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https://github.com/dkogan/feedgnuplot

Tool to plot realtime and stored data from the commandline, using gnuplot.
https://github.com/dkogan/feedgnuplot

Last synced: 12 days ago
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Tool to plot realtime and stored data from the commandline, using gnuplot.

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README 

        
=head1 TALK



I just gave a talk about this at L. Here are the L and the

L<"slides"|https://github.com/dkogan/talk-feedgnuplot-vnlog/blob/master/feedgnuplot-vnlog.org>.



=head1 NAME



feedgnuplot - General purpose pipe-oriented plotting tool



=head1 SYNOPSIS



Simple plotting of piped data:



 $ seq 5 | awk '{print 2*$1, $1*$1}'

 2 1

 4 4

 6 9

 8 16

 10 25



 $ seq 5 | awk '{print 2*$1, $1*$1}' |

   feedgnuplot               \

     --lines                 \

     --points                \

     --title "Test plot"     \

     --y2 1                  \

     --unset key             \

     --unset grid



=for html 



Simple real-time plotting example: plot how much data is received on the wlan0

network interface in bytes/second. This plot updates at 1Hz, and shows the last

10sec of history. The plot shown here is the final state of a sample run



 $ while true; do

     sleep 1;

     cat /proc/net/dev;

   done \

   | gawk '/wlan0/ {if(b) {print $2-b; N++; fflush()} b=$2} N==15 {exit}' \

   | feedgnuplot            \

       --lines              \

       --title "wlan0 throughput" \

       --stream             \

       --xlen 10            \

       --ylabel 'Bytes/sec' \

       --xlabel seconds     \

       --unset key          \

       --unset grid



=for html 



=head1 DESCRIPTION



This is a flexible, command-line-oriented frontend to Gnuplot. It creates plots

from data coming in on STDIN or given in a filename passed on the commandline.

Various data representations are supported, as is hardcopy output and streaming

display of live data. For a tutorial and a gallery please see the guide at

L



A simple example:



 $ seq 5 | awk '{print 2*$1, $1*$1}' | feedgnuplot



You should see a plot with two curves. The C command generates some data to

plot and the C reads it in from STDIN and generates the plot. The

C invocation is just an example; more interesting things would be plotted

in normal usage. No commandline-options are required for the most basic

plotting. Input parsing is flexible; every line need not have the same number of

points. New curves will be created as needed.



The most commonly used functionality of gnuplot is supported directly by the

script. Anything not directly supported can still be done with options such as

C<--set>, C<--cmds> C<--style>, etc. Arbitrary gnuplot commands can be passed in

with C<--cmds>. For example, to turn off the grid, you can pass in C<--cmds

'unset grid'>. Commands C<--set> and C<--unset> exists to provide nicer syntax,

so this is equivalent to passing C<--unset grid>. As many of these options as

needed can be passed in. To add arbitrary curve styles, use C<--style curveID

extrastyle>. Pass these more than once to affect more than one curve.



To apply an extra style to I the curves that lack an explicit C<--style>,

pass in C<--styleall extrastyle>. In the most common case, the extra style is

C. To support this more simply, you can pass in C<--with

something> instead of C<--styleall 'with something'>. C<--styleall> and

C<--with> are mutually exclusive. Furthermore any curve-specific C<--style>

overrides the global C<--styleall> or C<--with> setting.



=head2 Data formats



By default, each value present in the incoming data represents a distinct data

point, as demonstrated in the original example above (we had 10 numbers in the

input and 10 points in the plot). If requested, the script supports more

sophisticated interpretation of input data



=head3 Domain selection



If C<--domain> is passed in, the first value on each line of input is

interpreted as the I-value for the rest of the data on that line. Without

C<--domain> the I-value is the line number, and the first value on a line is

a plain data point like the others. Default is C<--nodomain>. Thus the original

example above produces 2 curves, with B<1,2,3,4,5> as the I-values. If we run

the same command with C<--domain>:



 $ seq 5 | awk '{print 2*$1, $1*$1}' | feedgnuplot --domain



we get only 1 curve, with B<2,4,6,8,10> as the I-values. As many points as

desired can appear on a single line, but all points on a line are associated

with the I-value at the start of that line.



=head3 Curve indexing



We index the curves in one of 3 ways: sequentially, explicitly with a

C<--dataid> or by C<--vnlog> headers.



