From 16c58bfcf5c2af5f923c7214734f665352511f8b Mon Sep 17 00:00:00 2001
From: Antonio Andriella <aandriella@iri.upc.edu>
Date: Wed, 23 Sep 2020 14:20:21 +0200
Subject: [PATCH] Add function to update the bn model loading a folder
---
bn_functions.py | 55 ++++++++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 54 insertions(+), 1 deletion(-)
diff --git a/bn_functions.py b/bn_functions.py
index 5137463..4bcf5f3 100644
--- a/bn_functions.py
+++ b/bn_functions.py
@@ -1,6 +1,8 @@
import bnlearn
import numpy as np
import random
+import os
+import utils
'''Father class in which the basic functionalities to call the bnlearn library are developed
This class can be used to implement individual Persona simulator or just generative models starting from
@@ -23,6 +25,7 @@ def get_cpdf(dag_cpds, variable):
return index, (cpds_table[index].values)
break
index += 1
+ return None, None
def compute_prob(cpds_table):
'''
@@ -127,7 +130,7 @@ def get_stochastic_action(actions_distr_prob):
Return the index of the most closest value in values to target
Args:
target: the target value
- values: a list of values from 0 to 1
+ values: a list of values from 0 to 1a
Return:
return the index of the value closer to target
'''
@@ -213,3 +216,53 @@ def interpret_action_output(action_id, col, row, targets):
print("robot_feed ", robot_assistance, 'robot_ass ', robot_feedback)
return robot_assistance, robot_feedback
+def update_episodes_batch(bn_model_user_action, bn_model_user_react_time,
+ bn_model_agent_assistance, bn_model_agent_feedback,
+ folder_filename, with_caregiver=True, with_feedback=True):
+ bn_belief_user_action_file = "bn_belief_user_action.pkl"
+ bn_belief_user_react_time_file = "bn_belief_user_react_time.pkl"
+ bn_belief_agent_assistance_file = ""; bn_belief_agent_feedback_file = "";
+ if with_caregiver and with_feedback:
+ bn_belief_agent_assistance_file = "bn_belief_caregiver_assistive_action.pkl"
+ bn_belief_agent_feedback_file = "bn_belief_caregiver_feedback_action.pkl"
+ elif with_caregiver and not with_feedback:
+ bn_belief_agent_assistance_file = "bn_belief_caregiver_assistive_action.pkl"
+ bn_belief_agent_feedback_file = ""
+ elif not with_caregiver and with_feedback:
+ bn_belief_agent_assistance_file = "bn_belief_robot_assistive_action.pkl"
+ bn_belief_agent_feedback_file = ""
+ else:
+ bn_belief_agent_assistance_file = "bn_belief_robot_assistive_action.pkl"
+ bn_belief_agent_feedback_file = "bn_belief_robot_feedback_action.pkl"
+
+ #check if the folder is empty
+ dir = os.listdir(path=folder_filename)
+ if dir==[]:
+ assert "Folder is empty"
+ return
+ else:
+ dir_list = next(os.walk(folder_filename))[1]
+ for sub_folder in dir_list:
+ #read the files in it (we already know their name)
+ bn_belief_user_action = utils.read_user_statistics_from_pickle(folder_filename+"/"+sub_folder+"/"+bn_belief_user_action_file)
+ bn_belief_user_react_time = utils.read_user_statistics_from_pickle(folder_filename+"/"+sub_folder+"/"+bn_belief_user_react_time_file)
+ bn_belief_agent_assistance = utils.read_user_statistics_from_pickle(folder_filename+"/"+sub_folder+"/"+bn_belief_agent_assistance_file)
+ bn_belief_agent_feedback = utils.read_user_statistics_from_pickle(folder_filename+"/"+sub_folder+"/"+bn_belief_agent_feedback_file)
+ bn_model_user_action = update_cpds_tables(bn_model=bn_model_user_action,
+ variables_tables=bn_belief_user_action)
+ bn_model_user_react_time = update_cpds_tables(bn_model=bn_model_user_react_time,
+ variables_tables=bn_belief_user_react_time)
+ bn_model_agent_assistance = update_cpds_tables(bn_model=bn_model_agent_assistance,
+ variables_tables=bn_belief_agent_assistance)
+ bn_model_agent_feedback = update_cpds_tables(bn_model=bn_model_agent_feedback,
+ variables_tables=bn_belief_agent_feedback)
+ #return the 4 models
+ return bn_model_user_action, bn_model_user_react_time, bn_model_agent_assistance, bn_model_agent_feedback
+
+# bn_model_caregiver_assistance = bnlearn.import_DAG('bn_agent_model/agent_assistive_model.bif')
+# bn_model_caregiver_feedback = bnlearn.import_DAG('bn_agent_model/agent_feedback_model.bif')
+# bn_model_user_action = bnlearn.import_DAG('bn_persona_model/user_action_model.bif')
+# bn_model_user_react_time = bnlearn.import_DAG('bn_persona_model/user_react_time_model.bif')
+# update_episodes_batch(bn_model_user_action, bn_model_user_react_time, bn_model_caregiver_assistance,
+# bn_model_caregiver_feedback, folder_filename="/home/pal/carf_ws/src/carf/caregiver_in_the_loop/log/0/")
+
--
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