def main_pse(config=Config()):
# -------------------------------Reading data-----------------------------------
reader = Reader()
writer = H5Writer()
head = reader.read_head(config.input.HEAD)
logger = initialize_logger(__name__, config.out.FOLDER_LOGS)
# --------------------------Manual Hypothesis definition-----------------------------------
n_samples = 100
x0_indices = [20]
x0_values = [0.9]
e_indices = [70]
e_values = [0.9]
disease_indices = x0_indices + e_indices
n_disease = len(disease_indices)
n_x0 = len(x0_indices)
n_e = len(e_indices)
all_regions_indices = np.array(range(head.number_of_regions))
healthy_indices = np.delete(all_regions_indices, disease_indices).tolist()
n_healthy = len(healthy_indices)
# This is an example of x0_values mixed Excitability and Epileptogenicity Hypothesis:
hyp_x0_E = HypothesisBuilder(
head.connectivity.number_of_regions).set_x0_hypothesis(
x0_indices,
x0_values).set_e_hypothesis(e_indices,
e_values).build_hypothesis()
# Now running the parameter search analysis:
logger.info("running PSE LSA...")
model_config, lsa_service, lsa_hypothesis, pse_res = pse_from_hypothesis(
hyp_x0_E,
head.connectivity.normalized_weights,
head.connectivity.region_labels,
n_samples,
param_range=0.1,
global_coupling=[{
"indices": all_regions_indices
}],
healthy_regions_parameters=[{
"name": "x0_values",
"indices": healthy_indices
}],
save_services=True)[:4]
logger.info("Plotting LSA...")
Plotter(config).plot_lsa(lsa_hypothesis,
model_config,
lsa_service.weighted_eigenvector_sum,
lsa_service.eigen_vectors_number,
region_labels=head.connectivity.region_labels,
pse_results=pse_res,
lsa_service=lsa_service)
logger.info("Saving LSA results ...")
writer.write_dictionary(
pse_res,
os.path.join(config.out.FOLDER_RES,
lsa_hypothesis.name + "_PSE_LSA_results.h5"))
def main_sensitivity_analysis(config=Config()):
# -------------------------------Reading data-----------------------------------
reader = Reader()
writer = H5Writer()
head = reader.read_head(config.input.HEAD)
# --------------------------Hypothesis definition-----------------------------------
n_samples = 100
# Manual definition of hypothesis...:
x0_indices = [20]
x0_values = [0.9]
e_indices = [70]
e_values = [0.9]
disease_indices = x0_indices + e_indices
n_disease = len(disease_indices)
n_x0 = len(x0_indices)
n_e = len(e_indices)
all_regions_indices = np.array(range(head.connectivity.number_of_regions))
healthy_indices = np.delete(all_regions_indices, disease_indices).tolist()
n_healthy = len(healthy_indices)
# This is an example of x0_values mixed Excitability and Epileptogenicity Hypothesis:
hyp_x0_E = HypothesisBuilder(
head.connectivity.number_of_regions).set_x0_hypothesis(
x0_indices,
x0_values).set_e_hypothesis(e_indices,
e_values).build_hypothesis()
# Now running the sensitivity analysis:
logger.info("running sensitivity analysis PSE LSA...")
for m in METHODS:
try:
model_configuration_builder, model_configuration, lsa_service, lsa_hypothesis, sa_results, pse_results = \
sensitivity_analysis_pse_from_hypothesis(hyp_x0_E,
head.connectivity.normalized_weights,
head.connectivity.region_labels,
n_samples, method=m, param_range=0.1,
global_coupling=[{"indices": all_regions_indices,
"low": 0.0, "high": 2 * K_DEF}],
healthy_regions_parameters=[
{"name": "x0_values", "indices": healthy_indices}],
config=config, save_services=True)
Plotter(config).plot_lsa(
lsa_hypothesis,
model_configuration,
lsa_service.weighted_eigenvector_sum,
lsa_service.eigen_vectors_number,
region_labels=head.connectivity.region_labels,
pse_results=pse_results,
title=m + "_PSE_LSA_overview_" + lsa_hypothesis.name,
lsa_service=lsa_service)
# , show_flag=True, save_flag=False
result_file = os.path.join(
config.out.FOLDER_RES,
m + "_PSE_LSA_results_" + lsa_hypothesis.name + ".h5")
writer.write_dictionary(pse_results, result_file)
result_file = os.path.join(
config.out.FOLDER_RES,
m + "_SA_LSA_results_" + lsa_hypothesis.name + ".h5")
writer.write_dictionary(sa_results, result_file)
except:
logger.warning("Method " + m + " failed!")