Update ffill and bfill

Author: phamquiluan

RCAEval/classes/data.py

@@ -101,7 +101,7 @@ def preprocess(
         data_frame[0] = pd.to_datetime(data_frame[0], unit=kwargs.get("unit", "s"), utc=True)
         data_frame: pd.DataFrame = data_frame.set_index(0).resample(interval, origin="start").mean()
         data_frame.interpolate(method="time", limit_direction="both", inplace=True)
-        data_frame.fillna(method="bfill", inplace=True)
+        data_frame.bfill(inplace=True)
 
         # 3. Return values only
         data_frame.sort_index(inplace=True)

RCAEval/e2e/baro.py

@@ -91,7 +91,7 @@ def mmnsigma(data, inject_time=None, dataset=None, num_loop=None, sli=None, anom
 
     # == traces_err ==
     if dataset == "mm-tt" or dataset == "mm-ob":
-        traces_err = traces_err.fillna(method='ffill')
+        traces_err = traces_err.ffill()
         traces_err = traces_err.fillna(0)
         traces_err = drop_constant(traces_err)
 
@@ -100,7 +100,7 @@ def mmnsigma(data, inject_time=None, dataset=None, num_loop=None, sli=None, anom
 
      # == traces_lat ==
     if dataset == "mm-tt" or dataset == "mm-ob":
-        traces_lat = traces_lat.fillna(method='ffill')
+        traces_lat = traces_lat.ffill()
         traces_lat = traces_lat.fillna(0)
         traces_lat = drop_constant(traces_lat)
         normal_traces_lat = traces_lat[traces_lat["time"] < inject_time].drop(columns=["time"])

RCAEval/e2e/mscred.py

@@ -577,7 +577,7 @@ def mscred(data, inject_time=None, dataset=None, num_loop=None, sli=None, anomal
         inject_time = int(f.readlines()[0].strip())
     data = data.loc[:, ~data.columns.str.endswith("_latency-50")]
     data = data.replace([np.inf, -np.inf], np.nan)
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(0)
 
     # select only n time series

RCAEval/graph_construction/cmlp.py

@@ -594,7 +594,7 @@ def cmlp(data: pd.DataFrame, max_iter=None):
 
     node_names = data.columns.to_list()
     # fill nan by ffill
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.to_numpy().astype(float)
     device = torch.device("cpu")
 

RCAEval/graph_construction/fci.py

@@ -6,7 +6,7 @@ def fci_default(data: pd.DataFrame):
     node_names = data.columns.to_list()
 
     # fill nan by ffill
-    data = data.fillna(method="ffill")
+    data = data.ffill()
 
     data = data.to_numpy().astype(float)
 

legacy/eval.py

@@ -292,7 +292,7 @@ def process(data_path):
     data = data.replace([np.inf, -np.inf], np.nan)
 
     # handle na
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(0)
 
     # check if there is any nan or inf

legacy/graph_eval.py

@@ -362,7 +362,7 @@ def process(data_path):
 
     # == PROCESS ==
     # func = globals()[args.model]
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(value=0)
     np_data = np.absolute(data.to_numpy().astype(float))
 

legacy/rq1.py

@@ -220,7 +220,7 @@ def process(data_path):
 
 
     # == PROCESS ==
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(value=0)
     np_data = np.absolute(data.to_numpy().astype(float))
 

main-ase.py

@@ -198,7 +198,7 @@ def process(data_path):
     data = data.replace([np.inf, -np.inf], np.nan)
 
     # handle na
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(0)
 
     cut_length = 0

main.py

@@ -197,7 +197,7 @@ def process(data_path):
     data = data.replace([np.inf, -np.inf], np.nan)
 
     # handle na
-    data = data.fillna(method="ffill")
+    data = data.ffill()
     data = data.fillna(0)
 
     with open(join(data_dir, "inject_time.txt")) as f: