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wassname
2020-10-26 14:41:07 +08:00
parent 49fdfdc3ab
commit 3ee1c5bbb8
11 changed files with 2405 additions and 4369 deletions
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seq2seq_time/data/dataset.py
+5 -3
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@@ -20,11 +20,11 @@ class Seq2SeqDataSet(torch.utils.data.Dataset):
Returns x_past, y_past, x_future, etc.
"""
def __init__(self, df: pd.DataFrame, window_past=40, window_future=10, columns_target=['energy(kWh/hh)'], columns_blank=[],):
def __init__(self, df: pd.DataFrame, window_past=40, window_future=10, columns_target=['energy(kWh/hh)'], columns_past=[],):
"""
Args:
- df: DataFrame with time index, already scaled
- columns_blank: The columns we will blank, in the future
- columns_past: The columns we will blank, in the future
"""
super().__init__()
assert isinstance(df.index, pd.DatetimeIndex), 'should have a datetime index'
@@ -38,7 +38,7 @@ class Seq2SeqDataSet(torch.utils.data.Dataset):
self.columns_target = columns_target
# For speed
self._icol_blank = [df.drop(columns = columns_target).columns.tolist().index(n) for n in columns_blank]
self._icol_blank = [df.drop(columns = columns_target).columns.tolist().index(n) for n in columns_past]
self._x = self.df.drop(columns = self.columns_target).values
self._y = self.df[columns_target].values
@@ -64,6 +64,8 @@ class Seq2SeqDataSet(torch.utils.data.Dataset):
# Stop it cheating by using future weather measurements. Fill in with last value
x_future[:, self._icol_blank] = x_past[0, self._icol_blank]
# x_future[:, self._icol_blank] = 0
return x_past, y_past, x_future, y_future