.vscode/launch.json

@@ -8,7 +8,7 @@
             "name": "Python: Current File",
             "type": "python",
             "request": "launch",
-            "program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\main.py",
+            "program": "C:\\Users\\ASUS\\OneDrive\\Project\\ScrAbm\\Dissertation\\IIabm\\model.py",
             "console": "integratedTerminal",
             "justMyCode": true
         }

computation.py

@@ -1,52 +0,0 @@
-import os
-import datetime
-
-from model import Model
-
-from typing import TYPE_CHECKING
-if TYPE_CHECKING:
-    from controller_db import ControllerDB
-    
-
-class Computation:
-
-    def __init__(self, c_db: 'ControllerDB'):
-        self.c_db = c_db
-        self.pid = os.getpid()
-
-    def run(self, str_code='0', s_id=None):
-        sample_random = self.c_db.fetch_a_sample(s_id)
-        if sample_random is None:
-            return True
-
-        # lock this row by update is_done_flag to 0
-        self.c_db.lock_the_sample(sample_random)
-        print(f"Pid {self.pid} ({str_code}) is running sample {sample_random.id} at {datetime.datetime.now()}")
-
-        dct_exp = {column: getattr(sample_random.experiment, column)
-                   for column in sample_random.experiment.__table__.c.keys()}
-        del dct_exp['id']
-
-        dct_sample_para = {'sample': sample_random,
-                           'seed': sample_random.seed,
-                           **dct_exp}
-        model = Model(dct_sample_para)
-        results = model.run(display=False)
-        return False
-
-
-if __name__ == '__main__':
-    str_exp = 'test'
-
-    from controller_db import ControllerDB
-
-    controller_db = ControllerDB(str_exp)
-    controller_db.reset_db()
-    # print(controller_db.dct_parameter)
-    exp = Computation(controller_db)
-    is_all_done = exp.run('999', 87)
-    # while 1:
-    #     # time.sleep(random.uniform(0, 10))
-    #     is_all_done = exp.run(str_exp)
-    #     if is_all_done:
-    #         break

conf_db.yaml

@@ -1,16 +0,0 @@
-# read by orm
-is_local_db: True
-
-local:
-  user_name: iiabm_yz
-  password: iiabm_yz
-  db_name: iiabmdb
-  address: 'localhost'
-  port: 3306
-
-remote:
-  user_name: iiabm_yz
-  password: iiabm_yz
-  db_name: iiabmdb
-  address: 'localhost'
-  port: 3307

conf_db_prefix.yaml

@@ -1 +0,0 @@
-db_name_prefix: test

conf_experiment.yaml

@@ -1,38 +0,0 @@
-# read by ControllerDB
-
-# run settings
-meta_seed: 0
-
-fixed:  # unchanged all the time
-  int_n_country: 2
-  max_int_n_supplier: 3  # make firms heterogeneous
-  flt_bm_price_ratio: 20.0
-  flt_beta_developing: 0.5
-
-test:  # only for test scenarios
-  int_n_product: 12
-  int_n_firm_per_product_per_country: 2
-  flt_demand_total: 1000.0
-  n_sample: 5
-  n_iter: 100
-
-not_test:  # normal scenarios
-  int_n_product: 50
-  int_n_firm_per_product_per_country: 10
-  flt_demand_total: 10000.0
-  n_sample: 50
-  n_iter: 10000
-
-default:
-  is_eliminated: 0  # add when all positive profits and keep max n supplier; remove the worst when all negative wealth
-  flt_beta_developed: 0.5  # benchmarks flt_beta_developed
-  tariff_percentage: 0
-
-experiment:
-  1:
-    range_lambda_tier: 0, 1, 0.1  # describe the network. 0: chain 1: one iter
-  2:
-    is_eliminated: 1
-  3:
-    range_flt_beta_developed: 0.5, 0.9, 0.1
-    range_tariff_percentage: 0, 1, 0.1

