From feb10b0bf25ae8586c3b08f862131fdc8c936c19 Mon Sep 17 00:00:00 2001 From: Philip Loche Date: Thu, 13 Feb 2025 14:05:20 +0100 Subject: [PATCH] fix some tests --- .github/workflows/build.yml | 2 +- .github/workflows/docs.yml | 2 +- .github/workflows/lint.yml | 2 +- .github/workflows/tests.yml | 2 +- .gitignore | 1 + .readthedocs.yaml | 2 +- pyproject.toml | 5 +- src/skmatter/_selection.py | 22 ++-- src/skmatter/decomposition/_kernel_pcovr.py | 2 +- src/skmatter/decomposition/_pcovr.py | 4 +- src/skmatter/utils/_pcovr_utils.py | 109 +++++++++++------- ...e.tsf-492-wpa-0-247.epfl.ch.11311.XpjwIfdx | Bin 53248 -> 0 bytes tests/test_feature_pcov_fps.py | 5 +- tests/test_greedy_selector.py | 8 +- tests/test_kernel_pcovr.py | 4 +- tests/test_pcovr.py | 9 +- tests/test_sample_pcov_fps.py | 5 +- 17 files changed, 105 insertions(+), 79 deletions(-) delete mode 100644 tests/.coverage.tsf-492-wpa-0-247.epfl.ch.11311.XpjwIfdx diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 058303f65..61e753ea9 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -15,7 +15,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v5 with: - python-version: "3.12" + python-version: "3.13" - name: install tests dependencies run: python -m pip install tox diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 75b82499a..1fa0d4420 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -16,7 +16,7 @@ jobs: - name: setup Python uses: actions/setup-python@v5 with: - python-version: "3.12" + python-version: "3.13" - name: install tests dependencies run: python -m pip install tox diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml index 1108289fd..5ae3af316 100644 --- a/.github/workflows/lint.yml +++ b/.github/workflows/lint.yml @@ -14,7 +14,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v5 with: - python-version: "3.12" + python-version: "3.13" - name: install tests dependencies run: python -m pip install tox diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index d9ebe3475..fe3609798 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -12,7 +12,7 @@ jobs: strategy: matrix: os: [ubuntu-22.04, macos-14, windows-2022] - python-version: ["3.9", "3.12"] + python-version: ["3.0", "3.13"] steps: - uses: actions/checkout@v4 diff --git a/.gitignore b/.gitignore index 226933088..1f74b6f04 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +*.coverage* *.pyc *.ipynb_checkpoints* __pycache__ diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 71882236f..b4c827c42 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -9,7 +9,7 @@ version: 2 build: os: ubuntu-22.04 tools: - python: "3.12" + python: "3.13" # Build documentation in the docs/ directory with Sphinx sphinx: diff --git a/pyproject.toml b/pyproject.toml index db7056b63..374d06293 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,7 +19,7 @@ authors = [ {name = "Michele Ceriotti"} ] readme = "README.rst" -requires-python = ">=3.9" +requires-python = ">=3.10" license = {text = "BSD-3-Clause"} classifiers = [ "Development Status :: 4 - Beta", @@ -75,9 +75,6 @@ include = [ [tool.coverage.xml] output = 'tests/coverage.xml' -[tool.pytest.ini_options] -testpaths = "tests" - [tool.isort] skip = "__init__.py" profile = "black" diff --git a/src/skmatter/_selection.py b/src/skmatter/_selection.py index 50e55cff3..224c020a7 100644 --- a/src/skmatter/_selection.py +++ b/src/skmatter/_selection.py @@ -561,8 +561,7 @@ def score(self, X, y=None): Parameters ---------- - X : numpy.ndarray of shape [n_samples, n_features] - The input samples. + X : ignored y : ignored Returns @@ -570,8 +569,7 @@ def score(self, X, y=None): score : numpy.ndarray of (n_to_select_from_) :math:`\pi` importance for the given samples or features """ - X, y = validate_data(self, X, y, reset=False) - + validate_data(self, X, y, reset=False) # present for API consistency return self.pi_ def _init_greedy_search(self, X, y, n_to_select): @@ -746,8 +744,7 @@ def score(self, X, y=None): score : numpy.ndarray of (n_to_select_from_) :math:`\pi` importance for the given samples or features """ - X, y = validate_data(self, X, y, reset=False) - + validate_data(self, X, y, reset=False) # present for API consistency return self.pi_ def _init_greedy_search(self, X, y, n_to_select): @@ -941,8 +938,7 @@ def score(self, X, y=None): ------- hausdorff : Hausdorff distances """ - X, y = validate_data(self, X, y, reset=False) - + validate_data(self, X, y, reset=False) return self.hausdorff_ def get_distance(self): @@ -1079,15 +1075,16 @@ def __init__( ) def fit(self, X, y=None, warm_start=False): - if self.mixing == 1.0: raise ValueError( - "Mixing = 1.0 corresponds to traditional FPS." - "Please use the FPS class." + "Mixing = 1.0 corresponds to traditional FPS. Please use the FPS class." ) return super().fit(X, y) + # docstring is inherited and set from the base class + fit.__doc__ = GreedySelector.fit.__doc__ + def score(self, X, y=None): """Returns the Hausdorff distances of all samples to previous selections. @@ -1104,8 +1101,7 @@ def score(self, X, y=None): ------- hausdorff : Hausdorff distances """ - X, y = validate_data(self, X, y, reset=False) - + validate_data(self, X, y, reset=False) return self.hausdorff_ def get_distance(self): diff --git a/src/skmatter/decomposition/_kernel_pcovr.py b/src/skmatter/decomposition/_kernel_pcovr.py index 65fe39a3e..825a0cf92 100644 --- a/src/skmatter/decomposition/_kernel_pcovr.py +++ b/src/skmatter/decomposition/_kernel_pcovr.py @@ -474,7 +474,7 @@ def score(self, X, y): """ check_is_fitted(self, ["pkt_", "X_fit_"]) - X, y = validate_data(self, X, y, reset=False) + X = validate_data(self, X, reset=False) K_NN = self._get_kernel(self.X_fit_, self.X_fit_) K_VN = self._get_kernel(X, self.X_fit_) diff --git a/src/skmatter/decomposition/_pcovr.py b/src/skmatter/decomposition/_pcovr.py index 8cdd24680..bc094a720 100644 --- a/src/skmatter/decomposition/_pcovr.py +++ b/src/skmatter/decomposition/_pcovr.py @@ -10,7 +10,7 @@ from sklearn.decomposition._pca import _infer_dimension from sklearn.linear_model import LinearRegression, Ridge, RidgeCV from sklearn.linear_model._base import LinearModel -from sklearn.utils import check_random_state +from sklearn.utils import check_array, check_random_state from sklearn.utils._arpack import _init_arpack_v0 from sklearn.utils.extmath import randomized_svd, stable_cumsum, svd_flip from sklearn.utils.validation import check_is_fitted, validate_data @@ -585,7 +585,7 @@ def predict(self, X=None, T=None): X = validate_data(self, X, reset=False) return X @ self.pxy_ else: - T = validate_data(self, T, reset=False) + T = check_array(T) return T @ self.pty_ def transform(self, X=None): diff --git a/src/skmatter/utils/_pcovr_utils.py b/src/skmatter/utils/_pcovr_utils.py