Replace estimagic dependency by optimagic (#17)

timmens · web-flow · commit 980e9ac5c361 · 2025-06-16T09:58:06.000+02:00
diff --git a/.envs/testenv-linux.yml b/.envs/testenv-linux.yml
@@ -10,7 +10,7 @@ dependencies:
   - pytest  # dev, tests
   - pytest-cov  # tests
   - pytest-xdist  # dev, tests
-  - estimagic  # run, tests
+  - optimagic  # run, tests
   - numba  # run, tests
   - numpy>=1.17.0  # run, tests
   - pandas  # run, tests
diff --git a/.envs/testenv-others.yml b/.envs/testenv-others.yml
@@ -9,7 +9,7 @@ dependencies:
   - pytest  # dev, tests
   - pytest-cov  # tests
   - pytest-xdist  # dev, tests
-  - estimagic  # run, tests
+  - optimagic  # run, tests
   - numba  # run, tests
   - numpy>=1.17.0  # run, tests
   - pandas  # run, tests
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
@@ -21,18 +21,18 @@ jobs:
         os:
           - ubuntu-latest
         python-version:
-          - '3.8'
-          - '3.9'
           - '3.10'
+          - '3.11'
+          - '3.12'
     steps:
       - uses: actions/checkout@v3
       - name: create build environment
-        uses: mamba-org/provision-with-micromamba@main
+        uses: mamba-org/setup-micromamba@v2
         with:
           environment-file: ./.envs/testenv-linux.yml
           environment-name: tranquilo
-          cache-env: true
-          extra-specs: |
+          cache-environment: true
+          create-args: >-
             python=${{ matrix.python-version }}
       - name: run pytest
         shell: bash -l {0}
@@ -54,18 +54,18 @@ jobs:
           - macos-latest
           - windows-latest
         python-version:
-          - '3.8'
-          - '3.9'
           - '3.10'
+          - '3.11'
+          - '3.12'
     steps:
       - uses: actions/checkout@v3
       - name: create build environment
-        uses: mamba-org/provision-with-micromamba@main
+        uses: mamba-org/setup-micromamba@v2
         with:
           environment-file: ./.envs/testenv-others.yml
           environment-name: tranquilo
-          cache-env: true
-          extra-specs: |
+          cache-environment: true
+          create-args: >-
             python=${{ matrix.python-version }}
       - name: run pytest
         shell: bash -l {0}
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -61,17 +61,17 @@ repos:
     rev: 1.13.0
     hooks:
       - id: blacken-docs
-  - repo: https://github.com/PyCQA/docformatter
-    rev: v1.5.1
-    hooks:
-      - id: docformatter
-        args:
-          - --in-place
-          - --wrap-summaries
-          - '88'
-          - --wrap-descriptions
-          - '88'
-          - --blank
+#   - repo: https://github.com/PyCQA/docformatter
+#     rev: v1.5.1
+#     hooks:
+#       - id: docformatter
+#         args:
+#           - --in-place
+#           - --wrap-summaries
+#           - '88'
+#           - --wrap-descriptions
+#           - '88'
+#           - --blank
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     rev: v0.0.261
     hooks:
diff --git a/docs/rtd_environment.yml b/docs/rtd_environment.yml
@@ -8,7 +8,7 @@ dependencies:
   - setuptools_scm
   - toml
   - pip
-  - estimagic
+  - optimagic
   - ipython
   - ipython_genutils
   - joblib
diff --git a/environment.yml b/environment.yml
@@ -14,7 +14,7 @@ dependencies:
   - pytest-xdist  # dev, tests
   - setuptools_scm  # dev
   - toml  # dev
-  - estimagic  # run, tests
+  - optimagic  # run, tests
   - numba  # run, tests
   - numpy>=1.17.0  # run, tests
   - pandas  # run, tests
diff --git a/setup.cfg b/setup.cfg
@@ -29,9 +29,9 @@ keywords =
 [options]
 packages = find:
 install_requires =
-    estimagic>=0.4.2
     numba
     numpy>=1.17.0
+    optimagic>=0.5.1
     pandas
     plotly
     scipy>=1.2.1
diff --git a/src/tranquilo/subsolvers/gqtpar.py b/src/tranquilo/subsolvers/gqtpar.py
@@ -74,7 +74,7 @@ def gqtpar(model, x_candidate, *, k_easy=0.1, k_hard=0.2, maxiter=200):
     zero_threshold = (
         model.square_terms.shape[0]
         * np.finfo(float).eps
-        * np.linalg.norm(model.square_terms, np.Inf)
+        * np.linalg.norm(model.square_terms, np.inf)
     )
     stopping_criteria = {
         "k_easy": k_easy,
@@ -174,7 +174,7 @@ def _get_initial_guess_for_lambdas(
     gradient_norm = np.linalg.norm(main_model.linear_terms)
     model_hessian = main_model.square_terms
 
