47 frame_bytes = cv2.imencode(".jpg", frame)[1].tobytes()
48
49 # Send the telemetry data to the specified port
50 conn, addr = s.accept()51 conn.sendall(frame_bytes)
52 conn.close()
53
74 # Perform hierarchical clustering on the genetic markers
75 Z = sch.linkage(genomic_data[["Marker1", "Marker2", "Marker3"]], method="ward")
76 fig = plt.figure(figsize=(10, 5))
77 dn = sch.dendrogram(Z) 78 plt.show()
79
80
57 None
58 """
59 # Plot the distribution of each genetic marker
60 fig, axs = plt.subplots(3, 1, figsize=(10, 15)) 61 sns.histplot(genomic_data["Marker1"], ax=axs[0])
62 sns.histplot(genomic_data["Marker2"], ax=axs[1])
63 sns.histplot(genomic_data["Marker3"], ax=axs[2])
42 bci = qnx.BrainComputerInterface()
43
44 # Load the patient's brain data
45 brain_data = load_brain_data(patient_data["patient_id"])46
47 # Start the rehabilitation program
48 ...
51 """
52 X = interim_data[["MolecularWeight", "LogP", "HBA", "ROTB"]]
53 y = interim_data["Activity"]
54 X_train, X_test, y_train, y_test = train_test_split( 55 X, y, test_size=0.2, random_state=42
56 )
57 model = RandomForestClassifier(n_estimators=100, random_state=42)
An unused variable takes up space in the code, and can lead to confusion, and it should be removed. If this variable is necessary, name the variable _
to indicate that it will be unused, or start the name with unused
or _unused
.
def update():
for i in range(10): # Usused variable `i`
time.sleep(0.01)
display_result()
def update():
for _ in range(10):
time.sleep(0.01)
display_result()