isnalyser 0.1.0

Create isnad graphs automatically.

Automated isnād tree visualisations

For scholars studying Ḥadīth texts, drawing an isnād tree with more than 40 transmitters is a tidious work and finding the right medium to desplay it fully can even prove to be impossible. The isnalyser is a simple program for the automation of isnād trees drawing and their customable display in handy formats.

The motivation behind the project

The isnalyser aims at facilitating the analysis of large quantity of aḥādīth and more specifically their chains of transmiters or asānid by allowing scholars to visualise these chains of transmitters quickly in a complete graph that includes geo-spatial and chronological information.

Who is it for?

The isnalyser is open-source and publicly available. It is meant for scholars in Ḥadīth studies who are analysing a great number of aḥādīth and need to visualise their chains of transmitters in a single graph. The program can also be used by any scholars in Islamic studies or else who want to visualise the transmission of a text or its recension history. All data that follows the pattern of numerous chains of transmitters/scribes/citations/etc. can serve as input for the present program.

How?

Isnalyser can be installed easily and is ready to use within seconds.

Installation

pip install isnalyser

Usage

• A nice function of isnalyser is view_graph. Let's import it!

from isnalyser import view_graph

• Now, if you already have some data available that you want to display as an Isnad tree, you can use the function we just imported like so:

view_graph(
	'/path/to/your/data/transmitters.csv', # path to transmitters file
	'/path/to/your/data/transmissions.csv', # path to transmissions file
	15) # step size of timeline

• If you don't have any data yet, or just want to get a feel for it, we provided some examples. By looking at them, you can also find out how the data needs to be structured for isnalyser to work.

view_graph(
	'', # you can write anyting here, as we don't need it
	'', # same is true here
	15, # 15 is a good step size for the example
	use_example=True) # use example data

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.