Write a function with signature double var(int n, double *xarr) that takes an array xarr of length n and returns the (population) variance of its values , where μ is the mean of its values. H Σ*, - μ)?

Write a function with signature double var(int n, double xarr) that takes an array xarr of length n and returns the (population) variance of its values , where μ is the mean of its values. H Σ, - μ)?

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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Write a Python function mat_to_prob (R) that returns the matrix P = (P₁, P2, ..., Pm) where Pi is the i-th row of matrix P , and Pi is the probability vector obtained from R; using the formulation in Question 1. In other words, convert each row of the input matrix into a probability vector. Sample inputs and outputs: • Input: np.array([[4, 6], [3.5, 9.11) Output: [[0.11920292 0.88079708] [0.00368424 0.99631576]] • Input: np.array([[2, 3.1, 5], [10, 3.7, 12], [4, 5.5, 0]])) Output: [[4.15115123e-02 1.24707475e-01 8.33781013e-01] [1.19176835e-01 2.18844992e-04 8.80604320e-01] [1.81818026e-01 8.14851861e-01 3.33011331e-03]] Hint: use numpy.sum with an appropriate axis and keepdims settings. You should also check broadcasting in numpy. Question 2b In fact, the function above is called the softmax function, and scipy has an implementation for it. First, read the API at: https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.softmax.html. Then write code to apply this version of…
Implement the following addArrays function which takes as input two linear arrays of the same length/capacity and constructs a new linear array of the same length/capacity as output. The first element of this new array should be the sum of the first element of the first array and the last element of the second array; the second element should be the sum of the second element of the first array and the second last element of the second array and so on. If there is any "None" value in any of the arrays, you can assume that it is a zero. You are not allowed to use any built-in python functions except len() and range() Using negative indices in python (such as ar[-1]) is not allowed. Python: def addArrays(arr1, arr2): #Write your code here ava: ublic int[] addArrays(int[] arr1, int[] arr2) { // Write your code here ample Input 1 = [1, 4, 5, 8, None, None, None] 2=[7, 4, 8, 9, 5, None, None] == addArrays(ar1, ar2) t(ar3) Sample Output [1, 4, 10, 17, 8, 4, 7] Explanat 1+None 4+None 5+5= 8+9=…
Rewrite the pattern match function so that, instead of finding only the first match, it reports all match locations, including overlapping matches. (It should report a match by printing "match at index k" where k is replaced by the first index of the match.) Assume that the prefix array π has already been computed
Write a function to find the maximum sum of a subarray within a given array of integers. The subarray should be contiguous, meaning the elements are adjacent to each other in the array. For example, given the array [-2, 1, -3, 4, -1, 2, 1, -5, 4], the maximum sum of a subarray is 6, which corresponds to the subarray [4, -1, 2, 1]. Write a function named `maxSubarraySum` that takes an array of integers as input and returns the maximum sum of a subarray. Note: If all the elements in the array are negative, the function should return O. Example: Input: [-2, 1, -3, 4, -1, 2, 1, -5, 4] Output: 6 Input: [-1, -2, -3, -4] Output: 0 Write the 'maxSubarraySum` function that solves this problem efficiently.
Using For-Loop and If-statement, find the smallest number divisible by 4 in the 1D array "a1". Do not use any shortcut functions. The code should be able to work with any 1D array of numbers | of any length. a1=np.array([-1,2,4,5,-10, 0, 4, 0,-8, 2.5, 2, 14])
Given two arrays a and b, where both arrays consisting of n positive integers. It is allowed to swap any element from array a with any element from b. Your task is to find the maximum possible sum you can obtain in the array a if you can do no more than (i.e. at most) k moves (swaps). Input • The first line of the test case contains two integers n and k (1Sns30;0sksn) - where n is the number of elements in a and b, while k is the maximum number of moves you can do. • The second line of the test case contains n integers a1,a2,... an • The third line of the test case contains n integers b1,b2,..,bn Output Print the answer – the maximum possible sum you can obtain in the array a if you can do no more than (i.e. at most) k swaps. Examples: Ex 1: Ex 2: Ex 3: Input 55 53 40 55665 1234 5 2243 12543 10 9 10 10 9 2423 Output: 27 39 11 • In the first test case of the example, you don't need to swap anything. • In the second test case of the example, you can swap a1=1 with bi=10, a3=3 with b3=10…
Given an array of integers, write a function to find the maximum sum of any contiguous subarray (i.e., a subarray with consecutive elements) in the array. For example, in the array [1, -2, 3, 4, -1, 2, 1, -5, 4], the maximum sum of a contiguous subarray is 6 (from index 2 to index 5).
