[MRG] Separated regression metrics from other metrics in test_sample_…

…weight_invariance in metrics/tests/test_common.py (scikit-learn#8537)

* Separated tests for regression features in test_sample_weight_invariance

* Fixed pep8

* Removed unecessary check for regression

* Updated regression metrics

* Joel's suggestions

sklearn/metrics/tests/test_common.py

@@ -1013,13 +1013,26 @@ def check_sample_weight_invariance(name, metric, y1, y2):
 
 def test_sample_weight_invariance(n_samples=50):
     random_state = check_random_state(0)
+    # regression
+    y_true = random_state.random_sample(size=(n_samples,))
+    y_pred = random_state.random_sample(size=(n_samples,))
+    for name in ALL_METRICS:
+        if name not in REGRESSION_METRICS:
+            continue
+        if name in METRICS_WITHOUT_SAMPLE_WEIGHT:
+            continue
+        metric = ALL_METRICS[name]
+        yield _named_check(check_sample_weight_invariance, name), name,\
+            metric, y_true, y_pred
 
     # binary
     random_state = check_random_state(0)
     y_true = random_state.randint(0, 2, size=(n_samples, ))
     y_pred = random_state.randint(0, 2, size=(n_samples, ))
     y_score = random_state.random_sample(size=(n_samples,))
     for name in ALL_METRICS:
+        if name in REGRESSION_METRICS:
+            continue
         if (name in METRICS_WITHOUT_SAMPLE_WEIGHT or
                 name in METRIC_UNDEFINED_BINARY):
             continue
@@ -1037,6 +1050,8 @@ def test_sample_weight_invariance(n_samples=50):
     y_pred = random_state.randint(0, 5, size=(n_samples, ))
     y_score = random_state.random_sample(size=(n_samples, 5))
     for name in ALL_METRICS:
+        if name in REGRESSION_METRICS:
+            continue
         if (name in METRICS_WITHOUT_SAMPLE_WEIGHT or
                 name in METRIC_UNDEFINED_BINARY_MULTICLASS):
             continue