controller_db.py

@@ -1,237 +0,0 @@
-# -*- coding: utf-8 -*-
-from orm import db_session, engine, Base, ins
-from orm import Experiment, Sample, Product, Firm
-from sqlalchemy.exc import OperationalError
-import yaml
-import random
-import numpy as np
-import platform
-
-
-class ControllerDB:
-    dct_parameter = None
-    is_test: bool = None
-    db_name_prefix: str = None
-    reset_flag: int
-
-    lst_saved_s_id_3: list
-    lst_saved_s_id_1_2: list
-    # n_sample_1_2: int
-
-    def __init__(self, prefix, reset_flag=0):
-        with open('conf_experiment.yaml') as yaml_file:
-            dct_conf_experiment = yaml.full_load(yaml_file)
-        self.is_test = prefix == 'test'
-        self.db_name_prefix = prefix
-        dct_para_in_test = dct_conf_experiment['test'] if self.is_test else dct_conf_experiment['not_test']
-        self.dct_parameter = {'meta_seed': dct_conf_experiment['meta_seed'],
-                              'experiment': dct_conf_experiment['experiment'],
-                              **dct_conf_experiment['fixed'], **dct_conf_experiment['default'], **dct_para_in_test}
-        self.reset_flag = reset_flag  # 0, not reset; 1, reset self; 2, reset all
-        self.lst_saved_s_id_1_2, self.lst_saved_s_id_3 = [], []
-
-    def init_tables(self):
-        self.fill_experiment_table()
-        self.fill_sample_table()
-
-    @staticmethod
-    def get_lst_of_range(str_range: str):
-        s1, s2, s3 = tuple(str_range.split(','))
-        return list(np.linspace(float(s1), float(s2), num=int((float(s2) - float(s1)) / float(s3)) + 1))
-
-    def fill_experiment_table(self):
-        # prepare the list of lambda tier
-        lst_lambda = self.get_lst_of_range(self.dct_parameter['experiment'][1]['range_lambda_tier'])
-        # prepare the list of alpha_2nd_country
-        lst_beta_developed = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_flt_beta_developed'])
-        # prepare the list of tariff_percentage
-        lst_tariff = self.get_lst_of_range(self.dct_parameter['experiment'][3]['range_tariff_percentage'])
-        # prepare the default values
-        is_eliminated = int(self.dct_parameter['is_eliminated'])
-        beta_developed = float(self.dct_parameter['flt_beta_developed'])
-        tariff_percentage_1 = tariff_percentage_2 = float(self.dct_parameter['tariff_percentage'])
-        for idx_scenario in self.dct_parameter['experiment'].keys():
-            n_exp = 0
-            # if idx_scenario == 1:  # add S1 experiments
-            #     n_exp = self.add_experiment_1(idx_scenario, lst_lambda, is_eliminated,
-            #                                   beta_developed, tariff_percentage_1, tariff_percentage_2)
-            # if idx_scenario == 2:  # add S2 experiments
-            #     n_exp = self.add_experiment_1(idx_scenario, lst_lambda,
-            #                                   int(self.dct_parameter['experiment'][idx_scenario]['is_eliminated']),
-            #                                   beta_developed, tariff_percentage_1, tariff_percentage_2)
-            if idx_scenario == 3:
-                # int_eliminated = int(self.dct_parameter['experiment'][idx_scenario-1]['is_eliminated'])
-                int_eliminated = is_eliminated  # is_eliminated is 0 at default, so stop eliminating under S3
-                for beta_developed in lst_beta_developed:
-                # for beta_developed in [0.5]:  # fix beta as 0.5
-                    for tariff_percentage_1 in lst_tariff:
-                        for tariff_percentage_2 in lst_tariff:
-                            # fix lambda as 0.5
-                            n_exp += self.add_experiment_1(idx_scenario, [0.5], int_eliminated,
-                                                           beta_developed, tariff_percentage_1, tariff_percentage_2)
-            print(f'Inserted {n_exp} experiments for exp {idx_scenario}!')
-
-    def add_experiment_1(self, idx_exp, lst_lambda, is_eliminated, flt_beta_developed,
-                         tariff_percentage_1: float, tariff_percentage_2: float):
-        lst_exp = []
-        for lambda_tier in lst_lambda:
-            e = Experiment(idx_exp=idx_exp,
-                           int_n_country=int(self.dct_parameter['int_n_country']),
-                           max_int_n_supplier=int(self.dct_parameter['max_int_n_supplier']),
-                           int_n_product=int(self.dct_parameter['int_n_product']),
-                           int_n_firm_per_product_per_country=int(
-                               self.dct_parameter['int_n_firm_per_product_per_country']),
-                           flt_demand_total=float(self.dct_parameter['flt_demand_total']),
-                           flt_bm_price_ratio=float(self.dct_parameter['flt_bm_price_ratio']),
-                           flt_beta_developing=float(self.dct_parameter['flt_beta_developing']),
-                           n_sample=int(self.dct_parameter['n_sample']),
-                           n_iter=int(self.dct_parameter['n_iter']),
-                           is_eliminated=is_eliminated,
-                           flt_beta_developed=flt_beta_developed,
-                           tariff_percentage_1=tariff_percentage_1,
-                           tariff_percentage_2=tariff_percentage_2,
-                           lambda_tier=float(lambda_tier))
-            lst_exp.append(e)
-        db_session.bulk_save_objects(lst_exp)
-        db_session.commit()
-        return len(lst_exp)
-
-    def fill_sample_table(self):
-        rng = random.Random(self.dct_parameter['meta_seed'])
-        lst_seed = [rng.getrandbits(32) for _ in range(int(self.dct_parameter['n_sample']))]
-        lst_exp = db_session.query(Experiment).all()
-        lst_sample = []