By default, each column represents a separate curve. The first column (after any

domain) is curve C<0>. The next one is curve C<1> and so on. This is fine unless

sparse data is to be plotted. With the C<--dataid> option, each point is

represented by 2 values: a string identifying the curve, and the value itself.

If we add C<--dataid> to the original example:



 $ seq 5 | awk '{print 2*$1, $1*$1}' | feedgnuplot --dataid --autolegend



we get 5 different curves with one point in each. The first column, as produced

by C, is B<2,4,6,8,10>. These are interpreted as the IDs of the curves to

be plotted.



If we're plotting C data (L) then we

can get the curve IDs from the vnlog header. Vnlog is a trivial data format

where lines starting with C<#> are comments and the first comment contains

column labels. If we have such data, C can interpret these

column labels if the C perl modules are available.



The C<--autolegend> option adds a legend using the given IDs to

label the curves. The IDs need not be numbers; generic strings are accepted. As

many points as desired can appear on a single line. C<--domain> can be used in

conjunction with C<--dataid> or C<--vnlog>.



=head3 Multi-value style support



Depending on how gnuplot is plotting the data, more than one value may be needed

to represent the range of a single point. Basic 2D plots have 2 numbers

representing each point: 1 domain and 1 range. But if plotting with

C<--circles>, for instance, then there's an extra range value: the radius. Many

other gnuplot styles require more data: errorbars, variable colors (C), variable sizes (C), labels and so on.

The feedgnuplot tool itself does not know about all these intricacies, but they

can still be used, by specifying the specific style with C<--style>, and

specifying how many values are needed for each point with any of

C<--rangesizeall>, C<--tuplesizeall>, C<--rangesize>, C<--tuplesize>. These

options are required I for styles not explicitly supported by feedgnuplot;

supported styles do the right thing automatically.



Specific example: if making a 2d plot of y error bars, the exact format can be

queried by running C and invoking C. This tells us

that there's a 3-column form: C and a 4-column form: C. With 2d plots feedgnuplot will always output the 1-value domain C, so

the rangesize is 2 and 3 respectively. Thus the following are equivalent:



 $ echo '1 2 0.3

         2 3 0.4

         3 4 0.5' | feedgnuplot --domain --rangesizeall 2 --with 'yerrorbars'



 $ echo '1 2 0.3

         2 3 0.4

         3 4 0.5' | feedgnuplot --domain --tuplesizeall 3 --with 'yerrorbars'



 $ echo '1 2 1.7 2.3

         2 3 2.6 3.4

         3 4 3.5 4.5' | feedgnuplot --domain --rangesizeall 3 --with 'yerrorbars'



=head3 3D data



To plot 3D data, pass in C<--3d>. C<--domain> MUST be given when plotting 3D

data to avoid domain ambiguity. If 3D data is being plotted, there are by

definition 2 domain values instead of one (I as a function of I and I

instead of I as a function of I). Thus the first 2 values on each line are

interpreted as the domain instead of just 1. The rest of the processing happens

the same way as before.



=head3 Time/date data



If the input data domain is a time/date, this can be interpreted with

C<--timefmt>. This option takes a single argument: the format to use to parse

the data. The format is documented in 'set timefmt' in gnuplot, although the

common flags that C understands are generally supported. The backslash

sequences in the format are I supported, so if you want a tab, put in a tab

instead of \t. Whitespace in the format I supported. When this flag is

given, some other options act a little bit differently:



=over



=item



C<--xlen> and C<--binwidth> are I in seconds



=item



C<--xmin> and C<--xmax> I use the format passed in to C<--timefmt>



=back



Using this option changes both the way the input is parsed I the way the

x-axis tics are labelled. Gnuplot tries to be intelligent in this labelling, but

it doesn't always do what the user wants. The labelling can be controlled with

the gnuplot C command, which takes the same type of format string as

C<--timefmt>. Example:



 $ sar 1 -1 |

   awk '$1 ~ /..:..:../ && $8 ~/^[0-9\.]*$/ {print $1,$8; fflush()}' |

   feedgnuplot --stream --domain

                --lines --timefmt '%H:%M:%S'

                --set 'format x "%H:%M:%S"'



This plots the 'idle' CPU consumption against time.



Note that while gnuplot supports the time/date on any axis, I

currently supports it I as the x-axis domain. This may change in the

future.



=head3 'using' expressions



We just described how feedgnuplot parses its input data. When passing this data

to gnuplot, each curve is sent independently. The domain appears in the leading

columns followed by C<--rangesize> columns to complete each row. Without

C<--domain>, feedgnuplot explicitly writes out sequential integers. gnuplot then

knows how many values it has for each point, and it knows which style we're

using, so it's able to interpret the data appropriately, and to make the correct

plot.



