def _check_exact_dimension(*args):
"""Wraps the dimension checking in order to provide additional logic.
Returns:
The wrapped function output.
"""
# Retrieving the object and the input from arguments
obj, x = args[0], args[1]
# Tries to squeeze the last dimension of `x` as it might be an array of (dim, 1)
try:
# Squeezes the array
x = np.squeeze(x, axis=1)
# If squeeze could not be performed, it means that there is no extra dimension
except ValueError:
pass
# If the function's number of dimensions is equal to `-1` (n-dimensional)
if obj.dims == -1:
# Checks if the input array is bigger than zero
if x.shape[0] == 0:
# If not, raises an error
raise e.SizeError(f'{obj.name} input should be n-dimensional')
return f(obj, x)
# If the input dimensions is different from function's allowed dimensions
if x.shape[0] != obj.dims:
# Raises an error
raise e.SizeError(f'{obj.name} input should be {obj.dims}-dimensional')
return f(obj, x)
def _check_less_equal_dimension(*args):
"""Wraps the dimension checking in order to provide additional logic.
Returns:
The wrapped function output.
"""
# Retrieving the object and the input from arguments
obj, x = args[0], args[1]
# Tries to squeeze the last dimension of `x` as it might be an array of (dim, 1)
try:
# Squeezes the array
x = np.squeeze(x, axis=1)
# If squeeze could not be performed, it means that there is no extra dimension
except ValueError:
pass
# If the input dimensions is different from function's allowed dimensions
if x.shape[0] > obj.dims:
# Raises an error
raise e.SizeError(f'{obj.name} input should be less or equal to {obj.dims}-dimensional')
return f(obj, x)
def test_size_error():
new_exception = exception.SizeError('error')
try:
raise new_exception
except exception.SizeError:
pass
def __init__(self,
name='Knapsack',
dims=-1,
continuous=False,
convex=False,
differentiable=False,
multimodal=False,
separable=False,
values=(0, ),
weights=(0, ),
max_capacity=0.0):
"""Initialization method.
Args:
name (str): Name of the function.
dims (int): Number of allowed dimensions.
continuous (bool): Whether the function is continuous.
convex (bool): Whether the function is convex.
differentiable (bool): Whether the function is differentiable.
multimodal (bool): Whether the function is multimodal.
separable (bool): Whether the function is separable.
values (tuple): Tuple of items values.
weights (tuple): Tuple of items weights.
max_capacity: Maximum capacity of the knapsack.
"""
# Override its parent class
super(Knapsack, self).__init__(name, dims, continuous, convex,
differentiable, multimodal, separable)
# Checking if values and weights have the same length
if len(values) != len(weights):
raise e.SizeError(
'`values` and `weights` needs to have the same size')
# Items values
self.values = values
# Items weights
self.weights = weights
# Maximum capacity of the knapsack
self.max_capacity = max_capacity
# Re-writes the correct number of dimensions
self.dims = len(values)
def _check_exact_dimension_and_auxiliary_matrix(*args):
"""Wraps the dimension checking in order to provide additional logic.
Returns:
The wrapped function output.
"""
# Retrieving the object and the input from arguments
obj, x = args[0], args[1]
# Tries to squeeze the last dimension of `x` as it might be an array of (dim, 1)
try:
# Squeezes the array
x = np.squeeze(x, axis=1)
# If squeeze could not be performed, it means that there is no extra dimension
except ValueError:
pass
# If the input dimensions differs from function's allowed dimensions
if x.shape[0] not in [2, 10, 30, 50]:
# Raises an error
raise e.SizeError(f'{obj.name} input should be 2-, 10-, 30- or 50-dimensional')
# If the input dimension is equal to 2
if x.shape[0] == 2:
# Defines the auxiliary matrix `M` as `M2`
setattr(obj, 'M', obj.M2)
# If the input dimension is equal to 10
elif x.shape[0] == 10:
# Defines the auxiliary matrix `M` as `M10`
setattr(obj, 'M', obj.M10)
# If the input dimension is equal to 30
elif x.shape[0] == 30:
# Defines the auxiliary matrix `M` as `M30`
setattr(obj, 'M', obj.M30)
# If the input dimension is equal to 50
elif x.shape[0] == 50:
# Defines the auxiliary matrix `M` as `M50`
setattr(obj, 'M', obj.M50)
return f(obj, x)