Conversions from floating point types to integral types.
从浮点类型到整型类型的转换。
Many languages have equivalents for the IDL simple types, such as integer and floating point types.
许多语言都拥有与IDL简单类型等同的内容，如整数类型和浮点类型。
Floating point types of course take care of this detail for you, although you get less choice about when renormalisation takes place.
当然，浮点类型照顾这个细节你，尽管你不选择重正化发生时。
Blue includes a number of built-in types, including Numbers (which covers integer and floating point types), strings, arrays, functions, and others.
Blue包含许多内置类型，包括数字(包含整型和浮点型)、字符串、数组、函数等等。
On a 64-bit system, integral types are converted to 64-bit integral types, and single precision floating point types are promoted to double precision.
在 64位系统上，整型被转换成 64 位的整型值，单精度的浮点类型被转换成双精度的浮点类型。
This technique can especially help in finding problems with floating-point values, conversion ratios, and lengths associated with data types.
这项技术特别有助于发现使用浮点值、转换率，以及与数据类型相关长度的问题。
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。
The difference lies in the fact that floating-point data types used in computers can't hold every real number.
区别在于一个事实：计算机中使用的浮点数据类型无法包含每个实数。
For example, the C programming language has integer and floating-point types.
例如，c编程语言具有整型和浮点类型。
Like C, Go offers a handful of primitive types. The usual Boolean, integer and floating-point types are available.
像C语言一样，Go提供了一系列的基本类型，常见的布尔，整数和浮点数类型都具备。
They support Numbers of different types (integers and floating point), characters, strings, and so on.
它们支持许多不同的类型(整型和浮点型)、字符、字符串等等。
In general supported types are Integer, Boolean, ASCII string, double-precision signed floating point number, date-time, set, list, properties.
通常支持的类型有整数、Boolean、ASCII字符串、双精度带符号浮点数、日期时间、集合、列表、属性。
Strings, numbers (floating point only), booleans, and the special nil type are basic types.
number（只有浮点数）、boolean和特殊的nil类型都是基本类型。
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。
Floating binary point types are much faster to work with than decimals.
二进制浮点点类型是更快的工作比小数。
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。
The imperceptible differences might be due to rounding or same-result calculations of a floating-point data types.
这些无法觉察的差异可能是由于浮点数据类型的舍入计算或生成相同结果的计算造成的。
These days, floating-point math is typically done in hardware that's designed to handle the full width of the floating-point types.
这些天，浮点数学一般是硬件的设计处理的完整宽度浮点类型。
For floating-point and fixed-point types, m is the total number of digits that can be stored.
对于浮点数及定点类型，M是数字存储的总位数。
You can mix numeric integral types and floating-point types in an expression.
您可以在一个运算式里混合数值整数型别和浮点型别。
In this case, the integral types are converted to floating-point types.
在这种情况里，整数型别会转换成浮点型别。
The following table shows the precision and approximate ranges for the floating-point types.
下表显示浮点型别的精确度和大概范围。
According to different situations the FFT algorithm is applied to. three types of fix-point, floating-point and block-floating-point complex FFT algorithms are presented.
根据不同的应用场合，分别实现了定点、浮点和块浮点三种数据格式的复数FFT算法。
According to different situations the FFT algorithm is applied to. three types of fix-point, floating-point and block-floating-point complex FFT algorithms are presented.
根据不同的应用场合，分别实现了定点、浮点和块浮点三种数据格式的复数FFT算法。
应用推荐