diff --git a/benchmarks/bench_plot_nmf.py b/benchmarks/bench_plot_nmf.py index a1e0358e392a0..c48977a49a725 100644 --- a/benchmarks/bench_plot_nmf.py +++ b/benchmarks/bench_plot_nmf.py @@ -203,15 +203,11 @@ class _PGNMF(NMF): def __init__(self, n_components=None, solver='pg', init=None, tol=1e-4, max_iter=200, random_state=None, alpha=0., l1_ratio=0., nls_max_iter=10): + super(_PGNMF, self).__init__( + n_components=n_components, init=init, solver=solver, tol=tol, + max_iter=max_iter, random_state=random_state, alpha=alpha, + l1_ratio=l1_ratio) self.nls_max_iter = nls_max_iter - self.n_components = n_components - self.init = init - self.solver = solver - self.tol = tol - self.max_iter = max_iter - self.random_state = random_state - self.alpha = alpha - self.l1_ratio = l1_ratio def fit(self, X, y=None, **params): self.fit_transform(X, **params) diff --git a/benchmarks/bench_plot_randomized_svd.py b/benchmarks/bench_plot_randomized_svd.py index e4c2f63e05632..96a0e91fa4400 100644 --- a/benchmarks/bench_plot_randomized_svd.py +++ b/benchmarks/bench_plot_randomized_svd.py @@ -182,7 +182,7 @@ def plot_time_vs_s(time, norm, point_labels, title): plt.figure() colors = ['g', 'b', 'y'] for i, l in enumerate(sorted(norm.keys())): - if l is not "fbpca": + if l != "fbpca": plt.plot(time[l], norm[l], label=l, marker='o', c=colors.pop()) else: plt.plot(time[l], norm[l], label=l, marker='^', c='red') @@ -200,7 +200,7 @@ def scatter_time_vs_s(time, norm, point_labels, title): plt.figure() size = 100 for i, l in enumerate(sorted(norm.keys())): - if l is not "fbpca": + if l != "fbpca": plt.scatter(time[l], norm[l], label=l, marker='o', c='b', s=size) for label, x, y in zip(point_labels, list(time[l]), list(norm[l])): plt.annotate(label, xy=(x, y), xytext=(0, -80), diff --git a/sklearn/covariance/graph_lasso_.py b/sklearn/covariance/graph_lasso_.py index aa5be9cb5253f..9292e9341208f 100644 --- a/sklearn/covariance/graph_lasso_.py +++ b/sklearn/covariance/graph_lasso_.py @@ -324,15 +324,13 @@ class GraphLasso(EmpiricalCovariance): def __init__(self, alpha=.01, mode='cd', tol=1e-4, enet_tol=1e-4, max_iter=100, verbose=False, assume_centered=False): + super(GraphLasso, self).__init__(assume_centered=assume_centered) self.alpha = alpha self.mode = mode self.tol = tol self.enet_tol = enet_tol self.max_iter = max_iter self.verbose = verbose - self.assume_centered = assume_centered - # The base class needs this for the score method - self.store_precision = True def fit(self, X, y=None): @@ -551,18 +549,13 @@ class GraphLassoCV(GraphLasso): def __init__(self, alphas=4, n_refinements=4, cv=None, tol=1e-4, enet_tol=1e-4, max_iter=100, mode='cd', n_jobs=1, verbose=False, assume_centered=False): + super(GraphLassoCV, self).__init__( + mode=mode, tol=tol, verbose=verbose, enet_tol=enet_tol, + max_iter=max_iter, assume_centered=assume_centered) self.alphas = alphas self.n_refinements = n_refinements - self.mode = mode - self.tol = tol - self.enet_tol = enet_tol - self.max_iter = max_iter - self.verbose = verbose self.cv = cv self.n_jobs = n_jobs - self.assume_centered = assume_centered - # The base class needs this for the score method - self.store_precision = True @property @deprecated("Attribute grid_scores was deprecated in version 0.19 and " diff --git a/sklearn/decomposition/sparse_pca.py b/sklearn/decomposition/sparse_pca.py index 23d1163fdc881..f5250cac8ace5 100644 --- a/sklearn/decomposition/sparse_pca.py +++ b/sklearn/decomposition/sparse_pca.py @@ -257,18 +257,14 @@ class MiniBatchSparsePCA(SparsePCA): def __init__(self, n_components=None, alpha=1, ridge_alpha=0.01, n_iter=100, callback=None, batch_size=3, verbose=False, shuffle=True, n_jobs=1, method='lars', random_state=None): - - self.n_components = n_components - self.alpha = alpha - self.ridge_alpha = ridge_alpha + super(MiniBatchSparsePCA, self).