As an example, if gnuplot is passed 2 columns of data, and it is plotting C, it will use column 1 for the x coordinate and column 2 for the y

coordinate. This is the default behavior, but the meaning of each column can be

controlled via a C expression in gnuplot (not feedgnuplot; keep reading).

The default is sequential integers, so this example uses C by

default. We can flip the meaning of the columns by passing C.

Arbitrary expressions may be specified by enclosing each field in C<()>, and

using C<$> to denote each data column. So to use the 2nd column as the x

coordinate and the sum of the two columns as the y coordinate, C is passed. Furthermore, the number of columns can vary. For instance

gnuplot can read the same two columns of data, but produce a plot with the extra

column encoding the sum as the color: C.

Please see the gnuplot documentation for lots of detail.



That's how I works. Most of the time, I doesn't pass any

C expressions at all, and gnuplot does the default thing. But if we want

to do something fancy, feedgnuplot supports C<--using curveID expression> and

C<--usingall expression>. So we can plot a parabola:



  seq 100 | feedgnuplot --lines --usingall '1:($2*$2)'



This is powerful, but there are some things to keep in mind:



=over



=item



C<--using> overrides whatever C expression feedgnuplot was going to pass.

feedgnuplot passes a C expression only if C<--histogram> or C<--timefmt>

or C<--xticlabels> are given. So if C<--using> is given together with any of

these, the user must take care to do the right thing (whatever that means at

that time).



=item



The C<--tuplesize> controls the data passed to feedgnuplot and the data then

passed to gnuplot. It does I directly control how gnuplot eventually

interprets the data: C<--using> does that. So for instance we can plot

color-coded points:



  seq 10 | feedgnuplot --with 'points pt 7 palette' --usingall '1:2:2'



Here feedgnuplot read 1 column of data. It defauled to C<--tuplesize 2>, so it

passed 2 columns of data to gnuplot. gnuplot then produced 3 values for each

point, and plotted them as indicated with the C style.



=item



You I need a column of data to generate a curve. You might want to use a

C expression to plot a time series I its cumulative integral. The

C expression can compute the integral, but you I pass in the data

twice; once for each curve to plot:



  seq 100 |                           \

    awk '{print $1,$1}' |             \

    feedgnuplot                       \

      --cmds 'sum=0'                  \

      --cmds 'accum(x) = (sum=sum+x)' \

      --using 1 '1:(accum($2))'       \

      --lines --y2 1



=back



=head2 Real-time streaming data



To plot real-time data, pass in the C<--stream [refreshperiod]> option. Data

will then be plotted as it is received. The plot will be updated every

C seconds. If the period isn't specified, a 1Hz refresh rate is

used. To refresh at specific intervals indicated by the data, set the

refreshperiod to 0 or to 'trigger'. The plot will then I be refreshed when

a data line 'replot' is received. This 'replot' command works in both triggered

and timed modes, but in triggered mode, it's the only way to replot. Look in

L"Special data commands"> for more information.



To plot only the most recent data (instead of I the data), C<--xlen

windowsize> can be given. This will create an constantly-updating, scrolling

view of the recent past. C should be replaced by the desired length

of the domain window to plot, in domain units (passed-in values if C<--domain>

or line numbers otherwise). If the domain is a time/date via C<--timefmt>, then

C is and I in seconds. If we're plotting a histogram, then

C<--xlen> causes a histogram over a moving window to be computed. The subtlely

here is that with a histogram you don't actually I the domain since only

the range is analyzed. But the domain is still there, and can be utilized with

C<--xlen>. With C<--xlen> we can plot I histograms or I

I-histograms.



=head3 Special data commands



If we are reading streaming data, the input stream can contain special commands

in addition to the raw data. Feedgnuplot looks for these at the start of every

input line. If a command is detected, the rest of the line is discarded. These

commands are



=over



=item C



This command refreshes the plot right now, instead of waiting for the next

refresh time indicated by the timer. This command works in addition to the timed

refresh, as indicated by C<--stream [refreshperiod]>.



=item C



This command clears out the current data in the plot. The plotting process

continues, however, to any data following the C.



=item C



This command causes feedgnuplot to exit.



