From b7771e21886537c4172f7c0357fd506f4dfedb5a Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Fri, 9 Dec 2022 13:23:14 +0000 Subject: [PATCH 001/170] Add pyproject.toml --- pyproject.toml | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 pyproject.toml diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 00000000..c91ad3e3 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,2 @@ +[build-system] +requires = ["cython >= 0.26", "numpy >= 1.15",, "setuptools"] From 3fc58ae5ac22f4ad319772c4ebbfa9aceb61b79b Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Fri, 9 Dec 2022 13:23:50 +0000 Subject: [PATCH 002/170] Fix syntax --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index c91ad3e3..77ced9ed 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,2 +1,2 @@ [build-system] -requires = ["cython >= 0.26", "numpy >= 1.15",, "setuptools"] +requires = ["cython >= 0.26", "numpy >= 1.15", "setuptools"] From b3f58865dd8328704b5f5e8120764212c97311e3 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Fri, 9 Dec 2022 13:28:06 +0000 Subject: [PATCH 003/170] Add version specification for setuptools --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 77ced9ed..142fd23c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,2 +1,2 @@ [build-system] -requires = ["cython >= 0.26", "numpy >= 1.15", "setuptools"] +requires = ["cython >= 0.26", "numpy >= 1.15", "setuptools>=39.0"] From 29f5f537dc1eb7b5ddfb340b1600338dc94a1ca4 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Fri, 9 Dec 2022 13:32:21 +0000 Subject: [PATCH 004/170] Specify build-backend --- pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/pyproject.toml b/pyproject.toml index 142fd23c..15b65b43 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,2 +1,3 @@ [build-system] requires = ["cython >= 0.26", "numpy >= 1.15", "setuptools>=39.0"] +build-backend = "setuptools.build_meta" From 10e2e48f8d12ca281da412cbac6a174da3836f3c Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Fri, 9 Dec 2022 13:36:24 +0000 Subject: [PATCH 005/170] Reduce pre-installation requirements in docs --- docs/source/install.rst | 4 ---- 1 file changed, 4 deletions(-) diff --git a/docs/source/install.rst b/docs/source/install.rst index e2195dfb..6a36f39b 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -30,10 +30,6 @@ dependencies: * pkg-config [only for Linux and Mac] * Ipopt [>= 3.13 on Windows] * Python 3.6+ - * setuptools - * cython - * numpy - * scipy [optional] The binaries and header files of the Ipopt package can be obtained from http://www.coin-or.org/download/binary/Ipopt/. These include a version compiled From 3bc2708afa35ba3df9a32e8913497b76ca7b8754 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Sat, 10 Dec 2022 02:21:04 +0000 Subject: [PATCH 006/170] Reduce diff --- docs/source/install.rst | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/source/install.rst b/docs/source/install.rst index 6a36f39b..e2195dfb 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -30,6 +30,10 @@ dependencies: * pkg-config [only for Linux and Mac] * Ipopt [>= 3.13 on Windows] * Python 3.6+ + * setuptools + * cython + * numpy + * scipy [optional] The binaries and header files of the Ipopt package can be obtained from http://www.coin-or.org/download/binary/Ipopt/. These include a version compiled From c508bf5650fba2e3172372e43c77aa4b56b98dbf Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 10 Dec 2022 13:13:38 +0100 Subject: [PATCH 007/170] Exclude pyproject.toml from the sdist until conda build can deal with it. --- MANIFEST.in | 1 + 1 file changed, 1 insertion(+) diff --git a/MANIFEST.in b/MANIFEST.in index 3c644b6c..7efc396c 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -3,6 +3,7 @@ include AUTHORS include LICENSE include CHANGELOG.rst include README.rst +exclude pyproject.toml recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py recursive-include tests *.py From 022499ec071aa61a5e376e322808fd4b6c7c8faf Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 10 Dec 2022 13:58:04 +0100 Subject: [PATCH 008/170] Remove appveyor (and old badges). Fixes #113. --- README.rst | 6 ---- appveyor.yml | 98 ---------------------------------------------------- 2 files changed, 104 deletions(-) delete mode 100644 appveyor.yml diff --git a/README.rst b/README.rst index b16b1355..bbb82149 100644 --- a/README.rst +++ b/README.rst @@ -31,12 +31,6 @@ Status - .. image:: https://readthedocs.org/projects/cyipopt/badge/?version=latest :target: https://cyipopt.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status - * - Travis CI - - .. image:: https://api.travis-ci.org/mechmotum/cyipopt.svg?branch=master - :target: https://travis-ci.org/mechmotum/cyipopt - * - Appveyor - - .. image:: https://ci.appveyor.com/api/projects/status/0o5yuogn3jx157ee?svg=true - :target: https://ci.appveyor.com/project/moorepants/cyipopt History ======= diff --git a/appveyor.yml b/appveyor.yml deleted file mode 100644 index a9756c94..00000000 --- a/appveyor.yml +++ /dev/null @@ -1,98 +0,0 @@ -environment: - - # Python 3 is tested with conda-forge's Ipopt, but we also test at least the - # latest Python with the official Ipopt binaries too. - matrix: - - PYTHON: "C:\\Miniconda36-x64" - PYTHON_VERSION: "3.6" - PYTHON_ARCH: "64" - CONDA_PY: "36" - IPOPT: "ipopt" - IPOPTWINDIR: "USECONDAFORGEIPOPT" - - # Test IPOPT 3.11 specifically for backwards compatibility - - PYTHON: "C:\\Miniconda37-x64" - PYTHON_VERSION: "3.7" - PYTHON_ARCH: "64" - CONDA_PY: "37" - IPOPT: "ipopt>=3.11,<3.13" - IPOPTWINDIR: "USECONDAFORGEIPOPT" - - - PYTHON: "C:\\Miniconda37-x64" - PYTHON_VERSION: "3.7" - PYTHON_ARCH: "64" - CONDA_PY: "37" - IPOPT: "ipopt" - IPOPTWINDIR: "USECONDAFORGEIPOPT" - - # There is not Miniconda38 on appveyor yet so use Miniconda37. - - PYTHON: "C:\\Miniconda37-x64" - PYTHON_VERSION: "3.8" - PYTHON_ARCH: "64" - CONDA_PY: "38" - IPOPT: "ipopt" - IPOPTWINDIR: "USECONDAFORGEIPOPT" - - # There is not Miniconda39 on appveyor yet so use Miniconda37. - - PYTHON: "C:\\Miniconda37-x64" - PYTHON_VERSION: "3.9" - PYTHON_ARCH: "64" - CONDA_PY: "39" - IPOPT: "ipopt" - IPOPTWINDIR: "USECONDAFORGEIPOPT" - - # There is not Miniconda38 on appveyor yet so use Miniconda37. - - PYTHON: "C:\\Miniconda37-x64" - PYTHON_VERSION: "3.8" - PYTHON_ARCH: "64" - CONDA_PY: "38" - IPOPT: "" - IPOPTWINDIR: "C:\\projects\\cyipopt\\Ipopt-3.13.3-win64-msvs2019-md" - -install: - - ECHO "Filesystem root:" - - ps: "ls \"C:/\"" - - - ECHO "Installed SDKs:" - - ps: "ls \"C:/Program Files/Microsoft SDKs/Windows\"" - - # This upates conda and installs the necessary packages. - - "CALL %PYTHON%\\Scripts\\activate.bat base" - - "%PYTHON%\\Scripts\\conda.exe clean --yes --all" - - "%PYTHON%\\Scripts\\conda.exe update --yes conda" - - "%PYTHON%\\Scripts\\conda.exe update --yes --all" - - "%PYTHON%\\Scripts\\conda.exe config --prepend channels conda-forge" - - "%PYTHON%\\Scripts\\conda.exe install --yes python=%PYTHON_VERSION% %IPOPT%" - - "%PYTHON%\\Scripts\\conda.exe install --yes --freeze-installed --file requirements.txt" - - "%PYTHON%\\Scripts\\conda.exe update -y --all" - - "%PYTHON%\\Scripts\\conda.exe info" - - "%PYTHON%\\Scripts\\conda.exe list" - - # This downloads and extracts a precomplied IPOPT for Windows. - - ps: >- - if(!($env:IPOPT -eq "ipopt ")){ - Start-FileDownload 'https://github.com/coin-or/Ipopt/releases/download/releases%2F3.13.3/Ipopt-3.13.3-win64-msvs2019-md.zip' - 7z x Ipopt-3.13.3-win64-msvs2019-md.zip - ls - } - # Prepend newly installed Python to the PATH of this build (this cannot be - # done from inside the powershell script as it would require to restart the - # parent CMD process). - - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PYTHON%\\Library\\bin;%PATH%" - - # Check that we have the expected version and architecture for Python - - "python --version" - - "python -c \"import struct; print(struct.calcsize('P') * 8)\"" - -build: false - -test_script: - # Test package install - - "python setup.py install" - - 'python -c "import cyipopt"' - - # Run test suite - - "conda.exe install --yes pytest>=3.3.2" - - "pytest" - - "conda.exe install --yes scipy>=0.19.1" - - "pytest" From f3907be48925abd01dfd841d40c12444411119a8 Mon Sep 17 00:00:00 2001 From: jhelgert Date: Sat, 17 Dec 2022 15:15:59 +0100 Subject: [PATCH 009/170] Add support for sparse jacobians and use sparse ones by default --- cyipopt/scipy_interface.py | 89 +++++++++++++++++++++++++++++++++----- 1 file changed, 79 insertions(+), 10 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index f7d3fed7..0b7f1ba2 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -20,6 +20,7 @@ SCIPY_INSTALLED = True del scipy from scipy.optimize import approx_fprime + import scipy.sparse try: from scipy.optimize import OptimizeResult except ImportError: @@ -31,6 +32,11 @@ except ImportError: # The optimize.optimize namespace is being deprecated from scipy.optimize.optimize import MemoizeJac + try: + from scipy.sparse import coo_array + except ImportError: + # coo_array was introduced with scipy 1.8 + from scipy.sparse import coo_matrix as coo_array import cyipopt @@ -60,13 +66,19 @@ class IpoptProblemWrapper(object): Explicitly defined Hessians are not yet supported for this class. constraints : {Constraint, dict} or List of {Constraint, dict}, optional See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html - for more information. + for more information. Note that the jacobian of each constraint + corresponds to the `'jac'` key and must be a callable function + with signature ``jac(x) -> {ndarray, coo_array}``. If the constraint's + value of `'jac'` is a boolean and True, the constraint function `fun` + is expected to return a tuple `(con_val, con_jac)` consisting of the + evaluated constraint `con_val` and the evaluated jacobian `con_jac`. eps : float, optional Epsilon used in finite differences. con_dims : array_like, optional Dimensions p_1, ..., p_m of the m constraint functions g_1, ..., g_m : R^n -> R^(p_i). """ + def __init__(self, fun, args=(), @@ -76,7 +88,10 @@ def __init__(self, hessp=None, constraints=(), eps=1e-8, - con_dims=()): + con_dims=(), + sparse_jacs=(), + jac_nnz_row=(), + jac_nnz_col=()): if not SCIPY_INSTALLED: msg = 'Install SciPy to use the `IpoptProblemWrapper` class.' raise ImportError() @@ -105,6 +120,8 @@ def __init__(self, self._constraint_dims = np.asarray(con_dims) self._constraint_args = [] self._constraint_kwargs = [] + self._constraint_jac_is_sparse = sparse_jacs + self._constraint_jacobian_structure = (jac_nnz_row, jac_nnz_col) if isinstance(constraints, dict): constraints = (constraints, ) for con in constraints: @@ -154,11 +171,25 @@ def constraints(self, x): con_values.append(fun(x, *args)) return np.hstack(con_values) + def jacobianstructure(self): + return self._constraint_jacobian_structure + def jacobian(self, x): - con_values = [] - for jac, args in zip(self._constraint_jacs, self._constraint_args): - con_values.append(jac(x, *args)) - return np.vstack(con_values) + # convert all dense constraint jacobians to sparse ones + jac_values = [] + for i, (jac, args) in enumerate(zip(self._constraint_jacs, self._constraint_args)): + if self._constraint_jac_is_sparse[i]: + jac_val = jac(x, *args) + else: + # convert dense constraint jacobian to sparse one + # problem: jac(x, *args) could yield zeros, + # so we assume all entries are nonzero + dense_jac_val = np.atleast_2d(jac(x, *args)) + jac_val = scipy.sparse.coo_array(np.ones_like(dense_jac_val)) + jac_val.data = dense_jac_val.flatten() + jac_values.append(jac_val) + J = scipy.sparse.vstack(jac_values) + return J.data def hessian(self, x, lagrange, obj_factor): H = obj_factor * self.obj_hess(x) # type: ignore @@ -185,12 +216,45 @@ def get_bounds(bounds): return lb, ub +def get_sparse_jacobian_structure(constraints, x0): + con_jac_is_sparse = [] + jacobians = [] + x0 = np.asarray(x0) + if isinstance(constraints, dict): + constraints = (constraints, ) + if len(constraints) == 0: + return [], [], [] + for con in constraints: + con_jac = con.get('jac', False) + if con_jac: + if isinstance(con_jac, bool): + _, jac_val = con['fun'](x0, *con.get('args', [])) + else: + jac_val = con_jac(x0, *con.get('args', [])) + # check if dense or sparse + if isinstance(jac_val, coo_array): + jacobians.append(jac_val) + con_jac_is_sparse.append(True) + else: + # Creating the coo_array from jac_val would yield to + # wrong dimensions if some values in jac_val are zero, + # so we assume all values in jac_val are nonzero + jacobians.append(coo_array(np.ones_like(np.atleast_2d(jac_val)))) + con_jac_is_sparse.append(False) + else: + # we approximate this jacobian later (=dense) + con_val = np.atleast_1d(con['fun'](x0, *con.get('args', []))) + jacobians.append(coo_array(np.ones((con_val.size, x0.size)))) + con_jac_is_sparse.append(False) + J = scipy.sparse.vstack(jacobians) + return con_jac_is_sparse, J.row, J.col + def get_constraint_dimensions(constraints, x0): con_dims = [] if isinstance(constraints, dict): constraints = (constraints, ) for con in constraints: - if con.get('jac', False) is True: + if con.get('jac', False) == True: m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []))[0])) else: m = len(np.atleast_1d(con['fun'](x0, *con.get('args', [])))) @@ -265,8 +329,10 @@ def minimize_ipopt(fun, _x0 = np.atleast_1d(x0) lb, ub = get_bounds(bounds) - cl, cu = get_constraint_bounds(constraints, x0) - con_dims = get_constraint_dimensions(constraints, x0) + cl, cu = get_constraint_bounds(constraints, _x0) + con_dims = get_constraint_dimensions(constraints, _x0) + sparse_jacs, jac_nnz_row, jac_nnz_col = get_sparse_jacobian_structure( + constraints, _x0) problem = IpoptProblemWrapper(fun, args=args, @@ -276,7 +342,10 @@ def minimize_ipopt(fun, hessp=hessp, constraints=constraints, eps=1e-8, - con_dims=con_dims) + con_dims=con_dims, + sparse_jacs=sparse_jacs, + jac_nnz_row=jac_nnz_row, + jac_nnz_col=jac_nnz_col) if options is None: options = {} From 84bcfc57b2bfbd13053597a31d53f1f9fc7cd391 Mon Sep 17 00:00:00 2001 From: jhelgert Date: Sat, 17 Dec 2022 15:16:52 +0100 Subject: [PATCH 010/170] Add tests --- cyipopt/tests/unit/test_scipy_optional.py | 105 +++++++++++++++++++++- 1 file changed, 104 insertions(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index bf87b7ff..df6b1a72 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -97,6 +97,109 @@ def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy( np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid of Scipy available") +def test_minimize_ipopt_sparse_jac_if_scipy(): + """ `minimize_ipopt` works with objective gradient, and sparse + constraint jacobian. Solves + Hock & Schittkowski's test problem 71: + + min x0*x3*(x0+x1+x2)+x2 + s.t. x0**2 + x1**2 + x2**2 + x3**2 - 40 = 0 + x0 * x1 * x2 * x3 - 25 >= 0 + 1 <= x0,x1,x2,x3 <= 5 + """ + from scipy.sparse import coo_array + + def obj(x): + return x[0] * x[3] * np.sum(x[:3]) + x[2] + + def grad(x): + return np.array([ + x[0] * x[3] + x[3] * np.sum(x[0:3]), x[0] * x[3], + x[0] * x[3] + 1.0, x[0] * np.sum(x[0:3]) + ]) + + # Note: + # coo_array(dense_jac_val(x)) only works if dense_jac_val(x0) + # doesn't contain any zeros for the initial guess x0 + + con_eq = { + "type": "eq", + "fun": lambda x: np.sum(x**2) - 40, + "jac": lambda x: coo_array(2 * x) + } + con_ineq = { + "type": "ineq", + "fun": lambda x: np.prod(x) - 25, + "jac": lambda x: coo_array(np.prod(x) / x), + } + constrs = (con_eq, con_ineq) + + x0 = np.array([1.0, 5.0, 5.0, 1.0]) + bnds = [(1, 5) for _ in range(x0.size)] + + res = cyipopt.minimize_ipopt(obj, jac=grad, x0=x0, + bounds=bnds, constraints=constrs) + assert isinstance(res, dict) + assert np.isclose(res.get("fun"), 17.01401727277449) + assert res.get("status") == 0 + assert res.get("success") is True + expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) + np.testing.assert_allclose(res.get("x"), expected_res) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid of Scipy available") +def test_minimize_ipopt_sparse_and_dense_jac_if_scipy(): + """ `minimize_ipopt` works with objective gradient, and sparse + constraint jacobian. Solves + Hock & Schittkowski's test problem 71: + + min x0*x3*(x0+x1+x2)+x2 + s.t. x0**2 + x1**2 + x2**2 + x3**2 - 40 = 0 + x0 * x1 * x2 * x3 - 25 >= 0 + 1 <= x0,x1,x2,x3 <= 5 + """ + from scipy.sparse import coo_array + + def obj(x): + return x[0] * x[3] * np.sum(x[:3]) + x[2] + + def grad(x): + return np.array([ + x[0] * x[3] + x[3] * np.sum(x[0:3]), x[0] * x[3], + x[0] * x[3] + 1.0, x[0] * np.sum(x[0:3]) + ]) + + # Note: + # coo_array(dense_jac_val(x)) only works if dense_jac_val(x0) + # doesn't contain any zeros for the initial guess x0 + + con_eq_dense = { + "type": "eq", + "fun": lambda x: np.sum(x**2) - 40, + "jac": lambda x: 2 * x + } + con_ineq_sparse = { + "type": "ineq", + "fun": lambda x: np.prod(x) - 25, + "jac": lambda x: coo_array(np.prod(x) / x), + } + constrs = (con_eq_dense, con_ineq_sparse) + + x0 = np.array([1.0, 5.0, 5.0, 1.0]) + bnds = [(1, 5) for _ in range(x0.size)] + + res = cyipopt.minimize_ipopt(obj, jac=grad, x0=x0, + bounds=bnds, constraints=constrs) + assert isinstance(res, dict) + assert np.isclose(res.get("fun"), 17.01401727277449) + assert res.get("status") == 0 + assert res.get("success") is True + expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) + np.testing.assert_allclose(res.get("x"), expected_res) + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_hs071(): @@ -168,4 +271,4 @@ def con_ineq_hess(x, v): assert res.get("status") == 0 assert res.get("success") is True expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) - np.testing.assert_allclose(res.get("x"), expected_res) \ No newline at end of file + np.testing.assert_allclose(res.get("x"), expected_res) From 14c0d22e8e96587323d387a488598456a834422c Mon Sep 17 00:00:00 2001 From: jhelgert Date: Sat, 17 Dec 2022 15:19:19 +0100 Subject: [PATCH 011/170] Fix spacing --- cyipopt/scipy_interface.py | 1 + cyipopt/tests/unit/test_scipy_optional.py | 1 + 2 files changed, 2 insertions(+) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 0b7f1ba2..2a3bdd0d 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -249,6 +249,7 @@ def get_sparse_jacobian_structure(constraints, x0): J = scipy.sparse.vstack(jacobians) return con_jac_is_sparse, J.row, J.col + def get_constraint_dimensions(constraints, x0): con_dims = [] if isinstance(constraints, dict): diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index df6b1a72..883e6414 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -200,6 +200,7 @@ def grad(x): expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) np.testing.assert_allclose(res.get("x"), expected_res) + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_hs071(): From 1a144c99747a94013d633a6b5816bf6916e599c7 Mon Sep 17 00:00:00 2001 From: Jonathan Helgert Date: Sun, 18 Dec 2022 08:46:39 +0100 Subject: [PATCH 012/170] Update cyipopt/scipy_interface.py Co-authored-by: Jason K. Moore --- cyipopt/scipy_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 2a3bdd0d..aeaa2581 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -255,7 +255,7 @@ def get_constraint_dimensions(constraints, x0): if isinstance(constraints, dict): constraints = (constraints, ) for con in constraints: - if con.get('jac', False) == True: + if con.get('jac', False): m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []))[0])) else: m = len(np.atleast_1d(con['fun'](x0, *con.get('args', [])))) From 55f09c8d394bbe1ead79c0af73f95a49682285cb Mon Sep 17 00:00:00 2001 From: jhelgert Date: Sun, 18 Dec 2022 08:50:30 +0100 Subject: [PATCH 013/170] Make get_sparse_jacobian_structure private --- cyipopt/scipy_interface.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index aeaa2581..31c5689a 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -216,7 +216,7 @@ def get_bounds(bounds): return lb, ub -def get_sparse_jacobian_structure(constraints, x0): +def _get_sparse_jacobian_structure(constraints, x0): con_jac_is_sparse = [] jacobians = [] x0 = np.asarray(x0) @@ -332,7 +332,7 @@ def minimize_ipopt(fun, lb, ub = get_bounds(bounds) cl, cu = get_constraint_bounds(constraints, _x0) con_dims = get_constraint_dimensions(constraints, _x0) - sparse_jacs, jac_nnz_row, jac_nnz_col = get_sparse_jacobian_structure( + sparse_jacs, jac_nnz_row, jac_nnz_col = _get_sparse_jacobian_structure( constraints, _x0) problem = IpoptProblemWrapper(fun, From 792fa63756f0437e420c3904fa4aabf612445f9a Mon Sep 17 00:00:00 2001 From: jhelgert Date: Mon, 19 Dec 2022 23:28:45 +0100 Subject: [PATCH 014/170] Performance improvement --- cyipopt/scipy_interface.py | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 31c5689a..7b06e702 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -185,8 +185,9 @@ def jacobian(self, x): # problem: jac(x, *args) could yield zeros, # so we assume all entries are nonzero dense_jac_val = np.atleast_2d(jac(x, *args)) - jac_val = scipy.sparse.coo_array(np.ones_like(dense_jac_val)) - jac_val.data = dense_jac_val.flatten() + jac_val = coo_array(dense_jac_val.shape) + jac_val.row, jac_val.col = _calculate_coo_indices(*dense_jac_val.shape) + jac_val.data = dense_jac_val.ravel() jac_values.append(jac_val) J = scipy.sparse.vstack(jac_values) return J.data @@ -216,6 +217,18 @@ def get_bounds(bounds): return lb, ub +def _calculate_coo_indices(M, N): + """8x faster than np.unravel_index(np.arange(M*N), (M, N))""" + rows = np.zeros(M*N, dtype=np.int32) + cols = np.zeros(M*N, dtype=np.int32) + tmp = np.arange(N) + + for i in range(M): + cols[i*N : (i+1)*N] = tmp + rows[i*N : (i+1)*N] = i + return rows, cols + + def _get_sparse_jacobian_structure(constraints, x0): con_jac_is_sparse = [] jacobians = [] From e40a01d9a5fbdff34e9c263402b200a00160b533 Mon Sep 17 00:00:00 2001 From: jhelgert Date: Wed, 21 Dec 2022 19:30:32 +0100 Subject: [PATCH 015/170] Added an example with sparse jacobians to the docs --- docs/source/tutorial.rst | 93 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 93 insertions(+) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index 8590db7c..73aa0541 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -26,6 +26,99 @@ the same behaviour as ``scipy.optimize.minimize``, for example:: success: True x: array([1., 1., 1., 1., 1.]) + +In order to demonstrate the usage of sparse jacobians, let's assume we want to +minimize the well-known rosenbrock function + +.. math:: + f(x) = \sum_{i=1}^{4} 100 (x_{i+1} - x_i^2)^2 + (1-x_i)^2 + +subject to some constraints, i.e. we want to solve the constraint +optimization problem + +.. math:: + \min_{x \in \mathbb{R}^5} f(x) \quad \text{s.t.