def show_account(self):
if self.node_csv_files is not None:
if len(self.node_csv_files[0]) == 5:
df = pd.read_csv(self.node_csv_files[0][0])
s = pandasModel(df)
self.show_content_table.setModel(s)
self.show_content_table.update()
else:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files correctly")
msg.setWindowTitle("Error")
msg.exec_()
else:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files")
msg.setWindowTitle("Error")
msg.exec_()
def analyze_data(self):
if self.node_csv_files is None or self.edge_csv_files is None:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files")
msg.setWindowTitle("Error")
msg.exec_()
elif len(self.edge_csv_files[0]) != 4 or len(
self.node_csv_files[0]) != 5:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files correctly")
msg.setWindowTitle("Error")
msg.exec_()
else:
'''phase 2---------------------------------------------------------------------------------'''
df = pd.read_csv(self.node_csv_files[0][3])
df = df[(df['work'].str.contains("بندر")) |
(df['work'].str.contains('گمرک'))]
# dataFrame = pd.read_csv("relationship.csv")
df = df.rename(columns={'ssn': 'from'})
flag_data_frame = pd.merge(df,
pd.read_csv(self.edge_csv_files[0][2]),
on=['from'],
how='inner')
# flag_data_frame = flag_data_frame.drop_duplicates()
dataf = pd.read_csv(self.edge_csv_files[0][1])
flag_data_frame1 = flag_data_frame.drop([
'to', 'relation', 'date', 'first_name', 'last_name',
'birthday', 'work', 'city'
],
axis=1)
flag_data_frame1 = pd.merge(flag_data_frame1,
dataf,
on=['from'],
how='inner')
flag_data_frame1 = flag_data_frame1.drop_duplicates()
flag_data_frame1.to_csv('noni.csv', index=False)
# print(flag_data_frame1)
flag_data_frame2 = flag_data_frame.drop([
'from', 'relation', 'date', 'first_name', 'last_name',
'birthday', 'work', 'city'
],
axis=1)
flag_data_frame2 = flag_data_frame2.rename(columns={'to': 'from'})
flag_data_frame2 = pd.merge(flag_data_frame2,
dataf,
on=['from'],
how='inner')
flag_data_frame2 = flag_data_frame2.drop_duplicates()
# print(flag_data_frame2)
flag_data_frame2 = pd.concat([flag_data_frame2, flag_data_frame1],
axis=0,
sort=False)
flag_data_frame2 = flag_data_frame2.drop_duplicates()
print(flag_data_frame2)
# flag_data_frame2.to_csv('noni.csv', index=False)
'''--------------------------------------------------------------------------------------'''
'''phase3--------------------------------------------------------------------------------'''
logger = mp.log_to_stderr(logging.DEBUG)
def worker(inqueues, outputs):
result = []
count = 0
for pair in iter(inqueues.get, sentinel):
source, target = pair
try:
y = isPath(tr, source=source, target=target)
# r = nx.all_simple_paths(tr, source=source, target=target, cutoff=10)
if y:
print(source, target)
result.append((source, target))
count += 1
if count % 10 == 0:
logger.info('{c}'.format(c=count))
except:
continue
outputs.put(result)
def test_workers():
result = []
inqueue = mp.Queue()
for source, target in IT.product(sources, targets):
inqueue.put((source, target))
procs = [
mp.Process(target=worker, args=(inqueue, output))
for _ in range(mp.cpu_count() - 1)
]
for proc in procs:
proc.daemon = True
proc.start()
for proc in procs:
inqueue.put(sentinel)
for proc in procs:
result.extend(output.get())
for proc in procs:
proc.join()
return result
sentinel = None
transaction = pd.read_csv(self.edge_csv_files[0][3])
tr = pandas_to_graph(transaction, 'from', 'to')
df = pd.read_csv(self.node_csv_files[0][3])
employees = df[(df['work'].str.contains("بندر")) |
(df['work'].str.contains('گمرک'))]
smugglers = df[df['work'].str.contains('قاچاقچی')]
smugglers = pd.merge(smugglers,
pd.read_csv(self.node_csv_files[0][0]),
on=['ssn'],
how='inner')
employees = pd.merge(employees,
