def predict(self, num_iterations: int) -> Results:
# TODO "method" rst
# TODO replace num_activation by proper test
"""
Parameters
----------
num_iterations : int
Discrete number of prediction iteration steps to perform by :method:predict method
Returns
-------
Results
Object containing results from all predication iterations.
"""
global num_activations
num_activations = 0
result = Results()
self.adjacency.transposed()
self.newly_activated_ = np.where(self.state_matrix_.matrix)
for l in range(num_iterations):
result.add_result(self.__single_iteration())
# print(num_activations)
return result
def save_results(result: Results, dir, num_predictions):
for iter in range(num_predictions):
matrix = result.get_result(iter).matrix
file_name = dir + '/result_' + str(iter) + '.pickle'
os.makedirs(os.path.dirname(file_name), exist_ok=True)
with open(file_name, 'wb') as file:
pickle.dump(matrix, file)
def save_results(result: Results, dir, num_predictions):
for iter in range(num_predictions):
matrix = result.get_result(iter).matrix
file_name = dir + 'result_' + str(iter) + '.pickle'
with open(file_name, 'wb') as file:
pickle.dump(matrix, file)