-    hessian_infinity_norm = np.linalg.norm(model_hessian, np.Inf)
+    hessian_infinity_norm = np.linalg.norm(model_hessian, np.inf)
     hessian_frobenius_norm = np.linalg.norm(model_hessian, "fro")
 
     hessian_gershgorin_lower, hessian_gershgorin_upper = _compute_gershgorin_bounds(
diff --git a/src/tranquilo/subsolvers/gqtpar_fast.py b/src/tranquilo/subsolvers/gqtpar_fast.py
@@ -60,7 +60,7 @@ def gqtpar_fast(model, x_candidate, *, k_easy=0.1, k_hard=0.2, maxiter=200):
     # than that backward substituition is not reliable.
     # See Golub, G. H., Van Loan, C. F. (2013), "Matrix computations", p.165.
     zero_threshold = (
-        model_hessian.shape[0] * np.finfo(float).eps * _norm(model_hessian, np.Inf)
+        model_hessian.shape[0] * np.finfo(float).eps * _norm(model_hessian, np.inf)
     )
     stopping_criteria = {
         "k_easy": k_easy,
@@ -179,7 +179,7 @@ def _get_initial_guess_for_lambdas(model_gradient, model_hessian):
     gradient_norm = _norm(model_gradient, -1.0)
     model_hessian = model_hessian
 
-    hessian_infinity_norm = _norm(model_hessian, np.Inf)
+    hessian_infinity_norm = _norm(model_hessian, np.inf)
     hessian_frobenius_norm = _norm(model_hessian, -1.0)
 
     hessian_gershgorin_lower, hessian_gershgorin_upper = _compute_gershgorin_bounds(
diff --git a/src/tranquilo/visualize.py b/src/tranquilo/visualize.py
@@ -8,7 +8,7 @@
 from plotly import graph_objects as go
 from plotly.subplots import make_subplots
 
-from estimagic.optimization.optimize_result import OptimizeResult
+from optimagic.optimization.optimize_result import OptimizeResult
 from tranquilo.clustering import cluster
 from tranquilo.geometry import log_d_quality_calculator
 from tranquilo.volume import get_radius_after_volume_scaling
@@ -25,8 +25,8 @@ def visualize_tranquilo(results, iterations):
     `nag_pybobyqa` and `nag_dfols`.
 
     Args:
-        results (dict or OptimizeResult): An estimagic optimization result or a
-            dictionary with different estimagic optimization results.
+        results (dict or OptimizeResult): An optimagic optimization result or a
+            dictionary with different optimagic optimization results.
         iterations (int, list, tuple or dict): The iterations to compare the results
             at. Can be an integer if we want to compare different results at the same
             iteration, a list or tuple if we want to compare different iterations of
diff --git a/src/tranquilo/wrap_criterion.py b/src/tranquilo/wrap_criterion.py
@@ -80,9 +80,9 @@ def process_batch_evaluator(batch_evaluator="joblib"):
         out = batch_evaluator
     elif isinstance(batch_evaluator, str):
         if batch_evaluator == "joblib":
-            from estimagic.batch_evaluators import joblib_batch_evaluator as out
+            from optimagic.batch_evaluators import joblib_batch_evaluator as out
         elif batch_evaluator == "pathos":
-            from estimagic.batch_evaluators import pathos_mp_batch_evaluator as out
+            from optimagic.batch_evaluators import pathos_mp_batch_evaluator as out
         else:
             raise ValueError(
                 "Invalid batch evaluator requested. Currently only 'pathos' and "
diff --git a/tests/subsolvers/test_gqtpar_lambdas.py b/tests/subsolvers/test_gqtpar_lambdas.py
@@ -1,18 +1,5 @@
-from estimagic.optimization.optimize import minimize
-from estimagic.benchmarking.get_benchmark_problems import get_benchmark_problems
-from tranquilo.tranquilo import _tranquilo
-from estimagic.decorators import mark_minimizer
-from functools import partial
-
-
-tranquilo = mark_minimizer(
-    func=partial(_tranquilo, functype="scalar"),
-    name="tranquilo",
-    primary_criterion_entry="value",
-    needs_scaling=True,
-    is_available=True,
-    is_global=False,
-)
+from optimagic.optimization.optimize import minimize
+from optimagic.benchmarking.get_benchmark_problems import get_benchmark_problems
 
 
 def test_gqtpar_lambdas():
@@ -26,8 +13,8 @@ def test_gqtpar_lambdas():
     problem_info = get_benchmark_problems("more_wild")["freudenstein_roth_good_start"]
 
