Design an algorithm in pseudo code to rearrange elements of a given array of n real numbers so that all its negative elements precede all its positive elements. Your algorithm should be No worse than Θ(n). Sample input: A = {-1, 4, -4, 3, 5, -2, 7, 8, 9, -10}

Create an array of size one million (1,000,019). Fill it in reverse sequentially with values (e.g. array[0] should equal 1,000,018, array[1] should equal 1,000,017, etc). Then the computer should select a random target number between 0 and array size – 1. You should then search the array for this value twice – once with a linear search algorithm, and then with a binary search algorithm. Start searching from the end of the array, rather than the beginning. Keep track of how long each one took, using the following criteria: Linear Search: Number of loop iterations before the target number was found Binary Search: Number of midpoints chosen (a.k.a “guesses”) taken before the target number was found Once both algorithms have been run, display the results and print which algorithm found the number first (or if there was a tie). Once both algorithms have been run, display the results and print which algorithm found the number first (or if there was a tie). In the rest of this assignment,…

Write an algorithm in pseudocode that finds the average of (n) numbers. For example) (numbers are [4,5,14,20,3,6] ?

Using DASK in Python to solve this problem. Given a dask array, compute the difference along axis 0 using mean squared error This can be done without loops -- think outside of the box! This also needs to work for 1D, 2D, 3D, 4D, etc. def sequential_MSE_axis0 (anArray): # this does use the earlier MSE implementation n_elements_axis0 = anArray. shape [0] - 1 anArray.shape[0] results = da.zeros(n_elements_axis0) for i in range(n_elements_axis0): results[i] = MSE (anArray[i], anArray[i+1]) return results Complete the function below. Don't call . compute() Test Result oneDda.arange(4); print (all (isclose(a, b) for a, b in zip (MSE_axis0 (oneD), [1., 1., 1.]))) twoD = True da.arange(4).reshape((2,2)); print (all(isclose(a, b) for a, True b in zip (MSE_axis 0 (twoD), [4.]))) = threeD da.arange(8).reshape((2, 2,2)); print (all(isclose(a, b). for a, b in zip (MSE_axis0 (threeD).compute(), [16.]))) True def MSE_axis0 (anArray): ## WRITE YOUR CODE HERE