-        for experiment in lst_exp:
-            for idx_sample in range(int(experiment.n_sample)):
-                s = Sample(e_id=experiment.id,
-                           idx_sample=idx_sample+1,
-                           seed=lst_seed[idx_sample],
-                           is_done_flag=-1)
-                lst_sample.append(s)
-        db_session.bulk_save_objects(lst_sample)
-        db_session.commit()
-        print(f'Inserted {len(lst_sample)} samples!')
-
-    def reset_db(self, force_drop=False):
-        # first, check if tables exist
-        lst_table_obj = [Base.metadata.tables[str_table] for str_table in ins.get_table_names()
-                         if str_table.startswith(self.db_name_prefix)]
-        is_exist = len(lst_table_obj) > 0
-        if force_drop:
-            while is_exist:
-                a_table = random.choice(lst_table_obj)
-                try:
-                    Base.metadata.drop_all(bind=engine, tables=[a_table])
-                except KeyError:
-                    pass
-                except OperationalError:
-                    pass
-                else:
-                    lst_table_obj.remove(a_table)
-                    print(f"Table {a_table.name} is dropped for exp: {self.db_name_prefix}!!!")
-                finally:
-                    is_exist = len(lst_table_obj) > 0
-
-        if is_exist:
-            print(f"All tables exist. No need to reset for exp: {self.db_name_prefix}.")
-            # change the is_done_flag from 0 to -1, to rerun the in-finished tasks
-            if self.reset_flag > 0:
-                if self.reset_flag == 2:
-                    result = db_session.query(Sample).filter(Sample.is_done_flag == 0)
-                elif self.reset_flag == 1:
-                    result = db_session.query(Sample).filter(Sample.is_done_flag == 0,
-                                                             Sample.computer_name == platform.node())
-                else:
-                    raise ValueError('Wrong reset flag')
-                if result.count() > 0:
-                    for res in result:
-                        qry_product = db_session.query(Product).filter_by(s_id=res.id)
-                        if qry_product.count() > 0:
-                            for p in qry_product:
-                                db_session.query(Firm).filter(Firm.p_id == p.id).delete()
-                                db_session.commit()
-                                db_session.query(Product).filter(Product.id == p.id).delete()
-                                db_session.commit()
-                        res.is_done_flag = -1
-                        db_session.commit()
-                        print(f"Reset the task id {res.id} flag from 0 to -1")
-        else:
-            Base.metadata.create_all()
-            self.init_tables()
-            print(f"All tables are just created and initialized for exp: {self.db_name_prefix}.")
-
-    def prepare_list_sample(self):
-        res = db_session.execute(f'''SELECT count(*) FROM {self.db_name_prefix}_sample s, 
-        {self.db_name_prefix}_experiment e WHERE s.e_id=e.id and e.idx_exp < 3''').scalar()
-        n_sample_1_2 = 0 if res is None else res
-        print(f'There are {n_sample_1_2} sample for exp 1 and 2.')
-        res = db_session.execute(f'SELECT id FROM {self.db_name_prefix}_sample WHERE is_done_flag = -1')
-        for row in res:
-            s_id = row[0]
-            if s_id <= n_sample_1_2:
-                self.lst_saved_s_id_1_2.append(s_id)
-            else:
-                self.lst_saved_s_id_3.append(s_id)
-        print(f'Left: {len(self.lst_saved_s_id_1_2)} for exp 1 and 2; {len(self.lst_saved_s_id_3)} for exp 3')
-
-    @staticmethod
-    def select_random_sample(lst_s_id):
-        while 1:
-            if len(lst_s_id) == 0:
-                return None
-            s_id = random.choice(lst_s_id)
-            lst_s_id.remove(s_id)
-            res = db_session.query(Sample).filter(Sample.id == int(s_id), Sample.is_done_flag == -1)
-            if res.count() == 1:
-                return res[0]
-
-    def fetch_a_sample(self, s_id=None):
-        if s_id is not None:
-            res = db_session.query(Sample).filter(Sample.id == int(s_id))
-            if res.count() == 0:
-                return None
-            else:
-                return res[0]
-
-        sample = self.select_random_sample(self.lst_saved_s_id_1_2)
-        if sample is not None:
-            return sample
-
-        sample = self.select_random_sample(self.lst_saved_s_id_3)
-        if sample is not None:
-            return sample
-
-        return None
-
-    @staticmethod
-    def lock_the_sample(sample: Sample):
-        sample.is_done_flag, sample.computer_name = 0, platform.node()
-        db_session.commit()
-
-
-if __name__ == '__main__':
-    # pprint.pprint(dct_exp_config)
-    # pprint.pprint(dct_conf_problem)
-    db = ControllerDB('first')
-    ratio = db_session.execute('SELECT COUNT(*) / 332750 FROM first_sample s WHERE s.is_done_flag = 1').scalar()
-    print(ratio)
-    # db.fill_experiment_table()
-    # print(db.dct_parameter)
-    # db.init_tables()
-    # db.fill_sample_table()
-    # pprint.pprint(dct_conf_exp)
-    # db.update_bi()
-    # db.reset_db(force_drop=True)
-    # db.prepare_list_sample()
-    #
-    # for i in range(1000):
-    #     if i % 10 == 0:
-    #         print(i)
-    #         print(len(db.lst_saved_s_id_1_2), len(db.lst_saved_s_id_3))
-    #     r = db.fetch_a_sample()
-    #     if i % 10 == 0:
-    #         print(len(db.lst_saved_s_id_1_2), len(db.lst_saved_s_id_3))
-    #         print(r, r.experiment.idx_exp)
-    #     if i == 400:
-    #         print()
-    #         pass

