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https://github.com/evamaerey/ggjudge

Say what you think about a plot up front
https://github.com/evamaerey/ggjudge

Last synced: 11 days ago
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Say what you think about a plot up front

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README 

        
---

output: github_document

---



```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```



# ggjudge



Discussion about the successes and failures of data visualization can be lengthy and nuanced.  This is in contrast to the speed at which data visualizations themselves communicate. Data visualization is powerful because of 'preattentive' visual processing:  patterns are perceived almost instantaneously compared with raw data counterparts.  



To facilitate in a 'bottom-line-up-front' discussion of data visualization questions, analysts have used meta annotation of plots to communicate their perspectives and overall assessments of plots' success. Wilke 2018.



The goal of ggjudge is to easily allow for more meta annotation in the ggplot2 framework. Using FDV (Wilke) strategy for expressing high level judgments about plot's effectiveness, also extending to code, and to text console output. Uses cowplot's ggdraw functions.



The code is based on code that was used in Wilke's book.



Furthermore, given the visual creators are likely to return to code, the same 'final judge' approach may be applied to code snippets to quickly communicate overall assessments of coding strategies. 



Therefore, ggjudge also makes functions available for code judgement; the downside is that this code is imaged in a data visualization which is not lightweight and does not allow for copy/paste. Finally, ggjudge provides the ability to judge text outputs.



Current functions are:



- judge_plot

- judge_chunk_code

- judge_chunk_output_plot

- judge_chunk_output_text



Later 3 assume use of .Rmds; 



These is not very customizable presently, but follows pretty closely to Wilk's choices, which were very effective. 



# Judge plot



```{r judge_plot, include = T}

#' Title

#'

#' @param plot 

#' @param color 

#' @param alpha 

#' @param judgement 

#' @param family 

#' @param fontface 

#' @param clip 

#' @param plot.margin 

#' @param x 

#' @param y 

#' @param vjust 

#' @param hjust 

#' @param size 

#' @param angle 

#'

#' @return

#' @export

#'

#' @examples

judge_plot <- function(

  plot = NULL, 

  color = "red", 

  alpha =.9, 

  judgement = "you made\na plot", 

  family = "Helvetica",

  fontface = "bold", 

  clip = "off", 

  plot.margin = margin(50, 70, 10, 10),

  x=1, y=1, vjust=1.1, hjust=1.1, size=35, angle = 0

  ){

  

  if(is.null(plot)){plot <- ggplot2::last_plot()}

  

  cowplot::ggdraw(plot + theme(plot.margin = plot.margin),

                  clip = clip) +

    cowplot::draw_text(paste0(judgement, ""), x=x, y=y, vjust=vjust, hjust=hjust, size=size, angle = angle,

              color=color, alpha=alpha, family = family, fontface = fontface) +

    

    cowplot::draw_line(c(1, 1), c(0, 1), size= 2.8, color=color, alpha=alpha)

}

```



```{r survived_plot}

library(tidyverse)



p <- tidytitanic::passengers %>% 

  mutate(adult = age >= 18 ) %>% 

  filter(!is.na(age)) %>% 

ggplot() + 

  aes(x = adult) + 

  geom_bar()



judge_plot(plot = p, judgement = "awkward")

```



# Judge chunk plot output



```{r judge_chunk_output_plot}

#' Title

#'

#' @param chunk_name 

#' @param judgement 

#'

#' @return

#' @export

#'

#' @examples

judge_chunk_output_plot <- function(chunk_name, judgement = "some output"){

    

  knitr::knit_code$get(name = chunk_name) |>  

  paste(collapse = "\n") ->

text

  

eval(parse(text = text)) -> p



p %>% judge_plot(family = "Helvetica", color = "red", alpha = .9, judgement = judgement, fontface = "bold")



}

```



```{r survived_plot2}

# chunk name: survived_plot2

p <- tidytitanic::passengers %>% 

  mutate(adult = age >= 18 ) %>% 

  filter(!is.na(age)) %>% 

ggplot() + 

  aes(x = adult) + 

  geom_bar()

```



```{r}

judge_chunk_output_plot(chunk_name = "survived_plot2")

```



# Judge code chunk code



```{r judge_chunk_code}

#' Title

#'

#' @param chunk_name 

#' @param judgement 

#' @param ... 