=back



=head2 Hardcopy output



The script is able to produce hardcopy output with C<--hardcopy outputfile>. The

output type can be inferred from the filename, if B<.ps>, B<.eps>, B<.pdf>,

B<.svg>, B<.png> or B<.gp> is requested. If any other file type is requested,

C<--terminal> I be passed in to tell gnuplot how to make the plot. If

C<--terminal> is passed in, then the C<--hardcopy> argument only provides the

output filename.



The B<.gp> output is special. Instead of asking gnuplot to plot to a particular

terminal, writing to a B<.gp> simply dumps a self-executable gnuplot script into

the given file. This is similar to what C<--dump> does, but writes to a file,

and makes sure that the file can be self-executing.



=head2 Self-plotting data files



This script can be used to enable self-plotting data files. There are several

ways of doing this: with a shebang (#!) or with inline perl data.



=head3 Self-plotting data with a #!



A self-plotting, executable data file C is formatted as



 $ cat data

 #!/usr/bin/feedgnuplot --lines --points

 2 1

 4 4

 6 9

 8 16

 10 25

 12 36

 14 49

 16 64

 18 81

 20 100

 22 121

 24 144

 26 169

 28 196

 30 225



This is the shebang (#!) line followed by the data, formatted as before. The

data file can be plotted simply with



 $ ./data



The caveats here are that on Linux the whole #! line is limited to 127

characters and that the full path to feedgnuplot must be given. The 127

character limit is a serious limitation, but this can likely be resolved with a

kernel patch. I have only tried on Linux 2.6.



=head3 Self-plotting data with gnuplot



Running C will create a self-executable

gnuplot script in C



=head3 Self-plotting data with perl inline data



Perl supports storing data and code in the same file. This can also be used to

create self-plotting files:



 $ cat plotdata.pl

 #!/usr/bin/perl

 use strict;

 use warnings;



 open PLOT, "| feedgnuplot --lines --points" or die "Couldn't open plotting pipe";

 while(  )

 {

   my @xy = split;

   print PLOT "@xy\n";

 }

 __DATA__

 2 1

 4 4

 6 9

 8 16

 10 25

 12 36

 14 49

 16 64

 18 81

 20 100

 22 121

 24 144

 26 169

 28 196

 30 225



This is especially useful if the logged data is not in a format directly

supported by feedgnuplot. Raw data can be stored after the __DATA__ directive,

with a small perl script to manipulate the data into a useable format and send

it to the plotter.



=head1 ARGUMENTS



=over



=item



--C<[no]domain>



If enabled, the first element of each line is the domain variable. If not, the

point index is used



=item



--C<[no]dataid>



If enabled, each data point is preceded by the ID of the data set that point

corresponds to. This ID is interpreted as a string, NOT as just a number. If not

enabled, the order of the point is used.



As an example, if line 3 of the input is "0 9 1 20" then



=over



=item



C<--nodomain --nodataid> would parse the 4 numbers as points in 4 different

curves at x=3



=item



C<--domain --nodataid> would parse the 4 numbers as points in 3 different

curves at x=0. Here, 0 is the x-variable and 9,1,20 are the data values



=item



C<--nodomain --dataid> would parse the 4 numbers as points in 2 different

curves at x=3. Here 0 and 1 are the data IDs and 9 and 20 are the

data values



=item



C<--domain --dataid> would parse the 4 numbers as a single point at

x=0. Here 9 is the data ID and 1 is the data value. 20 is an extra

value, so it is ignored. If another value followed 20, we'd get another

point in curve ID 20



=back



=item



C<--vnlog>



Vnlog is a trivial data format where lines starting with C<#> are comments and

the first comment contains column labels. Some tools for working with such data

are available from the C project: L.

With the C perl modules installed, we can read the vnlog column headers

with C. This replaces C<--dataid>, and we can do all the

normal things with these headers. For instance C will generate plot legends for each column in the vnlog, using the

vnlog column label in the legend.



=item



C<--[no]3d>



Do [not] plot in 3D. This only makes sense with C<--domain>. Each domain here is

an (x,y) tuple



=item



--C



Interpret the X data as a time/date, parsed with the given format



=item



C<--colormap>



This is a legacy option used to who a colormapped xy plot. It does:



- Adds C to C<--curvestyleall>



- Adds 1 to the default C<--tuplesize> (if C<--tuplesizeall> is not given



- Uses C<--zmin>, C<--zmax> to set the colorbar range



It's clearer to set the relevant options explicitly, but C<--colormap> still

exists for compatibility



=item



C<--stream [period]>



Plot the data as it comes in, in realtime. If period is given, replot every

period seconds. If no period is given, replot at 1Hz. If the period is given as

0 or 'trigger', replot I when the incoming data dictates this. See the

L"Real-time streaming data"> section of the man page.



