explore_network.py

# pip install biodivine_aeon

from biodivine_aeon import *
from pathlib import Path
import sys

model_string = Path(sys.argv[1]).read_text()

# Parse `model_string` as `.aeon` model file.
bn = BooleanNetwork.from_aeon(model_string)

# Get the underlying `RegulatoryGraph` of the `BooleanNetwork`.
# (Some basic functions are implemented for both BN and RG, but 
#  some more specific stuff is only available for the RG object)
rg = bn.graph()

# Note that we have a "VariableId" and "ParameterId" (parameter=uninterpreted function)
# objects that identify variables/parameters (this is mostly a technicality from 
# Rust, where using string names for everything would likely perform poorly). Typically, when 
# the API returns a variable, it returns it as a "VariableId". However, all Python
# functions that take a variable will also accept a string name. So if you have a known or
# fixed network, you can mostly use names as well as IDs.

# List all regulations in a file, grouped by the target variable:
for target in rg.variables():
	print(" > Regulations targeting", rg.get_variable_name(target))
	for regulator in rg.regulators(target):
		print("    > ", rg.get_variable_name(regulator), "regulates", rg.get_variable_name(target))
		regulation = rg.find_regulation(regulator, target)

		# 'activation' / 'inhibition' / None
		print("        > Monotonicity:", regulation['monotonicity'])
		# True/False
		print("        > Essential:", regulation['observable'])

# Also can list regulations grouped by regulator variable using `rg.targets(regulator)`.
# Or simply go through all regulation objects in arbitrary order using `rg.regulations()`.


# List all update functions.
for variable in bn.variables():
	# A string representing the function, or None if the function is undefined.
	function = bn.get_update_function(variable)	
	print("Function of", rg.get_variable_name(variable), "is:", function)

# List all named uninterpreted functions in the model. 
# (completely unknown update functions are not included - only the ones that 
#  explicitly appear as part of a larger function expression)
for parameter in bn.parameters():
	print("Uninterpreted function", bn.get_parameter_name(parameter), "has arity", bn.get_parameter_arity(parameter))