svgdigitizer 0.1.0

svgdigitizer is a Python library and command line tool to recover the measured data underlying plots in scientific publications.

SVGDigitizer — (x,y) Data Points from SVG files

The purpose of this project is to digitize plots in scientific publications, recovering the measured data visualized in such a plot.

Installation

pip install -e .

Command Line Interface

There's a simple command line interface.

$ svgdigitizer
Usage: svgdigitizer [OPTIONS] COMMAND [ARGS]...
  The svgdigitizer suite.
Options:
  --help  Show this message and exit.
Commands:
  cv        Digitize a cylic voltammogram.
  digitize  Digitize a plot.
  paginate  Render PDF pages as individual SVG files with linked PNG images.
  plot      Display a plot of the data traced in an SVG.

$ svgdigitizer plot test/data/xy.svg  # byexample: +skip
[displays a plot]

$ svgdigitizer digitize test/data/xy.svg
$ head test/data/xy.csv
x,y
-0.16009930563414798,-0.1986285897538036
-0.15992739743885453,-0.1957901668705444
-0.1597554892435611,-0.19295174398728543
-0.15958358104826764,-0.19011347237363185
-0.1594116728529742,-0.18727504949037288
-0.15923976465768075,-0.1844366266071139
-0.1590678564623873,-0.18159820372385482
-0.15889594826709386,-0.17875993211020125
-0.1587240400718004,-0.17592150922694227

$ svgdigitizer paginate test/data/mustermann_2021_svgdigitizer_1.pdf
$ ls test/data/mustermann_*
test/data/mustermann_2021_svgdigitizer_1.pdf
test/data/mustermann_2021_svgdigitizer_1_p0.png
test/data/mustermann_2021_svgdigitizer_1_p0.svg
test/data/mustermann_2021_svgdigitizer_1_p1.png
test/data/mustermann_2021_svgdigitizer_1_p1.svg
test/data/mustermann_2021_svgdigitizer_1_p2.png
test/data/mustermann_2021_svgdigitizer_1_p2.svg
test/data/mustermann_2021_svgdigitizer_1_p3.png
test/data/mustermann_2021_svgdigitizer_1_p3.svg

$ svgdigitizer cv doc/files/mustermann_2021_svgdigitizer_1/mustermann_2021_svgdigitizer_1_p1_2a_blue.svg
$ head doc/files/mustermann_2021_svgdigitizer_1/mustermann_2021_svgdigitizer_1_p1_2a_blue.csv
t,U,j
0.0,-0.0960124785649914,-2.080260291844327
0.7905675531192768,-0.05648410090902756,-1.0308948282866481
2.248602982368486,0.016417670553432906,-0.16935125824021272
3.987638717224935,0.10336945729625535,0.1323211424212127
5.432216587072722,0.17559835078864472,0.8935782484922993
6.137505185508352,0.2108627807104262,1.1030689590733505
7.034812039233036,0.2557281233966604,0.594205898184805
7.6578480240944335,0.2868799226397303,0.36151217639411015
8.628013087315537,0.3353881758007855,0.25379596409161875

API

You can also use the svgdigitizer package directly from Python.

The examples are based on the test files provided with svgdigitizer in the folder test/data.

>>> from svgdigitizer.svgplot import SVGPlot
>>> from svgdigitizer.svg import SVG

>>> svgplot = SVGPlot(SVG(open('test/data/xy_rate.svg', 'rb')))

svgplot.df provides a dataframe of the digitized curve. svgplot.plot() shows a plot of the digitized curve.

Submodule CV

The submodule electrochemistry.cv is specifically designed to digitize cyclic voltamograms commonly found in the field of electrochemistry.

>>> from svgdigitizer.svgplot import SVGPlot
>>> from svgdigitizer.svg import SVG
>>> from svgdigitizer.electrochemistry.cv import CV

>>> cv = CV(SVGPlot(SVG(open('test/data/xy_rate.svg', 'rb'))))

cv.df provides a dataframe with a time, voltage and current axis (in SI units). Depending on the type of data the current is expressed as current I in A or a current density j in A / m2.

The dataframe can for example be saved as csv via:

from pathlib import Path
cv.df.to_csv(Path(svgfile).with_suffix('.csv'), index=False)

cv.plot() shows a plot of the digitizd data with appropriate axis labels. cv.metadadata provides a dict with metadata of the original plot, such as original units of the axis.

CV also accepts a dict with metadata, which is updated with keywords related to the original figure (figure descripton), i.e., original axis units.

>>> import yaml
>>> from svgdigitizer.svgplot import SVGPlot
>>> from svgdigitizer.svg import SVG
>>> from svgdigitizer.electrochemistry.cv import CV

>>> with open('test/data/xy_rate.yaml') as f:
...    metadata = yaml.load(f, Loader=yaml.SafeLoader)

>>> cv = CV(SVGPlot(SVG(open('test/data/xy_rate.svg', 'rb'))), metadata=metadata)