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Updates to rep #114

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merged 5 commits into from
Jun 19, 2024
Merged

Updates to rep #114

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73dcd71
Updates
serbinsh Jun 17, 2024
d7add6f
Merge branch 'main' of github.com:plantphys/spectratrait into updates…
serbinsh Jun 17, 2024
4b2acaa
Merge branch 'main' of github.com:plantphys/spectratrait into updates…
serbinsh Jun 18, 2024
aeab015
Merge branch 'main' of github.com:plantphys/spectratrait into updates…
serbinsh Jun 18, 2024
a7ef314
Updates addressing issues #100, #113
serbinsh Jun 19, 2024
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9 changes: 5 additions & 4 deletions inst/scripts/simple_spectra-trait_plsr_example.R
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Original file line number Diff line number Diff line change
Expand Up @@ -191,24 +191,25 @@ cal.RMSEP <- round(sqrt(mean(plsr_data.output$PLSR_CV_Residuals^2)),2)
rng_quant <- quantile(plsr_data.output[,inVar], probs = c(0.001, 0.999))
cal_scatter_plot <- ggplot(plsr_data.output, aes(x=PLSR_CV_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ", paste0("RMSEP = ", cal.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

cal_resid_histogram <- ggplot(plsr_data.output, aes(x=PLSR_CV_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

# plot cal/val side-by-side
scatterplots <- grid.arrange(cal_scatter_plot, cal_resid_histogram, nrow=2, ncol=1)
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39 changes: 22 additions & 17 deletions inst/scripts/spectra-trait_ely_leafN_plsr_bootstrap_example.R
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Expand Up @@ -91,14 +91,16 @@ rm(split_data)
print(paste("Cal observations: ",dim(cal.plsr.data)[1],sep=""))
print(paste("Val observations: ",dim(val.plsr.data)[1],sep=""))

cal_hist_plot <- qplot(cal.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Cal. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),
alpha=I(.7))
val_hist_plot <- qplot(val.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Val. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),
alpha=I(.7))
cal_hist_plot <- ggplot(data = cal.plsr.data,
aes(x = cal.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Calibration Histogram for ",inVar), x = paste0(inVar),
y = "Count")
val_hist_plot <- ggplot(data = val.plsr.data,
aes(x = val.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Validation Histogram for ",inVar), x = paste0(inVar),
y = "Count")
histograms <- grid.arrange(cal_hist_plot, val_hist_plot, ncol=2)
ggsave(filename = file.path(outdir,paste0(inVar,"_Cal_Val_Histograms.png")), plot = histograms,
device="png", width = 30,
Expand Down Expand Up @@ -221,46 +223,49 @@ val.RMSEP <- round(sqrt(mean(val.plsr.output$PLSR_Residuals^2)),2)
rng_quant <- quantile(cal.plsr.output[,inVar], probs = c(0.001, 0.999))
cal_scatter_plot <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ", paste0("RMSEP = ", cal.RMSEP))) +
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ",
paste0("RMSEP = ", cal.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

cal_resid_histogram <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

rng_quant <- quantile(val.plsr.output[,inVar], probs = c(0.001, 0.999))
val_scatter_plot <- ggplot(val.plsr.output, aes(x=PLSR_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Validation: ", paste0("Rsq = ", val.R2), "; ", paste0("RMSEP = ", val.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

val_resid_histogram <- ggplot(val.plsr.output, aes(x=PLSR_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

# plot cal/val side-by-side
scatterplots <- grid.arrange(cal_scatter_plot, val_scatter_plot, cal_resid_histogram,
Expand Down
42 changes: 24 additions & 18 deletions inst/scripts/spectra-trait_ely_leafN_plsr_bootstrap_grp_example.R
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Expand Up @@ -92,14 +92,16 @@ rm(split_data)
print(paste("Cal observations: ",dim(cal.plsr.data)[1],sep=""))
print(paste("Val observations: ",dim(val.plsr.data)[1],sep=""))

cal_hist_plot <- qplot(cal.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Cal. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),
alpha=I(.7))
val_hist_plot <- qplot(val.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Val. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),
alpha=I(.7))
cal_hist_plot <- ggplot(data = cal.plsr.data,
aes(x = cal.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Calibration Histogram for ",inVar), x = paste0(inVar),
y = "Count")
val_hist_plot <- ggplot(data = val.plsr.data,
aes(x = val.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Validation Histogram for ",inVar), x = paste0(inVar),
y = "Count")
histograms <- grid.arrange(cal_hist_plot, val_hist_plot, ncol=2)
ggsave(filename = file.path(outdir,paste0(inVar,"_Cal_Val_Histograms.png")), plot = histograms,
device="png", width = 30,
Expand Down Expand Up @@ -216,46 +218,50 @@ val.RMSEP <- round(sqrt(mean(val.plsr.output$PLSR_Residuals^2)),2)
rng_quant <- quantile(cal.plsr.output[,inVar], probs = c(0.001, 0.999))
cal_scatter_plot <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ", paste0("RMSEP = ", cal.RMSEP))) +
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ",
paste0("RMSEP = ", cal.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

