Question

我需要像这样解析输入：“+ 704”
进入：切换器=“+”和c = 749
我明白了：

scanf("%c %d", &switcher, &c);

这不起作用。
Scanf返回1而不是2，c = 4196080，printf("%c", switcher)打印换行符我错过了什么？

Answer 1

所以基本上，有一个新行等待缓冲区。要摆脱它，只需在格式化字符串的开头添加一个空格即可。

library(shiny)
library(base64enc)
library(httr)
library(rjson)
library(bit64)
library(plyr)
library(stringr)
library(urltools)
library(twitteR)
library(ggplot2)

#initialize environment variables
consumerKey <- 'MUwukLPqlXp7pROuci6NGHiIo'
consumerSecret <- 'yCucMwTsjMsXFrrKDnHTyawxgKFzzRMGy3UeEyzGGvlQXzIHAV'
tokenKey <- '4095349632-uOfSHrUmPzbuTYDRkASHfUuJBy0YxCesY6QtWbe'
tokenSecret <- 'FS55U9PqOIBTCo3mbV3bHli7aEXMJEGmGjPlpfrifGeTL'
setup_twitter_oauth(consumerKey, consumerSecret, tokenKey, tokenSecret)
pos <- scan('res/positive-words.txt', what='character', comment.char=';')
neg <- scan('res/negative-words.txt', what='character', comment.char=';')

ui <- fluidPage(
  sliderInput(inputId = "nTweets", 
              label = "Choose a number of tweets to gather", 
              value = 10, min = 1, max = 100),
  textInput(inputId = "term", label = "Enter a hashtag or term to search:", value = "Canada"),
  actionButton(inputId = "go", 
               label = "Go/Refresh"),
  plotOutput("LHist")
)

server <- function(input, output) {

  rv <- reactiveValues()

  title <- eventReactive(input$go, {
    paste("sentiment on", rv$searchTerm, sep=" ")
  })
  tweets <- eventReactive(input$go, {
    searchTwitter(rv$searchTerm, n=rv$Tweets, lang="en")
  })
  Tweets.text <- eventReactive(input$go, {
    laply(tweets, function(t)t$getText())
  })
  analysis <- eventReactive(input$go, {
    score.sentiment(Tweets.text, pos, neg)
  })

  observeEvent(input$go, {
    rv$searchTerm <- input$term
    rv$Tweets <- input$nTweets
  })

  output$LHist <- renderPlot({
    #histogram
    ggplot(data=analysis()) +
      geom_bar(mapping=aes(x=score), binwidth=1) +
      theme_bw() + scale_color_brewer() +
      ggtitle(paste("Lexical analysis'", title()))
  })


}

shinyApp(ui = ui, server = server)

score.sentiment = function(sentences, pos.words, neg.words, .progress='none')
{

  require(plyr)
  require(stringr)
  scores = laply(sentences, function(sentence, pos.words, neg.words) {

    sentence = gsub('[[:punct:]]', '', sentence)
    sentence = gsub('[[:cntrl:]]', '', sentence)
    sentence = gsub('\\d+', '', sentence)
    # remove retweet entities
    sentence = gsub("(RT|via)((?:\\b\\W*@\\w+)+)", "", sentence)
    # remove at people
    sentence = gsub("@\\w+", "", sentence)
    sentence = gsub("http\\w+", "", sentence)
    word.list = str_split(sentence, '\\s+')
    words = unlist(word.list)
    pos.matches = match(words, pos.words)
    neg.matches = match(words, neg.words)
    pos.matches = !is.na(pos.matches)
    neg.matches = !is.na(neg.matches)
    score = sum(pos.matches) - sum(neg.matches)
    return(score)
  }, pos.words, neg.words, .progress=.progress )

  scores.df = data.frame(score=scores, text=sentences)

  return(scores.df)
}

C输入char和int由空格分隔

1 个答案: