Update get_cost in z_encoder

[hndgzkn]

Update get_cost function in _z_encoder to call compute_objective in _z_encoder.

As ztz and ztX are not initialized prior to calling compute_z, this requires some changes. Two possible solutions:

• get_cost function can return the value of cost function when z_hat=0 (i.e. 0.5 * np.linalg.norm(self.X[0]) ** 2) if ztz and ztX are not set.
  However test_get_cost fails with the following message (final cost after running compute_z is greater than the initial cost):

solver = 'l-bfgs'
X = array([[[ 0.49671415, -0.1382643 ,  0.64768854,  1.52302986,
         -0.23415337, -0.23413696,  1.57921282,  0.767434...     1.06667469,  1.16929559,  1.38215899,  0.64870989,
         -0.16711808,  0.14671369,  1.20650897, -0.81693567]]])
D_hat = array([[ 0.85771824,  0.1945646 ,  0.47588238,  0.69484882,  0.57908626,
        -0.30303112,  0.2946003 , -0.04693235...1623,  0.71909456,  0.68934122,  0.06912736,  0.16871127,
        -0.39607166, -0.88370123, -0.15521554,  0.06975264]])
requires_dicodile = None

    @pytest.mark.parametrize('solver, n_trials, rank1',
                             [('l-bfgs', 3, True),
                              ('dicodile', 1, False)])
    def test_get_cost(solver, X, D_hat, requires_dicodile):
        """Test for valid values."""
    
        with get_z_encoder_for(solver=solver,
                               X=X,
                               D_hat=D_hat,
                               n_atoms=N_ATOMS,
                               n_times_atom=N_TIMES_ATOM,
                               n_jobs=2) as z_encoder:
            initial_cost = z_encoder.get_cost()
    
            z_encoder.compute_z()
            z_hat = z_encoder.get_z_hat()
            final_cost = z_encoder.get_cost()
    
>           assert final_cost < initial_cost
E           assert 393.7852276977734 < 144.81588197885912

D_hat      = array([[ 0.85771824,  0.1945646 ,  0.47588238,  0.69484882,  0.57908626,
        -0.30303112,  0.2946003 , -0.04693235...1623,  0.71909456,  0.68934122,  0.06912736,  0.16871127,
        -0.39607166, -0.88370123, -0.15521554,  0.06975264]])
X          = array([[[ 0.49671415, -0.1382643 ,  0.64768854,  1.52302986,
         -0.23415337, -0.23413696,  1.57921282,  0.767434...     1.06667469,  1.16929559,  1.38215899,  0.64870989,
         -0.16711808,  0.14671369,  1.20650897, -0.81693567]]])
final_cost = 393.7852276977734
initial_cost = 144.81588197885912
requires_dicodile = None
solver     = 'l-bfgs'
z_encoder  = <alphacsc._z_encoder.AlphaCSCEncoder object at 0x7fef89941eb0>
z_hat      = array([[[0.03148913, 0.        , 0.11964971, ..., 0.        ,
         0.02470083, 0.        ],
        [0.        , 0...0967279, 0.        ],
        [0.12684568, 0.12219768, 0.02416528, ..., 0.        ,
         0.        , 0.        ]]])

• ztz and ztX should be set to 0 upon initialization as

        self.ztz = np.zeros((self.n_atoms, self.n_atoms,
                             2 * self.n_times_atom - 1))
        self.ztX = np.zeros((self.n_atoms, self.n_channels,
                             self. n_times_atom))

However test_get_cost fails with the following message (the cost computed in the test is not close to final_cost computed after compute_z is called. ):

solver = 'l-bfgs'
X = array([[[ 0.49671415, -0.1382643 ,  0.64768854,  1.52302986,
         -0.23415337, -0.23413696,  1.57921282,  0.767434...     1.06667469,  1.16929559,  1.38215899,  0.64870989,
         -0.16711808,  0.14671369,  1.20650897, -0.81693567]]])
D_hat = array([[ 0.85771824,  0.1945646 ,  0.47588238,  0.69484882,  0.57908626,
        -0.30303112,  0.2946003 , -0.04693235...1623,  0.71909456,  0.68934122,  0.06912736,  0.16871127,
        -0.39607166, -0.88370123, -0.15521554,  0.06975264]])
requires_dicodile = None

    @pytest.mark.parametrize('solver, n_trials, rank1',
                             [('l-bfgs', 3, True),
                              ('dicodile', 1, False)])
    def test_get_cost(solver, X, D_hat, requires_dicodile):
        """Test for valid values."""
    
        with get_z_encoder_for(solver=solver,
                               X=X,
                               D_hat=D_hat,
                               n_atoms=N_ATOMS,
                               n_times_atom=N_TIMES_ATOM,
                               n_jobs=2) as z_encoder:
            initial_cost = z_encoder.get_cost()
    
            z_encoder.compute_z()
            z_hat = z_encoder.get_z_hat()
            final_cost = z_encoder.get_cost()
    
            assert final_cost < initial_cost
    
            X_hat = construct_X_multi(z_hat, D_hat, n_channels=N_CHANNELS)
            cost = compute_objective(X=X, X_hat=X_hat, z_hat=z_hat, reg=0.1,
                                     D=D_hat)
    
>           assert np.isclose(cost, final_cost)
E           assert False
E            +  where False = <function isclose at 0x7f9aa010ac10>(396.9063356164568, 393.7852276977734)
E            +    where <function isclose at 0x7f9aa010ac10> = np.isclose

D_hat      = array([[ 0.85771824,  0.1945646 ,  0.47588238,  0.69484882,  0.57908626,
        -0.30303112,  0.2946003 , -0.04693235...1623,  0.71909456,  0.68934122,  0.06912736,  0.16871127,
        -0.39607166, -0.88370123, -0.15521554,  0.06975264]])
X          = array([[[ 0.49671415, -0.1382643 ,  0.64768854,  1.52302986,
         -0.23415337, -0.23413696,  1.57921282,  0.767434...     1.06667469,  1.16929559,  1.38215899,  0.64870989,
         -0.16711808,  0.14671369,  1.20650897, -0.81693567]]])
X_hat      = array([[[ 1.87670366e-02,  1.58087090e-02,  7.03257398e-02,
          1.36799839e-01,  3.19383914e-02,  5.76223312e-02...09410227e-01,  8.94328662e-02,
          6.66489290e-02,  4.55550879e-02,  1.00303005e-01,
         -1.48259646e-02]]])
cost       = 396.9063356164568
final_cost = 393.7852276977734
initial_cost = 432.6504303161992
requires_dicodile = None
solver     = 'l-bfgs'
z_encoder  = <alphacsc._z_encoder.AlphaCSCEncoder object at 0x7f9a7bbf7e50>
z_hat      = array([[[0.03148913, 0.        , 0.11964971, ..., 0.        ,
         0.02470083, 0.        ],
        [0.        , 0...0967279, 0.        ],
        [0.12684568, 0.12219768, 0.02416528, ..., 0.        ,
         0.        , 0.        ]]])

alphacsc/tests/test_z_encoder.py:274: AssertionError