Fix min delegation violation + rename id

batch-run.py

@@ -31,7 +31,7 @@ def main():
                         help='The percentage of players that will abstain from the game in this run. Default is 10%%.')
 
     fixed_params = {
-        "simulation_id": "temp",
+        "execution_id": "temp",
         "player_activation_order": "Random",
         "relative_utility_threshold": 0,
         "myopic_fraction": 0,
@@ -94,7 +94,7 @@ def main():
     run_data_MP = batch_run_MP.get_model_vars_dataframe()
     # print(run_data_MP.head())
 
-    output_dir = "output/19-11-21"
+    output_dir = "output/22-11-21"
     pickled_batch_run_data = output_dir + "/batch-run-data.pkl"
     with open(pickled_batch_run_data, "wb") as pkl_file:
         pkl.dump(run_data_MP, pkl_file)

experiments.sh

@@ -1,30 +1,32 @@
 #!/bin/bash
 
-python3.9 main.py --simulation_id=baseline-100-10 --n=100 --k=10 --alpha=0.3
+python3.9 main.py --execution_id=single-run-baseline-100-10 --n=100 --k=10 --alpha=0.3
 
-python3.9 main.py --simulation_id=baseline-1000-100 --n=1000 --k=100 --alpha=0.3
+python3.9 main.py --execution_id=single-run-baseline-1000-100 --n=1000 --k=100 --alpha=0.3
 
-python3.9 main.py --simulation_id=abstention-30-100-10 --n=100 --k=10 --alpha=0.3 --abstention_rate=0.3
+python3.9 main.py --execution_id=single-run-abstention-30-100-10 --n=100 --k=10 --alpha=0.3 --abstention_rate=0.3
 
-python3.9 main.py --simulation_id=parameter-change-k-100 --n=100 --k 10 20 --alpha=0.3
+python3.9 main.py --execution_id=single-run-parameter-change-k-100 --n=100 --k 10 20 --alpha=0.3
 
-python3.9 main.py --simulation_id=parameter-change-alpha-100-10 --n=100 --k=10 --alpha 0.03 0.3
+python3.9 main.py --execution_id=single-run-parameter-change-alpha-100-10 --n=100 --k=10 --alpha 0.03 0.3
 
-python3.9 main.py --simulation_id=parameter-change-k-1000 --n=1000 --k 100 200 --alpha=0.3
+python3.9 main.py --execution_id=single-run-parameter-change-k-1000 --n=1000 --k 100 200 --alpha=0.3
 
-python3.9 main.py --simulation_id=parameter-change-alpha-1000-100 --n=1000 --k=100 --alpha 0.03 0.3
+python3.9 main.py --execution_id=single-run-parameter-change-alpha-1000-100 --n=1000 --k=100 --alpha 0.03 0.3
 
-python3.9 main.py --simulation_id=alpha-zero-100-10 --n=100 --k=10 --alpha=0
+python3.9 main.py --execution_id=single-run-alpha-zero-100-10 --n=100 --k=10 --alpha=0
 
-python3.9 main.py --simulation_id=alpha-zero-1000-100 --n=1000 --k=100 --alpha=0
+python3.9 main.py --execution_id=single-run-alpha-zero-1000-100 --n=1000 --k=100 --alpha=0
 
-python3.9 batch-run.py --execution_id=varying-k-100 --n=100 --k 1 51 1 --alpha=0.3
+python3.9 batch-run.py --execution_id=batch-run-k-100 --n=100 --k 1 51 1 --alpha=0.3
 
-python3.9 batch-run.py --execution_id=varying-alpha-1000-100 --n=1000 --k=100 --alpha 0 10 0.25
+python3.9 batch-run.py --execution_id=batch-run-alpha-1000-100 --n=1000 --k=100 --alpha 0 10 0.25
 
-python3.9 batch-run.py --execution_id=varying-abstention-rate-1000-100 --n=1000 --k=100 --alpha=0.3 --abstention_rate 0 0.91 0.01
+python3.9 batch-run.py --execution_id=batch-run-alpha-zoom-in-1000-100 --n=1000 --k=100 --alpha 0 1 0.01
 
-python3.9 batch-run.py --execution_id=varying-k-1000 --n=1000 --k 1 251 2 --alpha=0.3
+python3.9 batch-run.py --execution_id=batch-run-abstention-rate-1000-100 --n=1000 --k=100 --alpha=0.3 --abstention_rate 0 0.91 0.01
+
+python3.9 batch-run.py --execution_id=batch-run-k-1000 --n=1000 --k 1 251 2 --alpha=0.3
 
