# File src/library/stats/R/termplot.R # Part of the R package, https://www.R-project.org # # Copyright (C) 1995-2014 The R Core Team # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # A copy of the GNU General Public License is available at # https://www.R-project.org/Licenses/ termplot <- function(model, data = NULL, envir = environment(formula(model)), partial.resid = FALSE, rug = FALSE, terms = NULL, se = FALSE, xlabs = NULL, ylabs = NULL, main = NULL, col.term = 2, lwd.term = 1.5, col.se = "orange", lty.se = 2, lwd.se = 1, col.res = "gray", cex = 1, pch = par("pch"), col.smth = "darkred", lty.smth = 2, span.smth = 2/3, ask = dev.interactive() && nb.fig < n.tms, use.factor.levels = TRUE, smooth = NULL, ylim = "common", plot = TRUE, transform.x = FALSE, ...) { which.terms <- terms terms <- ## need if(), since predict.coxph() has non-NULL default terms : if (is.null(terms)) predict(model, type = "terms", se.fit = se) else predict(model, type = "terms", se.fit = se, terms = terms) n.tms <- ncol(tms <- as.matrix(if(se) terms$fit else terms)) transform.x <- rep_len(transform.x, n.tms) mf <- model.frame(model) if (is.null(data)) data <- eval(model$call$data, envir) if (is.null(data)) data <- mf ## maybe rather use naresid() as for factor variables. use.rows <- if (NROW(tms) < NROW(data)) match(rownames(tms), rownames(data)) ## else NULL nmt <- colnames(tms) if (any(grepl(":", nmt, fixed = TRUE))) warning("'model' appears to involve interactions: see the help page", domain = NA, immediate. = TRUE) cn <- parse(text = nmt, keep.source = FALSE) ## Defaults: if (!is.null(smooth)) smooth <- match.fun(smooth) if (is.null(ylabs)) ylabs <- paste("Partial for",nmt) if (is.null(main)) main <- "" else if(is.logical(main)) main <- if(main) deparse(model$call, 500) else "" else if(!is.character(main)) stop("'main' must be TRUE, FALSE, NULL or character (vector).") main <- rep_len(main, n.tms) # recycling pf <- envir carrier <- function(term, transform) { # used for non-factor ones if (length(term) > 1L){ if (transform) tms[,i] else carrier(term[[2L]], transform) } else eval(term, data, enclos = pf) } carrier.name <- function(term){ if (length(term) > 1L) carrier.name(term[[2L]]) else as.character(term) } in.mf <- nmt %in% names(mf) is.fac <- sapply(nmt, function(i) i %in% names(mf) && is.factor(mf[, i])) if (!plot) { outlist <- vector("list", sum(in.mf)) for (i in 1L:n.tms) { if (!in.mf[i]) next ## add element to output list ## ww = index to rows in the data, selecting one of each unique ## predictor value if (is.fac[i]) { ## PR#15344 xx <- mf[, nmt[i]] if (!is.null(use.rows)) xx <- xx[use.rows] ## "nomatch' in case there is a level not in the data ww <- match(levels(xx), xx, nomatch = 0L) } else { xx <- carrier(cn[[i]], transform.x[i]) if (!is.null(use.rows)) xx <- xx[use.rows] ww <- match(sort(unique(xx)), xx) } outlist[[i]] <- if (se) data.frame(x = xx[ww], y = tms[ww, i], se = terms$se.fit[ww, i], row.names = NULL) else data.frame(x = xx[ww], y = tms[ww, i], row.names = NULL) } attr(outlist, "constant") <- attr(terms, "constant") ## might be on the fit component. if (se && is.null(attr(outlist, "constant"))) attr(outlist, "constant") <- attr(terms$fit, "constant") names(outlist) <- sapply(cn, carrier.name)[in.mf] return(outlist) } ## Defaults: