149 lines
6.5 KiB
TeX
149 lines
6.5 KiB
TeX
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%%% R code to generate the input data files from corresponding simulation logs
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% R> setwd("~/Work/tensorPredictors")
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% R>
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% R> for (sim.name in c("1a", "1b", "1c", "1d", "1e")) {
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% R> pattern <- paste0("sim\\_", sim.name, "\\_normal\\-[0-9T]*\\.csv")
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% R> log.file <- sort(
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% R> list.files(path = "sim/", pattern = pattern, full.names = TRUE),
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% R> decreasing = TRUE
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% R> )[[1]]
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% R>
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% R> sim <- read.csv(log.file)
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% R>
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% R> aggr <- aggregate(sim[, names(sim) != "sample.size"], list(sample.size = sim$sample.size), mean)
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% R>
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% R> write.table(aggr, file = paste0("LaTeX/plots/aggr-", sim.name, "-normal.csv"), row.names = FALSE, quote = FALSE)
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% R> }
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\documentclass[border=0cm]{standalone}
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\usepackage{tikz}
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\usepackage{pgfplots}
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\usepackage{bm}
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\definecolor{gmlm}{RGB}{0,0,0}
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\definecolor{mgcca}{RGB}{86,180,233}
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\definecolor{tsir}{RGB}{0,158,115}
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\definecolor{hopca}{RGB}{230,159,0}
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\definecolor{pca}{RGB}{240,228,66}
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\definecolor{lpca}{RGB}{0,114,178}
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\definecolor{clpca}{RGB}{213,94,0}
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\pgfplotsset{
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every axis/.style={
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xtick={100,200,300,500,750},
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ymin=-0.05, ymax=1.05,
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grid=both,
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grid style={gray, dotted}
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},
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every axis plot/.append style={
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mark = *,
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mark size = 1pt,
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line width=0.8pt
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}
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}
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\tikzset{
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legend entry/.style={
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mark = *,
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mark size = 1pt,
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mark indices = {2},
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line width=0.8pt
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}
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}
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\begin{document}
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\begin{tikzpicture}[>=latex]
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\begin{axis}[
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name=sim-1a,
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xticklabel=\empty
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]
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\addplot[color = gmlm, line width=1pt] table[x = sample.size, y = dist.subspace.gmlm] {aggr-1a-normal.csv};
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\addplot[color = pca] table[x = sample.size, y = dist.subspace.pca] {aggr-1a-normal.csv};
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\addplot[color = hopca] table[x = sample.size, y = dist.subspace.hopca] {aggr-1a-normal.csv};
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\addplot[color = tsir] table[x = sample.size, y = dist.subspace.tsir] {aggr-1a-normal.csv};
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\addplot[color = mgcca] table[x = sample.size, y = dist.subspace.mgcca] {aggr-1a-normal.csv};
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\end{axis}
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\node[anchor = base west, yshift = 0.3em] at (sim-1a.north west) {
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a: linear dependence on $\mathcal{F}_y \equiv y$
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};
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\begin{axis}[
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name=sim-1b,
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anchor=north west, at={(sim-1a.right of north east)}, xshift=0.1cm,
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xticklabel=\empty,
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ylabel near ticks, yticklabel pos=right
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]
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\addplot[color = pca] table[x = sample.size, y = dist.subspace.pca] {aggr-1b-normal.csv};
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\addplot[color = hopca] table[x = sample.size, y = dist.subspace.hopca] {aggr-1b-normal.csv};
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\addplot[color = tsir] table[x = sample.size, y = dist.subspace.tsir] {aggr-1b-normal.csv};
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\addplot[color = mgcca] table[x = sample.size, y = dist.subspace.mgcca] {aggr-1b-normal.csv};
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\addplot[color = gmlm, line width=1pt] table[x = sample.size, y = dist.subspace.gmlm] {aggr-1b-normal.csv};
