From df916b91c90f80e2c68f3e136a7b6e07b8c6bae1 Mon Sep 17 00:00:00 2001 From: jranke Date: Mon, 26 Nov 2012 23:03:19 +0000 Subject: - Added an S3 plot method for mkinfit models - Fixed a bug in the mkinfit summary method which crashed on missing covariance matrices git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@58 edb9625f-4e0d-4859-8d74-9fd3b1da38cb --- R/mkinfit.R | 2 +- R/mkinplot.R | 38 ++------------------------------------ R/plot.mkinfit.R | 45 +++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 48 insertions(+), 37 deletions(-) create mode 100644 R/plot.mkinfit.R (limited to 'R') diff --git a/R/mkinfit.R b/R/mkinfit.R index 0215596..3649b20 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -317,7 +317,7 @@ print.summary.mkinfit <- function(x, digits = max(3, getOption("digits") - 3), . print(x$SFORB, digits=digits,...) } - printcor <- !is.null(x$cov.unscaled) + printcor <- is.numeric(x$cov.unscaled) if (printcor){ Corr <- cov2cor(x$cov.unscaled) rownames(Corr) <- colnames(Corr) <- rownames(x$par) diff --git a/R/mkinplot.R b/R/mkinplot.R index 546c506..b9becfd 100644 --- a/R/mkinplot.R +++ b/R/mkinplot.R @@ -1,38 +1,4 @@ -mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), legend = TRUE, ...) +mkinplot <- function(fit, ...) { - solution_type = fit$solution_type - fixed <- fit$fixed$value - names(fixed) <- rownames(fit$fixed) - parms.all <- c(fit$parms.all, fixed) - ininames <- c( - rownames(subset(fit$start, type == "state")), - rownames(subset(fit$fixed, type == "state"))) - odeini <- parms.all[ininames] - names(odeini) <- names(fit$mkinmod$diffs) - - outtimes <- seq(xlim[1], xlim[2], length.out=100) - - odenames <- c( - rownames(subset(fit$start, type == "deparm")), - rownames(subset(fit$fixed, type == "deparm"))) - odeparms <- parms.all[odenames] - - out <- mkinpredict(fit$mkinmod, odeparms, odeini, outtimes, - solution_type = solution_type, atol = fit$atol, rtol = fit$rtol, ...) - - # Plot the data and model output - plot(0, type="n", - xlim = xlim, ylim = ylim, - xlab = xlab, ylab = ylab, ...) - col_obs <- pch_obs <- lty_obs <- 1:length(fit$mkinmod$map) - names(col_obs) <- names(pch_obs) <- names(lty_obs) <- names(fit$mkinmod$map) - for (obs_var in names(fit$mkinmod$map)) { - points(subset(fit$data, variable == obs_var, c(time, observed)), - pch = pch_obs[obs_var], col = col_obs[obs_var]) - } - matlines(out$time, out[-1]) - if (legend == TRUE) { - legend("topright", inset=c(0.05, 0.05), legend=names(fit$mkinmod$map), - col=col_obs, pch=pch_obs, lty=lty_obs) - } + plot(fit, ...) } diff --git a/R/plot.mkinfit.R b/R/plot.mkinfit.R new file mode 100644 index 0000000..1858aa8 --- /dev/null +++ b/R/plot.mkinfit.R @@ -0,0 +1,45 @@ +plot.mkinfit <- function(x, fit = x, + xlab = "Time", ylab = "Observed", + xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), + col_obs = 1:length(fit$mkinmod$map), + pch_obs = col_obs, lty_obs = rep(1, length(fit$mkinmod$map)), + add = FALSE, legend = !add, ...) +{ + solution_type = fit$solution_type + fixed <- fit$fixed$value + names(fixed) <- rownames(fit$fixed) + parms.all <- c(fit$parms.all, fixed) + ininames <- c( + rownames(subset(fit$start, type == "state")), + rownames(subset(fit$fixed, type == "state"))) + odeini <- parms.all[ininames] + names(odeini) <- names(fit$mkinmod$diffs) + + outtimes <- seq(xlim[1], xlim[2], length.out=100) + + odenames <- c( + rownames(subset(fit$start, type == "deparm")), + rownames(subset(fit$fixed, type == "deparm"))) + odeparms <- parms.all[odenames] + + out <- mkinpredict(fit$mkinmod, odeparms, odeini, outtimes, + solution_type = solution_type, atol = fit$atol, rtol = fit$rtol, ...) + + # Set up the plot if not to be added to an existing plot + if (add == FALSE) { + plot(0, type="n", + xlim = xlim, ylim = ylim, + xlab = xlab, ylab = ylab, ...) + } + # Plot the data and model output + names(col_obs) <- names(pch_obs) <- names(lty_obs) <- names(fit$mkinmod$map) + for (obs_var in names(fit$mkinmod$map)) { + points(subset(fit$data, variable == obs_var, c(time, observed)), + pch = pch_obs[obs_var], col = col_obs[obs_var]) + } + matlines(out$time, out[-1], col = col_obs, lty = lty_obs) + if (legend == TRUE) { + legend("topright", inset=c(0.05, 0.05), legend=names(fit$mkinmod$map), + col=col_obs, pch=pch_obs, lty=lty_obs) + } +} -- cgit v1.2.1