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| Name | Type | Size | Last Modified | Actions |
|---|---|---|---|---|
| arithmetic.pyi | File | 20805 bytes | April 17 2025 13:10:58. | |
| array_constructors.pyi | File | 11831 bytes | April 17 2025 13:10:58. | |
| arraypad.pyi | File | 694 bytes | April 17 2025 13:10:58. | |
| arrayprint.pyi | File | 686 bytes | April 17 2025 13:10:58. | |
| arraysetops.pyi | File | 4671 bytes | April 17 2025 13:10:58. | |
| arrayterator.pyi | File | 1128 bytes | April 17 2025 13:10:58. | |
| bitwise_ops.pyi | File | 3607 bytes | April 17 2025 13:10:58. | |
| char.pyi | File | 8047 bytes | April 17 2025 13:10:58. | |
| chararray.pyi | File | 6312 bytes | April 17 2025 13:10:58. | |
| comparisons.pyi | File | 8018 bytes | April 17 2025 13:10:58. | |
| constants.pyi | File | 1940 bytes | April 17 2025 13:10:58. | |
| ctypeslib.pyi | File | 5107 bytes | April 17 2025 13:10:58. | |
| datasource.pyi | File | 557 bytes | April 17 2025 13:10:58. | |
| dtype.pyi | File | 2787 bytes | April 17 2025 13:10:58. | |
| einsumfunc.pyi | File | 2173 bytes | April 17 2025 13:10:58. | |
| emath.pyi | File | 2538 bytes | April 17 2025 13:10:58. | |
| false_positives.pyi | File | 349 bytes | April 17 2025 13:10:58. | |
| fft.pyi | File | 1852 bytes | April 17 2025 13:10:58. | |
| flatiter.pyi | File | 819 bytes | April 17 2025 13:10:58. | |
| fromnumeric.pyi | File | 13631 bytes | April 17 2025 13:10:58. | |
| getlimits.pyi | File | 1547 bytes | April 17 2025 13:10:58. | |
| histograms.pyi | File | 1391 bytes | April 17 2025 13:10:58. | |
| index_tricks.pyi | File | 3481 bytes | April 17 2025 13:10:58. | |
| lib_function_base.pyi | File | 9140 bytes | April 17 2025 13:10:58. | |
| lib_polynomial.pyi | File | 6353 bytes | April 17 2025 13:10:58. | |
| lib_utils.pyi | File | 917 bytes | April 17 2025 13:10:58. | |
| lib_version.pyi | File | 605 bytes | April 17 2025 13:10:58. | |
| linalg.pyi | File | 5217 bytes | April 17 2025 13:10:58. | |
| matrix.pyi | File | 3033 bytes | April 17 2025 13:10:58. | |
| memmap.pyi | File | 755 bytes | April 17 2025 13:10:58. | |
| mod.pyi | File | 5989 bytes | April 17 2025 13:10:58. | |
| modules.pyi | File | 1994 bytes | April 17 2025 13:10:58. | |
| multiarray.pyi | File | 5670 bytes | April 17 2025 13:10:58. | |
| nbit_base_example.pyi | File | 500 bytes | April 17 2025 13:10:58. | |
| ndarray_conversion.pyi | File | 1913 bytes | April 17 2025 13:10:58. | |
| ndarray_misc.pyi | File | 7797 bytes | April 17 2025 13:10:58. | |
| ndarray_shape_manipulation.pyi | File | 904 bytes | April 17 2025 13:10:58. | |
| nditer.pyi | File | 2067 bytes | April 17 2025 13:10:58. | |
| nested_sequence.pyi | File | 648 bytes | April 17 2025 13:10:58. | |
| npyio.pyi | File | 4434 bytes | April 17 2025 13:10:58. | |
| numeric.pyi | File | 6802 bytes | April 17 2025 13:10:58. | |
| numerictypes.pyi | File | 1711 bytes | April 17 2025 13:10:58. | |
| random.pyi | File | 129510 bytes | April 17 2025 13:10:58. | |
| rec.pyi | File | 3380 bytes | April 17 2025 13:10:58. | |
| scalars.pyi | File | 5347 bytes | April 17 2025 13:10:58. | |
| shape_base.pyi | File | 2632 bytes | April 17 2025 13:10:58. | |
| stride_tricks.pyi | File | 1563 bytes | April 17 2025 13:10:58. | |
| testing.pyi | File | 8877 bytes | April 17 2025 13:10:58. | |
| twodim_base.pyi | File | 3327 bytes | April 17 2025 13:10:58. | |
| type_check.pyi | File | 3031 bytes | April 17 2025 13:10:58. | |
| ufunc_config.pyi | File | 1304 bytes | April 17 2025 13:10:58. | |
| ufunclike.pyi | File | 1319 bytes | April 17 2025 13:10:58. | |
| ufuncs.pyi | File | 2919 bytes | April 17 2025 13:10:58. | |
| version.pyi | File | 313 bytes | April 17 2025 13:10:58. | |
| warnings_and_errors.pyi | File | 420 bytes | April 17 2025 13:10:58. |
"""
Tests for :mod:`core.numeric`.
