recorder refine; signalTemp; fixbug

qlib/contrib/eva/alpha.py

@@ -0,0 +1,32 @@
+'''
+Here is a batch of evaluation functions.
+
+The interface should be redesigned carefully in the future.
+'''
+import pandas as pd
+
+
+def calc_ic(pred: pd.Series, label: pd.Series, date_col='datetime', dropna=False) -> (pd.Series, pd.Series):
+    """calc_ic.
+
+    Parameters
+    ----------
+    pred :
+        pred
+    label :
+        label
+    date_col :
+        date_col
+
+    Returns
+    -------
+    (pd.Series, pd.Series)
+        ic and rank ic
+    """
+    df = pd.DataFrame({'pred': pred, 'label': label})
+    ic = df.groupby(date_col).apply(lambda df: df['pred'].corr(df['label']))
+    ric = df.groupby(date_col).apply(lambda df: df['pred'].corr(df['label'], method='spearman'))
+    if dropna:
+        return ic.dropna(), ric.dropna()
+    else:
+        return ic, ric

qlib/contrib/model/gbdt.py

@@ -64,7 +64,7 @@ class LGBModel(ModelFT):
     def predict(self, dataset):
         if self.model is None:
             raise ValueError("model is not fitted yet!")
-        x_test = dataset.prepare("test", col_set="feature")
+        x_test = dataset.prepare("test", col_set="feature", data_key=DataHandlerLP.DK_I)
         return pd.Series(self.model.predict(np.squeeze(x_test.values)), index=x_test.index)
 
     def finetune(self, dataset: DatasetH, num_boost_round=10, verbose_eval=20):