r"""
Populate the cast128 database.
"""
import datetime
import json
import psycopg2
from boolean_cayley_graphs.bent_function import BentFunction
from boolean_cayley_graphs.bent_function_cayley_graph_classification import BentFunctionCayleyGraphClassification
from boolean_cayley_graphs.classification_database_psycopg2 import *
with open("BCG-DB.json") as auth_file:
auth = json.load(auth_file)
conn = create_classification_tables(
"cast128",
user=auth["user"],
password=auth["passwd"],
host=auth["host"])
for i in range(1,9):
stri = "%01d" % i
for j in range(32):
strj = "%02d" % j
sobj_name = "cast128_" + stri + "_" + str(j) + ".sobj"
name = "cast128_" + stri + "_" + strj
cgc = BentFunctionCayleyGraphClassification.load_mangled(
sobj_name,
directory="/data/sobj")
print(datetime.datetime.now(), stri, strj)
insert_classification(conn, cgc, name)
print(datetime.datetime.now())
curs = conn.cursor()
print(datetime.datetime.now(), "before")
curs.execute("SELECT COUNT(*) FROM cayley_graph")
print(datetime.datetime.now(), "after")
for row in curs:
for x in row:
print(x)
print(datetime.datetime.now(), "before")
curs.execute("SELECT COUNT(*) FROM graph")
print(datetime.datetime.now(), "after")
for row in curs:
for x in row:
print(x)
cgc1 = select_classification_where_name(
conn,
"cast128_1_09")
cgc1.report()
cgc2 = BentFunctionCayleyGraphClassification.load_mangled(
"cast128_1_9",
directory="/data/sobj")
bentf = BentFunction(cgc.algebraic_normal_form)
cgc3 = select_classification_where_bent_function(
conn,
bentf)
cgc3.report()
conn.close()