def get_swarm_informations_from_file(filename,
informations_grep,
information_map=float,
**kargs):
_, informations = SwarmParser.read_files_and_measures(
[('', filename)],
informations_grep=informations_grep,
information_map=information_map,
**kargs)
informations = informations[''][-1] # there is no window here!
# let's get the longest information sequence
max_information_length = float("-inf")
max_information_key = None
for information_grep in informations:
if len(informations[information_grep]) > max_information_length:
max_information_length = len(informations[information_grep])
max_information_key = information_grep
iterations = [
iteration for (iteration, _) in informations[max_information_key]
]
iterations.sort()
df = pd.DataFrame({'x': iterations})
for information_grep in informations:
dict_information = dict(informations[information_grep])
df[information_grep] = [
dict_information[i] if i in dict_information else float("nan")
for i in iterations
]
return df
def get_graph_matrices_from_files(filenames,
influence_graph_grep='ig\:#',
**kargs):
pos_callback = Callback.to_symmetric
graph_matrices, _ = SwarmParser.read_files_and_measures(
filenames,
influence_graph_grep=influence_graph_grep,
pos_callback=pos_callback,
**kargs)
return graph_matrices