=item



C<--[no]lines>



Do [not] draw lines to connect consecutive points



=item



C<--[no]points>



Do [not] draw points



=item



C<--circles>



Plot with circles. This requires a radius be specified for each point.

Automatically sets the C<--rangesize>/C<--tuplesize>. C supported for 3d

plots.



=item



C<--title xxx>



Set the title of the plot



=item



C<--legend curveID legend>



Set the label for a curve plot. Use this option multiple times for multiple

curves. With C<--dataid>, curveID is the ID. Otherwise, it's the index of the

curve, starting at 0



=item



C<--autolegend>



Use the curve IDs for the legend. Titles given with C<--legend> override these



=item



C<--xlen xxx>



When using C<--stream>, sets the size of the x-window to plot. Omit this or set

it to 0 to plot ALL the data. Does not make sense with 3d plots. Implies

C<--monotonic>. If we're plotting a histogram, then C<--xlen> causes a histogram

over a moving window to be computed. The subtlely here is that with a histogram

you don't actually I the domain since only the range is analyzed. But the

domain is still there, and can be utilized with C<--xlen>. With C<--xlen> we can

plot I histograms or I I-histograms.



=item



C<--xmin/xmax/x2min/x2max/ymin/ymax/y2min/y2max/zmin/zmax xxx>



Set the range for the given axis. These x-axis bounds are ignored in a streaming

plot. The x2/y2-axis bounds do not apply in 3d plots. The z-axis bounds apply

I to 3d plots or colormaps. Note that there is no C<--xrange> to set both

sides at once or C<--xinv> to flip the axis around: anything more than the

basics supported in this option is clearly obtainable by talking to gnuplot, for

instance C<--set 'xrange [20:10]'> to set the given inverted bounds.



=item



C<--xlabel/x2label/ylabel/y2label/zlabel/cblabel xxx>



Label the given axis. The x2/y2-axis labels do not apply to 3d plots while the

z-axis label applies I to 3d plots. The "cblabel" applies to the colorbar,

if there is one.



=item



C<--x2/--y2/--x1y2/--x2y1/--x2y2 xxx>



By default data is plotted against the x1 and y1 axes (the left and bottom one

respectively). If we want a particular curve plotted against a different axis,

we can specify that with these options. You pass C<--AXIS ID> where C

defines the axis (C or C or C or C or C) and the C

is the curve ID. C<--x2> is a synonym for C<--x2y1> and C<--y2> is a synonym for

C<--x1y2>. The curve ID is an ordered 0-based index or a specific ID if

C<--dataid> or C<--vnlog>. None of these apply to 3d plots. Can be passed

multiple times for different curve IDs, multiple IDs can be passed in as a

comma-separated list. By default the curves plotted against the various axes

aren not drawn in any differentiated way: the viewer of the resulting plot has

to be told which is which via an axes label, legend, colors, etc. Prior to

version 1.25 of C the curves plotted on the y2 axis were drawn with

a thicker line. This is no longer the case, but that behavior can be brought

back by passing something like



 --y2 curveid --style curveid 'linewidth 3'



=item



C<--histogram curveID>



Set up a this specific curve to plot a histogram. The bin width is given with

the C<--binwidth> option (assumed 1.0 if omitted). If a drawing style is not

specified for this curve (C<--curvestyle>) or all curves (C<--with>,

C<--curvestyleall>) then the default histogram style is set: filled boxes with

borders. This is what the user generally wants. This works with C<--domain>

and/or C<--stream>, but in those cases the x-value is used I to cull old

data because of C<--xlen> or C<--monotonic>. I.e. the domain values are I

drawn in any way. Can be passed multiple times, or passed a comma- separated

list



=item



C<--xticlabels>



If given, the x-axis tic labels are not numerical, but are read from the data.

This changes the interpretation of the input data: with C<--domain>, each line

begins with C. Without C<--domain>, each line begins with C. Clearly, the labels may not contain whitespace. This does I affect

the tuple size. This makes sense only without C<--3d>. Please see the guide

(L) for usage

examples.



=item



C<--binwidth width>



The width of bins when making histograms. This setting applies to ALL histograms

in the plot. Defaults to 1.0 if not given.



