BUG: transform_to_displacement_field_filter type inference

Customize implementation since we do not have a image arg that can used
to infer the filter type.

Output type is itk.Imgae[itk.Vector[itk.F, output_dim], output_dim]
because that is what is wrapped.

Closes #3860

Modules/Filtering/DisplacementField/wrapping/test/CMakeLists.txt

@@ -1,4 +1,6 @@
 if(ITK_WRAP_PYTHON)
   itk_python_add_test(NAME itkDisplacementFieldTransformPythonTest
                       COMMAND ${CMAKE_CURRENT_SOURCE_DIR}/itkDisplacementFieldTransformTest.py)
+  itk_python_add_test(NAME itkTransformToDisplacementFieldPythonTest
+                      COMMAND ${CMAKE_CURRENT_SOURCE_DIR}/itkTransformToDisplacementFieldTest.py)
 endif()

Modules/Filtering/DisplacementField/wrapping/test/itkTransformToDisplacementFieldTest.py

@@ -0,0 +1,29 @@
+# ==========================================================================
+#
+#   Copyright NumFOCUS
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#          https://www.apache.org/licenses/LICENSE-2.0.txt
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+#
+# ==========================================================================*/
+import numpy as np
+import itk
+
+itk.auto_progress(2)
+
+img = itk.image_from_array(np.zeros((10, 10, 10)))
+transform = itk.IdentityTransform[itk.D, 3].New()
+field = itk.transform_to_displacement_field_filter(
+    transform,
+    reference_image=img,
+    use_reference_image=True)
+print(field)

Wrapping/Generators/SwigInterface/igenerator.py

@@ -1210,6 +1210,34 @@ def generate_process_object_snake_case_functions(self, typedefs):
                 elif any([b.startswith("PathSource") for b in bases]):
                     return_typehint = "-> itkt.PathSourceReturn"
 
+                instantiation = f"""
+
+    instance = itk.{process_object}.New(*args, **kwargs)
+"""
+                if snake_case == 'transform_to_displacement_field_filter':
+                    instantiation = f"""
+    transform = None
+    if len(args):
+        transform = args[0]
+    elif 'transform' in kwargs:
+        transform = kwargs.pop('transform')
+    elif 'transform_input' in kwargs:
+        transform = kwargs.pop('transform_input')
+    else:
+        raise ValueError('A transform is required. Pass as the first argument.')
+
+    input_dim = transform.GetInputSpaceDimension()
+    output_dim = transform.GetOutputSpaceDimension()
+    ParametersType = itk.template(transform)[1][0]
+
+    decorator = itk.DataObjectDecorator[itk.Transform[ParametersType, input_dim, output_dim]].New()
+    decorator.Set(transform)
+
+    FieldType = itk.Image[itk.Vector[itk.F, output_dim], output_dim]
+
+    args = (decorator,)
+    instance = itk.TransformToDisplacementFieldFilter[FieldType, ParametersType].New(*args, **kwargs)
+"""
                 # print(args_typehint, kwargs_typehints, return_typehint)
                 self.outputFile.write(
                     f"""from itk.support import helpers
@@ -1224,8 +1252,7 @@ def {snake_case}(*args{args_typehint}, {kwargs_typehints}**kwargs){return_typehi
     kwarg_typehints = {{ {kwarg_dict} }}
     specified_kwarg_typehints = {{ k:v for (k,v) in kwarg_typehints.items() if kwarg_typehints[k] is not ... }}
     kwargs.update(specified_kwarg_typehints)
-
-    instance = itk.{process_object}.New(*args, **kwargs)
+{instantiation}
     return instance.__internal_call__()
 
 def {snake_case}_init_docstring():