} \quad + 10 - x_2^2 - x_3 \geq 0, \quad + 100 - x_5^2 \geq 0. + +We won't implement the rosenbrock function and its derivatives here, since +all three can be imported from ``scipy.optimize``. The constraint function +:math:`c` and the jacobian :math:`J_c` are given by + +.. math:: + c(x) &= \begin{pmatrix} c_1(x) \\ c_2(x) \end{pmatrix} = \begin{pmatrix} 10 - x_1^2 + x^3 \\ 100 - x_5^2 \end{pmatrix} \geq 0 \\ + J_c(x) &= \begin{pmatrix} 0 & -2x_2 & - 1 & 0 & 0 \\ 0 & 0 & 0 & 0 & -2x_5 \end{pmatrix} + +and we can implement the constraint and the sparse jacobian +by means of an ``scipy.sparse.coo_array`` like this:: + + from scipy.sparse import coo_array + + def con(x): + return np.array([ 10 -x[1]**2 - x[2], 100.0 - x[4]**2 ]) + + def con_jac(x): + # Dense Jacobian: + # J = (0 -2*x[1] -1 0 0 ) + # (0 0 0 0 -2*x[4] ) + # Sparse Jacobian (COO) + rows = np.array([0, 0, 1]) + cols = np.array(([1, 2, 4])) + data = np.array([-2*x[1], -1, -2*x[4]]) + return coo_array((data, (rows, cols))) + +In addition, we would like to pass the hessian of the objective and the constraints. +Note that Ipopt expects the hessian :math:`\nabla^2_x L` of the lagrangian function + +.. math:: + L(x, \lambda) = f(x) + \lambda^\top c(x) = f(x) + \sum_{j=1}^{2} \lambda_j c_j(x), + +which is given by + +.. math:: + \nabla^2_x L(x, \lambda) = \nabla^2 f(x) + \sum_{j=1}^2 \lambda_j \nabla^2 c_j(x). + +Hence, we need to pass the hessian-vector-product of the constraint hessians +:math:`\nabla^2 c_1(x)` and :math:`\nabla^2 c_2(x)` and the lagrangian multipliers +:math:`\lambda` (also known as dual variables). In code: :: + + def con_hess(x, _lambda): + H1 = np.array([ + [0, 0, 0, 0, 0], + [0, -2, 0, 0, 0 ], + [0, 0, 0, 0, 0 ], + [0, 0, 0, 0, 0 ], + [0, 0, 0, 0, 0 ] + ]) + + H2 = np.array([ + [0, 0, 0, 0, 0], + [0, 0, 0, 0, 0], + [0, 0, 0, 0, 0], + [0, 0, 0, 0, 0], + [0, 0, 0, 0, -2] + ]) + return _lambda[0] * H1 + _lambda[1] * H2 + +Ipopt only uses the lower triangle of the hessian-vector-product +under the hood, due to the symmetry of the hessians. Similar to sparse jacobians, +it also supports sparse hessians, but this isn't supported by the scipy interface yet. +However, you can use cyipopt's problem interface in case you need to pass sparse hessians. + +Finally, after defining the constraint and the initial guess, we can solve the +problem:: + + from scipy.optimize import rosen, rosen_der, rosen_hess + + constr = {'type': 'ineq', 'fun': con, 'jac': con_jac, 'hess': con_hess} + + # initial guess + x0 = np.array([1.1, 1.1, 1.1, 1.1, 1.1]) + + # solve the problem + res = minimize_ipopt(rosen, jac=rosen_der, hess=rosen_hess, x0=x0, constraints=constr) + + Algorithmic Differentation -------------------------- From 7b6edec75798945d62d898318e01f2f3b8e55bb6 Mon Sep 17 00:00:00 2001 From: jhelgert Date: Wed, 21 Dec 2022 19:31:26 +0100 Subject: [PATCH 016/170] Simplify code and reverse previous commit --- cyipopt/scipy_interface.py | 30 +++++++----------------------- 1 file changed, 7 insertions(+), 23 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 7b06e702..83bd51a9 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -175,22 +175,18 @@ def jacobianstructure(self): return self._constraint_jacobian_structure def jacobian(self, x): - # convert all dense constraint jacobians to sparse ones + # Convert all dense constraint jacobians to sparse ones. + # The structure ( = row and column indices) is already known at this point, + # so we only need to stack the evaluated jacobians jac_values = [] for i, (jac, args) in enumerate(zip(self._constraint_jacs, self._constraint_args)): if self._constraint_jac_is_sparse[i]: jac_val = jac(x, *args) + jac_values.append(jac_val.data) else: - # convert dense constraint jacobian to sparse one - # problem: jac(x, *args) could yield zeros, - # so we assume all entries are nonzero dense_jac_val = np.atleast_2d(jac(x, *args)) - jac_val = coo_array(dense_jac_val.shape) - jac_val.row, jac_val.col = _calculate_coo_indices(*dense_jac_val.shape) - jac_val.data = dense_jac_val.ravel() - jac_values.append(jac_val) - J = scipy.sparse.vstack(jac_values) - return J.data + jac_values.append(dense_jac_val.ravel()) + return np.hstack(jac_values) def hessian(self, x, lagrange, obj_factor): H = obj_factor * self.obj_hess(x) # type: ignore @@ -217,18 +213,6 @@ def get_bounds(bounds): return lb, ub -def _calculate_coo_indices(M, N): - """8x faster than np.unravel_index(np.arange(M*N), (M, N))""" - rows = np.zeros(M*N, dtype=np.int32) - cols = np.zeros(M*N, dtype=np.int32) - tmp = np.arange(N) - - for i in range(M): - cols[i*N : (i+1)*N] = tmp - rows[i*N : (i+1)*N] = i - return rows, cols - - def _get_sparse_jacobian_structure(constraints, x0): con_jac_is_sparse = [] jacobians = [] @@ -268,7 +252,7 @@ def get_constraint_dimensions(constraints, x0): if isinstance(constraints, dict): constraints = (constraints, ) for con in constraints: - if con.get('jac', False): + if con.get('jac', False) is True: m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []))[0])) else: m = len(np.atleast_1d(con['fun'](x0, *con.get('args', [])))) From 5ee9a059b93954756c57e0192573a6355c4be4d3 Mon Sep 17 00:00:00 2001 From: jhelgert Date: Wed, 21 Dec 2022 19:32:15 +0100 Subject: [PATCH 017/170] Updated docstring --- cyipopt/scipy_interface.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 83bd51a9..0bb8ff17 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -77,6 +77,15 @@ class IpoptProblemWrapper(object): con_dims : array_like, optional Dimensions p_1, ..., p_m of the m constraint functions g_1, ..., g_m : R^n -> R^(p_i). + sparse_jacs: array_like, optional + If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse. + Otherwise, the i-th constraint jacobian is assumed to be dense. + jac_nnz_row: array_like, optional + The row indices of the nonzero elements in the stacked + constraint jacobian matrix + jac_nnz_col: array_like, optional + The column indices of the nonzero elements in the stacked + constraint jacobian matrix """ def __init__(self, From e0e27f83bfd4b94427bb46fdc35f7825f1a4dac8 Mon Sep 17 00:00:00 2001 From: Sam Brockie Date: Thu, 12 Jan 2023 17:31:58 +0100 Subject: [PATCH 018/170] Change conda-build-version to mamba-version --- .github/workflows/docs.yml | 2 +- .github/workflows/test.yml | 2 +- .github/workflows/tests.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 293be802..cf0b01e5 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -28,7 +28,7 @@ jobs: activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - conda-build-version: '3.21.4' + mamba-version: '*' - name: Install basic dependencies run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt - name: Install CyIpopt diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index d58d190f..340bef7b 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -29,7 +29,7 @@ jobs: activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - conda-build-version: '3.21.4' + mamba-version: '*' - name: Install basic dependencies run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 082f4f6a..4d8543aa 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -36,7 +36,7 @@ jobs: activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - conda-build-version: '3.21.4' + mamba-version: '*' - name: Install basic dependencies run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt From 81971d029cee63da232f4ca92d94960dd70ec66e Mon Sep 17 00:00:00 2001 From: robbybp Date: Fri, 10 Feb 2023 00:13:11 -0700 Subject: [PATCH 019/170] start function to get iterate --- cyipopt/cython/ipopt_wrapper.pyx | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index f0e4c530..b8b52285 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -654,6 +654,18 @@ cdef class Problem: return np_x, info + def get_current_iterate(self): + # Access the NLP (IpoptProblem), which is necessary to get the iterate. + self.__nlp + + # + # Allocate arrays to hold the current iterate + # + cdef np.ndarray[DTYPEd_t, ndim=1] x_curr = np.zeros((self.__n,), dtype=DTYPEd) + cdef np.ndarray[DTYPEd_t, ndim=1] y_curr = np.zeros((self.__m,), dtype=DTYPEd) + print(" getting current iterate") + # TODO: Call GetIpoptCurrentIterate + # # Callback functions From c224638e9f9ab1d37799c6be5cfcb719da9008bc Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 10 Feb 2023 14:02:16 -0700 Subject: [PATCH 020/170] implement get_current_iterate and get_current_violations methods --- cyipopt/cython/ipopt.pxd | 26 +++++++++ cyipopt/cython/ipopt_wrapper.pyx | 96 ++++++++++++++++++++++++++++---- 2 files changed, 112 insertions(+), 10 deletions(-) diff --git a/cyipopt/cython/ipopt.pxd b/cyipopt/cython/ipopt.pxd index 91f32867..a1a6307f 100644 --- a/cyipopt/cython/ipopt.pxd +++ b/cyipopt/cython/ipopt.pxd @@ -167,3 +167,29 @@ cdef extern from "IpStdCInterface.h": Number* mult_x_U, UserDataPtr user_data ) + + Bool GetIpoptCurrentIterate( + IpoptProblem ipopt_problem, + Bool scaled, + Index n, + Number* x, + Number* z_L, + Number* z_U, + Index m, + Number* g, + Number* lambd + ) + + Bool GetIpoptCurrentViolations( + IpoptProblem ipopt_problem, + Bool scaled, + Index n, + Number* x_L_violation, + Number* x_U_violation, + Number* compl_x_L, + Number* compl_x_U, + Number* grad_lag_x, + Index m, + Number* nlp_constraint_violation, + Number* compl_g + ) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index b8b52285..eb2c105f 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -654,17 +654,93 @@ cdef class Problem: return np_x, info - def get_current_iterate(self): - # Access the NLP (IpoptProblem), which is necessary to get the iterate. - self.__nlp - - # + def get_current_iterate(self, scaled=False): # Allocate arrays to hold the current iterate - # - cdef np.ndarray[DTYPEd_t, ndim=1] x_curr = np.zeros((self.__n,), dtype=DTYPEd) - cdef np.ndarray[DTYPEd_t, ndim=1] y_curr = np.zeros((self.__m,), dtype=DTYPEd) - print(" getting current iterate") - # TODO: Call GetIpoptCurrentIterate + cdef np.ndarray[DTYPEd_t, ndim=1] np_x + cdef np.ndarray[DTYPEd_t, ndim=1] np_mult_x_L + cdef np.ndarray[DTYPEd_t, ndim=1] np_mult_x_U + cdef np.ndarray[DTYPEd_t, ndim=1] np_g + cdef np.ndarray[DTYPEd_t, ndim=1] np_mult_g + np_x = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_mult_x_L = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_mult_x_U = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_g = np.zeros((self.__m,), dtype=DTYPEd).flatten() + np_mult_g = np.zeros((self.__m,), dtype=DTYPEd).flatten() + + # Cast to C data types + x = np_x.data + mult_x_L = np_mult_x_L.data + mult_x_U = np_mult_x_U.data + g = np_g.data + mult_g = np_mult_g.data + + ret = GetIpoptCurrentIterate( + self.__nlp, + scaled, + self.__n, + x, + mult_x_L, + mult_x_U, + self.__m, + g, + mult_g, + ) + + # Return values to user + # - Is another data type (e.g. dict, namedtuple) more appropriate than + # simply a tuple? + # - Should `ret` be returned here? + return (np_x, np_mult_x_L, np_mult_x_U, np_g, np_mult_g) + + def get_current_violations(self, scaled=False): + # Allocate arrays to hold current violations + cdef np.ndarray[DTYPEd_t, ndim=1] np_x_L_viol + cdef np.ndarray[DTYPEd_t, ndim=1] np_x_U_viol + cdef np.ndarray[DTYPEd_t, ndim=1] np_compl_x_L + cdef np.ndarray[DTYPEd_t, ndim=1] np_compl_x_U + cdef np.ndarray[DTYPEd_t, ndim=1] np_grad_lag_x + cdef np.ndarray[DTYPEd_t, ndim=1] np_g_viol + cdef np.ndarray[DTYPEd_t, ndim=1] np_compl_g + np_x_L_viol = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_x_U_viol = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_compl_x_L = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_compl_x_U = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_grad_lag_x = np.zeros((self.__n,), dtype=DTYPEd).flatten() + np_g_viol = np.zeros((self.__m,), dtype=DTYPEd).flatten() + np_compl_g = np.zeros((self.__m,), dtype=DTYPEd).flatten() + + # Cast to C data types + x_L_viol = np_x_L_viol.data + x_U_viol = np_x_U_viol.data + compl_x_L = np_compl_x_L.data + compl_x_U = np_compl_x_U.data + grad_lag_x = np_grad_lag_x.data + g_viol = np_g_viol.data + compl_g = np_compl_g.data + + ret = GetIpoptCurrentViolations( + self.__nlp, + scaled, + self.__n, + x_L_viol, + x_U_viol, + compl_x_L, + compl_x_U, + grad_lag_x, + self.__m, + g_viol, + compl_g, + ) + + return ( + np_x_L_viol, + np_x_U_viol, + np_compl_x_L, + np_compl_x_U, + np_grad_lag_x, + np_g_viol, + np_compl_g, + ) # From f356322e59a2e396075752ef43bf3cd9d5a11ef8 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 10 Feb 2023 14:53:43 -0700 Subject: [PATCH 021/170] fix typo in definition instance fixture --- cyipopt/tests/conftest.py | 6 +++--- cyipopt/tests/unit/test_deprecations.py | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/cyipopt/tests/conftest.py b/cyipopt/tests/conftest.py index f9c18aad..41a1805b 100644 --- a/cyipopt/tests/conftest.py +++ b/cyipopt/tests/conftest.py @@ -111,7 +111,7 @@ def intermediate(*args): @pytest.fixture() -def hs071_defintion_instance_fixture(hs071_objective_fixture, +def hs071_definition_instance_fixture(hs071_objective_fixture, hs071_gradient_fixture, hs071_constraints_fixture, hs071_jacobian_fixture, @@ -175,7 +175,7 @@ def hs071_constraint_upper_bounds_fixture(): @pytest.fixture() -def hs071_problem_instance_fixture(hs071_defintion_instance_fixture, +def hs071_problem_instance_fixture(hs071_definition_instance_fixture, hs071_initial_guess_fixture, hs071_variable_lower_bounds_fixture, hs071_variable_upper_bounds_fixture, @@ -183,7 +183,7 @@ def hs071_problem_instance_fixture(hs071_defintion_instance_fixture, hs071_constraint_upper_bounds_fixture, ): """Return a default cyipopt.Problem instance of the hs071 test problem.""" - problem_definition = hs071_defintion_instance_fixture + problem_definition = hs071_definition_instance_fixture x0 = hs071_initial_guess_fixture lb = hs071_variable_lower_bounds_fixture ub = hs071_variable_upper_bounds_fixture diff --git a/cyipopt/tests/unit/test_deprecations.py b/cyipopt/tests/unit/test_deprecations.py index 0ca66b73..ebf56b3f 100644 --- a/cyipopt/tests/unit/test_deprecations.py +++ b/cyipopt/tests/unit/test_deprecations.py @@ -22,7 +22,7 @@ def test_ipopt_import_deprecation(): import ipopt -def test_non_pep8_class_name_deprecation(hs071_defintion_instance_fixture, +def test_non_pep8_class_name_deprecation(hs071_definition_instance_fixture, hs071_initial_guess_fixture, hs071_variable_lower_bounds_fixture, hs071_variable_upper_bounds_fixture, @@ -36,7 +36,7 @@ def test_non_pep8_class_name_deprecation(hs071_defintion_instance_fixture, with pytest.warns(FutureWarning, match=expected_warning_msg): _ = cyipopt.problem(n=len(hs071_initial_guess_fixture), m=len(hs071_constraint_lower_bounds_fixture), - problem_obj=hs071_defintion_instance_fixture, + problem_obj=hs071_definition_instance_fixture, lb=hs071_variable_lower_bounds_fixture, ub=hs071_variable_upper_bounds_fixture, cl=hs071_constraint_lower_bounds_fixture, From 7c82b25f36661b595edd38d50c48ac8e9caeef1a Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 10 Feb 2023 16:19:52 -0700 Subject: [PATCH 022/170] tests for get_current_iterate and get_current_violations --- cyipopt/tests/unit/test_ipopt_funcs.py | 213 +++++++++++++++++++++++++ 1 file changed, 213 insertions(+) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index e69de29b..8998c844 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -0,0 +1,213 @@ +import numpy as np +import pytest + +import cyipopt + +@pytest.mark.skipif(True, reason="This segfaults. Ideally, it fails gracefully") +def test_get_iterate_uninit(hs071_problem_instance_fixture): + """Test that we can call get_current_iterate on an uninitialized problem + """ + nlp = hs071_problem_instance_fixture + x, zL, zU, g, lam = nlp.get_current_iterate() + + +@pytest.mark.skipif(True, reason="This also segfaults") +def test_get_iterate_postsolve( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, +): + x0 = hs071_initial_guess_fixture + nlp = hs071_problem_instance_fixture + x, info = nlp.solve(x0) + + x, zL, zU, g, lam = nlp.get_current_iterate() + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + +@pytest.mark.skipif(True, reason="Segfaults") +def test_get_violations_uninit(hs071_problem_instance_fixture): + nlp = hs071_problem_instance_fixture + x, zL, zU, g, lam = nlp.get_current_violations() + + +@pytest.mark.skipif(True, reason="Segfaults") +def test_get_violations_postsolve( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, +): + x0 = hs071_initial_guess_fixture + nlp = hs071_problem_instance_fixture + x, info = nlp.solve(x0) + + x, zL, zU, g, lam = nlp.get_current_violations() + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + +def test_get_iterate_hs071( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + problem_definition = hs071_definition_instance_fixture + + # + # Define a callback that uses some "global" information to call + # get_current_iterate and store the result + # + x_iterates = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + # CyIpopt's C wapper expects a callback with this signature. If we + # implemented this as a method on problem_definition, we could store + # and access global information on self. + + # This callback must be defined before constructing the Problem, but can + # be defined after (or as part of) problem_definition. If we attach the + # Problem to the "definition", then we can call get_current_iterate + # from this callback. + iterate = problem_definition.nlp.get_current_iterate(scaled=False) + x, zL, zU, g, lam = iterate + x_iterates.append(x) + + # Hack so we may get the number of iterations after the solve + problem_definition.iter_count = iter_count + + # Replace "intermediate" attribute with our callback, which knows + # about the "Problem", and therefore can call get_current_iterate. + problem_definition.intermediate = intermediate + + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + # Add nlp (the "Problem") as an attribute on our "problem definition". + # This way we can call methods on the Problem, like get_current_iterate, + # during the solve. + problem_definition.nlp = nlp + + # Disable bound push to make testing easier + nlp.add_option("bound_push", 1e-9) + x, info = nlp.solve(x0) + + # Assert correct solution + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + # + # Assert some very basic information about the collected primal iterates + # + assert len(x_iterates) == (1 + problem_definition.iter_count) + + # These could be different due to bound_push (and scaling) + np.testing.assert_allclose(x_iterates[0], x0) + + # These could be different due to honor_original_bounds (and scaling) + np.testing.assert_allclose(x_iterates[-1], x) + + +def test_get_violations_hs071( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + problem_definition = hs071_definition_instance_fixture + + pr_violations = [] + du_violations = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + violations = problem_definition.nlp.get_current_violations(scaled=True) + ( + xL_viol, xU_viol, xL_compl, xU_compl, grad_lag, g_viol, g_compl + ) = violations + pr_violations.append(g_viol) + du_violations.append(grad_lag) + + # Hack so we may get the number of iterations after the solve + problem_definition.iter_count = iter_count + + problem_definition.intermediate = intermediate + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + problem_definition.nlp = nlp + + nlp.add_option("tol", 1e-8) + x, info = nlp.solve(x0) + + # Assert correct solution + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + # + # Assert some very basic information about the collected violations + # + assert len(pr_violations) == (1 + problem_definition.iter_count) + assert len(du_violations) == (1 + problem_definition.iter_count) + + # + # With atol=1e-8, this check fails. This differs from what I see in the + # Ipopt log, where inf_pr is 1.77e-11 at the final iteration. I see + # final primal violations: [2.455637e-07, 1.770672e-11] + # Not sure if a bug or not... + # + np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-8) + + np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) From bf7de5cf03bfa1bf96664a759d51b7d230d6b911 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 10 Feb 2023 16:20:25 -0700 Subject: [PATCH 023/170] TODO comments --- cyipopt/cython/ipopt_wrapper.pyx | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index eb2c105f..a99e52c7 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -674,6 +674,10 @@ cdef class Problem: g = np_g.data mult_g = np_mult_g.data + # NOTE: GetIpoptCurrentIterate can *only* be called during an + # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) + # TODO: Either catch error or avoid calling if we are not in an + # intermediate callback ret = GetIpoptCurrentIterate( self.__nlp, scaled, @@ -718,6 +722,10 @@ cdef class Problem: g_viol = np_g_viol.data compl_g = np_compl_g.data + # NOTE: GetIpoptCurrentViolations can *only* be called during an + # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) + # TODO: Either catch error or avoid calling if we are not in an + # intermediate callback ret = GetIpoptCurrentViolations( self.__nlp, scaled, From dfa93c42ecb97659719a5cfa0db42abaaa961368 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 10 Feb 2023 16:33:38 -0700 Subject: [PATCH 024/170] update tolerance in primal infeas test --- cyipopt/tests/unit/test_ipopt_funcs.