#'

#' @return

#' @export

#'

#' @examples

judge_chunk_code <- function(chunk_name, judgement = "you wrote code", ...){

  

  knitr::knit_code$get(name = chunk_name) |>  

  paste(collapse = "\n") ->

code



# text <- "tidytitanic::passengers %>% \n  mutate(adult = age >=18 ) %>% \n  filter(!is.na(age)) %>% \nggplot() + \n  aes(x = adult) + \n  geom_bar()"



ggplot2::ggplot(data = data.frame(x = c(0, 1), y = c(0,1))) +

  ggplot2::aes(x = x, y = y) +

  ggplot2::geom_blank() +

  ggplot2::annotate("text", label = code, x = 0, y = 1, hjust = 0, vjust = 1, size = 5, family = "Courier") + 

  ggplot2::theme_void() ->

syntax_plot



syntax_plot %>% judge_plot(judgement = judgement, ...)

  

}

```



```{r titanic_plot, eval = F}

tidytitanic::passengers %>% 

  ggplot() + 

  aes(x = ifelse(survived, 

                 "survived",

                 "not survived")) + 

  geom_bar() + 

  labs(x = NULL)

```



```{r}

judge_chunk_code("titanic_plot", judgement = "repetative")

```



# Judge chunk text output



```{r judge_chunk_output_text, eval = T}

#' Title

#'

#' @param chunk_name 

#' @param judgement 

#'

#' @return

#' @export

#'

#' @examples

judge_chunk_output_text <- function(chunk_name, judgement = "some output"){

    

  knitr::knit_code$get(name = chunk_name) |>  

  paste(collapse = "\n") ->

text

  

capture.output(eval(parse(text = text))) -> output



output %>% 

   paste(collapse = "\n") ->

output_clean



library(ggplot2)

ggplot(data = data.frame(x = c(0, 1), y = c(0,1))) +

  aes(x = x, y = y) +

  geom_blank() +

  annotate("text", label = output_clean, 

           x = 0, y = 1, hjust = 0, vjust = 1, 

           size = 5, family = "Courier") + 

  theme_void() ->

output_plot



output_plot %>% judge_plot(family = "Helvetica", color = "red", alpha = .9, judgement = judgement, fontface = "bold")



}

```



```{r titanic_table}

library(magrittr)

tidytitanic::passengers |> 

  janitor::tabyl(sex, survived)

```



```{r}

judge_chunk_output_text(chunk_name = "titanic_table")

```



# send functions to package .R dir



```{r}

chunk_send_to_dir_r <- function(chunk_name){

  

  for(i in 1:length(chunk_name)){



knitr::knit_code$get(name = chunk_name[i]) |>

    paste(collapse = "\n") |>

    writeLines(con = paste0("R/", chunk_name[i], ".R"))

    

  }

  

}



chunk_send_to_dir_r(chunk_name = c("judge_plot", "judge_chunk_code", "judge_chunk_output_plot", "judge_chunk_output_text"))

```



# send tests to tests 



```{r}

chunk_send_to_dir_tests_testthat <- function(chunk_name){

  

  for(i in 1:length(chunk_name)){



knitr::knit_code$get(name = chunk_name[i]) |>

    paste(collapse = "\n") |>

    writeLines(con = paste0("tests/testthat/", chunk_name[i], ".R"))

    

  }

  

}



```



```{r test_judge_chunk_code, eval = F}

testthat::test_that("multiplication works", {

  expect_equal(2 * 2, 4)

})

```



```{r}

chunk_send_to_dir_tests_testthat("test_judge_chunk_code")

```



# maybe later ideas



```{r, eval = F}

library(patchwork)



judge_chunk_plot <- function



judge_chunk <- function(chunk_name, 

                        judgement_code = "code", 

                        judgement_output = "output", 

                        ...){

  

  

  judge_chunk_code(chunk_name = chunk_name, 

                   judgement = judgement_code) /

    judge_chunk_output(chunk_name = chunk_name, 

                       judgement = judgement_output)

  

  

}



```



```{r, fig.width=7, fig.height=10, eval = F}

judge_chunk(chunk_name = "table_chunk", 

            judgement_code = "code: using indicator variable directly",

            judgement_output = "output: information is lost")

```