You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

65 lines
1.8 KiB

import stormpy
# Check if numpy is available
try:
import numpy as np
numpy_found = True
except ModuleNotFoundError:
numpy_found = False
def example_building_mas_01():
if not numpy_found:
print("Numpy not available")
return
# Building the transition matrix using numpy
transitions = np.array([
[0, 1, 0, 0, 0],
[0.8, 0, 0.2, 0, 0],
[0.9, 0, 0, 0.1, 0],
[0, 0, 0, 0, 1],
[0, 0, 0, 1, 0],
[0, 0, 0, 0, 1]
], dtype='float64')
# Build matrix and define indices of row groups (ascending order)
transition_matrix = stormpy.build_sparse_matrix(transitions, [0, 2, 3, 4, 5])
print(transition_matrix)
# StateLabeling
state_labeling = stormpy.storage.StateLabeling(5)
# Add labels
state_labels = {'init', 'deadlock'}
# Set labeling of states
for label in state_labels:
state_labeling.add_label(label)
state_labeling.add_label_to_state('init', 0)
# Choice labeling
choice_labeling = stormpy.storage.ChoiceLabeling(6)
# Add labels
choice_labels = {'alpha', 'beta'}
# Set labeling of choices
for label in choice_labels:
choice_labeling.add_label(label)
choice_labeling.add_label_to_choice('alpha', 0)
choice_labeling.add_label_to_choice('beta', 1)
exit_rates = [0.0, 10.0, 12.0, 1.0, 1.0]
markovian_states = stormpy.BitVector(5, [1, 2, 3, 4])
# Collect components
components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling,
markovian_states=markovian_states)
components.choice_labeling = choice_labeling
components.exit_rates = exit_rates
# Build the model
ma = stormpy.storage.SparseMA(components)
print(ma)
if __name__ == '__main__':
example_building_mas_01()