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1. Write a function (call it mylm) that takes two inputs: a vector y of n elements and a matrix X of n times k elements, where n should be greater than k, and returns three outputs: bhat = solve(X'X)X'y, X'X and X'y (the prime symbol means transpose). Use the attr method to return the second and third outputs. Note that you do not need to specify values for y and X when you write this function.
Using the linear_predict function that you previously wrote, write a function linear_residuals that given the learned weights in the linear_regression function calculates the residuals vector. Your functions takes the following arguments as input: 1. X:A numpy array of the shape (N,d) where N is the number of data points, and d is the data dimension. Do not assume anything about N or d other than being a positive integer. 2. beta : Anumpy array of the shape (d+1,1) where d is the data dimension Bo Ba 3. Y: A numpy array of the shape (N,) where N is the number of data points. Your function should produce the e numpy array with the shape of (N,), whose i" element is defined as el) = yl) – (Bo + Bix? + Bzx + + Bax) In [ ]: def linear_residuals (X,beta,Y): assert X.ndim==2 N = X.shape[0] х.shape[1] assert beta.shape assert Y.shape d = (d+1,1) (N,) == == #3 your code here e e.reshape(-1) %3D assert e.size return e (np.arange ( 35).reshape ( 7,5) ** 13) % 20 2.** (-np.arange (6).reshape…
Given an array of integers and a positive integer k, determine the number of (i, j) pairs where i < j and ar[i] + ar[j] is divisible by k. Example ar [1, 2, 3, 4, 5, 6] k=5 Three pairs meet the criteria: [1, 4], [2, 3], and [4, 6]. Function Description Complete the divisibleSumPairs function in the editor below. divisibleSumPairs has the following parameter(s): • int n: the length of array ar ⚫int ar[n]: an array of integers . int k: the integer divisor Returns -int: the number of pairs Input Format The first line contains 2 space-separated integers, 11 and k. The second line contains space-separated integers, each a value of arr[i]. Constraints • 2 ≤ n ≤ 100 • 1<k<100 • 1 ≤ ar[i] ≤ 100 Sample Input More STDIN 63 1 3 2 6 12 Function n6, k3 ar [1, 3, 2, 6, 1, 2] Sample Output 5 Explanation Here are the 5 valid pairs when k = 3: (0,2) ar[0] + ar[2]=1+2=3 (0,5) ar[0] + ar[5]=1+2=3 • (1,3) ar[1]+ar [3]=3+6=9 (2, 4) ar[2] + ar[4] = 2+1=3 • (4,5)→ ar[4] + ar[5]=1+ 2=3 with…
Given an array of integers and a positive integer k, determine the number of (i, j) pairs where i < j and ar[i] + ar[j] is divisible by k. Example ar [1, 2, 3, 4, 5, 6] k=5 Three pairs meet the criteria: [1, 4], [2, 3], and [4, 6]. Function Description Complete the divisibleSumPairs function in the editor below. divisibleSumPairs has the following parameter(s): • int n: the length of array ar ⚫int ar[n]: an array of integers . int k: the integer divisor Returns -int: the number of pairs Input Format The first line contains 2 space-separated integers, 11 and k. The second line contains space-separated integers, each a value of arr[i]. Constraints • 2 ≤ n ≤ 100 • 1<k<100 • 1 ≤ ar[i] ≤ 100 Sample Input fin Contest ends in 5 days Submissions: 45 Max Score: 20 Difficulty: Easy Rate This Challenge: More STDIN 63 1 3 2 6 12 Function n6, k3 ar [1, 3, 2, 6, 1, 2] Sample Output 5 Explanation Here are the 5 valid pairs when k = 3: (0,2) ar[0] + ar[2]=1+2=3 (0,5) ar[0] + ar[5]=1+2=3 •…