The source code and dockerfile for the GSW2024 AI Lab.
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import stormpy
# Check if numpy is available
try:
import numpy as np
numpy_found = True
except ModuleNotFoundError:
numpy_found = False
def example_building_ctmcs_01():
if not numpy_found:
print("Numpy not available")
return
# Building the transition matrix using numpy
transitions = np.array([
[0, 1.5, 0, 0],
[3, 0, 1.5, 0],
[0, 3, 0, 1.5],
[0, 0, 3, 0], ], dtype='float64')
# Default row groups: [0,1,2,3]
transition_matrix = stormpy.build_sparse_matrix(transitions)
print(transition_matrix)
# State labeling
state_labeling = stormpy.storage.StateLabeling(4)
state_labels = {'empty', 'init', 'deadlock', 'full'}
for label in state_labels:
state_labeling.add_label(label)
# Adding label to states
state_labeling.add_label_to_state('init', 0)
state_labeling.add_label_to_state('empty', 0)
state_labeling.add_label_to_state('full', 3)
# Exit rate for each state
exit_rates = [1.5, 4.5, 4.5, 3.0]
# Collect components
# rate_transitions = True, because the transition values are interpreted as rates
components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, rate_transitions=True)
components.exit_rates = exit_rates
# Build the model
ctmc = stormpy.storage.SparseCtmc(components)
print(ctmc)
if __name__ == '__main__':
example_building_ctmcs_01()