API: Add complex.DataArray.npview() function

Signed-off-by: Michael Jackson <[email protected]>
BlueQuartzSoftware · Oct 17, 2023 · 031a04b · 031a04b
1 parent 677ddc6
commit 031a04b
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Showing 8 changed files with 29 additions and 47 deletions.
diff --git a/src/Plugins/ComplexCore/wrapping/python/complexpy.cpp b/src/Plugins/ComplexCore/wrapping/python/complexpy.cpp
@@ -169,6 +169,19 @@ auto BindDataArray(py::handle scope, const char* name)
 {
   py::class_<DataArray<T>, IDataArray, std::shared_ptr<DataArray<T>>> dataArray(scope, name);
   dataArray.def_property_readonly_static("dtype", []([[maybe_unused]] py::object self) { return py::dtype::of<T>(); });
+  dataArray.def(
+      "npview",
+      [](DataArray<T>& dataArray) {
+        using DataArrayType = DataArray<T>;
+        using DataStoreType = DataStore<T>;
+        const typename DataArrayType::store_type& abstractDataStore = dataArray.getDataStoreRef();
+        const DataStoreType& dataStore = dynamic_cast<const DataStoreType&>(abstractDataStore);
+        IDataStore::ShapeType shape = dataStore.getTupleShape();
+        IDataStore::ShapeType componentShape = dataStore.getComponentShape();
+        shape.insert(shape.end(), componentShape.cbegin(), componentShape.cend());
+        return py::array_t<T, py::array::c_style>(shape, dataStore.data(), py::cast(dataStore));
+      },
+      py::return_value_policy::reference_internal);
   return dataArray;
 }
 

diff --git a/wrapping/python/docs/source/Python_Introduction.rst b/wrapping/python/docs/source/Python_Introduction.rst
@@ -307,15 +307,8 @@ The next code section was take from `basic_arrays.py <https://github.com/BlueQua
                                         output_data_array=output_array_path, 
                                         tuple_dimensions=tuple_dims)
 
-    # First get the array from the DataStructure
-    data_array = data_structure[output_array_path]
-    # Get the underlying complex.DataStore object
-    data_store = data_array.store
     # Get the raw data as an Numpy View
-    npdata = data_store.npview()
-
-    # The developer could also just do this in a single line
-    npdata = data_structure[output_array_path].store.npview()
+    npdata = data_structure[output_array_path].npview()
 
 The next code section was take from `basic_arrays.py <https://github.com/BlueQuartzSoftware/complex/tree/develop/wrapping/python/examples/angle_conversion.py>`__
 

diff --git a/wrapping/python/examples/angle_conversion.py b/wrapping/python/examples/angle_conversion.py
@@ -26,11 +26,7 @@
     print("No errors running the CreateDataArray")
 
 # Get a numpy.view into the newly created DataArray
-data_array = data_structure[array_path]
-# Get the underlying DataStore object
-data_store = data_array.store
-# Get a Numpy View into the data
-npdata = data_store.npview()
+npdata = data_structure[array_path].npview()
 
 # Read the CSV file into the DataArray using the numpy view
 file_path = 'angles.csv'

diff --git a/wrapping/python/examples/basic_arrays.py b/wrapping/python/examples/basic_arrays.py
@@ -37,12 +37,7 @@
     print("No errors running the filter")
 
 # We can check the output of the filter by simply printing the array
-# First get the array from the DataStructure
-data_array = data_structure[output_array_path]
-# Get the underlying DataStore object
-data_store = data_array.store
-# Get the raw data as an Numpy View
-npdata = data_store.npview()
+npdata = data_structure[output_array_path].npview()
 print(npdata)
 
 #------------------------------------------------------------------------------
@@ -68,9 +63,7 @@
 else:
     print("No errors running the filter")
 
-data_array = data_structure[output_array_path]
-data_store = data_array.store
-npdata = data_store.npview()
+npdata = data_structure[output_array_path].npview()
 print(npdata)
 
 
@@ -97,9 +90,7 @@
 else:
     print("No errors running the filter")
 
-data_array = data_structure[output_array_path]
-data_store = data_array.store
-npdata = data_store.npview()
+npdata = data_structure[output_array_path].npview()
 print(npdata)
 
 result = cx.CreateAttributeMatrixFilter.execute(data_structure=data_structure, 

diff --git a/wrapping/python/examples/basic_numpy.py b/wrapping/python/examples/basic_numpy.py
@@ -23,12 +23,7 @@
                                   output_data_array=array_path, 
                                   initialization_value='0')
 
