Dear R-list,
Among the (R-)tools, I've seen on the net, for (bivariate) Principal Component
scatter plots (+histograms), "plotpc" [1] is the one I like most.
By default it performs PCA on a bivariate dataset based on R's "princomp()"
(which is the eigenvector-based algebraic solution to PCA). I would like to
modify "plotpc()" in order be able, as an end-user, to define whether the PCA
should be performed by using:
(a) "princomp()" (the default currently)
(b) the "prcomp()" function (which is the SVD-based algebraic solution to
PCA)
Of course I want to have control over the parameters that "prcomp()" accepts,
namely:
- data centering (argument "center")
- data scaling (argument "scale")
Hopefully this is the right place to post this question(s). I started the
modification by attempting first to get a "prcomp" version of "plotpc()"
(named it "plotpc.svd()") by altering the following:
- accept the arguments "pccenter" and "pcscale" in line 1:
--%<---
"function ( x , pccenter = TRUE, scale = FALSE, xrange =... )"
-->%---
- accept both the "center" and the "scale" parameters for the "scale()"
function in line 134:
--%<---
x <- scale (x , center = pccenter , scale = pcscale )
-->%---
- change "princomp" to "prcomp" in line 140 as well as all required
arguments (that I know off):
--%<---
pc <- prcomp ( x[, 1:2] , center = FALSE , scale = FALSE , retx = TRUE ,
na.action = na.fail )
-->%---
-- in line 144:
--%<---
angle <- atan2(pc$rotation[2, 1], pc$rotation[1, 1])
-->%---
-- in lines 147 and 148, I replaced "pc$scores" with "pc$x"
Running the modified function ends up with an error:
--%<---
# "x" is a data.frame with two columns and works fine with plotpc()
plotpc.svd (x , pccenter = TRUE , pcscale = FALSE )
Error in inherits(unit, "unit") : could not find function "un"
# getting more info
traceback()
5: inherits(unit, "unit")
4: is.unit(y)
3: textGrob(label = label, x = x, y = y, just = just, hjust = hjust,
vjust = vjust, rot = rot, check.overlap = check.overlap,
default.units = default.units, name = name, gp = gp, vp = vp)
2: grid.text(main, y = un(ymean + xlim[2] + xrange/10), gp = gpar(cex = 1,
font = 2))
1: plotpc.svd(x, pccenter = TRUE, pcscale = FALSE)
-->%---
I am bit lost now about where I should continue looking for required
modifications in the code. Any hints?
Thanks in advance, Nikos
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