Update README file (#5)

* Update README file.

* Move scripts for contingency file manipulations to one place.

Author: pelesh

LICENSE

@@ -1,9 +1,13 @@
 Copyright (c) 2026, UT-Battelle.
 All rights reserved.
 
-ExaGO™ version 2
+This work uses code from the ExaGO v1.6.0:
+Copyright (c) 2020-2025, Battelle Memorial Institute
+All rights reserved.
 
 
+ExaGO™ version 2
+
 Open Source License:
 
 Subject to the conditions of this License, UT-Battelle, LLC, hereby grants

README.md

@@ -64,8 +64,7 @@ Instructions for executing the different ExaGO<sup>TM</sup> applications is give
 - [SCOPFLOW](docs/web/scopflow.md)
 - [PFLOW](docs/web/pflow.md)
 
-We also provide our user manual as a pdf [manual.pdf](docs/manual/manual.pdf)
--> need to update this regularly with CI / move to quarto docs.
+We also provide our user manual as a pdf [manual.pdf](docs/manual/manual.pdf).
 
 ## Tutorials
 
@@ -84,7 +83,11 @@ Each application has a different set of options that are described in depth in
 the usage notes. These options can be passed optionally through an options file
 (`-optionsfile <option_file>`), or directly on the command line.
 
-Since options may be specified in more than one location (on the command line, and through an options file), it is worth noting that the option specified on the command line supersede those in the options file. For example, if `opflowoptions` options file set the network file via the option `-netfile case9mod.m`, the following behavior occurs:
+Since options may be specified in more than one location (on the command line,
+and through an options file), it is worth noting that the option specified on
+the command line supersede those in the options file. For example, if
+`opflowoptions` options file set the network file via the option
+`-netfile case9mod.m`, the following behavior occurs:
 
 ```bash
 # This uses case9mod.m
@@ -106,22 +109,11 @@ attempting to contribute. Feel free to raise an issue or contact the team if
 the guidelines are ambiguous or you have a particular question.
 
 ## Authors
-ExaGO<sup>TM</sup> was designed and implemented by Shrirang Abhyankar. It has
-received significant from following developers: 
-- Slaven Peles
-- Nicholson Koukpaizan
-- Maksudul Alam
-- Asher Mancinelli
-- Cameron Rutherford
-- Joshua Hambrick
-- Philip Fackler
-- Eve Tsybina
-- Bruce Palmer
-- Jaelyn Litzinger
-- William Perkins
-- Sayef Azad Sakin
-- Joseph Macam
-- Ryan Danehy
+ExaGO<sup>TM</sup> was designed and implemented by Shrirang Abhyankar and has
+received significant from Slaven Peles, Nicholson Koukpaizan, Maksudul Alam,
+Asher Mancinelli, Cameron Rutherford, Joshua Hambrick, Philip Fackler, Eve
+Tsybina, Bruce Palmer, Jaelyn Litzinger, William Perkins, Sayef Azad Sakin,
+Joseph Macam, and Ryan Danehy.
 
 ## Acknowledgement
 ExaGO<sup>TM</sup> has been originally developed as a part of
@@ -135,8 +127,7 @@ Copyright &copy; 2026, UT Battelle.
 ExaGO<sup>TM</sup> (v2) is a free software distributed under a BSD-style
 license. See the [LICENSE](LICENSE) and [NOTICE](NOTICE) files for details.
 All new contributions to ExaGO<sup>TM</sup> must be made under the same
-licensing terms. ExaGO<sup>TM</sup> v2 contains code from ExaGO v1.6.0,
-licensed under 2-clause BSD [license](LICENSE-1.6.0).
+licensing terms.
 
 Please Note If you are using ExaGO<sup>TM</sup> with any third party libraries
 linked in (e.g., CoinHSL), be sure to review the respective license of the

scripts/contingency_native_psse.py …contingencies/contingency_native_psse.pyscripts/contingency_native_psse.py renamed to datafiles/contingencies/contingency_native_psse.py scripts/contingency_native_psse.py renamed to datafiles/contingencies/contingency_native_psse.py

@@ -0,0 +1,121 @@
+input_file = r'case_ACTIVSg70k.m'
+output_folder = r'out'
+
+import os
+import re
+import pandas as pd
+
+def extract_matrix_with_headers(text, key):
+    pattern = rf"(?:%%[^\r\n]*[\r\n])?%[ \t]*([^\r\n]*)[\r\n]\s*mpc\.{key}\s*=\s*\[(.*?)\];"
+    match = re.search(pattern, text, re.DOTALL)
+    header_line = match.group(1).strip()
+    raw_headers = re.split(r'[ \t]+', header_line)
+    headers = raw_headers if any(not re.fullmatch(r'\d+', h) for h in raw_headers) else None
+    block = match.group(2)
+    lines = [line.strip().rstrip(';') for line in block.strip().split('\n') if line.strip()]
+    data = [list(map(float, re.split(r'[ \t]+', line))) for line in lines]