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 8998c844..db19c30e 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -208,6 +208,6 @@ def intermediate( # final primal violations: [2.455637e-07, 1.770672e-11] # Not sure if a bug or not... # - np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-8) + np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-6) np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) From 82ae67e6758754b158e0957852c783607222d320 Mon Sep 17 00:00:00 2001 From: Sam Brockie Date: Thu, 12 Jan 2023 17:43:24 +0100 Subject: [PATCH 025/170] Update to actions/checkout@v3 Try mambaforge variant. Use mamba to install. Remove the pyproject.toml file before installing. Use correct multi line command syntax. --- .github/workflows/docs.yml | 10 ++++++---- .github/workflows/test.yml | 16 +++++++++------- .github/workflows/tests.yml | 16 +++++++++------- 3 files changed, 24 insertions(+), 18 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index cf0b01e5..c3aaf680 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -21,17 +21,19 @@ jobs: shell: bash -l {0} steps: - name: Checkout CyIpopt - uses: actions/checkout@v2 + uses: actions/checkout@v3 - uses: conda-incubator/setup-miniconda@v2 with: auto-update-conda: true activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - mamba-version: '*' + miniforge-variant: Mambaforge - name: Install basic dependencies - run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt + run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt - name: Install CyIpopt - run: python -m pip install . + run: | + rm pyproject.toml + python -m pip install . - name: Test building documentation run: cd docs && make clean && make html && cd .. diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 340bef7b..1fe15417 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -22,22 +22,24 @@ jobs: shell: bash -l {0} steps: - name: Checkout CyIpopt - uses: actions/checkout@v2 + uses: actions/checkout@v3 - uses: conda-incubator/setup-miniconda@v2 with: auto-update-conda: true activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - mamba-version: '*' + miniforge-variant: Mambaforge - name: Install basic dependencies - run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt - run: python -m pip install . + run: | + rm pyproject.toml + python -m pip install . - name: Test with pytest - run: + run: | python -c "import cyipopt" - conda install -y -q pytest>=3.3.2 + mamba install -y -q pytest>=3.3.2 pytest - conda install -y -q scipy>=0.19.1 + mamba install -y -q scipy>=0.19.1 pytest diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 4d8543aa..e3031849 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -29,22 +29,24 @@ jobs: shell: bash -l {0} steps: - name: Checkout CyIpopt - uses: actions/checkout@v2 + uses: actions/checkout@v3 - uses: conda-incubator/setup-miniconda@v2 with: auto-update-conda: true activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - mamba-version: '*' + miniforge-variant: Mambaforge - name: Install basic dependencies - run: conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt - run: python -m pip install . + run: | + rm pyproject.toml + python -m pip install . - name: Test with pytest - run: + run: | python -c "import cyipopt" - conda install -y -q pytest>=3.3.2 + mamba install -y -q pytest>=3.3.2 pytest - conda install -y -q scipy>=0.19.1 + mamba install -y -q scipy>=0.19.1 pytest From b87a2351c84f81b2d048cb2d6883a15d3eb9db22 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 11 Feb 2023 09:08:35 +0100 Subject: [PATCH 026/170] coo_array not available in older scipy versions, accomodated tests for this. --- cyipopt/tests/unit/test_scipy_optional.py | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 883e6414..ba42622b 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -76,7 +76,7 @@ def test_minimize_ipopt_nojac_constraints_if_scipy(): reason="Test only valid if Scipy available.") def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy( ): - """`minimize_ipopt` works with objective gradient and Hessian + """`minimize_ipopt` works with objective gradient and Hessian and constraint jacobians and Hessians.""" from scipy.optimize import rosen, rosen_der, rosen_hess x0 = [0.0, 0.0] @@ -109,7 +109,10 @@ def test_minimize_ipopt_sparse_jac_if_scipy(): x0 * x1 * x2 * x3 - 25 >= 0 1 <= x0,x1,x2,x3 <= 5 """ - from scipy.sparse import coo_array + try: + from scipy.sparse import coo_array + except ImportError: + from scipy.sparse import coo_matrix as coo_array def obj(x): return x[0] * x[3] * np.sum(x[:3]) + x[2] @@ -161,7 +164,10 @@ def test_minimize_ipopt_sparse_and_dense_jac_if_scipy(): x0 * x1 * x2 * x3 - 25 >= 0 1 <= x0,x1,x2,x3 <= 5 """ - from scipy.sparse import coo_array + try: + from scipy.sparse import coo_array + except ImportError: + from scipy.sparse import coo_matrix as coo_array def obj(x): return x[0] * x[3] * np.sum(x[:3]) + x[2] @@ -204,10 +210,10 @@ def grad(x): @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_hs071(): - """ `minimize_ipopt` works with objective gradient and Hessian and + """ `minimize_ipopt` works with objective gradient and Hessian and constraint jacobians and Hessians. - The objective and the constraints functions return a tuple containing + The objective and the constraints functions return a tuple containing the function value and the evaluated gradient or jacobian. Solves Hock & Schittkowski's test problem 71: From 7ccf44e457100cfdd7ff373262c9b8c7eb4849cb Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 11 Feb 2023 09:14:07 +0100 Subject: [PATCH 027/170] Remove -q flag from mamba install, add mamba list for default install. Add mamba list calls. Try the conda experimental sovler solution. Use an explicit install command with all packages, --freeze-installed did not seem to work. Try removing lapack before installing scipy. Make sure only the conda forge channel is used in scipy install. Use SciPy 1.9 with Ipopt 3.12. Try skipping only the builds that have issues with scipy being involved. --- .github/workflows/docs.yml | 3 ++- .github/workflows/test.yml | 7 ++++--- .github/workflows/tests.yml | 20 ++++++++++++++++---- 3 files changed, 22 insertions(+), 8 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index c3aaf680..f453bbd3 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -30,10 +30,11 @@ jobs: channels: conda-forge miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt + run: mamba install -y -v lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt - name: Install CyIpopt run: | rm pyproject.toml python -m pip install . + mamba list - name: Test building documentation run: cd docs && make clean && make html && cd .. diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 1fe15417..77294f80 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -31,15 +31,16 @@ jobs: channels: conda-forge miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + run: mamba install -y -v lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt run: | rm pyproject.toml python -m pip install . + mamba list - name: Test with pytest run: | python -c "import cyipopt" - mamba install -y -q pytest>=3.3.2 + mamba install -y -v cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 pytest - mamba install -y -q scipy>=0.19.1 + mamba install -y -v cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.1 pytest diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index e3031849..5cc2742f 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -36,17 +36,29 @@ jobs: activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge - miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + run: | + conda install -n base conda-libmamba-solver + conda config --set solver libmamba + conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt run: | rm pyproject.toml python -m pip install . + conda list - name: Test with pytest run: | python -c "import cyipopt" - mamba install -y -q pytest>=3.3.2 + conda remove lapack + conda install -q -y cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 + conda list pytest - mamba install -y -q scipy>=0.19.1 + - name: Test with pytest and scipy, new ipopt + # cyipopt can build with these dependencies, but it seems impossible to + # also install scipy into these environments likely due to SciPy and + # Ipopt needed different libfortrans. + if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') + run: | + conda install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.0 + conda list pytest From e76fe1d90243edaef72e0b65fda9a8d3c2ba8b3e Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 12 Feb 2023 11:03:33 +0100 Subject: [PATCH 028/170] Import MemoizeJac from scipy.optimize._optimize. --- cyipopt/scipy_interface.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 0bb8ff17..b7aea09c 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -28,9 +28,10 @@ from scipy.optimize import Result OptimizeResult = Result try: - from scipy.optimize import MemoizeJac + # MemoizeJac has been made a private class, see + # https://github.com/scipy/scipy/issues/17572 + from scipy.optimize._optimize import MemoizeJac except ImportError: - # The optimize.optimize namespace is being deprecated from scipy.optimize.optimize import MemoizeJac try: from scipy.sparse import coo_array @@ -67,10 +68,10 @@ class IpoptProblemWrapper(object): constraints : {Constraint, dict} or List of {Constraint, dict}, optional See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html for more information. Note that the jacobian of each constraint - corresponds to the `'jac'` key and must be a callable function + corresponds to the `'jac'` key and must be a callable function with signature ``jac(x) -> {ndarray, coo_array}``. If the constraint's value of `'jac'` is a boolean and True, the constraint function `fun` - is expected to return a tuple `(con_val, con_jac)` consisting of the + is expected to return a tuple `(con_val, con_jac)` consisting of the evaluated constraint `con_val` and the evaluated jacobian `con_jac`. eps : float, optional Epsilon used in finite differences. @@ -78,7 +79,7 @@ class IpoptProblemWrapper(object): Dimensions p_1, ..., p_m of the m constraint functions g_1, ..., g_m : R^n -> R^(p_i). sparse_jacs: array_like, optional - If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse. + If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse. Otherwise, the i-th constraint jacobian is assumed to be dense. jac_nnz_row: array_like, optional The row indices of the nonzero elements in the stacked From 47ecb965fbae0c10213de6bac3a25d9354d7808c Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 12 Feb 2023 11:09:39 +0100 Subject: [PATCH 029/170] Added Ubuntu 22.04 install instructions, fixes #166. --- docs/source/install.rst | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/docs/source/install.rst b/docs/source/install.rst index e2195dfb..3fe320ea 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -108,6 +108,22 @@ official python.org distribution. Even though it has been tested to work with th latest builds, it is well-known for causing issues. (see https://github.com/mechmotum/cyipopt/issues/52). +On Ubuntu 22.04 Using APT Dependencies +-------------------------------------- + +All of the dependencies can be installed with Ubuntu's package manager:: + + $ apt install build-essential pkg-config python3-pip python3-dev cython3 python3-numpy coinor-libipopt1v5 coinor-libipopt-dev + +You can then install cyipopt from the PyPi release with:: + + $ python3 -m pip install cyipopt + +Or you use a local copy with:: + + $ cd /cyipopt/source/directory/ + $ python3 setup.py install + On Ubuntu 18.04 Using APT Dependencies -------------------------------------- From ac4c580752b3a57cf3ff693c71d77158de86b17e Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 12 Feb 2023 11:19:48 +0100 Subject: [PATCH 030/170] Update license to EPL 2.0, fixes #165. --- LICENSE | 433 ++++++++++++++++++------------- README.rst | 2 +- cyipopt/__init__.py | 4 +- cyipopt/cython/ipopt.pxd | 4 +- cyipopt/cython/ipopt_wrapper.pyx | 4 +- cyipopt/scipy_interface.py | 10 +- cyipopt/version.py | 4 +- docs/source/index.rst | 4 +- examples/exception_handling.py | 4 +- examples/hs071.py | 4 +- examples/lasso.py | 4 +- setup.py | 4 +- 12 files changed, 277 insertions(+), 204 deletions(-) diff --git a/LICENSE b/LICENSE index 8f48f685..d3087e4c 100644 --- a/LICENSE +++ b/LICENSE @@ -1,204 +1,277 @@ -Eclipse Public License - v 1.0 +Eclipse Public License - v 2.0 -THE ACCOMPANYING PROGRAM IS PROVIDED UNDER THE TERMS OF THIS ECLIPSE PUBLIC -LICENSE ("AGREEMENT"). 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The Program (including Contributions) may always be +Distributed subject to the version of the Agreement under which it was +received. In addition, after a new version of the Agreement is published, +Contributor may elect to Distribute the Program (including its +Contributions) under the new version. + +Except as expressly stated in Sections 2(a) and 2(b) above, Recipient +receives no rights or licenses to the intellectual property of any +Contributor under this Agreement, whether expressly, by implication, +estoppel or otherwise. All rights in the Program not expressly granted +under this Agreement are reserved. Nothing in this Agreement is intended +to be enforceable by any entity that is not a Contributor or Recipient. +No third-party beneficiary rights are created under this Agreement. + +Exhibit A - Form of Secondary Licenses Notice + +"This Source Code may also be made available under the following +Secondary Licenses when the conditions for such availability set forth +in the Eclipse Public License, v. 2.0 are satisfied: {name license(s), +version(s), and exceptions or additional permissions here}." + + Simply including a copy of this Agreement, including this Exhibit A + is not sufficient to license the Source Code under Secondary Licenses. + + If it is not possible or desirable to put the notice in a particular + file, then You may include the notice in a location (such as a LICENSE + file in a relevant directory) where a recipient would be likely to + look for such a notice. + + You may add additional accurate notices of copyright ownership. diff --git a/README.rst b/README.rst index bbb82149..8c90b145 100644 --- a/README.rst +++ b/README.rst @@ -60,7 +60,7 @@ License cyipopt is open-source code released under the EPL_ license, see the ``LICENSE`` file. -.. _EPL: http://www.eclipse.org/legal/epl-v10.html +.. _EPL: https://www.eclipse.org/legal/epl-2.0/ Contributing ============ diff --git a/cyipopt/__init__.py b/cyipopt/__init__.py index 67327ef3..f116f35e 100644 --- a/cyipopt/__init__.py +++ b/cyipopt/__init__.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ from ipopt_wrapper import * diff --git a/cyipopt/cython/ipopt.pxd b/cyipopt/cython/ipopt.pxd index 91f32867..d86bc2fd 100644 --- a/cyipopt/cython/ipopt.pxd +++ b/cyipopt/cython/ipopt.pxd @@ -4,9 +4,9 @@ cyipopt: Python wrapper for the Ipopt optimization package, written in Cython. Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2021 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ cdef extern from "IpStdCInterface.h": diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index f0e4c530..493baafe 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -4,9 +4,9 @@ cyipopt: Python wrapper for the Ipopt optimization package, written in Cython. Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2021 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ import logging diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 0bb8ff17..6ea49320 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ import sys @@ -67,10 +67,10 @@ class IpoptProblemWrapper(object): constraints : {Constraint, dict} or List of {Constraint, dict}, optional See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html for more information. Note that the jacobian of each constraint - corresponds to the `'jac'` key and must be a callable function + corresponds to the `'jac'` key and must be a callable function with signature ``jac(x) -> {ndarray, coo_array}``. If the constraint's value of `'jac'` is a boolean and True, the constraint function `fun` - is expected to return a tuple `(con_val, con_jac)` consisting of the + is expected to return a tuple `(con_val, con_jac)` consisting of the evaluated constraint `con_val` and the evaluated jacobian `con_jac`. eps : float, optional Epsilon used in finite differences. @@ -78,7 +78,7 @@ class IpoptProblemWrapper(object): Dimensions p_1, ..., p_m of the m constraint functions g_1, ..., g_m : R^n -> R^(p_i). sparse_jacs: array_like, optional - If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse. + If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse. Otherwise, the i-th constraint jacobian is assumed to be dense. jac_nnz_row: array_like, optional The row indices of the nonzero elements in the stacked diff --git a/cyipopt/version.py b/cyipopt/version.py index 3980992e..bfacf1ab 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ __version__ = '1.3.0.dev0' diff --git a/docs/source/index.rst b/docs/source/index.rst index eb7cd080..4d8004ce 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -53,5 +53,5 @@ Copyright | Copyright (C) 2012-2015 Amit Aides | Copyright (C) 2015-2017 Matthias Kümmerer -| Copyright (C) 2017-2021 cyipopt developers -| License: EPL 1.0 +| Copyright (C) 2017-2023 cyipopt developers +| License: EPL 2.0 diff --git a/examples/exception_handling.py b/examples/exception_handling.py index fd7a8d9f..b0416b0c 100644 --- a/examples/exception_handling.py +++ b/examples/exception_handling.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ # Test the "ipopt" Python interface on the Hock & Schittkowski test problem diff --git a/examples/hs071.py b/examples/hs071.py index 9cd31142..d2661eb3 100644 --- a/examples/hs071.py +++ b/examples/hs071.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ # Test the "ipopt" Python interface on the Hock & Schittkowski test problem diff --git a/examples/lasso.py b/examples/lasso.py index 0d7e2569..ef473608 100644 --- a/examples/lasso.py +++ b/examples/lasso.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 Usage:: diff --git a/setup.py b/setup.py index fd55f060..bc203c0b 100644 --- a/setup.py +++ b/setup.py @@ -4,9 +4,9 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2022 cyipopt developers +Copyright (C) 2017-2023 cyipopt developers -License: EPL 1.0 +License: EPL 2.0 """ import sys From 444f0bca304de102f33c14454df368276640b9f7 Mon Sep 17 00:00:00 2001 From: robbybp Date: Sun, 12 Feb 2023 23:08:30 -0700 Subject: [PATCH 031/170] check ipopt version before calling GetIpoptCurrentIterate --- cyipopt/cython/ipopt.pxd | 9 ++++++++ cyipopt/cython/ipopt_wrapper.pyx | 20 +++++++++++++++- cyipopt/tests/unit/test_ipopt_funcs.py | 32 ++++++++++++++++++++++++++ 3 files changed, 60 insertions(+), 1 deletion(-) diff --git a/cyipopt/cython/ipopt.pxd b/cyipopt/cython/ipopt.pxd index a1a6307f..27c88bd2 100644 --- a/cyipopt/cython/ipopt.pxd +++ b/cyipopt/cython/ipopt.pxd @@ -9,6 +9,15 @@ Copyright (C) 2017-2021 cyipopt developers License: EPL 1.0 """ +cdef extern from "IpoptConfig.h": + + int IPOPT_VERSION_MAJOR + + int IPOPT_VERSION_MINOR + + int IPOPT_VERSION_RELEASE + + cdef extern from "IpStdCInterface.h": ctypedef double Number diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index a99e52c7..4f739209 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -19,7 +19,11 @@ cimport numpy as np from cyipopt.utils import deprecated_warning, generate_deprecation_warning_msg from ipopt cimport * -__all__ = ["set_logging_level", "setLoggingLevel", "Problem", "problem"] +__all__ = [ + "set_logging_level", "setLoggingLevel", "Problem", "problem", "IPOPT_VERSION" +] + +IPOPT_VERSION = (IPOPT_VERSION_MAJOR, IPOPT_VERSION_MINOR, IPOPT_VERSION_RELEASE) DTYPEi = np.int32 ctypedef np.int32_t DTYPEi_t @@ -655,6 +659,13 @@ cdef class Problem: return np_x, info def get_current_iterate(self, scaled=False): + major, minor, release = IPOPT_VERSION + if major < 3 or (major == 3 and minor < 14): + raise RuntimeError( + "get_current_iterate only supports Ipopt version >=3.14.0" + " CyIpopt is compiled with version %s.%s.%s" + % (major, minor, release) + ) # Allocate arrays to hold the current iterate cdef np.ndarray[DTYPEd_t, ndim=1] np_x cdef np.ndarray[DTYPEd_t, ndim=1] np_mult_x_L @@ -697,6 +708,13 @@ cdef class Problem: return (np_x, np_mult_x_L, np_mult_x_U, np_g, np_mult_g) def get_current_violations(self, scaled=False): + major, minor, release = IPOPT_VERSION + if major < 3 or (major == 3 and minor < 14): + raise RuntimeError( + "get_current_violations only supports Ipopt version >=3.14.0" + " CyIpopt is compiled with version %s.%s.