more guide plots

guide/guide.org

@@ -117,9 +117,9 @@ perl -nE '$thdeg = $_/100.*360.;
           $s  = sin($th);
           $c  = cos($th);
           say "$c $s $thdeg";' | \
-feedgnuplot --lines --points --domain --square \
+feedgnuplot --domain --square \
             --tuplesizeall 3  \
-            --styleall 'with points palette'
+            --styleall 'with linespoints palette'
 #+END_SRC
 
 #+RESULTS:
@@ -281,6 +281,9 @@ feedgnuplot --dataid \
 #+RESULTS:
 [[file:guide-10.svg]]
 
+Here we used =--set= to set the range of the colorbar. =--set= (and =--unset=)
+map to the gnuplot =set= (and =--unset=) command.
+
 ** Error bars
 As before, the =gnuplot= documentation has the styling details:
 
@@ -388,3 +391,63 @@ feedgnuplot --domain          \
 
 #+RESULTS:
 [[file:guide-14.svg]]
+
+** 3D plots
+We can plot in 3D by passing =--3d=. When plotting interactively, you can use
+the mouse to rotate the plot, and look at it from different directions.
+Otherwise, the viewing angle can be set with =--set 'view ...'=. See
+
+#+BEGIN_SRC sh :results none :exports code
+gnuplot -e 'help set view'
+#+END_SRC
+
+Unlike 2D plots, 3D plots have a 2-dimensional domain, and =--domain= is
+/required/. So each line is interpreted =x y z0 z1 z2...=.
+
+A double-helix with variable color and variable pointsize
+
+#+BEGIN_SRC sh :results file link :exports both
+seq 200 | \
+perl -nE '$, = " ";
+          $th = $_/10;
+          $z  = $_/40;
+          $c  = cos($th);
+          $s  = sin($th);
+          $size = 0.5 + abs($c);
+          $color = $z;
+          say  $c,  $s, 0, $z, $size, $color;
+          say -$c, -$s, 1, $z, $size, $color;' | \
+feedgnuplot --domain --dataid --3d \
+            --with 'points pointsize variable pointtype 7 palette' \
+            --tuplesizeall 5 \
+            --title "Double helix" \
+            --squarexy
+#+END_SRC
+
+#+RESULTS:
+[[file:guide-15.svg]]
+
+** Histograms
+=gnuplot= (and =feedgnuplot=) has support for histograms. So we can give it
+data, and have it bin it for us. Pre-sorting the data is unnecessary. Let's look
+at the central limit theorem: we look at the distribution of sums of 10 uniform
+samples in [-1,1]: it should be normal-ish. And let's draw the expected perfect
+PDF on top (as an equation, evaluated by =gnuplot=).
+
+#+BEGIN_SRC sh :results file link :exports both
+N=1000;
+Nsum=200;
+var=$((Nsum/3));
+binwidth=0.2;
+seq $N | \
+perl -nE '$Nsum = '$Nsum';
+          $s = 0; for $i (1..$Nsum) { $s += rand()*2-1; }
+          say $s;' | \
+feedgnuplot --histo 0 --binwidth $binwidth \
+            --equation-above "($N * sqrt(2.*pi*$var) * erf($binwidth/(2.*sqrt(2.*$var)))) * \
+                              exp(-(x*x)/(2.*$var)) / \
+                              sqrt(2.*pi*$var) title \"Limit gaussian\" with lines lw 2"
+#+END_SRC
+
+#+RESULTS:
+[[file:guide-16.svg]]