pd.read_csv(self.node_csv_files[0][0]),
on=['ssn'],
how='inner')
sources = list(smugglers['account_id'])
targets = list(employees['account_id'])
# print(len(sources), len(targets))
output = mp.Queue()
s = test_workers()
rel = pd.DataFrame(s, columns=['from', 'to'])
# rel.to_csv('reli.csv', index=False)
print("finish")
print(rel)
'''---------------------------------------------------------------------------------------------'''
'''phase4---------------------------------------------------------------------------------------'''
rel = rel.rename(columns={'from': 'account_id'})
f = pd.merge(rel,
pd.read_csv(self.node_csv_files[0][0]),
on=['account_id'],
how='inner')
f = f.drop(['to', 'account_id', 'bank_name', 'IBAN'], axis=1)
rel = rel.rename(columns={'account_id': 'from'})
rel = rel.rename(columns={'to': 'account_id'})
t = pd.merge(rel,
pd.read_csv(self.node_csv_files[0][0]),
on=['account_id'],
how='inner')
t = t.drop(['from', 'account_id', 'bank_name', 'IBAN'], axis=1)
f = pd.merge(f,
pd.read_csv(self.node_csv_files[0][4]),
on=['ssn'],
how='left')
t = pd.merge(t,
pd.read_csv(self.node_csv_files[0][4]),
on=['ssn'],
how='left')
f = f.drop(['ssn', 'operator'], axis=1)
f = f.rename(columns={'number': 'from'})
t = t.drop(['ssn', 'operator'], axis=1)
t = t.rename(columns={'number': 'to'})
concat = pd.concat([f, t], axis=1, sort=False)
concat = concat.dropna()
concat = concat.reset_index(drop=True)
concat = concat.astype(int)
concat = concat.drop_duplicates(subset='to')
print(concat)
w = pd.merge(concat,
pd.read_csv(self.edge_csv_files[0][0]),
on=['from', 'to'],
how='inner')
concat = concat.rename(columns={'from': 'to', 'to': 'from'})
x = pd.merge(concat,
pd.read_csv(self.edge_csv_files[0][0]),
on=['from', 'to'],
how='inner')
x = x[['from', 'to', 'call_id', 'date', 'duration']]
print(x)
# print(concat)
print(w)
z = pd.concat([w, x], axis=0)
self.result = z
print(z)
if z.empty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("We didn't find Embezzler")
msg.setWindowTitle("info")
msg.exec_()
else:
r = pandasModel(z)
self.show_content_table.setModel(r)
self.show_content_table.update()
def show_contents(self):
fr = str(self.from_lineEdit.text())
to = str(self.to_lineEdit.text())
relation = str(self.relation_lineEdit.text())
if self.node_csv_files is None or self.edge_csv_files is None:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files")
msg.setWindowTitle("Error")
msg.exec_()
elif len(self.edge_csv_files[0]) != 4 or len(
self.node_csv_files[0]) != 5:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("You didn't choose files correctly")
msg.setWindowTitle("Error")
msg.exec_()
elif self.from_lineEdit.text() == "" and self.to_lineEdit.text(
) == "" and self.relation_lineEdit.text() == "":
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("All line edits are empty")
msg.setWindowTitle("Error")
msg.exec_()
elif fr != "" and to == "" and relation == "":
from_text = str(self.from_comboBox.currentText())
from_sub_text = str(self.sub_comboBox.currentText())
if from_sub_text == "ssn" or from_sub_text == "price" or from_sub_text == 'postal code' \
or from_sub_text == "size" or from_sub_text == "account number":
flag = fr.isdigit()
if flag:
df = pd.read_csv(from_text + ".csv")
w = df[df[from_sub_text] == int(fr)]
dataframeIsEmpty = w.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(w)
self.show_content_table.setModel(s)
self.show_content_table.update()
else:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Your input must be digit")
msg.setWindowTitle("Error")
msg.exec_()
else:
df = pd.read_csv(from_text + ".csv")
w = df[df[from_sub_text] == str(fr)]
dataframeIsEmpty = w.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(w)
