【R语言】seq()函数的调用方法

看到有很多读者浏览了这篇文章，心里很是开心，为了能够更好地帮助大家，决定再修改一下，帮助大家更好地理解。

--------修改于：2018年4月28日

为了方便大家在开发环境中直接实验测试代码，下面，我将说明和函数的用法全部用英文给出（避免乱码），并加以注释，希望能够对大家有所帮助！

首先，我们来看一个seq()函数应用的实例！

x <- seq(0, 10, by = 0.01)
y <- sin(x)
plot(y)

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下面，我们来看函数的主要使用方法！

注意：在本文调用函数时，均采用写出入口参数名的方法，比如：

seq(from = 1, to = 2)

这样函数的调用更加清晰，在调用较多函数时，不会发生混乱和参数匹配错误。

• 方式一：seq(from, to)

from：生成向量的起点，to：生成向量的终点，默认步长为1（可修改）

a <- seq(from = 1, to = 2)
# [1, 2]

• 方式二：seq(from, to, by = )

by：向量元素之间的步长

a <- seq(from = 1, to = 3, by = 0.5)
# [1, 1.5, 2, 2.5, 3]

• 方式三：seq(from, to, length.out = )

length.out：向量中元素数目

a <- seq(from = 1, to = 3, length.out = 5)
# [1, 1.5, 2, 2.5, 3]

• 方式四：seq(along.with = )

along.with：表示生成的向量为现有一向量元素的索引

x <- c(1.2, 5.2, 6.3, 4.6)
a <- seq(along.with = x)
# [1, 2, 3, 4]

• 方式五：seq(from)

该方式和方式四功能相似

x <- c(1.2, 5.2, 6.3, 4.6)
a <- seq(from = x)
# [1, 2, 3, 4]

 

• 方式6：seq(length.out = )

生成从1开始，步长为1，长度为length.out的向量

a <- seq(length.out = 5)
# [1, 2, 3, 4, 5]

上述几种方式为较为常见的方式，详细的函数说明如下：

 

Sequence Generation

• Description

Generate regular sequences. seq is a standard generic with a default method. seq.int is a primitive which can be much faster but has a few restrictions. seq_along and seq_len are very fast primitives for two common cases.

---------------------------------------------

• Usage

seq(...)
## Default S3 method:
seq(from = 1, to = 1, by = ((to - from)/(length.out - 1)),
    length.out = NULL, along.with = NULL, ...)
seq.int(from, to, by, length.out, along.with, ...)
seq_along(along.with)

seq_len(length.out)

---------------------------------------------

• Arguments

1：...

arguments passed to or from methods.

2：from, to

the starting and (maximal) end values of the sequence. Of length 1 unless just from is supplied as an unnamed argument.

3：by

number: increment of the sequence.

4：length.out

desired length of the sequence. A non-negative number, which for seq and seq.int will be rounded up if fractional.

5：along.with

take the length from the length of this argument.

 

参考：https://blog.csdn.net/jiluben/article/details/40024607