Fix bug occurring when using ToolBaseplate with *_dtype_hint='preserve' for bool images

giatools/image.py

@@ -480,8 +480,19 @@ def clip_to_dtype(self, dtype: _np.dtype, force_copy: bool = False) -> _T.Self:
         Raises:
             TypeError: If `dtype` is `bool`.
         """
-        if dtype in (bool, _np.bool_):
-            raise TypeError('Clipping to boolean dtype is not supported.')
+        if _np.issubdtype(dtype, bool):
+            if _np.issubdtype(self.data.dtype, bool):
+                if force_copy:
+                    return Image(
+                        data=self.data.copy(),
+                        axes=self.axes,
+                        original_axes=self.original_axes,
+                        metadata=self.metadata,
+                    )
+                else:
+                    return self
+            else:
+                raise TypeError('Clipping to boolean dtype is not supported.')
 
         # Determine the actual range of the source image
         min_src_value, max_src_value = _get_min_max_values(self.data)

giatools/version.py

@@ -1,5 +1,5 @@
 VERSION_MAJOR = 0
 VERSION_MINOR = 7
-VERSION_PATCH = 2
+VERSION_PATCH = 3
 
 __version__ = '%d.%d.%d' % (VERSION_MAJOR, VERSION_MINOR, VERSION_PATCH)

tests/integration/test__cli.py

@@ -4,6 +4,7 @@
 import subprocess
 import sys
 import tempfile
+import types
 import unittest
 
 import numpy as np
@@ -12,7 +13,10 @@
 import giatools.image
 import giatools.typing as _T
 
-from ..tools import minimum_python_version
+from ..tools import (
+    minimum_python_version,
+    random_io_test,
+)
 
 
 def _threshold(image1: np.ndarray, image2: _T.Optional[np.ndarray]) -> np.ndarray:
@@ -45,7 +49,7 @@ def _threshold(image1: np.ndarray, image2: _T.Optional[np.ndarray]) -> np.ndarra
             proc['output'] = _threshold(proc['input1'].data, None)
 
 
-class ToolBaseplate(unittest.TestCase):
+class ToolBaseplate__cli(unittest.TestCase):
 
     def setUp(self):
         super().setUp()
@@ -159,3 +163,24 @@ def test__params(self):
                 '--output', output_filepath,
             )
             self.assertEqual(result.stdout.strip('\n'), str(params))
+
+
+class ToolBaseplate(unittest.TestCase):
+
+    @minimum_python_version(3, 11)
+    @random_io_test(shape=(10, 10), dtype=bool, ext='tiff')
+    def test__preserve__bool(self, filepath, data):
+        output_filepath = str(pathlib.Path(filepath).parent / 'output.tiff')
+        tool = giatools.cli.ToolBaseplate(params_required=False)
+        tool.add_input_image('input')
+        tool.add_output_image('output')
+        tool.args = types.SimpleNamespace(
+            params=None,
+            verbose=False,
+            input_filepaths={'input': filepath},
+            input_images={'input': giatools.image.Image(data, axes='YX', original_axes='YX')},
+            output_filepaths={'output': output_filepath},
+            raw_args=types.SimpleNamespace(),
+        )
+        for section in tool.run('YX', output_dtype_hint='preserve'):
+            section['output'] = section['input'].data

tests/tools.py

@@ -61,8 +61,14 @@ def wrapper(self):
                 # Create random image data
                 np.random.seed(0)
                 data = np.random.rand(*shape)
-                if not np.issubdtype(dtype, np.floating):
+                if np.issubdtype(dtype, np.floating):
+                    pass
+                elif np.issubdtype(dtype, np.integer):
                     data = (data * np.iinfo(dtype).max).astype(dtype)
+                elif np.issubdtype(dtype, bool):
+                    data = (data > 0.5).round().astype(bool)
+                else:
+                    assert False, f'Unsupported dtype {dtype}'
 
                 # Supply a temporary file to write the image to
                 filepath = os.path.join(temp_path, f'test.{ext}')

tests/unit/test__image.py

@@ -195,24 +195,40 @@ def test__spurious_axis(self):
 
 class Image__clip_to_dtype(ImageTestCase):
 
+    def _issubdtype(self, a, b):
+        ret = self._issubdtype__results.get((a, b), None)
+        assert ret is not None, f'Unexpected args to issubdtype: {a}, {b}'
+        return ret
+
     def test__bool(self):
+        self._issubdtype__results = {
+            (bool, bool): True,
+            (self.img1.data.dtype, bool): False,
+        }
+        self._np.issubdtype.side_effect = self._issubdtype
         with self.assertRaises(TypeError):
             self.img1.clip_to_dtype(bool)
 
     def test__to_superset_int(self):
         self._get_min_max_values.return_value = (-15, +15)
-        self._np.issubdtype.return_value = True  # target dtype is an integer type
+        self._issubdtype__results = {
+            (self._np.uint8, bool): False,
+            (self._np.uint8, self._np.integer): True,  # target dtype is an integer type
+        }
         self._np.iinfo.return_value.min = -15
         self._np.iinfo.return_value.max = +15
-        img_clipped = self.img1.clip_to_dtype('mocked-int-type')
+        img_clipped = self.img1.clip_to_dtype(self._np.uint8)
         self.assertIs(img_clipped, self.img1)
         self.img1.data.copy.assert_not_called()
 
     def test__to_superset_float(self):
         self._get_min_max_values.return_value = (-15, +15)
-        self._np.issubdtype.return_value = False  # target dtype is a float type
+        self._issubdtype__results = {
+            (self._np.uint8, bool): False,
+            (self._np.uint8, self._np.integer): False,  # target dtype is a float type
+        }
         self._np.finfo.return_value.min.item.return_value = -15.
         self._np.finfo.return_value.max.item.return_value = +15.
-        img_clipped = self.img1.clip_to_dtype('mocked-float-type')
+        img_clipped = self.img1.clip_to_dtype(self._np.float64)
         self.assertIs(img_clipped, self.img1)
         self.img1.data.copy.assert_not_called()