Comments and cleanup

README.md

@@ -14,7 +14,7 @@ $ pip install -r requirements.txt
 
 ## Simulation 
 
-Execute the simulation with this command
+Execute a single simulation run with the command:
 
 ```
 $ python3 start.py
@@ -25,9 +25,9 @@ $ python3 start.py
 The ```start.py``` script accepts a number of options. 
 
 ```
-usage: start.py [-h] [--abce] [--oneriskmodel] [--riskmodels {1,2,3,4}]
-                [--replicid REPLICID] [--replicating]
-                [--randomseed RANDOMSEED] [--foreground] [-p] [-v]
+usage: start.py [--oneriskmodel] [--riskmodels {1,2,3,4}] [--replicid REPLICID]
+                [--replicating] [--randomseed RANDOMSEED] [--foreground]
+                [--shownetwork] [-p] [-v] [--save_iterations]
 ```
 
 See the help for more details
@@ -36,17 +36,9 @@ See the help for more details
 python3 start.py --help
 ```
 
-## Graphical simulation runs
-
-abce can be used to run simulations with a graphical interface:
-
-```
-python3 start.py --abce
-```
-
 ## Ensemble simulations
 
-The bash scripts ```starter_*.sh``` can be used to run ensembles of a large number of simulations for settings with 1-4 different riskmodels. ```starter_two.sh``` is set up to generate random seeds and risk event schedules that are - for consistency and comparability - also used by the other scripts (i.e. ```starter_two.sh``` needs to be run first).
+The bash scripts ```starter_*.sh``` can be used to run ensembles of a large number of simulations for settings with 1-4 different risk models. ```starter_two.sh``` is set up to generate random seeds and risk event schedules that are - for consistency and comparability - also used by the other scripts (i.e. ```starter_two.sh``` needs to be run first).
 
 ```
 bash starter_two.sh
@@ -55,7 +47,23 @@ bash starter_four.sh
 bash starter_three.sh
 ```
 
-## Plotting
+## Visualisation
+
+#### Single runs
+Use the script ```visualisation.py [--single]``` from the command line to plot data from a single run. It also takes the 
+arguments ```[--pie] [--timeseries]``` for which data representation is wanted.
+
+If the necessary data has been saved a network animation can also be created by running ```visualization_network.py``` 
+which takes the arguments ```[--save] [--number_iterations]``` if you want the animation to be saved as an mp4, and how
+many time iterations you want in the animation.
+
+#### Ensemble runs
+Ensemble runs can be plotted if the correct data is available using ``visualisation.py`` which has a number of arguments.
+
+```
+visualiation.py [--timeseries_comparison] [--firmdistribution] 
+                [--bankruptcydistribution] [--compare_riskmodels]
+```
 
-Use the scripts ```plotter_pl_timescale.py``` and  ```visualize.py``` for plotting/visualizing single simulation runs. Use  ```.py```,  ```metaplotter_pl_timescale.py```, or  ```metaplotter_pl_timescale_additional_measures.py``` to visualize ensemble runs.
+See help for more information.
 

centralbank.py

@@ -0,0 +1,62 @@
+from isleconfig import simulation_parameters
+
+
+class CentralBank:
+    def __init__(self):
+        """Constructor Method.
+            No accepted arguments.
+        Constructs the CentralBank class. This class is currently only used to award interest payments."""
+        self.interest_rate = simulation_parameters['interest_rate']
+        self.inflation_target = 0.02
+        self.actual_inflation = 0
+        self.onemonth_CPI = 0
+        self.twelvemonth_CPI = 0
+        self.feedback_counter = 0
+        self.prices_list = []
+
+    def set_interest_rate(self):
+        """Method to set the interest rate
+            No accepted arguments
+            No return values
+        This method is meant to set interest rates dependant on prices however insurance firms have little effect on
+        interest rates therefore is not used and needs work if to be used."""
+        if self.actual_inflation > self.inflation_target:
+            if self.feedback_counter > 4:
+                self.interest_rate += 0.0001
+                self.feedback_counter = 0
+            else:
+                self.feedback_counter += 1
+        elif self.actual_inflation < -0.01:
+            if self.feedback_counter > 4:
+                if self.interest_rate > 0.0001:
+                    self.interest_rate -= 0.0001
+                    self.feedback_counter = 0
+            else:
+                self.feedback_counter += 1
+        else:
+            self.feedback_counter = 0
+        print(self.interest_rate)
+
+    def award_interest(self, firm, total_cash):
+        """Method to award interest.
+            Accepts:
+                firm: Type class, the agent that is to be awarded interest.
+                total_cash: Type decimal
+        This method takes an agents cash and awards it an interest payment on the cash."""
+        interest_payment = total_cash * self.interest_rate
+        firm.receive(interest_payment)
+
+    def calculate_inflation(self, current_price, time):
+        """Method to calculate inflation in insurance prices.
+            Accepts:
+                current_price: Type decimal
+                time: Type integer
+        This method is designed to calculate both the percentage change in insurance price last 1 and 12 months as an
+        estimate of inflation. This is to help calculate how insurance rates should be set. Currently unused."""
+        self.prices_list.append(current_price)
+        if time < 13:
+            self.actual_inflation = self.inflation_target
+        else:
+            self.onemonth_CPI = (current_price - self.prices_list[-2])/self.prices_list[-2]
+            self.twelvemonth_CPI = (current_price - self.prices_list[-13])/self.prices_list[-13]
+            self.actual_inflation = self.twelvemonth_CPI

distributiontruncated.py

@@ -3,6 +3,7 @@
 from math import ceil
 import scipy.integrate
 
+
 class TruncatedDistWrapper():
     def __init__(self, dist, lower_bound=0, upper_bound=1):
         self.dist = dist

ensemble.py

@@ -1,6 +1,6 @@
-#This script allows to launch an ensemble of simulations for different number of risks models.
-#It can be run locally if no argument is passed when called from the terminal.
-#It can be run in the cloud if it is passed as argument the server that will be used.
+"""This script allows to launch an ensemble of simulations for different number of risks models.
+It can be run locally if no argument is passed when called from the terminal.
+It can be run in the cloud if it is passed as argument the server that will be used."""
 import sys
 import random
 import os
@@ -16,7 +16,6 @@
 from sandman2.api import operation, Session
 
