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Dec 10, 2019
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DOC correct indents in _split.py #15843

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66 changes: 33 additions & 33 deletions sklearn/model_selection/_split.py
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Original file line number Diff line number Diff line change
Expand Up @@ -135,10 +135,10 @@ class LeaveOneOut(BaseCrossValidator):
>>> print(loo)
LeaveOneOut()
>>> for train_index, test_index in loo.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
TRAIN: [1] TEST: [0]
[[3 4]] [[1 2]] [2] [1]
TRAIN: [0] TEST: [1]
Expand Down Expand Up @@ -222,9 +222,9 @@ class LeavePOut(BaseCrossValidator):
>>> print(lpo)
LeavePOut(p=2)
>>> for train_index, test_index in lpo.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [1 3] TEST: [0 2]
TRAIN: [1 2] TEST: [0 3]
Expand Down Expand Up @@ -398,9 +398,9 @@ class KFold(_BaseKFold):
>>> print(kf)
KFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in kf.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [0 1] TEST: [2 3]

Expand Down Expand Up @@ -604,9 +604,9 @@ class StratifiedKFold(_BaseKFold):
>>> print(skf)
StratifiedKFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in skf.split(X, y):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [1 3] TEST: [0 2]
TRAIN: [0 2] TEST: [1 3]

Expand Down Expand Up @@ -769,9 +769,9 @@ class TimeSeriesSplit(_BaseKFold):
>>> print(tscv)
TimeSeriesSplit(max_train_size=None, n_splits=5)
>>> for train_index, test_index in tscv.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [0] TEST: [1]
TRAIN: [0 1] TEST: [2]
TRAIN: [0 1 2] TEST: [3]
Expand Down Expand Up @@ -861,10 +861,10 @@ class LeaveOneGroupOut(BaseCrossValidator):
>>> print(logo)
LeaveOneGroupOut()
>>> for train_index, test_index in logo.split(X, y, groups):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
TRAIN: [2 3] TEST: [0 1]
[[5 6]
[7 8]] [[1 2]
Expand Down Expand Up @@ -980,10 +980,10 @@ class LeavePGroupsOut(BaseCrossValidator):
>>> print(lpgo)
LeavePGroupsOut(n_groups=2)
>>> for train_index, test_index in lpgo.split(X, y, groups):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print(X_train, X_test, y_train, y_test)
TRAIN: [2] TEST: [0 1]
[[5 6]] [[1 2]
[3 4]] [1] [1 2]
Expand Down Expand Up @@ -1405,7 +1405,7 @@ class ShuffleSplit(BaseShuffleSplit):
>>> print(rs)
ShuffleSplit(n_splits=5, random_state=0, test_size=0.25, train_size=None)
>>> for train_index, test_index in rs.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... print("TRAIN:", train_index, "TEST:", test_index)
TRAIN: [1 3 0 4] TEST: [5 2]
TRAIN: [4 0 2 5] TEST: [1 3]
TRAIN: [1 2 4 0] TEST: [3 5]
Expand All @@ -1414,7 +1414,7 @@ class ShuffleSplit(BaseShuffleSplit):
>>> rs = ShuffleSplit(n_splits=5, train_size=0.5, test_size=.25,
... random_state=0)
>>> for train_index, test_index in rs.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... print("TRAIN:", train_index, "TEST:", test_index)
TRAIN: [1 3 0] TEST: [5 2]
TRAIN: [4 0 2] TEST: [1 3]
TRAIN: [1 2 4] TEST: [3 5]
Expand Down Expand Up @@ -1508,7 +1508,7 @@ class GroupShuffleSplit(ShuffleSplit):
>>> gss.get_n_splits()
2
>>> for train_idx, test_idx in gss.split(X, y, groups):
... print("TRAIN:", train_idx, "TEST:", test_idx)
... print("TRAIN:", train_idx, "TEST:", test_idx)
TRAIN: [2 3 4 5 6 7] TEST: [0 1]
TRAIN: [0 1 5 6 7] TEST: [2 3 4]
'''
Expand Down Expand Up @@ -1620,9 +1620,9 @@ class StratifiedShuffleSplit(BaseShuffleSplit):
>>> print(sss)
StratifiedShuffleSplit(n_splits=5, random_state=0, ...)
>>> for train_index, test_index in sss.split(X, y):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [5 2 3] TEST: [4 1 0]
TRAIN: [5 1 4] TEST: [0 2 3]
TRAIN: [5 0 2] TEST: [4 3 1]
Expand Down Expand Up @@ -1837,9 +1837,9 @@ class PredefinedSplit(BaseCrossValidator):
>>> print(ps)
PredefinedSplit(test_fold=array([ 0, 1, -1, 1]))
>>> for train_index, test_index in ps.split():
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [1 2 3] TEST: [0]
TRAIN: [0 2] TEST: [1 3]
"""
Expand Down