Does not include tests which fall under ``array_constructors``.
"""
import numpy as np
import numpy.typing as npt
class SubClass(npt.NDArray[np.int64]):
...
i8: np.int64
AR_b: npt.NDArray[np.bool_]
AR_u8: npt.NDArray[np.uint64]
AR_i8: npt.NDArray[np.int64]
AR_f8: npt.NDArray[np.float64]
AR_c16: npt.NDArray[np.complex128]
AR_m: npt.NDArray[np.timedelta64]
AR_O: npt.NDArray[np.object_]
B: list[int]
C: SubClass
reveal_type(np.count_nonzero(i8)) # E: int
reveal_type(np.count_nonzero(AR_i8)) # E: int
reveal_type(np.count_nonzero(B)) # E: int
reveal_type(np.count_nonzero(AR_i8, keepdims=True)) # E: Any
reveal_type(np.count_nonzero(AR_i8, axis=0)) # E: Any
reveal_type(np.isfortran(i8)) # E: bool
reveal_type(np.isfortran(AR_i8)) # E: bool
reveal_type(np.argwhere(i8)) # E: ndarray[Any, dtype[{intp}]]
reveal_type(np.argwhere(AR_i8)) # E: ndarray[Any, dtype[{intp}]]
reveal_type(np.flatnonzero(i8)) # E: ndarray[Any, dtype[{intp}]]
reveal_type(np.flatnonzero(AR_i8)) # E: ndarray[Any, dtype[{intp}]]
reveal_type(np.correlate(B, AR_i8, mode="valid")) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.correlate(AR_i8, AR_i8, mode="same")) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.correlate(AR_b, AR_b)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.correlate(AR_b, AR_u8)) # E: ndarray[Any, dtype[unsignedinteger[Any]]]
reveal_type(np.correlate(AR_i8, AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.correlate(AR_i8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
reveal_type(np.correlate(AR_i8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
reveal_type(np.correlate(AR_i8, AR_m)) # E: ndarray[Any, dtype[timedelta64]]
reveal_type(np.correlate(AR_O, AR_O)) # E: ndarray[Any, dtype[object_]]
reveal_type(np.convolve(B, AR_i8, mode="valid")) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.convolve(AR_i8, AR_i8, mode="same")) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.convolve(AR_b, AR_b)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.convolve(AR_b, AR_u8)) # E: ndarray[Any, dtype[unsignedinteger[Any]]]
reveal_type(np.convolve(AR_i8, AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.convolve(AR_i8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
reveal_type(np.convolve(AR_i8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
reveal_type(np.convolve(AR_i8, AR_m)) # E: ndarray[Any, dtype[timedelta64]]
reveal_type(np.convolve(AR_O, AR_O)) # E: ndarray[Any, dtype[object_]]
reveal_type(np.outer(i8, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.outer(B, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.outer(AR_i8, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.outer(AR_i8, AR_i8, out=C)) # E: SubClass
reveal_type(np.outer(AR_b, AR_b)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.outer(AR_b, AR_u8)) # E: ndarray[Any, dtype[unsignedinteger[Any]]]
reveal_type(np.outer(AR_i8, AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.convolve(AR_i8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
reveal_type(np.outer(AR_i8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
reveal_type(np.outer(AR_i8, AR_m)) # E: ndarray[Any, dtype[timedelta64]]
reveal_type(np.outer(AR_O, AR_O)) # E: ndarray[Any, dtype[object_]]