     minimize(
-        criterion=problem_info["inputs"]["criterion"],
+        criterion=problem_info["inputs"]["fun"],
         params=problem_info["inputs"]["params"],
         algo_options=algo_options,
-        algorithm=tranquilo,
+        algorithm="tranquilo",
     )
diff --git a/tests/subsolvers/test_minimize_trust_region.py b/tests/subsolvers/test_minimize_trust_region.py
@@ -245,7 +245,7 @@ def test_update_candidate_vector_and_reduction_without_active_bounds():
         step_len,
         total_reduction,
         curve_min,
-        np.array([]),
+        None,
         gradient_projected_sumsq,
         gradient_sumsq,
         g_hess_g,
diff --git a/tests/test_fit_models.py b/tests/test_fit_models.py
@@ -1,6 +1,6 @@
 import numpy as np
 import pytest
-from estimagic.differentiation.derivatives import first_derivative, second_derivative
+from optimagic.differentiation.derivatives import first_derivative, second_derivative
 from tranquilo.fit_models import _quadratic_features, get_fitter
 from tranquilo.region import Region
 from numpy.testing import assert_array_almost_equal, assert_array_equal
diff --git a/tests/test_poisedness.py b/tests/test_poisedness.py
@@ -112,7 +112,9 @@ def evaluate_scalar_model(x, intercept, linear_terms, square_terms):
 ]
 
 
-@pytest.mark.skipif(sys.platform == "win32", reason="Test is inaccurate on Windows.")
+@pytest.mark.skipif(
+    sys.platform in ("win32", "darwin"), reason="Test is inaccurate on Windows and Mac."
+)
 @pytest.mark.parametrize("sample, shape, maxiter, expected", TEST_CASES)
 def test_improve_poisedness(sample, shape, maxiter, expected):
     _, got_lambdas = improve_poisedness(sample=sample, shape=shape, maxiter=maxiter)
diff --git a/tests/test_tranquilo.py b/tests/test_tranquilo.py
@@ -2,30 +2,21 @@
 
 import numpy as np
 import pytest
-from estimagic.optimization.optimize import minimize
+from optimagic.optimization.optimize import minimize
 from tranquilo.tranquilo import _tranquilo
-from numpy.testing import assert_array_almost_equal as aaae
-from estimagic.decorators import mark_minimizer
 from functools import partial
+from numpy.testing import assert_array_almost_equal as aaae
+from optimagic import mark
 
 
-tranquilo = mark_minimizer(
-    func=partial(_tranquilo, functype="scalar"),
-    name="tranquilo",
-    primary_criterion_entry="value",
-    needs_scaling=True,
-    is_available=True,
-    is_global=False,
+tranquilo = partial(
+    _tranquilo,
+    functype="scalar",
 )
 
-
-tranquilo_ls = mark_minimizer(
-    func=partial(_tranquilo, functype="least_squares"),
-    primary_criterion_entry="root_contributions",
-    name="tranquilo_ls",
-    needs_scaling=True,
-    is_available=True,
-    is_global=False,
+tranquilo_ls = partial(
+    _tranquilo,
+    functype="least_squares",
 )
 
 
@@ -132,7 +123,7 @@ def test_external_tranquilo_scalar_sphere_defaults():
     res = minimize(
         criterion=lambda x: x @ x,
         params=np.arange(4),
-        algorithm=tranquilo,
+        algorithm="tranquilo",
     )
 
     aaae(res.params, np.zeros(4), decimal=4)
@@ -183,9 +174,9 @@ def test_internal_tranquilo_ls_sphere_defaults(
 
 def test_external_tranquilo_ls_sphere_defaults():
     res = minimize(
-        criterion=lambda x: x,
+        criterion=mark.least_squares(lambda x: x),
         params=np.arange(5),
-        algorithm=tranquilo_ls,
+        algorithm="tranquilo_ls",
     )
 
     aaae(res.params, np.zeros(5), decimal=5)
@@ -196,7 +187,7 @@ def test_external_tranquilo_ls_sphere_defaults():
 # ======================================================================================
 
 
-@pytest.mark.parametrize("algo", [tranquilo, tranquilo_ls])
+@pytest.mark.parametrize("algo", ["tranquilo", "tranquilo_ls"])
 def test_tranquilo_with_noise_handling_and_deterministic_function(algo):
     def _f(x):
         return {"root_contributions": x, "value": x @ x}
@@ -222,7 +213,7 @@ def _f(x):
     res = minimize(
         criterion=_f,
         params=np.ones(3),
-        algorithm=tranquilo_ls,
+        algorithm="tranquilo_ls",
         algo_options={"noisy": True, "n_evals_per_point": 10},
     )
 
@@ -239,7 +230,7 @@ def sum_of_squares(x):
     return {"value": contribs.sum(), "contributions": contribs, "root_contributions": x}
 
 
-@pytest.mark.parametrize("algorithm", [tranquilo, tranquilo_ls])
+@pytest.mark.parametrize("algorithm", ["tranquilo", "tranquilo_ls"])
 def test_tranquilo_with_binding_bounds(algorithm):
     res = minimize(
         criterion=sum_of_squares,
diff --git a/tests/test_visualize.py b/tests/test_visualize.py
