Fix handling of None and NaN filling values in MaskedImageMixin

Author: PierreRaybaut

CHANGELOG.md

@@ -1,5 +1,15 @@
 # Changelog #
 
+## Version 2.8.2 ##
+
+🛠️ Bug fixes:
+
+* Fixed `RuntimeWarning` when changing masked image data type from float to integer:
+  * `MaskedImageItem.update_mask()` now handles NaN and None `filling_value` gracefully
+  * When converting to integer dtypes, NaN/None values are replaced with 0 instead of triggering numpy cast warnings
+  * When converting to float dtypes, NaN is preserved as the fill value
+  * Added comprehensive tests to validate dtype conversion scenarios
+
 ## Version 2.8.1 ##
 
 🛠️ Bug fixes:

plotpy/items/image/masked.py

@@ -154,7 +154,17 @@ def update_mask(self) -> None:
             # in future versions of NumPy (at the time of writing, this raises a
             # DeprecationWarning "NumPy will stop allowing conversion of out-of-bound
             # Python integers to integer arrays.")
-            val = np.array(self.param.filling_value).astype(self.data.dtype)
+            filling_value = self.param.filling_value
+            if filling_value is None or (
+                isinstance(filling_value, float) and np.isnan(filling_value)
+            ):
+                # Use a safe default for integer types when filling_value is None or NaN
+                if np.issubdtype(self.data.dtype, np.integer):
+                    val = np.array(0, dtype=self.data.dtype)
+                else:
+                    val = np.array(np.nan, dtype=self.data.dtype)
+            else:
+                val = np.array(filling_value).astype(self.data.dtype)
 
             self.data.set_fill_value(val)
 

plotpy/tests/unit/test_masked_dtype_change.py

@@ -0,0 +1,121 @@
+# -*- coding: utf-8 -*-
+#
+# Licensed under the terms of the BSD 3-Clause
+# (see plotpy/LICENSE for details)
+
+"""
+Test for MaskedImageItem dtype changes
+
+This test verifies that changing the data type of a masked image from float to
+integer types (like float64 to uint8) doesn't raise RuntimeWarnings when the
+filling_value is NaN or None.
+"""
+
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from plotpy.builder import make
+
+
+def test_masked_image_dtype_change_from_float_to_uint8():
+    """Test changing masked image dtype from float64 to uint8 with NaN filling_value"""
+    # Create a float64 masked array with NaN as fill value (the default)
+    data = np.random.rand(10, 10).astype(np.float64)
+    mask = np.zeros_like(data, dtype=bool)
+    mask[3:5, 3:5] = True
+    masked_data = np.ma.masked_array(data, mask=mask)
+
+    # Create masked image item
+    item = make.maskedimage(masked_data, colormap="viridis", show_mask=True)
+
+    # Verify initial state
+    assert item.data.dtype == np.float64
+
+    # Set filling_value to NaN (typical for float images)
+    item.param.filling_value = np.nan
+
+    # Change data dtype to uint8
+    new_data = (masked_data * 255).astype(np.uint8)
+    item.set_data(new_data)
+
+    # This should not raise a RuntimeWarning
+    with pytest.warns(None) as warning_list:
+        item.update_mask()
+
+    # Check that no RuntimeWarning was raised
+    runtime_warnings = [
+        w for w in warning_list if issubclass(w.category, RuntimeWarning)
+    ]
+    assert len(runtime_warnings) == 0, "RuntimeWarning should not be raised"
+
+    # Verify the data type changed
+    assert item.data.dtype == np.uint8
+
+
+def test_masked_image_dtype_change_with_none_filling_value():
+    """Test changing masked image dtype with None filling_value"""
+    # Create a float64 masked array
+    data = np.random.rand(10, 10).astype(np.float64)
+    mask = np.zeros_like(data, dtype=bool)
+    mask[3:5, 3:5] = True
+    masked_data = np.ma.masked_array(data, mask=mask)
+
+    # Create masked image item
+    item = make.maskedimage(masked_data, colormap="viridis", show_mask=True)
+
+    # Set filling_value to None
+    item.param.filling_value = None
+
+    # Change data dtype to uint8
+    new_data = (masked_data * 255).astype(np.uint8)
+    item.set_data(new_data)
+
+    # This should not raise a RuntimeWarning
+    with pytest.warns(None) as warning_list:
+        item.update_mask()
+
+    # Check that no RuntimeWarning was raised
+    runtime_warnings = [
+        w for w in warning_list if issubclass(w.category, RuntimeWarning)
+    ]
+    assert len(runtime_warnings) == 0, "RuntimeWarning should not be raised"
+
+
+def test_masked_image_filling_value_defaults():
+    """Test that filling_value defaults are appropriate for different dtypes"""
+    test_dtypes = [np.uint8, np.uint16, np.int16, np.float32, np.float64]
+
+    for dtype in test_dtypes:
+        data = np.random.rand(5, 5)
+        if np.issubdtype(dtype, np.integer):
+            data = (data * 100).astype(dtype)
+        else:
+            data = data.astype(dtype)
+
+        mask = np.zeros_like(data, dtype=bool)
+        mask[2:3, 2:3] = True
+        masked_data = np.ma.masked_array(data, mask=mask)
+
+        item = make.maskedimage(masked_data, colormap="viridis", show_mask=True)
+
+        # Set filling_value to NaN (typical initial state for float images)
+        item.param.filling_value = np.nan
+
+        # This should handle the conversion gracefully
+        with pytest.warns(None) as warning_list:
+            item.update_mask()
+
+        # Check that no RuntimeWarning was raised
+        runtime_warnings = [
+            w for w in warning_list if issubclass(w.category, RuntimeWarning)
+        ]
+        assert len(runtime_warnings) == 0, f"RuntimeWarning for dtype {dtype}"
+
+
+if __name__ == "__main__":
+    test_masked_image_dtype_change_from_float_to_uint8()
+    test_masked_image_dtype_change_with_none_filling_value()
+    test_masked_image_filling_value_defaults()
+    print("All tests passed!")