firm.py

@@ -41,7 +41,7 @@ class FirmAgent(ap.Agent):
                 ]
                 # print(select_edges)
                 if len(select_edges) == 0:
-                    print(self.name, remove_product.code, 'affect', customer.name)
+                    print('affect', customer.name, remove_product.code)
                     if remove_product not in \
                             customer.a_list_up_product_removed:
                         customer.a_list_up_product_removed.append(
@@ -136,7 +136,3 @@ class FirmAgent(ap.Agent):
 
     def clean_before_trial(self):
         self.dct_request_prod_from_firm = {}
-
-    def clean_before_time_step(self):
-        self.dct_num_trial_up_product_removed = {}
-        self.a_list_up_product_removed = ap.AgentList(self.model, [])

main.py

@@ -1,52 +0,0 @@
-import os
-import random
-import time
-from multiprocessing import Process
-import argparse
-from computation import Computation
-from sqlalchemy.orm import close_all_sessions
-
-import yaml
-
-
-def do_computation(c_db):
-    exp = Computation(c_db)
-
-    while 1:
-        time.sleep(random.uniform(0, 10))
-        is_all_done = exp.run()
-        if is_all_done:
-            break
-
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='setting')
-    parser.add_argument('--exp', type=str, default='test')
-    parser.add_argument('--job', type=int, default='3')
-    parser.add_argument('--reset', type=int, default='0')
-
-    args = parser.parse_args()
-    assert args.job >= 1, 'Number of jobs should >= 1'
-
-    prefix_file_name = 'conf_db_prefix.yaml'
-    if os.path.exists(prefix_file_name):
-        os.remove(prefix_file_name)
-    with open(prefix_file_name, 'w', encoding='utf-8') as file:
-        yaml.dump({'db_name_prefix': args.exp}, file)
-
-    from controller_db import ControllerDB
-    controller_db = ControllerDB(args.exp, reset_flag=args.reset)
-    controller_db.reset_db()
-
-    controller_db.prepare_list_sample()
-
-    close_all_sessions()
-
-    process_list = []
-    for i in range(int(args.job)):
-        p = Process(target=do_computation, args=(controller_db,))
-        p.start()
-        process_list.append(p)
-
-    for i in process_list:
-        i.join()

model.py

@@ -8,15 +8,9 @@ from product import ProductAgent
 
 sample = 0
 seed = 0
-n_iter = 10
+n_iter = 3
 # dct_list_init_remove_firm_prod = {133: ['1.4.4.1'], 2: ['1.1.3']}
-# dct_list_init_remove_firm_prod = {
-#     135: ['1.3.2.1'],
-#     133: ['1.4.4.1'],
-#     2: ['1.1.3']
-# }
 dct_list_init_remove_firm_prod = {
-    140: ['1.4.5.1'],
     135: ['1.3.2.1'],
     133: ['1.4.4.1'],
     2: ['1.1.3']
@@ -183,7 +177,6 @@ class Model(ap.Model):
         self.draw_network()
 
     def update(self):
-        self.a_list_total_firms.clean_before_time_step()
         # stop simulation if reached terminal number of iteration
         if self.t == self.int_n_iter or len(
                 self.dct_list_remove_firm_prod) == 0:
@@ -239,7 +232,6 @@ class Model(ap.Model):
         self.dct_list_remove_firm_prod = {}
         for firm in self.a_list_total_firms:
             if len(firm.a_list_up_product_removed) > 0:
-                print(firm.name, 'a_list_up_product_removed', [product.code for product in firm.a_list_up_product_removed])
                 for product in firm.a_list_product:
                     n_up_product_removed = 0
                     for up_product_removed in firm.a_list_up_product_removed:
@@ -259,9 +251,8 @@ class Model(ap.Model):
                                     1) / (max(list_revenue_log) -
                                           min(list_revenue_log) + 1)
                         p_remove = 1 - std_size * (1 - lost_percent)
-                        # flag = self.nprandom.choice([1, 0],
+                        flag = self.nprandom.choice([1, 0],
-                        #                             p=[p_remove, 1 - p_remove])
+                                                    p=[p_remove, 1 - p_remove])
-                        flag = 1
                         if flag == 1:
                             firm.a_list_product_removed.append(product)
                             # if firm in
@@ -324,5 +315,5 @@ class Model(ap.Model):
         plt.savefig("network.png")
 
 
-# model = Model(dct_sample_para)
+model = Model(dct_sample_para)
-# model.run()
+model.run()

