Python中动态重构Vector AutoRegression(VAR)算法输出字典的实现求助

I've got you covered with a dynamic function that will handle any set of vital signs your VAR algorithm outputs—no hardcoding needed! Here's how to do it:

Approach #

The core idea is straightforward:

1. Grab the fixed Date value from your input dictionary
2. Loop through every other key (your dynamic vital signs)
3. For each vital sign, build a nested dictionary containing the date-value pair plus the fixed risk_value: 1

The Code #

def transform_var_output(input_dict):
    # Extract the date from the input (since it's always present)
    record_date = input_dict['Date']
    # Initialize an empty dictionary to hold our transformed result
    transformed_data = {}
    
    # Iterate over all key-value pairs in the input
    for vital_sign, value in input_dict.items():
        # Skip the 'Date' key since we handle it separately
        if vital_sign == 'Date':
            continue
        # Build the nested structure for each vital sign
        transformed_data[vital_sign] = {
            record_date: value,
            'risk_value': 1
        }
    
    return transformed_data

Example Usage #

Let's test it with both of your sample inputs to prove it works dynamically:

Test with Original Sample Input

sample_input_1 = {
    'Date': '2021-05-07',
    'BMI': 40.53002073252068,
    'BP': 123.00463807559225,
    'BloodSugar': 126.85415609085157,
    'ThyroidFunction': 3.0,
    'TF': 5.0
}

print(transform_var_output(sample_input_1))

Output:

{
    'BMI': {'2021-05-07': 40.53002073252068, 'risk_value': 1},
    'BP': {'2021-05-07': 123.00463807559225, 'risk_value': 1},
    'BloodSugar': {'2021-05-07': 126.85415609085157, 'risk_value': 1},
    'ThyroidFunction': {'2021-05-07': 3.0, 'risk_value': 1},
    'TF': {'2021-05-07': 5.0, 'risk_value': 1}
}

Test with Dynamic Input (New Vital Signs)

sample_input_2 = {
    'Date': '2021-05-07',
    'weight': '170lbs',
    'height': '175cm',
    'BMI': 39.3252068004638,
    'BP': 104.530020707559225,
    'BloodSugar': 126.85415609085157,
}

print(transform_var_output(sample_input_2))

Output:

{
    'weight': {'2021-05-07': '170lbs', 'risk_value': 1},
    'height': {'2021-05-07': '175cm', 'risk_value': 1},
    'BMI': {'2021-05-07': 39.3252068004638, 'risk_value': 1},
    'BP': {'2021-05-07': 104.530020707559225, 'risk_value': 1},
    'BloodSugar': {'2021-05-07': 126.85415609085157, 'risk_value': 1}
}

Why This Works #

• It's fully dynamic: any new or changed vital signs (like cholestrolLevel or HeartRate) will automatically be included in the output without modifying the function
• It respects your requirement for fixed risk_value: 1
• It skips the Date key as instructed, using its value to populate each vital sign's nested dictionary

内容的提问来源于stack exchange，提问作者Karan Dewani