diff --git a/README.md b/README.md index 9c23bd9..6532a50 100644 --- a/README.md +++ b/README.md @@ -20,13 +20,23 @@ git clone https://github.com/hiplot/hiplot-plugin-generator cd hiplot-plugin-generator ``` -Then you can prepare a R script descibe below. +Then you can prepare a R script named `source.R` with: -Let's get started with the Hello World plugin for Hiplot, which shows the core concept of **Hisub** and most common setting. +```sh +./hisub.R template +``` + +Next modify the `source.R` as your wish and convert it into your Hiplot plugin. + +```sh +./hisub.R source.R +``` ### Hello World +For preparing the core R script, let's get started with the Hello World plugin for Hiplot, which shows the core concept of **Hisub** and most common setting. + The contents of `helloworld.R`: ```R diff --git a/examples/ezcox.R b/examples/ezcox.R index 0419420..d33446a 100644 --- a/examples/ezcox.R +++ b/examples/ezcox.R @@ -78,16 +78,17 @@ call_ezcox <- function(data, vars_to_show, drop_controls, add_caption) { - if (ncol(data) < 3) { stop("Input data should have at least 3 columns!") } if (!all(c("time", "status") %in% colnames(data))) { cat("WARN: 'time' and 'status' colnames not exist in input data.", - sep = "\n") + sep = "\n" + ) cat("WARN: rename the first and the second column as 'time' and 'status'.", - sep = "\n") + sep = "\n" + ) colnames(data)[1:2] <- c("time", "status") } @@ -119,5 +120,3 @@ call_ezcox <- function(data, add_caption = add_caption ) } - - diff --git a/examples/pcatools.R b/examples/pcatools.R index b8e765b..7bf8354 100644 --- a/examples/pcatools.R +++ b/examples/pcatools.R @@ -81,71 +81,82 @@ call_pcatools <- function(datTable, sampleInfo, plotloadingsHighCol, eigencorplotMetavars, eigencorplotComponents) { - row.names(datTable) <- datTable[,1] - datTable <- datTable[,-1] - row.names(sampleInfo) <- sampleInfo[,1] - sampleInfo <- sampleInfo[,-1] + row.names(datTable) <- datTable[, 1] + datTable <- datTable[, -1] + row.names(sampleInfo) <- sampleInfo[, 1] + sampleInfo <- sampleInfo[, -1] data3 <- pca(datTable, metadata = sampleInfo, removeVar = (100 - top_var) / 100) p1 <- PCAtools::screeplot( - data3, components = getComponents(data3, 1:screeplotComponents), + data3, + components = getComponents(data3, 1:screeplotComponents), axisLabSize = 14, titleLabSize = 20, colBar = screeplotColBar, gridlines.major = FALSE, gridlines.minor = FALSE, - returnPlot = TRUE) + returnPlot = TRUE + ) p2 <- PCAtools::pairsplot( - data3, components = getComponents(data3, c(1:pairsplotComponents)), + data3, + components = getComponents(data3, c(1:pairsplotComponents)), triangle = TRUE, trianglelabSize = 12, hline = 0, vline = 0, pointSize = 0.8, gridlines.major = FALSE, gridlines.minor = FALSE, - colby = 'Grade', - title = '', plotaxes = FALSE, - margingaps = unit(c(0.01, 0.01, 0.01, 0.01), 'cm'), + colby = "Grade", + title = "", plotaxes = FALSE, + margingaps = unit(c(0.01, 0.01, 0.01, 0.01), "cm"), returnPlot = TRUE, - colkey = get_hiplot_color(conf$general$palette, -1, - conf$general$palette_custom)) #!! + colkey = get_hiplot_color( + conf$general$palette, -1, + conf$general$palette_custom + ) + ) # !! params_biplot <- list(data3, - showLoadings = TRUE, - lengthLoadingsArrowsFactor = 1.5, - sizeLoadingsNames = 4, - colLoadingsNames = 'red4', - # other parameters - lab = NULL, - hline = 0, vline = c(-25, 0, 25), - vlineType = c('dotdash', 'solid', 'dashed'), - gridlines.major = FALSE, gridlines.minor = FALSE, - pointSize = 5, - legendPosition = 'none', legendLabSize = 16, legendIconSize = 8.0, - drawConnectors = FALSE, - title = 'PCA bi-plot', - subtitle = 'PC1 versus PC2', - caption = '27 PCs ≈ 80%', - returnPlot = TRUE) - if (!is.null(biplotShapeBy) && biplotShapeBy != "") { + showLoadings = TRUE, + lengthLoadingsArrowsFactor = 1.5, + sizeLoadingsNames = 4, + colLoadingsNames = "red4", + # other parameters + lab = NULL, + hline = 0, vline = c(-25, 0, 25), + vlineType = c("dotdash", "solid", "dashed"), + gridlines.major = FALSE, gridlines.minor = FALSE, + pointSize = 5, + legendPosition = "none", legendLabSize = 16, legendIconSize = 8.0, + drawConnectors = FALSE, + title = "PCA bi-plot", + subtitle = "PC1 versus PC2", + caption = "27 PCs ≈ 80%", + returnPlot = TRUE + ) + if (!is.null(biplotShapeBy) && biplotShapeBy != "") { params_biplot$shape <- biplotShapeBy } if (!is.null(biplotColBy) && biplotColBy != "") { params_biplot$colby <- biplotColBy - params_biplot$colkey <- get_hiplot_color(conf$general$palette, -1, - conf$general$palette_custom) #!! + params_biplot$colkey <- get_hiplot_color( + conf$general$palette, -1, + conf$general$palette_custom + ) # !! } p3 <- do.call(PCAtools::biplot, params_biplot) p4 <- PCAtools::plotloadings( - data3, rangeRetain = 0.01, labSize = 4, + data3, + rangeRetain = 0.01, labSize = 4, components = getComponents(data3, c(1:plotloadingsComponents)), - title = 'Loadings plot', axisLabSize = 12, - subtitle = 'PC1, PC2, PC3, PC4, PC5', - caption = 'Top 1% variables', + title = "Loadings plot", axisLabSize = 12, + subtitle = "PC1, PC2, PC3, PC4, PC5", + caption = "Top 1% variables", gridlines.major = FALSE, gridlines.minor = FALSE, shape = 24, shapeSizeRange = c(4, 8), col = c(plotloadingsLowCol, plotloadingsMidCol, plotloadingsHighCol), - legendPosition = 'none', + legendPosition = "none", drawConnectors = FALSE, - returnPlot = TRUE) + returnPlot = TRUE + ) eigencorplotMetavars <- unlist(eigencorplotMetavars) if (length(eigencorplotMetavars) > 0) { @@ -159,43 +170,47 @@ call_pcatools <- function(datTable, sampleInfo, metavars = metavars, cexCorval = 1.0, fontCorval = 2, - posLab = 'all', + posLab = "all", rotLabX = 45, scale = TRUE, main = "PC clinical correlates", cexMain = 1.5, plotRsquared = FALSE, - corFUN = 'pearson', - corUSE = 'pairwise.complete.obs', - signifSymbols = c('****', '***', '**', '*', ''), + corFUN = "pearson", + corUSE = "pairwise.complete.obs", + signifSymbols = c("****", "***", "**", "*", ""), signifCutpoints = c(0, 0.0001, 0.001, 0.01, 0.05, 1), - returnPlot = TRUE) + returnPlot = TRUE + ) p6 <- plot_grid( p1, p2, p3, ncol = 3, - labels = c('A', 'B Pairs plot', 'C'), - label_fontfamily = 'serif', - label_fontface = 'bold', + labels = c("A", "B Pairs plot", "C"), + label_fontfamily = "serif", + label_fontface = "bold", label_size = 22, - align = 'h', - rel_widths = c(1.10, 0.80, 1.10)) + align = "h", + rel_widths = c(1.10, 0.80, 1.10) + ) p7 <- plot_grid( p4, as.grob(p5), ncol = 2, - labels = c('D', 'E'), - label_fontfamily = 'serif', - label_fontface = 'bold', + labels = c("D", "E"), + label_fontfamily = "serif", + label_fontface = "bold", label_size = 22, - align = 'h', - rel_widths = c(0.8, 1.2)) + align = "h", + rel_widths = c(0.8, 1.2) + ) p <- plot_grid( p6, p7, ncol = 1, - rel_heights = c(1.1, 0.9)) + rel_heights = c(1.1, 0.9) + ) out_xlsx <- paste(opt$outputFilePrefix, ".xlsx", sep = "") write.xlsx(as.data.frame(data3$rotated), out_xlsx, row.names = TRUE) diff --git a/hisub.R b/hisub.R index 99e4351..f14881b 100755 --- a/hisub.R +++ b/hisub.R @@ -10,7 +10,67 @@ # 6. 基于配置和输入文件生成 plot.R # # ./hisub.R examples/helloworld.R test_hello -VERSION = 0.1 +VERSION <- 0.2 + +TEMPLATE <- '# @hiplot start +# @appname helloworld +# @apptitle +# Hiplot Hello World +# Hiplot 示例插件 +# @target basic +# @tag test dotplot +# @author your name +# @url your project link +# @citation any reference you should link to +# @version 0.1.0 +# @release 2021-01-01 +# @description +# en: One sentence to describe this plugin. +# zh: 插件一段话简单介绍。 +# @main helloworld +# @library ggplot2 readr +# @param data export::data::hiplot-textarea::{"default": "data.txt", "required": true} +# en: Data Table +# zh: 数据表 +# @param x export::dataArg::data::{"index":1, "default": "mpg", "required": true} +# en: X Axis Variable +# zh: X 轴变量 +# @param y export::dataArg::data::{"index":2, "default": "vs", "blackItems": "carb", "required": false} +# en: X Axis Variable +# zh: Y 轴变量 +# @param size export::extra::slider::{"default":2, "min":0.5, "max":5, "step":0.5, "class":"col-12"} +# en: Dot Size +# zh: 点大小 +# @param add_line export::extra::switch::{"default": true, "class":"col-12"} +# en: Add Line +# zh: 添加线图 +# @return ggplot::["pdf", "png"]::{"cliMode": true, "title": "A test plot", "width":4, "height": 4, "theme": "theme_bw"} +# @data +# # You can write the code to generate the example data +# # "data.txt" described in parameter data, or you can +# # omit this tag and submit prepared data files. +# # File size <100Kb is recommended. +# # 此处可以编写生成示例数据（建议小于 100Kb）的代码 +# # 示例数据文件需要跟数据表格参数对应起来 +# # 或者忽略该标签，提交已经准备好的示例数据 +# library(readr) +# data("mtcars") +# write_tsv(mtcars, "data.txt") +# @hiplot end + +library(ggplot2) +helloworld <- function(data, x, y, size = 2, add_line = TRUE) { + if (y == "") stop("y must be provided!") + p <- ggplot(data, aes_string(x = x, y = y)) + p <- p + geom_point(size = size) + if (add_line) { + p <- p + geom_line() + } + # Here export a ggplot object + # Or the whole main function generate a basic R plot + return(p) +} +' message("HiSub version ", VERSION) message("Copyright (c) 2021 Hiplot (https://hiplot.com.cn/)") @@ -25,6 +85,15 @@ message("Checking input...") Args <- commandArgs(trailingOnly = TRUE) # Args <- c("test.R", "test-plugin2") +if (length(Args) == 1) { + if (Args[1] == "template") { + message("'template' command detected. Generating template 'source.R'.") + write_lines(TEMPLATE, file = "source.R") + message("Done") + quit("no") + } +} + # 如果传入的不是 2 个参数，中间的文件原样拷贝到插件目录以支持 # 已准备好的数据文件或其他所需脚本 fc <- file_content <- read_lines(Args[1])