=item



C<--histstyle style>



Normally, histograms are generated with the 'smooth frequency' gnuplot style.

C<--histstyle> can be used to select different C settings (see the

gnuplot C page for more info). Allowed values are 'frequency' (the

default), 'fnormal' (available in very recent gnuplots), 'unique', 'cumulative'

and 'cnormal'. 'fnormal' is a normalized histogram. 'unique' indicates whether a

bin has at least one item in it: instead of counting the items, it'll always

report 0 or 1. 'cumulative' is the integral of the 'frequency' histogram.

'cnormal' is like 'cumulative', but rescaled to end up at 1.0.



=item



C<--style curveID style>



Additional styles per curve. With C<--dataid>, curveID is the ID. Otherwise,

it's the index of the curve, starting at 0. curveID can be a comma-separated

list of IDs to which the given style should apply. Use this option multiple

times for multiple curves. C<--styleall> does I apply to curves that have a

C<--style>.



=item



C<--curvestyle curveID>



Synonym for C<--style>



=item



C<--styleall xxx>



Additional styles for all curves that have no C<--style>. This is overridden by

any applicable C<--style>. Exclusive with C<--with>.



=item



C<--curvestyleall xxx>



Synonym for C<--styleall>



=item



C<--with xxx>



Same as C<--styleall>, but prefixed with "with". Thus



 --with boxes



is equivalent to



 --styleall 'with boxes'



Exclusive with C<--styleall>.



=item



C<--every curveID factor>



Decimates the input. Instead of plotting every point in the given curve, plot

one point per factor. This is useful to quickly process huge datasets. For

instance, to plot 1% of the data, pass a factor of 100.



=item



C<--everyall factor>



Decimates the input. This works exactly like C<--every>, except it applies to

I the curves.



=item



C<--using curveID expression>



Specifies a C expression to micromanage the plot. This is a powerful

option that allows gnuplot to interpret the input data in arbitrary ways. A

C expression tells gnuplot how to map the input columns of data to tuples

expected by the plotting style. Please see the L"'using' expressions"> section above for more detail.



=item



C<--usingall expression>



Global "using" expressions. This works exactly like C<--using>, except it

applies to I the curves.



=item



C<--cmds xxx>



Additional commands to pass on to gnuplot verbatim. These could contain extra

global styles for instance. Can be passed multiple times.



=item



C<--extracmds xxx>



Synonym for C<--cmds xxx>



=item



C<--set xxx>



Additional 'set' commands to pass on to gnuplot verbatim. C<--set 'a b c'> will

result in gnuplot seeing a C command. Can be passed multiple times.



=item



C<--unset xxx>



Additional 'unset' commands to pass on to gnuplot verbatim. C<--unset 'a b c'>

will result in gnuplot seeing a C command. Can be passed multiple

times.



=item



C<--image filename>



Overlays the data on top of a raster image given in C. This is passed

through to gnuplot via C<--equation>, and is not interpreted by C

other than checking for existence. Usually images have their origin at the

top-left corner, while plots have it in the bottom-left corner instead. Thus if

the y-axis extents are not specified (C<--ymin>, C<--ymax>, C<--set 'yrange

...'>) this option will also flip around the y axis to make the image appear

properly. Since this option is just a passthrough to gnuplot, finer control can

be achieved by passing in C<--equation> and C<--set yrange ...> directly.



=item



C<--equation xxx>



Gnuplot can plot both data and symbolic equations. C generally

plots data, but with this option can plot symbolic equations I. This is

generally intended to augment data plots, since for equation-only plots you

don't need C. C<--equation> can be passed multiple times for

multiple equations. The given strings are passed to gnuplot directly without

anything added or removed, so styling and such should be applied in the string.

A basic example:



 seq 100 | awk '{print $1/10, $1/100}' |

   feedgnuplot --with 'lines lw 3' --domain --ymax 1

               --equation 'sin(x)/x' --equation 'cos(x)/x with lines lw 4'



Here I plot the incoming data (points along a line) with the given style (a line

with thickness 3), I I plot two damped sinusoids on the same plot. The

sinusoids are not affected by C styling, so their styles are set

separately, as in this example. More complicated example:



 seq 360 | perl -nE '$th=$_/360 * 3.14*2; $c=cos($th); $s=sin($th); say "$c $s"' |

   feedgnuplot --domain --square

               --set parametric --set "trange [0:2*3.14]" --equation "sin(t),cos(t)"



Here the data I generate is points along the unit circle. I plot these as

points, and I I plot a true circle as a parametric equation.



