B- Use for or while-end loop to calculate the summation of all numbers that existing in the first column and third raw of the matrix below -4.50 -9.10 -7.47 3.48 -0.80 -4.45 9.92 2.56 1.49 12.52 -6.42 7.72 7.61 -3.59 2.03 Matlab -12.72 -13.38 0.92 8.38 13.02 -11.10 2.06 -0.92 -14.64 -4.89 -10.13 8.83 -5.66 0.86 -10.03 3.06 -7.11 4.62 5.68 7.44

B- Use for or while-end loop to calculate the summation of all numbers that existing in the first column and third raw of the matrix below -4.50 -9.10 -7.47 3.48 -0.80 -4.45 9.92 2.56 1.49 12.52 -6.42 7.72 7.61 -3.59 2.03 Matlab -12.72 -13.38 0.92 8.38 13.02 -11.10 2.06 -0.92 -14.64 -4.89 -10.13 8.83 -5.66 0.86 -10.03 3.06 -7.11 4.62 5.68 7.44

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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16. Get the sum of all the values in matrix In [ ]: In [28]: # DON'T WRITE HERE Out[28]: 1275 17. Get the standard deviation of the values in matrix In [29]: # Code Here In [30]: # DON'T WRITE HERE Out[30]: 14.430869689661812
Python numpy library functions to perform basic matrix operations are as follows.• 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.Python code to show the implementation of these methods in a sample matrix.
Q10:- . using to print the element of secondary diagonal for a matrix A(N,N), where l represent row and j represent column. disp(A(i,N+1-j)) Use By Matlab disp(A(i,N+1-i)) disp(A(i,i+j+N+1)) disp(A(i.j))
Help with computer graphics mcq The digitization process i.e. the digital image has M rows and N columns, requires decisions about values for M, N, and for the number, L, of max gray levels. There are no requirements on M and N, other than that M and N have to be positive integer. However, the number of gray levels typically is a) An integer power of 2 i.e. L = 2k b) A Real power of 2 i.e. L = 2k c) Two times the integer value i.e. L = 2k d) None of the mentioned
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which code can be used for changing the dimensions of a matrix as follows? input matrix: 1 2 3 4 5 6 output matrix: 1 4 2 5 3 6
The 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.
Horizontal sequence :VIRL Vertical sequence:MKF Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. SW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: V I R L M K F 2. Set up, initialize and complete the SW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). V I R L M K F Align and score all optimal alignments here. PLZ the arrows and circles for the matrix and path(s) AND SHOW ALL possible Alignment
• 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 matrix
All MATLAB variables are multidimensional arrays True False MATLAB allows you to process all of the values in a matrix using multiple arithmetic operator or function T F Other: Zero or negative subscripts are not supported in MATLAB От OF
Lab 1 - 2D Lists For this lab, you will work with two-dimensional lists in Python. Do the following: 1. [4 points] Write a function that returns the sum of all the elements in a specified column in a matrix using the following header: def sumColumn(matrix, columnindex) 2. [2 points] Write a function display() that displays the elements in a matrix row by row, where the values in each row are displayed on a separate line. Use a single space to separate different values. Sample output from this function when it is called on a 3 X4 matrix is as follows: 2.5 3.0 4.0 1.5 1.5 4.0 2.0 7.5 3.5 1.0 1.0 2.5 3. [4 points] Given this partial code def getMatrix(numRows, numColumns): "returns a matrix with the specified number of rows and columns" m = [] # the 2D list (i.e., matrix), initially empty for row in range(numRows): matrix_dimensions_string = str(numRows) + "-by-" + str(numColumns) line = input("Enter a "+ matrix_dimensions_string + " matrix row for row "+ str(row) + ": ") return m write a…