making the expert demonstration processor go through all agents in order when producing a single (default) trajectory file, using a randomized agent environment in optionsgail, starting function to process and store all expert data

scratch/arec/intersimple/data/process_all_experts.py

@@ -0,0 +1,40 @@
+import tqdm
+import expert
+import copy
+import sys, os
+
+def process_all_experts(env_args={}, policy_args={}):
+    """
+    Process all experts in the Interaction Dataset
+    For now, using NormalizedIntersimpleExpert with NRasterizedIncrementingAgent environment
+
+    Args:
+        env_args (dict): default environment kwargs
+        policy_args (dict): default policy kwargs
+    """
+
+    for loc in LOCATIONS:
+        for track in TRACKS:
+            
+            it_env_args = copy.deepcopy(env_args)
+            it_env_args.update({
+                'loc':loc,
+                'track':track,
+            })
+
+            it_path = 'newpathname'
+
+            expert.demonstrations(
+                expert='NormalizedIntersimpleExpert', 
+                env='NRasterizedIncrementingAgent', 
+                path=it_path, 
+                env_args=it_env_args, 
+                policy_args=policy_args,
+                )
+    
+
+if __name__=='__main__':
+    import fire
+    fire.Fire(process_all_experts)
+
+