The next two—float and double—represent floating-point numbers, again with different dynamic ranges.
随后的两种——float和double，代表了浮点型数，同样具有不同的动态范围。
The non-ordered nature of NaN adds further opportunities for error when comparing floating point numbers.
NaN的无序性质使得在比较浮点数时更容易发生错误。
HTTP content negotiation uses short floating point numbers to indicate the relative importance, or weight, of various negotiable parameters.
HTTP内容协商使用短浮点数来表示各种可协商参数的相对重要性（或权重）。
The only time floats are used is in manipulation of large multidimensional arrays of floating-point numbers with limited precision in which the storage space would be significant.
使用float的惟一时机就是操纵精度有限的大型多维浮点数字数组，此时存储空间较为重要。
The main thing to understand is that Psyco is useful for handling blocks that loop many times, and it knows how to optimize operations involving integers and floating point numbers.
主要是要明白Psyco对于处理多次循环的块是很有用的，而且它知道如何优化涉及整数和浮点数的操作。
You can pad both integer and floating-point numbers with leading zeros by using a custom numeric format string.
通过使用自定义数字格式字符串，可以用前导零填充整数和浮点数。
This article proposes a quick sort method based on the machine code of floating point numbers, which can sort the floating point numbers distributed at random.
本文提出一种可对任意分布的浮点数进行排序的快速排序方法，它基于浮点数的机内编码，具有速度快、实现简单、实用的特点。
Floating-point Numbers are not real Numbers.
浮点数并不是实数。
Don't use floating point Numbers for exact values.
不要用浮点值表示精确值。
SQL does not support the modulus operator on floating-point Numbers.
SQL不支持对浮点数字使用取模运算符。
Be aware, however, that the comparison of floating-point Numbers is very strict.
但要注意，对浮点数字的比较是非常严格的。
Trace point Numbers appear consecutively in a chronologically formatted output file.
跟踪点号按照年月顺序出现在格式化的输出文件中。
There are differences in the definition of floating-point Numbers and long variable types.
浮点型数字和长变量类型的定义是有差异的。
Supported variables include integers, floating point Numbers, strings, arrays, and objects.
支持的变量包括整型、浮点型的数字、字符串、数组和对象。
Floating point Numbers are not exact, and manipulating them will result in rounding errors.
浮点数不是精确值，所以使用它们会导致舍入误差。
IEEE 754 represents floating point Numbers as base 2 decimal Numbers in scientific notation.
IEEE 754用科学记数法以底数为2的小数来表示浮点数。
The fundamental types are characters, and integers and floating point Numbers of several sizes.
其基本类型为几种大小的字符、整数和浮点数类型。
If you need to represent fixed point Numbers, such as dollars and cents, use BigDecimal instead.
如果需要表示定点数(譬如，几美元和几美分)，则使用BigDecimal。
For floating-point Numbers, you place a decimal as the separator between the whole part of the number and the fraction.
对于浮点数，您将在整数部分和小数部分之间放置小数点。
Floating point Numbers are best reserved for values such as measurements, whose values are fundamentally inexact to begin with.
浮点数最好用来表示象测量值这类数值，这类值从一开始就不怎么精确。
In Part 2, I'll explore the functions more designed for operating on floating point Numbers as opposed to abstract real Numbers.
在第2部分，我将探讨专为操作浮点数(与抽象实数相反)而设计的函数。
A secure pseudorandom bit sequence generator is designed and the bit sequences are then transformed into floating point Numbers.
设计了一种密码安全的伪随机比特序列发生器，再将比特序列转化为浮点数序列。
Color changes are another common alteration. Values for color are floating point Numbers from 0 to 1, 0 being black, 1 being white.
修改颜色是另一个常见的操作。颜色值是一个从0到1的浮点数，0代表黑色，1代表白色。
You can also use a fixed-precision decimal type, or cast floating-point Numbers to a fixed-precision decimal type before you work with them.
您也可以使用固定精度的十进制类型，或者在使用浮点数之前将它们强制转换为固定精度的十进制类型。
Similarly, on platforms without native support for fixed-point or double-precision floating-point Numbers, implementations must emulate these types.
类似地，在没有本地定点或双精度浮点数支持的平台上，实现必须模拟这些类型。
To analyze the rounding error of calculator floating-point Numbers arithmetic operation is the foundation of numerical calculation method's error analysis.
对计算机浮点数算术运算的舍入误差进行分析，是对数值计算方法作误差分析的基础。
In most programming languages, Numbers that include a decimal fraction are called floating-point Numbers, which are used to approximate real Numbers in mathematics.
在大部分的编程语言中，包含了小数点的数字称之为浮点数，可以用它来表示数学中的实数。
Here in Part 2, I focus on the functions that make sense only when you realize that they're designed for operating on floating-point Numbers instead of abstract real Numbers.
在第2部分中，我主要关注这样一些函数，它们的目的是操作浮点数，而不是抽象实数。
Information contained in this output includes process, thread, and node number, as well as trace point Numbers, function names, trace record types and, in some cases, probe Numbers.
该输出中的信息包括进程、线程、节点号，以及跟踪点号、函数名、跟踪记录类型，在某些情况下还包括探测号。
So the arguments (the data) — whether they are floating-point Numbers, integers, character strings, or complex objects — are encoded into a format that can be transferred to the RPC receiver.
所以自变量(数据)-无论是浮点数、整数、字符串还是复杂对象-都要编码成可以传输到RPC接收方的格式。
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