orm.py

@@ -1,151 +0,0 @@
-# -*- coding: utf-8 -*-
-from sqlalchemy import create_engine, inspect
-from sqlalchemy.ext.declarative import declarative_base
-from sqlalchemy import Column, Integer, String, ForeignKey, BigInteger, DECIMAL, DateTime, Text
-from sqlalchemy.sql import func
-from sqlalchemy.orm import relationship, Session
-from sqlalchemy.pool import NullPool
-import yaml
-
-
-with open('conf_db.yaml') as file:
-    dct_conf_db_all = yaml.full_load(file)
-    is_local_db = dct_conf_db_all['is_local_db']
-    if is_local_db:
-        dct_conf_db = dct_conf_db_all['local']
-    else:
-        dct_conf_db = dct_conf_db_all['remote']
-
-with open('conf_db_prefix.yaml') as file:
-    dct_conf_db_prefix = yaml.full_load(file)
-    db_name_prefix = dct_conf_db_prefix['db_name_prefix']
-
-
-str_login = 'mysql://{}:{}@{}:{}/{}'.format(dct_conf_db['user_name'], dct_conf_db['password'],
-                                            dct_conf_db['address'], dct_conf_db['port'], dct_conf_db['db_name'])
-print('DB is {}:{}/{}'.format(dct_conf_db['address'], dct_conf_db['port'], dct_conf_db['db_name']))
-
-engine = create_engine(str_login, poolclass=NullPool)  # must be null pool to avoid connection lost error
-ins = inspect(engine)
-
-Base = declarative_base(constructor=engine)
-
-db_session = Session(bind=engine)
-
-
-class Experiment(Base):
-    __tablename__ = f"{db_name_prefix}_experiment"
-    id = Column(Integer, primary_key=True, autoincrement=True)
-
-    idx_exp = Column(Integer, nullable=False)
-
-    # fixed parameters
-    int_n_country = Column(Integer, nullable=False)
-    max_int_n_supplier = Column(Integer, nullable=False)  # uni(1, max), random parameter 1 of firm
-    int_n_product = Column(Integer, nullable=False)
-    int_n_firm_per_product_per_country = Column(Integer, nullable=False)
-    flt_demand_total = Column(DECIMAL(10, 2), nullable=False)  # tri(0, total_demand, mean), to compute random para a
-    flt_bm_price_ratio = Column(DECIMAL(10, 2), nullable=False)  # benchmark value of b, same for both countries
-    flt_beta_developing = Column(DECIMAL(10, 2), nullable=False)  # benchmark value of c(beta), for developing countries
-    n_sample = Column(Integer, nullable=False)
-    n_iter = Column(Integer, nullable=False)
-
-    # variables
-    is_eliminated = Column(Integer, nullable=False)
-    flt_beta_developed = Column(DECIMAL(10, 2), nullable=False)  # larger, for developed countries
-    lambda_tier = Column(DECIMAL(10, 2), nullable=False)
-    tariff_percentage_1 = Column(DECIMAL(10, 2), nullable=False)
-    tariff_percentage_2 = Column(DECIMAL(10, 2), nullable=False)
-
-    sample = relationship('Sample', back_populates='experiment', lazy='dynamic')
-
-    def __repr__(self):
-        return f'<Experiment: {self.id}>'
-
-
-class Sample(Base):
-    __tablename__ = f"{db_name_prefix}_sample"
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    e_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_experiment")), nullable=False)
-
-    idx_sample = Column(Integer, nullable=False)
-    seed = Column(BigInteger, nullable=False)
-    is_done_flag = Column(Integer, nullable=False)  # -1, waiting; 0, running; 1, done
-    computer_name = Column(String(64), nullable=True)
-    ts_done = Column(DateTime(timezone=True), onupdate=func.now())
-    stop_t = Column(Integer, nullable=True)
-
-    c1_wealth = Column(DECIMAL(20, 2), nullable=True)  # country 1, developing countries
