More comments and output

fire_evacuation/server.py

@@ -8,6 +8,7 @@
 from .agent import FireExit, Wall, Furniture, Fire, Smoke, Human, Sight, Door, DeadHuman
 
 
+# Creates a visual portrayal of our model in the browser interface
 def fire_evacuation_portrayal(agent):
     if agent is None:
         return
@@ -66,9 +67,10 @@ def fire_evacuation_portrayal(agent):
     return portrayal
 
 
-# Was hoping floorplan could dictate the size of the grid, but seems the grid needs to be specified first :/
+# Was hoping floorplan could dictate the size of the grid, but seems the grid needs to be specified first, so the size is fixed to 50x50
 canvas_element = CanvasGrid(fire_evacuation_portrayal, 50, 50, 800, 800)
 
+# Define the charts on our web interface visualisation
 status_chart = ChartModule([{"Label": "Alive", "Color": "blue"},
                             {"Label": "Dead", "Color": "red"},
                             {"Label": "Escaped", "Color": "green"}])
@@ -84,6 +86,7 @@ def fire_evacuation_portrayal(agent):
 # Get list of available floorplans
 floor_plans = [f for f in listdir("fire_evacuation/floorplans") if path.isfile(path.join("fire_evacuation/floorplans", f))]
 
+# Specify the parameters changeable by the user, in the web interface
 model_params = {
     "floor_plan_file": UserSettableParameter("choice", "Floorplan", value=floor_plans[0], choices=floor_plans),
     "human_count": UserSettableParameter("number", "Number Of Human Agents", value=10),
@@ -94,5 +97,6 @@ def fire_evacuation_portrayal(agent):
     "save_plots": UserSettableParameter('checkbox', 'Save plots to file', value=True)
 }
 
+# Start the visual server with the model
 server = ModularServer(FireEvacuation, [canvas_element, status_chart, mobility_chart, collaboration_chart], "Fire Evacuation",
                        model_params)

run.py

@@ -1,3 +1,4 @@
 from fire_evacuation.server import server
 
+# Starts a visual server with our model
 server.launch()

run_batch.py

@@ -21,6 +21,10 @@
 GRAPH_WIDTH = 1920
 GRAPH_HEIGHT = 1080
 
+"""
+This script starts a batch run of our model, without visualisation, for obtaining the final statistics we require, over multiple iterations
+"""
+
 
 # Concatenate all of the dataframe files found in the OUTPUT_DIR
 def merge_dataframes():
@@ -73,20 +77,24 @@ def merge_dataframes():
 # Create the batch runner
 print("Running batch test with %i runs for each parameter and %i human agents." % (runs, human_count))
 
-start = time.time()  # Time the batch run
+batch_start = time.time()  # Time the batch run
+
+# Run the batch runner 'runs' times (the number of iterations to make) and output a dataset and graphs each iteration
 for i in range(1, runs + 1):
+    iteration_start = time.time()  # Time the iteration
+
     param_run = BatchRunner(FireEvacuation, variable_parameters=variable_params, fixed_parameters=fixed_params, model_reporters=model_reporter)
 
     param_run.run_all()  # Run all simulations
 
-    end = time.time()
+    iteration_end = time.time()
     end_timestamp = time.strftime("%Y%m%d-%H%M%S")
 
     # Save the dataframe to a file so we have the oppurtunity to concatenate separate dataframes from separate runs
     dataframe = param_run.get_model_vars_dataframe()
     dataframe.to_pickle(path=OUTPUT_DIR + "/batch_results/dataframe_" + end_timestamp + ".pickle")
 
-    elapsed = end - start  # Get the elapsed time in seconds
+    elapsed = iteration_end - iteration_start  # Get the elapsed time in seconds
     print("Batch runner finished iteration %i. Took: %s" % (i, str(timedelta(seconds=elapsed))))
 
     dataframe, count = merge_dataframes()
@@ -113,3 +121,7 @@ def merge_dataframes():
     plt.ylim(0, 100)
     plt.savefig(OUTPUT_DIR + "/batch_graphs/batch_run_boxplot_" + end_timestamp + ".png", dpi=GRAPH_DPI)
     plt.close(fig)
+
+batch_end = time.time()
+elapsed = batch_end - batch_start  # Get the elapsed time in seconds
+print("Batch runner finished all iterations. Took: %s" % str(timedelta(seconds=elapsed)))