Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num rows, num cols, x): for į in range(num rows): for j in range(num cols): if m[i]G)==x: return True return False How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer. Implement Python code to read in a cSV file which contains the matrix that implements your approach. Please comment on code so I can better understand. Sample text file contains: (1,7,16,21,34 4,9,20,25,41 6,16,31,33,44 11,19,49,50,61)

Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num rows, num cols, x): for į in range(num rows): for j in range(num cols): if m[i]G)==x: return True return False How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer. Implement Python code to read in a cSV file which contains the matrix that implements your approach. Please comment on code so I can better understand. Sample text file contains: (1,7,16,21,34 4,9,20,25,41 6,16,31,33,44 11,19,49,50,61)

C++ Programming: From Problem Analysis to Program Design

8th Edition

ISBN:9781337102087

Author:D. S. Malik

Publisher:D. S. Malik

Chapter15: Recursion

Section: Chapter Questions

Problem 18SA

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I am having trouble with a individual coding problem I am doing in python: Ar = int(input("How many rows does your matrix have? "))Ac = int(input("How many columns does your matrix have? ")) win = GraphWin('Matrix A', 300,300) win.setBackground('white') for p in range(Ac):y = 75 + 40*pfor q in range(Ac):x = 50 + 50*qinputText = Entry(Point(x,y), 3)inputText.setText('0')inputText.draw(win) ## The issue I having is that I want to be able to get the users inputs from their entries so that I can do matrix operations on them. However, anytime I try to append their entries at best I just get their last entry repeated (n)(m) times. I would be very thankful if you can show me how I can change my code so that I append all user entries correctly.
A matrix is an array of numbers of size m by n (i.e., m x n). When we multiply 2 matrices, we multiply the matching numbers, then sum them up. Multiplying a matrix of size m x n with another matrix of size n x q will result in a matrix of size m x q. An example is shown in Figure 1: [ ? ? ? ? ? ? ] x [ ? ? ? ? ] = [ ?? +?? ?? + ?? ?? + ?? ?? + ?? ?? + ?? ?? + ?? ] Matrix 3 x 2 Matrix 2 x 2 Matrix 3 x 2 Figure 1: Multiplication of Matrix 3 x 2 and 2 x 2 Write a C++ program that multiplies 2 matrices and return the sum of the transposed matrix. Your program shall include the following: a) Define two 2 dimensional arrays, M and N that each represents a matrix of size 3 x 2 and a matrix of size 2 x 2. Request the user to enter the values for the 2 arrays using advanced pointer notations (refer to your slides for the list of array pointer notations). b) Create a function named multMatrix() that passes as arguments, the values of array M and N, multiplies them and store the results in a new…
Let m be a matrix with n rows and n columns whose entries are either 1 or 0. recall that the element of m on row i and column j is denoted by mij . the diagonal entries of m are {mii} for 1 ≤ i ≤ n. We call M permutable if it is possible to swap some of the rows and some of columns so that all diagonal entries are 1. Design a polynomial time algorithm that decides whether a binary matrix M is permutable or not. Note that we can swap any two rows or two columns. Also, the order in which these swaps are done is not important.
Search a sorted matrix: The input consists of a real number x and a matrix A[1..n, 1..m] of nm real values, where A[i, 1..m] and A[1..n, j] are the rows and columns, respectively, of the matrix. The objective is to either state that all of the members of A are greater than x or to locate the largest array entry A[i, j] that is less than or equal to x. Create and evaluate an iterative approach for this issue that looks at the least amount of matrix entries feasible. If you think the issue can be resolved with a straightforward binary search, think twice.
You will be given a square matrix of N rows and N columns (1 <= N <= 1000) containing positive and negative integers with absolute value not larger than 1000. You are required to compute the greatest sum achievable by walking a path, starting at any cell of the matrix and always moving downwards or rightwards. Additionally, you have to report the number of times that value is achievable. N will be in the first line of the input. N lines follow with N integers each. You should output a single line with two integers separated by a single blank space: first one is the greatest sum, second one is the number of times this value can be reached.
you will be given a square matrix of N rows and N columns (1 <= N <= 1000) containing positive and negative integers with absolute value not larger than 1000. You are required to compute the greatest sum achievable by walking a path, starting at any cell of the matrix and always moving downwards or rightwards. Additionally, you have to report the number of times that value is achievable. N will be in the first line of the input. N lines follow with N integers each. You should output a single line with two integers separated by a single blank space: first one is the greatest sum, second one is the number of times this value can be reached. Case 1: For the input provided as follows: 53 1 -2 1 1-6 -1 4 -1 -41 1 1 1 12 2 2 2 21 1 1 1 1 Output of the program will be: 15 1 Case 2: For the input provided as follows: 31 1 12 2 23 3 3 Output of the program will be: 12 1
Matrix 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…
When dealing with large dense symmetric matrix it is recommended that to either store upper right or lower left entries only to avoid redundancy and thereby saving a lot of space (particularly when the matrix elements are of double type or any other user-defined datatype). Let us assume that we have decided to store only the upper right entries of a matrix inside a 1D array in the row-major arrangement. 1. Design an algorithm for accepting a symmetric matrix from the user and printing the same matrix. 2. Design an algorithm for multiplying a given symmetric matrix stored in a 1D array with a compatible vector.
Search a sorted matrix: The input consistsof a real number x and a matrix A[1..n, 1..m] of nm real numbers such that each rowA[i, 1..m] is sorted and each column A[1..n, j] is sorted. The goal is to find the maximum array entry A[i, j] that is less than or equal to x, or report that all elements of Aare larger than x. Design and analyze an iterative algorithm for this problem that examines as few matrix entries as possible. Becareful if you believe that a simple binarysearch solves the problem. make a lower bound, and recursive algorithm.
Search a sorted matrix: The input consistsof a real number x and a matrix A[1..n, 1..m] of nm real numbers such that each rowA[i, 1..m] is sorted and each column A[1..n, j] is sorted. The goal is to find the maximum array entry A[i, j] that is less than or equal to x, or report that all elements of Aare larger than x. Design and analyze an iterative algorithm for this problem that examines as few matrix entries as possible. Becareful if you believe that a simple binarysearch solves the problem.
Question 2) We have N jobs and N workers to do these jobs. It is known at what cost each worker will do each job (as a positive numerical value). We want to assign jobs to workers in such a way that the total cost of completion of all jobs is minimal among other possible alternative assignments. For this problem, write the algorithm as pseudocode, whose input is a matrix representing worker/job costs, and the output is a list of tuples showing which work will be done by which worker, and that tries to reach the solution with GREEDY technique. Explain in what sense your algorithm exhibits greedy behavior. What is the time complexity of your algorithm? Interpret if your algorithm always produces the best (optimum) result for each instance of the problem.
I am supposed to solve the question marks in this code. I am given a matrix and I have to complete the following: Step 1 : Find number of columns or rows, in above example it is 3, set this as row_size = 3 Step 2 : For i in range(row_size), do following > select ith rows and divide it with i th values in diagonals # non ith rows non_ithrows = np.arange(row_size)!=i # now select all the col values associated with non ith rows from augment factors = ?? # now from factors select only the ith column and update factors factors = ?? # now compute prods which we will subtract from non ith rows prods = (factors.reshape(1,-1) * augmat[i].reshape(-1,1)).T # now subtract these prods from non_ithrows of augmat and assign to non_ithrows of augmat augmat[non_ithrows] = ?? # finally return last columns of augmat def…