if (!is.null(smooth)) smooth <- match.fun(smooth) if (is.null(ylabs)) ylabs <- paste("Partial for",nmt) if (is.null(main)) main <- "" else if(is.logical(main)) main <- if(main) deparse(model$call, 500) else "" else if(!is.character(main)) stop("'main' must be TRUE, FALSE, NULL or character (vector).") main <- rep_len(main, n.tms) # recycling if (is.null(xlabs)){ xlabs <- unlist(lapply(cn,carrier.name)) if(any(transform.x)) xlabs <- ifelse(transform.x, lapply(cn, deparse), xlabs) } if (partial.resid || !is.null(smooth)){ pres <- residuals(model, "partial") if (!is.null(which.terms)) pres <- pres[, which.terms, drop = FALSE] } se.lines <- function(x, iy, i, ff = 2) { tt <- ff * terms$se.fit[iy, i] lines(x, tms[iy, i] + tt, lty = lty.se, lwd = lwd.se, col = col.se) lines(x, tms[iy, i] - tt, lty = lty.se, lwd = lwd.se, col = col.se) } nb.fig <- prod(par("mfcol")) if (ask) { oask <- devAskNewPage(TRUE) on.exit(devAskNewPage(oask)) } ylims <- ylim if(identical(ylims, "common")) { ylims <- if(!se) range(tms, na.rm = TRUE) else range(tms + 1.05*2*terms$se.fit, tms - 1.05*2*terms$se.fit, na.rm = TRUE) if (partial.resid) ylims <- range(ylims, pres, na.rm = TRUE) if (rug) ylims[1L] <- ylims[1L] - 0.07*diff(ylims) } ##---------- Do the individual plots : ---------- for (i in 1L:n.tms) { if(identical(ylim, "free")) { ylims <- range(tms[, i], na.rm = TRUE) if (se) ylims <- range(ylims, tms[, i] + 1.05*2*terms$se.fit[, i], tms[, i] - 1.05*2*terms$se.fit[, i], na.rm = TRUE) if (partial.resid) ylims <- range(ylims, pres[, i], na.rm = TRUE) if (rug) ylims[1L] <- ylims[1L] - 0.07*diff(ylims) } if (!in.mf[i]) next if (is.fac[i]) { ff <- mf[, nmt[i]] if (!is.null(model$na.action)) ff <- naresid(model$na.action, ff) ll <- levels(ff) xlims <- range(seq_along(ll)) + c(-.5, .5) xx <- as.numeric(ff) ## needed if rug or partial if(rug) { xlims[1L] <- xlims[1L] - 0.07*diff(xlims) xlims[2L] <- xlims[2L] + 0.03*diff(xlims) } plot(1, 0, type = "n", xlab = xlabs[i], ylab = ylabs[i], xlim = xlims, ylim = ylims, main = main[i], xaxt="n", ...) if (use.factor.levels) axis(1, at = seq_along(ll), labels = ll, ...) else axis(1) for(j in seq_along(ll)) { ww <- which(ff == ll[j])[c(1, 1)] jf <- j + c(-0.4, 0.4) lines(jf, tms[ww, i], col = col.term, lwd = lwd.term, ...) if(se) se.lines(jf, iy = ww, i = i) } } else { ## continuous carrier xx <- carrier(cn[[i]], transform.x[i]) if (!is.null(use.rows)) xx <- xx[use.rows] xlims <- range(xx, na.rm = TRUE) if(rug) xlims[1L] <- xlims[1L] - 0.07*diff(xlims) oo <- order(xx) plot(xx[oo], tms[oo, i], type = "l", xlab = xlabs[i], ylab = ylabs[i], xlim = xlims, ylim = ylims, main = main[i], col = col.term, lwd = lwd.term, ...) if(se) se.lines(xx[oo], iy = oo, i = i) } if (partial.resid){ if (!is.fac[i] && !is.null(smooth)){ smooth(xx,pres[, i], lty = lty.smth, cex = cex, pch = pch, col = col.res, col.smooth = col.smth, span = span.smth) } else points(xx, pres[, i], cex = cex, pch = pch, col = col.res) } if (rug) { n <- length(xx) ## Fixme: Isn't this a kludge for segments() ? lines(rep.int(jitter(xx), rep.int(3, n)), rep.int(ylims[1L] + c(0, 0.05, NA)*diff(ylims), n)) if (partial.resid) lines(rep.int(xlims[1L] + c(0, 0.05, NA)*diff(xlims), n), rep.int(pres[, i], rep.int(3, n))) } } invisible(n.tms) }