plotme

A script written in python that plots data from a file or from a dataframe, outputs that graph as an image or pdf.

Command Line Arguments

Description and valid values for each argument. Examples are presented in a different section.

File Handling

Verbose	Short	Default	Description	Valid Values
--fileName	-f	required	Name of the files that contain the data for the graph. It can be a directory as well, as long as there are csv files in it.	filename with or without path.extension / directory name with or without path
--fileExtension	-ext	'.csv'	File extension to be chosen if a directory is passed.	string
--dontSave	-ds	Saves the plot	Defines if plot will be saved.	-
--displayPlot	-dp	Doesn't display the plot	Defines if plot will be displayed.	-
--separator	-sep	,(comma)	Defines the separator used in the input file, for parsing purposes.	' ', '\t', regular expressions and other file delimiters
--comment	-com	#	The character that will indicate if a line should be treated as comment.	string
--output	-o	.pdf	Name and/or extension of the output file.	'.png', 'name', 'name.png'

Plot Configuration

Verbose	Short	Default	Description	Valid Values
--graphType	-g	line	Type of graph that will be plotted.	line, scatter, pie and bar
--figSize	-fig	auto	Size of the graph and the exported image (Bounding Box).	float,float
--plotTitle	-pt	none	Title that appears at the top of the plot.	string
--fontSize	-fs	auto	Size of the font used in the graph itself.	int
--showSpine	-st	Doesn't show	Shows the spines from the graph.	-
--symbols	-s	point symbol	Shape of the symbols used.	Lists [ex: vhD] or values in https://matplotlib.org/3.1.0/api/markers_api.html
--distBetSymbols	-d	auto	Distance between each symbol.	int
--symbolSize	-ss	auto	Size of each symbol.	float
--lineWidth	-l	auto	Size of the line on a Line plot.	int or float
--pieLabel	-pl	none	Labels of the data in the pie plot.	string1,string2,...,stringN

Axis Configuration

Verbose	Short	Default	Description	Valid Values
--x	-x	first column	The x-axis of the plot.	Indexes of columns *
--y	-y	second column	The y-axis of the plot.	Indexes of columns(value, list [ex: 2,3,4] or sequences [ex: 2-4] *
--xmax	-xmax	auto	Maximum value of x to be plotted.	float
--xmin	-xmin	auto	Minimum value of x to be plotted.	float
--ymax	-ymax	auto	Maximum value of y to be plotted.	float
--ymin	-ymin	auto	Minimum value of y to be plotted.	float
--xLabel	-xl	column name	Label of the x-axis.	string
--yLabel	-yl	column name	Label of the y-axis.	string

Color Configuration

Verbose	Short	Default	Description	Valid Values
--setPalette	-p	colorblind	Graph color palette.	deep, muted, pastel, bright, dark and colorblind
--bgColor	-bgc	lightgrey	Changes the color of the background.	'red','black','lightyellow','#abc','#ff701E' **
--gColor	-gc	grey	Changes the color of the grid.	'red','black','lightyellow','#abc','#ff701E' **
--colors	-c	cycles default colors	Selects the colors of the plotted y-axes in the scatter and line plots.	'red','black','lightyellow','#abc','#ff701E

Miscellaneous

Verbose	Short	Default	Description	Valid Values
--movingAverageWindow	-w	1	Plots the moving average, given the window	-
--standardDeviation	-sd	Doesn't calculate	Makes a plot of the mean and the standard deviation over all the files, ploting the shadow. To plot standard deviation, there must be at least two files. If a directory is provided, it must only contain the files that are to be plotted. All files must have the same number of rows.	-
--areaUnderCurve	-auc	Doesn't calculate	Calculates the area under the curve for a given file and the y index(es). If activated, doesn't generate a plot. Only accepts one file (if more than one files are given, will only calculate auc for the first file and ignore the others).	-
--areaUnderCurveMethod	-aucm	'simpson'	The method that is going to be used for the auc calculation. It can be the simpson rule, the trapezoidal rule or the mean of them.	'simpson', 'trapz' or 'mean'

• Column indexes begin at 1, not 0 ** See https://matplotlib.org/stable/tutorials/colors/colors.html for more examples *** 'lightblue', 'yellow', 'grey', 'lightpink', 'brown', 'pink', 'orange', 'green', 'dark yellow', 'blue'

Examples

• Line plot: py plotme.py -f (path)filename.extension -x columnIndex -y columnIndex
  • The only required argument is the filename
• Scatter plot with differente output name and plot title: py plotme.py -f (path)file.ext -g scatter -pt title -o export
• Bar plot: py plotme.py -f (path)filename.extension
  • The first item in the column is interpreted as the label of the axis, the subsequent itens in that column NEED to be of type int or float
• Pie chart with labels on each slice while using a tab separated input file: py plotme.py -f (path)filename.extension -sep '\t' -pl label,label2,...,labelN
  • The first item in the column is interpreted as the label of the axis, the subsequent itens in that column NEED to be of type int or float
  • Each label corresponds to a single slice in the chart, from 1 to N, every label is assigned a slice following the file order. The number of labels need to be the same as the number of elements in the column.