+    df = pd.DataFrame(data)
+    if headers and len(headers) == df.shape[1]:
+        df.columns = headers
+    return df
+
+def process_m_with_headers_df(m_file_path):
+    with open(m_file_path, 'r') as f:
+        content = f.read()
+    summary_index = content.find('mpc.summary')
+    if summary_index != -1:
+        content = content[:summary_index]
+    dfs = {}
+    for key in ['bus', 'gen', 'branch']:
+        df = extract_matrix_with_headers(content, key)
+        output_path = os.path.join(output_folder, f"{key}.csv")
+        #df.to_csv(output_path, index=False)
+        dfs[key] = df
+    df_load = dfs.get('bus')
+    df_gen = dfs.get('gen')
+    df_branch = dfs.get('branch')
+    return df_load, df_gen, df_branch
+
+df_load_initial, df_gen_initial, df_branch_initial = process_m_with_headers_df(input_file)
+
+df_load = df_load_initial[df_load_initial['Pd'] > 0].reset_index(drop=True)
+n_loads = df_load.shape[0]
+df_load = df_load.sort_values('bus_i').reset_index(drop=True)
+df_load['id_or_circuit'] = df_load.groupby('bus_i').cumcount() + 1
+
+df_gen = df_gen_initial[df_gen_initial['status'] == 1].reset_index(drop=True)
+n_gen = df_gen.shape[0]
+df_gen = df_gen.sort_values('bus').reset_index(drop=True)
+df_gen['id_or_circuit'] = df_gen.groupby('bus').cumcount() + 1
+
+df_branch = df_branch_initial[(df_branch_initial['status'] == 1) & (df_branch_initial['ratio'] == 0)].reset_index(drop=True)
+n_branch = df_branch.shape[0]
+df_branch = df_branch.sort_values(['fbus', 'tbus']).reset_index(drop=True)
+df_branch['id_or_circuit'] = df_branch.groupby(['fbus', 'tbus']).cumcount() + 1
+
+df_tr = df_branch_initial[(df_branch_initial['status'] == 1) & (df_branch_initial['ratio'] > 0)].reset_index(drop=True)
+n_tr = df_tr.shape[0]
+df_tr = df_tr.sort_values(['fbus', 'tbus']).reset_index(drop=True)
+df_tr['id_or_circuit'] = df_tr.groupby(['fbus', 'tbus']).cumcount() + 1
+
+def create_contingency_df(df, df_type):
+    cont_df = pd.DataFrame()
+    cont_df['Num'] = df.index + 1  # contingency numbers starting from 1
+    type_mapping = {'gen': 1, 'branch': 2, 'tr': 3, 'load': 4}
+    cont_df['Type'] = type_mapping[df_type]
+    if df_type == 'gen':
+        cont_df['Bus'] = df['bus']
+    elif df_type == 'load':
+        cont_df['Bus'] = df['bus_i']
+    else:  # branch or transformer
+        cont_df['Bus'] = 0
+    if df_type in ['branch', 'tr']:
+        cont_df['Fbus'] = df['fbus']
+    else:
+        cont_df['Fbus'] = 0
+    if df_type in ['branch', 'tr']:
+        cont_df['Tbus'] = df['tbus']
+    else:
+        cont_df['Tbus'] = 0
+    cont_df['Id'] = df['id_or_circuit']
+    cont_df['Status'] = 0
+    cont_df['Prob'] = 0.001
+    return cont_df
+
+df_gen_cont = create_contingency_df(df_gen, 'gen')
+df_load_cont = create_contingency_df(df_load, 'load')
+df_branch_cont = create_contingency_df(df_branch, 'branch')
+df_tr_cont = create_contingency_df(df_tr, 'tr')
+
+df_all = pd.concat([df_gen_cont, df_load_cont, df_branch_cont, df_tr_cont], ignore_index=True)
+df_all = df_all.sample(frac=1, random_state=42).reset_index(drop=True)  # random_state for reproducibility
+df_all['Num'] = df_all.index + 1  # start from 1 if you like
+#df_all.to_csv('cont.csv', header=False, index=False)
+
+columns_order = ['Num', 'Type', 'Bus', 'Fbus', 'Tbus', 'Id', 'Status', 'Prob']
+df_all['Num'] = df_all['Num'].astype(int)
+df_all['Type'] = df_all['Type'].astype(int)
+df_all['Bus'] = df_all['Bus'].astype(int)
+df_all['Fbus'] = df_all['Fbus'].astype(int)
+df_all['Tbus'] = df_all['Tbus'].astype(int)
+df_all['Id'] = df_all['Id'].astype(str)
+df_all['Status'] = df_all['Status'].astype(int)
+df_all['Prob'] = df_all['Prob'].astype(float)
+df_txt = df_all[columns_order]
+
+df_txt.to_csv('70thousandbus.cont', sep=',', header=False, index=False, float_format='%.3f', lineterminator='\n')
+
+with open('70thousandbus.cont', 'r') as f:
+    lines = f.readlines()
+with open('70thousandbus.cont', 'w') as f:
+    for line in lines:
+        parts = [p.strip() for p in line.strip().split(',')]
+        padded = []
+        for i, p in enumerate(parts):
+            if i in [0,1,2,3,4,6]:   # integer columns
+                padded.append(f'{int(p):>5}')
+            elif i == 5:              # string column
+                padded.append(f"'{p}'")
+            else:                     # float column
+                padded.append(f'{float(p):>6.3f}')
+        f.write(', '.join(padded) + '\n')