add .imag and .real properties to NamedArray
#8365
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andersy005
changed the title
.imag and .real properties and .astype method to NamedArray.imag and .real properties to NamedArray
| @@ -516,6 +512,28 @@ def data(self, data: duckarray[Any, _DType_co]) -> None: | |||
| self._check_shape(data) | |||
| self._data = data | |||
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| @property | |||
| def imag(self) -> Self: | |||
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When you use imag you're changing the dtype of the class, so it's not Self you're returning but rather a new NamedArray. Which won't match with self.
This should similar to the function, like:
def imag(
self: NamedArray[_ShapeType, np.dtype[_SupportsImag[_ScalarType]]], / # type: ignore[type-var]
) -> NamedArray[_ShapeType, np.dtype[_ScalarType]]:Here's how numpy does it:
https://github.com/numpy/numpy/blob/14bb214bca49b167abc375fa873466a811e62102/numpy/__init__.pyi#L1495-L1500
Variable will also need this style of typing.
| -------- | ||
| numpy.ndarray.imag | ||
| """ | ||
| return self._replace(data=self.data.imag) # type: ignore |
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Only use ._replace if the shape or dtype wont change.
return self._new(data=self.data.imag)| return self._replace(data=self.data.imag) # type: ignore | ||
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| @property | ||
| def real(self) -> Self: |
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Same idea here. Follow the same idea but use _SupportsReal instead.
| -------- | ||
| numpy.ndarray.real | ||
| """ | ||
| return self._replace(data=self.data.real) # type: ignore |
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Same idea, dtype or shape has changed in this method so use ._new.
| def test_real_and_imag() -> None: | ||
| named_array: NamedArray[Any, Any] | ||
| named_array = NamedArray(["x"], np.arange(3) - 1j * np.arange(3)) | ||
| expected_real = np.arange(3) | ||
| assert np.array_equal(named_array.real.data, expected_real) | ||
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| expected_imag = -np.arange(3) | ||
| assert np.array_equal(named_array.imag.data, expected_imag) |
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You're not testing dtypes here. They don't match.
expected_imagis an int dtype.named_array.imag.datais a float dtype.
The test should look something like this:
def test_real_and_imag() -> None:
expected_real: np.ndarray[Any, np.dtype[np.float64]]
expected_real = np.arange(3, dtype=np.float64)
expected_imag: np.ndarray[Any, np.dtype[np.float64]]
expected_imag = -np.arange(3, dtype=np.float64)
arr: np.ndarray[Any, np.dtype[np.complex128]]
arr = expected_real + 1j * expected_imag
named_array: NamedArray[Any, np.dtype[np.complex128]]
named_array = NamedArray(["x"], arr)
actual_real: np.ndarray[Any, np.dtype[np.float64]] = named_array.real.data
assert np.array_equal(actual_real, expected_real)
assert actual_real.dtype == expected_real.dtype
actual_imag: np.ndarray[Any, np.dtype[np.float64]] = named_array.imag.data
assert np.array_equal(actual_imag, expected_imag)
assert actual_imag.dtype == expected_imag.dtypeThere was a problem hiding this comment.
thank you for the review... i'm going to address these in a follow up PR.
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