Attempt to catch error where NaN is introduced.

src/stats/chi.rs

@@ -25,12 +25,22 @@ fn test_statistic<const N: usize, C: Categorical<N>>(table: &ContingencyTable<N,
         let observed_count = table.observed_by_index(i) as i64;
         let diff = observed_count - expected_count;
         let error = diff.pow(2) as f64;
-        let incremental_error = error / (expected_count as f64);
+        let incremental_error = error / error_denominator(expected_count);
+        debug_assert!(!incremental_error.is_nan(), "The error must never be NaN.");
         sum += incremental_error;
     }
     sum
 }
 
+// TODO: explain how we got here.
+fn error_denominator(expected_count: i64) -> f64 {
+    if expected_count == 0 {
+        1.0
+    } else {
+        expected_count as f64
+    }
+}
+
 /// calculates the p-value given the test statistic and the degrees of freedom.
 /// This is determined by the area of the Chi Square distribution (which is a special
 /// case of the gamma distribution).