index 15286e341..8852a6386 100644 --- a/src/skmatter/utils/_pcovr_utils.py +++ b/src/skmatter/utils/_pcovr_utils.py @@ -9,18 +9,30 @@ def check_lr_fit(regressor, X, y): - r""" + """ Checks that a (linear) regressor is fitted, and if not, - fits it with the provided data - - :param regressor: sklearn-style regressor - :type regressor: object - :param X: feature matrix with which to fit the regressor - if it is not already fitted - :type X: array - :param y: target values with which to fit the regressor - if it is not already fitted - :type y: array + fits it with the provided data. + + Parameters + ---------- + regressor : object + sklearn-style regressor + X : array-like + Feature matrix with which to fit the regressor if it is not already fitted + y : array-like + Target values with which to fit the regressor if it is not already fitted + + Returns + ------- + fitted_regressor : object + The fitted regressor. If input regressor was already fitted and compatible with + the data, returns a deep copy. Otherwise returns a newly fitted regressor. + + Raises + ------ + ValueError + If the fitted regressor's coefficients dimensions are incompatible with the + target space. """ try: check_is_fitted(regressor) @@ -32,18 +44,18 @@ def check_lr_fit(regressor, X, y): # Check compatibility with y if fitted_regressor.coef_.ndim != y.ndim: raise ValueError( - "The regressor coefficients have a dimension incompatible " - "with the supplied target space. " - "The coefficients have dimension %d and the targets " - "have dimension %d" % (fitted_regressor.coef_.ndim, y.ndim) + "The regressor coefficients have a dimension incompatible with the " + "supplied target space. The coefficients have dimension " + f"{fitted_regressor.coef_.ndim} and the targets have dimension " + f"{y.ndim}" ) elif y.ndim == 2: if fitted_regressor.coef_.shape[0] != y.shape[1]: raise ValueError( - "The regressor coefficients have a shape incompatible " - "with the supplied target space. " - "The coefficients have shape %r and the targets " - "have shape %r" % (fitted_regressor.coef_.shape, y.shape) + "The regressor coefficients have a shape incompatible with the " + "supplied target space. The coefficients have shape " + f"{fitted_regressor.coef_.shape} and the targets have shape " + f"{y.shape}" ) except NotFittedError: @@ -54,20 +66,37 @@ def check_lr_fit(regressor, X, y): def check_krr_fit(regressor, K, X, y): - r""" + """ Checks that a (kernel ridge) regressor is fitted, and if not, - fits it with the provided data - - :param regressor: sklearn-style regressor - :type regressor: object - :param K: kernel matrix with which to fit the regressor - if it is not already fitted - :type K: array - :param X: feature matrix with which to check the regressor - :type X: array - :param y: target values with which to fit the regressor - if it is not already fitted - :type y: array + fits it with the provided data. + + Parameters + ---------- + regressor : object + sklearn-style regressor + K : array-like + Kernel matrix with which to fit the regressor if it is not already fitted + X : array-like + Feature matrix with which to check the regressor + y : array-like + Target values with which to fit the regressor if it is not already fitted + + Returns + ------- + fitted_regressor : object + The fitted regressor. If input regressor was already