I try to plot contour with only one cntrlabel per line but I do not succeed. I tried
set cntrlabel onecolor start 50 interval 10000000
and
set cntrlabel onecolor start 50 interval -1
but it does not work. Is there a mean to force 1 label per line ?
Moreover, I would like to shift the cntrlabel in order to prevent them to be overlayed (as observed on the top-left of the graph with the label 45, 50, 55, and 60). How should I do ?
The code used to obtain this graph is the following:
FILE = "data_sensibilite_correlation_phiFR_Tpfr_fusion_ordre"
set contour base
set cntrparam level discrete 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 50, 55, 60
#set cntrparam level incremental 2, 4, 60
set cntrlabel onecolor start 50 interval 10000000
set xrange [-10:10]
set yrange [0.55:0.95]
#set cbrange [0:20]
set style textbox opaque
unset key
set view map
set xlabel "{/Symbol e}_{/Symbol q} [%]"
set ylabel "T_b / T_{c} uncertainties on T_c"
set cblabel "{/Symbol e}_{{/Symbol F} cs} [%]"
set pm3d noborder
splot FILE u 1:2:3 w pm3d, \
FILE u 1:2:3 w l lc "black" nosurface, \
FILE with labels boxed
The data is available here: https://filesender.renater.fr/?s=download&token=c718b69b-1496-47db-9da4-21d48cf08aa4
Some time ago, I experienced the same issue.
Since your data is not accessible anymore, I am creating some test data in the script itself.
The problem is that you see too many labels although you are trying to limit them via
set cntrlabel {start <int>} {interval <int>}.
Let me try to explain: If you plot the contour line into a datablock you will notice that although some contour lines in the graph look like continuous lines, however, in fact, they are interrupted by empty lines in the data.
I guess this comes from the algorithm how gnuplot determines the contour lines. It seems, the more data points you have, the higher the probability that some contour lines are interrupted.
In the first graph below I made the interruptions visible by setting variable line color depending on pseudocolumn -1 (check help pseudocolumns). For the time being ignore the yellow line.
For example, the contour line for the level 8 consists of 5 pieces (i.e. 5 different colors).
This means when plotting the contour labels even if you set every 200 (or interval 10000000) you will get at least as many labels per contour line as many "broken" parts you have for that line.
Test Graph:
So, you could try to merge these interrupted lines which might be feasible, however, is not so easy because:
you have contour lines which should not be merged, e.g. level 15 on the left side and on the right side of the graph
you cannot easily connect the interrupted lines by simply removing the empty lines because the data points of the line parts are not in the right order
A different approach:
Hence, here is another "simple" idea, but not so simple to realize:
Define a parametric curve (yellow line in the above graph) which will intersect all the contour lines which you want to have labeled.
The script will determine the intersection points and will place a label at these positions.
The determination of the intersections is somewhat lengthy and the code is taken from here.
This procedure is certainly slow and not very efficient because it checks each yellow segment against all other segments.
Currently, the sampling of the yellow line needs to be high enough (here: N=21) such that each yellow segment will intersect with one contour line segment. The calculation time for the intersections can probably be shortened considerably if one yellow segment can intersect several contour line segments. Alternatively, the intersection lines could be filtered by level and then intersected. I will try these options asap.
If anyone has a more ideas to improve, please let me know.
Script:
### add contour labels nicely aligned
reset session
# create some test data
f(x,y) = ((4*x)**2 + (-y-5)**2)/10.
