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Having done some further investigation into this tutorials problem from the previous post (lecture 15) I further simplified the code to eliminate all the code in the first for loop except the line that creates the factor. I ran the code and expected to see all the modified b(i)'s as a result using the pause in the loop. But there was still a problem with the wrong number of parameters. Going back to some of my previous monkeying around with some of your examples, I recalled there being a function called factor(). Renaming factor to faktor the problem about the wrong number of parameters went away! So this example has at least two problems! This being the second one, and the first is the wrong code inside the 3rd loop evaluating A(i,j).
http://spoken-tutorial.org/watch/Scilab/Linear%2Bequations%2BGaussian%2BMethods/English/\r\nIn this tutorial the first loop in the code makes an UT array. Or, at least it's supposed to.\r\nLooking at this code using the debugger with breaks set at 32 and 34 I get the following results for the loop indexes: k=1, j=2, i=2 for the first iteration of the code.\r\nLine 32 shows the factor, line 34 shows the code to zero out the following columns below the index element.\r\nAt line 32: factor = A(2,1)/A(1,1) is evaluated at the given index values which is OK. A(1,1) to normalize the row and A(2,1) to get rid of the first col in the following row. That's OK.\r\nAt line 34 we get A(i,j)=A(i,j)-factor*A(k,j) which resolves to\r\nA(2,2)=A(2,2)-factor*A(1,2) using the i, j, k values. Not good!\r\nThis code should resolve to \r\nA(2,1)=A(2,1) - factor * A(1,1)\r\n to set A(2,1) to zero, the rest of the loop changes the other elements in this row by the same factor. So this loop is screwed up. If I change the code so A(2,1) is used where it should, the element is now zero, but the code shows an index error when I run it. So I'll have to monkey around with the code to make the UT array, but there is definitely a problem with this example! \r\nAnd the last loop back substitutes to get the solution: I hope the last loop works as I have not tried it yet!\r\nI modified the original code to make debugging simpler: I hard wired in the A and b arrays, and deleted the back substitution section, so I can focus only on the UT matrix code.
--> exec('C:\Users\MYPC\Desktop\IIT BOMBAY-SCILAB FDP 29.05.2023 to 03.06.2023\V-18 code\GaussJordanElimination.sci', -1)Enter the coeffiecient matrix : [0.7,1725;0.4352,-5.433]Enter the right-hand side matrix : [1739;3.271]--> GaussJordanElimination(A,b)at line 55 of function GaussJordanElimination ( C:\Users\MYPC\Desktop\IIT BOMBAY-SCILAB FDP 29.05.2023 to 03.06.2023\V-18 code\GaussJordanElimination.sci line 67 )With input arguments, return / resume expects output arguments.
can the newton raphson method be solved along with the fast decoupled method?
I am using Scilab 6.1.0 over Ubuntu 19.10. After executing the command GaussJordanElimination(A,b), I get the error "With input arguments, return / resume expects output arguments."
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Outline: * ગોસ એલિમિનેશન મેથડ એલ્ગોરીધમ ને સ્પસ્ટ કરવું * ગોસ એલિમિનેશન મેથડ માટે કોડ સ્પસ્ટ કરવા અને કોડ વાપરીને ઉદાહરણ હલ કરવા. * ગોસ જોર્ડન મેથડ એલ્ગોરીધમ ને સ્પસ્ટ કરવું * ગોસ જોર્ડન મેથડ માટે કોડ સ્પસ્ટ કરવા અને કોડ વાપરીને ઉદાહરણ હલ કરવા.
* ગોસ એલિમિનેશન મેથડ એલ્ગોરીધમ ને સ્પસ્ટ કરવું * ગોસ એલિમિનેશન મેથડ માટે કોડ સ્પસ્ટ કરવા અને કોડ વાપરીને ઉદાહરણ હલ કરવા. * ગોસ જોર્ડન મેથડ એલ્ગોરીધમ ને સ્પસ્ટ કરવું * ગોસ જોર્ડન મેથડ માટે કોડ સ્પસ્ટ કરવા અને કોડ વાપરીને ઉદાહરણ હલ કરવા.
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