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The plot() function in R is used to create the line graph.
GRAPH creates bar charts, pie charts, line charts, error bar charts, high-low-close charts, scatterplots, and Pareto charts. Options. Titles and Footnotes. You can specify a title, subtitle, and footnote for the chart using the TITLE , SUBTITLE , and FOOTNOTE subcommands.
Try gnuplot. It has very powerful graphing possibilities.
It can output to your terminal in the following way:
gnuplot> set terminal dumb
Terminal type set to 'dumb'
Options are 'feed 79 24'
gnuplot> plot sin(x)
1 ++----------------**---------------+----**-----------+--------**-----++
+ *+ * + * * + sin(x) ****** +
0.8 ++ * * * * * * ++
| * * * * * * |
0.6 ++ * * * * * * ++
* * * * * * * |
0.4 +* * * * * * * ++
|* * * * * * * |
0.2 +* * * * * * * ++
| * * * * * * * |
0 ++* * * * * * *++
| * * * * * * *|
-0.2 ++ * * * * * * *+
| * * * * * * *|
-0.4 ++ * * * * * * *+
| * * * * * * *
-0.6 ++ * * * * * * ++
| * * * * * * |
-0.8 ++ * * * * * * ++
+ * * + * * + * * +
-1 ++-----**---------+----------**----+---------------**+---------------++
-10 -5 0 5 10
While gnuplot is powerful, it's also really irritating when you just want to pipe in a bunch of points and get a graph.
Thankfully, someone created eplot (easy plot), which handles all the nonsense for you.
It doesn't seem to have an option to force terminal graphs; I patched it like so:
--- eplot.orig 2012-10-12 17:07:35.000000000 -0700
+++ eplot 2012-10-12 17:09:06.000000000 -0700
@@ -377,6 +377,7 @@
# ---- print the options
com="echo '\n"+getStyleString+@oc["MiscOptions"]
com=com+"set multiplot;\n" if doMultiPlot
+ com=com+"set terminal dumb;\n"
com=com+"plot "+@oc["Range"]+comString+"\n'| gnuplot -persist"
printAndRun(com)
# ---- convert to PDF
An example of use:
[$]> git shortlog -s -n | awk '{print $1}' | eplot 2> /dev/null
3500 ++-------+-------+--------+--------+-------+--------+-------+-------++
+ + + "/tmp/eplot20121012-19078-fw3txm-0" ****** + * | 3000 +* ++ |* | | * | 2500 ++* ++ | * |
| * |
2000 ++ * ++
| ** |
1500 ++ **** ++
| * |
| ** |
1000 ++ * ++
| * |
| * |
500 ++ *** ++
| ************** |
+ + + + ********** + + + +
0 ++-------+-------+--------+--------+-----***************************++
0 5 10 15 20 25 30 35 40
Another option I've just run across is bashplotlib. Here's an example run on (roughly) the same data as my eplot example:
[$]> git shortlog -s -n | awk '{print $1}' | hist
33| o
32| o
30| o
28| o
27| o
25| o
23| o
22| o
20| o
18| o
16| o
15| o
13| o
11| o
10| o
8| o
6| o
5| o
3| o o o
1| o o o o o
0| o o o o o o o
----------------------
-----------------------
| Summary |
-----------------------
| observations: 50 |
| min value: 1.000000 |
| mean : 519.140000 |
|max value: 3207.000000|
-----------------------
Adjusting the bins helps the resolution a bit:
[$]> git shortlog -s -n | awk '{print $1}' | hist --nosummary --bins=40
18| o
| o
17| o
16| o
15| o
14| o
13| o
12| o
11| o
10| o
9| o
8| o
7| o
6| o
5| o o
4| o o o
3| o o o o o
2| o o o o o
1| o o o o o o o
0| o o o o o o o o o o o o o
| o o o o o o o o o o o o o
--------------------------------------------------------------------------------
See also: asciichart (implemented in Node.js, Python, Java, Go and Haskell)
feedgnuplot is another front end to gnuplot, which handles piping in data.