%s" + % (major, minor, release) + ) # Allocate arrays to hold current violations cdef np.ndarray[DTYPEd_t, ndim=1] np_x_L_viol cdef np.ndarray[DTYPEd_t, ndim=1] np_x_U_viol diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index db19c30e..32feede4 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -3,6 +3,8 @@ import cyipopt +IPVERSION = cyipopt.IPOPT_VERSION + @pytest.mark.skipif(True, reason="This segfaults. Ideally, it fails gracefully") def test_get_iterate_uninit(hs071_problem_instance_fixture): """Test that we can call get_current_iterate on an uninitialized problem @@ -45,6 +47,32 @@ def test_get_violations_postsolve( np.testing.assert_allclose(x, expected_x) +@pytest.mark.skipif( + IPVERSION[0] == 3 and IPVERSION[1] >= 14, + reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", +) +def test_get_iterate_fail_pre_3_14_0(hs071_problem_instance_fixture): + nlp = hs071_problem_instance_fixture + with pytest.Raises(RuntimeError): + # TODO: Test error message + x, zL, zU, g, lam = nlp.get_current_iterate() + + +@pytest.mark.skipif( + IPVERSION[0] == 3 and IPVERSION[1] >= 14, + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", +) +def test_get_violations_fail_pre_3_14_0(hs071_problem_instance_fixture): + nlp = hs071_problem_instance_fixture + with pytest.Raises(RuntimeError): + # TODO: Test error message + violations = nlp.get_current_violations() + + +@pytest.mark.skipif( + IPVERSION[0] < 3 or (IPVERSION[0] == 3 and IPVERSION[1] < 14), + reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", +) def test_get_iterate_hs071( hs071_initial_guess_fixture, hs071_definition_instance_fixture, @@ -134,6 +162,10 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) +@pytest.mark.skipif( + IPVERSION[0] < 3 or (IPVERSION[0] == 3 and IPVERSION[1] < 14), + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", +) def test_get_violations_hs071( hs071_initial_guess_fixture, hs071_definition_instance_fixture, From 7e5913b983ea07c86aaf8c655c8d93793daa91f6 Mon Sep 17 00:00:00 2001 From: Sam Brockie Date: Mon, 13 Feb 2023 10:30:10 +0100 Subject: [PATCH 032/170] Update remaining references to EPL 2.0 from EPL 1.0 --- setup.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/setup.py b/setup.py index bc203c0b..93ddd329 100644 --- a/setup.py +++ b/setup.py @@ -52,10 +52,10 @@ "numpy>=1.15", "setuptools>=39.0", ] -LICENSE = "EPL-1.0" +LICENSE = "EPL-2.0" CLASSIFIERS = [ "Development Status :: 5 - Production/Stable", - "License :: OSI Approved :: Eclipse Public License 1.0 (EPL-1.0)", + "License :: OSI Approved :: Eclipse Public License 2.0 (EPL-2.0)", "Intended Audience :: Science/Research", "Operating System :: OS Independent", "Programming Language :: Python :: 3.7", From 5b3290685b036f20f701a70fa7a16fda20c1e05f Mon Sep 17 00:00:00 2001 From: robbybp Date: Mon, 13 Feb 2023 22:44:16 -0700 Subject: [PATCH 033/170] check Ipopt version at build time --- cyipopt/cython/ipopt.pxd | 70 +++++++++++++++++++++++++- cyipopt/cython/ipopt_wrapper.pyx | 4 +- cyipopt/tests/unit/test_ipopt_funcs.py | 18 ++++--- 3 files changed, 81 insertions(+), 11 deletions(-) diff --git a/cyipopt/cython/ipopt.pxd b/cyipopt/cython/ipopt.pxd index 27c88bd2..f4cecc35 100644 --- a/cyipopt/cython/ipopt.pxd +++ b/cyipopt/cython/ipopt.pxd @@ -19,6 +19,68 @@ cdef extern from "IpoptConfig.h": cdef extern from "IpStdCInterface.h": + """ + #define VERSION_LT_3_14_0\ + (IPOPT_VERSION_MAJOR < 3\ + || (IPOPT_VERSION_MAJOR == 3 && IPOPT_VERSION_MINOR < 14)) + + #if VERSION_LT_3_14_0 + // If not defined, define dummy versions of these functions + Bool GetIpoptCurrentIterate( + IpoptProblem ipopt_problem, + Bool scaled, + Index n, + Number* x, + Number* z_L, + Number* z_U, + Index m, + Number* g, + Number* lambd + ){ + return 0; + } + Bool GetIpoptCurrentViolations( + IpoptProblem ipopt_problem, + Bool scaled, + Index n, + Number* x_L_violation, + Number* x_U_violation, + Number* compl_x_L, + Number* compl_x_U, + Number* grad_lag_x, + Index m, + Number* nlp_constraint_violation, + Number* compl_g + ){ + return 0; + } + #define _ip_get_iter(\ + problem, scaled, n, x, z_L, z_U, m, g, lambd\ + )\ + GetIpoptCurrentIterate(\ + problem, scaled, n, x, z_L, z_U, m, g, lambd\ + ) + #define _ip_get_viol(\ + problem, scaled, n, xL, xU, complxL, complxU, glx, m, cviol, complg\ + )\ + GetIpoptCurrentViolations(\ + problem, scaled, n, xL, xU, complxL, complxU, glx, m, cviol, complg\ + ) + #else + #define _ip_get_iter(\ + problem, scaled, n, x, z_L, z_U, m, g, lambd\ + )\ + GetIpoptCurrentIterate(\ + problem, scaled, n, x, z_L, z_U, m, g, lambd\ + ) + #define _ip_get_viol(\ + problem, scaled, n, xL, xU, complxL, complxU, glx, m, cviol, complg\ + )\ + GetIpoptCurrentViolations(\ + problem, scaled, n, xL, xU, complxL, complxU, glx, m, cviol, complg\ + ) + #endif + """ ctypedef double Number @@ -177,7 +239,9 @@ cdef extern from "IpStdCInterface.h": UserDataPtr user_data ) - Bool GetIpoptCurrentIterate( + # Wrapper around GetIpoptCurrentIterate with a dummy implementation in + # case it is not defined (i.e. Ipopt < 3.14.0) + Bool CyGetCurrentIterate "_ip_get_iter" ( IpoptProblem ipopt_problem, Bool scaled, Index n, @@ -189,7 +253,9 @@ cdef extern from "IpStdCInterface.h": Number* lambd ) - Bool GetIpoptCurrentViolations( + # Wrapper around GetIpoptCurrentViolations with a dummy implementation in + # case it is not defined (i.e. Ipopt < 3.14.0) + Bool CyGetCurrentViolations "_ip_get_viol" ( IpoptProblem ipopt_problem, Bool scaled, Index n, diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 4f739209..ee944448 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -689,7 +689,7 @@ cdef class Problem: # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) # TODO: Either catch error or avoid calling if we are not in an # intermediate callback - ret = GetIpoptCurrentIterate( + ret = CyGetCurrentIterate( self.__nlp, scaled, self.__n, @@ -744,7 +744,7 @@ cdef class Problem: # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) # TODO: Either catch error or avoid calling if we are not in an # intermediate callback - ret = GetIpoptCurrentViolations( + ret = CyGetCurrentViolations( self.__nlp, scaled, self.__n, diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 32feede4..bb59bbbe 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -3,7 +3,11 @@ import cyipopt -IPVERSION = cyipopt.IPOPT_VERSION +pre_3_14_0 = ( + cyipopt.IPOPT_VERSION[0] < 3 + or (cyipopt.IPOPT_VERSION[0] == 3 and cyipopt.IPOPT_VERSION[1] < 14) +) + @pytest.mark.skipif(True, reason="This segfaults. Ideally, it fails gracefully") def test_get_iterate_uninit(hs071_problem_instance_fixture): @@ -48,29 +52,29 @@ def test_get_violations_postsolve( @pytest.mark.skipif( - IPVERSION[0] == 3 and IPVERSION[1] >= 14, + not pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", ) def test_get_iterate_fail_pre_3_14_0(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - with pytest.Raises(RuntimeError): + with pytest.raises(RuntimeError): # TODO: Test error message x, zL, zU, g, lam = nlp.get_current_iterate() @pytest.mark.skipif( - IPVERSION[0] == 3 and IPVERSION[1] >= 14, + not pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", ) def test_get_violations_fail_pre_3_14_0(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - with pytest.Raises(RuntimeError): + with pytest.raises(RuntimeError): # TODO: Test error message violations = nlp.get_current_violations() @pytest.mark.skipif( - IPVERSION[0] < 3 or (IPVERSION[0] == 3 and IPVERSION[1] < 14), + pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", ) def test_get_iterate_hs071( @@ -163,7 +167,7 @@ def intermediate( @pytest.mark.skipif( - IPVERSION[0] < 3 or (IPVERSION[0] == 3 and IPVERSION[1] < 14), + pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", ) def test_get_violations_hs071( From f2a0acf9060afaf39e83fa39e73d2f530b5dbc23 Mon Sep 17 00:00:00 2001 From: robbybp Date: Mon, 13 Feb 2023 22:47:49 -0700 Subject: [PATCH 034/170] update pre/post-solve tests so they work with latest Ipopt branch --- cyipopt/tests/unit/test_ipopt_funcs.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index bb59bbbe..be605728 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -26,7 +26,7 @@ def test_get_iterate_postsolve( nlp = hs071_problem_instance_fixture x, info = nlp.solve(x0) - x, zL, zU, g, lam = nlp.get_current_iterate() + x_iter, zL, zU, g, lam = nlp.get_current_iterate() expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) @@ -34,7 +34,7 @@ def test_get_iterate_postsolve( @pytest.mark.skipif(True, reason="Segfaults") def test_get_violations_uninit(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - x, zL, zU, g, lam = nlp.get_current_violations() + violations = nlp.get_current_violations() @pytest.mark.skipif(True, reason="Segfaults") @@ -46,7 +46,7 @@ def test_get_violations_postsolve( nlp = hs071_problem_instance_fixture x, info = nlp.solve(x0) - x, zL, zU, g, lam = nlp.get_current_violations() + violations = nlp.get_current_violations() expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) From 77efa0dadd64784bdb07ebcd6f7ffda6f187b9f2 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 14 Feb 2023 13:52:26 -0700 Subject: [PATCH 035/170] add flag to degect whether we are in a call to IpoptSolve --- cyipopt/cython/ipopt_wrapper.pyx | 45 ++++++++++++++++++++--- cyipopt/tests/unit/test_ipopt_funcs.py | 50 +++++++++++++++++++------- 2 files changed, 78 insertions(+), 17 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index ee944448..2a9e4312 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -279,6 +279,7 @@ cdef class Problem: cdef public Index __m cdef public object __exception + cdef Bool __in_ipopt_solve def __init__(self, n, m, problem_obj=None, lb=None, ub=None, cl=None, cu=None): @@ -437,6 +438,10 @@ cdef class Problem: self.__exception = None + # This flag is necessary to prevent segfaults in Ipopt <=3.14.11 due + # to the lack of guard for __nlp->tnlp being NULL or undefined. + self.__in_ipopt_solve = False + def __dealloc__(self): if self.__nlp != NULL: FreeIpoptProblem(self.__nlp) @@ -632,6 +637,9 @@ cdef class Problem: cdef Number obj_val = 0 + # Set flag that we are in a solve, so __nlp->tnlp references (e.g. in + # get_current_iterate) are valid. + self.__in_ipopt_solve = True stat = IpoptSolve(self.__nlp, np_x.data, g.data, @@ -641,6 +649,8 @@ cdef class Problem: mult_x_U.data, self ) + # Unset flag + self.__in_ipopt_solve = False if self.__exception: raise self.__exception[0], self.__exception[1], self.__exception[2] @@ -659,6 +669,8 @@ cdef class Problem: return np_x, info def get_current_iterate(self, scaled=False): + # Check that we are using an Ipopt version that supports this + # functionality major, minor, release = IPOPT_VERSION if major < 3 or (major == 3 and minor < 14): raise RuntimeError( @@ -666,6 +678,13 @@ cdef class Problem: " CyIpopt is compiled with version %s.%s.%s" % (major, minor, release) ) + # Check that we are in a solve. This is necessary to prevent segfaults + # pre-Ipopt 3.14.12 + if not self.__in_ipopt_solve: + raise RuntimeError( + "get_current_iterate can only be called during a call to solve," + " e.g. in an intermediate callback." + ) # Allocate arrays to hold the current iterate cdef np.ndarray[DTYPEd_t, ndim=1] np_x cdef np.ndarray[DTYPEd_t, ndim=1] np_mult_x_L @@ -689,7 +708,7 @@ cdef class Problem: # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) # TODO: Either catch error or avoid calling if we are not in an # intermediate callback - ret = CyGetCurrentIterate( + successful = CyGetCurrentIterate( self.__nlp, scaled, self.__n, @@ -700,11 +719,14 @@ cdef class Problem: g, mult_g, ) + if not successful: + raise RuntimeError( + "Ipopt could not get the current iterate. This can happen when" + " get_current_iterate is called outside of an intermediate" + " callback." + ) # Return values to user - # - Is another data type (e.g. dict, namedtuple) more appropriate than - # simply a tuple? - # - Should `ret` be returned here? return (np_x, np_mult_x_L, np_mult_x_U, np_g, np_mult_g) def get_current_violations(self, scaled=False): @@ -715,6 +737,13 @@ cdef class Problem: " CyIpopt is compiled with version %s.%s.%s" % (major, minor, release) ) + # Check that we are in a solve. This is necessary to prevent segfaults + # pre-Ipopt 3.14.12 + if not self.__in_ipopt_solve: + raise RuntimeError( + "get_current_violations can only be called during a call to solve," + " e.g. in an intermediate callback." + ) # Allocate arrays to hold current violations cdef np.ndarray[DTYPEd_t, ndim=1] np_x_L_viol cdef np.ndarray[DTYPEd_t, ndim=1] np_x_U_viol @@ -744,7 +773,7 @@ cdef class Problem: # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) # TODO: Either catch error or avoid calling if we are not in an # intermediate callback - ret = CyGetCurrentViolations( + successful = CyGetCurrentViolations( self.__nlp, scaled, self.__n, @@ -757,6 +786,12 @@ cdef class Problem: g_viol, compl_g, ) + if not successful: + raise RuntimeError( + "Ipopt could not get the current violations. This can happen" + " when get_current_violations is called outside of an" + " intermediate callback." + ) return ( np_x_L_viol, diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index be605728..b8087b1f 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -9,15 +9,25 @@ ) -@pytest.mark.skipif(True, reason="This segfaults. Ideally, it fails gracefully") +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", + # skip these tests in old versions as the version check happens before + # the __in_ipopt_solve check +) def test_get_iterate_uninit(hs071_problem_instance_fixture): """Test that we can call get_current_iterate on an uninitialized problem """ nlp = hs071_problem_instance_fixture - x, zL, zU, g, lam = nlp.get_current_iterate() + msg = "can only be called during a call to solve" + with pytest.raises(RuntimeError, match=msg): + x, zL, zU, g, lam = nlp.get_current_iterate() -@pytest.mark.skipif(True, reason="This also segfaults") +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", +) def test_get_iterate_postsolve( hs071_initial_guess_fixture, hs071_problem_instance_fixture, @@ -26,18 +36,28 @@ def test_get_iterate_postsolve( nlp = hs071_problem_instance_fixture x, info = nlp.solve(x0) - x_iter, zL, zU, g, lam = nlp.get_current_iterate() + msg = "can only be called during a call to solve" + with pytest.raises(RuntimeError, match=msg): + x, zL, zU, g, lam = nlp.get_current_iterate() expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) -@pytest.mark.skipif(True, reason="Segfaults") +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", +) def test_get_violations_uninit(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - violations = nlp.get_current_violations() + msg = "can only be called during a call to solve" + with pytest.raises(RuntimeError, match=msg): + violations = nlp.get_current_violations() -@pytest.mark.skipif(True, reason="Segfaults") +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", +) def test_get_violations_postsolve( hs071_initial_guess_fixture, hs071_problem_instance_fixture, @@ -46,7 +66,9 @@ def test_get_violations_postsolve( nlp = hs071_problem_instance_fixture x, info = nlp.solve(x0) - violations = nlp.get_current_violations() + msg = "can only be called during a call to solve" + with pytest.raises(RuntimeError, match=msg): + violations = nlp.get_current_violations() expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) @@ -57,8 +79,10 @@ def test_get_violations_postsolve( ) def test_get_iterate_fail_pre_3_14_0(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - with pytest.raises(RuntimeError): - # TODO: Test error message + # Note that the version check happens before the __in_ipopt_solve + # check, so we don't need to call solve to test this. + msg = "only supports Ipopt version >=3.14.0" + with pytest.raises(RuntimeError, match=msg): x, zL, zU, g, lam = nlp.get_current_iterate() @@ -68,8 +92,10 @@ def test_get_iterate_fail_pre_3_14_0(hs071_problem_instance_fixture): ) def test_get_violations_fail_pre_3_14_0(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture - with pytest.raises(RuntimeError): - # TODO: Test error message + # Note that the version check happens before the __in_ipopt_solve + # check, so we don't need to call solve to test this. + msg = "only supports Ipopt version >=3.14.0" + with pytest.raises(RuntimeError, match=msg): violations = nlp.get_current_violations() From 0ad62e84553142342069a81cdd21953a8ed42596 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 14 Feb 2023 13:53:20 -0700 Subject: [PATCH 036/170] remove outdated comment --- cyipopt/cython/ipopt_wrapper.pyx | 8 -------- 1 file changed, 8 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 2a9e4312..3744f3c7 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -704,10 +704,6 @@ cdef class Problem: g = np_g.data mult_g = np_mult_g.data - # NOTE: GetIpoptCurrentIterate can *only* be called during an - # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) - # TODO: Either catch error or avoid calling if we are not in an - # intermediate callback successful = CyGetCurrentIterate( self.__nlp, scaled, @@ -769,10 +765,6 @@ cdef class Problem: g_viol = np_g_viol.data compl_g = np_compl_g.data - # NOTE: GetIpoptCurrentViolations can *only* be called during an - # intermediate callback (otherwise __nlp->tnlp->ip_data_ is NULL) - # TODO: Either catch error or avoid calling if we are not in an - # intermediate callback successful = CyGetCurrentViolations( self.__nlp, scaled, From fd4356ff2bd120ef63de0503dd69d572ee89919a Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 14 Feb 2023 14:17:08 -0700 Subject: [PATCH 037/170] update return types from get_current_* to dicts --- cyipopt/cython/ipopt_wrapper.pyx | 26 ++++++++++++++++---------- cyipopt/tests/unit/test_ipopt_funcs.py | 16 ++++++---------- 2 files changed, 22 insertions(+), 20 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 3744f3c7..a0c9fd1b 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -723,7 +723,13 @@ cdef class Problem: ) # Return values to user - return (np_x, np_mult_x_L, np_mult_x_U, np_g, np_mult_g) + return { + "x": np_x, + "mult_x_L": np_mult_x_L, + "mult_x_U": np_mult_x_U, + "g": np_g, + "mult_g": np_mult_g, + } def get_current_violations(self, scaled=False): major, minor, release = IPOPT_VERSION @@ -785,15 +791,15 @@ cdef class Problem: " intermediate callback." ) - return ( - np_x_L_viol, - np_x_U_viol, - np_compl_x_L, - np_compl_x_U, - np_grad_lag_x, - np_g_viol, - np_compl_g, - ) + return { + "x_L_violation": np_x_L_viol, + "x_U_violation": np_x_U_viol, + "compl_x_L": np_compl_x_L, + "compl_x_U": np_compl_x_U, + "grad_lag_x": np_grad_lag_x, + "nlp_constraint_violation": np_g_viol, + "compl_g": np_compl_g, + } # diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index b8087b1f..4883a923 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -21,7 +21,7 @@ def test_get_iterate_uninit(hs071_problem_instance_fixture): nlp = hs071_problem_instance_fixture msg = "can only be called during a call to solve" with pytest.raises(RuntimeError, match=msg): - x, zL, zU, g, lam = nlp.get_current_iterate() + iterate = nlp.get_current_iterate() @pytest.mark.skipif( @@ -38,7 +38,7 @@ def test_get_iterate_postsolve( msg = "can only be called during a call to solve" with pytest.raises(RuntimeError, match=msg): - x, zL, zU, g, lam = nlp.get_current_iterate() + iterate = nlp.get_current_iterate() expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) @@ -83,7 +83,7 @@ def test_get_iterate_fail_pre_3_14_0(hs071_problem_instance_fixture): # check, so we don't need to call solve to test this. msg = "only supports Ipopt version >=3.14.0" with pytest.raises(RuntimeError, match=msg): - x, zL, zU, g, lam = nlp.get_current_iterate() + iterate = nlp.get_current_iterate() @pytest.mark.skipif( @@ -148,8 +148,7 @@ def intermediate( # Problem to the "definition", then we can call get_current_iterate # from this callback. iterate = problem_definition.nlp.get_current_iterate(scaled=False) - x, zL, zU, g, lam = iterate - x_iterates.append(x) + x_iterates.append(iterate["x"]) # Hack so we may get the number of iterations after the solve problem_definition.iter_count = iter_count @@ -230,11 +229,8 @@ def intermediate( ls_trials, ): violations = problem_definition.nlp.get_current_violations(scaled=True) - ( - xL_viol, xU_viol, xL_compl, xU_compl, grad_lag, g_viol, g_compl - ) = violations - pr_violations.append(g_viol) - du_violations.append(grad_lag) + pr_violations.append(violations["nlp_constraint_violation"]) + du_violations.append(violations["grad_lag_x"]) # Hack so we may get the number of iterations after the solve problem_definition.iter_count = iter_count From d4c7a7c6d28a8e0c5507d651b2878ae49447f61d Mon Sep 17 00:00:00 2001 From: robbybp Date: Wed, 15 Feb 2023 12:45:40 -0700 Subject: [PATCH 038/170] turn off bound relaxation and set atol for (final) intermediate primal infeasibility to 1e-8 --- cyipopt/tests/unit/test_ipopt_funcs.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index be605728..69661fe4 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -226,6 +226,11 @@ def intermediate( problem_definition.nlp = nlp nlp.add_option("tol", 1e-8) + # Note that Ipopt appears to check tolerance in the scaled, bound-relaxed + # NLP. To ensure our intermediate infeasibilities, which are in the user's + # original NLP, are less than the above tolerance at the final iteration, + # we must turn off bound relaxation. + nlp.add_option("bound_relax_factor", 0.0) x, info = nlp.solve(x0) # Assert correct solution @@ -238,12 +243,5 @@ def intermediate( assert len(pr_violations) == (1 + problem_definition.iter_count) assert len(du_violations) == (1 + problem_definition.iter_count) - # - # With atol=1e-8, this check fails. This differs from what I see in the - # Ipopt log, where inf_pr is 1.77e-11 at the final iteration. I see - # final primal violations: [2.455637e-07, 1.770672e-11] - # Not sure if a bug or not... - # - np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-6) - + np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-8) np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) From 7cf21e1b19fb8ca5c1d765053f3e43832c8a33e7 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Thu, 16 Feb 2023 11:47:14 -0700 Subject: [PATCH 039/170] install libarchive --- .github/workflows/tests.