给定精度的浮子范围 [英] Range of floats with a given precision

问题描述

我想创建一个数组，其中包含[0.000，1.000]范围内的所有浮点数，所有浮点数均具有3个小数位/4的精度.

I want to create an array of all floating point numbers in the range [0.000, 1.000], all with 3 decimal places / precision of 4.

例如

>>> np.arange(start=0.000, stop=1.001, decimals=3)
[0.000, 0.001, ..., 0.100, 0.101, ..., 0.900, ..., 0.999, 0.000]

能做到这一点吗?

推荐答案

您可以使用 np.linspace :

You could use np.linspace:

>>> import numpy as np
>>> np.linspace(0, 1, 1001)
array([ 0.   ,  0.001,  0.002, ...,  0.998,  0.999,  1.   ])

或 np.arange 使用整数然后除法:

or np.arange using integers and then dividing:

>>> np.arange(0, 1001) / 1000
array([ 0.   ,  0.001,  0.002, ...,  0.998,  0.999,  1.   ])

但是，这实际上不是3位小数，因为所有这些值都是浮点数，并且浮点数不精确.这意味着其中一些数字看起来好像有3个小数，但没有！

However, that's not really 3 decimals because all of these values are floats and floats are inexact. That means some of those numbers may look like they have 3 decimals but they haven't!

>>> '{:.40f}'.format((np.arange(0, 1001) / 1000)[1])  # show 40 decimals of second element
'0.0010000000000000000208166817117216851329'

NumPy不支持固定的小数，因此为了获得完美的结果"，您需要使用Python.例如带有 fractions.Fraction :

NumPy doesn't support fixed decimals so in order to get a "perfect result" you need to use Python. For example a list with fractions.Fraction:

>>> from fractions import Fraction
>>> [Fraction(i, 1000) for i in range(0, 1001)]
[Fraction(0, 1), Fraction(1, 1000), ..., Fraction(999, 1000), Fraction(1, 1)]

或 decimal.Decimal :

>>> from decimal import Decimal
>>> [Decimal(i) / 1000 for i in range(1, 1001)]
[Decimal('0.001'), Decimal('0.002'), ..., Decimal('0.999'), Decimal('1')]

这篇关于给定精度的浮子范围的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！