xorbits.numpy.rint#

xorbits.numpy.rint(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])[源代码]#

Round elements of the array to the nearest integer.

参数

  • x (array_like) – Input array.

  • out (ndarray, None, or tuple of ndarray and None, optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

  • where (array_like, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.

  • **kwargs – For other keyword-only arguments, see the ufunc docs.

返回

out – Output array is same shape and type as x. This is a scalar if x is a scalar.

返回类型

ndarray or scalar

参见

fix, ceil, floor, trunc

提示

For values exactly halfway between rounded decimal values, NumPy rounds to the nearest even value. Thus 1.5 and 2.5 round to 2.0, -0.5 and 0.5 round to 0.0, etc.

实际案例

>>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0])  
>>> np.rint(a)  
array([-2., -2., -0.,  0.,  2.,  2.,  2.])

This docstring was copied from numpy.