0209review: firm risk component + 2way interation on n_max_trial and cap_limit_level

.gitignore

@@ -1 +1,4 @@
 .idea/
+venv
+# intermediate file for analysis_firm_risk_component.ipynb (2GB)
+count_with_gfirm.csv

.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": "${workspaceFolder}\\main.py",
             "console": "integratedTerminal",
             "justMyCode": true,
             "args": [

SQL_duplicate_without_exp_tables.sql

@@ -0,0 +1,43 @@
+-- SQL script to duplicate without_exp tables from iiabmdb20260127 to iiabmdb
+-- This allows reusing previous experiment results as the baseline for new experiments
+
+-- Drop existing tables if they exist (optional - comment out if you want to keep existing data)
+DROP TABLE IF EXISTS iiabmdb.without_exp_result;
+
+DROP TABLE IF EXISTS iiabmdb.without_exp_sample;
+
+DROP TABLE IF EXISTS iiabmdb.without_exp_experiment;
+
+-- Create and copy without_exp_experiment table
+CREATE TABLE iiabmdb.without_exp_experiment LIKE iiabmdb20260127.without_exp_experiment;
+
+INSERT INTO
+    iiabmdb.without_exp_experiment
+SELECT *
+FROM iiabmdb20260127.without_exp_experiment;
+
+-- Create and copy without_exp_sample table
+CREATE TABLE iiabmdb.without_exp_sample LIKE iiabmdb20260127.without_exp_sample;
+
+INSERT INTO
+    iiabmdb.without_exp_sample
+SELECT *
+FROM iiabmdb20260127.without_exp_sample;
+
+-- Create and copy without_exp_result table
+CREATE TABLE iiabmdb.without_exp_result LIKE iiabmdb20260127.without_exp_result;
+
+INSERT INTO
+    iiabmdb.without_exp_result
+SELECT *
+FROM iiabmdb20260127.without_exp_result;
+
+-- Verify the copy
+SELECT 'without_exp_experiment' as table_name, COUNT(*) as row_count
+FROM iiabmdb.without_exp_experiment
+UNION ALL
+SELECT 'without_exp_sample', COUNT(*)
+FROM iiabmdb.without_exp_sample
+UNION ALL
+SELECT 'without_exp_result', COUNT(*)
+FROM iiabmdb.without_exp_result;

analysis/20260128experiment_result.csv

@@ -0,0 +1,10 @@
+idx_scenario,n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n,mean_count_firm_prod,mean_count_firm,mean_count_prod,mean_max_ts_firm_prod,mean_max_ts_firm,mean_max_ts_prod,mean_n_remove_firm_prod,mean_n_all_prod_remove_firm,mean_end_ts
+0,7,1,1,uniform,5.0000,0.5000,5,2,2.6036,2.6036,2.0808,1.0808,1.0808,1.0808,0.6044,0.2131,1.8726
+1,7,1,1,uniform,10.0000,0.5000,5,2,2.6817,2.6798,2.1509,1.1509,1.1509,1.1509,0.8539,0.2994,2.2829
+2,7,1,1,uniform,15.0000,0.5000,5,2,2.7181,2.7154,2.1827,1.1827,1.1827,1.1827,1.0015,0.3398,2.5124
+3,5,1,1,uniform,5.0000,0.5000,5,2,2.6036,2.6036,2.0808,1.0808,1.0808,1.0808,0.6044,0.2131,1.8726
+4,5,1,1,uniform,10.0000,0.5000,5,2,2.6832,2.6813,2.1518,1.1518,1.1518,1.1518,0.8543,0.2996,2.2840
+5,5,1,1,uniform,15.0000,0.5000,5,2,2.7196,2.7168,2.1838,1.1838,1.1838,1.1838,1.0046,0.3406,2.5189
+6,3,1,1,uniform,5.0000,0.5000,5,2,2.6042,2.6042,2.0815,1.0815,1.0815,1.0815,0.6046,0.2131,1.8754
+7,3,1,1,uniform,10.0000,0.5000,5,2,2.6891,2.6872,2.1575,1.1575,1.1575,1.1575,0.8674,0.3057,2.3349
+8,3,1,1,uniform,15.0000,0.5000,5,2,2.7280,2.7253,2.1928,1.1928,1.1928,1.1928,1.0196,0.3469,2.5918