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 5cc2742f..c9c4b0ce 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -38,6 +38,7 @@ jobs: channels: conda-forge - name: Install basic dependencies run: | + conda install -n base libarchive conda install -n base conda-libmamba-solver conda config --set solver libmamba conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 From c6c01f963b28a14f2688ef8ec20b81c65f2bfc19 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 18 Feb 2023 06:22:32 +0100 Subject: [PATCH 040/170] Change CI to use mambaforge. --- .github/workflows/tests.yml | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 5cc2742f..381cd1a2 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -36,22 +36,21 @@ jobs: activate-environment: test-environment python-version: ${{ matrix.python-version }} channels: conda-forge + miniforge-variant: Mambaforge - name: Install basic dependencies run: | - conda install -n base conda-libmamba-solver - conda config --set solver libmamba - conda install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - name: Install CyIpopt run: | rm pyproject.toml python -m pip install . - conda list + mamba list - name: Test with pytest run: | python -c "import cyipopt" - conda remove lapack - conda install -q -y cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 - conda list + mamba remove lapack + mamba install -q -y cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 + mamba list pytest - name: Test with pytest and scipy, new ipopt # cyipopt can build with these dependencies, but it seems impossible to @@ -59,6 +58,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - conda install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.0 - conda list + mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.0 + mamba list pytest From 02bd357e854a59aa04fc607a106ba1bf3d4ba588 Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 08:18:21 -0700 Subject: [PATCH 041/170] get_current_iterate docstring --- cyipopt/cython/ipopt_wrapper.pyx | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index a0c9fd1b..323d3f00 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -669,6 +669,23 @@ cdef class Problem: return np_x, info def get_current_iterate(self, scaled=False): + """Return the current iterate vectors during an Ipopt solve + + The iterate contains vectors for primal variables, bound multipliers, + constraint function values, and constraint multipliers. + + Parameters + ---------- + scaled: Bool + Whether the scaled iterate vectors should be returned + + Returns + ------- + dict + A dict containing the iterate vector with keys ``x``, + ``mult_x_L``, ``mult_x_U``, ``g``, and ``mult_g`` + + """ # Check that we are using an Ipopt version that supports this # functionality major, minor, release = IPOPT_VERSION From e91ceffa70dbfe0435f3b2f806fbfd399d4cf569 Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 14:17:07 -0700 Subject: [PATCH 042/170] docstring for get_current_violations --- cyipopt/cython/ipopt_wrapper.pyx | 24 ++++++++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 323d3f00..9ac8aeb3 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -682,8 +682,8 @@ cdef class Problem: Returns ------- dict - A dict containing the iterate vector with keys ``x``, - ``mult_x_L``, ``mult_x_U``, ``g``, and ``mult_g`` + A dict containing the iterate vector with keys ``"x"``, + ``"mult_x_L"``, ``"mult_x_U"``, ``"g"``, and ``"mult_g"`` """ # Check that we are using an Ipopt version that supports this @@ -749,6 +749,26 @@ cdef class Problem: } def get_current_violations(self, scaled=False): + """Return the current violation vectors during an Ipopt solve + + Violations returned are primal variable bound violations, bound + complementarities, the gradient of the Lagrangian, constraint + violation, and constraint complementarity. + + Parameters + ---------- + scaled: Bool + Whether to scale the returned violations + + Returns + ------- + dict + A dict containing the violation vector with keys + ``"x_L_violation"``, ``"x_U_violation"``, ``"compl_x_L"``, + ``"compl_x_U"``, ``"grad_lag_x"``, ``"nlp_constraint_violation"``, + and ``"compl_g"`` + + """ major, minor, release = IPOPT_VERSION if major < 3 or (major == 3 and minor < 14): raise RuntimeError( From e74299b304211e7529ec739707b539d57ef49d18 Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 21:55:33 -0700 Subject: [PATCH 043/170] return none from get_current_* if values are not loaded --- cyipopt/cython/ipopt_wrapper.pyx | 69 ++++++++++++++++---------------- 1 file changed, 35 insertions(+), 34 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 9ac8aeb3..146608c5 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -672,7 +672,9 @@ cdef class Problem: """Return the current iterate vectors during an Ipopt solve The iterate contains vectors for primal variables, bound multipliers, - constraint function values, and constraint multipliers. + constraint function values, and constraint multipliers. Here, the + constraints are treated as a single function rather than separating + equality and inequality constraints. Parameters ---------- @@ -732,28 +734,28 @@ cdef class Problem: g, mult_g, ) - if not successful: - raise RuntimeError( - "Ipopt could not get the current iterate. This can happen when" - " get_current_iterate is called outside of an intermediate" - " callback." - ) - - # Return values to user - return { - "x": np_x, - "mult_x_L": np_mult_x_L, - "mult_x_U": np_mult_x_U, - "g": np_g, - "mult_g": np_mult_g, - } + if successful: + # Return values to user + return { + "x": np_x, + "mult_x_L": np_mult_x_L, + "mult_x_U": np_mult_x_U, + "g": np_g, + "mult_g": np_mult_g, + } + else: + # This happens if this method is called during IpoptSolve, + # but outside of an intermediate callback. + return None def get_current_violations(self, scaled=False): """Return the current violation vectors during an Ipopt solve Violations returned are primal variable bound violations, bound complementarities, the gradient of the Lagrangian, constraint - violation, and constraint complementarity. + violation, and constraint complementarity. Here, the constraints + are treated as a single function rather than separating equality + and inequality constraints. Parameters ---------- @@ -765,7 +767,7 @@ cdef class Problem: dict A dict containing the violation vector with keys ``"x_L_violation"``, ``"x_U_violation"``, ``"compl_x_L"``, - ``"compl_x_U"``, ``"grad_lag_x"``, ``"nlp_constraint_violation"``, + ``"compl_x_U"``, ``"grad_lag_x"``, ``"g_violation"``, and ``"compl_g"`` """ @@ -821,22 +823,21 @@ cdef class Problem: g_viol, compl_g, ) - if not successful: - raise RuntimeError( - "Ipopt could not get the current violations. This can happen" - " when get_current_violations is called outside of an" - " intermediate callback." - ) - - return { - "x_L_violation": np_x_L_viol, - "x_U_violation": np_x_U_viol, - "compl_x_L": np_compl_x_L, - "compl_x_U": np_compl_x_U, - "grad_lag_x": np_grad_lag_x, - "nlp_constraint_violation": np_g_viol, - "compl_g": np_compl_g, - } + if successful: + # Return values to the user + return { + "x_L_violation": np_x_L_viol, + "x_U_violation": np_x_U_viol, + "compl_x_L": np_compl_x_L, + "compl_x_U": np_compl_x_U, + "grad_lag_x": np_grad_lag_x, + "g_violation": np_g_viol, + "compl_g": np_compl_g, + } + else: + # This happens if this method is called during IpoptSolve, + # but outside of an intermediate callback. + return None # From 5d08fed26842b43b4632bee66215eb30517a4e9e Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 22:25:23 -0700 Subject: [PATCH 044/170] update key in violation dict --- cyipopt/tests/unit/test_ipopt_funcs.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 69cc80a9..a7e38f23 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -229,7 +229,7 @@ def intermediate( ls_trials, ): violations = problem_definition.nlp.get_current_violations(scaled=True) - pr_violations.append(violations["nlp_constraint_violation"]) + pr_violations.append(violations["g_violation"]) du_violations.append(violations["grad_lag_x"]) # Hack so we may get the number of iterations after the solve From f0dba5e69c88e3eb9c3e176739d518892ccbb4db Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 22:38:41 -0700 Subject: [PATCH 045/170] update docstrings --- cyipopt/cython/ipopt_wrapper.pyx | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 4a04674d..64fa734a 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -674,7 +674,10 @@ cdef class Problem: The iterate contains vectors for primal variables, bound multipliers, constraint function values, and constraint multipliers. Here, the constraints are treated as a single function rather than separating - equality and inequality constraints. + equality and inequality constraints. This method can only be called + during an intermediate callback. + + **Only supports Ipopt >=3.14.0** Parameters ---------- @@ -685,7 +688,8 @@ cdef class Problem: ------- dict A dict containing the iterate vector with keys ``"x"``, - ``"mult_x_L"``, ``"mult_x_U"``, ``"g"``, and ``"mult_g"`` + ``"mult_x_L"``, ``"mult_x_U"``, ``"g"``, and ``"mult_g"``. + If iterate vectors cannot be obtained, ``None`` is returned. """ # Check that we are using an Ipopt version that supports this @@ -755,7 +759,10 @@ cdef class Problem: complementarities, the gradient of the Lagrangian, constraint violation, and constraint complementarity. Here, the constraints are treated as a single function rather than separating equality - and inequality constraints. + and inequality constraints. This method can only be called during + an intermediate callback. + + **Only supports Ipopt >=3.14.0** Parameters ---------- @@ -764,11 +771,12 @@ cdef class Problem: Returns ------- - dict + dict or None A dict containing the violation vector with keys ``"x_L_violation"``, ``"x_U_violation"``, ``"compl_x_L"``, ``"compl_x_U"``, ``"grad_lag_x"``, ``"g_violation"``, - and ``"compl_g"`` + and ``"compl_g"``. If violation vectors cannot be obtained, + ``None`` is returned. """ major, minor, release = IPOPT_VERSION From 2aa23ab0749b8149f3e417d06b22582e13cca8ac Mon Sep 17 00:00:00 2001 From: robbybp Date: Sat, 18 Feb 2023 22:40:11 -0700 Subject: [PATCH 046/170] update docstring --- cyipopt/cython/ipopt_wrapper.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 64fa734a..fb77d31b 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -686,7 +686,7 @@ cdef class Problem: Returns ------- - dict + dict or None A dict containing the iterate vector with keys ``"x"``, ``"mult_x_L"``, ``"mult_x_U"``, ``"g"``, and ``"mult_g"``. If iterate vectors cannot be obtained, ``None`` is returned. From 29393b2776d4bcd1448741c8fe7599c3eca64a9e Mon Sep 17 00:00:00 2001 From: robbybp Date: Sun, 19 Feb 2023 11:25:21 -0700 Subject: [PATCH 047/170] prototype support for 12-arg intermediate callback --- cyipopt/cython/ipopt_wrapper.pyx | 46 +++++++++++---- cyipopt/tests/unit/test_ipopt_funcs.py | 81 ++++++++++++++++++++++++++ 2 files changed, 115 insertions(+), 12 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index fb77d31b..e87811c7 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -12,6 +12,7 @@ License: EPL 2.0 import logging import sys import warnings +import inspect import numpy as np cimport numpy as np @@ -279,6 +280,7 @@ cdef class Problem: cdef public Index __m cdef public object __exception + cdef public object __n_callback_args cdef Bool __in_ipopt_solve def __init__(self, n, m, problem_obj=None, lb=None, ub=None, cl=None, @@ -430,6 +432,11 @@ cdef class Problem: raise RuntimeError(msg) SetIntermediateCallback(self.__nlp, intermediate_cb) + if self.__intermediate is None: + self.__n_callback_args = None + else: + cb_signature = inspect.signature(self.__intermediate) + self.__n_callback_args = len(cb_signature.parameters) if self.__hessian is None: msg = b"Hessian callback not given, using approximation" @@ -1122,18 +1129,33 @@ cdef Bool intermediate_cb(Index alg_mod, if not self.__intermediate: return True - ret_val = self.__intermediate(alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials - ) + if self.__n_callback_args == 12: + ret_val = self.__intermediate(alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + self + ) + else: + ret_val = self.__intermediate(alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials + ) if ret_val is None: return True diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index a7e38f23..ef019041 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -191,6 +191,87 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", +) +def test_get_iterate_hs071_12arg_callback( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + # + # Define a callback that uses some "global" information to call + # get_current_iterate and store the result + # + x_iterates = [] + iter_counts = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + problem, + ): + iterate = problem.get_current_iterate(scaled=False) + x_iterates.append(iterate["x"]) + + # Hack so we may get the number of iterations after the solve + iter_counts.append(iter_count) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + # Disable bound push to make testing easier + nlp.add_option("bound_push", 1e-9) + x, info = nlp.solve(x0) + + # Assert correct solution + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + # + # Assert some very basic information about the collected primal iterates + # + iter_count = iter_counts[-1] + assert len(x_iterates) == (1 + iter_count) + + # These could be different due to bound_push (and scaling) + np.testing.assert_allclose(x_iterates[0], x0) + + # These could be different due to honor_original_bounds (and scaling) + np.testing.assert_allclose(x_iterates[-1], x) + + @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", From ded0efc179224408c8a320fe338c242b499cb298 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 22:44:59 +0000 Subject: [PATCH 048/170] Use oldest-supported-numpy in pyproject.toml As per https://numpy.org/devdocs/dev/depending_on_numpy.html#build-time-dependency --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 15b65b43..c8e60ea0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,3 +1,3 @@ [build-system] -requires = ["cython >= 0.26", "numpy >= 1.15", "setuptools>=39.0"] +requires = ["cython >= 0.26", "oldest-supported-numpy", "setuptools>=39.0"] build-backend = "setuptools.build_meta" From 23bc8db94caf087e107f870c293877d8850e0b15 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 23:15:54 +0000 Subject: [PATCH 049/170] Script for building manylinux wheels --- build_many_linux_wheels.sh | 45 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 build_many_linux_wheels.sh diff --git a/build_many_linux_wheels.sh b/build_many_linux_wheels.sh new file mode 100644 index 00000000..eab2c17d --- /dev/null +++ b/build_many_linux_wheels.sh @@ -0,0 +1,45 @@ +#!/bin/bash +# Builds manylinux cyipopt wheels with Ipopt 3.14.11 based on MUMPS 3.0.4, and OpenBLAS 0.3.15 +set -eu # Stop script if a line fails +TAG=${1} +echo "Building cyipopt with tag $TAG" + +# Install efficient BLAS & LAPACK library +yum install -y openblas-devel-0.3.15-4.el8 + +pushd /tmp + +# MUMPS (Linear solver used by Ipopt) +git clone https://github.com/coin-or-tools/ThirdParty-Mumps --depth=1 --branch releases/3.0.4 +pushd ThirdParty-Mumps +sh get.Mumps +./configure --with-lapack="-L/usr/include/openblas -lopenblas" +make +make install +popd + + +# Ipopt (The solver itself) +git clone https://github.com/coin-or/Ipopt --depth=1 --branch releases/3.14.11 +pushd Ipopt +./configure --with-lapack="-L/usr/include/openblas -lopenblas" +make +make install +popd + +# build cyipopt for many python versions +git clone https://github.com/mechmotum/cyipopt --depth=1 --branch $TAG +pushd cyipopt +mkdir dist +for PYVERSION in "cp311-cp311" "cp310-cp310" "cp39-cp39" "cp38-cp38" "pp39-pypy39_pp73" "pp38-pypy38_pp73" ; do + /opt/python/$PYVERSION/bin/pip wheel --no-deps --wheel-dir=./dist . +done +for wheel in dist/cyipopt*; do + auditwheel repair $wheel # Inject solver's shared libraries to wheel +done +for wheel in wheelhouse/*.whl; do + cp -rf $wheel /wheels/ # Copy repaired wheel to shared volume +done +popd + +popd From dd9c772d6c7cf7842cfb957f0a8883c35b68ea20 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 23:16:35 +0000 Subject: [PATCH 050/170] Rename build_many_linux_wheels.sh to build_manylinux_wheels.sh --- build_many_linux_wheels.sh => build_manylinux_wheels.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename build_many_linux_wheels.sh => build_manylinux_wheels.sh (100%) diff --git a/build_many_linux_wheels.sh b/build_manylinux_wheels.sh similarity index 100% rename from build_many_linux_wheels.sh rename to build_manylinux_wheels.sh From 8a4ad3f96fcc3e20d1dc46d04bb4f32fed043b68 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 23:17:08 +0000 Subject: [PATCH 051/170] Update README.rst --- README.rst | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/README.rst b/README.rst index 8c90b145..546bc3f3 100644 --- a/README.rst +++ b/README.rst @@ -54,6 +54,23 @@ Other `installation options`_ are present in the documentation. .. _installation options: https://github.com/mechmotum/cyipopt/blob/master/docs/source/install.rst + +Building `manylinux` wheels +=========================== + +manylinux wheels can be built for a tagged version of cyipopt via docker by running (while in the root of this repo):: + + docker run -v $(pwd):/wheels --rm --platform=linux/amd64 quay.io/pypa/manylinux_2_28_x86_64 bash /wheels/build_manylinux_wheels.sh GIT_TAG + +for linux/amd64 and:: + + docker run -v $(pwd):/wheels --rm --platform=linux/aarch64 quay.io/pypa/manylinux_2_28_aarch64 bash /wheels/build_manylinux_wheels.sh GIT_TAG + +for linux/aarch64 platforms. Built wheels appear at the folder the command was executed from. + +.. warning:: + Docker supports emulating non-native platforms to e.g. produce ARM binaries from an ARM64 host. However this can be quite slow (~1h for our case). + License ======= From 35116bfc76e585aecddbfa6cc52914556b1f8502 Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 23:42:36 +0000 Subject: [PATCH 052/170] Correct typos --- README.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.rst b/README.rst index 546bc3f3..6da2154f 100644 --- a/README.rst +++ b/README.rst @@ -58,7 +58,7 @@ Other `installation options`_ are present in the documentation. Building `manylinux` wheels =========================== -manylinux wheels can be built for a tagged version of cyipopt via docker by running (while in the root of this repo):: +manylinux wheels can be built for a tagged version (GIT_TAG below) of cyipopt via docker by running (while in the root of this repo):: docker run -v $(pwd):/wheels --rm --platform=linux/amd64 quay.io/pypa/manylinux_2_28_x86_64 bash /wheels/build_manylinux_wheels.sh GIT_TAG @@ -69,7 +69,7 @@ for linux/amd64 and:: for linux/aarch64 platforms. Built wheels appear at the folder the command was executed from. .. warning:: - Docker supports emulating non-native platforms to e.g. produce ARM binaries from an ARM64 host. However this can be quite slow (~1h for our case). + Docker supports emulating non-native platforms to e.g. produce ARM binaries from an AMD64 host. However this can be quite slow (~1h for our case). License ======= From b75a00514311e88c75387ba98c2abd25da8142cf Mon Sep 17 00:00:00 2001 From: Nikitas Rontsis Date: Tue, 21 Feb 2023 23:53:14 +0000 Subject: [PATCH 053/170] Correct typo (mumps version) --- build_manylinux_wheels.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/build_manylinux_wheels.sh b/build_manylinux_wheels.sh index eab2c17d..eecabb28 100644 --- a/build_manylinux_wheels.sh +++ b/build_manylinux_wheels.sh @@ -1,5 +1,5 @@ #!