def test_nuclear_norm(self):
"""Test nuclear_norm."""
npt.assert_almost_equal(
matrix.nuclear_norm(self.data1),
15.49193338482967,
err_msg='Incorrect nuclear norm',
)
def _cost_method(self, *args, **kwargs):
"""Calculate low-rank component of the cost.
This method returns the nuclear norm error of the deconvolved data in
matrix form.
Parameters
----------
args : interable
Positional arguments
kwargs : dict
Keyword arguments
Returns
-------
float
Low-rank cost component
"""
cost_val = self.thresh * nuclear_norm(cube2matrix(args[0]))
if 'verbose' in kwargs and kwargs['verbose']:
print(' - NUCLEAR NORM (X):', cost_val)
return cost_val
def _cost_method(self, *args, **kwargs):
"""Calculate low-rank component of the cost
This method returns the nuclear norm error of the deconvolved data in
matrix form
Returns
-------
float low-rank cost component
"""
cost_val = self.thresh * nuclear_norm(cube2matrix(args[0]))
if 'verbose' in kwargs and kwargs['verbose']:
print(' - NUCLEAR NORM (X):', cost_val)
return cost_val