analysis_sum_result.py

@@ -1,4 +1,5 @@
 from orm import engine
+from sqlalchemy import text
 import pandas as pd
 import networkx as nx
 import json
@@ -12,8 +13,8 @@ BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
 
 with open('SQL_analysis_risk.sql', 'r') as f:
     str_sql = f.read()
-result = pd.read_sql(sql=str_sql,
+with engine.connect() as conn:
-                     con=engine)
+    result = pd.read_sql(sql=text(str_sql), con=conn)
 result.to_csv('analysis\\count.csv',
               index=False,
               encoding='utf-8-sig')
@@ -23,10 +24,11 @@ print(result)
 plt.rcParams['font.sans-serif'] = 'SimHei'
 
 exp_id = 1
-G_bom_str = pd.read_sql(
+with engine.connect() as conn:
-    sql=f'select g_bom from iiabmdb.without_exp_experiment '
+    G_bom_str = pd.read_sql(
-        f'where id = {exp_id};',
+        sql=text(f'select g_bom from iiabmdb.without_exp_experiment '
-    con=engine)['g_bom'].tolist()[0]
+                 f'where id = {exp_id};'),
+        con=conn)['g_bom'].tolist()[0]
 G_bom = nx.adjacency_graph(json.loads(G_bom_str))
 pos = nx.nx_agraph.graphviz_layout(G_bom, prog="twopi", args="")
 node_labels = nx.get_node_attributes(G_bom, 'Name')
@@ -44,9 +46,10 @@ plt.close()
 plt.rcParams['font.sans-serif'] = 'SimHei'
 
 sample_id = 1
-G_firm_str = pd.read_sql(
+with engine.connect() as conn:
-    sql=f'select g_firm from iiabmdb.without_exp_sample where id = {exp_id};',
+    G_firm_str = pd.read_sql(
-    con=engine)['g_firm'].tolist()[0]
+        sql=text(f'select g_firm from iiabmdb.without_exp_sample where id = {exp_id};'),
+        con=conn)['g_firm'].tolist()[0]
 G_firm = nx.adjacency_graph(json.loads(G_firm_str))
 pos = nx.nx_agraph.graphviz_layout(G_firm, prog="twopi", args="")
 node_label = nx.get_node_attributes(G_firm, 'Name')

anova_visualization.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {

check_db.py

@@ -0,0 +1,19 @@
+from orm import engine
+from sqlalchemy import text
+import pandas as pd
+import networkx as nx
+import json
+import matplotlib.pyplot as plt
+
+# prep data
+Firm = pd.read_csv("Firm_amended.csv")
+Firm['Code'] = Firm['Code'].astype('string')
+Firm.fillna(0, inplace=True)
+BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
+
+with open('SQL_analysis_risk.sql', 'r') as f:
+    str_sql = f.read()
+str_sql = str_sql.replace('iiabmdb', 'iiabmdb20260127')
+with engine.connect() as conn:
+    result = pd.read_sql(sql=text(str_sql), con=conn)
+print(result)

computation.py

@@ -1,5 +1,6 @@
 import os
 import datetime
+import time
 
 from model import Model
 
@@ -21,6 +22,9 @@ class Computation:
 
         # lock this row by update is_done_flag to 0
         self.c_db.lock_the_sample(sample_random)
+        
+        # Record start time
+        start_time = time.time()
         print(
             f"Pid {self.pid} ({str_code}) is running "
             f"sample {sample_random.id} at {datetime.datetime.now()}")
@@ -34,6 +38,14 @@ class Computation:
                            **dct_exp}
         model = Model(dct_sample_para)
         results = model.run(display=False)
+        
+        # Calculate elapsed time
+        elapsed_time = time.time() - start_time
+        print(
+            f"Pid {self.pid} ({str_code}) completed "
+            f"sample {sample_random.id} in {elapsed_time:.2f} seconds "
+            f"(stopped at t={sample_random.stop_t})")
+        
         return False
 
 

controller_db.py

@@ -56,7 +56,8 @@ class ControllerDB:
         if self.is_with_exp:
             with open('SQL_export_high_risk_setting.sql', 'r') as f:
                 str_sql = f.read()
-            result = pd.read_sql(sql=str_sql, con=engine)
+            with engine.connect() as conn:
+                result = pd.read_sql(sql=text(str_sql), con=conn)
             result['dct_lst_init_disrupt_firm_prod'] = \
                 result['dct_lst_init_disrupt_firm_prod'].apply(
                 lambda x: pickle.loads(x))
@@ -261,5 +262,8 @@ class ControllerDB:
 
