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

Project description

Installation

You can install iggy by running:

$ pip install --user iggy

On Linux the executable scripts can then be found in ~/.local/bin

and on MacOS the scripts are under /Users/YOURUSERNAME/Library/Python/3.2/bin.

Usage

Typical usage is:

$ iggy.py network.sif observation.obs --show_labelings 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_labelings SHOW_LABELINGS]
       [--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_labelings SHOW_LABELINGS
                        number of labelings 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: demo_data.tar.gz

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