1. X-0:0.5 5, X is row vecter has . clements. 2. To detemine the dimensions of a matrix or vector, use the command . 3. MATLAB uses a default variable ....... to store the results of the current calculation.
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- What to input here to run properly? % Encode the Matrix A and the column vector b. A= b= % Solve for Determinant of A. Set as dA. dA = % Find the Inverse of A. set as iA. iA = % Form the Reduced Row Echelon of A. Set as rA. rA= %Find the number of rows and number of columns of Ab. set as rowA and colA. % Find the sum of the columns of A. Set as SumA. %In each of the columns of A, find the highest values and its indices.Set as highA and locA. %Augment A with b; Set as Ab. % Find b\A. Set as Root1. %Form the Reduced Row Echelon Form of Ab. Set as refAb. %Extract the last column of refAb.Set as Root2. %Create a matrix A whose elements are the same as matrix A, but the first column is the column vector b. Set as Ax. %Create a matrix A whose elements are the same as matrix A, but the second column is the column vector b. Set as Ay. %Create a matrix A whose elements are the same as matrix A, but the third column is the column vector b. Set as Az. %Create…Create a MATLAB function file that solves matrices with the following conditions: a. Create a 4 x 4 vector C (range of vector numbers should be multiples of 3) b. Find the sums of columns 1 and 2 of C c. Find a version of C with rows 2 and 4 d. Display the fourth column of transpose C• C=numpy.add(A, B): Combine two matrices A and B and save the result in C.• C=numpy.subtract(A, B): Subtract matrices A and B and store the result in C.• C=numpy.divide(A, B): Divide matrices A and B and save the result in C.• C stands for numeric.multiply(A, B): Multiply matrices A and B and store the result in C.• C=numpy.sum(A): Add the elements of matrix A and store the result in c R.• C=numpy.sum(A, axis = 0): Perform a column-wise sum of matrix A and store the result in vector C.• C=numpy.sum(A, axis = 1): Perform a row-by-row summation of matrix A and store the result in vector C. Write Python code to demonstrate the use of these methods in a sample matrix. give accurate code with output otherwise you will get downvote
- 23( The matrix below is stored in the Row-Major order in the linear memory, so in what order are the numbers stored. a. 8, 4, 3, 7, 9, -8, 5, 6, -2. b. 8, 6, -8, 7, 3, 4, -5, 9, -2. c. 8, -5, 7, 4, 6, 9, 3, -2 , -8. d. 8, 4, 3, -5, 6, -2, 7, 9, -8.Q5. Write a program that reads from the user an integer matrix with 10x10, and then rotate that matrix 180° (UPSIDE DOWN) after that, calculate the sum and the average of the main diagonal. Print the matrix after the rotation and the values of the sum and the average of the main diagonal.Create a MATLAB script file that solves matrices with the following conditions: a. Create a 4 x 4 vector C (range of vector numbers should be multiples of 3) b. Find the sums of columns 1 and 2 of C c. Find a version of C with rows 2 and 4 d. Display the fourth column of transpose C
- Create a 3-by-3 matrix: A = [1 2 3;4 5 6;7 8 10] (a)Extract a submatrix B consisting of rows 1 and 3 and columns 1 and 2 of the matrix A (b)Interchange rows 1 and 3 of A and put it in a variable C. Hint: use the vector of row indices together with the colon operator (c)Create a vector version of the original matrix A. (d)Delete the 2nd column of the original matrix A and put it in a variable called A. (e)Insert a 2nd column to the new matrix A to restore it back to its original form A. (f) Extract those entries of the original matrix A that are greater than 5Use C Language The Pascal triangle can be used to compute the coefficients of the terms in the expansion (a + b)n. For example, (a + b)2 = a2 + 2ab + b2 where 1, 2, and 1 are coefficients. Write a C program that creates a two-dimensional matrix a representing the Pascal triangle of size n. For example, a Pascal triangle of size 6 is shown below: 1 1 1 1 2 1 1 3 3 1 1 4 6 4 1 1 5 10 10 5 1Matrix multiplication plays an important role in a number of applications. Two matrices can only be multiplied if the number of columns of the fi rst matrix is equal to the number of rows in the second.Let’s assume we have an m × n matrix A and we want to multiply it by an n × p matrix B. We can express their product as an m × p matrix denoted by AB (or A ⋅ B). If we assign C = AB, and ci,j denotes the entry in C at position (i, j), then for each element i and j with 1 ≤ i ≤ m and 1 ≤ j ≤ p. Now we want to see if we can parallelize the computation of C. Assume that matrices are laid out in memory sequentially as follows: a1,1, a2,1, a3,1, a4,1, ..., etc.Assume that we are going to compute C on both a single core shared memory machine and a 4-core shared-memory machine. Compute the speedup we would expect to obtain on the 4-core machine, ignoring any memory issues.Repeat above Exercise, assuming that updates to C incur a cache miss due to false sharing when consecutive elements are in a…
- A C_++ program for Solving system of linear equations with two variables using Cramer’s rule. In mathematics the coefficientsof linear equations are represented in the form of matrices. A matrix is a two-dimensional array inprogramming. The steps of Cramer’s rule to solve the system of equations are: Step 1: Determining the coefficient matrix from linear equations e.g.a1x+b1y=d1a2x+b2y=d2Coefficient matrix: D =Step 2: Determining the constant column C =Step 3: Finding determinant |D| = (a1*b2) - (b1*a2) and checking if |D| is not equal to zero then do thefollowing:1. Determining X-matrix: DX =The coefficients of the x−column are replaced by the constant columna1 b1a2 b2d1d2d1 b1d2 b22. Determining Y-matrix: Dy =The coefficients of the Y−column are replaced by the constant column3. To solve for x: x=|DX|/|D|4. To solve for y: y=|Dy|/|D|Note that if |D|=0 then the matrix is singular and solving the system of equationis not possible.You’re required to automate all these steps by writing a…• C=numpy.add(A, B): Add two matrices A and B and store result in C.• C=numpy.subtract(A, B): Subtract matrix B from matrix A and store result in C.• C=numpy.divide(A, B): Divide matrix A by matrix B and store result in C.• C=numpy.multiply(A, B): Multiply matrix A by matrix B and store result in C.• C=numpy.sum(A): Form the sum of elements of matrix A and store result in c ∈ R.• C=numpy.sum(A, axis = 0): Form the column wise summation of matrix A andstore result in vector C.• C=numpy.sum(A, axis = 1): Form the row wise summation of matrix A, storeresult in vector C.Write Python code to shows the implementation of these methods in asample matrixpublic static void WriteToFile(StreamWriter w, int[,] m) { // Write the elements of the "m" array in the matrix format // to the file "myFile.txt". // -------------------------------------- // Call the "AverageOfAllElements" method and // write the returned value after the text // "The average of all elements of the matrix:" in the file "myFile.txt". // -------------------------------------- // Put the header "LIST OF ODD NUMBERS IN EACH ROW:" in the file "myFile.txt". // Call the "WriteOddNumbersOfEachRow" method. // -------------------------------------- // Put the header "LIST OF EVEN NUMBERS IN EACH COLUMN" in the file "myFile.txt" // Call the "WriteEvenNumbersOfEachColumn" method. }