[MRG + 1] FIX raise an error message when n_groups > number of groups (…

…scikit-learn#7681) (scikit-learn#7683)

* FIX raise an error message when n_groups > actual number of groups (scikit-learn#7681)

This change addresses issue scikit-learn#7681:
- Raise ValueError when n_groups > actual number of unique groups in LeaveOneGroupOut and LeavePGroupsOut.
- Add unit test.

* Make requested changes

- Check error message with `assert_raise_message`
- Pass parameters to `assert_raise_message` instead of defining functions

* Update condition and exception message

sklearn/model_selection/_split.py

@@ -773,6 +773,10 @@ def _iter_test_masks(self, X, y, groups):
  # We make a copy of groups to avoid side-effects during iteration
  groups = np.array(groups, copy=True)
  unique_groups = np.unique(groups)
+ if len(unique_groups) <= 1:
+ raise ValueError(
+ "The groups parameter contains fewer than 2 unique groups "
+ "(%s). LeaveOneGroupOut expects at least 2." % unique_groups)
  for i in unique_groups:
  yield groups == i
 
@@ -862,6 +866,12 @@ def _iter_test_masks(self, X, y, groups):
  raise ValueError("The groups parameter should not be None")
  groups = np.array(groups, copy=True)
  unique_groups = np.unique(groups)
+ if self.n_groups >= len(unique_groups):
+ raise ValueError(
+ "The groups parameter contains fewer than (or equal to) "
+ "n_groups (%d) numbers of unique groups (%s). LeavePGroupsOut "
+ "expects that at least n_groups + 1 (%d) unique groups be "
+ "present" % (self.n_groups, unique_groups, self.n_groups + 1))
  combi = combinations(range(len(unique_groups)), self.n_groups)
  for indices in combi:
  test_index = np.zeros(_num_samples(X), dtype=np.bool)

sklearn/model_selection/tests/test_split.py

@@ -724,6 +724,31 @@ def test_leave_group_out_changing_groups():
  assert_equal(3, LeaveOneGroupOut().get_n_splits(X, y, groups))
 
 
+def test_leave_one_p_group_out_error_on_fewer_number_of_groups():
+ X = y = groups = np.ones(0)
+ msg = ("The groups parameter contains fewer than 2 unique groups ([]). "
+ "LeaveOneGroupOut expects at least 2.")
+ assert_raise_message(ValueError, msg, next,
+ LeaveOneGroupOut().split(X, y, groups))
+ X = y = groups = np.ones(1)
+ msg = ("The groups parameter contains fewer than 2 unique groups ([ 1.]). "
+ "LeaveOneGroupOut expects at least 2.")
+ assert_raise_message(ValueError, msg, next,
+ LeaveOneGroupOut().split(X, y, groups))
+ X = y = groups = np.ones(1)
+ msg = ("The groups parameter contains fewer than (or equal to) n_groups "
+ "(3) numbers of unique groups ([ 1.]). LeavePGroupsOut expects "
+ "that at least n_groups + 1 (4) unique groups be present")
+ assert_raise_message(ValueError, msg, next,
+ LeavePGroupsOut(n_groups=3).split(X, y, groups))
+ X = y = groups = np.arange(3)
+ msg = ("The groups parameter contains fewer than (or equal to) n_groups "
+ "(3) numbers of unique groups ([0 1 2]). LeavePGroupsOut expects "
+ "that at least n_groups + 1 (4) unique groups be present")
+ assert_raise_message(ValueError, msg, next,
+ LeavePGroupsOut(n_groups=3).split(X, y, groups))
+
+
 def test_train_test_split_errors():
  assert_raises(ValueError, train_test_split)
  assert_raises(ValueError, train_test_split, range(3), train_size=1.1)