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feature scaling supports upper and lower for specific columns, not only all columns #5266

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feature scaling supports upper and lower for specific columns, not only all columns #5266

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28 changes: 14 additions & 14 deletions python/federatedml/feature/feature_scale/base_scale.py
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Original file line number Diff line number Diff line change
Expand Up @@ -123,13 +123,13 @@ def __get_min_max_value_by_normal(self, data):

if self.feat_upper is not None:
if isinstance(self.feat_upper, list):
self.__check_equal(data_shape, len(self.feat_upper))
for i in range(data_shape):
if i in scale_column_idx_set:
if column_max_value[i] > self.feat_upper[i]:
column_max_value[i] = self.feat_upper[i]
if column_min_value[i] > self.feat_upper[i]:
column_min_value[i] = self.feat_upper[i]
self.__check_equal(len(scale_column_idx_set), len(self.feat_upper))
for upper_index, col_index in enumerate(scale_column_idx_set):
if col_index < data_shape:
if column_max_value[col_index] > self.feat_upper[upper_index]:
column_max_value[col_index] = self.feat_upper[upper_index]
if column_min_value[col_index] > self.feat_upper[upper_index]:
column_min_value[col_index] = self.feat_upper[upper_index]
else:
for i in range(data_shape):
if i in scale_column_idx_set:
Expand All @@ -140,13 +140,13 @@ def __get_min_max_value_by_normal(self, data):

if self.feat_lower is not None:
if isinstance(self.feat_lower, list):
self.__check_equal(data_shape, len(self.feat_lower))
for i in range(data_shape):
if i in scale_column_idx_set:
if column_min_value[i] < self.feat_lower[i]:
column_min_value[i] = self.feat_lower[i]
if column_max_value[i] < self.feat_lower[i]:
column_max_value[i] = self.feat_lower[i]
self.__check_equal(len(scale_column_idx_set), len(self.feat_lower))
for lower_index, col_index in enumerate(scale_column_idx_set):
if col_index < data_shape:
if column_min_value[col_index] < self.feat_lower[lower_index]:
column_min_value[col_index] = self.feat_lower[lower_index]
if column_max_value[col_index] < self.feat_lower[lower_index]:
column_max_value[col_index] = self.feat_lower[lower_index]
else:
for i in range(data_shape):
if i in scale_column_idx_set:
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