/bin/bash -# Builds manylinux cyipopt wheels with Ipopt 3.14.11 based on MUMPS 3.0.4, and OpenBLAS 0.3.15 +# Builds manylinux cyipopt wheels with Ipopt 3.14.11 based on MUMPS 5.5.1, and OpenBLAS 0.3.15 set -eu # Stop script if a line fails TAG=${1} echo "Building cyipopt with tag $TAG" From d6b4300499a0c4482c6ff819a14fb8867c8bdc0d Mon Sep 17 00:00:00 2001 From: nrontsis Date: Thu, 23 Feb 2023 10:01:44 +0000 Subject: [PATCH 054/170] Add licenses for all libraries we bundle --- build_manylinux_wheels.sh | 6 +- .../README.md | 1 + .../gfortran.txt | 81 ++++++ .../ipopt.txt | 269 ++++++++++++++++++ .../libquadmath.txt | 81 ++++++ .../mumps.txt | 57 ++++ .../openblas.txt | 38 +++ 7 files changed, 532 insertions(+), 1 deletion(-) create mode 100644 licenses_manylinux_bundled_libraries/README.md create mode 100644 licenses_manylinux_bundled_libraries/gfortran.txt create mode 100644 licenses_manylinux_bundled_libraries/ipopt.txt create mode 100644 licenses_manylinux_bundled_libraries/libquadmath.txt create mode 100644 licenses_manylinux_bundled_libraries/mumps.txt create mode 100644 licenses_manylinux_bundled_libraries/openblas.txt diff --git a/build_manylinux_wheels.sh b/build_manylinux_wheels.sh index eecabb28..e3ade524 100644 --- a/build_manylinux_wheels.sh +++ b/build_manylinux_wheels.sh @@ -30,7 +30,11 @@ popd # build cyipopt for many python versions git clone https://github.com/mechmotum/cyipopt --depth=1 --branch $TAG pushd cyipopt -mkdir dist +echo "------------------------------" >> LICENSE +echo "This binary distribution of cyipopt also bundles the following software" >> LICENSE +for bundled_license in licenses_manylinux_bundled_libraries/*.txt; do + cat $bundled_license >> LICENSE +done for PYVERSION in "cp311-cp311" "cp310-cp310" "cp39-cp39" "cp38-cp38" "pp39-pypy39_pp73" "pp38-pypy38_pp73" ; do /opt/python/$PYVERSION/bin/pip wheel --no-deps --wheel-dir=./dist . done diff --git a/licenses_manylinux_bundled_libraries/README.md b/licenses_manylinux_bundled_libraries/README.md new file mode 100644 index 00000000..3e68dc16 --- /dev/null +++ b/licenses_manylinux_bundled_libraries/README.md @@ -0,0 +1 @@ +This folder contains licenses for all the libraries that are bundled in the `manylinux` wheels of `cyipopt`. These linceses are appended to the main LICENSE when building these wheels in `build_manylinux_wheel.sh`. \ No newline at end of file diff --git a/licenses_manylinux_bundled_libraries/gfortran.txt b/licenses_manylinux_bundled_libraries/gfortran.txt new file mode 100644 index 00000000..7f286510 --- /dev/null +++ b/licenses_manylinux_bundled_libraries/gfortran.txt @@ -0,0 +1,81 @@ +############# +start of gfortran license +applicable for bundled libraries: .libs/libgfortran*.so +license text obtained from https://github.com/gcc-mirror/gcc/blob/748086b7b2201112aff2dea9d037af1fc92567ff/COPYING.RUNTIME +############# + +GCC RUNTIME LIBRARY EXCEPTION + +Version 3.1, 31 March 2009 + +Copyright (C) 2009 Free Software Foundation, Inc. + +Everyone is permitted to copy and distribute verbatim copies of this +license document, but changing it is not allowed. + +This GCC Runtime Library Exception ("Exception") is an additional +permission under section 7 of the GNU General Public License, version +3 ("GPLv3"). It applies to a given file (the "Runtime Library") that +bears a notice placed by the copyright holder of the file stating that +the file is governed by GPLv3 along with this Exception. + +When you use GCC to compile a program, GCC may combine portions of +certain GCC header files and runtime libraries with the compiled +program. The purpose of this Exception is to allow compilation of +non-GPL (including proprietary) programs to use, in this way, the +header files and runtime libraries covered by this Exception. + +0. Definitions. + +A file is an "Independent Module" if it either requires the Runtime +Library for execution after a Compilation Process, or makes use of an +interface provided by the Runtime Library, but is not otherwise based +on the Runtime Library. + +"GCC" means a version of the GNU Compiler Collection, with or without +modifications, governed by version 3 (or a specified later version) of +the GNU General Public License (GPL) with the option of using any +subsequent versions published by the FSF. + +"GPL-compatible Software" is software whose conditions of propagation, +modification and use would permit combination with GCC in accord with +the license of GCC. + +"Target Code" refers to output from any compiler for a real or virtual +target processor architecture, in executable form or suitable for +input to an assembler, loader, linker and/or execution +phase. Notwithstanding that, Target Code does not include data in any +format that is used as a compiler intermediate representation, or used +for producing a compiler intermediate representation. + +The "Compilation Process" transforms code entirely represented in +non-intermediate languages designed for human-written code, and/or in +Java Virtual Machine byte code, into Target Code. Thus, for example, +use of source code generators and preprocessors need not be considered +part of the Compilation Process, since the Compilation Process can be +understood as starting with the output of the generators or +preprocessors. + +A Compilation Process is "Eligible" if it is done using GCC, alone or +with other GPL-compatible software, or if it is done without using any +work based on GCC. For example, using non-GPL-compatible Software to +optimize any GCC intermediate representations would not qualify as an +Eligible Compilation Process. + +1. Grant of Additional Permission. + +You have permission to propagate a work of Target Code formed by +combining the Runtime Library with Independent Modules, even if such +propagation would otherwise violate the terms of GPLv3, provided that +all Target Code was generated by Eligible Compilation Processes. You +may then convey such a combination under terms of your choice, +consistent with the licensing of the Independent Modules. + +2. No Weakening of GCC Copyleft. + +The availability of this Exception does not imply any general +presumption that third-party software is unaffected by the copyleft +requirements of the license of GCC. + +############# +end of gfortran license \ No newline at end of file diff --git a/licenses_manylinux_bundled_libraries/ipopt.txt b/licenses_manylinux_bundled_libraries/ipopt.txt new file mode 100644 index 00000000..e28c4f50 --- /dev/null +++ b/licenses_manylinux_bundled_libraries/ipopt.txt @@ -0,0 +1,269 @@ +############# +start of Ipopt license +applicable for bundled libraries: .libs/libipopt*.so +license text obtained from https://github.com/coin-or/Ipopt/blob/332132a4ab18e53153d85fd637880babf1d7ff03/LICENSE +############# + +Eclipse Public License - v 2.0 + + THE ACCOMPANYING PROGRAM IS PROVIDED UNDER THE TERMS OF THIS ECLIPSE + PUBLIC LICENSE ("AGREEMENT"). ANY USE, REPRODUCTION OR DISTRIBUTION + OF THE PROGRAM CONSTITUTES RECIPIENT'S ACCEPTANCE OF THIS AGREEMENT. + +1. 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The Program (including Contributions) may always be +Distributed subject to the version of the Agreement under which it was +received. In addition, after a new version of the Agreement is published, +Contributor may elect to Distribute the Program (including its +Contributions) under the new version. + +Except as expressly stated in Sections 2(a) and 2(b) above, Recipient +receives no rights or licenses to the intellectual property of any +Contributor under this Agreement, whether expressly, by implication, +estoppel or otherwise. All rights in the Program not expressly granted +under this Agreement are reserved. Nothing in this Agreement is intended +to be enforceable by any entity that is not a Contributor or Recipient. +No third-party beneficiary rights are created under this Agreement. + +############# +end of Ipopt license \ No newline at end of file diff --git a/licenses_manylinux_bundled_libraries/libquadmath.txt b/licenses_manylinux_bundled_libraries/libquadmath.txt new file mode 100644 index 00000000..eec3f7a6 --- /dev/null +++ b/licenses_manylinux_bundled_libraries/libquadmath.txt @@ -0,0 +1,81 @@ +############# +start of libquadmath license +applicable for bundled libraries: .libs/libquadmath*.so +license text obtained from https://github.com/gcc-mirror/gcc/blob/748086b7b2201112aff2dea9d037af1fc92567ff/COPYING.RUNTIME +############# + +GCC RUNTIME LIBRARY EXCEPTION + +Version 3.1, 31 March 2009 + +Copyright (C) 2009 Free Software Foundation, Inc. + +Everyone is permitted to copy and distribute verbatim copies of this +license document, but changing it is not allowed. + +This GCC Runtime Library Exception ("Exception") is an additional +permission under section 7 of the GNU General Public License, version +3 ("GPLv3"). It applies to a given file (the "Runtime Library") that +bears a notice placed by the copyright holder of the file stating that +the file is governed by GPLv3 along with this Exception. + +When you use GCC to compile a program, GCC may combine portions of +certain GCC header files and runtime libraries with the compiled +program. The purpose of this Exception is to allow compilation of +non-GPL (including proprietary) programs to use, in this way, the +header files and runtime libraries covered by this Exception. + +0. Definitions. + +A file is an "Independent Module" if it either requires the Runtime +Library for execution after a Compilation Process, or makes use of an +interface provided by the Runtime Library, but is not otherwise based +on the Runtime Library. + +"GCC" means a version of the GNU Compiler Collection, with or without +modifications, governed by version 3 (or a specified later version) of +the GNU General Public License (GPL) with the option of using any +subsequent versions published by the FSF. + +"GPL-compatible Software" is software whose conditions of propagation, +modification and use would permit combination with GCC in accord with +the license of GCC. + +"Target Code" refers to output from any compiler for a real or virtual +target processor architecture, in executable form or suitable for +input to an assembler, loader, linker and/or execution +phase. Notwithstanding that, Target Code does not include data in any +format that is used as a compiler intermediate representation, or used +for producing a compiler intermediate representation. + +The "Compilation Process" transforms code entirely represented in +non-intermediate languages designed for human-written code, and/or in +Java Virtual Machine byte code, into Target Code. Thus, for example, +use of source code generators and preprocessors need not be considered +part of the Compilation Process, since the Compilation Process can be +understood as starting with the output of the generators or +preprocessors. + +A Compilation Process is "Eligible" if it is done using GCC, alone or +with other GPL-compatible software, or if it is done without using any +work based on GCC. For example, using non-GPL-compatible Software to +optimize any GCC intermediate representations would not qualify as an +Eligible Compilation Process. + +1. Grant of Additional Permission. + +You have permission to propagate a work of Target Code formed by +combining the Runtime Library with Independent Modules, even if such +propagation would otherwise violate the terms of GPLv3, provided that +all Target Code was generated by Eligible Compilation Processes. You +may then convey such a combination under terms of your choice, +consistent with the licensing of the Independent Modules. + +2. No Weakening of GCC Copyleft. + +The availability of this Exception does not imply any general +presumption that third-party software is unaffected by the copyleft +requirements of the license of GCC. + +############# +end of libquadmath license \ No newline at end of file diff --git a/licenses_manylinux_bundled_libraries/mumps.txt b/licenses_manylinux_bundled_libraries/mumps.txt new file mode 100644 index 00000000..768e5e78 --- /dev/null +++ b/licenses_manylinux_bundled_libraries/mumps.txt @@ -0,0 +1,57 @@ +############# +start of MUMPS license +applicable for bundled libraries: .libs/libcoinmumps*.so +license text obtained from file LICENSE of http://coin-or-tools.github.io/ThirdParty-Mumps/MUMPS_5.5.1.tar.gz +############# + + Copyright 1991-2022 CERFACS, CNRS, ENS Lyon, INP Toulouse, Inria, + Mumps Technologies, University of Bordeaux. + + This version of MUMPS is provided to you free of charge. It is + released under the CeCILL-C license + (see doc/CeCILL-C_V1-en.txt, doc/CeCILL-C_V1-fr.txt, and + https://cecill.info/licences/Licence_CeCILL-C_V1-en.html), + except for variants of AMD ordering and xMUMPS_TRUNCATED_RRQR + derived from the LAPACK package distributed under BSD 3-clause + license (see headers of ana_orderings.F and lr_core.F), + and except for the external and optional ordering PORD provided + in a separate directory PORD (see PORD/README for License information). + + You can acknowledge (using references [1] and [2]) the contribution + of this package in any scientific publication dependent upon the use + of the package. Please use reasonable endeavours to notify the authors + of the package of this publication. + + [1] P. R. Amestoy, I. S. Duff, J. Koster and J.-Y. L'Excellent, + A fully asynchronous multifrontal solver using distributed dynamic + scheduling, SIAM Journal on Matrix Analysis and Applications, + Vol 23, No 1, pp 15-41 (2001). + + [2] P. R. Amestoy, A. Buttari, J.-Y. L'Excellent and T. Mary, + Performance and scalability of the block low-rank multifrontal + factorization on multicore architectures, + ACM Transactions on Mathematical Software, + Vol 45, Issue 1, pp 2:1-2:26 (2019) + + As a counterpart to the access to the source code and rights to copy, + modify and redistribute granted by the license, users are provided only + with a limited warranty and the software's author, the holder of the + economic rights, and the successive licensors have only limited + liability. + + In this respect, the user's attention is drawn to the risks associated + with loading, using, modifying and/or developing or reproducing the + software by the user in light of its specific status of free software, + that may mean that it is complicated to manipulate, and that also + therefore means that it is reserved for developers and experienced + professionals having in-depth computer knowledge. Users are therefore + encouraged to load and test the software's suitability as regards their + requirements in conditions enabling the security of their systems + and/or data to be ensured and, more generally, to use and operate it + in the same conditions as regards security. + + The fact that you are presently reading this means that you have had + knowledge of the CeCILL-C license and that you accept its terms. + +############# +end of MUMPS license \ No newline at end of file diff --git a/licenses_manylinux_bundled_libraries/openblas.txt b/licenses_manylinux_bundled_libraries/openblas.txt new file mode 100644 index 00000000..3a6ff49c --- /dev/null +++ b/licenses_manylinux_bundled_libraries/openblas.txt @@ -0,0 +1,38 @@ +############# +start of OpenBLAS license +applicable for bundled libraries: .libs/libopenblas*.so +license text obtained from https://github.com/xianyi/OpenBLAS/blob/2fb02626dacae6a3d85af15ada74415691f6205b/LICENSE +############# + +Copyright (c) 2011-2014, The OpenBLAS Project +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in + the documentation and/or other materials provided with the + distribution. + 3. Neither the name of the OpenBLAS project nor the names of + its contributors may be used to endorse or promote products + derived from this software without specific prior written + permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE +USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +############# +end of OpenBLAS license \ No newline at end of file From a579ca7c3f51f464309559082f0c9266bd2b2e4d Mon Sep 17 00:00:00 2001 From: nrontsis Date: Thu, 23 Feb 2023 10:02:21 +0000 Subject: [PATCH 055/170] Rephrase --- licenses_manylinux_bundled_libraries/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/licenses_manylinux_bundled_libraries/README.md b/licenses_manylinux_bundled_libraries/README.md index 3e68dc16..68832085 100644 --- a/licenses_manylinux_bundled_libraries/README.md +++ b/licenses_manylinux_bundled_libraries/README.md @@ -1 +1 @@ -This folder contains licenses for all the libraries that are bundled in the `manylinux` wheels of `cyipopt`. These linceses are appended to the main LICENSE when building these wheels in `build_manylinux_wheel.sh`. \ No newline at end of file +This folder contains licenses for all the libraries that are bundled in the `manylinux` wheels of `cyipopt`. These linceses are appended to `cyipopt`'s `LICENSE` file when building these wheels in `build_manylinux_wheel.sh`. \ No newline at end of file From 55d833d4d0a3240b099c84f3449b705c07986a86 Mon Sep 17 00:00:00 2001 From: robbybp Date: Sun, 26 Feb 2023 20:25:22 -0700 Subject: [PATCH 056/170] update get_current_violations test to not rely on special attribute of problem_definition --- cyipopt/tests/unit/test_ipopt_funcs.py | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index ef019041..95779088 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -276,7 +276,7 @@ def intermediate( pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", ) -def test_get_violations_hs071( +def test_get_violations_hs071_12arg_callback( hs071_initial_guess_fixture, hs071_definition_instance_fixture, hs071_variable_lower_bounds_fixture, @@ -296,6 +296,7 @@ def test_get_violations_hs071( pr_violations = [] du_violations = [] + iter_counts = [] def intermediate( alg_mod, iter_count, @@ -308,14 +309,16 @@ def intermediate( alpha_du, alpha_pr, ls_trials, + problem, ): - violations = problem_definition.nlp.get_current_violations(scaled=True) + violations = problem.get_current_violations(scaled=True) pr_violations.append(violations["g_violation"]) du_violations.append(violations["grad_lag_x"]) # Hack so we may get the number of iterations after the solve - problem_definition.iter_count = iter_count + iter_counts.append(iter_count) + # Override the default callback with our locally defined callback. problem_definition.intermediate = intermediate nlp = cyipopt.Problem( n=n, @@ -326,7 +329,6 @@ def intermediate( cl=cl, cu=cu, ) - problem_definition.nlp = nlp nlp.add_option("tol", 1e-8) # Note that Ipopt appears to check tolerance in the scaled, bound-relaxed @@ -343,8 +345,9 @@ def intermediate( # # Assert some very basic information about the collected violations # - assert len(pr_violations) == (1 + problem_definition.iter_count) - assert len(du_violations) == (1 + problem_definition.iter_count) + iter_count = iter_counts[-1] + assert len(pr_violations) == (1 + iter_count) + assert len(du_violations) == (1 + iter_count) np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-8) np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) From f502ceeda1ae207da885d5a44b1301c4e930cd4a Mon Sep 17 00:00:00 2001 From: robbybp Date: Sun, 26 Feb 2023 20:57:36 -0700 Subject: [PATCH 057/170] add test using subclass of Problem --- cyipopt/tests/unit/test_ipopt_funcs.py | 98 ++++++++++++++++++++++++++ 1 file changed, 98 insertions(+) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 95779088..b3ca4620 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -272,6 +272,104 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", +) +def test_get_iterate_hs071_subclass_Problem( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + problem_definition = hs071_definition_instance_fixture + + x_iterates = [] + class MyProblem(cyipopt.Problem): + + def objective(self, x): + return problem_definition.objective(x) + + def gradient(self, x): + return problem_definition.gradient(x) + + def constraints(self, x): + return problem_definition.constraints(x) + + def jacobian(self, x): + return problem_definition.jacobian(x) + + def jacobian_structure(self, x): + return problem_definition.jacobian_structure(x) + + def hessian(self, x, lagrange, obj_factor): + return problem_definition.hessian(x, lagrange, obj_factor) + + def hessian_structure(self, x): + return problem_definition.hessian_structure(x) + + def intermediate( + self, + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + # By subclassing Problem, we can call get_current_iterate + # without any "global" information, even with the backward- + # compatible 11-argument intermediate callback. + iterate = self.get_current_iterate(scaled=False) + x_iterates.append(iterate["x"]) + + # Hack so we may get the number of iterations after the solve + self.iter_count = iter_count + + nlp = MyProblem( + n=n, + m=m, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + # Disable bound push to make testing easier + nlp.add_option("bound_push", 1e-9) + x, info = nlp.solve(x0) + + # Assert correct solution + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + # + # Assert some very basic information about the collected primal iterates + # + assert len(x_iterates) == (1 + nlp.iter_count) + + # These could be different due to bound_push (and scaling) + np.testing.assert_allclose(x_iterates[0], x0) + + # These could be different due to honor_original_bounds (and scaling) + np.testing.assert_allclose(x_iterates[-1], x) + + @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", From 02aa4390b33d46cc5e7676b860ad96daa620a0f0 Mon Sep 17 00:00:00 2001 From: "Benjamin A. Beasley" Date: Wed, 8 Mar 2023 09:22:27 -0500 Subject: [PATCH 058/170] =?UTF-8?q?Don=E2=80=99t=20use=20deprecated/remove?= =?UTF-8?q?d=20np.float=20alias?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit In examples/lasso.py, change np.float (which was deprecated in numpy 1.20 and removed in numpy 1.24) to np.float64. --- examples/lasso.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/lasso.py b/examples/lasso.py index 995bc1de..e1ffa31d 100644 --- a/examples/lasso.py +++ b/examples/lasso.py @@ -142,7 +142,7 @@ def hessian(self, x, lagrange, obj_factor): # n = 100 e = 1 - beta = np.array((0, 0, 2, -4, 0, 0, -1, 3), dtype=np.float).reshape((-1, 1)) + beta = np.array((0, 0, 2, -4, 0, 0, -1, 3), dtype=np.float64).reshape((-1, 1)) # # Set the random number generator seed. From ad973f5036c0134c649197be0458c8014fd1a1c3 Mon Sep 17 00:00:00 2001 From: robbybp Date: Thu, 16 Mar 2023 21:36:20 -0600 Subject: [PATCH 059/170] document optional problem argument in intermediate callback --- cyipopt/cython/ipopt_wrapper.pyx | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index e87811c7..cb4ec722 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -248,6 +248,12 @@ cdef class Problem: The stepsize for the primal variables. ``ls_trials``: The number of backtracking line search steps. + ``problem`` (optional): + The ``Problem`` object itself. This argument can be used + to call the ``get_current_iterate`` and + ``get_current_violations`` methods from a callback that + is not a method on this class. This argument is optional + for backwards compatibility. more information can be found in the following link: https://coin-or.github.io/Ipopt/OUTPUT.html From 7e5923f53e2c0f5fd9f5bbb0fc9296087301eeb9 Mon Sep 17 00:00:00 2001 From: robbybp Date: Thu, 16 Mar 2023 22:55:40 -0600 Subject: [PATCH 060/170] raise error if intermediate call signature is not something we expect --- cyipopt/cython/ipopt_wrapper.pyx | 36 +++++++++++++++++- cyipopt/tests/unit/test_ipopt_funcs.py | 51 ++++++++++++++++++++++++++ 2 files changed, 86 insertions(+), 1 deletion(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index cb4ec722..abf7a418 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -442,7 +442,41 @@ cdef class Problem: self.__n_callback_args = None else: cb_signature = inspect.signature(self.__intermediate) - self.__n_callback_args = len(cb_signature.parameters) + pos_args = [ + param for param in cb_signature.parameters.values() + if param.kind in { + inspect.Parameter.POSITIONAL_ONLY, + inspect.Parameter.POSITIONAL_OR_KEYWORD, + } + ] + var_args = [ + param for param in cb_signature.parameters.values() + if param.kind == inspect.Parameter.VAR_POSITIONAL + ] + kwd_args = [ + param for param in cb_signature.parameters.values() + if param.kind == inspect.Parameter.VAR_KEYWORD + ] + if kwd_args: + kwd_names = [param.name for param in kwd_args] + raise RuntimeError( + "Keyword arguments are not allowed in the intermediate" + " callback function. Got keyword arguments %s" + % (kwd_args,) + ) + if var_args: + # If a catchall *args argument is specified in the callback, + # send all 12 possible callback arguments. + self.