src.test.test_general_method

 1import pandas as pd
 2import sys
 3import os
 4import numpy as np
 5sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
 6from general_method import run_general_method
 7
 8def generate_synthetic_dataset(num_users=5, num_values=10):
 9    """
10    Generates a synthetic dataset for testing.
11
12    Args:
13        num_users (int): The number of users to generate in the dataset (default is 5).
14        num_values (int): The number of values per user in the dataset (default is 10).
15
16    Returns:
17        pd.DataFrame: A DataFrame containing the synthetic dataset with user IDs and associated values.
18    
19    The dataset contains two columns:
20        - 'user': A list of user IDs in the form 'u1', 'u2', ..., 'un'.
21        - 'values': A list of values assigned to each user, with each user having a list of randomly chosen "AOI" values.
22    """
23    data = {
24        "user": [f"u{i+1}" for i in range(num_users)],
25        "values": [np.random.choice([f"AOI {str(i+1).zfill(3)}" for i in range(3)], num_values).tolist() for _ in range(num_users)]
26    }
27    return pd.DataFrame(data)
28
29def test_general_method():
30    """
31    Tests the general method with a generated synthetic dataset.
32
33    Generates a synthetic dataset and passes it to the `run_general_method` function for processing.
34    """
35    df = generate_synthetic_dataset()
36    run_general_method(df)
37
38if __name__ == "__main__":
39    test_general_method()
def generate_synthetic_dataset(num_users=5, num_values=10):
10def generate_synthetic_dataset(num_users=5, num_values=10):
11    """
12    Generates a synthetic dataset for testing.
13
14    Args:
15        num_users (int): The number of users to generate in the dataset (default is 5).
16        num_values (int): The number of values per user in the dataset (default is 10).
17
18    Returns:
19        pd.DataFrame: A DataFrame containing the synthetic dataset with user IDs and associated values.
20    
21    The dataset contains two columns:
22        - 'user': A list of user IDs in the form 'u1', 'u2', ..., 'un'.
23        - 'values': A list of values assigned to each user, with each user having a list of randomly chosen "AOI" values.
24    """
25    data = {
26        "user": [f"u{i+1}" for i in range(num_users)],
27        "values": [np.random.choice([f"AOI {str(i+1).zfill(3)}" for i in range(3)], num_values).tolist() for _ in range(num_users)]
28    }
29    return pd.DataFrame(data)

Generates a synthetic dataset for testing.

Args: num_users (int): The number of users to generate in the dataset (default is 5). num_values (int): The number of values per user in the dataset (default is 10).

Returns: pd.DataFrame: A DataFrame containing the synthetic dataset with user IDs and associated values.

The dataset contains two columns: - 'user': A list of user IDs in the form 'u1', 'u2', ..., 'un'. - 'values': A list of values assigned to each user, with each user having a list of randomly chosen "AOI" values.

def test_general_method():
31def test_general_method():
32    """
33    Tests the general method with a generated synthetic dataset.
34
35    Generates a synthetic dataset and passes it to the `run_general_method` function for processing.
36    """
37    df = generate_synthetic_dataset()
38    run_general_method(df)

Tests the general method with a generated synthetic dataset.

Generates a synthetic dataset and passes it to the run_general_method function for processing.