chore(deps): add compatibility with python3.13 and remove python3.8

.github/workflows/ci.yml

@@ -17,14 +17,15 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v3
-    - name: Set up Python 3.10
+    - name: Set up Python 3.13
       uses: actions/setup-python@v3
       with:
-        python-version: "3.10"
+        python-version: "3.13"
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install poetry
+        pip install poetry poetry-plugin-export
+        poetry self add poetry-plugin-export
         poetry export --with dev > requirements.txt
         pip install -r requirements.txt
     - name: Lint with flake8
@@ -39,7 +40,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
     steps:
     - uses: actions/checkout@v3
     - uses: codecov/codecov-action@v3
@@ -50,7 +51,8 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install poetry
+        pip install poetry poetry-plugin-export
+        poetry self add poetry-plugin-export
         poetry install --with dev
     - name: Test with pytest
       run: |

.github/workflows/pypi.yml

@@ -25,7 +25,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v3
       with:
-        python-version: '3.10'
+        python-version: '3.13'
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip

README.md

@@ -2,9 +2,10 @@
 [![Documentation Status](https://readthedocs.org/projects/pygam/badge/?version=latest)](https://pygam.readthedocs.io/en/latest/?badge=latest)
 [![PyPI version](https://badge.fury.io/py/pygam.svg)](https://badge.fury.io/py/pygam)
 [![codecov](https://codecov.io/gh/dswah/pygam/branch/master/graph/badge.svg)](https://codecov.io/gh/dswah/pygam)
-[![python38](https://img.shields.io/badge/python-3.8-blue.svg)](https://badge.fury.io/py/pygam)
-[![python39](https://img.shields.io/badge/python-3.9-blue.svg)](https://badge.fury.io/py/pygam)
 [![python310](https://img.shields.io/badge/python-3.10-blue.svg)](https://badge.fury.io/py/pygam)
+[![python311](https://img.shields.io/badge/python-3.11-blue.svg)](https://badge.fury.io/py/pygam)
+[![python312](https://img.shields.io/badge/python-3.12-blue.svg)](https://badge.fury.io/py/pygam)
+[![python313](https://img.shields.io/badge/python-3.13-blue.svg)](https://badge.fury.io/py/pygam)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1208723.svg)](https://doi.org/10.5281/zenodo.1208723)
 
 

gen_imgs.py

@@ -38,11 +38,11 @@ def gen_basis_fns():
 
     plt.figure()
     fig, ax = plt.subplots(2, 1)
-    ax[0].plot(XX, gam._modelmat(XX, term=0).A)
+    ax[0].plot(XX, gam._modelmat(XX, term=0).toarray())
     ax[0].set_title('b-Spline Basis Functions')
 
     ax[1].scatter(X, y, facecolor='gray', edgecolors='none')
-    ax[1].plot(XX, gam._modelmat(XX).A * gam.coef_)
+    ax[1].plot(XX, gam._modelmat(XX).toarray() * gam.coef_)
     ax[1].plot(XX, gam.predict(XX), 'k')
     ax[1].set_title('Fitted Model')
     fig.tight_layout()

pygam/pygam.py

@@ -703,7 +703,7 @@ def _initial_estimate(self, y, modelmat):
 
         # solve the linear problem
         return np.linalg.solve(
-            load_diagonal(modelmat.T.dot(modelmat).A), modelmat.T.dot(y_)
+            load_diagonal(modelmat.T.dot(modelmat).toarray()), modelmat.T.dot(y_)
         )
 
         # not sure if this is faster...
@@ -780,7 +780,7 @@ def _pirls(self, X, Y, weights):
             self._on_loop_start(vars())
 
             WB = W.dot(modelmat[mask, :])  # common matrix product
-            Q, R = np.linalg.qr(WB.A)
+            Q, R = np.linalg.qr(WB.toarray())
 
             if not np.isfinite(Q).all() or not np.isfinite(R).all():
                 raise ValueError(
@@ -1401,7 +1401,7 @@ def _get_quantiles(
         idxs = self.terms.get_coef_indices(term)
         cov = self.statistics_['cov'][idxs][:, idxs]
 
-        var = (modelmat.dot(cov) * modelmat.A).sum(axis=1)
+        var = (modelmat.dot(cov) * modelmat.toarray()).sum(axis=1)
         if prediction:
             var += self.distribution.scale
 

pygam/terms.py

@@ -1500,7 +1500,7 @@ def _build_marginal_constraints(self, i, coef, constraint_lam, constraint_l2):
             )
 
