## ----setup, echo=FALSE, results='hide', warning=FALSE--------------------------------------------- knitr::opts_chunk$set( message = FALSE, warning = FALSE, background = '#F7F7F7', fig.align = 'center', dev = 'png', comment = "#>" ) # keep examples from using more than 2 cores data.table::setDTthreads(Sys.getenv("OMP_THREAD_LIMIT", unset = 2)) options(width = 100, stringsAsFactors = FALSE, timeout = 600) ## ------------------------------------------------------------------------------------------------- library(aqp) library(soilDB) ## ------------------------------------------------------------------------------------------------- # example data data("jacobs2000") # fully populated plotSPC(jacobs2000, name.style = 'center-center', cex.names = 0.8, color = 'time_saturated') # missing some data plotSPC(jacobs2000, name.style = 'center-center', cex.names = 0.8, color = 'concentration_color') # very nearly complete plotSPC(jacobs2000, name.style = 'center-center', cex.names = 0.8, color = 'matrix_color') # variables to consider v <- c('time_saturated', 'concentration_color', 'matrix_color') # compute data completeness by profile # ignore 2C horizons jacobs2000$data.complete <- evalMissingData( jacobs2000, vars = v, method = 'relative', p = '2C' ) jacobs2000$data.complete.abs <- evalMissingData( jacobs2000, vars = v, method = 'absolute', p = '2C' ) # compute data completeness by horizon # ignore 2C horizons jacobs2000$hz.data.complete <- evalMissingData( jacobs2000, vars = v, method = 'horizon', p = '2C' ) # "fraction complete" by horizon plotSPC( jacobs2000, name.style = 'center-center', cex.names = 0.8, color = 'hz.data.complete' ) # rank on profile completeness new.order <- order(jacobs2000$data.complete) # plot along data completeness ranking plotSPC( jacobs2000, name.style = 'center-center', cex.names = 0.8, color = 'hz.data.complete', plot.order = new.order ) # add relative completeness axis # note re-ordering of axis labels axis( side = 1, at = 1:length(jacobs2000), labels = round(jacobs2000$data.complete[new.order], 2), line = 0, cex.axis = 0.75 ) # add absolute completeness (cm) axis( side = 1, at = 1:length(jacobs2000), labels = jacobs2000$data.complete.abs[new.order], line = 2.5, cex.axis=0.75 ) # label axes mtext('Relative\nCompleteness', side = 1, at = 0.25, line = 0.25, cex = 0.8) mtext('Absolute\nCompleteness (cm)', side = 1, at = 0.25, line = 2.75, cex = 0.8) ## ------------------------------------------------------------------------------------------------- x <- fetchKSSL(series = 'pierre') par(mar = c(0, 0, 3, 2)) plotSPC(x, color = 'clay', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') plotSPC(x, color = 'cec7', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') plotSPC(x, color = 'estimated_oc', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') plotSPC(x, color = 'ph_h2o', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') plotSPC(x, color = 'db_13b', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') par(mar = c(1, 0, 3, 2)) plotSPC(x, color = 'ph_h2o', width = 0.3, name.style = 'center-center', label = 'pedon_completeness_index') .b <- x[, , .LAST, .BOTTOM] text(x = 1:length(x), y = .b, labels = x$pi, cex = 0.85, pos = 1) mtext('Profile Information Index (bytes)', side = 1, line = -0.5) v <- c('clay', 'db_13b', 'cec7', 'ph_h2o') x$rel.not.missing <- evalMissingData(x, vars = v, method = 'relative') x$abs.not.missing <- evalMissingData(x, vars = v, method = 'absolute') x$hz.not.missing <- evalMissingData(x, vars = v, method = 'horizon') o <- order(x$rel.not.missing) plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o) text(x = 1:length(x), y = .b[o], labels = round(x$rel.not.missing[o], 2), cex = 0.85, pos = 1) mtext('Relative Non-Missing Fraction', side = 1, line = -0.5) o <- order(x$abs.not.missing) plotSPC(x, color = 'hz.not.missing', width = 0.33, name.style = 'center-center', label = 'pedon_completeness_index', plot.order = o) text(x = 1:length(x), y = .b[o], labels = x$abs.not.missing[o], cex = 0.85, pos = 1) mtext('Absolute Non-Missing (cm)', side = 1, line = -0.5)