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[R-package] GPL2 dependency reduction and some fixes (dmlc#1401)
* [R] do not remove zero coefficients from gblinear dump * [R] switch from stringr to stringi * fix dmlc#1399 * [R] separate ggplot backend, add base r graphics, cleanup, more plots, tests * add missing include in amalgamation - fixes building R package in linux * add forgotten file * [R] fix DESCRIPTION * [R] fix travis check issue and some cleanup
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| Original file line number | Diff line number | Diff line change |
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| # ggplot backend for the xgboost plotting facilities | ||
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| #' @rdname xgb.plot.importance | ||
| #' @export | ||
| xgb.ggplot.importance <- function(importance_matrix = NULL, top_n = NULL, measure = NULL, | ||
| rel_to_first = FALSE, n_clusters = c(1:10), ...) { | ||
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| importance_matrix <- xgb.plot.importance(importance_matrix, top_n = top_n, measure = measure, | ||
| rel_to_first = rel_to_first, plot = FALSE, ...) | ||
| if (!requireNamespace("ggplot2", quietly = TRUE)) { | ||
| stop("ggplot2 package is required", call. = FALSE) | ||
| } | ||
| if (!requireNamespace("Ckmeans.1d.dp", quietly = TRUE)) { | ||
| stop("Ckmeans.1d.dp package is required", call. = FALSE) | ||
| } | ||
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| clusters <- suppressWarnings( | ||
| Ckmeans.1d.dp::Ckmeans.1d.dp(importance_matrix$Importance, n_clusters) | ||
| ) | ||
| importance_matrix[, Cluster := as.character(clusters$cluster)] | ||
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| plot <- | ||
| ggplot2::ggplot(importance_matrix, | ||
| ggplot2::aes(x = factor(Feature, levels = rev(Feature)), y = Importance, width = 0.05), | ||
| environment = environment()) + | ||
| ggplot2::geom_bar(ggplot2::aes(fill = Cluster), stat = "identity", position = "identity") + | ||
| ggplot2::coord_flip() + | ||
| ggplot2::xlab("Features") + | ||
| ggplot2::ggtitle("Feature importance") + | ||
| ggplot2::theme(plot.title = ggplot2::element_text(lineheight = .9, face = "bold"), | ||
| panel.grid.major.y = ggplot2::element_blank()) | ||
| return(plot) | ||
| } | ||
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| #' @rdname xgb.plot.deepness | ||
| #' @export | ||
| xgb.ggplot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.depth", "med.weight")) { | ||
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| if (!requireNamespace("ggplot2", quietly = TRUE)) | ||
| stop("ggplot2 package is required for plotting the graph deepness.", call. = FALSE) | ||
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| which <- match.arg(which) | ||
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| dt_depths <- xgb.plot.deepness(model = model, plot = FALSE) | ||
| dt_summaries <- dt_depths[, .(.N, Cover = mean(Cover)), Depth] | ||
| setkey(dt_summaries, 'Depth') | ||
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| if (which == "2x1") { | ||
| p1 <- | ||
| ggplot2::ggplot(dt_summaries) + | ||
| ggplot2::geom_bar(ggplot2::aes(x = Depth, y = N), stat = "Identity") + | ||
| ggplot2::xlab("") + | ||
| ggplot2::ylab("Number of leafs") + | ||
| ggplot2::ggtitle("Model complexity") + | ||
| ggplot2::theme( | ||
| plot.title = ggplot2::element_text(lineheight = 0.9, face = "bold"), | ||
| panel.grid.major.y = ggplot2::element_blank(), | ||
| axis.ticks = ggplot2::element_blank(), | ||
| axis.text.x = ggplot2::element_blank() | ||
| ) | ||
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| p2 <- | ||
| ggplot2::ggplot(dt_summaries) + | ||
| ggplot2::geom_bar(ggplot2::aes(x = Depth, y = Cover), stat = "Identity") + | ||
| ggplot2::xlab("Leaf depth") + | ||
| ggplot2::ylab("Weighted cover") | ||
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| multiplot(p1, p2, cols = 1) | ||
| return(invisible(list(p1, p2))) | ||
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| } else if (which == "max.depth") { | ||
| p <- | ||
| ggplot2::ggplot(dt_depths[, max(Depth), Tree]) + | ||
| ggplot2::geom_jitter(ggplot2::aes(x = Tree, y = V1), | ||
| height = 0.15, alpha=0.4, size=3, stroke=0) + | ||
| ggplot2::xlab("tree #") + | ||
| ggplot2::ylab("Max tree leaf depth") | ||
| return(p) | ||
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| } else if (which == "med.depth") { | ||
| p <- | ||
| ggplot2::ggplot(dt_depths[, median(as.numeric(Depth)), Tree]) + | ||
| ggplot2::geom_jitter(ggplot2::aes(x = Tree, y = V1), | ||
| height = 0.15, alpha=0.4, size=3, stroke=0) + | ||
| ggplot2::xlab("tree #") + | ||
| ggplot2::ylab("Median tree leaf depth") | ||
| return(p) | ||
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| } else if (which == "med.weight") { | ||
| p <- | ||
| ggplot2::ggplot(dt_depths[, median(abs(Weight)), Tree]) + | ||
| ggplot2::geom_point(ggplot2::aes(x = Tree, y = V1), | ||
| alpha=0.4, size=3, stroke=0) + | ||
| ggplot2::xlab("tree #") + | ||
| ggplot2::ylab("Median absolute leaf weight") | ||
| return(p) | ||
| } | ||
| } | ||
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| # Plot multiple ggplot graph aligned by rows and columns. | ||
| # ... the plots | ||
| # cols number of columns | ||
| # internal utility function | ||
| multiplot <- function(..., cols = 1) { | ||
| plots <- list(...) | ||
| num_plots = length(plots) | ||
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| layout <- matrix(seq(1, cols * ceiling(num_plots / cols)), | ||
| ncol = cols, nrow = ceiling(num_plots / cols)) | ||
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| if (num_plots == 1) { | ||
| print(plots[[1]]) | ||
| } else { | ||
| grid::grid.newpage() | ||
| grid::pushViewport(grid::viewport(layout = grid::grid.layout(nrow(layout), ncol(layout)))) | ||
| for (i in 1:num_plots) { | ||
| # Get the i,j matrix positions of the regions that contain this subplot | ||
| matchidx <- as.data.table(which(layout == i, arr.ind = TRUE)) | ||
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| print( | ||
| plots[[i]], vp = grid::viewport( | ||
| layout.pos.row = matchidx$row, | ||
| layout.pos.col = matchidx$col | ||
| ) | ||
| ) | ||
| } | ||
| } | ||
| } | ||
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| globalVariables(c( | ||
| "Cluster", "ggplot", "aes", "geom_bar", "coord_flip", "xlab", "ylab", "ggtitle", "theme", | ||
| "element_blank", "element_text" | ||
| )) |
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