moddeddot.py

import numpy as np

def modified_dot_product_and_sum_corrected(A, B):
    A = np.array(A)
    B = np.array(B)
    
    # Validate that A and B are 2D matrices
    if A.ndim != 2 or B.ndim != 2:
        raise ValueError("Both A and B must be 2D matrices.")
    
    # Get the shape of matrix A
    m, n = A.shape
    
    # Get the shape of matrix B
    p, q = B.shape
    
    # Create a new array to hold the result
    result = np.zeros((m, n, p, q))
    
    # Compute the modified dot product
    for i in range(m):
        for j in range(n):
            result[i, j] = A[i, j] * B
    
    # Sum across the first two axes to collapse into the shape of B
    final_result = result.sum(axis=0).sum(axis=0)
    return final_result

# Example matrices
A = [[3, 5], [7, 9]]
B = [[2, 8], [22, 19]]

# Calculate the modified dot product and then sum appropriately
result = modified_dot_product_and_sum_corrected(A, B)
print("Final Summed Result:")
print(result)
import numpy as np

def modified_dot_product_and_sum_corrected(A, B):
    A = np.array(A)
    B = np.array(B)
    
    # Validate that A and B are 2D matrices
    if A.ndim != 2 or B.ndim != 2:
        raise ValueError("Both A and B must be 2D matrices.")
    
    # Get the shape of matrix A
    m, n = A.shape
    
    # Get the shape of matrix B
    p, q = B.shape
    
    # Create a new array to hold the result
    result = np.zeros((m, n, p, q))
    
    # Compute the modified dot product
    for i in range(m):
        for j in range(n):
            result[i, j] = A[i, j] * B
    
    # Sum across the first two axes to collapse into the shape of B
    final_result = result.sum(axis=0).sum(axis=0)
    return final_result

# Example matrices
A = [[5, 6], [11, 12]]
B = [[1, 2], [3, 4]]

# Calculate the modified dot product and then sum appropriately
result = modified_dot_product_and_sum_corrected(A, B)
print("Final Summed Result:")
print(result)