set samples 200
set isosamples 200
set table $Data
splot '++' u (x):(y):(f(x,y))
set table $Contours
unset surface
set contour
set cntrparam levels discrete 2,4,6,8,10,15,20,25,30,40
splot $Data u 1:2:3
unset table
set colorsequence classic
set style textbox opaque
set key noautotitle
set view map
# define parametric function for "line of labels"
xmin = -5.5
xmax = 5.5
N = 21
g(x) = 0.25*x**2 - 2
gx(t) = xmin + t*(xmax-xmin)/N
gy(t) = g(gx(t))
set table $LabelLine
plot '+' u (gx($0)):(gy($0)) every ::::N w table
unset table
set xrange [:] noextend
set yrange [:] noextend
# this plotting part can be skipped, it's just for illustration purpose
plot $Contours u 1:2:-1 w l lc var, \
'' u 1:2:3 every 200 w labels boxed, \
$LabelLine u 1:2 w lp pt 7 lc "yellow" noautoscale
pause -1
# some necessary functions
# orientation of 3 points a,b,c: -1=clockwise, 0=linear, +1=counterclockwise
Orientation(a,b,c) = sgn((word(b,1)-word(a,1))*(word(c,2)-word(a,2)) - \
(word(c,1)-word(a,1))*(word(b,2)-word(a,2)))
# check for intersection of segment a-b with segment c-d,
# 0=no intersection, 1=intersection
IntersectionCheck(a,b,c,d) = \
(Orientation(a,c,b)==Orientation(a,d,b)) || (Orientation(c,a,d)==Orientation(c,b,d)) ? 0 : 1
# calculate coordinates of intersection point, "" if identical points
M(a,b) = real(word(a,1)*word(b,2) - word(a,2)*word(b,1))
N(a,b,c,d) = (word(a,1)-word(b,1))*(word(c,2)-word(d,2)) - \
(word(a,2)-word(b,2))*(word(c,1)-word(d,1))
Intersection(a,b,c,d) = N(a,b,c,d) !=0 ? sprintf("%g %g", \
(M(a,b)*(word(c,1)-word(d,1)) - (word(a,1)-word(b,1))*M(c,d))/N(a,b,c,d), \
(M(a,b)*(word(c,2)-word(d,2)) - (word(a,2)-word(b,2))*M(c,d))/N(a,b,c,d)) : ""
# looping data segments for finding intersections
set print $Intersections
do for [i=1:|$LabelLine|-1] {
a = sprintf("%s %s", word($LabelLine[i], 1),word($LabelLine[i], 2))
b = sprintf("%s %s", word($LabelLine[i+1],1),word($LabelLine[i+1],2))
Line = ''
Intersection0 = ''
do for [j=1:|$Contours|-1] {
c = $Contours[j]
d = $Contours[j+1]
if (strlen(c)!=0 && strlen(d)!=0 && c[1:1] ne '#' && c[1:1] ne '#') {
if (IntersectionCheck(a,b,c,d)) {
Intersection1 = Intersection(a,b,c,d)
if ((Intersection0 ne Intersection1)) {
Level = word($Contours[j],3)
print sprintf("%s %s %s",Intersection0, Intersection1, Level)
}
Intersection0 = Intersection1
}
}
else {Intersection0 = ''}
}
}
set print
set palette rgb 33,13,10
plot $Data u 1:2:3 w image, \
$Contours u 1:2 w l lc "black", \
$Intersections u 1:2:3 w labels boxed
### end of script
Result:
Here is a much simpler solution resulting in only one label per level, however, depending on your data you won't know where exactly the labels will be positioned.
The contour lines per level are separated by two empty lines. The different pieces within a contour line of one specific level might be separated into (sub-)blocks separated by a single empty line.
Now, you can address specific rows and sub-blocks via every (check help every). For example, if you only want to plot each second row of each first sub-block you can specify every ::1:0:1:0 (indices are zero-based). You need to play with these numbers, depending on your data and how many contour line breaks you have. However, most likely the labels will not be nicely aligned as in my other (much more complicated) answer. Furthermore, the labeling will be only once per level, i.e. no labels on the left side of the plot in the example below.
Script:
### add contour labels, only one per level
reset session
# create some test data
f(x,y) = ((4*x)**2 + (-y-5)**2)/10.
set samples 200
set isosamples 200
set table $Data
splot '++' u (x):(y):(f(x,y))
set table $Contours
unset surface
set contour
set cntrparam levels discrete 2,4,6,8,10,15,20,25,30,40
splot $Data u 1:2:3
unset table
set colorsequence classic
set style textbox opaque
set key noautotitle
set view map
set xrange [:] noextend
set yrange [:] noextend
set tics out
set palette rgb 33,13,10
plot $Data u 1:2:3 w image, \
$Contours u 1:2 w l lc "black", \
$Contours u 1:2:3 every ::1:1:1:1 w labels boxed
### end of script
Result:
I have an unsorted data set of two columns with most of the points aligning diagonally along y=x, however some points misalign.
I would like to show that most of the points actually do align along the function, however just pointplotting would just overlap the over-represented points to one. The viewer would then get the impression that the data points are actually scattered randomly because there is no weight to the occurrence count.