fitted and compatible with + the data, returns a deep copy. Otherwise returns a newly fitted regressor. + + Raises + ------ + ValueError + If the fitted regressor's coefficients dimensions are incompatible with the + target space. + + Notes + ----- + For unfitted regressors, sets the kernel to "precomputed" before fitting with the + provided kernel matrix K to avoid recomputation. """ try: check_is_fitted(regressor) @@ -79,18 +108,18 @@ def check_krr_fit(regressor, K, X, y): # Check compatibility with y if fitted_regressor.dual_coef_.ndim != y.ndim: raise ValueError( - "The regressor coefficients have a dimension incompatible " - "with the supplied target space. " - "The coefficients have dimension %d and the targets " - "have dimension %d" % (fitted_regressor.dual_coef_.ndim, y.ndim) + "The regressor coefficients have a dimension incompatible with the " + "supplied target space. The coefficients have dimension " + f"{fitted_regressor.dual_coef_.ndim} and the targets have dimension " + f"{y.ndim}" ) elif y.ndim == 2: if fitted_regressor.dual_coef_.shape[1] != y.shape[1]: raise ValueError( - "The regressor coefficients have a shape incompatible " - "with the supplied target space. " - "The coefficients have shape %r and the targets " - "have shape %r" % (fitted_regressor.dual_coef_.shape, y.shape) + "The regressor coefficients have a shape incompatible with the " + "supplied target space. The coefficients have shape " + f"{fitted_regressor.dual_coef_.shape} and the targets have shape " + f"{y.shape}" ) except NotFittedError: diff --git a/tests/.coverage.tsf-492-wpa-0-247.epfl.ch.11311.XpjwIfdx b/tests/.coverage.tsf-492-wpa-0-247.epfl.ch.11311.XpjwIfdx deleted file mode 100644 index 5d637632bf921d7fd0c0dfe157ca23af76774c48..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 53248 zcmeI)O>Y}T7zglOyYv4m3ax6_rXM;(~-bUXPOn@2<1E z&dUKIr$~{I_y&mY#5dsB6E{v=c%GddubsqIZ&l5I6+8PfGduH}XJ(vi+Hamc@e(Bl zVdTq1yl<^rwrxEU!m_L~z1HYuHivfZm;?H5&+ISSEnDr&M{Bijt!n8vtM>ic)7oD3 z_qF#{|E&7uUswNdWZ9()*dPD_2teTfEiidjb?RGN_T^8B>w!J;EFQV{Fj8r5B-cSiI=zFeAyx>SA$I7H0$Ewc@9i5}4juW=i z{Jhuo`jjhCM^wZp@_ZRxh#%EOD@~ByEm7x*K0$>j?4s_YYm;qoAP)-1-W6==i2uo8MwzPZV5SUp&L>?&lBC+ zDD)pBp%{8W+RPyK5-$vdI#=#EQTx;-z6r#t1jpqZXt5ITH)aoq4InGX^kMZ=*82kDUE+(LH_Mf2>K zd0;SP!~;!)SwgDm8;v%uEY(5uhGB0$*3yWH6%7!Y3rw=XIB$S@+yC+ zF7{64kYH_j(V^67?X>uCgUxjh( z(Xz_RR{XI!D;mc#=2<9ih+Y^Dl??RSKsg@AbWbl9X&r8^N}uLs#1~w~(P<;ClUZDN znm?pLXT}%p_`VGK*?Psxur8J6ejc2BA3cdsM$w=_8PgEGR;DR5yUH_`DZf1;6E4-4 zeLdW{Q)Ws$J61P})2q=JGEs@=E5S+9%A|pHCS&17iZ0Sx+H4eG6$ac}-44I=PsuC% zQEswhJN5hb?a4SBjC!8w#3$X z_R^}oto`#=HV~DD00bZa0SG_<0uX=z1Rwwb2tZ&eP%YlG&94CpmEv|e`z=8F5B%4s z$*=z{}fB*y_009U<00Izz00c4tJpV^1KmY;|fB*y_009U<00Izz00fp_ z0MGxIzmL&E2tWV=5P$##AOHafKmY;|fB>HVBL*M<0SG_<0uX=z1Rwwb2tWV=%P)ZE z|I6RUXdwh3009U<00Izz00bZa0SG_<&;Jnv5P$##AOHafKmY;|fB*y_0De diff --git a/tests/test_feature_pcov_fps.py b/tests/test_feature_pcov_fps.py index 321cc78ee..e6910f9a1 100644 --- a/tests/test_feature_pcov_fps.py +++ b/tests/test_feature_pcov_fps.py @@ -24,11 +24,12 @@ def test_restart(self): def test_no_mixing_1(self): """Check that the model throws an error when mixing = 1.0.""" + selector = PCovFPS(n_to_select=1, mixing=1.0) with self.assertRaises(ValueError) as cm: - _ = PCovFPS(n_to_select=1, mixing=1.0) + selector.fit(self.X, y=self.y) self.assertEqual( str(cm.exception), - "Mixing = 1.0 corresponds