-
-data_array = data_structure[array_path]
-# Get the underlying DataStore object
-data_store = data_array.store
-# Get a Numpy View into the data
-npdata = data_store.npview()
+npdata = data_structure[array_path].npview()
 # Manipulate the underlying array
 npdata += 42.0
 

diff --git a/wrapping/python/examples/geometry_examples.py b/wrapping/python/examples/geometry_examples.py
@@ -65,7 +65,7 @@
                                         output_data_array=output_array_path, 
                                         tuple_dimensions=tuple_dims)
 
-x_coords =  data_structure[output_array_path].store.npview()
+x_coords = data_structure[output_array_path].npview()
 x_coords = np.squeeze(x_coords, axis=1)
 x_coords[:] = np.arange(0, 10, 1)
 
@@ -81,7 +81,7 @@
                                         output_data_array=output_array_path, 
                                         tuple_dimensions=tuple_dims)
 
-y_coords =  data_structure[output_array_path].store.npview()
+y_coords = data_structure[output_array_path].npview()
 y_coords = np.squeeze(y_coords, axis=1)
 y_coords[:] = np.arange(10, 20, 1)
 
@@ -97,7 +97,7 @@
                                         output_data_array=output_array_path, 
                                         tuple_dimensions=tuple_dims)
 
-z_coords =  data_structure[output_array_path].store.npview()
+z_coords = data_structure[output_array_path].npview()
 z_coords = np.squeeze(z_coords, axis=1)
 z_coords[:] = np.arange(20, 30, 1)
 
@@ -131,7 +131,7 @@
                                     initialization_value='0')
 
 # Read the CSV file into the DataArray using the numpy view
-vertex_coords = data_structure[array_path].store.npview()
+vertex_coords = data_structure[array_path].npview()
 file_path = 'complex/test/Data/VertexCoordinates.csv'
 vertex_coords[:] = np.loadtxt(file_path, delimiter=',', skiprows=1)
 
@@ -145,7 +145,7 @@
                                     initialization_value='0')
 
 # Read the CSV file into the DataArray using the numpy view
-triangles = data_structure[array_path].store.npview()
+triangles = data_structure[array_path].npview()
 file_path = 'complex/test/Data/TriangleConnectivity.csv'
 triangles[:] = np.loadtxt(file_path, delimiter=',', skiprows=1)
 
@@ -179,7 +179,7 @@
                                     initialization_value='0')
 
 # Read the CSV file into the DataArray using the numpy view
-vertex_coords = data_structure[array_path].store.npview()
+vertex_coords = data_structure[array_path].npview()
 file_path = 'complex/test/Data/VertexCoordinates.csv'
 vertex_coords[:] = np.loadtxt(file_path, delimiter=',', skiprows=1)
 
@@ -193,7 +193,7 @@
                                     initialization_value='0')
 
 # Read the CSV file into the DataArray using the numpy view
-edges = data_structure[array_path].store.npview()
+edges = data_structure[array_path].npview()
 file_path = 'complex/test/Data/EdgeConnectivity.csv'
 edges[:] = np.loadtxt(file_path, delimiter=',', skiprows=1)
 

diff --git a/wrapping/python/examples/import_d3d.py b/wrapping/python/examples/import_d3d.py
@@ -26,12 +26,8 @@
 #------------------------------------------------------------------------------
 # Get the underlying data from the DataStructure
 #------------------------------------------------------------------------------
-data_array = data_structure[cx.DataPath(["Small IN100", "Scan Data", "Image Quality"])]
-# Get the underlying DataStore object
-data_store = data_array.store
+npview = data_structure[["Small IN100", "Scan Data", "Image Quality"]].npview()
 
-# Get a View into the DataArray through a Numpy.View
-npview = data_store.npview()
 # Change the underlying data based on some criteria using Numpy
 npview[npview < 120] = 0
 
@@ -53,7 +49,7 @@
 # View with MatPlotLib
 #------------------------------------------------------------------------------
 # Make a copy to that we can use MatPlotLib
-npdata = data_store.npview().copy()
+npdata = data_structure[["Small IN100", "Scan Data", "Image Quality"]].npview().copy()
 
 # Remove any dimension with '1' for MatPlotLib?
 npdata = np.squeeze(npdata, axis=0)

diff --git a/wrapping/python/examples/output_file.py b/wrapping/python/examples/output_file.py
@@ -25,9 +25,7 @@
 else:
     print("No errors running the filter")
 
-data_array = data_structure[output_array_path]
-data_store = data_array.store
-npdata = data_store.npview()
+npdata = data_structure[output_array_path].npview()
 print(npdata)
 
 output_file_path = "output_file_example.dream3d"