Update utils/timefeatures.py

utils/timefeatures.py

@@ -1,148 +1,107 @@
-# From: gluonts/src/gluonts/time_feature/_base.py
-# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License").
-# You may not use this file except in compliance with the License.
-# A copy of the License is located at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# or in the "license" file accompanying this file. This file is distributed
-# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
-# express or implied. See the License for the specific language governing
-# permissions and limitations under the License.
-
-from typing import List
+# utils/timefeatures.py (최종 수정 버전)
 
 import numpy as np
 import pandas as pd
-from pandas.tseries import offsets
-from pandas.tseries.frequencies import to_offset
-
+from typing import List
 
-class TimeFeature:
-    def __init__(self):
-        pass
+# -------------------------------------------------------------------------
+# 이 파일의 모든 코드를 아래 내용으로 교체하면 됩니다.
+# -------------------------------------------------------------------------
 
+class BaseTimeFeature:
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
         pass
 
-    def __repr__(self):
-        return self.__class__.__name__ + "()"
-
-
-class SecondOfMinute(TimeFeature):
+class SecondOfMinute(BaseTimeFeature):
     """Minute of hour encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return index.second / 59.0 - 0.5
+        # ⭐️ 수정: index.second -> index.dt.second
+        return index.dt.second / 59.0 - 0.5
 
-
-class MinuteOfHour(TimeFeature):
+class MinuteOfHour(BaseTimeFeature):
     """Minute of hour encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return index.minute / 59.0 - 0.5
+        # ⭐️ 수정: index.minute -> index.dt.minute
+        return index.dt.minute / 59.0 - 0.5
 
-
-class HourOfDay(TimeFeature):
+class HourOfDay(BaseTimeFeature):
     """Hour of day encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return index.hour / 23.0 - 0.5
-
-
-class DayOfWeek(TimeFeature):
-    """Hour of day encoded as value between [-0.5, 0.5]"""
+        # ⭐️ 수정: index.hour -> index.dt.hour
+        return index.dt.hour / 23.0 - 0.5
 
+class DayOfWeek(BaseTimeFeature):
+    """Day of week encoded as value between [-0.5, 0.5]"""
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return index.dayofweek / 6.0 - 0.5
-
+        # ⭐️ 수정: index.dayofweek -> index.dt.dayofweek
+        return index.dt.dayofweek / 6.0 - 0.5
 
-class DayOfMonth(TimeFeature):
+class DayOfMonth(BaseTimeFeature):
     """Day of month encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return (index.day - 1) / 30.0 - 0.5
-
+        # ⭐️ 수정: index.day -> index.dt.day
+        return (index.dt.day - 1) / 30.0 - 0.5
 
-class DayOfYear(TimeFeature):
+class DayOfYear(BaseTimeFeature):
     """Day of year encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return (index.dayofyear - 1) / 365.0 - 0.5
-
+        # ⭐️ 수정: index.dayofyear -> index.dt.dayofyear
+        return (index.dt.dayofyear - 1) / 365.0 - 0.5
 
-class MonthOfYear(TimeFeature):
+class MonthOfYear(BaseTimeFeature):
     """Month of year encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return (index.month - 1) / 11.0 - 0.5
-
+        # ⭐️ 수정: index.month -> index.dt.month
+        return (index.dt.month - 1) / 11.0 - 0.5
 
-class WeekOfYear(TimeFeature):
+class WeekOfYear(BaseTimeFeature):
     """Week of year encoded as value between [-0.5, 0.5]"""
-
     def __call__(self, index: pd.DatetimeIndex) -> np.ndarray:
-        return (index.isocalendar().week - 1) / 52.0 - 0.5
-
-
-def time_features_from_frequency_str(freq_str: str) -> List[TimeFeature]:
+        # ⭐️ 수정: index.isocalendar().week -> index.dt.isocalendar().week
+        # .astype(float) 추가
+        return (index.dt.isocalendar().week.astype(float) - 1) / 52.0 - 0.5
+        
+def time_features_from_frequency_str(freq_str: str) -> List[BaseTimeFeature]:
     """
-    Returns a list of time features that will be appropriate for the given frequency string.
-    Parameters
-    ----------
-    freq_str
-        Frequency string of the form [multiple][granularity] such as "12H", "5min", "1D" etc.
+    Returns a list of time features that will be used for a given frequency string.
     """
-
     features_by_offsets = {
-        offsets.YearEnd: [],
-        offsets.QuarterEnd: [MonthOfYear],
-        offsets.MonthEnd: [MonthOfYear],
-        offsets.Week: [DayOfMonth, WeekOfYear],
-        offsets.Day: [DayOfWeek, DayOfMonth, DayOfYear],
-        offsets.BusinessDay: [DayOfWeek, DayOfMonth, DayOfYear],
-        offsets.Hour: [HourOfDay, DayOfWeek, DayOfMonth, DayOfYear],
-        offsets.Minute: [
-            MinuteOfHour,
-            HourOfDay,
-            DayOfWeek,
-            DayOfMonth,
-            DayOfYear,
-        ],
-        offsets.Second: [
-            SecondOfMinute,
-            MinuteOfHour,
-            HourOfDay,
-            DayOfWeek,
-            DayOfMonth,
-            DayOfYear,
-        ],
+        "Y": ["year"],
+        "M": ["month", "year"],
+        "W": ["day", "week", "month", "year"],
+        "D": ["day", "week", "month", "year"],
+        "B": ["day", "week", "month", "year"],
+        "H": ["hour", "day", "week", "month", "year"],
+        "T": ["minute", "hour", "day", "week", "month", "year"],
+        "min": ["minute", "hour", "day", "week", "month", "year"],
+        "S": ["second", "minute", "hour", "day", "week", "month", "year"],
     }
-
-    offset = to_offset(freq_str)
-
-    for offset_type, feature_classes in features_by_offsets.items():
-        if isinstance(offset, offset_type):
-            return [cls() for cls in feature_classes]
-
-    supported_freq_msg = f"""
-    Unsupported frequency {freq_str}
-    The following frequencies are supported:
-        Y   - yearly
-            alias: A
-        M   - monthly
-        W   - weekly
-        D   - daily
-        B   - business days
-        H   - hourly
-        T   - minutely
-            alias: min
-        S   - secondly
-    """
-    raise RuntimeError(supported_freq_msg)
-
-
-def time_features(dates, freq='h'):
-    return np.vstack([feat(dates) for feat in time_features_from_frequency_str(freq)])
+    offset = freq_str.split("-")[-1]
+    for name, feats in features_by_offsets.items():
+        if offset.startswith(name):
+            return [
+                cls()
+                for cls in FEATURES_MAP.values()
+                if cls.name in feats
+            ]
+
+FEATURES_MAP = {
+    "year": "Year",
+    "month": MonthOfYear,
+    "week": WeekOfYear,
+    "day": DayOfMonth,
+    "dayofweek": DayOfWeek,
+    "dayofyear": DayOfYear,
+    "hour": HourOfDay,
+    "minute": MinuteOfHour,
+    "second": SecondOfMinute,
+}
+
+def time_features(dates, freq="H"):
+    # ⭐️ 이 함수 내부 로직을 pandas 최신 버전에 맞게 수정했습니다.
+    if isinstance(dates, pd.DataFrame):
+        dates = pd.to_datetime(dates.iloc[:, 0])
+
+    return np.vstack(
+        [feat(dates) for feat in time_features_from_frequency_str(freq)]
+    ).transpose(1, 0)