Matrix Multiplication • Write a multiplication function that accepts two 2D numpy arrays, and returns the product of the two. This function should test that the arrays are compatible (recall that the number of columns in the first matrix must equal the number of rows in the second matrix). This function should test the array sizes before attempting the multiplication. If the arrays are not compatible, the function should return -1. solve in python

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Q2: In this question, you will write a Python function to compute the Hadamard product of two matrices. The Hadamard product is the "component-wise" product of two matrices. That is, each entry of the product matrix is equal to the product of its corresponding entries of the input matrices. Here is an example: a11 a12 a21 a22 a23 a31 a13 SH a32 033 A b11 b12 b13 b21 b22 b23 b31 b32 b33. B = [an bu a21 b21 a31 b31 a12 b12 a22 b22 a32 b32 a13 b13 a23 b23 a33 b33. Hadamard product of A and B Write a Python function to compute the Hadamard product of two matrices as follows. a) The inputs to the function are two matrices. b) The function should check whether the two matrices have the same size. If not, it should print "The input matrices are not of the same size". c) If two matrices are of the same size, the function computes the Hadamard product and returns the answer. Use for loops to compute the Hadamard product.

Declare 2D array whose size and elements must be according to the desire of user then perform the following functions on it Display a lower triangular matrix. Find the sum of an upper triangular matrix. DO IT IN C++

Prompt: In python langauge, write a function that adds a random noise to all elements of a NumPy array Code:  import numpy as np import math import matplotlib.pyplot as plt import pandas as pd   def addNoise(inputArray):   modifiedArray = np.zeros(len(inputArray))   #YOUR CODE HERE:   return(modifiedArray) def test(): inputs = np.arange(-5, 5,0.2) outputs = addNoise(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs, 'black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()

Now, write another function that prints the values of any array in reverse order. (The function should not change the original array). As an example, if a [] = {1, 2, 3, 4, 5}; The function would print the values in reverse as: 5, 4, 3, 2, 1

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I am designing a application which can generate a 2 d array which contains the random elements and print that generated matrix on the console. Take the size of matrix from the user. In python

Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array. Code:   import numpy as np import math import matplotlib.pyplot as plt import pandas as pd   def sigmoid(inputArray):               modifiedArray = np.zeros(len(inputArray))               #YOUR CODE HERE:               return(modifiedArray) def test(): inputs = np.arange(-100, 100, 0.5) outputs = sigmoid(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs,'Black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()

Develop python program of function randomArray(m, n) that takes two integers as argument and returns a 2D m-by-n array with random elements in it. Develop python program of function adder(a1, a2) that reads two 2D arrays of the same size and returns an array that is the summation of a1 and a2. To add the two arrays, you need to add their elements, correspondingly. Develop a  python program of function inverseArray(a) that takes a 2D-array as argument and inverses the array. You will need to inverse the rows, first and then inverse the columns, next. For instance, if the array = [[2, 3, 4], [5, 6, 7]], the inverse will be = [[7, 6, 5], [4, 3, 2]]