quadratic_function.py
View Options

			import numpy as np

			# This function implements S(x) as given in the exercise sheet
			# If matrix A or vector b are not specified through "args", the function assumes
			# that A and b are those given in Exercise 1
			# Not that you CANNOT only specify A or b, both must be specified such that
			# args[0] = A and args[1] = b
			def quadratic_function(x, *args):

			if len(args) == 0:
			A = np.array([[4, 0], [1, 3]])
			b = np.array([0, 1])
			else:
			A = args[0]
			b = args[1]

			# reshape into column vectors
			x.reshape(-1, 1)
			b.reshape(-1, 1)

			# return S(x)
			return ((x.transpose() @ A) @ x) - (x.transpose() @ b)

			# TESTING AND VALIDATING FUNCTION
			#print(quadratic_function(np.array([1,2]) ))
			#print(quadratic_function(np.array([1,2]), np.array([[4, 0], [1, 3]]), np.array([0, 1]) ))

R9484/hw1-conjugate-gradient/quadratic_function.pyf58f9fd9c380master