lysis-curve 0.1

Lysis curve package

lysis_curve.py (deprecated)

This function generates automated lysis curves (OD curves) for bacteriophage research via plotly. It can also split a spaghetti lineplot into up to 9 subplots.

lysis_curve_pub.py

This variant generates automated OD curves with modifications with a more professional (less Plotly) styling more suitable for publication. Dynamic interaction with the plots is sometimes buggy due to an issue on Plotly's end.

Running in Jupyter

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

import os
os.chdir('your_path_here')

Next, import the lysis_curve.py file or just copy/paste it into a jupyter cell and execute.

Generate basic plot

This basic plot is good for cases where you do not wish to visually group your data

lysis_curve('yourcsvfile.csv')

Generate plot with subplots

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

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('yourcsvfile.csv', group=['1', '2|3', '4|5', '6|7|8'])

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.

Generate plot with annotations

Use the argument annotations=True and follow the prompts.

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)