lysis-curve 1.0.1

Lysis curve package

Lysis-curve

This package generates automated lysis curves (bacterial growth curves) for biological research via Plotly and utilizes code for automated grouping, titles, annotations and subplotting within a single custom graphing function.

Simply changing the function arguments can generate a variety of bacterial growth curves.

The graphs are dynamic when generated within a webpage (i.e. Jupyter) which can be useful when teasing apart data.

For a very similar package which generates non-dynamic but prettier bacterial growth curves / lysis curves using R rather than Python, see Cody Martin's lysis_curves package.

Install Package Using PyPi

At the command line, run

pip install lysis-curve

Running (in Jupyter or at command line)

First, make sure your x-axis (time) data is your zeroth (first) column (this script always plots the first column in the csv file as the x-axis). Next, make sure you save your data in the .csv file format.

Next, navigate to the directory containing your .csv file in Jupyter.

import os
os.chdir('your_path_here')

Next, import the lysis_curve.py file using

from lysis_curve import lysis_curve

Alternatively, copy/paste the file into a jupyter cell from github and you can modify the code yourself.

Generate basic plot

from lysis_curve import lysis_curve

lysis_curve('yourcsvfile.csv')

Generate plot with grouping

This argument is useful if you wish to visually group your data by color. It automatically sets each line in each group the same color, but assigns them different markers. Does not work with subplots. Pass the argument to group as a list of strings, with each column in a group separated by vertical bars.

lysis_curve('122120JSC.csv',
           title='Title Goes Here',
           group = ['1', '4','3|5'],
           annotate=True)

Generate plot with annotations

Use the argument annotations=True and follow the prompts.

Generate plot with subplots

Use the argument subplots=True to split your data into subplots.

lysis_curve('051321JSC.csv',
           title='Title Goes Here',
           subplots=True)

Generate plot with custom title

Use the argument title='Your Custom Title Here' By default, the title will be taken from your csv file name - thus 'yourcsvfile' if 'yourcsvfile.csv' is passed.

Pass custom colors

lysis_curve('yourcsvfile.csv', colors=['red', 'blue', 'blah'])

Save as .png

Set the argument png=True and the function will generate a .png file of the graph in your current directory.

Save as .svg

Set the argument svg=True and the function will generate a .svg file of the graph in your current directory. Requires Kaleido or Orca

Save .png, .svg and legendless .svg

save=True Saves three versions of the graph: (1) a .png version with a legend (2) a .svg version with a legend (3) a .svg version without a legend and square dimensions

Dependencies

• Python 3.5+
• Pandas pip install pandas
• Plotly pip install plotly
• Requests pip install requests
• Kaleido pip install kaleido (Kaleido is recommended over Orca according to Plotly)