-    c2_wealth = Column(DECIMAL(20, 2), nullable=True)  # country 2, developed countries
-    c1_wealth_dgt = Column(Integer, nullable=True)
-    c2_wealth_dgt = Column(Integer, nullable=True)
-    c1_tariff = Column(DECIMAL(20, 2), nullable=True)  # country 1, developing countries
-    c2_tariff = Column(DECIMAL(20, 2), nullable=True)  # country 2, developed countries
-    c1_tariff_dgt = Column(Integer, nullable=True)
-    c2_tariff_dgt = Column(Integer, nullable=True)
-    c1_n_firms = Column(Integer, nullable=True)
-    c2_n_firms = Column(Integer, nullable=True)
-    c1_n_positive_firms = Column(Integer, nullable=True)
-    c2_n_positive_firms = Column(Integer, nullable=True)
-    network = Column(Text(4294000000), nullable=True)
-    network_order = Column(Text(4294000000), nullable=True)
-    network_country = Column(Text(4294000000), nullable=True)
-
-    experiment = relationship('Experiment', back_populates='sample', uselist=False)
-    product = relationship('Product', back_populates='sample', lazy='dynamic')
-
-    def __repr__(self):
-        return f'<Sample id: {self.id}>'
-
-
-class Product(Base):
-    __tablename__ = f"{db_name_prefix}_product"
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    s_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_sample")), nullable=False)
-
-    int_name = Column(Integer, nullable=False)
-    int_tier = Column(Integer, nullable=False)
-    n_up_products = Column(Integer, nullable=False)
-    n_peer_products = Column(Integer, nullable=False)
-    n_positive_firms = Column(Integer, nullable=False)
-    n_all_firms = Column(Integer, nullable=False)
-    gini_acc_demand_per_age = Column(DECIMAL(10, 2), nullable=False)
-    gini_acc_wealth_per_age = Column(DECIMAL(10, 2), nullable=False)
-    gini_acc_demand_per_age_all = Column(DECIMAL(10, 2), nullable=False)
-    gini_acc_wealth_per_age_all = Column(DECIMAL(10, 2), nullable=False)
-    # lst_n_positive_firms = Column(Text(4294000000), nullable=False)
-    # lst_n_all_firms = Column(Text(4294000000), nullable=False)
-    # lst_gini_acc_demand_per_age = Column(Text(4294000000), nullable=False)
-    # lst_gini_acc_wealth_per_age = Column(Text(4294000000), nullable=False)
-    # lst_gini_acc_demand_per_age_all = Column(Text(4294000000), nullable=False)
-    # lst_gini_acc_wealth_per_age_all = Column(Text(4294000000), nullable=False)
-
-    sample = relationship('Sample', back_populates='product', uselist=False)
-    firm = relationship('Firm', back_populates='product', lazy='dynamic')
-
-    def __repr__(self):
-        return f'<Product id: {self.id}>'
-
-
-class Firm(Base):
-    __tablename__ = f"{db_name_prefix}_firm"
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    p_id = Column(Integer, ForeignKey('{}.id'.format(f"{db_name_prefix}_product")), nullable=False)
-
-    idx_firm = Column(Integer, nullable=False)
-    int_n_supplier = Column(Integer, nullable=False)
-    flt_fix_cost = Column(DECIMAL(20, 2), nullable=False)
-    flt_q_star = Column(DECIMAL(20, 2), nullable=False)
-    acc_demand_per_age = Column(DECIMAL(20, 2), nullable=False)
-    acc_wealth_per_age = Column(DECIMAL(20, 2), nullable=False)
-    std_demand_per_age = Column(DECIMAL(20, 2), nullable=False)
-
-    product = relationship('Product', back_populates='firm', uselist=False)
-
-    def __repr__(self):
-        return f'<Firm id: {self.id}>'
-
-
-if __name__ == '__main__':
-    Base.metadata.drop_all()
-    Base.metadata.create_all()