self.show_content_table.setModel(s)
self.show_content_table.update()
elif (fr == "" and to == "") or (fr == "" and relation == "") or (
to == "" and relation == ""):
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
else:
from_text = str(self.from_comboBox.currentText())
from_sub_text = str(self.sub_comboBox.currentText())
to_text = str(self.to_comboBox.currentText())
to_sub_text = str(self.sub_to_comboBox.currentText())
relation_text = str(self.relation_combobox.currentText())
relation_sub_text = str(self.sub_relation_combobox.currentText())
if relation_text == "relationship":
if from_text != "person" or from_sub_text != "ssn" or to_text != "person" or to_sub_text != "ssn" \
or fr.isdigit() is False or to.isdigit() is False or relation_sub_text == "":
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
else:
df = pd.read_csv(relation_text + ".csv")
df = df[(df['from'] == int(fr)) & (df['to'] == int(to)) &
(df[relation_sub_text] == relation)]
dataframeIsEmpty = df.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(df)
self.show_content_table.setModel(s)
self.show_content_table.update()
elif relation_text == "transaction":
if from_text != "account" or from_sub_text != "account_id" or to_text != "account" \
or to_sub_text != "account_id" or fr.isdigit() is False \
or to.isdigit() is False or relation_sub_text == "":
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
else:
df = pd.read_csv(relation_text + ".csv")
if relation.isdigit():
df = df[(df['from'] == int(fr)) & (df['to'] == int(to))
& (df[relation_sub_text] == int(relation))]
else:
df = df[(df['from'] == int(fr)) & (df['to'] == int(to))
& (df[relation_sub_text] == str(relation))]
dataframeIsEmpty = df.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(df)
self.show_content_table.setModel(s)
self.show_content_table.update()
elif relation_text == "ownership":
if from_text != "person" or from_sub_text != "ssn" \
or fr.isdigit() is False or relation_sub_text == "":
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
else:
df = pd.read_csv(relation_text + ".csv")
if to_sub_text == "plate":
if relation.isdigit():
df = df[(df['from'] == int(fr)) & (df['to'] == to)
& (df[relation_sub_text] == int(relation))]
else:
df = df[(df['from'] == int(fr)) & (df['to'] == to)
& (df[relation_sub_text] == relation)]
elif to_sub_text == "postal_code":
if to.isdigit():
if relation.isdigit():
df = df[(df['from'] == int(fr))
& (df['to'] == to) &
(df[relation_sub_text]
== int(relation))]
else:
df = df[(df['from'] == int(fr))
& (df['to'] == to) &
(df[relation_sub_text] == relation)]
else:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
return
else:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
return
dataframeIsEmpty = df.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(df)
self.show_content_table.setModel(s)
self.show_content_table.update()
elif relation_text == "contact":
if from_text != "phone" or to_text != "phone" or from_sub_text != "number" or to_sub_text != "number" \
or fr.isdigit() is False or to.isdigit() is False:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("Wrong input method")
msg.setWindowTitle("Error")
msg.exec_()
else:
df = pd.read_csv(relation_text + ".csv")
if relation.isdigit():
df = df[(df['from'] == int(fr)) & (df['to'] == int(to))
& (df[relation_sub_text] == int(relation))]
else:
df = df[(df['from'] == int(fr)) & (df['to'] == int(to))
& (df[relation_sub_text] == relation)]
dataframeIsEmpty = df.empty
if dataframeIsEmpty:
msg = QMessageBox()
msg.setIcon(QMessageBox.Critical)
msg.setText("No information found")
msg.setWindowTitle("Error")
msg.exec_()
else:
s = pandasModel(df)
self.show_content_table.setModel(s)
self.show_content_table.update()