_path=output / "predictions/preds.csv",
feature_cols=feature_cols,
tourn_path=tourn)
print("Predictions Saved!")
if cfg.EVAL.SUBMIT_PREDS:
print("Submitting Predictions!")
napi.upload_predictions(output / "predictions/preds.csv",
model_id=os.environ.get("NUMERAI_MODEL_ID"))
# Append results to config file
RESULTS = {
'RESULTS': {
'CORRS': corrs,
'SHARPES': sharpes,
'MEAN_CORR': np.array(corrs).mean().item(),
'MEAN_SHARPE': np.array(sharpes).mean().item()
}
}
cfg.update_config(RESULTS)
logname = f'logs/log_{cfg.MODEL.TYPE}_{cfg.MODEL.NAME}_{cfg.SYSTEM.TIME}.yaml'
cfg.dump_config(path=output / logname)