requirements.txt

@@ -8,7 +8,6 @@ cycler==0.11.0
 decorator==5.1.1
 dill==0.3.6
 docutils==0.19
-greenlet==2.0.2
 idna==3.4
 imagesize==1.4.1
 importlib-metadata==6.0.0
@@ -19,7 +18,6 @@ MarkupSafe==2.1.2
 matplotlib==3.3.4
 matplotlib-inline==0.1.6
 multiprocess==0.70.14
-mysqlclient==2.1.1
 networkx==2.5
 numpy==1.20.3
 numpydoc==1.1.0
@@ -28,11 +26,10 @@ pandas==1.4.1
 pandas-stubs==1.2.0.39
 Pillow==9.4.0
 Pygments==2.14.0
-pygraphviz @ file:///C:/Users/ASUS/Downloads/pygraphviz-1.9-cp38-cp38-win_amd64.whl
+pygraphviz @ file:///C:/Users/ASUS/OneDrive/Project/ScrAbm/Dissertation/IIabm/pygraphviz-1.9-cp38-cp38-win_amd64.whl
 pyparsing==3.0.9
 python-dateutil==2.8.2
 pytz==2022.7.1
-PyYAML==6.0
 requests==2.28.2
 SALib==1.4.7
 scipy==1.10.1
@@ -45,10 +42,7 @@ sphinxcontrib-htmlhelp==2.0.1
 sphinxcontrib-jsmath==1.0.1
 sphinxcontrib-qthelp==1.0.3
 sphinxcontrib-serializinghtml==1.1.5
-SQLAlchemy==2.0.5.post1
 traitlets==5.9.0
-typing_extensions==4.5.0
 urllib3==1.26.14
 wincertstore==0.2
-yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
 zipp==3.15.0