Postcards from Asturias

Some days of hollidays this Easter to spend in Asturias. Up is a picture I take in  Lastres.
Down another nice village "Cudillero". 
Wish to all this Blog readers a nice Easter time.

Desearos a todos los lectores de este blog unos felices días de Semana Santa. Yo los he aprovechado para venir a Asturias.
En la foto superior os muestro Lastres, famoso poblado marinero,  debajo una foto de Cudillero.

Generating PDF docs with "R"

It is really amazing how while you are reading papers, bibliography,...., from the R community, how you can apply all these knowledge´s to your work in order to prepare nice documents.
In this plot you can see the spectra from sunflower seed without any treatment in the first column, and treated with MSC in the second (to remove scatter).

This plot has been generated in a PDF document with the script:

pdf("fig-1-1.pdf",width=9,height=7)
par(mfrow=c(3,2),mar=c(4,4,3,3))

Now we add all the plot script:

matplot(wave.ALL,t(ALL),type="l",lty=1,xlab="nm",
      ylab="log 1/R",col="blue",main="Sunflower RAW Spectra")
matplot(wave.VIS,t(VIS),type="l",lty=1,xlab="nm",
      ylab="log 1/R",col="blue",main="Sunflower RAW Spectra")
matplot(wave.NIR,t(NIR),type="l",lty=1,xlab="nm",
        ylab="log 1/R",col="blue",main="Sunflower RAW Spectra")
matplot(wave.ALL,t(ALLmsc),type="l",lty=1,xlab="nm",
ylab="log 1/R",col="blue",main="SFLW Spec MSC")
matplot(wave.VIS,t(VISmsc),type="l",lty=1,xlab="nm",
        ylab="log 1/R",col="blue",main="VIS segment SFLW Spec with MSC")
matplot(wave.NIR,t(NIRmsc),type="l",lty=1,xlab="nm",
        ylab="log 1/R",col="blue",main="NIR segment SFLW Spec with MSC")

and we finish with:

dev.off()

I use in this case for the documents the same settings than

Statistical Data Analysis Explained

This is a good page to practice R script.
http://www.statistik.tuwien.ac.at/StatDA/R-scripts/
I will practice these days some of the scripts specially for graphics. The book seems to be very interesting, so I hope to buy it soon.

The Joy of Stats

Overlapping "Reference" and "Predicted" histograms.

Some days ago reading the post:"Overlapping Histogram in R" , I thought that it could be a good idea to add this type of overlapping histograms plots to the monitor function, to see in this case the reference values histogram with the predicted values histogram overlapped.

In a perfect case we will see all the bars in a purple color, if not we will see the red (reference) and blue (predicted) colors, indicating the areas where the model is performing worse.

Monitor function is continuously updating, I have some future plans for process monitoring, and other tasks.

 

Energy Thermal Images | Tyrone Turner Photojournalism Multimedia Advertising Washington, DC

Energy Thermal Images | Tyrone Turner Photojournalism Multimedia Advertising Washington, DC

I really recommend having a a look to this wonderful pictures from Tyrone Turner. They have been published in  the National Geographic Magazine. He used an Infrared Camera.
What you see is temperature: Red is hottest and Blue coldest (Nat. Geographic-March 2009).

SkyJib with hyperspectral sensors