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POHow to plot in a single plot different outputs of a function that internally uses par-mfrow?
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copied!<p>I'm using a function that among several things plots the results in two panels using <code>par(mfrow = c(1, 2))</code>.</p> <p>I would like to run the function with three different datasets and plot the outputs together so that each one is in a row, as if I were using <code>par(mfrow = c(3, 2))</code>.</p> <p>If there a way of doing this without modifying the function itself?</p> <p>Probably basic issue, but help very much appreciated. </p> <p>The function is a little bit long, but the relevant part plots a PCoA:</p> <pre><code># perform classical multidimensional sclaing (PCoA) of the dist matrix acop <- cmdscale(dat.d, k = nrow(as.matrix(dat.d)) - 1, eig = TRUE) # keep n-1 eigenvalues axes.tot <- acop$eig # eig are the n eigenvalues computed by cmdscale. Axes are ranked by their eigenvalues, so the first axis has the highest eigenvalue, the second axis has the second highest eigenvalue, etc. inertia <- sum(acop$eig[acop$eig > 0]) percents <- round(as.numeric(100 * axes.tot/inertia), digits = 0) # The eigenvalues represent the variance extracted by each axis, here they are expressed as a percentage of the sum of all eigenvalues (i.e. total variance). par() par(mfrow = c(1, 2), pty = "s") coord1 <- acop$points[, c(1, 2)] # points is a matrix whose rows give the coordinates of the points chosen to represent the dissimilarities col.grps <- data.frame(vect.grps, coord1) # plot so that the maximum variance is projected along the first axis, then on the second and so on plot(coord1, asp = 1, cex = 0.1, xlab = paste("Axis 1 ", "(", percents[1], " % variance explained)", sep = ""), ylab = paste("Axis 2 ", "(", percents[2], " % variance explained)", sep = ""), main = "", type = "n", bty = "n") abline(h = 0, lty = 2, col = "grey") abline(v = 0, lty = 2, col = "grey") if (length(vect.grps) == nrow(as.matrix(dat.d))) { for (g in 1:length(names.grps)) { text(x = coord1[col.grps[, 1] == names.grps[g], 1], y = coord1[col.grps[, 1] == names.grps[g], 2], labels = names.grps[g], col = topo.col[g], cex = 0.7) } } else { points(coord1, pch = 19, col = "blue", cex = 0.5) } coord1 <- acop$points[, c(3, 4)] col.grps <- data.frame(vect.grps, coord1) plot(coord1, asp = 1, cex = 0.1, xlab = paste("Axis 3 ", "(", percents[3], " % variance explained)", sep = ""), ylab = paste("Axis 4 ", "(", percents[4], " % variance explained)", sep = ""), main = "", type = "n", bty = "n") abline(h = 0, lty = 2, col = "grey") abline(v = 0, lty = 2, col = "grey") if (length(vect.grps) == nrow(as.matrix(dat.d))) { for (g in 1:length(names.grps)) { text(x = coord1[col.grps[, 1] == names.grps[g], 1], y = coord1[col.grps[, 1] == names.grps[g], 2], labels = names.grps[g], col = topo.col[g], cex = 0.7) } } else { points(coord1, pch = 19, col = "blue", cex = 0.5) </code></pre>

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