waveform: Add __eq__ and __repr__ magic methods (#11)

* waveform: Implement __eq__

* waveform: Implement repr and corresponding constructor arguments

* tests: Remove an xfail

Author: bkeryan

src/nitypes/waveform/_analog_waveform.py

@@ -3,7 +3,7 @@
 import datetime as dt
 import sys
 import warnings
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from typing import Any, Generic, SupportsIndex, TypeVar, Union, cast, overload
 
 import hightime as ht
@@ -17,6 +17,7 @@
     CHANNEL_NAME,
     UNIT_DESCRIPTION,
     ExtendedPropertyDictionary,
+    ExtendedPropertyValue,
 )
 from nitypes.waveform._scaling import NO_SCALING, ScaleMode
 from nitypes.waveform._timing import BaseTiming, PrecisionTiming, Timing, convert_timing
@@ -83,6 +84,9 @@ def from_array_1d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> AnalogWaveform[_ScalarType]: ...
 
     @overload
@@ -94,6 +98,9 @@ def from_array_1d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> AnalogWaveform[_ScalarType]: ...
 
     @overload
@@ -105,6 +112,9 @@ def from_array_1d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> AnalogWaveform[Any]: ...
 
     @staticmethod
@@ -115,6 +125,9 @@ def from_array_1d(
         copy: bool = True,
         start_index: SupportsIndex | None = 0,
         sample_count: SupportsIndex | None = None,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = None,
+        timing: Timing | PrecisionTiming | None = None,
+        scale_mode: ScaleMode | None = None,
     ) -> AnalogWaveform[_ScalarType]:
         """Construct an analog waveform from a one-dimensional array or sequence.
 
@@ -125,6 +138,9 @@ def from_array_1d(
             copy: Specifies whether to copy the array or save a reference to it.
             start_index: The sample index at which the analog waveform data begins.
             sample_count: The number of samples in the analog waveform.
+            extended_properties: The extended properties of the analog waveform.
+            timing: The timing information of the analog waveform.
+            scale_mode: The scale mode of the analog waveform.
 
         Returns:
             An analog waveform containing the specified data.
@@ -143,9 +159,12 @@ def from_array_1d(
             raise invalid_arg_type("input array", "one-dimensional array or sequence", array)
 
         return AnalogWaveform(
-            _data=np.asarray(array, dtype, copy=copy),
+            raw_data=np.asarray(array, dtype, copy=copy),
             start_index=start_index,
             sample_count=sample_count,
+            extended_properties=extended_properties,
+            timing=timing,
+            scale_mode=scale_mode,
         )
 
     @overload
@@ -157,6 +176,9 @@ def from_array_2d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> list[AnalogWaveform[_ScalarType]]: ...
 
     @overload
@@ -168,6 +190,9 @@ def from_array_2d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> list[AnalogWaveform[_ScalarType]]: ...
 
     @overload
@@ -179,6 +204,9 @@ def from_array_2d(
         copy: bool = ...,
         start_index: SupportsIndex | None = ...,
         sample_count: SupportsIndex | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> list[AnalogWaveform[Any]]: ...
 
     @staticmethod
@@ -189,6 +217,9 @@ def from_array_2d(
         copy: bool = True,
         start_index: SupportsIndex | None = 0,
         sample_count: SupportsIndex | None = None,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = None,
+        timing: Timing | PrecisionTiming | None = None,
+        scale_mode: ScaleMode | None = None,
     ) -> list[AnalogWaveform[_ScalarType]]:
         """Construct a list of analog waveforms from a two-dimensional array or nested sequence.
 
@@ -199,9 +230,16 @@ def from_array_2d(
             copy: Specifies whether to copy the array or save a reference to it.
             start_index: The sample index at which the analog waveform data begins.
             sample_count: The number of samples in the analog waveform.
+            extended_properties: The extended properties of the analog waveform.
+            timing: The timing information of the analog waveform.
+            scale_mode: The scale mode of the analog waveform.
 
         Returns:
             A list containing an analog waveform for each row of the specified data.
+
+        When constructing multiple analog waveforms, the same extended properties, timing
+        information, and scale mode are applied to all analog waveforms. Consider assigning
+        these properties after construction.
         """
         if isinstance(array, np.ndarray):
             if array.ndim != 2:
@@ -218,9 +256,12 @@ def from_array_2d(
 
         return [
             AnalogWaveform(
-                _data=np.asarray(array[i], dtype, copy=copy),
+                raw_data=np.asarray(array[i], dtype, copy=copy),
                 start_index=start_index,
                 sample_count=sample_count,
+                extended_properties=extended_properties,
+                timing=timing,
+                scale_mode=scale_mode,
             )
             for i in range(len(array))
         ]
@@ -251,9 +292,12 @@ def __init__(  # noqa: D107 - Missing docstring in __init__ (auto-generated noqa
         sample_count: SupportsIndex | None = ...,
         dtype: None = ...,
         *,
+        raw_data: None = ...,
         start_index: SupportsIndex | None = ...,
         capacity: SupportsIndex | None = ...,
-        _data: None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> None: ...
 