 
 

logic/sim.py

@@ -49,7 +49,7 @@ def __init__(
             relative_utility_threshold=0, absolute_utility_threshold=1e-9,
             min_steps_to_keep_pool=5, pool_splitting=True, seed=42, pareto_param=2.0, max_iterations=1000,
             common_cost=1e-4, cost_min=0.001, cost_max=0.002, player_activation_order="Random", total_stake=1,
-            ms=10, simulation_id=''
+            ms=10, execution_id=''
     ):
         # todo make sure that the input is valid? n > 0, 0 < k <= n
 
@@ -90,7 +90,7 @@ def __init__(
 
         self.perceived_active_stake = total_stake
         self.beta = total_stake / self.k
-        self.simulation_id = simulation_id if simulation_id != '' else self.generate_simulation_id()
+        self.execution_id = execution_id if execution_id != '' else self.generate_execution_id()
 
         self.running = True  # for batch running and visualisation purposes
         self.schedule = self.player_activation_orders[player_activation_order](self)
@@ -245,18 +245,18 @@ def dump_state_to_csv(self):
               "Private" if pool.is_private else "Public"]
              for pool in pools])
 
-        output_dir = "output/19-11-21/"
+        output_dir = "output/22-11-21/"
         path = pathlib.Path.cwd() / output_dir
         pathlib.Path(path).mkdir(parents=True, exist_ok=True)
-        filename = (path / (self.simulation_id + '-final_configuration.csv')) \
-            if self.has_converged() else (path / (self.simulation_id + '-intermediate-configuration.csv'))
+        filename = (path / (self.execution_id + '-final_configuration.csv')) \
+            if self.has_converged() else (path / (self.execution_id + '-intermediate-configuration.csv'))
         with open(filename, 'w', newline='') as file:
             writer = csv.writer(file)
             writer.writerows(row_list)
 
         # temporary, used to extract results in latex format for easier reporting
         latex_dir = output_dir + "latex/"
-        hlp.to_latex(row_list, self.simulation_id, latex_dir)
+        hlp.to_latex(row_list, self.execution_id, latex_dir)
 
     def get_pools_list(self):
         return list(self.pools.values())
@@ -270,7 +270,7 @@ def get_players_list(self):
     def get_status(self):
         print("Step {}: {} pools".format(self.schedule.steps, len(self.pools)))
 
-    def generate_simulation_id(self):
+    def generate_execution_id(self):
         return "".join(['-' + str(key) + '=' + str(value) for key, value in self.arguments.items()
                         if type(value) == bool or type(value) == int or type(value) == float])[:147]
 

logic/stakeholder.py

@@ -496,7 +496,7 @@ def find_delegation_move_desirability(self, stake_to_delegate=None):
                                                                                         stake_to_saturation)
                         stake_to_delegate -= allocation
                         allocations[pool_id] = allocation
-                    if stake_to_delegate == 0:
+                    if stake_to_delegate <= MIN_STAKE_UNIT:
                         break
                 # there were not enough non-saturated pools for the player to delegate their stake to
                 # so they have to choose a saturated pool

main.py

@@ -47,7 +47,7 @@ def main():
     parser.add_argument('--ms', type=int, default=10,
                         help='The minimum consecutive idle steps that are required to declare convergence. '
                              'Default is 10. But if min_steps_to_keep_pool > ms then ms = min_steps_to_keep_pool + 1. ')
-    parser.add_argument('--simulation_id', type=str, default='unnamed-simulation',
+    parser.add_argument('--execution_id', type=str, default='unnamed-simulation',
                         help='An optional identifier for the specific simulation run, '
                              'which will be included in the output.')
 
