JezK
Edit File: ndarray_misc.py
""" Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods. More extensive tests are performed for the methods' function-based counterpart in `../from_numeric.py`. """ from __future__ import annotations import operator from typing import cast, Any import numpy as np class SubClass(np.ndarray): ... i4 = np.int32(1) A: np.ndarray[Any, np.dtype[np.int32]] = np.array([[1]], dtype=np.int32) B0 = np.empty((), dtype=np.int32).view(SubClass) B1 = np.empty((1,), dtype=np.int32).view(SubClass) B2 = np.empty((1, 1), dtype=np.int32).view(SubClass) C: np.ndarray[Any, np.dtype[np.int32]] = np.array([0, 1, 2], dtype=np.int32) D = np.ones(3).view(SubClass) i4.all() A.all() A.all(axis=0) A.all(keepdims=True) A.all(out=B0) i4.any() A.any() A.any(axis=0) A.any(keepdims=True) A.any(out=B0) i4.argmax() A.argmax() A.argmax(axis=0) A.argmax(out=B0) i4.argmin() A.argmin() A.argmin(axis=0) A.argmin(out=B0) i4.argsort() A.argsort() i4.choose([()]) _choices = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32) C.choose(_choices) C.choose(_choices, out=D) i4.clip(1) A.clip(1) A.clip(None, 1) A.clip(1, out=B2) A.clip(None, 1, out=B2) i4.compress([1]) A.compress([1]) A.compress([1], out=B1) i4.conj() A.conj() B0.conj() i4.conjugate() A.conjugate() B0.conjugate() i4.cumprod() A.cumprod() A.cumprod(out=B1) i4.cumsum() A.cumsum() A.cumsum(out=B1) i4.max() A.max() A.max(axis=0) A.max(keepdims=True) A.max(out=B0) i4.mean() A.mean() A.mean(axis=0) A.mean(keepdims=True) A.mean(out=B0) i4.min() A.min() A.min(axis=0) A.min(keepdims=True) A.min(out=B0) i4.newbyteorder() A.newbyteorder() B0.newbyteorder('|') i4.prod() A.prod() A.prod(axis=0) A.prod(keepdims=True) A.prod(out=B0) i4.ptp() A.ptp() A.ptp(axis=0) A.ptp(keepdims=True) A.astype(int).ptp(out=B0) i4.round() A.round() A.round(out=B2) i4.repeat(1) A.repeat(1) B0.repeat(1) i4.std() A.std() A.std(axis=0) A.std(keepdims=True) A.std(out=B0.astype(np.float64)) i4.sum() A.sum() A.sum(axis=0) A.sum(keepdims=True) A.sum(out=B0) i4.take(0) A.take(0) A.take([0]) A.take(0, out=B0) A.take([0], out=B1) i4.var() A.var() A.var(axis=0) A.var(keepdims=True) A.var(out=B0) A.argpartition([0]) A.diagonal() A.dot(1) A.dot(1, out=B0) A.nonzero() C.searchsorted(1) A.trace() A.trace(out=B0) void = cast(np.void, np.array(1, dtype=[("f", np.float64)]).take(0)) void.setfield(10, np.float64) A.item(0) C.item(0) A.ravel() C.ravel() A.flatten() C.flatten() A.reshape(1) C.reshape(3) int(np.array(1.0, dtype=np.float64)) int(np.array("1", dtype=np.str_)) float(np.array(1.0, dtype=np.float64)) float(np.array("1", dtype=np.str_)) complex(np.array(1.0, dtype=np.float64)) operator.index(np.array(1, dtype=np.int64))