     @staticmethod
     def lock_the_sample(sample: Sample):
-        sample.is_done_flag, sample.computer_name = 0, platform.node()
+        from datetime import datetime
+        sample.is_done_flag = 0
+        sample.computer_name = platform.node()
+        sample.ts_start = datetime.now()
         db_session.commit()

model.py

@@ -447,6 +447,7 @@ class Model(ap.Model):
 
     def end(self):
         # print('/' * 20, 'output', '/' * 20)
+        from datetime import datetime
         
         qry_result = db_session.query(Result).filter_by(s_id=self.sample.id)
         if qry_result.count() == 0:
@@ -468,6 +469,12 @@ class Model(ap.Model):
                             lst_result_info.append(db_r)
             db_session.bulk_save_objects(lst_result_info)
             db_session.commit()
+        
+        # Calculate elapsed time if ts_start exists
+        if self.sample.ts_start is not None:
+            elapsed = (datetime.now() - self.sample.ts_start).total_seconds()
+            self.sample.elapsed_seconds = elapsed
+        
         self.sample.is_done_flag = 1
         self.sample.computer_name = platform.node()
         self.sample.stop_t = self.int_stop_ts

oa_with_exp.csv

@@ -1,37 +1,10 @@
-X12,X1,X2,X3,X13,X14,X15,X16,X4,X5,X6,X7,X8,X9,X10,X11,X17,X18,X19,X20,X21,X22,X23
+X12,X1,X2,X3,X13,X14,X15,X16
-0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,1,1,1
-1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1
+0,0,0,0,1,1,1,1
-2,0,0,0,2,2,2,2,0,0,0,0,0,0,0,0,2,2,2,2,2,2,2
+0,0,0,0,2,1,1,1
-0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,2,2,2,2
+1,0,0,0,0,1,1,1
-1,0,0,0,1,1,1,2,0,0,1,1,1,1,1,1,2,2,2,0,0,0,0
+1,0,0,0,1,1,1,1
-2,0,0,0,2,2,2,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1
+1,0,0,0,2,1,1,1
-0,0,0,1,0,1,2,0,1,1,0,0,0,1,1,1,1,2,2,0,1,1,2
+2,0,0,0,0,1,1,1
-1,0,0,1,1,2,0,1,1,1,0,0,0,1,1,1,2,0,0,1,2,2,0
+2,0,0,0,1,1,1,1
-2,0,0,1,2,0,1,2,1,1,0,0,0,1,1,1,0,1,1,2,0,0,1
+2,0,0,0,2,1,1,1
-0,0,1,0,0,2,1,0,1,1,0,1,1,0,0,1,2,1,2,1,0,2,1
-1,0,1,0,1,0,2,1,1,1,0,1,1,0,0,1,0,2,0,2,1,0,2
-2,0,1,0,2,1,0,2,1,1,0,1,1,0,0,1,1,0,1,0,2,1,0
-0,0,1,1,1,2,0,2,0,1,1,0,1,0,1,0,1,0,2,2,1,0,1
-1,0,1,1,2,0,1,0,0,1,1,0,1,0,1,0,2,1,0,0,2,1,2
-2,0,1,1,0,1,2,1,0,1,1,0,1,0,1,0,0,2,1,1,0,2,0
-0,0,1,1,1,2,1,0,1,0,1,1,0,1,0,0,0,2,1,2,2,1,0
-1,0,1,1,2,0,2,1,1,0,1,1,0,1,0,0,1,0,2,0,0,2,1
-2,0,1,1,0,1,0,2,1,0,1,1,0,1,0,0,2,1,0,1,1,0,2
-0,1,0,1,1,0,2,2,1,0,0,1,1,0,1,0,2,0,1,1,0,1,2
-1,1,0,1,2,1,0,0,1,0,0,1,1,0,1,0,0,1,2,2,1,2,0
-2,1,0,1,0,2,1,1,1,0,0,1,1,0,1,0,1,2,0,0,2,0,1
-0,1,0,1,1,1,2,2,0,1,1,1,0,0,0,1,0,1,0,0,2,2,1
-1,1,0,1,2,2,0,0,0,1,1,1,0,0,0,1,1,2,1,1,0,0,2
-2,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,2,0,2,2,1,1,0
-0,1,0,0,2,1,0,1,1,1,1,0,1,1,0,0,2,2,0,2,0,1,1
-1,1,0,0,0,2,1,2,1,1,1,0,1,1,0,0,0,0,1,0,1,2,2
-2,1,0,0,1,0,2,0,1,1,1,0,1,1,0,0,1,1,2,1,2,0,0
-0,1,1,1,2,1,1,1,0,0,0,0,1,1,0,1,0,0,2,1,2,0,2
-1,1,1,1,0,2,2,2,0,0,0,0,1,1,0,1,1,1,0,2,0,1,0
-2,1,1,1,1,0,0,0,0,0,0,0,1,1,0,1,2,2,1,0,1,2,1
-0,1,1,0,2,2,2,1,1,0,1,0,0,0,1,1,2,1,1,0,1,0,0
-1,1,1,0,0,0,0,2,1,0,1,0,0,0,1,1,0,2,2,1,2,1,1
-2,1,1,0,1,1,1,0,1,0,1,0,0,0,1,1,1,0,0,2,0,2,2
-0,1,1,0,2,0,1,2,0,1,0,1,0,1,1,0,1,2,0,1,1,2,0
-1,1,1,0,0,1,2,0,0,1,0,1,0,1,1,0,2,0,1,2,2,0,1
-2,1,1,0,1,2,0,1,0,1,0,1,0,1,1,0,0,1,2,0,0,1,2