Is there a way to implement a weight to the points that occur more than once - maybe through point size? Couldnt find anything on this topic.
Thanks a lot!
You don't show data so I assumed something from your description. As #Christoph already mentioned you could use jitter or transparency to indicate that there are many more datapoints more or less at the same location. However, transparency is limited to 256 values (actually, 255 because fully transparent you won't see). So, in extreme case, if you have more than 255 points on top of each other you won't see a difference to 255 points on top of each other.
Basically, you're asking for displaying the density of points. This reminds me to this question: How to plot (x,y,z) points showing their density
In the example below a "pseudo" 2D-histogram is created. I'm not aware of 2D-histograms in gnuplot, so you have to do it as 1D-histogram mapping it onto 2D. You divide the plot into fields and count the occurrence of point in each field. This number you use either for setting the point variable color via palette or for variable pointsize.
The code example will generate 5 ways to plot the data:
solid points
empty points
transparent points
colored points
sized points (your question)
I leave it up to you to judge which way is suitable. Certainly it will depend pretty much on the data and your special case.
Code:
### different ways to show density of datapoints
reset session
# create some random test data
set print $Data
do for [i=1:1000] {
x=invnorm(rand(0))
y=x+invnorm(rand(0))*0.05
print sprintf("%g %g",x,y)
}
do for [i=1:1000] {
x=rand(0)*8-4
y=rand(0)*8-4
print sprintf("%g %g",x,y)
}
set print
Xmin=-4.0; Xmax=4.0
Ymin=-4.0; Ymax=4.0
BinXSize = 0.1
BinYSize = 0.1
BinXCount = int((Xmax-Xmin)/BinXSize)+1
BinYCount = int((Ymax-Ymin)/BinYSize)+1
BinXNo(x) = floor((x-Xmin)/BinXSize)
BinYNo(y) = floor((y-Ymin)/BinYSize)
myBinNo(x,y) = (_tmp =BinYNo(y)*BinXCount + BinXNo(x), \
_tmp < 0 || _tmp > BinXCount*BinYCount-1 ? NaN : int(_tmp+1))
# get data into 1D histogram
set table $Bins
plot [*:*][*:*] $Data u (myBinNo($1,$2)):(1) smooth freq
unset table
# initialize array all values to 0
array BinArr[BinXCount*BinYCount]
do for [i=1:BinXCount*BinYCount] { BinArr[i] = 0 }
# get histogram values into array
set table $Dummy
plot myMax=NaN $Bins u ($2<myMax?0:myMax=$2, BinArr[int($1)] = int($2)) w table
unset table
myBinValue(x,y) = (_tmp2 = myBinNo(x,y), _tmp2>0 && _tmp2<=BinXCount*BinYCount ? BinArr[_tmp2] : NaN)
# point size settings
myPtSizeMin = 0.0
myPtSizeMax = 2.0
myPtSize(x,y) = myBinValue(x,y)*(myPtSizeMax-myPtSizeMin)/myMax*myPtSizeMax + myPtSizeMin
set size ratio -1
set xrange [Xmin:Xmax]
set yrange [Ymin:Ymax]
set key top center out opaque box
set multiplot layout 2,3
plot $Data u 1:2 w p pt 7 lc "red" ti "solid points"
plot $Data u 1:2 w p pt 6 lc "red" ti "empty points"
plot $Data u 1:2 w p pt 7 lc "0xeeff0000" ti "transparent points"
set multiplot next
plot $Data u 1:2:(myBinValue($1,$2)) w p pt 7 ps 0.5 palette z ti "colored points"
plot $Data u 1:2:(myPtSize($1,$2)) w p pt 7 ps var lc "web-blue" ti "sized points"
unset multiplot
### end of code
Result:
I'd like to know how to set the same number of ytics for both independent y and y2 axis using gnuplot, still using automatic scaling, so that the grid is well aligned.
Right now, as you can see below, there are 6 ticks for the y axis and 7 for y2, and the chart looks poorly readable.
As far as I know, Gnuplot lets you only to specify the increment defining the tics not their count. A slightly dirty workaround would be to first generate the plot into a "fake" terminal, remember the detected autoscaled ranges on each axis, calculate the required tics spacing, and finally generate the image with these settings.