     @overload
@@ -262,9 +306,12 @@ def __init__(  # noqa: D107 - Missing docstring in __init__ (auto-generated noqa
         sample_count: SupportsIndex | None = ...,
         dtype: type[_ScalarType_co] | np.dtype[_ScalarType_co] = ...,
         *,
+        raw_data: None = ...,
         start_index: SupportsIndex | None = ...,
         capacity: SupportsIndex | None = ...,
-        _data: None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> None: ...
 
     @overload
@@ -273,9 +320,12 @@ def __init__(  # noqa: D107 - Missing docstring in __init__ (auto-generated noqa
         sample_count: SupportsIndex | None = ...,
         dtype: None = ...,
         *,
+        raw_data: npt.NDArray[_ScalarType_co] | None = ...,
         start_index: SupportsIndex | None = ...,
         capacity: SupportsIndex | None = ...,
-        _data: npt.NDArray[_ScalarType_co] | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> None: ...
 
     @overload
@@ -284,45 +334,71 @@ def __init__(  # noqa: D107 - Missing docstring in __init__ (auto-generated noqa
         sample_count: SupportsIndex | None = ...,
         dtype: npt.DTypeLike = ...,
         *,
+        raw_data: npt.NDArray[Any] | None = ...,
         start_index: SupportsIndex | None = ...,
         capacity: SupportsIndex | None = ...,
-        _data: npt.NDArray[Any] | None = ...,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = ...,
+        timing: Timing | PrecisionTiming | None = ...,
+        scale_mode: ScaleMode | None = ...,
     ) -> None: ...
 
     def __init__(
         self,
         sample_count: SupportsIndex | None = None,
         dtype: npt.DTypeLike = None,
         *,
+        raw_data: npt.NDArray[_ScalarType_co] | None = None,
         start_index: SupportsIndex | None = None,
         capacity: SupportsIndex | None = None,
-        _data: npt.NDArray[_ScalarType_co] | None = None,
+        extended_properties: Mapping[str, ExtendedPropertyValue] | None = None,
+        timing: Timing | PrecisionTiming | None = None,
+        scale_mode: ScaleMode | None = None,
     ) -> None:
         """Construct an analog waveform.
 
         Args:
             sample_count: The number of samples in the analog waveform.
             dtype: The NumPy data type for the analog waveform data. If not specified, the data
                 type defaults to np.float64.
+            raw_data: A NumPy ndarray to use for sample storage. The analog waveform takes ownership
+                of this array. If not specified, an ndarray is created based on the specified dtype,
+                start index, sample count, and capacity.
             start_index: The sample index at which the analog waveform data begins.
             sample_count: The number of samples in the analog waveform.
             capacity: The number of samples to allocate. Pre-allocating a larger buffer optimizes
                 appending samples to the waveform.
+            extended_properties: The extended properties of the analog waveform.
+            timing: The timing information of the analog waveform.
+            scale_mode: The scale mode of the analog waveform.
 
         Returns:
             An analog waveform.
-
-        Arguments that are prefixed with an underscore are internal implementation details and are
-        subject to change.
         """
-        if _data is None:
+        if raw_data is None:
             self._init_with_new_array(
                 sample_count, dtype, start_index=start_index, capacity=capacity
             )
-        else:
+        elif isinstance(raw_data, np.ndarray):
             self._init_with_provided_array(
-                _data, dtype, start_index=start_index, sample_count=sample_count, capacity=capacity
+                raw_data,
+                dtype,
+                start_index=start_index,
+                sample_count=sample_count,
+                capacity=capacity,
             )
+        else:
+            raise invalid_arg_type("raw data", "NumPy ndarray", raw_data)
+
+        self._extended_properties = ExtendedPropertyDictionary(extended_properties)
+
+        if timing is None:
+            timing = Timing.empty
+        self._timing = timing
+        self._converted_timing_cache = {}
+
+        if scale_mode is None:
+            scale_mode = NO_SCALING
+        self._scale_mode = scale_mode
 
     def _init_with_new_array(
         self,
@@ -357,10 +433,6 @@ def _init_with_new_array(
         self._data = np.zeros(capacity, dtype)
         self._start_index = start_index
         self._sample_count = sample_count
-        self._extended_properties = ExtendedPropertyDictionary()
-        self._timing = Timing.empty
-        self._converted_timing_cache = {}
-        self._scale_mode = NO_SCALING
 
     def _init_with_provided_array(
         self,
@@ -414,10 +486,6 @@ def _init_with_provided_array(
         self._data = data
         self._start_index = start_index
         self._sample_count = sample_count
-        self._extended_properties = ExtendedPropertyDictionary()
-        self._timing = Timing.empty
-        self._converted_timing_cache = {}
-        self._scale_mode = NO_SCALING
 
