write code for decision matrix method in python

main.py
import numpy as np

# Define the decision alternatives (rows) and criteria (columns)
alternatives = ['A', 'B', 'C']
criteria = ['Price', 'Quality', 'Delivery', 'Service']

# Define the criteria weights and check if they sum up to 1.0
weights = [0.3, 0.4, 0.2, 0.1]
if np.abs(np.sum(weights) - 1.0) > 1e-10:
    raise ValueError('Weights do not sum up to 1.0')

# Define the decision matrix as a 2D array
decision_matrix = np.array([[100, 80, 90, 70],
                            [90, 70, 80, 90],
                            [80, 90, 70, 80]])

# Multiply each alternative by its criteria weight to obtain the weighted scores
weighted_matrix = decision_matrix * weights

# Normalize the weighted scores by dividing them by the maximum score for each criteria
normalized_matrix = weighted_matrix / np.max(weighted_matrix, axis=0)

# Multiply the normalized scores by 100 to obtain percentages
percent_matrix = normalized_matrix * 100

# Sum up the percentages for each alternative to obtain the total score
total_scores = np.sum(percent_matrix, axis=1)

# Rank the alternatives based on their total score in descending order
ranked_indices = np.argsort(total_scores)[::-1]
ranked_alternatives = [alternatives[i] for i in ranked_indices]

print('Decision matrix:')
print(decision_matrix)
print('Weighted matrix:')
print(weighted_matrix)
print('Normalized matrix:')
print(normalized_matrix)
print('Percentage matrix:')
print(percent_matrix)
print('Total scores:')
print(total_scores)
print('Ranked alternatives:')
print(ranked_alternatives)
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main.py
Decision matrix:
[[100  80  90  70]
 [ 90  70  80  90]
 [ 80  90  70  80]]
Weighted matrix:
[[30.  32.  18.  7. ]
 [27.  28.  16.  9. ]
 [24.  36.  14.  8. ]]
Normalized matrix:
[[1.         0.88888889 1.         0.77669903]
 [0.9        0.77777778 0.88888889 1.        ]
 [0.8        1.         0.77777778 0.89655172]]
Percentage matrix:
[[100.          88.88888889 100.           77.66990317]
 [ 90.          77.77777778  88.88888889 100.        ]
 [ 80.         100.          77.77777778  89.65517241]]
Total scores:
[366.55869043 356.66666667 347.43395062]
Ranked alternatives:
['A', 'B', 'C']
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