• R Programming week 3-Debugging


    Something’s Wrong!

    Indications that something’s not right

    message: A generic notification/diagnostic message produced by the message function;execution of the function continues

    warning: An indication that something is wrong but not necessarily fatal; execution of thefunction continues; generated by the warning function

    error: An indication that a fatal problem has occurred; execution stops; produced by the stop function

    condition: A generic concept for indicating that something unexpected can occur; programmers can create their own conditions

    How do you know that something is wrong with your function?

    What was your input?

    How did you call the function?

    What were you expecting? Output, messages, other results?

    What did you get?

    How does what you get differ from what you were expecting?

    Were your expectations correct in the first place?

    Can you reproduce the problem (exactly)?

    Debugging Tools in R

    The primary tools for debugging functions in R are:

    traceback: prints out the function call stack after an error occurs; does nothing if there’s no error

    debug: flags a function for “debug” mode which allows you to step through execution of a function one line at a time

    browser: suspends the execution of a function wherever it is called and puts the function in debug mode

    trace: allows you to insert debugging code into a function a specific places

    recover: allows you to modify the error behavior so that you can browse the function call stack

    These are interactive tools specifically designed to allow you to pick through a function. There’s also the more blunt technique of inserting print/cat statements in the function.

    traceback

    > lm(y ~ x)

    Error in eval(expr, envir, enclos) : object ’y’ not found

    > traceback()

    7: eval(expr, envir, enclos)

    6: eval(predvars, data, env)

    5: model.frame.default(formula = y ~ x, drop.unused.levels = TRUE)

    4: model.frame(formula = y ~ x, drop.unused.levels = TRUE)

    3: eval(expr, envir, enclos)

    2: eval(mf, parent.frame())

    1: lm(y ~ x)

    debug

    > debug(lm)

    > lm(y ~ x)

    debugging in: lm(y ~ x)

    debug: {

    ret.x <- x

    ret.y <- y

    cl <- match.call()

    ...

    if (!qr)

    z$qr <- NULL

    z

    }

    Browse[

    2]>

    Browse[2]> n

    debug: ret.x <- x

    Browse[2]> n

    debug: ret.y <- y

    Browse[2]> n

    debug: cl <- match.call()

    Browse[2]> n

    debug: mf <- match.call(expand.dots = FALSE)

    Browse[2]> n

    debug: m <- match(c("formula", "data", "subset", "weights", "na.action",

    "offset"), names(mf), 0L)

    recover

    > options(error = recover)

    > read.csv("nosuchfile")

    Error in file(file, "rt") : cannot open the connection

    In addition: Warning message:

    In file(file, "rt") :

    cannot open file ’nosuchfile’: No such file or directory

    Enter a frame number, or 0 to exit

    1: read.csv("nosuchfile")

    2: read.table(file = file, header = header, sep = sep, quote = quote, dec =

    3: file(file, "rt")

    Selection:

    Summary

    There are three main indications of a problem/condition: message, warning, error- only an error is fatal

    When analyzing a function with a problem, make sure you can reproduce the problem, clearly state your expectations and how the output differs from your expectation

    Interactive debugging tools traceback, debug, browser, trace, and recover can be used to find problematic code in functions

    Debugging tools are not a substitute for thinking!

    欢迎关注:

  • 相关阅读:
    记录日常Linux常用软件
    CentOS7.2重置root密码的处理方法
    Nginx配置文件详细说明
    ES项目实战
    foreachRDD
    Hive的数据倾斜
    SparkStreaming实战(数据库(NoSQL))
    Spark(4)
    SparkStreming中 `transform()`算子的 的使用
    RDD源码分析
  • 原文地址:https://www.cnblogs.com/jpld/p/4451738.html
Copyright © 2020-2023  润新知