__init__( + n_components=n_components, alpha=alpha, verbose=verbose, + ridge_alpha=ridge_alpha, n_jobs=n_jobs, method=method, + random_state=random_state) self.n_iter = n_iter self.callback = callback self.batch_size = batch_size - self.verbose = verbose self.shuffle = shuffle - self.n_jobs = n_jobs - self.method = method - self.random_state = random_state def fit(self, X, y=None): """Fit the model from data in X. diff --git a/sklearn/mixture/gaussian_mixture.py b/sklearn/mixture/gaussian_mixture.py index 11784f86febfa..59e4942d508c1 100644 --- a/sklearn/mixture/gaussian_mixture.py +++ b/sklearn/mixture/gaussian_mixture.py @@ -91,7 +91,7 @@ def _check_precision_matrix(precision, covariance_type): def _check_precisions_full(precisions, covariance_type): """Check the precision matrices are symmetric and positive-definite.""" - for k, prec in enumerate(precisions): + for prec in precisions: _check_precision_matrix(prec, covariance_type) diff --git a/sklearn/random_projection.py b/sklearn/random_projection.py index eebb8da80da4a..f498873d66940 100644 --- a/sklearn/random_projection.py +++ b/sklearn/random_projection.py @@ -309,7 +309,7 @@ def __init__(self, n_components='auto', eps=0.1, dense_output=False, self.random_state = random_state @abstractmethod - def _make_random_matrix(n_components, n_features): + def _make_random_matrix(self, n_components, n_features): """ Generate the random projection matrix Parameters diff --git a/sklearn/tree/export.py b/sklearn/tree/export.py index f526c771af047..451c0f0b1e93c 100644 --- a/sklearn/tree/export.py +++ b/sklearn/tree/export.py @@ -66,7 +66,7 @@ def _color_brew(n): class Sentinel(object): - def __repr__(): + def __repr__(self): return '"tree.dot"' SENTINEL = Sentinel() diff --git a/sklearn/utils/mocking.py b/sklearn/utils/mocking.py index 013644a285115..06d5a7cbd3671 100644 --- a/sklearn/utils/mocking.py +++ b/sklearn/utils/mocking.py @@ -36,6 +36,9 @@ def __array__(self, dtype=None): def __eq__(self, other): return MockDataFrame(self.array == other.array) + def __ne__(self, other): + return not self == other + class CheckingClassifier(BaseEstimator, ClassifierMixin): """Dummy classifier to test pipelining and meta-estimators. diff --git a/sklearn/utils/sparsefuncs.py b/sklearn/utils/sparsefuncs.py index 9b081ec45f421..38b8b0a6eff16 100644 --- a/sklearn/utils/sparsefuncs.py +++ b/sklearn/utils/sparsefuncs.py @@ -302,9 +302,9 @@ def inplace_swap_row(X, m, n): Index of the row of X to be swapped. """ if isinstance(X, sp.csc_matrix): - return inplace_swap_row_csc(X, m, n) + inplace_swap_row_csc(X, m, n) elif isinstance(X, sp.csr_matrix): - return inplace_swap_row_csr(X, m, n) + inplace_swap_row_csr(X, m, n) else: _raise_typeerror(X) @@ -329,9 +329,9 @@ def inplace_swap_column(X, m, n): if n < 0: n += X.shape[1] if isinstance(X, sp.csc_matrix): - return inplace_swap_row_csr(X, m, n) + inplace_swap_row_csr(X, m, n) elif isinstance(X, sp.csr_matrix): - return inplace_swap_row_csc(X, m, n) + inplace_swap_row_csc(X, m, n) else: _raise_typeerror(X)