# Functions for plotting matrices, or for splitting them and for maing suitable summaries `Mplot` plots data from (a list of) matrices. `Msplit` splits a matrix in a list according to factors (or unique values). `Mcommon` creates a list of matrices that have only common variables. `Msummary` and `Mdescribe` create suitable summaries of all columns of a matrix or list. ```r Mplot (M, ..., x = 1, select = NULL, which = select, subset = NULL, ask = NULL, legend = list(x = "center"), pos.legend = NULL, xyswap = FALSE, rev = "") Msummary (M, ..., select = NULL, which = select, subset = NULL) Mdescribe (M, ..., select = NULL, which = select, subset = NULL) Msplit (M, split = 1, subset = NULL) Mcommon (M, ..., verbose = FALSE) ``` ## Arguments - `M`: Matrix or data.frame to be plotted, or treated. For `Mplot`, `M` can be a list with matrices or data.frames. - `x`: Name or number of the column to be used as the x-values. - `select`: Which variable/columns to be selected. This is added for consistency with the R-function `subset`. - `which`: The name(s) or the index to the variables that should be plotted or selected. Default = all variables, except `time`. - `subset`: Logical expression indicating elements or rows to keep in `select`: missing values are taken as `FALSE` - `ask`: Logical; if `TRUE`, the user is **ask**ed before each plot, if `NULL` the user is only asked if more than one page of plots is necessary and the current graphics device is set interactive, see `par(ask)` and `dev.interactive`. - `legend`: A `list` with parameters for the legend to be added. If `FALSE`, then no legend will be drawn. - `pos.legend`: The position of the legend, a number. The default is to put the legend in the last figure. Also allowed is `pos.legend = 0`, which will create a new figure with only the legend. - `xyswap`: If `TRUE`, then the x- and y-values will be swapped. - `rev`: a character string which contains "x" if the x axis is to be reversed, "y" if the y axis is to be reversed and "xy" or "yx" if both axes are to be reversed. - `split`: The name or number of the column with the factor according to which the matrix will be split. - `verbose`: If `TRUE` will write output to the screen. - ``...``: Additional arguments passed to the methods. For `Mplot`: can also be extra matrices to plot. The arguments after `...` must be matched exactly. ## Returns Function `Msplit` returns a list with the matrices, split according to the factors; the names of the elements is set by the factor's name. It is similar to the R-function split . Function `Mcommon` returns a list with the matrices, which only have the common variables. Function `Msummary` returns a data.frame with summary values (minimum, first quantile, median, mean, 3rd quantile, maximum) for each column of the input (variable). If there are more than one object to be summarised, or if M is a list of objects, the name of the object is in the second column. Function `Mdescribe` returns a data.frame with summary values (number of data, number of missing values, number of unique values, mean value, the standard deviation, the minimum, the p = 0.05, 0.1, 0.5, 0.9, 0.95 quantiles, and the maximum) for each column of the input (variable). If there are more than one object to be summarised, or if M is a list of objects, the name of the object is in the second column. ## Author(s) Karline Soetaert ## Examples ```r # save plotting parameters pm <- par("mfrow") ## ======================================================================= ## Create three dummy matrices ## ======================================================================= M1 <- matrix(nrow = 10, ncol = 5, data = 1:50) colnames(M1) <- LETTERS[1:5] M2 <- M1[, c(1, 3, 4, 5, 2)] M2[ ,-1] <- M2[,-1] /2 colnames(M2)[3] <- "CC" # Different name M3 <- matrix(nrow = 5, ncol = 4, data = runif(20)*10) M3[,1] <- sort(M3[,1]) colnames(M3) <- colnames(M1)[-3] # show them head(M1); head(M2); head(M3) Msummary(M1) Msummary(M1, M2, M3) # plot all columns of M3 - will change mfrow Mplot(M3, type = "b", pch = 18, col = "red") # plot results of all three data sets Mplot(M1, M2, M3, lwd = 2, mtext = "All variables versus 1st column", legend = list(x = "top", legend = c("M1", "M2", "M3"))) ## ======================================================================= ## Plot a selection or only common elements ## ======================================================================= Mplot(M1, M2, M3, x = "B", select = c("A", "E"), pch = c(NA, 16, 1), type = c("l", "p", "b"), col = c("black", "red", "blue"), legend = list(x = "right", legend = c("M1", "M2", "M3"))) Mplot(Mcommon(M1, M2, M3), lwd = 2, mtext = "common variables", legend = list(x = "top", legend = c("M1", "M2", "M3"))) Mdescribe(Mcommon(M1, M2, M3)) ## ======================================================================= ## The iris and Orange data set ## ======================================================================= # Split the matrix according to the species Irislist <- Msplit(iris, split = "Species") names(Irislist) Mdescribe(Irislist, which = "Sepal.Length") Mdescribe(iris, which = "Sepal.Length", subset = Species == "setosa") # legend in a separate plot Mplot(Irislist, type = "p", pos.legend = 0, legend = list(x = "center", title = "species")) Mplot(Msplit(Orange,1), lwd = 2, legend = list(x = "topleft", title = "tree nr")) Msummary(Msplit(Orange,1)) # reset plotting parameters par(mfrow = pm) ```

Mplot function