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add tests for ridge regression and new tests for NARXNN

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+61

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Lines changed: 2 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -86,9 +86,9 @@ class FROLS(Estimators, BaseMSS):`
`86`	`86`	`filter.`
`87`	`87`	`mu : float, default=0.01`
`88`	`88`	`The convergence coefficient (learning rate) of the filter.`
`89`		`- eps : float`
	`89`	`+ eps : float, default=np.finfo(np.float64).eps`
`90`	`90`	`Normalization factor of the normalized filters.`
`91`		`- ridge_param : float`
	`91`	`+ ridge_param : float, default=np.finfo(np.float64).eps`
`92`	`92`	`Regularization parameter used in ridge regression`
`93`	`93`	`gama : float, default=0.2`
`94`	`94`	`The leakage factor of the Leaky LMS method.`

Lines changed: 2 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -96,6 +96,7 @@ def test_default_values():`
`96`	`96`	`"offset_covariance": 0.2,`
`97`	`97`	`"mu": 0.01,`
`98`	`98`	`"eps": np.finfo(np.float64).eps,`
	`99`	`+ "ridge_param": np.finfo(np.float64).eps,`
`99`	`100`	`"gama": 0.2,`
`100`	`101`	`"weight": 0.02,`
`101`	`102`	`"model_type": "NARMAX",`
`@@ -115,6 +116,7 @@ def test_default_values():`
`115`	`116`	`model.offset_covariance,`
`116`	`117`	`model.mu,`
`117`	`118`	`model.eps,`
	`119`	`+ model.ridge_param,`
`118`	`120`	`model.gama,`
`119`	`121`	`model.weight,`
`120`	`122`	`model.model_type,`

Lines changed: 24 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -446,6 +446,30 @@ def forward(self, xb):`
`446`	`446`	`assert_almost_equal(yhat.mean(), y_test.mean(), decimal=2)`
`447`	`447`
`448`	`448`
	`449`	`+def test_raise_batch_size():`
	`450`	`+ assert_raises(`
	`451`	`+ ValueError, NARXNN, batch_size=0.3, basis_function=Polynomial(degree=2)`
	`452`	`+ )`
	`453`	`+`
	`454`	`+`
	`455`	`+def test_raise_epochs():`
	`456`	`+ assert_raises(ValueError, NARXNN, epochs=0.3, basis_function=Polynomial(degree=2))`
	`457`	`+`
	`458`	`+`
	`459`	`+def test_raise_train_percentage():`
	`460`	`+ assert_raises(`
	`461`	`+ ValueError, NARXNN, train_percentage=-1, basis_function=Polynomial(degree=2)`
	`462`	`+ )`
	`463`	`+`
	`464`	`+`
	`465`	`+def test_raise_verbose():`
	`466`	`+ assert_raises(TypeError, NARXNN, verbose=None, basis_function=Polynomial(degree=2))`
	`467`	`+`
	`468`	`+`
	`469`	`+def test_raise_device():`
	`470`	`+ assert_raises(ValueError, NARXNN, device="CPU", basis_function=Polynomial(degree=2))`
	`471`	`+`
	`472`	`+`
`449`	`473`	`def test_model_predict_fourier():`
`450`	`474`	`basis_function = Fourier(degree=1)`
`451`	`475`

Lines changed: 1 addition & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -51,7 +51,7 @@ def _validate_params(self):`
`51`	`51`	`"offset_covariance": self.offset_covariance,`
`52`	`52`	`"mu": self.mu,`
`53`	`53`	`"eps": self.eps,`
`54`		`- "ridge_param": self.ridge_param,# for regularized ridge regression`
	`54`	`+ "ridge_param": self.ridge_param,`
`55`	`55`	`"gama": self.gama,`
`56`	`56`	`"weight": self.weight,`
`57`	`57`	`}`

Lines changed: 32 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -42,6 +42,38 @@ def test_least_squares():`
`42`	`42`	`assert_almost_equal(model.theta, theta, decimal=2)`
`43`	`43`
`44`	`44`
	`45`	`+def test_ridge_regression():`
	`46`	`+ x, y, theta = create_test_data()`
	`47`	`+ basis_function = Polynomial(degree=2)`
	`48`	`+ model = FROLS(`
	`49`	`+ n_terms=5,`
	`50`	`+ extended_least_squares=False,`
	`51`	`+ ylag=[1, 2],`
	`52`	`+ xlag=2,`
	`53`	`+ estimator="ridge_regression",`
	`54`	`+ ridge_param=np.finfo(np.float64).eps,`
	`55`	`+ basis_function=basis_function,`
	`56`	`+ )`
	`57`	`+ model.fit(X=x, y=y)`
	`58`	`+ assert_almost_equal(model.theta, theta, decimal=2)`
	`59`	`+`
	`60`	`+`
	`61`	`+def test_raise_ridge_regression():`
	`62`	`+ assert_raises(`
	`63`	`+ ValueError, Estimators, ridge_param=-0.3, basis_function=Polynomial(degree=2)`
	`64`	`+ )`
	`65`	`+`
	`66`	`+`
	`67`	`+def test_raise():`
	`68`	`+ assert_raises(`
	`69`	`+ ValueError, Estimators, lam="0.97", basis_function=Polynomial(degree=2)`
	`70`	`+ )`
	`71`	`+`
	`72`	`+`
	`73`	`+def test_lam_raise():`
	`74`	`+ assert_raises(ValueError, Estimators, lam=1.01, basis_function=Polynomial(degree=2))`
	`75`	`+`
	`76`	`+`
`45`	`77`	`def test_total_least_squares():`
`46`	`78`	`x, y, theta = create_test_data()`
`47`	`79`	`model = FROLS(`

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