[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

Author: polmauri

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)