$ seq 5 | awk '{print 2*$1, $1*$1}' |
feedgnuplot --lines --points --legend 0 "data 0" --title "Test plot" --y2 1 \
--terminal 'dumb 80,40' --exit
Test plot
10 ++------+--------+-------+-------+-------+--------+-------+------*A 25
+ + + + + + + + **#+
| : : : : : : data 0+**A*** |
| : : : : : : :** # |
9 ++.......................................................**.##....|
| : : : : : : ** :# |
| : : : : : : ** # |
| : : : : : :** ##: ++ 20
8 ++................................................A....#..........|
| : : : : : **: # : |
| : : : : : ** : ## : |
| : : : : : ** :# : |
| : : : : :** B : |
7 ++......................................**......##................|
| : : : : ** : ## : : ++ 15
| : : : : ** : # : : |
| : : : :** : ## : : |
6 ++..............................*A.......##.......................|
| : : : ** : ##: : : |
| : : : ** : # : : : |
| : : :** : ## : : : ++ 10
5 ++......................**........##..............................|
| : : ** : #B : : : |
| : : ** : ## : : : : |
| : :** : ## : : : : |
4 ++...............A.......###......................................|
| : **: ##: : : : : |
| : ** : ## : : : : : ++ 5
| : ** : ## : : : : : |
| :** ##B# : : : : : |
3 ++.....**..####...................................................|
| **#### : : : : : : |
| **## : : : : : : : |
B** + + + + + + + +
2 A+------+--------+-------+-------+-------+--------+-------+------++ 0
1 1.5 2 2.5 3 3.5 4 4.5 5
You can install it on Debian and Ubuntu by running sudo apt install feedgnuplot .
Plots in a single line are really simple, and can help one see patterns of highs and lows.
See also pysparklines.
(Does anyone know of unicode slanting lines, which could be fit together to make
line, not bar, plots ?)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division
import numpy as np
__version__ = "2015-01-02 jan denis"
#...............................................................................
def onelineplot( x, chars=u"▁▂▃▄▅▆▇█", sep=" " ):
""" numbers -> v simple one-line plots like
f ▆ ▁ ▁ ▁ █ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ osc 47 ▄ ▁ █ ▇ ▄ ▆ ▅ ▇ ▇ ▇ ▇ ▇ ▄ ▃ ▃ ▁ ▃ ▂ rosenbrock
f █ ▅ █ ▅ █ ▅ █ ▅ █ ▅ █ ▅ █ ▅ █ ▅ ▁ ▁ ▁ ▁ osc 58 ▂ ▁ ▃ ▂ ▄ ▃ ▅ ▄ ▆ ▅ ▇ ▆ █ ▇ ▇ ▃ ▃ ▇ rastrigin
f █ █ █ █ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ ▁ osc 90 █ ▇ ▇ ▁ █ ▇ █ ▇ █ ▇ █ ▇ █ ▇ █ ▇ █ ▇ ackley
Usage:
astring = onelineplot( numbers [optional chars= sep= ])
In:
x: a list / tuple / numpy 1d array of numbers
chars: plot characters, default the 8 Unicode bars above
sep: "" or " " between plot chars
How it works:
linscale x -> ints 0 1 2 3 ... -> chars ▁ ▂ ▃ ▄ ...
See also: https://github.com/RedKrieg/pysparklines
"""
xlin = _linscale( x, to=[-.49, len(chars) - 1 + .49 ])
# or quartiles 0 - 25 - 50 - 75 - 100
xints = xlin.round().astype(int)
assert xints.ndim == 1, xints.shape # todo: 2d
return sep.join([ chars[j] for j in xints ])
def _linscale( x, from_=None, to=[0,1] ):
""" scale x from_ -> to, default min, max -> 0, 1 """
x = np.asanyarray(x)
m, M = from_ if from_ is not None \
else [np.nanmin(x), np.nanmax(x)]
if m == M:
return np.ones_like(x) * np.mean( to )
return (x - m) * (to[1] - to[0]) \
/ (M - m) + to[0]
#...............................................................................
if __name__ == "__main__": # standalone test --
import sys
if len(sys.argv) > 1: # numbers on the command line, may be $(cat myfile)
x = map( float, sys.argv[1:] )
else:
np.random.seed( 0 )
x = np.random.exponential( size=20 )
print onelineplot( x )
Check the package plotext which allows to plot data directly on terminal using python3. It is very intuitive as its use is very similar to the matplotlib package.
Here is a basic example:
You can install it with the following command:
sudo -H pip install plotext
As for matplotlib, the main functions are scatter (for single points), plot (for points joined by lines) and show (to actually print the plot on terminal). It is easy to specify the plot dimensions, the point and line styles and whatever to show the axes, number ticks and final equations, which are used to convert the plotted coordinates to the original real values.
Here is the code to produce the plot shown above:
import plotext.plot as plx
import numpy as np
l=3000
x=np.arange(0, l)
y=np.sin(4*np.pi/l*np.array(x))*np.exp(-0.5*np.pi/l*x)
plx.scatter(x, y, rows = 17, cols = 70)
plx.show(clear = 0)
The option clear=True inside show is used to clear the terminal before plotting: this is useful, for example, when plotting a continuous flow of data.
An example of plotting a continuous data flow is shown here:
The package description provides more information how to customize the plot. The package has been tested on Ubuntu 16 where it works perfectly. Possible future developments (upon request) could involve extension to python2 and to other graphical interfaces (e.g. jupiter). Please let me know if you have any issues using it. Thanks.
I hope this answers your problem.
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