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author | jranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb> | 2010-05-18 12:58:38 +0000 |
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committer | jranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb> | 2010-05-18 12:58:38 +0000 |
commit | 16f5b1d3c0136413e92b2be0f20d365e92e9cd1c (patch) | |
tree | edab7b27ba4253b9dd45520e504c54851f65f26f /R/mkinplot.R | |
parent | 30cbb4092f6d2d3beff5800603374a0d009ad770 (diff) |
Much more complete version that was just submitted to CRAN.
git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@9 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
Diffstat (limited to 'R/mkinplot.R')
-rw-r--r-- | R/mkinplot.R | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/R/mkinplot.R b/R/mkinplot.R new file mode 100644 index 00000000..d2880c0e --- /dev/null +++ b/R/mkinplot.R @@ -0,0 +1,49 @@ +mkinplot <- function(fit, xlab = "Time", ylab = "Observed", xlim = range(fit$data$time), ylim = range(fit$data$observed, na.rm = TRUE), ...) +{ + fixed <- fit$fixed$value + names(fixed) <- rownames(fit$fixed) + parms.all <- c(fit$par, fixed) + ininames <- c( + rownames(subset(fit$start, type == "state")), + rownames(subset(fit$fixed, type == "state"))) + odeini <- parms.all[ininames] + names(odeini) <- names(fit$diffs) + + outtimes <- seq(xlim[1], xlim[2], length.out=100) + + odenames <- c( + rownames(subset(fit$start, type == "deparm")), + rownames(subset(fit$fixed, type == "deparm"))) + odeparms <- parms.all[odenames] + + # Solve the ode + out <- ode( + y = odeini, + times = outtimes, + func = fit$mkindiff, + parms = odeparms) + + # Output transformation for models with unobserved compartments like SFORB + out_transformed <- data.frame(time = out[,"time"]) + for (var in names(fit$map)) { + if(length(fit$map[[var]]) == 1) { + out_transformed[var] <- out[, var] + } else { + out_transformed[var] <- rowSums(out[, fit$map[[var]]]) + } + } + + # Plot the data and model output + plot(0, type="n", + xlim = xlim, ylim = ylim, + xlab = xlab, ylab = ylab, ...) + col_obs <- pch_obs <- 1:length(fit$map) + names(col_obs) <- names(pch_obs) <- names(fit$map) + for (obs_var in names(fit$map)) { + points(subset(fit$data, variable == obs_var, c(time, observed)), + pch = pch_obs[obs_var], col = col_obs[obs_var]) + } + matlines(out_transformed$time, out_transformed[-1]) + legend("topright", inset=c(0.05, 0.05), legend=names(fit$map), + col=col_obs, pch=pch_obs, lty=1:length(pch_obs)) +} |