tabplot

WORK IN PROGRESS

When working from the terminal, I'd need to quickly (and beautifully) plot the data in csv-style text files. This meant good colors, axis labels, plot labels, adjustable axis limits, etc. I started with making a simple wrapper script around matplotlib to do this. Over time, I kept adding pre- and post-processing functionality such as scaling, normalizing, and linear regression, not to mention exposing more of matplotlib's properties and functions. Since the script kept growing, I decided to move it into its own separate package.

Installation

You can install tabplot via testpypi

pip install git+https://github.com/jayghoshter/tabplot

Check out SciencePlots for added plot beautification.

Examples

Simple line plots

Assuming text data stored in csv-style files with the following assumptions:

No header labels
x,y data in columns 0,1 respectively
Either space or comma separated

The following code will generate basic plots. For customization options please refer to the examples section or test cases.

from tabplot import Plot
plot = Plot()
plot.files = ['./file_1.csv', './file_2.csv'],
plot.linewidths = 2,
plot.labels = ['A', 'B']
plot.read()
plot.draw()
plot.show()
plot.close()

from tabplot import Plot
Plot(
    files = ['./file_1.csv', './file_2.csv'],
    linewidths = 2,
    labels = ['A', 'B']
).read().draw().show().close()

Most used plot properties are exposed directly on the Plot object.
files, twinx, and labels can be specified on Plot or in the read() method
read() loads the data from the given files into .xs and .ys, which can be accessed and manipulated as wished.
setup() creates a .fig and .ax if not already done
draw() plots the lines etc. to the figure
save('file.pdf') will write to file.pdf
show() will display the plotted image

Bar plots

from tabplot import BarPlot
files = ['dummy.csv']
BarPlot(bar_width = 0.5).read(files).draw().save('dummy.pdf').close()

BarPlot is derived from Plot

Notes/Issues

Operator chaining is possible as seen above.
Currently only uses one subplot
Make sure to close the current plot with .close(). Unless garbage collected, plots may linger and calling .show() for some other object may also display a previous unclosed figure.
hlines/vlines must be called after all plots/fit_lines etc are done so that no further changes to xlims, ylims are effected later.
legends don't include hlines
preload-style can affect legend style even if not explicitly specified because we use setrc() in _update_params. So the default value overrides anything given in the style. While this is to be expected, the question is if this is user-friendly or not. Maybe a n otice is sufficient, that --preload-style can have this behavior.
- [TASK] perhaps I can separate out the setrc_defaults() and call it at another time? Or only call it if the user has specified changes to the default values

jayghoshter / tabplot