to traditional FPS." "Please use the FPS class.", + "Mixing = 1.0 corresponds to traditional FPS. Please use the FPS class.", ) diff --git a/tests/test_greedy_selector.py b/tests/test_greedy_selector.py index 0bfe6de99..f85dbeb34 100644 --- a/tests/test_greedy_selector.py +++ b/tests/test_greedy_selector.py @@ -73,7 +73,7 @@ def test_bad_transform(self): _ = selector.transform(self.X[:, :3]) self.assertEqual( str(cm.exception), - "X has a different shape than during fitting. Reshape your data.", + "X has 3 features, but GreedyTester is expecting 10 features as input.", ) def test_no_nfeatures(self): @@ -124,8 +124,8 @@ def test_size_input(self): selector_feature.fit(X) self.assertEqual( str(cm.exception), - f"Found array with 1 feature(s) (shape={X.shape})" - " while a minimum of 2 is required.", + f"Found array with 1 feature(s) (shape={X.shape}) while a minimum of 2 is " + "required by GreedyTester.", ) X = X.reshape(1, -1) @@ -135,7 +135,7 @@ def test_size_input(self): self.assertEqual( str(cm.exception), f"Found array with 1 sample(s) (shape={X.shape}) while a minimum of 2 is " - "required.", + "required by GreedyTester.", ) diff --git a/tests/test_kernel_pcovr.py b/tests/test_kernel_pcovr.py index e4bbda52e..80adf584e 100644 --- a/tests/test_kernel_pcovr.py +++ b/tests/test_kernel_pcovr.py @@ -182,6 +182,8 @@ def test_centerer(self): self.assertTrue(hasattr(kpcovr, "centerer_")) _ = kpcovr.predict(self.X) _ = kpcovr.transform(self.X) + + print(self.Y.shape) _ = kpcovr.score(self.X, self.Y) def test_prefit_regressor(self): @@ -255,7 +257,7 @@ def test_incompatible_coef_shape(self): # Dimension mismatch with self.assertRaises(ValueError) as cm: - kpcovr.fit(self.X, self.Y[:, 0]) + kpcovr.fit(self.X, np.zeros(self.Y.shape + (2,))) self.assertTrue( str(cm.exception), "The regressor coefficients have a dimension incompatible " diff --git a/tests/test_pcovr.py b/tests/test_pcovr.py index e589978d2..2059eed44 100644 --- a/tests/test_pcovr.py +++ b/tests/test_pcovr.py @@ -491,13 +491,12 @@ def test_incompatible_coef_shape(self): # Dimension mismatch with self.assertRaises(ValueError) as cm: - pcovr.fit(self.X, self.Y.squeeze()) + pcovr.fit(self.X, np.zeros((self.Y.shape[0], 2))) self.assertEqual( str(cm.exception), - "The regressor coefficients have a dimension incompatible " - "with the supplied target space. " - "The coefficients have dimension %d and the targets " - "have dimension %d" % (regressor.coef_.ndim, self.Y.squeeze().ndim), + "The regressor coefficients have a dimension incompatible with the " + "supplied target space. The coefficients have dimension 1 and the targets " + "have dimension 2", ) # Shape mismatch (number of targets) diff --git a/tests/test_sample_pcov_fps.py b/tests/test_sample_pcov_fps.py index 7679abb0a..b6ed08662 100644 --- a/tests/test_sample_pcov_fps.py +++ b/tests/test_sample_pcov_fps.py @@ -24,11 +24,12 @@ def test_restart(self): def test_no_mixing_1(self): """Check that the model throws an error when mixing = 1.0.""" + selector = PCovFPS(n_to_select=1, mixing=1.0) with self.assertRaises(ValueError) as cm: - _ = PCovFPS(n_to_select=1, mixing=1.0) + selector.fit(self.X, y=self.y) self.assertEqual( str(cm.exception), - "Mixing = 1.0 corresponds to traditional FPS." "Please use the FPS class.", + "Mixing = 1.0 corresponds to traditional FPS. Please use the FPS class.", )