N = 6
set term unknown
set ytics
set y2tics #setting y2tics affects autoscale
set ylabel 'MSE'
set y2label 'CE'
set grid
set format y "%.2f"
set format y2 "%.1f"
plot \
'mse.dat' u 1:2 axis x1y1 w l t 'MSE', \
'ce.dat' u 1:2 axis x1y2 w l t 'CE'
min_y1 = GPVAL_Y_MIN
max_y1 = GPVAL_Y_MAX
min_y2 = GPVAL_Y2_MIN
max_y2 = GPVAL_Y2_MAX
dy1 = (max_y1 - min_y1) / N
dy2 = (max_y2 - min_y2) / N
set ytics min_y1, dy1
set y2tics min_y2, dy2
set yr [min_y1:max_y1]
set y2r [min_y2:max_y2]
set term png enhanced
set output "test.png"
replot
This then produces (using a digitized approximation of your data):
I want to create a streamline like arrow lines in Gnuplot,I already have the data points that I needed, so I think my problem is not the same as this post says and different from this post because I have already obtain the data needed for stramlines.
What I have done is like this:
So the red lines are vectors show flow field and green line is streamlines to guide the readers the direction of the flux. And all the large blue arrows are my aim to be plotted in GNUPLOT. I have kown how to plot middle arrows as this post has shown but what code I need to do if I want to plot more arrows along the lines?
To be more detailed, How can I plot like this:
I supply my data file here :
velocity.txt is for vector flow field data as "index,X,Y,vx,vy,particle-numbers"
line.txt is for streamline data as "X,Y"
and My gnu file is bleow:
set terminal postscript eps size 108,16 enhanced font "Arial-Bold,100"
set output 'vector.eps'
unset key
set tics
set colorbox
set border 0
set xtics 2
#set xlabel 'x'
#set ylabel 'y'
set xrange [0:108]
set yrange [0:16]
#set cbrange [0:40]
set nolabel
set style line 4 lt 2 lc rgb "green" lw 2
plot 'velcoity.txt' u 2:3:(250*$4):(250*$5) with vectors lc 1,'line.txt' u 1:2 ls 4
Thank you!
To plot arrows along a line you can again use the vectors plotting style like you do already for the stream field.
But to get a proper plot you must consider several points:
Usually gnuplot limits the size of the arrow heads to a fraction of the arrow length. So, if you want to plot a continuous line with arrows heads, the arrows themselves should have a very short length. To avoid downscaling of the arrow heads, use the size ... fixed option, which is available only since version 5.0
You have only the trajectory, x and y values, of the line. To extract the arrow direction, the simplest approach would be to use the difference between two neighbouring points (or at a distance of two or three points).
You can extract these differences in the using statement. As pseudo code, one could do the following:
if rownumber modulo 10 == 0:
save x and y values
else if rownumber modulo 10 == 1:
draw arrow from previous point to current point, only with a head
else
ignore the point.
Putting this pseudo-code in the using statement gives the following:
ev = 10
avg = 1
sc = 0.1
plot 'line.txt' u (prev_x = (int($0)%ev == 0 ? $1 : prev_x), prev_y = (int($0)%ev == 0 ? $2 : prev_y), int($0)%ev == avg ? $1 : 1/0):2:(sc*(prev_x-$1)):(sc*(prev_y-$2)) w vectors backhead size 2,20,90 fixed ls 4
To make things more flexible, I introduced some variables: ev tells you the difference count between two arrows heads, avg the distance between two points used to calculate the arrow direction, and sc the length of the arrow shaft.
As further improvement you can use the length of the stream field arrows to colour the stream field vectors. This gives the following script
reset
unset key
set tics
set colorbox
set border 0
set xtics 2
set autoscale xfix
set autoscale yfix
set autoscale cbfix
set style line 4 lt 2 lc rgb "green" lw 2
ev=30
avg=3
sc=0.1
field_scale=500
plot 'velcoity.txt' u 2:3:(field_scale*$4):(field_scale*$5):(sqrt($4**2+$5**2)) with vectors size 1,15,45 noborder lc palette,\
'line.txt' u 1:2 ls 4 w l,\
'' u (prev_x = (int($0)%ev == 0 ? $1 : prev_x), prev_y = (int($0)%ev == 0 ? $2 : prev_y), int($0)%ev == avg ? $1 : 1/0):2:(sc*(prev_x-$1)):(sc*(prev_y-$2)) w vectors backhead size 2,20,90 fixed ls 4
With the result (qt terminal):