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\end{axis}
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\node[anchor = base west, yshift = 0.3em] at (sim-1b.north west) {
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b: cubic dependence on $y$
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};
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\begin{axis}[
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name=sim-1c,
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anchor=north west, at={(sim-1a.below south west)}, yshift=-.8em,
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xticklabel=\empty
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]
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\addplot[color = pca] table[x = sample.size, y = dist.subspace.pca] {aggr-1c-normal.csv};
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\addplot[color = hopca] table[x = sample.size, y = dist.subspace.hopca] {aggr-1c-normal.csv};
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\addplot[color = tsir] table[x = sample.size, y = dist.subspace.tsir] {aggr-1c-normal.csv};
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\addplot[color = mgcca] table[x = sample.size, y = dist.subspace.mgcca] {aggr-1c-normal.csv};
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\addplot[color = gmlm, line width=1pt] table[x = sample.size, y = dist.subspace.gmlm] {aggr-1c-normal.csv};
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\end{axis}
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\node[anchor = base west, yshift = 0.3em] at (sim-1c.north west) {
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c: rank $1$ $\boldsymbol{\beta}$'s
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};
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\begin{axis}[
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name=sim-1d,
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anchor=north west, at={(sim-1c.right of north east)}, xshift=0.1cm,
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ylabel near ticks, yticklabel pos=right
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]
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\addplot[color = pca] table[x = sample.size, y = dist.subspace.pca] {aggr-1d-normal.csv};
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\addplot[color = hopca] table[x = sample.size, y = dist.subspace.hopca] {aggr-1d-normal.csv};
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\addplot[color = tsir] table[x = sample.size, y = dist.subspace.tsir] {aggr-1d-normal.csv};
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\addplot[color = mgcca] table[x = sample.size, y = dist.subspace.mgcca] {aggr-1d-normal.csv};
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\addplot[color = gmlm, line width=1pt] table[x = sample.size, y = dist.subspace.gmlm] {aggr-1d-normal.csv};
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\end{axis}
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\node[anchor = base west, yshift = 0.3em] at (sim-1d.north west) {
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d: tri-diagonal $\boldsymbol{\Omega}$'s
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};
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\begin{axis}[
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name=sim-1e,
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anchor=north west, at={(sim-1c.below south west)}, yshift=-.8em
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]
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\addplot[color = pca] table[x = sample.size, y = dist.subspace.pca] {aggr-1e-normal.csv};
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\addplot[color = hopca] table[x = sample.size, y = dist.subspace.hopca] {aggr-1e-normal.csv};
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\addplot[color = tsir] table[x = sample.size, y = dist.subspace.tsir] {aggr-1e-normal.csv};
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\addplot[color = mgcca] table[x = sample.size, y = dist.subspace.mgcca] {aggr-1e-normal.csv};
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\addplot[color = gmlm, line width=1pt] table[x = sample.size, y = dist.subspace.gmlm] {aggr-1e-normal.csv};
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\end{axis}
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\node[anchor = base west, yshift = 0.3em] at (sim-1e.north west) {
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e: missspecified
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};
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\matrix[anchor = center] at (sim-1e.right of east -| sim-1d.south) {
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\draw[color=gmlm, legend entry, line width=1pt] plot coordinates {(0, 0) (.3, 0) (.6, 0)}; & \node[anchor=west] {GMLM}; \\
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\draw[color=tsir, legend entry] plot coordinates {(0, 0) (.3, 0) (.6, 0)}; & \node[anchor=west] {TSIR}; \\
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\draw[color=mgcca, legend entry] plot coordinates {(0, 0) (.3, 0) (.6, 0)}; & \node[anchor=west] {MGCCA}; \\
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\draw[color=hopca, legend entry] plot coordinates {(0, 0) (.3, 0) (.6, 0)}; & \node[anchor=west] {HOPCA}; \\
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\draw[color=pca, legend entry] plot coordinates {(0, 0) (.3, 0) (.6, 0)}; & \node[anchor=west] {PCA}; \\
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};
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\node[anchor = north] at (current bounding box.south) {Sample Size $n$};
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\node[anchor = south, rotate = 90] at (current bounding box.west) {Subspace Distance $d(\boldsymbol{B}, \hat{\boldsymbol{B}})$};
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\node[anchor = south, rotate = 270] at (current bounding box.east) {\phantom{Subspace Distance $d(\boldsymbol{B}, \hat{\boldsymbol{B}})$}};
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\node[anchor = south, font=\large] at (current bounding box.north) {Tensor Normal Simulation};
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\end{tikzpicture}
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\end{document}
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