     @property
     def raw_data(self) -> npt.NDArray[_ScalarType_co]:
@@ -784,3 +852,32 @@ def _increase_capacity(self, amount: int) -> None:
         new_capacity = self._start_index + self._sample_count + amount
         if new_capacity > self.capacity:
             self.capacity = new_capacity
+
+    def __eq__(self, value: object, /) -> bool:
+        """Return self==value."""
+        if not isinstance(value, self.__class__):
+            return NotImplemented
+        return (
+            self.dtype == value.dtype
+            and np.array_equal(self.raw_data, value.raw_data)
+            and self._extended_properties == value._extended_properties
+            and self._timing == value._timing
+            and self._scale_mode == value._scale_mode
+        )
+
+    def __repr__(self) -> str:
+        """Return repr(self)."""
+        args = [f"{self._sample_count}"]
+        if self.dtype != np.float64:
+            args.append(f"{self.dtype.name}")
+        # start_index and capacity are not shown because they are allocation details. raw_data hides
+        # the unused data before start_index and after start_index+sample_count.
+        if self._sample_count > 0:
+            args.append(f"raw_data={self.raw_data!r}")
+        if self._extended_properties:
+            args.append(f"extended_properties={self._extended_properties._properties!r}")
+        if self._timing is not Timing.empty and self._timing is not PrecisionTiming.empty:
+            args.append(f"timing={self._timing!r}")
+        if self._scale_mode is not NO_SCALING:
+            args.append(f"scale_mode={self._scale_mode}")
+        return f"{self.__class__.__module__}.{self.__class__.__name__}({', '.join(args)})"

src/nitypes/waveform/_extended_properties.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import operator
+from collections.abc import Mapping
 from typing import Iterator, MutableMapping, Union
 
 from nitypes._typing import TypeAlias
@@ -18,40 +19,40 @@
 class ExtendedPropertyDictionary(MutableMapping[str, ExtendedPropertyValue]):
     """A dictionary of extended properties."""
 
-    def __init__(self) -> None:
+    def __init__(self, properties: Mapping[str, ExtendedPropertyValue] | None = None, /) -> None:
         """Construct an ExtendedPropertyDictionary."""
         self._properties: dict[str, ExtendedPropertyValue] = {}
+        if properties is not None:
+            self._properties.update(properties)
 
-    def __len__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self,
-    ) -> int:
+    def __len__(self) -> int:
+        """Return len(self)."""
         return len(self._properties)
 
-    def __iter__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self,
-    ) -> Iterator[str]:
+    def __iter__(self) -> Iterator[str]:
+        """Implement iter(self)."""
         return iter(self._properties)
 
-    def __contains__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self, x: object, /
-    ) -> bool:
-        return operator.contains(self._properties, x)
+    def __contains__(self, value: object, /) -> bool:
+        """Implement value in self."""
+        return operator.contains(self._properties, value)
 
-    def __getitem__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self, key: str, /
-    ) -> ExtendedPropertyValue:
+    def __getitem__(self, key: str, /) -> ExtendedPropertyValue:
+        """Get self[key]."""
         return operator.getitem(self._properties, key)
 
-    def __setitem__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self, key: str, value: ExtendedPropertyValue, /
-    ) -> None:
+    def __setitem__(self, key: str, value: ExtendedPropertyValue, /) -> None:
+        """Set self[key] to value."""
         operator.setitem(self._properties, key, value)
 
-    def __delitem__(  # noqa: D105 - Missing docstring in magic method (auto-generated noqa)
-        self, key: str, /
-    ) -> None:
+    def __delitem__(self, key: str, /) -> None:
+        """Delete self[key]."""
         operator.delitem(self._properties, key)
 
     def _merge(self, other: ExtendedPropertyDictionary) -> None:
         for key, value in other.items():
             self._properties.setdefault(key, value)
+
+    def __repr__(self) -> str:
+        """Return repr(self)."""
+        return f"{self.__class__.__module__}.{self.__class__.__name__}({self._properties!r})"