@@ -74,53 +74,53 @@ def main():
         pool_splitting=args.pool_splitting,
         max_iterations=args.max_iterations,
         ms=args.ms,
-        simulation_id=args.simulation_id
+        execution_id=args.execution_id
     )
 
     sim.run_model()
 
     sim_df = sim.datacollector.get_model_vars_dataframe()
 
-    simulation_id = args.simulation_id
-    if simulation_id == '':
+    execution_id = args.execution_id
+    if execution_id == '':
         # No identifier was provided by the user, so we construct one based on the simulation's parameter values
-        simulation_id = "".join(['-' + str(key) + '=' + str(value) for key, value in sim.arguments.items()
+        execution_id = "".join(['-' + str(key) + '=' + str(value) for key, value in sim.arguments.items()
                                  if type(value) == bool or type(value) == int or type(value) == float])[:180]
 
-    pickled_simulation_filename = "output/simulation-object-" + simulation_id + ".pkl"
+    pickled_simulation_filename = "output/simulation-object-" + execution_id + ".pkl"
     with open(pickled_simulation_filename, "wb") as pkl_file:
         pkl.dump(sim, pkl_file)
 
-    output_dir = "output/19-11-21/"
+    output_dir = "output/22-11-21/"
     figures_dir = output_dir + "figures/"
     path = pathlib.Path.cwd() / figures_dir
     pathlib.Path(path).mkdir(parents=True, exist_ok=True)
 
     margin_changes = sim_df["MarginChanges"]
-    '''plot_line(simulation_id, sim_df["MarginChanges"], 'C0', "Number of pools over time", "Round",
+    '''plot_line(execution_id, sim_df["MarginChanges"], 'C0', "Number of pools over time", "Round",
               "#Pools", "poolCount", equilibrium_steps=[], pivot_steps=[])'''
 
     pool_nums = sim_df["#Pools"]
     if sim.schedule.steps >= sim.max_iterations:
         # If the max number of iterations was reached, then we save the data about the pool numbers
         # in order to later analyse the statistic properties of the execution
-        filename = output_dir + simulation_id + "-poolCount" + ".pkl"
+        filename = output_dir + execution_id + "-poolCount" + ".pkl"
         with open(filename, "wb") as pkl_file:
             pkl.dump(pool_nums, pkl_file)
 
     equilibrium_steps = sim.equilibrium_steps
     pivot_steps = sim.pivot_steps
 
-    plot_line(simulation_id, sim_df["#Pools"], 'C0', "Number of pools over time", "Round",
+    plot_line(execution_id, sim_df["#Pools"], 'C0', "Number of pools over time", "Round",
               "#Pools", "poolCount", equilibrium_steps, pivot_steps, figures_dir, True)
 
-    plot_line(simulation_id, sim_df["AvgPledge"], 'red', "Average pledge over time", "Round",
+    plot_line(execution_id, sim_df["AvgPledge"], 'red', "Average pledge over time", "Round",
               "Average pledge", "avgPledge", equilibrium_steps, pivot_steps, figures_dir, True)
 
-    plot_line(simulation_id, sim_df["TotalPledge"], 'purple', "Total pledge over time", "Round",
+    plot_line(execution_id, sim_df["TotalPledge"], 'purple', "Total pledge over time", "Round",
               "Total pledge", "totalPledge", equilibrium_steps, pivot_steps, figures_dir, True)
 
-    plot_line(simulation_id, sim_df["MeanAbsDiff"], 'green', "Mean Absolute Difference of Controlled Stake", "Round",
+    plot_line(execution_id, sim_df["MeanAbsDiff"], 'green', "Mean Absolute Difference of Controlled Stake", "Round",
               "Mean abs diff", "meanAbsDiff", equilibrium_steps, pivot_steps, figures_dir, False)
 
     '''pool_sizes_by_step = sim_df["PoolSizes"]  # todo fix
@@ -135,7 +135,7 @@ def main():
         plt.savefig(figures_dir + "poolDynamics.png", bbox_inches='tight')'''
 
 
-def plot_line(simulation_id, data, color, title, x_label, y_label, filename, equilibrium_steps, pivot_steps,
+def plot_line(execution_id, data, color, title, x_label, y_label, filename, equilibrium_steps, pivot_steps,
               figures_dir, show_equilibrium=False):
     path = pathlib.Path.cwd() / figures_dir
     pathlib.Path(path).mkdir(parents=True, exist_ok=True)
@@ -156,7 +156,7 @@ def plot_line(simulation_id, data, color, title, x_label, y_label, filename, equ
     plt.xlabel(x_label)
     plt.ylabel(y_label)
     plt.legend()
-    plt.savefig(figures_dir + simulation_id + "-" + filename + ".png", bbox_inches='tight')
+    plt.savefig(figures_dir + execution_id + "-" + filename + ".png", bbox_inches='tight')
 
     # plt.show()