stat: add panic notice to ROC and fix typo

stat/roc.go

@@ -26,7 +26,8 @@ import (
 // assigned class labels are compared with the true values in the classes
 // slice and used to calculate the FPR and TPR.
 //
-// If weights is nil, all weights are treated as 1.
+// If weights is nil, all weights are treated as 1. If weights is not nil
+// it must have the same length as y and classes, otherwise ROC will panic.
 //
 // If cutoffs is nil or empty, all possible cutoffs are calculated,
 // resulting in fpr and tpr having length one greater than the number of

stat/roc_test.go

@@ -25,7 +25,7 @@ func TestROC(t *testing.T) {
 	}{
 		// Test cases were informed by using sklearn metrics.roc_curve when
 		// cutoffs is nil, but all test cases (including when cutoffs is not
-		// nil) where calculated manually.
+		// nil) were calculated manually.
 		// Some differences exist between unweighted ROCs from our function
 		// and metrics.roc_curve which appears to use integer cutoffs in that
 		// case. sklearn also appears to do some magic that trims leading zeros