基于R中的表值更新图形

我正在R中运行一个代码，它有几个迭代。每个结果都存储在一个名为accatable的表中。如您所见，在下面的示例中，只有行S2*的结果

我要创建的是一个使用ggplot2显示演变的图形。例如，运行第一次迭代并获取第S2行*第1列的值。然后在第二次迭代中，您将获得第S2行*第2列的值，以此类推

目标是在每次迭代后绘制一个图形，该图形将在每次更新时显示演变

到目前为止，我已经成功地创建了该图，但只有当所有的表都完成时。这是我试过的测试。我首先创建df并将其从宽格式转换为长格式。然后我使用ggplot将输出装箱

testdf <- replicate(7, sample(0:10,5,rep=TRUE))
colnames(testdf) <- as.character(seq(1,7))
rownames(testdf) <- c("S1", "S2", "S1_S2", "S2*", "S1_S2*")
test <- melt(testdf, id.vars=testdf[[1]])
colnames(test) <- c("Input", "Images", "Acca")
test

test$IMAGES <- as.numeric(as.vector(test$Images))

ggplot (data = test, aes(x=Images, y=Acca, group=Input, colour=Input)) + 
  geom_line(aes(linetype=Input)) + 
  geom_point() + 
  scale_colour_manual(name="Scenario", 
                      values = c("black","black","blue","blue","red","red", 
                                 "darkgreen","darkgreen")) + 
  scale_linetype_manual(name="Scenario",
                        values=c("solid","dashed","solid","dashed","solid", "dashed", 
                                 "solid","dashed","solid","dashed", "solid","dashed")) + 
  theme_minimal() + 
  labs(x="Images", y="Acca",title="test") + 
  theme(plot.title = element_text(hjust = 0.5)) + 
  scale_x_continuous("Images", c(1,2,3,4,5,6,7), c(1,2,3,4,5,6,7))

你知道如何在每次添加新值时调整ggplot代码来绘制表格吗？

这里有一个tidyverse解决方案

为了说明这一点，我创建了一个与testdf大小相同的空白数据框，以进行迭代更新：

testdf <- as.data.frame(testdf)
accatable <- data.frame(`1` = rep(NA, 5), `2` = rep(NA, 5),
                        `3` = rep(NA, 5), `4` = rep(NA, 5),
                        `5` = rep(NA, 5), `6` = rep(NA, 5),
                        `7` = rep(NA, 5),
                        row.names = rownames(testdf))

> accatable
       X1 X2 X3 X4 X5 X6 X7
S1     NA NA NA NA NA NA NA
S2     NA NA NA NA NA NA NA
S1_S2  NA NA NA NA NA NA NA
S2*    NA NA NA NA NA NA NA
S1_S2* NA NA NA NA NA NA NA

结果如下所示：

---

我在示例代码中省略了scale_XX规范，因为我认为它们对解决方案不是必需的。您可以根据需要调整外观。

感谢您的解决方案。我以您的代码为灵感管理了一个变通解决方案

testdf <- as.data.frame(testdf)
accatable <- data.frame(`1` = rep(NA, 5), `2` = rep(NA, 5),
                        `3` = rep(NA, 5), `4` = rep(NA, 5),
                        `5` = rep(NA, 5), `6` = rep(NA, 5),
                        `7` = rep(NA, 5),
                        row.names = rownames(testdf))

> accatable
       X1 X2 X3 X4 X5 X6 X7
S1     NA NA NA NA NA NA NA
S2     NA NA NA NA NA NA NA
S1_S2  NA NA NA NA NA NA NA
S2*    NA NA NA NA NA NA NA
S1_S2* NA NA NA NA NA NA NA

library(dplyr)

p.list <- vector("list", ncol(accatable))

for(i in seq_along(accatable)){

  accatable[, i] <- testdf[, i] # replace with your actual updating code

  p <- ggplot(accatable[, seq(1, i), drop = FALSE] %>%      # keep only first 1-i columns
           tibble::rownames_to_column(var = "Scenario") %>% # add row name as a column
           tidyr::gather(iteration, value, -Scenario),      # convert to long format
         aes(x = iteration, y = value, group = Scenario,
             color = Scenario, linetype = Scenario)) +
    geom_line() +
    geom_point() +
    labs(x = "Images", y = "ACCA", title = paste("Iteration:", i)) +
    theme_minimal()

  print(p)                       # if you just want to SEE the result from each iteration
  p.list[[i]] <- ggplotGrob(p)   # if you want to SAVE the result from each iteration
}

gridExtra::grid.arrange(grobs = p.list, ncol = 1)