Add Utility Method in SampleMeasurement to convert Double2DArray To/From NDArray and List(List(Float)) (#1036)

* feat(array_utils): add utilities for converting Double2DArray to/from numpy NDArray and list(list(float))

* feat(measurement): Update SampleMeasurement to use utility method.

* feat(array_utils): add type hints to conversion functions and update mypy configuration

* fix lint issues

* fix: remove unused numpy import and update variable names

* feat(array_utils): update method signature and add tests for conversion methods

* fix: TypeError in _array_utils

* feat(array_utils): Add NDArray Type Def in method signatures

* refactor(array_utils): Update type hints and improve import structure for numpy compatibility

* refactor(tests): Rename utility tests for clarity and improve test function names

---------

Co-authored-by: Avi Goel <[email protected]>

Author: Blahpapto1

examples/sample_measurement/_array_utils.py

@@ -0,0 +1,45 @@
+"""Double2DArray Conversion Utilities."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, List
+
+from ni_measurement_plugin_sdk_service._internal.stubs.ni.protobuf.types import (
+    array_pb2,
+)
+
+if TYPE_CHECKING:
+    import numpy as np
+    import numpy.typing as npt
+
+
+def double2darray_to_ndarray(double2darray: array_pb2.Double2DArray) -> npt.NDArray[np.float64]:
+    """Convert Double2DArray to numpy NDArray."""
+    import numpy as np
+
+    return np.array(double2darray.data, dtype=np.float64).reshape(
+        double2darray.rows, double2darray.columns
+    )
+
+
+def ndarray_to_double2darray(ndarray: npt.NDArray[np.float64]) -> array_pb2.Double2DArray:
+    """Convert numpy NDArray to Double2DArray."""
+    return array_pb2.Double2DArray(
+        data=ndarray.flatten().tolist(), rows=ndarray.shape[0], columns=ndarray.shape[1]
+    )
+
+
+def list_to_double2darray(data: List[List[float]]) -> array_pb2.Double2DArray:
+    """Convert list of lists to Double2DArray."""
+    rows = len(data)
+    columns = len(data[0]) if rows > 0 else 0
+    flattened_data = [item for sublist in data for item in sublist]
+    return array_pb2.Double2DArray(data=flattened_data, rows=rows, columns=columns)
+
+
+def double2darray_to_list(double2darray: array_pb2.Double2DArray) -> List[List[float]]:
+    """Convert Double2DArray to list of lists."""
+    data = double2darray.data
+    rows = double2darray.rows
+    columns = double2darray.columns
+    return [data[i * columns : (i + 1) * columns] for i in range(rows)]

examples/sample_measurement/measurement.py

@@ -6,6 +6,7 @@
 from enum import Enum
 from typing import Iterable, Tuple
 
+import _array_utils
 import click
 import ni_measurement_plugin_sdk_service as nims
 from _helpers import configure_logging, verbosity_option
@@ -39,6 +40,13 @@ class Color(Enum):
     BLUE = 3
 
 
+# Define a list of lists of floats
+_list_of_lists = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]
+
+# Convert the list of lists to a Double2DArray
+_converted_double_2d_array = _array_utils.list_to_double2darray(_list_of_lists)
+
+
 @measurement_service.register_measurement
 @measurement_service.configuration("Float In", nims.DataType.Float, 0.06)
 @measurement_service.configuration("Double Array In", nims.DataType.DoubleArray1D, [0.1, 0.2, 0.3])
@@ -64,6 +72,7 @@ class Color(Enum):
 )
 @measurement_service.output("String Array out", nims.DataType.StringArray1D)
 @measurement_service.output("Double 2D Array Out", nims.DataType.Double2DArray)
+@measurement_service.output("Converted Double 2D Array", nims.DataType.Double2DArray)
 def measure(
     float_input: float,
     double_array_input: Iterable[float],
@@ -81,6 +90,7 @@ def measure(
     color_pb2.ProtobufColor.ValueType,
     Iterable[str],
     array_pb2.Double2DArray,
+    array_pb2.Double2DArray,
 ]:
     """Perform a loopback measurement with various data types."""
     logging.info("Executing measurement")
@@ -100,6 +110,7 @@ def cancel_callback() -> None:
     double_2d_array_output = array_pb2.Double2DArray(
         rows=2, columns=3, data=[1.5, 2.5, 3.5, 4.5, 5.5, 6.5]
     )
+    converted_double_2d_array_output = _converted_double_2d_array
     logging.info("Completed measurement")
 
     return (
@@ -111,6 +122,7 @@ def cancel_callback() -> None:
         protobuf_enum_output,
         string_array_output,
         double_2d_array_output,
+        converted_double_2d_array_output,
     )
 