             # now enter it into the composite
-            composite_C[tuple(np.meshgrid(slice_, slice_))] = slice_C.A
+            composite_C[tuple(np.meshgrid(slice_, slice_))] = slice_C.toarray()
 
         return sp.sparse.csc_matrix(composite_C)
 

pygam/tests/test_penalties.py

@@ -23,13 +23,13 @@ def test_single_spline_penalty():
     monotonic_ and convexity_ should be 0.
     """
     coef = np.array(1.0)
-    assert np.alltrue(derivative(1, coef).A == 0.0)
-    assert np.alltrue(l2(1, coef).A == 1.0)
-    assert np.alltrue(monotonic_inc(1, coef).A == 0.0)
-    assert np.alltrue(monotonic_dec(1, coef).A == 0.0)
-    assert np.alltrue(convex(1, coef).A == 0.0)
-    assert np.alltrue(concave(1, coef).A == 0.0)
-    assert np.alltrue(none(1, coef).A == 0.0)
+    assert np.all(derivative(1, coef).toarray() == 0.0)
+    assert np.all(l2(1, coef).toarray() == 1.0)
+    assert np.all(monotonic_inc(1, coef).toarray() == 0.0)
+    assert np.all(monotonic_dec(1, coef).toarray() == 0.0)
+    assert np.all(convex(1, coef).toarray() == 0.0)
+    assert np.all(concave(1, coef).toarray() == 0.0)
+    assert np.all(none(1, coef).toarray() == 0.0)
 
 
 def test_wrap_penalty():
@@ -43,12 +43,12 @@ def test_wrap_penalty():
 
     fit_linear = True
     p = wrap_penalty(none, fit_linear, linear_penalty=linear_penalty)
-    P = p(n, coef).A
+    P = p(n, coef).toarray()
     assert P.sum() == linear_penalty
 
     fit_linear = False
     p = wrap_penalty(none, fit_linear, linear_penalty=linear_penalty)
-    P = p(n, coef).A
+    P = p(n, coef).toarray()
     assert P.sum() == 0.0
 
 

pygam/tests/test_terms.py

@@ -315,10 +315,10 @@ def der1(*args, **kwargs):
 
     # check all the dimensions
     for i in range(3):
-        P = term._build_marginal_penalties(i).A
+        P = term._build_marginal_penalties(i).toarray()
         C = term._build_marginal_constraints(
             i, -np.arange(term.n_coefs), constraint_lam=1, constraint_l2=0
-        ).A
+        ).toarray()
 
         assert (P == C).all()
 
@@ -362,11 +362,11 @@ def test_compose_penalties(self):
         term = SplineTerm(feature=0, penalties=['auto', 'none'])
 
         # penalties should be equivalent
-        assert (term.build_penalties() == base_term.build_penalties()).A.all()
+        assert (term.build_penalties() == base_term.build_penalties()).toarray().all()
 
         # multitple penalties should be additive, not multiplicative,
         # so 'none' penalty should have no effect
-        assert np.abs(term.build_penalties().A).sum() > 0
+        assert np.abs(term.build_penalties().toarray()).sum() > 0
 
     def test_compose_constraints(self, hepatitis_X_y):
         """we should be able to compose penalties

pygam/utils.py

@@ -64,7 +64,7 @@
 
         if sparse:
             return L.T  # upper triangular factorization
-        return L.T.A  # upper triangular factorization
+        return L.T.toarray()  # upper triangular factorization
 
     else:
         msg = (
@@ -78,7 +78,7 @@
             warnings.warn(msg)
 
         if sp.sparse.issparse(A):
-            A = A.A
+            A = A.toarray()
 
         try:
             L = sp.linalg.cholesky(A, lower=False)
@@ -951,10 +951,10 @@
         raise ValueError('both arguments must have the same number of samples')
 
     if sp.sparse.issparse(a):
-        a = a.A
+        a = a.toarray()
 
     if sp.sparse.issparse(b):
-        b = b.A
+        b = b.toarray()
 
     tensor = a[..., :, None] * b[..., None, :]
 

pyproject.toml

@@ -6,35 +6,33 @@ authors = ["Daniel Servén Marín", "Charlie Brummitt"]
 license = "Apache-2.0"
 readme = "README.md"
 
+[tool.poetry.requires-plugins]
+poetry-plugin-export = "^1.8"
+
 [tool.poetry.dependencies]
-python = ">=3.8.1, <3.13"
-numpy = [
-  { version = ">=1.24.2,<1.25", python = "<3.9,>=3.8" },
-  { version = ">=1.25", python = "<3.13,>=3.9" },
-]
-progressbar2 = "^4.2.0"
-scipy = [
-  { version = ">=1.10.1,<1.11", python = "<3.9,>=3.8" },
-  { version = ">=1.11.1,<1.12", python = "<3.13,>=3.9" }
-]
+python = ">=3.10, <3.14"
+numpy = "^2.1.0"
+progressbar2 = "^4.5.0"
+scipy = "1.15.*"
 
 [tool.poetry.group.dev.dependencies]
-pandas = ">=1.6"
-pytest = "^7.2.2"
-flake8 = "^6.0.0"
-codecov = "^2.1.12"
-pytest-cov = "^4.0.0"
-mock = "^5.0.1"
-nbsphinx = "^0.9.0"
-sphinx-rtd-theme = "^1.2.0"
+pandas = "^2.2.3"
+pytest = "^8.3.4"
+flake8 = "^7.1.1"
+codecov = "^2.1.13"
+pytest-cov = "^6.0.0"
+mock = "^5.1.0"
+nbsphinx = "^0.9.6"
+sphinx-rtd-theme = "^3.0.2"
 sphinxcontrib-napoleon = "^0.7"
-ipython = "^8.11.0"
-black = "^23.1.0"
+ipython = "^8.31.0"
+black = "^24.10.0"
+pyzmq="^26.2.0"
 
 [tool.black]
 line-length = 88
 skip-string-normalization = true
-target-version = ['py39']
+target-version = ['py313']
 include = '\.pyi?$'
 exclude = '''
 /(