gnuplot 2D contour with multicolumn tabular dataset - plot

Question

How to turn the following tabular dataset into a simple 2D density plot to show a loc-number distribution?
I am new to gnuplot. Attempted a tutorial. A simple x,y plot with multiple columns of data, the plot is fine of course. Then tried this answer.. However I encountered the following issue, though x values are defined. I am guessing fundamentally my data set is lacking?(!).. what am I not doing right here? How to achieve a simple 2D contour from below data?
Updating based on recommended suggestions while OP aim remains intact.
Following is the input sample data used. File is single-space delimited. x = x, y=y, z1 = locid (1 to n) or z2=loctype (scuba, shower, swimming, restrooms, sushi, cafe, restaurant, etc)
input data :
ametype amename X(1000) Y1000) km-to-carpark
Scuba SCUB1 10.72 49.01
Scuba SCUB2 13.88 47.32
Scuba SCUB3 14.58 46.46
Scuba SCUB4 14.52 48.23
Scuba SCUB5 13.05 47.23
Scuba SCUB6 12.21 47.95
Scuba SCUB7 12.66 46.19
Cafe CAFE1 13.97 47.45
Cafe CAFE4 31.63 30.3
Playground PARK2 31.57 30.2
Playground PARK1 27.51 31.87
Cafe CAFE5 67.71 109.09
Scuba SCUB8 68.58 109.54
Scuba SCUB9 67.14 109.99
Cafe CAFE2 13.83 46.24
SUSHI SUSH1 79.59 41.22
SUSHI SUSHI2 73.81 54.14
SUSHI SUSHI3 72.87 55.47
SUSHI SUSHI4 75.05 56.51
RESTROOM RESTR1 74.1 56.05
RESTROOM RESTR2 74.96 57.9
RESTROOM RESTR3 75.06 55.59
RESTAURANT RESTAU1 76.57 56.33
RESTAURANT RESTAU1 76.95 55.1
RESTAURANT RESTAU2 77.75 54.69
RESTAURANT RESTAU2 76.15 54.34
code tried for a different dataset where x,y weren't coordinates;
set view map
set contour
set isosample 250, 250
set cntrparam level incremental 1, 0.1
set palette rgbformulae 33,13,10
splot 'data.dat' with lines nosurface
#splot for [col=1:10] ‘data.dat’ u ($1):(column(col) > 2 ? 1/0 : column(col)):3
errors:
1) All points x value undefined
2) Tabular output of this 3D plot style not implemented
updated:
a) increased data points
c) a possible chicken scratch to give simple impression.
Expecting a distribution density map like this.

Answer 1

This is an interesting plotting challenge.
The input data format is also straightforward, but needs some processing until the desired contour lines can be plotted with gnuplot.
Comments:
The data is all in one file. Data entries for the types can be random, no order necessary.
the example below will create some random test data with "Cafe, Scuba, Sushi" and 50 entries of each. Skip this part if you want to use your own file.
the further lines of the script, have no idea about the content of the test data file (i.e. how many types, type names, coordinates, etc.), all will be determined automatically.
create a unique list of types. The list will be in the order of first occurrence.
define a grid (here dx=0.2, dy=0.2, i.e. reasonable values within the data range) and count for each grid point the occurrences for each type within a certain radius (here: 0.5). Calculate the density by dividing the count by the unit area (area of the circle).
for each type create the contour lines via plotting to a file indexed by a two digit number. So far, I don't know how one would easily write this into indexed datablocks to avoid files on disk.
finally, plot the contour line files and the original data points by using a filter to get the right color.
One thing which I haven't figured out yet is set cntrparam level 2: I would like to have exactly 2 contour lines per type, but it seems gnuplot still uses the option set cntrparam level auto 2 and adjusts the number of levels itself.
As you can imagine this graph will probably look pretty confusing with 10 or more types.
For sure, there is room for improvement and no guarantee that there are no bugs in this script. Look at it as a starting point for further optimization. Suggestions for improvements are welcome!
Script:
### plot density contours from simple x,y location file
reset session
FILE = "SO73244095.dat"
# create some random test data
myTypes = "Cafe Scuba Sushi"
set print FILE
do for [p=1:words(myTypes)] {
a = word(myTypes,p)
x0 = rand(0)*5
y0 = rand(0)*5
do for [i=1:20] {
print sprintf("%s %s%d %.3g %.3g",a,a,i,invnorm(rand(0))+x0,invnorm(rand(0))+y0)
}
}
set print
# create a unique list of types
# and extract min, max data
addToList(list,col) = list.(_s='"'.strcol(col).'"', strstrt(list,_s)>0 ? '' : _s)
myTypes = ''
myType(i) = word(myTypes,i)
stats FILE u (myTypes=addToList(myTypes,1),$3):4 name "DATA" nooutput
Nt = words(myTypes)
print sprintf("%d types found: %s",Nt,myTypes)
# get densities for each type
dx = 0.2 # adjust the grid as you like...
dy = 0.2 # ... time for graph creation will increase with finer grid
Radius = 0.5 # adjust radius to a reasonable value
Nx = ceil((DATA_max_x-DATA_min_x)/dx)
Ny = ceil((DATA_max_y-DATA_min_y)/dy)
Dist(x0,y0,x1,y1) = sqrt((x1-x0)**2 + (y1-y0)**2)
print "Please wait..."
set print $Densities
do for [nt=1:Nt] {
do for [ny=0:Ny] {
do for [nx=0:Nx] {
c = 0
x = DATA_min_x+nx*dx
y = DATA_min_y+ny*dy
stats FILE u (Dist(x,y,$3,$4)<=Radius && (strcol(1) eq word(myTypes,nt)) ? c=c+1 : 0) nooutput
d = c / (pi * Radius**2) # density per unit area
print sprintf("%g %g %g",x,y,d)
}
print "" # empty line
}
print ""; print "" # two empty lines
}
set print
# get contour lines via splot into files
myContFile(n) = sprintf("%s.cont%02d",FILE,n)
unset surface
set contour
set cntrparam cubicspline levels 2 # cubicspline for "nice" round curves
do for [nt=1:Nt] {
set table myContFile(nt)
splot $Densities u 1:2:3 index nt-1
unset table
}
# set size ratio -1 # uncomment if equal x,y scale is important
set grid x,y
set key out noautotitle
set xrange[:] noextend
set yrange[:] noextend
set colorsequence classic
myFilter(colD,colF,valF) = strcol(colF) eq valF ? column(colD) : NaN
plot for [i=1:Nt] myContFile(i) u 1:2 w l lc i, \
for [i=1:Nt] FILE u 3:(myFilter(4,1,myType(i))) w p pt 7 lc i ti myType(i)
### end of script
Result: (a few random examples)