cal_resid_histogram <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

rng_quant <- quantile(val.plsr.output[,inVar], probs = c(0.001, 0.999))
val_scatter_plot <- ggplot(val.plsr.output, aes(x=PLSR_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Validation: ", paste0("Rsq = ", val.R2), "; ", paste0("RMSEP = ", val.RMSEP))) +
title=paste0("Validation: ", paste0("Rsq = ", val.R2), "; ",
paste0("RMSEP = ", val.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

val_resid_histogram <- ggplot(val.plsr.output, aes(x=PLSR_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

# plot cal/val side-by-side
scatterplots <- grid.arrange(cal_scatter_plot, val_scatter_plot, cal_resid_histogram,
Expand Down
37 changes: 22 additions & 15 deletions inst/scripts/spectra-trait_kit_sla_plsr_example.R
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Original file line number Diff line number Diff line change
Expand Up @@ -123,12 +123,16 @@ rm(split_data)
print(paste("Cal observations: ",dim(cal.plsr.data)[1],sep=""))
print(paste("Val observations: ",dim(val.plsr.data)[1],sep=""))

cal_hist_plot <- qplot(cal.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Cal. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),alpha=I(.7))
val_hist_plot <- qplot(val.plsr.data[,paste0(inVar)],geom="histogram",
main = paste0("Val. Histogram for ",inVar),
xlab = paste0(inVar),ylab = "Count",fill=I("grey50"),col=I("black"),alpha=I(.7))
cal_hist_plot <- ggplot(data = cal.plsr.data,
aes(x = cal.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Calibration Histogram for ",inVar), x = paste0(inVar),
y = "Count")
val_hist_plot <- ggplot(data = val.plsr.data,
aes(x = val.plsr.data[,paste0(inVar)])) +
geom_histogram(fill=I("grey50"),col=I("black"),alpha=I(.7)) +
labs(title=paste0("Validation Histogram for ",inVar), x = paste0(inVar),
y = "Count")
histograms <- grid.arrange(cal_hist_plot, val_hist_plot, ncol=2)
ggsave(filename = file.path(outdir,paste0(inVar,"_Cal_Val_Histograms.png")),
plot = histograms, device="png", width = 30, height = 12, units = "cm",
Expand Down Expand Up @@ -252,46 +256,49 @@ val.RMSEP <- round(sqrt(mean(val.plsr.output$PLSR_Residuals^2)),2)
rng_quant <- quantile(cal.plsr.output[,inVar], probs = c(0.001, 0.999))
cal_scatter_plot <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Calibration: ", paste0("Rsq = ", cal.R2), "; ", paste0("RMSEP = ", cal.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

cal_resid_histogram <- ggplot(cal.plsr.output, aes(x=PLSR_CV_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

rng_quant <- quantile(val.plsr.output[,inVar], probs = c(0.001, 0.999))
val_scatter_plot <- ggplot(val.plsr.output, aes(x=PLSR_Predicted, y=get(inVar))) +
theme_bw() + geom_point() + geom_abline(intercept = 0, slope = 1, color="dark grey",
linetype="dashed", size=1.5) + xlim(rng_quant[1], rng_quant[2]) +
linetype="dashed", linewidth=1.5) +
xlim(rng_quant[1], rng_quant[2]) +
ylim(rng_quant[1], rng_quant[2]) +
labs(x=paste0("Predicted ", paste(inVar), " (units)"),
y=paste0("Observed ", paste(inVar), " (units)"),
title=paste0("Validation: ", paste0("Rsq = ", val.R2), "; ", paste0("RMSEP = ", val.RMSEP))) +
title=paste0("Validation: ", paste0("Rsq = ", val.R2), "; ",
paste0("RMSEP = ", val.RMSEP))) +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

val_resid_histogram <- ggplot(val.plsr.output, aes(x=PLSR_Residuals)) +
geom_histogram(alpha=.5, position="identity") +
geom_vline(xintercept = 0, color="black",
linetype="dashed", size=1) + theme_bw() +
linetype="dashed", linewidth=1) + theme_bw() +
theme(axis.text=element_text(size=18), legend.position="none",
axis.title=element_text(size=20, face="bold"),
axis.text.x = element_text(angle = 0,vjust = 0.5),
panel.border = element_rect(linetype = "solid", fill = NA, size=1.5))
panel.border = element_rect(linetype = "solid", fill = NA, linewidth=1.5))

# plot cal/val side-by-side
scatterplots <- grid.arrange(cal_scatter_plot, val_scatter_plot, cal_resid_histogram,
Expand Down
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