fix: Regression in hist panicking on out of bounds index

crates/polars-ops/src/chunked_array/hist.rs

@@ -93,21 +93,22 @@ where
     let min_break: f64 = breaks[0];
     let max_break: f64 = breaks[num_bins];
     let width = breaks[1] - min_break; // guaranteed at least one bin
-    let is_integer = !T::get_dtype().is_float();
 
     for chunk in ca.downcast_iter() {
         for item in chunk.non_null_values_iter() {
             let item = item.to_f64().unwrap();
             if include_lower && item == min_break {
                 count[0] += 1;
-            } else if item > min_break && item <= max_break {
-                let idx = (item - min_break) / width;
-                // This is needed for numeric stability for integers.
-                // We can fall directly on a boundary with an integer.
-                let idx = if is_integer && (idx.round() - idx).abs() < 0.0000001 {
-                    idx.round() - 1.0
+            } else if item == max_break {
+                count[num_bins - 1] += 1;
+            } else if item > min_break && item < max_break {
+                let width_multiple = (item - min_break) / width;
+                let idx = width_multiple.floor();
+                // handle the case where item lands on the boundary
+                let idx = if idx == width_multiple {
+                    idx - 1.0
                 } else {
-                    idx.ceil() - 1.0
+                    idx
                 };
                 count[idx as usize] += 1;
             }

py-polars/tests/unit/operations/test_hist.py

@@ -410,3 +410,16 @@ def test_hist_floating_point() -> None:
         upper = bp[i]
 
         assert ((s <= upper) & (s > lower)).sum() == count[i]
+
+
+def test_hist_max_boundary_19998() -> None:
+    s = pl.Series(
+        [
+            9514.988509739183,
+            30738.098872148617,
+            41400.15705103004,
+            49093.06982022727,
+        ]
+    )
+    result = s.hist(bin_count=50)
+    assert result["count"].sum() == 4