The pseudo-code to create the matrix: Procedure AdjacencyMatrix(N): //N represents the number of nodes Matrix[N][N] for i from 1 to N for j from 1 to N Take input -> Matrix[i][j] endfor endfor Make Java code implemented using above pseudo-code:
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The pseudo-code to create the matrix:
Procedure AdjacencyMatrix(N): //N represents the number of nodes
Matrix[N][N]
for i from 1 to N
for j from 1 to N
Take input -> Matrix[i][j]
endfor
endfor
Make Java code implemented using above pseudo-code:
Step by step
Solved in 3 steps with 2 images
- Array implementation of List ADT Display the array elements from Left to Right and Right to left. Input: Enter the size of array MAX Enter number of elements N Enter the element to be inserted. Output: Display the Array For example: Test Input 1 2 10 W3 123 10 5 11 12 13 14 15 Result Forward: 1 2 3 Backward:3 2 1 Forward: 11 12 13 14 15 Backward:15 14 13 12 11%Encode A1, b1 and x1 as the vector of unknowns. A1 = b1 = syms xv1 = %Check the size of A, set it as m1 and n1 [m1,n1] = %Augment A and b to form AM1 AM1 = %Solve the Reduced Rwo Echelon of AM1. RREFA1 = %Collect the last column and set as bnew1, set the remaining elements as Anew1 bnew1= Anew1 = %Check if Anew is an identity matrix, if it is, bnew is the solution if Anew1 =eye(m1,n1) Root1 = bnew1 else display("No Solution") end %Augment the matrix A1 with the identity Matrix of the same size, set the result as AMI1 AMI1 = %Find the reduced row echelon form of AMI1, set the result as RREFAI1 RREFAI1= %Collect the second half of the matrix as AInew1, set the remaining elements as AIold1 AInew1= AIold1 = %Check if AIold1 is an identity matrix, if it is, AInew1 is the inverse %Encode A2, b2 and xv2 as the vector of unknowns. A2 = b2 = syms xv2 = %Check the size of A2, set it as m2 and n2 [m2,n2] = %Augment A2 and b2 to form AM2 AM2 = %Solve the…java programming language *matrices refers to 2d arrays note: In the question, it is asked to rotate the points(counterclockwise) inside of the matrix, obviously not the matrix itself. For example,|[1, 2]| -> |[1.866, 1.232]||[3, 4]| (30deg) => |[4.598, 1.964]||[5, 6]| -> |[7.330, 2.696]| it should work in any Nx2 matrice like 2x2, 3x2,4x2. N and the angle (in degrees) should be determined by the user
- java programming language *matrices refers to 2d arrays note: In the question, it is asked to rotate the points(counterclockwise) inside of the matrix, obviously not the matrix itself. For example,|[1, 2]| -> |[1.866, 1.232]||[3, 4]| (30deg) => |[4.598, 1.964]||[5, 6]| -> |[7.330, 2.696]|Consider the following matrix transpose routine:1 typedef int array[4][4];23 void transpose2(array dst, array src)4 {5 int i, j;67 for (i = 0; i < 4; i++) {8 for (j = 0; j < 4; j++) {9 dst[j][i] = src[i][j];10 }11 }12 }Assume this code runs on a machine with the following properties:An array may contain multiple duplicate values, as shown below. In order to design an algorithm with the best average performance to remove all duplicate values, which of the following data structures should be used? 110, 1100, s, 10, s6, s, 96, 34, s, 34, 20, 110, 30 Question 16 options: hash table stack list priority queue
- Figure 2 void sort_Algo (int anArray[], int n) { int i, j, idx; for (i = 0; i anArray[ idx ]) idx = j; Swap (anArray[ idx ], anArray[ i ]); } } int main() { const int n = 8; int anArray[n] { -9, 14, 52, 106, 22, -1, 99}; sort_Algo(anArray, n); } Name the sorting algorithm exercised by the sort_Algo() function. * Your answer Determine if anArray[] is to be sorted into ascending, or descending order. Your answer Trace the sorting algorithm in Figure 2 as it sorts anArray[]. (Answer the question according to the format, eg. Pass 0:3, 3, 3; Pass 1: 3, 3, 3; Pass2: 3, 3, 3;) * Your answerThe formula C=numpy.add(A, B) adds the two matrices A and B and stores the result in C.• To subtract matrix B from matrix A, enter C=numpy.subtract(A, B). The result is stored in C.• C=numpy.divide(A, B): Split matrix A into two equal parts and store the result in C.• C stands for numpy.multiply(A, B): Multiply matrices A and B, then store the result in matrices C.• C=numpy.sum(A): Calculate the sum of each element in the matrix A, then store the result in c R.• C=numpy.sum(A, axis = 0): Create a vector C by adding the columns of the matrix A.• C=numpy.sum(A, axis = 1): Summarize matrix A row-by-row and store the result in the vector C. Create Python code that demonstrates the use of these techniques in a sample matrix.In [20]: NumPy Operations In [29]: 16. Get the sum of all the values in matrix Sum of all the elements is 21 In [28]: # DON'T WRITE HERE Out [28]: 1275 17. Get the standard deviation of the values in matrix In [30] # DON'T WRITE HERE Out [30]: 14.430869689661812
- ASAP Solution needed / Solution | Given a matrix mtx, implement a function that returns the complete sentence as a string, with the words separated by a space between them. Examples transposeMatrix ([ ["Enter"], ["the"], ["Matrix!"] ]) "Enter the Matrix!"Bishops on a binge def safe_squares_bishops(n, bishops): A generalized n-by-n chessboard has been taken over by some bishops, each represented as a tuple (row, column) of the row and the column of the square the bishop stands on. Same as in the earlier version of this problem with rampaging rooks, the rows and columns are numbered from 0 to n - 1. Unlike a chess rook whose moves are axis-aligned, a chess bishop covers all squares that are on the same diagonal with that bishop arbitrarily far into any of the four diagonal compass directions. Given the board size n and the list of bishops on that board, count the number of safe squares that are not covered by any bishop. To determine whether two squares (r1, c1) and (r2, c2) are reachable from each other in one diagonal move, use abs(r1-r2) == abs(c1-c2) to check whether the horizontal distance between those squares equals their vertical distance, which is both necessary and sufficient for the squares to lie on the same diagonal. This…Write in C Language Description A sparse matrix is a matrix in which most of the elements are zero. Representing a sparse matrix by a 2D array leads to wastage of lots of memory as zeroes in the matrix are of no use in most of the cases. So, we can compress the sparse matrix by only store non-zero elements. This means storing non-zero elements with triples- (Row, Column, value). 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 6 0 0 0 0 9 0 0 0 0 0 0 0 12 0 Here is a 5X6 matrix, there are 4 element non-zero, we using three number represent it 5 6 4 After the three number are (Row, Column, value): row col val 1 1 3 2 3 6 3 2 9 4 4 12 Write a program to read the compressed matrix and print out the original matrix. Input First line consists 3 integers. First and second integers shows the dimensions of original matrix. Third integer k shows number of non-zero elements. Followed k lines are content of the sparse matrix. Each line consists 3 integers, row number, column number, and data. Output Output…