oa_with_exp_interaction.csv

@@ -0,0 +1,15 @@
+X12,X1,X2,X3,X13,X14,X15,X16
+0,0,0,0,0,1,1,1
+0,0,0,0,1,1,1,1
+0,0,0,0,2,1,1,1
+1,0,0,0,0,1,1,1
+1,0,0,0,1,1,1,1
+1,0,0,0,2,1,1,1
+2,0,0,0,0,1,1,1
+2,0,0,0,1,1,1,1
+2,0,0,0,2,1,1,1
+,,,,,,,
+n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n
+15,TRUE,TRUE,uniform,5,0.3,3,3
+10,FALSE,FALSE,normal,10,0.5,5,2
+5,,,,15,0.7,7,1

orm.py

@@ -22,7 +22,7 @@ with open('conf_db_prefix.yaml') as file:
     db_name_prefix = dct_conf_db_prefix['db_name_prefix']
 
 
-str_login = 'mysql://{}:{}@{}:{}/{}'.format(dct_conf_db['user_name'],
+str_login = 'mysql+pymysql://{}:{}@{}:{}/{}'.format(dct_conf_db['user_name'],
                                             dct_conf_db['password'],
                                             dct_conf_db['address'],
                                             dct_conf_db['port'],
@@ -82,6 +82,8 @@ class Sample(Base):
     is_done_flag = Column(Integer, nullable=False)
     computer_name = Column(String(64), nullable=True)
     ts_done = Column(DateTime(timezone=True), onupdate=func.now())
+    ts_start = Column(DateTime(timezone=True), nullable=True)
+    elapsed_seconds = Column(DECIMAL(10, 2), nullable=True)
     stop_t = Column(Integer, nullable=True)
 
     g_firm = Column(Text(4294000000), nullable=True)

requirements.txt

@@ -1,7 +1,7 @@
 agentpy==0.1.5
 alabaster==0.7.13
 Babel==2.12.1
-certifi @ file:///C:/b/abs_85o_6fm0se/croot/certifi_1671487778835/work/certifi
+# certifi @ file:///C:/b/abs_85o_6fm0se/croot/certifi_1671487778835/work/certifi
 charset-normalizer==3.0.1
 colorama==0.4.6
 cycler==0.11.0
@@ -28,7 +28,7 @@ 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/Downloads/pygraphviz-1.9-cp38-cp38-win_amd64.whl
 pyparsing==3.0.9
 python-dateutil==2.8.2
 pytz==2022.7.1
@@ -50,5 +50,5 @@ traitlets==5.9.0
 typing_extensions==4.5.0
 urllib3==1.26.14
 wincertstore==0.2
-yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
+# yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
 zipp==3.15.0

xv_with_exp.csv

@@ -1,4 +1,4 @@
-n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n
+n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n
 7,TRUE,TRUE,uniform,5,0.3,3,3
 5,FALSE,FALSE,normal,10,0.5,5,2
 3,,,,15,0.7,7,1