src.test.test_general_method API documentation

# src.test.test_general_method

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     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): View Source

    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(): View Source

    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.