__n_callback_args = 12 + else: + self.__n_callback_args = len(pos_args) + if self.__n_callback_args not in {11, 12}: + raise RuntimeError( + "Invalid intermediate callback call signature. This" + " callback must accept either 11 or 12 positional" + " arguments or a variable number of positional" + " arguments." + ) if self.__hessian is None: msg = b"Hessian callback not given, using approximation" diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index b3ca4620..4047d341 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -191,6 +191,57 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) +def test_hs071_bad_intermediate_callback( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + obj_values = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + problem, + extra_arg, + ): + obj_values.append(obj_value) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + msg = "Invalid intermediate callback call signature" + with pytest.raises(RuntimeError, match=msg): + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", From 8573c6782b80d1cd8328348733f25f64d798c44e Mon Sep 17 00:00:00 2001 From: robbybp Date: Fri, 17 Mar 2023 10:13:01 -0600 Subject: [PATCH 061/170] add test callback with variable number of arguments --- cyipopt/tests/unit/test_ipopt_funcs.py | 71 ++++++++++++++++++++++++++ 1 file changed, 71 insertions(+) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 4047d341..b4b92ad5 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -323,6 +323,77 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) +@pytest.mark.skipif( + pre_3_14_0, + reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", +) +def test_get_iterate_hs071_vararg_callback( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + # This test makes sure we pass the correct information to the user's + # callback even when using a callback with variable number of arguments, + # i.e. using *args. + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + # + # Define a callback that uses some "global" information to call + # get_current_iterate and store the result + # + x_iterates = [] + iter_counts = [] + def intermediate(*args): + iterate = args[11].get_current_iterate(scaled=False) + x_iterates.append(iterate["x"]) + + # Hack so we may get the number of iterations after the solve + iter_counts.append(args[1]) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + # Disable bound push to make testing easier + nlp.add_option("bound_push", 1e-9) + x, info = nlp.solve(x0) + + # Assert correct solution + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + np.testing.assert_allclose(x, expected_x) + + # + # Assert some very basic information about the collected primal iterates + # + iter_count = iter_counts[-1] + assert len(x_iterates) == (1 + iter_count) + + # These could be different due to bound_push (and scaling) + np.testing.assert_allclose(x_iterates[0], x0) + + # These could be different due to honor_original_bounds (and scaling) + np.testing.assert_allclose(x_iterates[-1], x) + + @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", From c1f1b636d4f8db3a73d7ec4be2fac1fb5404085f Mon Sep 17 00:00:00 2001 From: robbybp Date: Fri, 17 Mar 2023 10:39:59 -0600 Subject: [PATCH 062/170] clarify logic and change name of flag when deciding which callback to use --- cyipopt/cython/ipopt_wrapper.pyx | 46 ++++++++++++++++++++------------ 1 file changed, 29 insertions(+), 17 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index abf7a418..2722ed9e 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -286,7 +286,7 @@ cdef class Problem: cdef public Index __m cdef public object __exception - cdef public object __n_callback_args + cdef public object __send_self_to_intermediate cdef Bool __in_ipopt_solve def __init__(self, n, m, problem_obj=None, lb=None, ub=None, cl=None, @@ -439,8 +439,10 @@ cdef class Problem: SetIntermediateCallback(self.__nlp, intermediate_cb) if self.__intermediate is None: - self.__n_callback_args = None + self.__send_self_to_intermediate = None else: + # A callback was provided. We need to know whether to send this + # callback 11 arguments or 12 arguments. cb_signature = inspect.signature(self.__intermediate) pos_args = [ param for param in cb_signature.parameters.values() @@ -458,25 +460,35 @@ cdef class Problem: if param.kind == inspect.Parameter.VAR_KEYWORD ] if kwd_args: - kwd_names = [param.name for param in kwd_args] + # **kwds is not allowed in the intermediate callback raise RuntimeError( - "Keyword arguments are not allowed in the intermediate" - " callback function. Got keyword arguments %s" - % (kwd_args,) + "Variable keyword arguments are not allowed in the" + " intermediate callback function." ) - if var_args: + elif var_args: + # Even if *args is provided, having more than 12 positional + # arguments is an error. + if len(pos_args) > 12: + raise RuntimeError( + "More than 12 positional arguments were specified in" + " the intermediate callback." + ) # If a catchall *args argument is specified in the callback, # send all 12 possible callback arguments. - self.__n_callback_args = 12 + self.__send_self_to_intermediate = True + elif len(pos_args) == 11: + # If the callback takes 11 arguments, do not send self + self.__send_self_to_intermediate = False + elif len(pos_args) == 12: + # If the callback takes 12 arguments, do send self + self.__send_self_to_intermediate = True else: - self.__n_callback_args = len(pos_args) - if self.__n_callback_args not in {11, 12}: - raise RuntimeError( - "Invalid intermediate callback call signature. This" - " callback must accept either 11 or 12 positional" - " arguments or a variable number of positional" - " arguments." - ) + raise RuntimeError( + "Invalid intermediate callback call signature. This" + " callback must accept either 11 or 12 positional" + " arguments or a variable number of positional" + " arguments." + ) if self.__hessian is None: msg = b"Hessian callback not given, using approximation" @@ -1169,7 +1181,7 @@ cdef Bool intermediate_cb(Index alg_mod, if not self.__intermediate: return True - if self.__n_callback_args == 12: + if self.__send_self_to_intermediate: ret_val = self.__intermediate(alg_mod, iter_count, obj_value, From f93733a330909f430c2327e718d2dec96c1720ca Mon Sep 17 00:00:00 2001 From: robbybp Date: Fri, 17 Mar 2023 10:51:06 -0600 Subject: [PATCH 063/170] add tests for exceptions with different invalid intermediate call signatures --- cyipopt/tests/unit/test_exceptions.py | 153 +++++++++++++++++++++++++ cyipopt/tests/unit/test_ipopt_funcs.py | 51 --------- 2 files changed, 153 insertions(+), 51 deletions(-) diff --git a/cyipopt/tests/unit/test_exceptions.py b/cyipopt/tests/unit/test_exceptions.py index e69de29b..96bf31ae 100644 --- a/cyipopt/tests/unit/test_exceptions.py +++ b/cyipopt/tests/unit/test_exceptions.py @@ -0,0 +1,153 @@ +import pytest +import cyipopt + + +def test_hs071_extra_arg_intermediate_with_varargs( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + obj_values = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + problem, + extra_arg, + *args, + ): + obj_values.append(obj_value) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + msg = "More than 12 positional arguments" + with pytest.raises(RuntimeError, match=msg): + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + +def test_hs071_toofew_arg_intermediate( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + obj_values = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ): + obj_values.append(obj_value) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + msg = "Invalid intermediate callback call signature" + with pytest.raises(RuntimeError, match=msg): + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + +def test_hs071_intermediate_with_kwds( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) + + obj_values = [] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + problem, + **kwds, + ): + obj_values.append(obj_value) + + problem_definition = hs071_definition_instance_fixture + # Replace "intermediate" attribute with our callback + problem_definition.intermediate = intermediate + + msg = "Variable keyword arguments are not allowed" + with pytest.raises(RuntimeError, match=msg): + nlp = cyipopt.Problem( + n=n, + m=m, + problem_obj=problem_definition, + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index b4b92ad5..b621f9dc 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -191,57 +191,6 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) -def test_hs071_bad_intermediate_callback( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - obj_values = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - problem, - extra_arg, - ): - obj_values.append(obj_value) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - msg = "Invalid intermediate callback call signature" - with pytest.raises(RuntimeError, match=msg): - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) - - @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", From a0c46e9ce5e7a52f893c3e993e3440489018a1f3 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 2 Apr 2023 18:45:01 -0700 Subject: [PATCH 064/170] DOC: minimize_ipopt: add documentation --- cyipopt/scipy_interface.py | 76 +++++++++++++++++++++++++++++++++++--- docs/source/conf.py | 9 +++++ 2 files changed, 80 insertions(+), 5 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 75521d63..11a77de9 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -324,11 +324,77 @@ def minimize_ipopt(fun, callback=None, options=None): """ - Minimize a function using ipopt. The call signature is exactly like for - ``scipy.optimize.mimize``. In options, all options are directly passed to - ipopt. Check [http://www.coin-or.org/Ipopt/documentation/node39.html] for - details. The options ``disp`` and ``maxiter`` are automatically mapped to - their ipopt-equivalents ``print_level`` and ``max_iter``. + Minimization using Ipopt with an interface like `scipy.optimize.minimize`. + + This function can be used to solve general nonlinear programming problems + of the form: + + .. math:: + + \min_ {x \in R^n} f(x) + + subject to + + .. math:: + + g_L \leq g(x) \leq g_U + + x_L \leq x \leq x_U + + Where :math:`x` are the optimization variables, :math:`f(x)` is the + objective function, :math:`g(x)` are the general nonlinear constraints, + and :math:`x_L` and :math:`x_U` are the upper and lower bounds + (respectively) on the decision variables. The constraints, :math:`g(x)`, + have lower and upper bounds :math:`g_L` and :math:`g_U`. Note that equality + constraints can be specified by setting :math:`g^i_L = g^i_U`. + + Parameters + ---------- + fun : callable + The objective function to be minimized: ``fun(x, *args, **kwargs) -> + float``. + x0 : array-like, shape(n, ) + Initial guess. Array of real elements of shape (n,), + where ``n`` is the number of independent variables. + args : tuple, optional + Extra arguments passed to the objective function and its + derivatives (``fun``, ``jac``, and ``hess``). + kwargs : dictionary, optional + Extra keyword arguments passed to the objective function and its + derivatives (``fun``, ``jac``, ``hess``). + method : str, optional + This parameter is ignored. `minimize_ipopt` always uses Ipopt; use + `scipy.optimize.minimize` directly for other methods. + jac : callable, optional + The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> + ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. + hess : callable, optional + If ``None``, the Hessian is computed using IPOPT's numerical methods. + Explicitly defined Hessians are not yet supported via this interface. + hessp : callable, optional + If ``None``, the Hessian is computed using IPOPT's numerical methods. + Explicitly defined Hessians are not yet supported via this interface. + bounds : sequence, shape(n, ), optional + Sequence of ``(min, max)`` pairs for each element in `x`. Use ``None`` + to specify no bound. + constraints : {Constraint, dict}, optional + See `scipy.optimize.minimize` for more information. Note that the + Jacobian of each constraint corresponds to the ``'jac'`` key and must + be a callable function with signature + ``jac(x) -> {ndarray, coo_array}``. If the constraint's + value of ``'jac'`` is ``True``, the constraint function ``fun`` must + return a tuple ``(con_val, con_jac)`` consisting of the evaluated + constraint ``con_val`` and the evaluated Jacobian ``con_jac``. + tol : float, optional (default=1e-8) + The desired relative convergence tolerance, passed as an option to + Ipopt. See [https://coin-or.github.io/Ipopt/OPTIONS.html] for details. + options : dict, optional + A dictionary of solver options. The options ``disp`` and ``maxiter`` + are automatically mapped to their Ipopt equivalents ``print_level`` + and ``max_iter``. All other options are passed directly to Ipopt. See + [https://coin-or.github.io/Ipopt/OPTIONS.html] for details. + callback : callable, optional + This parameter is ignored. """ if not SCIPY_INSTALLED: msg = 'Install SciPy to use the `minimize_ipopt` function.' diff --git a/docs/source/conf.py b/docs/source/conf.py index f3a2457f..08a9385d 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -36,6 +36,7 @@ 'sphinx.ext.napoleon', 'sphinx.ext.todo', 'sphinx.ext.viewcode', + 'sphinx.ext.intersphinx' ] # Add any paths that contain templates here, relative to this directory. @@ -255,3 +256,11 @@ # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' + +# ----------------------------------------------------------------------------- +# Intersphinx configuration +# ----------------------------------------------------------------------------- +intersphinx_mapping = { + 'python': ('https://docs.python.org/dev', None), + 'scipy': ('https://docs.scipy.org/doc/scipy/reference', None), +} From 596aeb39f4ba584a30824f5a258a1b863d3b6eaf Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Wed, 5 Apr 2023 17:32:03 -0700 Subject: [PATCH 065/170] DOC: minimize_ipopt: add reference, example --- cyipopt/scipy_interface.py | 62 ++++++++++++++++++++++++++++++++++---- 1 file changed, 56 insertions(+), 6 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 11a77de9..66b23dbb 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -341,7 +341,7 @@ def minimize_ipopt(fun, x_L \leq x \leq x_U - Where :math:`x` are the optimization variables, :math:`f(x)` is the + where :math:`x` are the optimization variables, :math:`f(x)` is the objective function, :math:`g(x)` are the general nonlinear constraints, and :math:`x_L` and :math:`x_U` are the upper and lower bounds (respectively) on the decision variables. The constraints, :math:`g(x)`, @@ -369,11 +369,12 @@ def minimize_ipopt(fun, The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. hess : callable, optional + The Hessian of the objective function: + ``hess(x) -> ndarray, shape(n, )``. If ``None``, the Hessian is computed using IPOPT's numerical methods. - Explicitly defined Hessians are not yet supported via this interface. hessp : callable, optional - If ``None``, the Hessian is computed using IPOPT's numerical methods. - Explicitly defined Hessians are not yet supported via this interface. + This parameter is currently unused. An error will be raised if a value + other than ``None`` is provided. bounds : sequence, shape(n, ), optional Sequence of ``(min, max)`` pairs for each element in `x`. Use ``None`` to specify no bound. @@ -387,14 +388,63 @@ def minimize_ipopt(fun, constraint ``con_val`` and the evaluated Jacobian ``con_jac``. tol : float, optional (default=1e-8) The desired relative convergence tolerance, passed as an option to - Ipopt. See [https://coin-or.github.io/Ipopt/OPTIONS.html] for details. + Ipopt. See [1]_ for details. options : dict, optional A dictionary of solver options. The options ``disp`` and ``maxiter`` are automatically mapped to their Ipopt equivalents ``print_level`` and ``max_iter``. All other options are passed directly to Ipopt. See - [https://coin-or.github.io/Ipopt/OPTIONS.html] for details. + [1]_ for details. callback : callable, optional This parameter is ignored. + + References + ---------- + .. [1] COIN-OR Project. "Ipopt: Ipopt Options". + https://coin-or.github.io/Ipopt/OPTIONS.html + + Examples + -------- + Consider the problem of minimizing the Rosenbrock function. The Rosenbrock + function and its derivatives are implemented in `scipy.optimize.rosen`, + `scipy.optimize.rosen_der`, and `scipy.optimize.rosen_hess`. + + >>> from cyipopt import minimize_ipopt + >>> from scipy.optimize import rosen, rosen_der + >>> x0 = [1.3, 0.7, 0.8, 1.9, 1.2] # initial guess + + If we provide the objective function but no derivatives, Ipopt finds the + correct minimizer (``[1, 1, 1, 1, 1]``) with a minimum objective value of + 0. However, it does not report success, and it requires many iterations + and function evaluations before termination. This is because SciPy's + ``approx_fprime`` requires many objective function evaluations to + approximate the gradient, and still the approximation is not very accurate, + delaying convergence. + + >>> res = minimize_ipopt(rosen, x0, jac=rosen_der) + >>> res.success + False + >>> res.x + array([1., 1., 1., 1., 1.]) + >>> res.nit, res.nfev, res.njev + (46, 528, 48) + + To improve performance, provide the gradient using the `jac` keyword. + In this case, Ipopt recognizes its own success, and requires fewer function + evaluations to do so. + + >>> res = minimize_ipopt(rosen, x0, jac=rosen_der) + >>> res.success + True + >>> res.nit, res.nfev, res.njev + (37, 200, 39) + + For best results, provide the Hessian, too. + + >>> res = minimize_ipopt(rosen, x0, jac=rosen_der, hess=rosen_hess) + >>> res.success + True + >>> res.nit, res.nfev, res.njev + (17, 29, 19) """ if not SCIPY_INSTALLED: msg = 'Install SciPy to use the `minimize_ipopt` function.' From a55e0bba71bb975781b96e4691d10c824391ec14 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Thu, 6 Apr 2023 07:05:02 +0200 Subject: [PATCH 066/170] args & kwargs work with all user funcs in minimize_ipopt - Passed in args and kwargs to all IpoptProblemWrapper. - Added a unit test with args and kwargs for all funcs. --- cyipopt/scipy_interface.py | 45 +++++++++++++++-------- cyipopt/tests/unit/test_scipy_optional.py | 34 +++++++++++++++++ 2 files changed, 63 insertions(+), 16 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 75521d63..6c5a7176 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -171,14 +171,17 @@ def objective(self, x): self.nfev += 1 return self.fun(x, *self.args, **self.kwargs) + # TODO : **kwargs is ignored, not sure why it is here. def gradient(self, x, **kwargs): self.njev += 1 return self.jac(x, *self.args, **self.kwargs) # .T def constraints(self, x): con_values = [] - for fun, args in zip(self._constraint_funs, self._constraint_args): - con_values.append(fun(x, *args)) + for fun, args, kwargs in zip(self._constraint_funs, + self._constraint_args, + self._constraint_kwargs): + con_values.append(fun(x, *args, **kwargs)) return np.hstack(con_values) def jacobianstructure(self): @@ -189,22 +192,25 @@ def jacobian(self, x): # The structure ( = row and column indices) is already known at this point, # so we only need to stack the evaluated jacobians jac_values = [] - for i, (jac, args) in enumerate(zip(self._constraint_jacs, self._constraint_args)): + for i, (jac, args, kwargs) in enumerate(zip(self._constraint_jacs, + self._constraint_args, + self._constraint_kwargs)): if self._constraint_jac_is_sparse[i]: - jac_val = jac(x, *args) + jac_val = jac(x, *args, **kwargs) jac_values.append(jac_val.data) else: - dense_jac_val = np.atleast_2d(jac(x, *args)) + dense_jac_val = np.atleast_2d(jac(x, *args, **kwargs)) jac_values.append(dense_jac_val.ravel()) return np.hstack(jac_values) def hessian(self, x, lagrange, obj_factor): - H = obj_factor * self.obj_hess(x) # type: ignore + H = obj_factor * self.obj_hess(x, *self.args, **self.kwargs) # type: ignore # split the lagrangian multipliers for each constraint hessian lagrs = np.split(lagrange, np.cumsum(self._constraint_dims[:-1])) - for hessian, args, lagr in zip(self._constraint_hessians, - self._constraint_args, lagrs): - H += hessian(x, lagr, *args) + for hessian, args, kwargs, lagr in zip(self._constraint_hessians, + self._constraint_args, + self._constraint_kwargs, lagrs): + H += hessian(x, lagr, *args, **kwargs) return H[np.tril_indices(x.size)] def intermediate(self, alg_mod, iter_count, obj_value, inf_pr, inf_du, mu, @@ -235,9 +241,11 @@ def _get_sparse_jacobian_structure(constraints, x0): con_jac = con.get('jac', False) if con_jac: if isinstance(con_jac, bool): - _, jac_val = con['fun'](x0, *con.get('args', [])) + _, jac_val = con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {})) else: - jac_val = con_jac(x0, *con.get('args', [])) + jac_val = con_jac(x0, *con.get('args', []), + **con.get('kwargs', {})) # check if dense or sparse if isinstance(jac_val, coo_array): jacobians.append(jac_val) @@ -250,7 +258,8 @@ def _get_sparse_jacobian_structure(constraints, x0): con_jac_is_sparse.append(False) else: # we approximate this jacobian later (=dense) - con_val = np.atleast_1d(con['fun'](x0, *con.get('args', []))) + con_val = np.atleast_1d(con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {}))) jacobians.append(coo_array(np.ones((con_val.size, x0.size)))) con_jac_is_sparse.append(False) J = scipy.sparse.vstack(jacobians) @@ -263,9 +272,11 @@ def get_constraint_dimensions(constraints, x0): constraints = (constraints, ) for con in constraints: if con.get('jac', False) is True: - m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []))[0])) + m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {}))[0])) else: - m = len(np.atleast_1d(con['fun'](x0, *con.get('args', [])))) + m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {})))) con_dims.append(m) return