def get_valid_solutions(states_df: pd.DataFrame, input_graph: list) -> tuple:
"""Get the frequency of valid solution, by summing frequencies of lowest
energy states in the degenrate case, and outputs all valid solutions
found.
:param states_df: dataframe containing the states and energy
:param input_graph: graph defining the problem to be solved
:return: a tuple made of:
- input dataframe with a column added to check if solution is valid
- frequency of solution
- all valid solutions
"""
enriched_states_df = states_df.copy()
enriched_states_df['is_valid'] = False
states_df.groupby(by='state')
lowest_energy = states_df['energy'].min()
lowest_energy_states_df = states_df[states_df['energy'] == lowest_energy]
solutions = []
solution_frequency = 0
for index, row in lowest_energy_states_df.iterrows():
edges_solution = utils.convert_list_of_strings_to_list_of_tuples(
eval(row['state']))
frequency_temp = row['relative_frequency']
is_valid = graph.is_valid(edges_solution, input_graph)
enriched_states_df.loc[enriched_states_df['state'] == row['state'],
'is_valid'] = is_valid
if is_valid:
solution_frequency += frequency_temp
solutions.append(edges_solution)
print(f'number of different solutions: {len(solutions)}')
return enriched_states_df, solution_frequency, solutions
def test_false_cycles_of_length_two_present(self):
edges_input = [(0, 1), (1, 0), (3, 4), (4, 5), (5, 3)]
edges_output = [(0, 1), (1, 0), (3, 4), (4, 5), (5, 3)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is False
def test_false_flow_not_conserved(self):
edges_input = [(0, 1), (1, 2), (3, 4), (4, 5), (5, 3)]
edges_output = [(0, 1), (1, 2), (3, 4), (4, 5), (5, 3)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is False
def test_false_max_one_in_not_respected(self):
edges_input = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3), (3, 0)]
edges_output = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3), (3, 0)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is False
def test_false_not_all_vertices_covered(self):
edges_input = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3), (0, 3)]
edges_output = [(0, 1), (1, 2), (2, 0)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is False
def test_false_no_subset(self):
edges_input = [(0, 1), (1, 2), (2, 0)]
edges_output = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is False
def test_true(self):
edges_input = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3), (0, 3)]
edges_output = [(0, 1), (1, 2), (2, 0), (3, 4), (4, 5), (5, 3)]
actual_is_legit_value = graph.is_valid(edges_output, edges_input)
assert actual_is_legit_value is True