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Fix "intprim.util.gaussian" and "debug" related problems #3

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Fix "intprim.util.gaussian" and "debug" related problems #3

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12 changes: 6 additions & 6 deletions scripts/intprim_service.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
import intprim.basis.polynomial_model
import intprim.basis.sigmoidal_model
import intprim.basis.selection
import intprim.util.gaussian
# import intprim.util.gaussian
import intprim_framework_ros.msg
import intprim_framework_ros.srv
import itertools
Expand Down Expand Up @@ -675,7 +675,7 @@ def get_statistics_callback(self, request):
self.statistics_publisher.publish(message)

# Export debugging XML file here.
if(self.bip_parameters[0]["debug"]):
if(self.bip_parameters[request.interaction_id]["debug"]):
self.stat_collector.export(self.bip_instances[request.interaction_id], self.bip_parameters[request.interaction_id]["debug_directory"], request.bag_file, self.bip_parameters[request.interaction_id]["num_samples"])

# Return values as part of service call as well
Expand Down Expand Up @@ -708,11 +708,11 @@ def initialize_state_callback(self, request):
self.initialize_state()

# Initialize stat collection for debugging
if(self.bip_parameters[0]["debug"]):
self.stat_collector = analysis.stat_collector.StatCollector(self.bip_instances[0], self.bip_parameters[0]["generate_indices"], np.setdiff1d(self.bip_parameters[0]["all_active_dofs"], self.bip_parameters[0]["generate_indices"]))
if(self.bip_parameters[self.primary_instance]["debug"]):
self.stat_collector = analysis.stat_collector.StatCollector(self.bip_instances[self.primary_instance], self.bip_parameters[self.primary_instance]["generate_indices"], np.setdiff1d(self.bip_parameters[self.primary_instance]["all_active_dofs"], self.bip_parameters[self.primary_instance]["generate_indices"]))

generated_trajectory = self.bip_instances[0].get_mean_trajectory(num_samples = self.bip_parameters[0]["num_samples"])
self.stat_collector.collect(self.bip_instances[0], np.array([[] for _ in range(generated_trajectory.shape[0])]), generated_trajectory.T, None)
generated_trajectory = self.bip_instances[self.primary_instance].get_mean_trajectory(num_samples = self.bip_parameters[self.primary_instance]["num_samples"])
self.stat_collector.collect(self.bip_instances[self.primary_instance], np.array([[] for _ in range(generated_trajectory.shape[0])]), generated_trajectory.T, None)

return intprim_framework_ros.srv.InitializeStateResponse(True)

Expand Down