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from typing import Any, Literal, TypeAlias, TypeVar, overload import numpy as np import numpy.typing as npt from numpy import ( # noqa: F401 False_, ScalarType, True_, __array_namespace_info__, __version__, abs, absolute, acos, acosh, add, all, allclose, amax, amin, angle, any, append, apply_along_axis, apply_over_axes, arange, arccos, arccosh, arcsin, arcsinh, arctan, arctan2, arctanh, argmax, argmin, argpartition, argsort, argwhere, around, array, array2string, array_equal, array_equiv, array_repr, array_split, array_str, asanyarray, asarray, asarray_chkfinite, ascontiguousarray, asfortranarray, asin, asinh, asmatrix, astype, atan, atan2, atanh, atleast_1d, atleast_2d, atleast_3d, average, bartlett, base_repr, binary_repr, bincount, bitwise_and, bitwise_count, bitwise_invert, bitwise_left_shift, bitwise_not, bitwise_or, bitwise_right_shift, bitwise_xor, blackman, block, bmat, bool, bool_, broadcast, broadcast_arrays, broadcast_shapes, broadcast_to, busday_count, busday_offset, busdaycalendar, byte, bytes_, c_, can_cast, cbrt, cdouble, ceil, char, character, choose, clip, clongdouble, column_stack, common_type, complex64, complex128, complex256, complexfloating, compress, concat, concatenate, conj, conjugate, convolve, copy, copysign, copyto, core, corrcoef, correlate, cos, cosh, count_nonzero, cov, cross, csingle, ctypeslib, cumprod, cumsum, cumulative_prod, cumulative_sum, datetime64, datetime_as_string, datetime_data, deg2rad, degrees, delete, diag, diag_indices, diag_indices_from, diagflat, diagonal, diff, digitize, divide, divmod, dot, double, dsplit, dstack, dtype, dtypes, e, ediff1d, einsum, einsum_path, emath, empty_like, equal, errstate, euler_gamma, exceptions, exp, exp2, expand_dims, expm1, extract, f2py, fabs, fft, fill_diagonal, finfo, fix, flatiter, flatnonzero, flexible, flip, fliplr, flipud, float16, float32, float64, float128, float_power, floating, floor, floor_divide, fmax, fmin, fmod, format_float_positional, format_float_scientific, frexp, from_dlpack, frombuffer, fromfile, fromfunction, fromiter, frompyfunc, fromregex, fromstring, full, full_like, gcd, generic, genfromtxt, geomspace, get_include, get_printoptions, getbufsize, geterr, geterrcall, gradient, greater, greater_equal, half, hamming, hanning, heaviside, histogram, histogram2d, histogram_bin_edges, histogramdd, hsplit, hstack, hypot, i0, iinfo, imag, index_exp, indices, inexact, inf, info, inner, insert, int8, int16, int32, int64, int_, intc, integer, interp, intersect1d, intp, invert, is_busday, isclose, iscomplex, iscomplexobj, isdtype, isfinite, isfortran, isin, isinf, isnan, isnat, isneginf, isposinf, isreal, isrealobj, isscalar, issubdtype, iterable, ix_, kaiser, kron, lcm, ldexp, left_shift, less, less_equal, lexsort, lib, linalg, linspace, little_endian, load, loadtxt, log, log1p, log2, log10, logaddexp, logaddexp2, logical_and, logical_not, logical_or, logical_xor, logspace, long, longdouble, longlong, ma, mask_indices, matmul, matrix, matrix_transpose, matvec, max, maximum, may_share_memory, mean, median, memmap, meshgrid, mgrid, min, min_scalar_type, minimum, mintypecode, mod, modf, moveaxis, multiply, nan, nan_to_num, nanargmax, nanargmin, nancumprod, nancumsum, nanmax, nanmean, nanmedian, nanmin, nanpercentile, nanprod, nanquantile, nanstd, nansum, nanvar, ndarray, ndenumerate, ndim, ndindex, nditer, negative, nested_iters, newaxis, nextafter, nonzero, not_equal, number, object_, ogrid, ones_like, outer, packbits, pad, partition, percentile, permute_dims, pi, piecewise, place, poly, poly1d, polyadd, polyder, polydiv, polyfit, polyint, polymul, polynomial, polysub, polyval, positive, pow, power, printoptions, prod, promote_types, ptp, put, put_along_axis, putmask, quantile, r_, rad2deg, radians, random, ravel, ravel_multi_index, real, real_if_close, rec, recarray, reciprocal, record, remainder, repeat, require, reshape, resize, result_type, right_shift, rint, roll, rollaxis, roots, rot90, round, row_stack, s_, save, savetxt, savez, savez_compressed, sctypeDict, searchsorted, select, set_printoptions, setbufsize, setdiff1d, seterr, seterrcall, setxor1d, shape, shares_memory, short, show_config, show_runtime, sign, signbit, signedinteger, sin, sinc, single, sinh, size, sort, sort_complex, spacing, split, sqrt, square, squeeze, stack, std, str_, strings, subtract, sum, swapaxes, take, take_along_axis, tan, tanh, tensordot, test, testing, tile, timedelta64, trace, transpose, trapezoid, tri, tril, tril_indices, tril_indices_from, trim_zeros, triu, triu_indices, triu_indices_from, true_divide, trunc, typecodes, typename, typing, ubyte, ufunc, uint, uint8, uint16, uint32, uint64, uintc, uintp, ulong, ulonglong, union1d, unique, unique_all, unique_counts, unique_inverse, unique_values, unpackbits, unravel_index, unsignedinteger, unstack, unwrap, ushort, vander, var, vdot, vecdot, vecmat, vectorize, void, vsplit, vstack, where, zeros_like, ) from numpy._typing import _ArrayLike, _DTypeLike __all__ = ["rand", "randn", "repmat"] __all__ += np.__all__ ### _ScalarT = TypeVar("_ScalarT", bound=np.generic) _Matrix: TypeAlias = np.matrix[tuple[int, int], np.dtype[_ScalarT]] _Order: TypeAlias = Literal["C", "F"] ### # @overload def empty(shape: int | tuple[int, int], dtype: None = None, order: _Order = "C") -> _Matrix[np.float64]: ... @overload def empty(shape: int | tuple[int, int], dtype: _DTypeLike[_ScalarT], order: _Order = "C") -> _Matrix[_ScalarT]: ... @overload def empty(shape: int | tuple[int, int], dtype: npt.DTypeLike, order: _Order = "C") -> _Matrix[Any]: ... # @overload def ones(shape: int | tuple[int, int], dtype: None = None, order: _Order = "C") -> _Matrix[np.float64]: ... @overload def ones(shape: int | tuple[int, int], dtype: _DTypeLike[_ScalarT], order: _Order = "C") -> _Matrix[_ScalarT]: ... @overload def ones(shape: int | tuple[int, int], dtype: npt.DTypeLike, order: _Order = "C") -> _Matrix[Any]: ... # @overload def zeros(shape: int | tuple[int, int], dtype: None = None, order: _Order = "C") -> _Matrix[np.float64]: ... @overload def zeros(shape: int | tuple[int, int], dtype: _DTypeLike[_ScalarT], order: _Order = "C") -> _Matrix[_ScalarT]: ... @overload def zeros(shape: int | tuple[int, int], dtype: npt.DTypeLike, order: _Order = "C") -> _Matrix[Any]: ... # @overload def identity(n: int, dtype: None = None) -> _Matrix[np.float64]: ... @overload def identity(n: int, dtype: _DTypeLike[_ScalarT]) -> _Matrix[_ScalarT]: ... @overload def identity(n: int, dtype: npt.DTypeLike | None = None) -> _Matrix[Any]: ... # @overload def eye( n: int, M: int | None = None, k: int = 0, dtype: type[np.float64] | None = ..., order: _Order = "C", ) -> _Matrix[np.float64]: ... @overload def eye(n: int, M: int | None, k: int, dtype: _DTypeLike[_ScalarT], order: _Order = "C") -> _Matrix[_ScalarT]: ... @overload def eye(n: int, M: int | None = None, k: int = 0, *, dtype: _DTypeLike[_ScalarT], order: _Order = "C") -> _Matrix[_ScalarT]: ... @overload def eye(n: int, M: int | None = None, k: int = 0, dtype: npt.DTypeLike | None = ..., order: _Order = "C") -> _Matrix[Any]: ... # @overload def rand(arg: int | tuple[()] | tuple[int] | tuple[int, int], /) -> _Matrix[np.float64]: ... @overload def rand(arg: int, /, *args: int) -> _Matrix[np.float64]: ... # @overload def randn(arg: int | tuple[()] | tuple[int] | tuple[int, int], /) -> _Matrix[np.float64]: ... @overload def randn(arg: int, /, *args: int) -> _Matrix[np.float64]: ... # @overload def repmat(a: _Matrix[_ScalarT], m: int, n: int) -> _Matrix[_ScalarT]: ... @overload def repmat(a: _ArrayLike[_ScalarT], m: int, n: int) -> npt.NDArray[_ScalarT]: ... @overload def repmat(a: npt.ArrayLike, m: int, n: int) -> npt.NDArray[Any]: ...