Migrate from cvxopt to cvxpy (+osqp / clarabel)

.gitignore

@@ -1,3 +1,163 @@
-*.pyc
-*.egg-info
-*.npy
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Visual Studio Code
+.vscode/

example_rosenbrock.py

@@ -29,7 +29,7 @@
 problem = SQPGS(f, gI, gE, x0=None, tol=1e-6, max_iter=100, verbose=True)
 x = problem.solve()
 
-print("Distance to solution:", f"{np.linalg.norm(x-xstar):.9f}")
+print("Distance to solution:", f"{np.linalg.norm(x - xstar):.9f}")
 
 # %% Solve from multiple starting points and plot
 

pyproject.toml

@@ -26,7 +26,8 @@ classifiers = [
 dependencies = [
   "numpy",
   "torch",
-  "cvxopt",
+  "cvxpy-base",
+  "clarabel",
 ]
 
 [project.urls]

scripts/train_max_fun.py

@@ -97,7 +97,7 @@ def sample_batch(num_samples, b):
         optimizer.step()
         epoch_loss += loss.item()
 
-    print(f"Epoch {epoch+1}/{num_epochs}: loss={np.mean(epoch_loss)}")
+    print(f"Epoch {epoch + 1}/{num_epochs}: loss={np.mean(epoch_loss)}")
     scheduler.step()
 
 print("Learned parameters:")

src/ncopt/funs.py

@@ -10,7 +10,7 @@ class f_rosenbrock:
     Nonsmooth Rosenbrock function (see 5.1 in Curtis, Overton
     "SQP FOR NONSMOOTH CONSTRAINED OPTIMIZATION")
 
-    x -> w|x_1^2 − x_2| + (1 − x_1)^2
+    x -> w|x_1^2 - x_2| + (1 - x_1)^2
     """
 
     def __init__(self, w=8):