In jrminter/rpemepma: Processing of data from PENEPMA simulations using R

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = NA
)

Our objective is to convert an output spectrum from a Monte Carlo simulation using PENEPMA into a R dataframe for analysis and other processing.

Load a spectrum

First we get our exemplar file.

spcPath <- system.file("extdata", "pe-spect-01.dat", package = "rpenepma")
spcPath

Then we create an R dataframe using the penepma_read_raw_data function.

library(rpenepma)
library(pander)
library(ggplot2)

df <- penepma_read_raw_data(spcPath)
rownames(df) <- c()

pander(head(df))

and the tail

pander(tail(df))

pander(summary(df))

Now we are ready to plot the spectrum. There is a very large dynamic range for both the probability density and the uncertainty. Penepma sets a lower limit for data at 1.0e-35. Missing values are set to zero. We want to remove values from the dataframe that are below a useful limit. We do this below and plot a copy of the dataframe that is limited to the useful values.

plt <- ggplot(df, aes(x = keV, y = pd.mu)) +
       geom_line() + 
       scale_x_continuous(breaks = seq(from = 0, to = 15, by = 1),
                          limits = c(0,15)) +
       scale_y_log10() +
       xlab(label="X-ray energy [keV]") +
       ylab(label="probability density") +
       # (1/(eV*sr*electron)") +
       ggtitle('PENEPMA simulation of Corning EagleXG glass at 15 kV') +
       theme(axis.text=element_text(size=12),
             axis.title=element_text(size=12),
             # center the title
             plot.title = element_text(hjust = 0.5))

print(plt)