Generate Random Attribute

This operation augments a feature model with a randomly generated numeric attribute attached to its features. It is useful for creating attributed feature models on which to exercise attribute-based analyses (for example optimization or feature bounds) when the original model has no attributes.

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Code Examples

from flamapy.metamodels.fm_metamodel.transformations import UVLReader
from flamapy.metamodels.fm_metamodel.operations import GenerateRandomAttribute

feature_model = UVLReader('model.uvl').transform()
model_with_attribute = GenerateRandomAttribute().execute(feature_model).get_result()

Or, more simply, through the facade (values are drawn from the [min_value, max_value] range):

from flamapy.interfaces.python.flamapy_feature_model import FLAMAFeatureModel

fm = FLAMAFeatureModel('model.uvl')
model_with_attribute = fm.generate_random_attribute('cost', min_value=0, max_value=100)