 

examples/sample_measurement/pyproject.toml

@@ -27,5 +27,12 @@ build-backend = "poetry.core.masonry.api"
 [tool.mypy]
 disallow_untyped_defs = true
 
+[[tool.mypy.overrides]]
+module = [
+    # numpy has type hints but this example does not depend on numpy.
+    "numpy.*",
+]
+ignore_missing_imports = true
+
 [tool.ni-python-styleguide]
 extend_exclude = '*_pb2_grpc.py,*_pb2_grpc.pyi,*_pb2.py,*_pb2.pyi'

packages/service/tests/unit/test_array_utils.py

@@ -0,0 +1,43 @@
+import numpy
+import numpy.typing
+
+from ni_measurement_plugin_sdk_service._internal.stubs.ni.protobuf.types import (
+    array_pb2,
+)
+from tests.utilities import _array_utils
+
+
+def test___valid_double2darray___double2darray_to_ndarray___converts_data():
+    double2darray = array_pb2.Double2DArray(data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rows=2, columns=3)
+
+    ndarray = _array_utils.double2darray_to_ndarray(double2darray)
+
+    assert numpy.array_equal(ndarray, numpy.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]))
+
+
+def test___valid_ndarray___ndarray_to_double2darray___converts_data():
+    ndarray = numpy.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+
+    double2darray = _array_utils.ndarray_to_double2darray(ndarray)
+
+    assert double2darray == array_pb2.Double2DArray(
+        data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rows=2, columns=3
+    )
+
+
+def test___valid_list___list_to_double2darray___converts_data():
+    data = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]
+
+    double2darray = _array_utils.list_to_double2darray(data)
+
+    assert double2darray == array_pb2.Double2DArray(
+        data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rows=2, columns=3
+    )
+
+
+def test___valid_double2darray___double2darray_to_list___converts_data():
+    double2darray = array_pb2.Double2DArray(data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rows=2, columns=3)
+
+    data = _array_utils.double2darray_to_list(double2darray)
+
+    assert data == [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]

packages/service/tests/utilities/_array_utils.py

@@ -0,0 +1,45 @@
+"""Double2DArray Conversion Utilities."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, List
+
+from ni_measurement_plugin_sdk_service._internal.stubs.ni.protobuf.types import (
+    array_pb2,
+)
+
+if TYPE_CHECKING:
+    import numpy as np
+    import numpy.typing as npt
+
+
+def double2darray_to_ndarray(double2darray: array_pb2.Double2DArray) -> npt.NDArray[np.float64]:
+    """Convert Double2DArray to numpy NDArray."""
+    import numpy as np
+
+    return np.array(double2darray.data, dtype=np.float64).reshape(
+        double2darray.rows, double2darray.columns
+    )
+
+
+def ndarray_to_double2darray(ndarray: npt.NDArray[np.float64]) -> array_pb2.Double2DArray:
+    """Convert numpy NDArray to Double2DArray."""
+    return array_pb2.Double2DArray(
+        data=ndarray.flatten().tolist(), rows=ndarray.shape[0], columns=ndarray.shape[1]
+    )
+
+
+def list_to_double2darray(data: List[List[float]]) -> array_pb2.Double2DArray:
+    """Convert list of lists to Double2DArray."""
+    rows = len(data)
+    columns = len(data[0]) if rows > 0 else 0
+    flattened_data = [item for sublist in data for item in sublist]
+    return array_pb2.Double2DArray(data=flattened_data, rows=rows, columns=columns)
+
+
+def double2darray_to_list(double2darray: array_pb2.Double2DArray) -> List[List[float]]:
+    """Convert Double2DArray to list of lists."""
+    data = double2darray.data
+    rows = double2darray.rows
+    columns = double2darray.columns
+    return [data[i * columns : (i + 1) * columns] for i in range(rows)]