=item



C<--equation-below xxx>



Synonym for C<--equation>. These are rendered I all the other data.



=item



C<--equation-above xxx>



Like C<--equation>, but is rendered I of all the other data.



=item



C<--square>



Plot data with aspect ratio 1. For 3D plots, this controls the aspect ratio for

all 3 axes



=item



C<--square-xy>



For 3D plots, set square aspect ratio for ONLY the x,y axes



=item



C<--hardcopy xxx>



If not streaming, output to a file specified here. Format inferred from

filename, unless specified by C<--terminal>. If C<--terminal> is given,

C<--hardcopy> sets I the output filename.



=item



C<--terminal xxx>



String passed to 'set terminal'. No attempts are made to validate this.

C<--hardcopy> sets this to some sensible defaults if C<--hardcopy> is set to a

filename ending in C<.png>, C<.pdf>, C<.ps>, C<.eps> or C<.svg>. If any other

file type is desired, use both C<--hardcopy> and C<--terminal>



=item



C<--maxcurves N>



The maximum allowed number of curves. This is 100 by default, but can be reset

with this option. This exists purely to prevent perl from allocating all of the

system's memory when reading bogus data



=item



C<--monotonic>



If C<--domain> is given, checks to make sure that the x-coordinate in the input

data is monotonically increasing. If a given x-variable is in the past, all data

currently cached for this curve is purged. Without C<--monotonic>, all data is

kept. Does not make sense with 3d plots. No C<--monotonic> by default. The data

is replotted before being purged. This is useful in streaming plots where the

incoming data represents multiple iterations of the same process (repeated

simulations of the same period in time, for instance).



=item



C<--rangesize curveID N>



The options C<--rangesizeall> and C<--rangesize> set the number of values are

needed to represent each point being plotted (see L"Multi-value style

support"> above). These options are I needed if unknown styles are used,

with C<--styleall> or C<--with> for instance.



C<--rangesize> is used to set how many values are needed to represent the range

of a point for a particular curve. This overrides any defaults that may exist

for this curve only.



With C<--dataid>, curveID is the ID. Otherwise, it's the index of the curve,

starting at 0. curveID can be a comma-separated list of IDs to which the given

rangesize should apply.



=item



C<--tuplesize curveID N>



Very similar to C<--rangesize>, but instead of specifying the I only,

this specifies the whole tuple. For instance if we're plotting circles, the

tuplesize is 3: C. In a 2D plot there's a 1-dimensional domain:

C, so the rangesize is 2: C. This dimensionality can be given

either way.



=item



C<--rangesizeall N>



Like C<--rangesize>, but applies to I the curves.



=item



C<--tuplesizeall N>



Like C<--tuplesize>, but applies to I the curves.



=item



C<--dump>



Instead of printing to gnuplot, print to STDOUT. Very useful for debugging. It

is possible to send the output produced this way to gnuplot directly.



=item



C<--exit>



This controls what happens when the input data is exhausted, or when some part

of the C pipeline is killed. This option does different things

depending on whether C<--stream> is active, so read this closely.



With interactive gnuplot terminals (qt, x11, wxt), the plot windows live in a

separate process from the main C process. It is thus possible for the

main C process to exit, while leaving the plot windows up (a caveat is

that such decapitated windows aren't interactive). There are 3 possible states

of the polotting pipeline:



=over



=item Alive: C, C alive, plot window process alive, no

shell prompt (shell busy with C)



=item Half-alive: C, C dead, plot window process alive

(but non-interactive), shell prompt available



=item Dead: C, C dead, plot window process dead, shell

prompt available



=back



The possibilities are:



=over



=item No C<--stream>, all data read in



=over



=item no C<--exit> (default)



Alive. Need to Ctrl-C to get back into the shell



=item C<--exit>



Half-alive. Non-interactive prompt up, and the shell accepts new commands.

Without C<--stream> the goal is to show a plot, so a Dead state would not be

useful.



=back



=item C<--stream>, all data read in or the C process terminated



=over



=item no C<--exit> (default)



Alive. Need to Ctrl-C to get back into the shell. This means that when making

live plots, the first Ctrl-C kills the data feeding process, but leaves the

final plot up for inspection. A second Ctrl-C kills feedgnuplot as well.



=item C<--exit>



Dead. No plot is shown, and the shell accepts new commands. With C<--stream> the

goal is to show a plot as the data comes in, which we have been doing. Now that

we're done, we can clean up everything.



