python中向下取整(round向下取整)

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from numpy\core_multiarray_umath.py

np.floor()

def floor(x, *args, **kwargs): # real signature unknown; NOTE: unreliably restored from __doc__ 
    """ floor(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) Return the floor of the input, element-wise. 以元素为单位返回输入的下限。 The floor of the scalar `x` is the largest integer `i`, such that `i <= x`. It is often denoted as :math:`\lfloor x \rfloor`. 标量“ x”的下限是最大的整数“ i”，因此“ i <= x”。 它通常表示为：\ lfloor x \ rfloor`。 Parameters ---------- x : array_like Input data. 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. 结果存储的位置。 如果提供，它必须具有输入广播到的形状。 如果未提供或没有，则返回一个新分配的数组。 元组（只能作为关键字参数）的长度必须等于输出的数量。 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. 此条件通过输入广播。 在条件为True的位置，将`out`数组设置为ufunc结果。 在其他地方，`out`数组将保留其原始值。 请注意，如果通过默认的“ out = None”创建了未初始化的“ out”数组， 则条件为False的数组中的位置将保持未初始化状态。 **kwargs For other keyword-only arguments, see the :ref:`ufunc docs <ufuncs.kwargs>`. Returns ------- y : ndarray or scalar The floor of each element in `x`. This is a scalar if `x` is a scalar. x中每个元素的下限。 如果x是标量，则这是标量。 See Also -------- ceil, trunc, rint Notes ----- Some spreadsheet programs calculate the "floor-towards-zero", in other words ``floor(-2.5) == -2``. NumPy instead uses the definition of `floor` where `floor(-2.5) == -3`. 某些电子表格程序会计算“底数朝零”，而其他单词``floor（-2.5）== -2''。 NumPy改为使用`floor`其中`floor（-2.5）== -3` Examples -------- >>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) >>> np.floor(a) array([-2., -2., -1., 0., 1., 1., 2.]) """
    pass

np.ceil()同理

示例

# -*- coding: utf-8 -*-
""" @File : test.py @Time : 2020/6/25 11:27 @Author : Dontla @Email : sxana@qq.com @Software: PyCharm """
import numpy as np

print(np.ceil(1.7)) # 2.0