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SainsburyWellcomeCentre · Jul 20, 2023 · d82031a · d82031a
1 parent 9b90af1
commit d82031a
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diff --git a/examples/comparisons_examples/Comparision_from_manadger.ipynb b/examples/comparisons_examples/Comparision_from_manadger.ipynb
diff --git a/neuralplayground/backend/default_simulation.py b/neuralplayground/backend/default_simulation.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 from neuralplayground.agents import Stachenfeld2018, Weber2018
-from neuralplayground.arenas import MergingRoom, Sargolini2006, Simple2D, Wernle2018
+from neuralplayground.arenas import Hafting2008, MergingRoom, Sargolini2006, Simple2D, Wernle2018
 from neuralplayground.backend import default_training_loop, episode_based_training_loop
 
 from .cross_comparison import SingleSim
@@ -89,7 +89,13 @@
 }
 
 sim4_params = {
-    "simulation_id": "weber_2018_in_Wernle",
+    "simulation_id": "weber_2018_in_Sargolini2006",
+    "env_class": Sargolini2006,
+    "env_params": {
+        "use_behavioral_data": True,
+        "time_step_size": 0.1,
+        "agent_step_size": None,
+    },
     "agent_class": Weber2018,
     "agent_params": {
         "exc_eta": 2e-4,
@@ -108,17 +114,39 @@
         "agent_step_size": 0.1,
         "resolution": 100,
         "ro": 1,
-        "room_width": 200.0,
-        "room_depth": 200.0,
+        "room_width": 100,
+        "room_depth": 100,
         "disable_tqdm": True,
     },
-    "env_class": Wernle2018,
-    "env_params": {"merge_time": 20, "switch_time": 10, "time_step_size": 0.2, "agent_step_size": 3},
     "training_loop": default_training_loop,
     "training_loop_params": {"n_steps": 1000},
 }
+
+
 sim5_params = {
-    "simulation_id": "weber_2018_in_Haftinglike",
+    "simulation_id": "stachenfeld_2018_in_Hafting2008",
+    "agent_class": Stachenfeld2018,
+    "env_class": Hafting2008,
+    "env_params": {
+        "use_behavioral_data": True,
+        "time_step_size": 0.1,
+        "agent_step_size": None,
+    },
+    "agent_params": {
+        "discount": 0.9,
+        "threshold": 1e-6,
+        "lr_td": 1e-2,
+        "state_density": 1,
+        "room_width": 20.0,
+        "room_depth": 2,
+        "twoD": True,
+    },
+    "training_loop": episode_based_training_loop,
+    "training_loop_params": {"t_episode": 100, "n_episode": 100},
+}
+
+sim6_params = {
+    "simulation_id": "weber_2018_in_Hafting2008",
     "agent_class": Weber2018,
     "agent_params": {
         "exc_eta": 2e-4,
@@ -141,20 +169,18 @@
         "room_depth": 2,
         "disable_tqdm": True,
     },
-    "env_class": Simple2D,
+    "env_class": Hafting2008,
     "env_params": {
-        "arena_x_limits": np.array([-10, 10]),
-        "arena_y_limits": np.array([-1.0, 1.0]),
-        "env_name": "hafting_like",
-        "time_step_size": 1,
-        "agent_step_size": 0.5,
+        "use_behavioral_data": True,
+        "time_step_size": 0.1,
+        "agent_step_size": None,
     },
     "training_loop": default_training_loop,
     "training_loop_params": {"n_steps": 1000},
 }
 
-sim6_params = {
-    "simulation_id": "weber_2018_in_Merging_Room",
+sim7_params = {
+    "simulation_id": "weber_2018_in_Wernle",
     "agent_class": Weber2018,
     "agent_params": {
         "exc_eta": 2e-4,
@@ -173,32 +199,19 @@
         "agent_step_size": 0.1,
         "resolution": 100,
         "ro": 1,
-        "room_width": 20.0,
-        "room_depth": 20.0,
+        "room_width": 200.0,
+        "room_depth": 200.0,
         "disable_tqdm": True,
     },
-    "env_class": MergingRoom,
-    "env_params": {
-        "arena_x_limits": [-10, 10],
-        "arena_y_limits": [-10, 10],
-        "time_step_size": 0.2,
-        "agent_step_size": 10,
-        "merge_time": 270.0,
-        "switch_time": 270.0,
-    },
+    "env_class": Wernle2018,
+    "env_params": {"merge_time": 20, "switch_time": 10, "time_step_size": 0.2, "agent_step_size": 3},
     "training_loop": default_training_loop,
     "training_loop_params": {"n_steps": 1000},
 }
 
 
-sim7_params = {
-    "simulation_id": "weber_2018_in_Sargolini2006",
-    "env_class": Sargolini2006,
-    "env_params": {
-        "use_behavioral_data": True,
-        "time_step_size": 0.1,
-        "agent_step_size": None,
-    },
+sim8_params = {
+    "simulation_id": "weber_2018_in_Merging_Room",
     "agent_class": Weber2018,
     "agent_params": {
         "exc_eta": 2e-4,
@@ -217,10 +230,19 @@
         "agent_step_size": 0.1,
         "resolution": 100,
         "ro": 1,
-        "room_width": 100,
-        "room_depth": 100,
+        "room_width": 20.0,
+        "room_depth": 20.0,
         "disable_tqdm": True,
     },
+    "env_class": MergingRoom,
+    "env_params": {
+        "arena_x_limits": [-10, 10],
+        "arena_y_limits": [-10, 10],
+        "time_step_size": 0.2,
+        "agent_step_size": 10,
+        "merge_time": 270.0,
+        "switch_time": 270.0,
+    },
     "training_loop": default_training_loop,
     "training_loop_params": {"n_steps": 1000},
 }
@@ -234,3 +256,4 @@
 sim_object5 = SingleSim(**sim5_params)
 sim_object6 = SingleSim(**sim6_params)
 sim_object7 = SingleSim(**sim7_params)
+sim_object8 = SingleSim(**sim8_params)
diff --git a/neuralplayground/plotting/plot_utils.py b/neuralplayground/plotting/plot_utils.py
@@ -261,7 +261,7 @@ def make_agent_comparison(envs, parameters, agents, exps=None, recording_index=N
         for m, exp in enumerate(exps):
             if exp is not None:
                 ax[0, i + k + m + 2].text(0, 1.1, exp.experiment_name, fontsize=config_vars.FONTSIZE)
-                render_mpl_table(exp.show_data(), ax=ax[0, i + k + m + 2])
+                render_mpl_table(exp.recording_list, ax=ax[0, i + k + m + 2])
                 exp.plot_recording_tetr(recording_index=recording_index, tetrode_id=tetrode_id, ax=ax[1][i + k + m + 2])
                 r_out_im, x_bin, y_bin = exp.recording_tetr()
                 GridScorer_SR = GridScorer(x_bin - 1)