=back



=back



Note that one usually invokes C as a part of a shell pipeline:



 $ write_data | feedgnuplot



If the user terminates this pipeline with ^C, then I the processes in the

pipeline receive SIGINT. This normally kills C and all its

C children, and we let this happen unless C<--stream> and no C<--exit>.

If C<--stream> and no C<--exit>, then we ignore the first ^C. The data feeder

dies, and we behave as if the input data was exhausted. A second ^C kills us

also.



=item



C<--geometry>



Specifies the size, position of the plot window. This applies I to the

C gnuplot terminal, and has no effect otherwise. To control the window size

for any other terminal, ask for the terminal explicitly, with the options

specifying the size. For instance C<--terminal 'qt size 1024,768'>



=item



C<--version>



Print the version and exit



=back



=head1 RECIPES



For a tutorial and a gallery please see the guide at

L



=head2 Basic plotting of piped data



 $ seq 5 | awk '{print 2*$1, $1*$1}'

 2 1

 4 4

 6 9

 8 16

 10 25



 $ seq 5 | awk '{print 2*$1, $1*$1}' |

   feedgnuplot --lines --points --legend 0 "data 0" --title "Test plot" --y2 1



=head2 Realtime plot of network throughput



Looks at wlan0 on Linux.



 $ while true; do sleep 1; cat /proc/net/dev; done |

   gawk '/wlan0/ {if(b) {print $2-b; fflush()} b=$2}' |

   feedgnuplot --lines --stream --xlen 10 --ylabel 'Bytes/sec' --xlabel seconds



=head2 Realtime plot of battery charge in respect to time



Uses the result of the C command.



 $ while true; do acpi; sleep 15; done |

   perl -nE 'BEGIN{ $| = 1; } /([0-9]*)%/; say join(" ", time(), $1);' |

   feedgnuplot --stream --ymin 0 --ymax 100 --lines --domain --xlabel 'Time' --timefmt '%s' --ylabel "Battery charge (%)"



=head2 Realtime plot of temperatures in an IBM Thinkpad



Uses C, which reports temperatures at various locations

in a Thinkpad.



 $ while true; do cat /proc/acpi/ibm/thermal | awk '{$1=""; print}' ; sleep 1; done |

   feedgnuplot --stream --xlen 100 --lines --autolegend --ymax 100 --ymin 20 --ylabel 'Temperature (deg C)'



=head2 Plotting a histogram of file sizes in a directory, granular to 10MB



 $ ls -l | awk '{print $5/1e6}' |

   feedgnuplot --histogram 0

     --binwidth 10

     --ymin 0 --xlabel 'File size (MB)' --ylabel Frequency



=head2 Plotting a live histogram of the ping round-trip times for the past 20 seconds



 $ ping -D 8.8.8.8 |

   perl -anE 'BEGIN { $| = 1; }

              $F[0] =~ s/[\[\]]//g or next;

              $F[7] =~ s/.*=//g    or next;

              say "$F[0] $F[7]"' |

   feedgnuplot --stream --domain --histogram 0 --binwidth 10 \

               --xlabel 'Ping round-trip time (s)'  \

               --ylabel Frequency --xlen 20



=head2 Plotting points on top of an existing image



This can be done with C<--image>:



 $ < features_xy.data

   feedgnuplot --points --domain --image "image.png"



or with C<--equation>:



 $ < features_xy.data

   feedgnuplot --points --domain

     --equation '"image.png" binary filetype=auto flipy with rgbimage'

     --set 'yrange [:] reverse'



The C<--image> invocation is a convenience wrapper for the C<--equation>

version. Finer control is available with C<--equation>.



Here an existing image is given to gnuplot verbatim, and data to plot on top of

it is interpreted by feedgnuplot as usual. C is useful here because

usually the y axis points up, but when looking at images, this is usually

reversed: the origin is the top-left pixel.



=head1 ACKNOWLEDGEMENT



This program is originally based on the driveGnuPlots.pl script from

Thanassis Tsiodras. It is available from his site at

L



=head1 REPOSITORY



L



=head1 AUTHOR



Dima Kogan, C<<  >>



=head1 LICENSE AND COPYRIGHT



Copyright 2011-2021 Dima Kogan.



This program is free software; you can redistribute it and/or modify it

under the terms of either: the GNU General Public License as published

by the Free Software Foundation; or the Artistic License.



See http://dev.perl.org/licenses/ for more information.



=cut