Skip to main content

A tool for consistency based analysis of influence graphs and observed systems behavio.

Project description

Installation
============


You can install iggy by running::

$ pip install --user iggy

The executable scripts can then be found in ~/.local/bin.


Usage
-----

Typical usage is::

$ iggy.py network.sif observation.obs --show_colorings 10 --show_predictions

For more options you can ask for help as follows::

$ iggy.py -h
usage: iggy.py [-h] [--no_zero_constraints]
[--propagate_unambigious_influences] [--no_founded_constraint]
[--autoinputs] [--scenfit] [--show_colorings SHOW_COLORINGS]
[--show_predictions]
networkfile observationfile

positional arguments:
networkfile influence graph in SIF format
observationfile observations in bioquali format

optional arguments:
-h, --help show this help message and exit
--no_zero_constraints
turn constraints on zero variations OFF, default is ON
--propagate_unambigious_influences
turn constraints ON that if all predecessor of a node
have the same influence this must have an effect,
default is ON
--no_founded_constraint
turn constraints OFF that every variation must be
explained by an input, default is ON
--autoinputs compute possible inputs of the network (nodes with
indegree 0)
--scenfit compute scenfit of the data, default is mcos
--show_colorings SHOW_COLORINGS
number of colorings to print, default is OFF, 0=all
--show_predictions show predictions


The second script contained is opt_graph.py
Typical usage is::

$ opt_graph.py network.sif observations_dir/ --show_repairs 10

For more options you can ask for help as follows::

$ opt_graph.py -h
usage: opt_graph.py [-h] [--no_zero_constraints]
[--propagate_unambigious_influences]
[--no_founded_constraint] [--autoinputs]
[--show_repairs SHOW_REPAIRS] [--opt_graph]
networkfile observationfiles

positional arguments:
networkfile influence graph in SIF format
observationfiles directory of observations in bioquali format

optional arguments:
-h, --help show this help message and exit
--no_zero_constraints
turn constraints on zero variations OFF, default is ON
--propagate_unambigious_influences
turn constraints ON that if all predecessor of a node
have the same influence this must have an effect,
default is ON
--no_founded_constraint
turn constraints OFF that every variation must be
explained by an input, default is ON
--autoinputs compute possible inputs of the network (nodes with
indegree 0)
--show_repairs SHOW_REPAIRS
number of repairs to show, default is OFF, 0=all
--opt_graph compute opt-graph repairs (allows also adding edges),
default is only removing edges


Samples
=======

Sample files available here:: iggy_demo_data.tar.gz_

.. _iggy_demo_data.tar.gz: http://www.cs.uni-potsdam.de/~sthiele/bioasp/downloads/samples/iggy_demo_data.tar.gz

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iggy-0.3.tar.gz (401.1 kB view details)

Uploaded Source

File details

Details for the file iggy-0.3.tar.gz.

File metadata

  • Download URL: iggy-0.3.tar.gz
  • Upload date:
  • Size: 401.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for iggy-0.3.tar.gz
Algorithm Hash digest
SHA256 4658b0c3f2be0ba46055ed5e3554dd031d7bb5c5d814508950ab27fccc4fc857
MD5 3a086f9b7066f8417cc31820acc12e26
BLAKE2b-256 6f887711b793bbcf11dc846154b3a70a5ca7cb2d10760b550eb26f928bd3374a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page