reveal_type(np.tensordot(B, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.tensordot(AR_i8, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.tensordot(AR_i8, AR_i8, axes=0)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.tensordot(AR_i8, AR_i8, axes=(0, 1))) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.tensordot(AR_b, AR_b)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.tensordot(AR_b, AR_u8)) # E: ndarray[Any, dtype[unsignedinteger[Any]]]
reveal_type(np.tensordot(AR_i8, AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.tensordot(AR_i8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
reveal_type(np.tensordot(AR_i8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
reveal_type(np.tensordot(AR_i8, AR_m)) # E: ndarray[Any, dtype[timedelta64]]
reveal_type(np.tensordot(AR_O, AR_O)) # E: ndarray[Any, dtype[object_]]
reveal_type(np.isscalar(i8)) # E: bool
reveal_type(np.isscalar(AR_i8)) # E: bool
reveal_type(np.isscalar(B)) # E: bool
reveal_type(np.roll(AR_i8, 1)) # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.roll(AR_i8, (1, 2))) # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.roll(B, 1)) # E: ndarray[Any, dtype[Any]]
reveal_type(np.rollaxis(AR_i8, 0, 1)) # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.moveaxis(AR_i8, 0, 1)) # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.moveaxis(AR_i8, (0, 1), (1, 2))) # E: ndarray[Any, dtype[{int64}]]
reveal_type(np.cross(B, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.cross(AR_i8, AR_i8)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.cross(AR_b, AR_u8)) # E: ndarray[Any, dtype[unsignedinteger[Any]]]
reveal_type(np.cross(AR_i8, AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
reveal_type(np.cross(AR_i8, AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
reveal_type(np.cross(AR_i8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
reveal_type(np.cross(AR_O, AR_O)) # E: ndarray[Any, dtype[object_]]
reveal_type(np.indices([0, 1, 2])) # E: ndarray[Any, dtype[{int_}]]
reveal_type(np.indices([0, 1, 2], sparse=True)) # E: tuple[ndarray[Any, dtype[{int_}]], ...]
reveal_type(np.indices([0, 1, 2], dtype=np.float64)) # E: ndarray[Any, dtype[{float64}]]
reveal_type(np.indices([0, 1, 2], sparse=True, dtype=np.float64)) # E: tuple[ndarray[Any, dtype[{float64}]], ...]
reveal_type(np.indices([0, 1, 2], dtype=float)) # E: ndarray[Any, dtype[Any]]
reveal_type(np.indices([0, 1, 2], sparse=True, dtype=float)) # E: tuple[ndarray[Any, dtype[Any]], ...]
reveal_type(np.binary_repr(1)) # E: str
reveal_type(np.base_repr(1)) # E: str
reveal_type(np.allclose(i8, AR_i8)) # E: bool
reveal_type(np.allclose(B, AR_i8)) # E: bool
reveal_type(np.allclose(AR_i8, AR_i8)) # E: bool
reveal_type(np.isclose(i8, i8)) # E: bool_
reveal_type(np.isclose(i8, AR_i8)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.isclose(B, AR_i8)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.isclose(AR_i8, AR_i8)) # E: ndarray[Any, dtype[bool_]]
reveal_type(np.array_equal(i8, AR_i8)) # E: bool
reveal_type(np.array_equal(B, AR_i8)) # E: bool
reveal_type(np.array_equal(AR_i8, AR_i8)) # E: bool
reveal_type(np.array_equiv(i8, AR_i8)) # E: bool
reveal_type(np.array_equiv(B, AR_i8)) # E: bool
reveal_type(np.array_equiv(AR_i8, AR_i8)) # E: bool
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