Detectors module upgrades

Summary: All pre-upgrade PSS2 changes for detectors and tests/detectors modules.

Reviewed By: islijepcevic

Differential Revision: D67505451

fbshipit-source-id: 0418fda3572843c5f6064524a6e8dbf75a748668

kats/detectors/cusum_model.py

@@ -973,7 +973,7 @@ def _reorganize_big_data(
 
         multi_ts_val_df = pd.DataFrame(multi_ts_val).T
 
-        multi_ts_df = pd.concat([multi_ts_time_df, multi_ts_val_df], 1)
+        multi_ts_df = pd.concat([multi_ts_time_df, multi_ts_val_df], axis=1)
         df_names = ["val_" + str(i) for i in range(multi_ts_val_df.shape[1])]
         multi_ts_df.columns = ["time"] + df_names
 

kats/detectors/multivariate_detector.py

@@ -134,7 +134,9 @@ def predict(
         output_scores_df = self.model.anomaly_score_df
 
         assert output_scores_df is not None
-        output_scores_df = output_scores_df[output_scores_df.index >= data.time.min()]
+        output_scores_df = output_scores_df[
+            output_scores_df.index.to_series().ge(data.time.min())
+        ]
 
         zeros = np.zeros(shape=(data.time.shape[0], output_scores_df.shape[1]))
         padding = np.empty(

kats/detectors/outlier.py

@@ -191,7 +191,7 @@ def __init__(
 
         time_diff = data.time.sort_values().diff().dropna()
         if len(time_diff.unique()) == 1:  # check constant frequenccy
-            freq = time_diff.unique()[0].astype("int")
+            freq = time_diff.unique().astype("int")[0]
             self.granularity_days: float = freq / (24 * 3600 * (10**9))
         else:
             raise RuntimeError(
@@ -342,7 +342,9 @@ def detector(self) -> pd.DataFrame:
             anomaly_scores_t = pd.DataFrame(
                 anomaly_scores_t, index=[fcstTime], copy=False
             )
-            anomaly_score_df = anomaly_score_df.append(anomaly_scores_t)
+            anomaly_score_df = pd.concat(
+                [anomaly_score_df, anomaly_scores_t], axis=0, ignore_index=False
+            )
 
         self.anomaly_score_df = anomaly_score_df
         return anomaly_score_df

kats/detectors/seasonality.py

@@ -300,7 +300,9 @@ def get_fft_peaks(
         pos_fft = fft.loc[fft["ampl"] > 0]
         median = pos_fft["ampl"].median()
         pos_fft_above_med = pos_fft[pos_fft["ampl"] > median]
-        mad = pos_fft_above_med["ampl"].mad()
+        mad = (
+            (pos_fft_above_med["ampl"] - pos_fft_above_med["ampl"].mean()).abs().mean()
+        )
 
         threshold = median + mad * mad_threshold