Thank you !

Thank you for the suggestion!

haha thank you !

kzfaq.info/get/bejne/h9Oaitqmy9uln5s.htmlfeature=shared

hahaha i'll take that as a compliment

Because, I have checked, when I put 0.8 in that matrix, I get the result 0.1 for the lambda, instead of you get the result 0.03... and then when I change the value 0.8 to 0.2 in the that matrix, I get 0.03 for the lambda, it is the same as you write

@@renaldyjohan1541 matrix = np.array([ [0.80, 0.73, 0.59, 0.61, 1], [0.73, 0.80, 0.60, 0.66, 1], [0.59, 0.60, 0.80, 0.68, 1], [0.61, 0.66, 0.68, 0.80, 1], [1, 1, 1, 1, 0.80] ]) Vector = np.array([0.69, 0.71, 0.69, 0.70, 1]) weights = np.linalg.solve(matrix, vector) Result : array([0.18837377, 0.28487231, 0.29616708, 0.20566864, 0.03114775]) it is also slightly different here because in the animation it is showing rounded values but in the background it is using float values without decimal limitation, as you can see the values in the above code snippet are also slightly different from the animation but still the LaGrange multiplier is 0.03