# I need to create an xyplot() where I control the specific order of # both my conditioning variables. The default code below plots the # data correctly (dispersed across all 14 columns), but fails in two # ways. Both the primary conditioning variable (Transect), and the # secondary conditioning variable (Offset) are in alphanumeric order, # rather than the specific order I need.
# Here is a call to the input datafile, which should be attached. df <- read.csv(file = "T_5-04b_LTC-SE-SO-Compared.csv") # Basic default plot (correct data, incorrect layout): xyplot((sbd+sed)/2 ~ Result | Offset+Transect, groups = PARLABEL, as.table = TRUE, data = df, layout = c(14,4), type = "b") # I attempted to control the order following the method described in # the thread "[R] xyplot() - can you control how the plots are # ordered?", but I appear to be missing, or misunderstanding # something. The modeled code is here. It does put all the # individual 'lattices'(?) in the needed order, BUT the graphics # for the individual sets dump all the measurements into a single # cell, on the diagonal, as if it's treating the conditioning # variables as an [i,j] index. Again not what I want. # Draft code (incorrect data, correct layout): Transects <- c("LNF02", "LSF02", "LUR01", "LURT1", "LUR03", "LUR05", "LUR09", "LUR11", "LUR12", "LUR15", "LUR16", "LUR21", "LURT3", "LUR25", "LURT4", "LUR28", "LUR36", "LUR38", "LUR46", "LURT5", "LUR48", "LLR04", "LLR10", "LLR11", "LLRT1", "LLR17", "LLRT2", "LLR18", "LLRT3", "LLR19") Transects <- factor(Transects, levels = Transects) Offsets <- c("T", "U", "V", "Y", "Z", "A", "B", "C", "D", "E", "F", "G", "H") Offsets <- factor(Offsets, levels = Offsets) xyplot((sbd+sed)/2 ~ Result | Offsets+Transects, groups = PARLABEL, as.table = TRUE, data = df, layout = c(13,5), type = "b") # What I am looking for is a combination of the default plot, but ordered in # the layout of the second code fragment. # Baring my likely misunderstanding of the example cited above, # there several comments in the help files that index.cond and/or # param.cond could be 'easily' used. I have read the lattice help, # the lattice pdf, and many items in the R site help files. The # use of these features remains a complete mystery to me, but # then, that doesn't surprise me at all. # This should clean up anything created by the above scripts: # Clean-up ---------------------------------------------------------------- rm(df, xLabel, yLabel, xlimit) Thanks for all the help. Cheers, Guy Jett, R.G. Project Geologist gj...@itsi.com
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