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))