def setup(self): n = 3 # Declare a vector of length 3 as input v1 = self.declare_input('v1', val=np.arange(n)) # Output the average of all the elements of the vector v1 self.register_output('single_vector_average', ot.average(v1))
def setup(self): n = 3 m = 6 # Declare a matrix of shape 3x6 as input M1 = self.declare_input('M1', val=np.arange(n * m).reshape((n, m))) # Output the average of all the elements of the matrix M1 self.register_output('single_matrix_average', ot.average(M1))
def setup(self): n = 3 m = 6 # Declare a matrix of shape 3x6 as input M1 = self.declare_input('M1', val=np.arange(n * m).reshape((n, m))) # Output the axiswise average of matrix M1 along the columns self.register_output('single_matrix_average_along_0', ot.average(M1, axes=(0, )))
def setup(self): n = 3 # Declare a vector of length 3 as input v1 = self.declare_input('v1', val=np.arange(n)) # Declare another vector of length 3 as input v2 = self.declare_input('v2', val=np.arange(n, 2 * n)) # Output the elementwise average of vectors v1 and v2 self.register_output('multiple_vector_average', ot.average(v1, v2))
def setup(self): n = 3 m = 6 p = 7 q = 10 # Declare a tensor of shape 3x6x7x10 as input T1 = self.declare_input('T1', val=np.arange(n * m * p * q).reshape( (n, m, p, q))) # Output the average of all the elements of the tensor T1 self.register_output('single_tensor_average', ot.average(T1))
def setup(self): n = 3 m = 6 # Declare a matrix of shape 3x6 as input M1 = self.declare_input('M1', val=np.arange(n * m).reshape((n, m))) # Declare another matrix of shape 3x6 as input M2 = self.declare_input('M2', val=np.arange(n * m, 2 * n * m).reshape( (n, m))) # Output the elementwise average of matrices M1 and M2 self.register_output('multiple_matrix_average', ot.average(M1, M2))
def setup(self): n = 3 m = 6 # Declare a matrix of shape 3x6 as input M1 = self.declare_input('M1', val=np.arange(n * m).reshape((n, m))) # Declare another matrix of shape 3x6 as input M2 = self.declare_input('M2', val=np.arange(n * m, 2 * n * m).reshape( (n, m))) # Output the elementwise average of the axiswise average of matrices M1 ad M2 along the columns self.register_output('multiple_matrix_average_along_1', ot.average(M1, M2, axes=(1, )))
def setup(self): n = 3 m = 6 p = 7 q = 10 # Declare a tensor of shape 3x6x7x10 as input T1 = self.declare_input('T1', val=np.arange(n * m * p * q).reshape( (n, m, p, q))) # Declare another tensor of shape 3x6x7x10 as input T2 = self.declare_input('T2', val=np.arange(n * m * p * q, 2 * n * m * p * q).reshape( (n, m, p, q))) # Output the elementwise average of tensors T1 and T2 self.register_output('multiple_tensor_average', ot.average(T1, T2))