1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88
|
#!/usr/bin/perl
#-------------------------------------------------------------------------------
#
# Plot a histogram (using R)
# Data is feed as a 1 column of numbers
#
# Note: Any line that does not match a numeric regular expression, is filtered out).
#
# Pablo Cingolani
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Main
#-------------------------------------------------------------------------------
# Parse command line option (file base name)
$base = 'hist';
if( $ARGV[0] ne '' ) { $base = $ARGV[0]; }
$pngFile = "$base.png";
$txtFile = "$base.txt";
# Read STDIN and create an R vector
open TXT, "> $txtFile" or die "Cannot open output file '$txtFile'\n";
print TXT "x\n";
for( $ln = 0 ; $l = <STDIN> ; ) {
chomp $l;
# Does the string contain exactly one number? (can be float)
if( $l =~ /^[-+]?[0-9]*\.?[0-9]+([eE][-+]?[0-9]+)?$/ ) { print TXT "$l\n"; }
}
close TXT;
#---
# Create an R program, save histogram plot as PNG image
#---
open R, "| R --vanilla --slave " or die "Cannot open R program\n";
print R <<EOF;
histDens <- function( x, title, q=1.0, breaks = 50 ) {
# Show only this part of the data
xmin <- quantile( x, 1-q )
xmax <- quantile( x, q )
data <- x[ (x >= xmin) & (x <= xmax) ];
dens <- density(data)
h <- hist(data, main=title, xlab = "data", ylab = "Frequency", freq = T, breaks=breaks);
# Adjust density height to 'frecuency'
dens\$y <- max(h\$counts) * dens\$y/max(dens\$y)
lines(dens, col='red')
# Mean & median calculated over the whola data
abline( v=mean(x), col='blue', lty=2, lwd=2);
abline( v=median(x), col='green', lty=2, lwd=2);
legend("topright",c("Mean","Median"),lty=c(1,1),col=c("blue","green"))
}
png('$pngFile', width = 1024, height = 1024);
par( mfrow=c(2,1) );
data <- read.csv("$txtFile", sep='\\t', header = TRUE);
x <- data\$x
histDens( x, "Histogram: All data", 1.0 );
histDens( x, "Histogram: Quantile [2% - 98%]", 0.98 );
print( summary( x ) )
cat('std:', sd(x), '\\n')
dev.off();
quit( save='no' )
EOF
close R;
#---
# Show figure
#---
$os = `uname`;
$show = "eog";
if( $os =~ "Darwin" ) { $show = "open"; }
`$show $pngFile &`;
|