File Handling

• f:

`python3 plotme.py -f 'name with spaces.csv'`

• ext:

`python3 plotme.py -f dir -y 3-5 -sd -ext txt`

• sp:

`python3 plotme.py -f dir -sp False`

• dp:

`python3 plotme.py -f dir -dp True`

• separator:

`python3 plotme.py -f file.txt -sep \t`
`python3 plotme.py -f file.csv -sep ,`
`python3 plotme.py -f file.csv -sep ' '`

• com:

`python3 plotme.py -f file -com @`

• output:

`python3 plotme.py -f file -o outputFile`
`python3 plotme.py -f file -o .tiff`
`python3 plotme.py -f file -o export.jpeg`

Plot Configuration

• graphType:

`python3 plotme.py -f file -g bar`

• figSize:

`python3 plotme.py -f file -fig 192,108`

• plotTitle:

`python3 plotme.py -f file -pt 'Tile of the plot'`

• fontSize:

`python3 plotme.py -f file -fs 14`

• hideSpine:

`python3 plotme.py -f file -st True`

• symbols:

`python3 plotme.py -f file -y 2,3 -s vH`
`python3 plotme.py -f file -y 2-6 -s vHDdv`
`python3 plotme.py -f file -y 2-6 -s v`

• distBetSymbols:

`python3 plotme.py -f file -d 3`

• symbolSize:

`python3 plotme.py -f file -s v -ss 15`

• lineWidth:

`python3 plotme.py -f file -l 15`

• pieLabel:

`python3 plotme.py -f file -g pie -pl slice1,'another slice',3`

Axis Configuration

• x:

`python3 plotme.py -f file -x 1`

• y:

`python3 plotme.py -f file -y 5-7`
`python3 plotme.py -f file -y 5,6,7`

• xmax:

`python3 plotme.py -f file -xmax 10`

• xmin:

`python3 plotme.py -f file -xmin 10`

• ymax:

`python3 plotme.py -f file -ymax 10`

• ymin:

`python3 plotme.py -f file -ymin 10`

• xLabel:

`python3 plotme.py -f file -xl 'label of x'`

• yLabel:

`python3 plotme.py -f file -yl 'label of y'`

Color Configuration

• setPalette:

`python3 plotme.py -f file -p deep`

• bgColor:

`python3 plotme.py -f file -bgc black`
`python3 plotme.py -f file -bgc '#ff701E'`

• gColor:

`python3 plotme.py -f file '#abc'`

• colors:

`python3 plotme.py -f file -y 2,4 -c yellow,green`
`python3 plotme.py -f file -y 2,4 -c '#ff701E','#abc'`

Miscellaneous

• w:

`python3 plotme.py -f file1 -w 100`
`python3 plotme.py -f file1 file2 file3 [...] -y 2 -sd -w 1000`

• sd:

`python3 plotme.py -f file1 file2 file3 [...] -y 2 -sd`
`python3 plotme.py -f file1 file2 file3 -y 2-4,7 -sd`
`python3 plotme.py -f directory -y 2 -sd`

• auc:

`python3 plotme.py -f file -y 4-6 -auc`
`python3 plotme.py -f file1 file2 file3 [...] -y 3,4 -auc`

• aucm:

`python3 plotme.py -f file -y 4-6 -auc -aucm simpson`
`python3 plotme.py -f file1 file2 file3 [...] -y 3,4 -auc -aucm trapz`

Using it as an imported module

1. After importing, you need to make an instance of the Plot class while passing, at least, the data(the imported version of fileName) argument with the dataframe, the rest of the arguments have the same names as their CLI counterparts.
2. Call the plotGraph() method. The file will be exported as Plot.pdf if no output argument was passed.

Use python3, as well as pip3 to install the dependencies

Dependencies: seaborn, matplotlib, pandas, argparse, re, ast, itertools