 
-
 @operation
 def agg(*outputs):
     # do nothing
@@ -29,13 +28,13 @@ def rake(hostname):
 
     """Configuration of the ensemble"""
 
-    replications = 70    #Number of replications to be carried out for each configuration. Usually one risk model, two risk models, three risk models, four risk models.
+    replications = 70    # Number of replications to be carried out for each configuration. Usually one risk model, two risk models, three risk models, four risk models.
 
     model = start.main
 
     m = operation(model, include_modules = True)
 
-    riskmodels = [1,2,3,4]   #The number of risk models that will be used.
+    riskmodels = [1,2,3,4]   # The number of risk models that will be used.
 
     parameters = isleconfig.simulation_parameters
 
@@ -73,19 +72,21 @@ def rake(hostname):
                'rc_event_schedule_initial':     '_rc_event_schedule.dat',
                'rc_event_damage_initial':       '_rc_event_damage.dat',
                'number_riskmodels':             '_number_riskmodels.dat'
+               'individual_contracts'           '_insurance_contracts.dat'
+               'reinsurance_contracts'          '_reinsurance_contracts.dat'
                 } 
 
     if isleconfig.slim_log:
-        for name in ['insurance_firms_cash', 'reinsurance_firms_cash']:
+        for name in ['insurance_firms_cash', 'reinsurance_firms_cash', 'individual_contracts', 'reinsurance_contracts']:
             del requested_logs[name]
 
     assert "number_riskmodels" in requested_logs
 
-    
+
     """Configure log directory and ensure that the directory exists"""
     dir_prefix = "/data/"
     directory = os.getcwd() + dir_prefix
-    try: #Here it is checked whether the directory to collect the results exists or not. If not it is created.
+    try:  # Here it is checked whether the directory to collect the results exists or not. If not it is created.
         os.stat(directory)
     except:
         os.mkdir(directory)
@@ -95,11 +96,11 @@ def rake(hostname):
         filename = os.getcwd() + dir_prefix + nums[str(i)] + "_history_logs.dat"
         if os.path.exists(filename):
             os.remove(filename)
-        
+
 
     """Setup of the simulations"""
 
-    setup = SetupSim()   #Here the setup for the simulation is done.
+    setup = SetupSim()   # Here the setup for the simulation is done.
     [general_rc_event_schedule, general_rc_event_damage, np_seeds, random_seeds] = setup.obtain_ensemble(replications)  #Since this script is used to carry out simulations in the cloud will usually have more than 1 replication..
     save_iter = isleconfig.simulation_parameters["max_time"] + 2    # never save simulation state in ensemble runs (resuming is impossible anyway)
 
@@ -108,7 +109,8 @@ def rake(hostname):
         simulation_parameters = copy.copy(parameters)       #Here the parameters used for the simulation are loaded. Clone is needed otherwise all the runs will be carried out with the last number of thee loop.
         simulation_parameters["no_riskmodels"] = i      #Since we want to obtain ensembles for different number of risk models, we vary here the number of risks models.
         job = [m(simulation_parameters, general_rc_event_schedule[x], general_rc_event_damage[x], np_seeds[x], random_seeds[x], save_iter, list(requested_logs.keys())) for x in range(replications)]  #Here is assembled each job with the corresponding: simulation parameters, time events, damage events, seeds, simulation state save interval (never, i.e. longer than max_time), and list of requested logs.
-        jobs.append(job)    #All jobs are collected in the jobs list.
+        jobs.append(job)    # All jobs are collected in the jobs list.
+
 
     """Here the jobs are submitted"""
 
@@ -118,17 +120,14 @@ def rake(hostname):
 
             """Run simulation and obtain result"""
             result = sess.submit(job)
-            
-            
-            """find number of riskmodels from log"""
+
+
+            """Find number of riskmodels from log"""
             delistified_result = [listify.delistify(list(res)) for res in result]
-            #nrmidx = result[0][-1].index("number_riskmodels")
-            #nrm = result[0][nrmidx]
             nrm = delistified_result[0]["number_riskmodels"]
 
             """These are the files created to collect the results"""
             wfiles_dict = {}
-
             logfile_dict = {}
 
             for name in requested_logs.keys():
@@ -154,8 +153,10 @@ def rake(hostname):
 
                 """Save logs as dict (to <num>_history_logs.dat)"""
                 L.save_log(True)
+                if isleconfig.save_network:
+                    L.save_network_data(ensemble=True)
 
-                """Save logs as indivitual files"""
+                """Save logs as individual files"""
                 for name in logfile_dict:
                     wfiles_dict[name].write(str(delistified_result[i][name]) + "\n")
 
@@ -168,5 +169,9 @@ def rake(hostname):
 if __name__ == '__main__':
     host = None
     if len(sys.argv) > 1:
-        host = sys.argv[1]     #The server is passed as an argument.
+        host = sys.argv[1]     # The server is passed as an argument.
     rake(host)
+
+# ID = OxeChiwQ3l0vsBnkLLXKMnpSBn948ptW
+# Secret = lfK_Gav8EK2B_gN0bsNXjUVQq84ua1iL2xlYs8Ef58tFyTSwzzJcWeDdSH21BnHx
+# Hostname = bright-lemur.clusters.sandman.ai