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<br>
Chapters:
</br>
<a href="Introduction.html">1: Introduction</a><br>
<a href="SimpleExample.html">2: Simple example</a><br>
<a href="InvokingGri.html">3: Invocation</a><br>
<a href="GettingMoreControl.html">4: Finer Control</a><br>
<a href="X-Y.html">5: X-Y Plots</a><br>
<a href="ContourPlots.html">6: Contour Plots</a><br>
<a href="Images.html">7: Image Plots</a><br>
<a href="Examples.html">8: Examples</a><br>
<a href="Commands.html">9: Gri Commands</a><br>
<a href="Programming.html">10: Programming</a><br>
<a href="Environment.html">11: Environment</a><br>
<a href="Emacs.html">12: Emacs Mode</a><br>
<a href="History.html">13: History</a><br>
<a href="Installation.html">14: Installation</a><br>
<a href="Bugs.html">15: Gri Bugs</a><br>
<a href="TestSuite.html">16: Test Suite</a><br>
<a href="Acknowledgments.html">17: Acknowledgments</a><br>
<a href="License.html">18: License</a><br>
<br>
Indices:</br>
<a href="ConceptIndex.html"><i>Concepts</i></a><br>
<a href="CommandIndex.html"><i>Commands</i></a><br>
<a href="BuiltinIndex.html"><i>Variables</i></a><br>
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<h2>8.9: Probability Density Function Diagram</h2>
A common application is to draw the probability density function for
(x,y) data. Gri has no builtin facility to do this, but the following
example shows how to create the gridded PDF data using a call to the
`<font color="#82140F"><code>perl</code></font>' system command. The gridded data thus generated are
contoured, creating a PDF diagram. As the comments in the program
state, the first call to Perl is specific to a particular dataset, and
can be ignored on first reading; it just creates the file
`<font color="#82140F"><samp>tmp-xy.\.pid.</samp></font>'.
<p>
<TABLE SUMMARY="Example" BORDER="0" BGCOLOR="#efefef" WIDTH="100%">
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<PRE>
<font color="#82140F">
# Draw prob-density-function TS diagram for Bravo data
<p>
# This first call to perl is specific to the
# particular (weird) dataset. All that matters
# is that a file of (x,y) data is created, and
# stored in the file called `tmp-xy.\.pid.'
system perl <<"EOF"
#
# Slurp in x[], y[] data
$dir = "/users/dek/kelley/Labrador/bravo/data";
$Sfile = "$dir/S_25db_1day";
$Tfile = "$dir/T_25db_1day";
open(S, "$Sfile") || die "Can't open input $Sfile";
open(T, "$Tfile") || die "Can't open input $Tfile";
open(ST, ">tmp-xy.\.pid.")
|| die "Can't open tmp-xy.\.pid.";
$day = 5;
$year = 1964;
while(<S>) {
@S = split;
$_ = <T>;
@T = split;
if (240 < $day && $day < 360) {
for ($i = 0; $i < $#S; $i++) { #all depths
print ST "$S[$i] $T[$i]\n";
}
}
$day += 1;
if ($day > 365) {
$year++;
$day = 0;
}
if ($year > 1967) { last; }
}
EOF
<p>
#
# Create 2D PDF for (x,y) data in file \infile
# storing the results in \outfile. X ranges
# between the indicated limits, with the indicated
# binsize, as does y. The synonyms defined
# on the next 4 lines are the only input this
# perlscript needs; the perlscript itself is
# quite general. For details of what it does,
# particularly the scaling of the PDF, see
# the perl comments.
\xmin = "33.5"; \xmax = "35.5"; \xinc = "0.05";
\ymin = "-2.0"; \ymax = "11.0"; \yinc = "0.25";
\infile = "tmp-xy.\.pid."
\outfile = "tmp-grid.\.pid."
system perl <<"EOF"
#
# Prepare 2 dimensional probability-density-function
# dataset for contouring by Gri. This reads (x,y)
# data from a file called $infile (defined below)
# and creates an output file called $outfile
# (also defined below) containing the
# x-grid, the y-grid, and then the grid data,
# suitable for reading/contouring by the Gri
# commands
# open tmp-grid.\.pid.
# read .number_of_data.
# read grid x
# read grid y
# read grid data
# draw contour
#
# The values in the output grid are defined so
# that they sum to the reciprocal of the
# product of the x binsize and y binsize (see
# definition of $factor below).
#
$xmin = \xmin; $xmax = \xmax; $xinc = \xinc;
$ymin = \ymin; $ymax = \ymax; $yinc = \yinc;
$infile = "\infile";
$outfile = "\outfile";
#
# Slurp in the x[], y[] data, storing
# the total number of data in $n.
open(IN, "$infile") || die "Can't open infile";
open(OUT, ">$outfile") || die "Can't open outfile";
$n = 0;
while(<IN>) {
($x[$n], $y[$n]) = split;
$n++;
}
#
# Zero out matrix (stored in a linear array scanned
# as one reads a book).
$cols = int(1 + ($xmax - $xmin) / $xinc);
$rows = int(1 + ($ymax - $ymin) / $yinc);
for ($y = $ymax; $y > $ymin; $y -= $yinc) {
for ($x = $xmin; $x < $xmax; $x += $xinc) {
$l = int(($x - $xmin) / $xinc
+ $cols * int(($y - $ymin) / $yinc));
$sum[$l] = 0;
}
}
#
# Cumulate (x,y) data into the matrix
$inside = 0;
for ($i = 0; $i < $n; $i++) {
if ($ymin <= $y[$i] && $y[$i] <= $ymax
&& $xmin <= $x[$i] && $x[$i] <= $xmax) {
$l = int(($x[$i] - $xmin) / $xinc
+ $cols * int(($y[$i] - $ymin) / $yinc));
$sum[$l]++;
$inside++;
} else {
print STDERR "($y[$i], $x[$i]) clipped\n";
}
}
#
# Print number of points (to allow renormalization
# if the user wishes)
print OUT "$inside\n";
#
# Print x grid, y grid, then grid itself
for ($x = $xmin; $x < $xmax; $x += $xinc) {
printf OUT "%lg\n", $x;
}
print OUT "\n";
for ($y = $ymax; $y > $ymin; $y -= $yinc) {
printf OUT "%lg\n", $y;
}
print OUT "\n";
#
# The $factor variable scales the PDF.
$factor = 1 / $xinc / $yinc / $inside;
for ($y = $ymax; $y > $ymin; $y -= $yinc) {
for ($x = $xmin; $x < $xmax; $x += $xinc) {
$l = int(($x - $xmin) / $xinc
+ $cols * int(($y - $ymin) / $yinc));
printf OUT "%lg ", $factor * $sum[$l];
}
print OUT "\n";
}
EOF
<p>
# Axes
set x margin 3
set x margin 6
set x name "Salinity [PSU]"
set y name "Potential Temperature [$\circ$C]"
set x axis 34.5 34.8 0.1
set y axis 5 9 1
draw axes
<p>
# PDF
open tmp-grid.\.pid.
read .number_of_data.
read grid x
read grid y
read grid data
.smooth. = 0
<p>
# Contours. Use clipping, since the axes are
# zooming in on part of the PDF.
set font size 8
set contour label position centered
set clip postscript on
set line width rapidograph 4x0
draw contour 0.2 2.2 0.4 unlabelled
set line width rapidograph 0
draw contour 0.4 2.4 0.4
set clip postscript off
end if
</font></PRE>
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