np.array(con_dims) @@ -277,9 +288,11 @@ def get_constraint_bounds(constraints, x0, INF=1e19): constraints = (constraints, ) for con in constraints: if con.get('jac', False) is True: - m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []))[0])) + m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {}))[0])) else: - m = len(np.atleast_1d(con['fun'](x0, *con.get('args', [])))) + m = len(np.atleast_1d(con['fun'](x0, *con.get('args', []), + **con.get('kwargs', {})))) cl.extend(np.zeros(m)) if con['type'] == 'eq': cu.extend(np.zeros(m)) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index ba42622b..0bdc2bc6 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -97,6 +97,40 @@ def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy( np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): + """Makes sure that args and kwargs can be passed to all user defined + functions in minimize_ipopt.""" + from scipy.optimize import rosen, rosen_der, rosen_hess + + rosen2 = lambda x, a, b=None: rosen(x)*a*b + rosen_der2 = lambda x, a, b=None: rosen_der(x)*a*b + rosen_hess2 = lambda x, a, b=None: rosen_hess(x)*a*b + + x0 = [0.0, 0.0] + constr = { + "type": "ineq", + "fun": lambda x, a, b=None: -x[0]**2 - x[1]**2 + 2*a*b, + "jac": lambda x, a, b=None: np.array([-2 * x[0], -2 * x[1]])*a*b, + "hess": lambda x, v, a, b=None: -2 * np.eye(2) * v[0]*a*b, + "args": (1.0, ), + "kwargs": {'b': 1.0}, + } + res = cyipopt.minimize_ipopt(rosen2, x0, + jac=rosen_der2, + hess=rosen_hess2, + args=constr['args'], + kwargs=constr['kwargs'], + constraints=constr) + assert isinstance(res, dict) + assert np.isclose(res.get("fun"), 0.0) + assert res.get("status") == 0 + assert res.get("success") is True + expected_res = np.array([1.0, 1.0]) + np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) + + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid of Scipy available") def test_minimize_ipopt_sparse_jac_if_scipy(): From 3a69165ddc503a3dad518f8203853de86b641614 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Thu, 6 Apr 2023 13:11:12 +0200 Subject: [PATCH 067/170] Fixed the intersphinx links to scipy. --- cyipopt/scipy_interface.py | 38 ++++++++++++++++++++------------------ 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 66b23dbb..5fe7495b 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -66,13 +66,13 @@ class IpoptProblemWrapper(object): If ``None``, the Hessian is computed using IPOPT's numerical methods. Explicitly defined Hessians are not yet supported for this class. constraints : {Constraint, dict} or List of {Constraint, dict}, optional - See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html - for more information. Note that the jacobian of each constraint - corresponds to the `'jac'` key and must be a callable function - with signature ``jac(x) -> {ndarray, coo_array}``. If the constraint's - value of `'jac'` is a boolean and True, the constraint function `fun` - is expected to return a tuple `(con_val, con_jac)` consisting of the - evaluated constraint `con_val` and the evaluated jacobian `con_jac`. + See :py:func:`scipy.optimize.minimize` for more information. Note that + the jacobian of each constraint corresponds to the `'jac'` key and must + be a callable function with signature ``jac(x) -> {ndarray, + coo_array}``. If the constraint's value of `'jac'` is a boolean and + True, the constraint function `fun` is expected to return a tuple + `(con_val, con_jac)` consisting of the evaluated constraint `con_val` + and the evaluated jacobian `con_jac`. eps : float, optional Epsilon used in finite differences. con_dims : array_like, optional @@ -324,7 +324,8 @@ def minimize_ipopt(fun, callback=None, options=None): """ - Minimization using Ipopt with an interface like `scipy.optimize.minimize`. + Minimization using Ipopt with an interface like + :py:func:`scipy.optimize.minimize`. This function can be used to solve general nonlinear programming problems of the form: @@ -364,7 +365,7 @@ def minimize_ipopt(fun, derivatives (``fun``, ``jac``, ``hess``). method : str, optional This parameter is ignored. `minimize_ipopt` always uses Ipopt; use - `scipy.optimize.minimize` directly for other methods. + :py:func:`scipy.optimize.minimize` directly for other methods. jac : callable, optional The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. @@ -379,13 +380,13 @@ def minimize_ipopt(fun, Sequence of ``(min, max)`` pairs for each element in `x`. Use ``None`` to specify no bound. constraints : {Constraint, dict}, optional - See `scipy.optimize.minimize` for more information. Note that the - Jacobian of each constraint corresponds to the ``'jac'`` key and must - be a callable function with signature - ``jac(x) -> {ndarray, coo_array}``. If the constraint's - value of ``'jac'`` is ``True``, the constraint function ``fun`` must - return a tuple ``(con_val, con_jac)`` consisting of the evaluated - constraint ``con_val`` and the evaluated Jacobian ``con_jac``. + See :py:func:`scipy.optimize.minimize` for more information. Note that + the Jacobian of each constraint corresponds to the ``'jac'`` key and + must be a callable function with signature ``jac(x) -> {ndarray, + coo_array}``. If the constraint's value of ``'jac'`` is ``True``, the + constraint function ``fun`` must return a tuple ``(con_val, con_jac)`` + consisting of the evaluated constraint ``con_val`` and the evaluated + Jacobian ``con_jac``. tol : float, optional (default=1e-8) The desired relative convergence tolerance, passed as an option to Ipopt. See [1]_ for details. @@ -405,8 +406,9 @@ def minimize_ipopt(fun, Examples -------- Consider the problem of minimizing the Rosenbrock function. The Rosenbrock - function and its derivatives are implemented in `scipy.optimize.rosen`, - `scipy.optimize.rosen_der`, and `scipy.optimize.rosen_hess`. + function and its derivatives are implemented in + :py:func:`scipy.optimize.rosen`, :py:func:`scipy.optimize.rosen_der`, and + :py:func:`scipy.optimize.rosen_hess`. >>> from cyipopt import minimize_ipopt >>> from scipy.optimize import rosen, rosen_der From 33fc93583bca22acdaeb285011d51783c3df13eb Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Thu, 6 Apr 2023 13:33:45 +0200 Subject: [PATCH 068/170] Added missing import in Jax example. --- docs/source/tutorial.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index 73aa0541..77f162d6 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -165,7 +165,7 @@ We start by importing all required libraries:: config.update('jax_platform_name', 'cpu') import jax.numpy as np - from jax import jit, grad, jacfwd + from jax import jit, grad, jacfwd, jacrev from cyipopt import minimize_ipopt From 1cea1d69a870ea1e808f25d5227733b4332e247b Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 7 Apr 2023 07:42:19 +0200 Subject: [PATCH 069/170] Remove test.yml, fixes #187. --- .github/workflows/test.yml | 46 ------------------------------------- .github/workflows/tests.yml | 6 +---- 2 files changed, 1 insertion(+), 51 deletions(-) delete mode 100644 .github/workflows/test.yml diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml deleted file mode 100644 index 77294f80..00000000 --- a/.github/workflows/test.yml +++ /dev/null @@ -1,46 +0,0 @@ -name: test - -on: [push, pull_request] - -# cancels prior builds for this workflow when new commit is pushed -concurrency: - group: ${{ github.workflow }}-${{ github.ref }} - cancel-in-progress: true - -jobs: - build: - name: Build and run tests - runs-on: ${{ matrix.os }} - strategy: - fail-fast: false - matrix: - os: [ubuntu-latest] - python-version: ['3.11'] - ipopt-version: ['3.14'] - defaults: - run: - shell: bash -l {0} - steps: - - name: Checkout CyIpopt - uses: actions/checkout@v3 - - uses: conda-incubator/setup-miniconda@v2 - with: - auto-update-conda: true - activate-environment: test-environment - python-version: ${{ matrix.python-version }} - channels: conda-forge - miniforge-variant: Mambaforge - - name: Install basic dependencies - run: mamba install -y -v lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 - - name: Install CyIpopt - run: | - rm pyproject.toml - python -m pip install . - mamba list - - name: Test with pytest - run: | - python -c "import cyipopt" - mamba install -y -v cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 - pytest - mamba install -y -v cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.1 - pytest diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 381cd1a2..b0b9bf58 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -1,10 +1,6 @@ name: tests -on: - push: - branches: master - pull_request: - branches: master +on: [push, pull_request] # cancels prior builds for this workflow when new commit is pushed concurrency: From 038a2c79fc7b8348d0210e9354fd5d1e85289bd0 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 7 Apr 2023 00:00:13 -0700 Subject: [PATCH 070/170] ENH: add support for SciPy `minimize` methods --- cyipopt/scipy_interface.py | 45 +++++++++++++++++++++-- cyipopt/tests/unit/test_scipy_optional.py | 15 +++++--- 2 files changed, 51 insertions(+), 9 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index b51df799..379274e7 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -19,7 +19,7 @@ else: SCIPY_INSTALLED = True del scipy - from scipy.optimize import approx_fprime + from scipy.optimize import approx_fprime, minimize import scipy.sparse try: from scipy.optimize import OptimizeResult @@ -323,6 +323,33 @@ def convert_to_bytes(options): pass +def _wrap_fun(fun, kwargs): + if callable(fun) and kwargs: + def new_fun(x, *args): + return fun(x, *args, **kwargs) + else: + new_fun = fun + return new_fun + +def _wrap_funs(fun, jac, hess, hessp, constraints, kwargs): + wrapped_fun = _wrap_fun(fun, kwargs) + wrapped_jac = _wrap_fun(jac, kwargs) + wrapped_hess = _wrap_fun(hess, kwargs) + wrapped_hessp = _wrap_fun(hessp, kwargs) + if isinstance(constraints, dict): + constraints = (constraints,) + wrapped_constraints = [] + for constraint in constraints: + constraint = constraint.copy() + ckwargs = constraint.pop('kwargs', {}) + constraint['fun'] = _wrap_fun(constraint.get('fun', None), ckwargs) + constraint['jac'] = _wrap_fun(constraint.get('jac', None), ckwargs) + wrapped_constraints.append(constraint) + return (wrapped_fun, wrapped_jac, wrapped_hess, wrapped_hessp, + wrapped_constraints) + + + def minimize_ipopt(fun, x0, args=(), @@ -377,8 +404,9 @@ def minimize_ipopt(fun, Extra keyword arguments passed to the objective function and its derivatives (``fun``, ``jac``, ``hess``). method : str, optional - This parameter is ignored. `minimize_ipopt` always uses Ipopt; use - :py:func:`scipy.optimize.minimize` directly for other methods. + If unspecified (default), Ipopt is used. + :py:func:`scipy.optimize.minimize` methods can also be used as long + as no `kwargs` are specified. jac : callable, optional The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. @@ -465,6 +493,17 @@ def minimize_ipopt(fun, msg = 'Install SciPy to use the `minimize_ipopt` function.' raise ImportError(msg) + if method is not None: + # if kwargs is not None: + # message = (f"`method={method}` may only be used if " + # "`kwargs` is `None` (default).") + # raise NotImplementedError(message) + funs = _wrap_funs(fun, jac, hess, hessp, constraints, kwargs) + fun, jac, hess, hessp, constraints = funs + res = minimize(fun, x0, args, method, jac, hess, hessp, + bounds, constraints, tol, callback, options) + return res + _x0 = np.atleast_1d(x0) lb, ub = get_bounds(bounds) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 0bdc2bc6..b44ac9c6 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -99,7 +99,8 @@ def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy( @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") -def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): +@pytest.mark.parametrize('method', [None, 'slsqp', 'trust-constr']) +def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(method): """Makes sure that args and kwargs can be passed to all user defined functions in minimize_ipopt.""" from scipy.optimize import rosen, rosen_der, rosen_hess @@ -118,17 +119,19 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): "kwargs": {'b': 1.0}, } res = cyipopt.minimize_ipopt(rosen2, x0, - jac=rosen_der2, - hess=rosen_hess2, + method=method, args=constr['args'], kwargs=constr['kwargs'], + jac=rosen_der2, + hess = rosen_hess2, constraints=constr) + assert isinstance(res, dict) - assert np.isclose(res.get("fun"), 0.0) + assert np.isclose(res.get("fun"), 0.0, atol=1e-6) assert res.get("status") == 0 - assert res.get("success") is True + assert res.get("success") == True expected_res = np.array([1.0, 1.0]) - np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) + np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-3) @pytest.mark.skipif("scipy" not in sys.modules, From ff88aeafc02a867f7a8b6679c5b0eb9ba3b9d6b0 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Sat, 8 Apr 2023 20:15:04 -0600 Subject: [PATCH 071/170] tutorial section using get_current_* by subclassing cyipopt.Problem --- docs/source/tutorial.rst | 136 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 136 insertions(+) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index 73aa0541..1f46d1f4 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -390,6 +390,142 @@ The method returns the optimal solution and an info dictionary that contains the status of the algorithm, the value of the constraints multipliers at the solution, and more. +Accessing iterate and infeasibility vectors in an intermediate callback +======================================================================= + +When debugging an Ipopt solve that converges slowly or not at all, it can be +very useful to track the primal/dual iterate and infeasibility vectors +to get a sense for the variable and constraint coordinates that are causing +a problem. This can be done with Ipopt's ``GetCurrentIterate`` and +``GetCurrentViolations`` functions, which were added to Ipopt's C interface in +version 3.14.0. These functions are accessed in CyIpopt via the +``get_current_iterate`` and ``get_current_violations`` methods of +``cyipopt.Problem``. +These methods can be accessed in one of two ways: + +- Subclassing ``cyipopt.Problem`` +- Augmenting the intermediate callback signature + +Subclassing cyipopt.Problem +--------------------------- + +In contrast to the previous example, we now define the HS071 +problem as a subclass of ``cyipopt.Problem``. This is the most straightforward +way to access to access the ``get_current_iterate`` and ``get_current_violations`` +methods.:: + + import cyipopt + import numpy as np + + class HS071(cyipopt.Problem): + + def objective(self, x): + """Returns the scalar value of the objective given x.""" + return x[0] * x[3] * np.sum(x[0:3]) + x[2] + + def gradient(self, x): + """Returns the gradient of the objective with respect to x.""" + return np.array([ + x[0]*x[3] + x[3]*np.sum(x[0:3]), + x[0]*x[3], + x[0]*x[3] + 1.0, + x[0]*np.sum(x[0:3]) + ]) + + def constraints(self, x): + """Returns the constraints.""" + return np.array((np.prod(x), np.dot(x, x))) + + def jacobian(self, x): + """Returns the Jacobian of the constraints with respect to x.""" + return np.concatenate((np.prod(x)/x, 2*x)) + + def hessianstructure(self): + """Returns the row and column indices for non-zero vales of the + Hessian.""" + + # NOTE: The default hessian structure is of a lower triangular matrix, + # therefore this function is redundant. It is included as an example + # for structure callback. + + return np.nonzero(np.tril(np.ones((4, 4)))) + + def hessian(self, x, lagrange, obj_factor): + """Returns the non-zero values of the Hessian.""" + + H = obj_factor*np.array(( + (2*x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (2*x[0]+x[1]+x[2], x[0], x[0], 0))) + + H += lagrange[0]*np.array(( + (0, 0, 0, 0), + (x[2]*x[3], 0, 0, 0), + (x[1]*x[3], x[0]*x[3], 0, 0), + (x[1]*x[2], x[0]*x[2], x[0]*x[1], 0))) + + H += lagrange[1]*2*np.eye(4) + + row, col = self.hessianstructure() + + return H[row, col] + + def intermediate(self, alg_mod, iter_count, obj_value, inf_pr, inf_du, mu, + d_norm, regularization_size, alpha_du, alpha_pr, + ls_trials): + """Prints information at every Ipopt iteration.""" + iterate = self.get_current_iterate() + infeas = self.get_current_violations() + primal = iterate["x"] + jac = self.jacobian(primal) + + print("Iteration:", iter_count) + print("Primal iterate:", primal) + print("Flattened Jacobian:", jac) + print("Dual infeasibility:", infeas["grad_lag_x"]) + + +Now, in the ``intermediate`` method of ``HS071``, we call +``self.get_current_iterate`` and ``self.get_current_violations``. +These are implemented on ``cyipopt.Problem``. These methods return dicts +that contain each component of the Ipopt iterate and infeasibility +vectors. The primal iterate and constraint dual iterate can be accessed +with ``iterate["x"]`` and ``iterate["mult_g"]``, while the primal and +dual infeasibilities can be accessed with ``infeas["g_violation"]`` +and ``infeas["grad_lag_x"]``. A full list of keys present in these +dictionaries can be found in the ``cyipopt.Problem`` documentation. + +We can now set up and solve the optimization problem. +Note that now we instantiate the ``HS071`` class and provide it the arguments +that are required by ``cyipopt.Problem``. +When we solve, we will see the primal iterate and dual infeasibility vectors +printed every iteration.:: + + lb = [1.0, 1.0, 1.0, 1.0] + ub = [5.0, 5.0, 5.0, 5.0] + + cl = [25.0, 40.0] + cu = [2.0e19, 40.0] + + x0 = [1.0, 5.0, 5.0, 1.0] + + nlp = HS071( + n=len(x0), + m=len(cl), + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + x, info = nlp.solve(x0) + +While here we have implemented a very basic callback, much more sophisticated +analysis is possible. For example, we could compute the condition number or +rank of the constraint Jacobian to identify when constraint qualifications +are close to being violated. + Where to go from here ===================== From c437bc108733429c551bd698f568cdc831cbf1e4 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 9 Apr 2023 17:25:10 -0700 Subject: [PATCH 072/170] TST: restore previous test --- cyipopt/tests/unit/test_scipy_optional.py | 15 ++++++--------- 1 file changed, 6 insertions(+), 9 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index b44ac9c6..0bdc2bc6 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -99,8 +99,7 @@ def test_minimize_ipopt_jac_and_hessians_constraints_if_scipy( @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") -@pytest.mark.parametrize('method', [None, 'slsqp', 'trust-constr']) -def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(method): +def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): """Makes sure that args and kwargs can be passed to all user defined functions in minimize_ipopt.""" from scipy.optimize import rosen, rosen_der, rosen_hess @@ -119,19 +118,17 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(method): "kwargs": {'b': 1.0}, } res = cyipopt.minimize_ipopt(rosen2, x0, - method=method, + jac=rosen_der2, + hess=rosen_hess2, args=constr['args'], kwargs=constr['kwargs'], - jac=rosen_der2, - hess = rosen_hess2, constraints=constr) - assert isinstance(res, dict) - assert np.isclose(res.get("fun"), 0.0, atol=1e-6) + assert np.isclose(res.get("fun"), 0.0) assert res.get("status") == 0 - assert res.get("success") == True + assert res.get("success") is True expected_res = np.array([1.0, 1.0]) - np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-3) + np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) @pytest.mark.skipif("scipy" not in sys.modules, From 0b89e14d9f529066ddbc403366f69ddaeaf72c29 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 9 Apr 2023 17:58:12 -0700 Subject: [PATCH 073/170] TST: minimize_ipopt: test SciPy optimization methods --- cyipopt/tests/unit/test_scipy_optional.py | 92 +++++++++++++++++++++++ 1 file changed, 92 insertions(+) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 0bdc2bc6..87368046 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -14,6 +14,10 @@ import cyipopt +# Hard-code rather than importing from scipy.optimize._minimize in a try/except +MINIMIZE_METHODS = ['nelder-mead', 'powell', 'cg', 'bfgs', 'newton-cg', + 'l-bfgs-b', 'tnc', 'cobyla', 'slsqp', 'trust-constr', + 'dogleg', 'trust-ncg', 'trust-exact', 'trust-krylov'] @pytest.mark.skipif("scipy" in sys.modules, reason="Test only valid if no Scipy available.") @@ -131,6 +135,94 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): np.testing.assert_allclose(res.get("x"), expected_res, rtol=1e-5) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +@pytest.mark.parametrize('method', MINIMIZE_METHODS) +def test_minimize_ipopt_jac_with_scipy_methods(method): + x0 = [0] * 4 + a0, b0, c0, d0 = 1, 2, 3, 4 + + def fun(x, a=0, e=0, b=0): + assert a == a0 + assert b == b0 + fun.count += 1 + return (x[0] - a) ** 2 + (x[1] - b) ** 2 + x[2] ** 2 + x[3] ** 2 + + def grad(x, a=0, e=0, b=0): + assert a == a0 + assert b == b0 + grad.count += 1 + return [2 * (x[0] - a), 2 * (x[1] - b), 2 * x[2], 2 * x[3]] + + def hess(x, a=0, e=0, b=0): + assert a == a0 + assert b == b0 + hess.count += 1 + return 2 * np.eye(4) + + def fun_constraint(x, c=0, e=0, d=0): + assert c == c0 + assert d == d0 + fun_constraint.count += 1 + return [(x[2] - c) ** 2, (x[3] - d) ** 2] + + def grad_constraint(x, c=0, e=0, d=0): + assert c == c0 + assert d == d0 + grad_constraint.count += 1 + return np.hstack((np.zeros((2, 2)), + np.diag([2 * (x[2] - c), 2 * (x[3] - d)]))) + + fun.count = 0 + grad.count = 0 + hess.count = 0 + fun_constraint.count = 0 + grad_constraint.count = 0 + + constr = { + "type": "eq", + "fun": fun_constraint, + "jac": grad_constraint, + "args": (c0,), + "kwargs": {'d': d0}, + } + + kwargs = {} + jac_methods = {'cg', 'bfgs', 'newton-cg', 'l-bfgs-b', 'tnc', 'slsqp,', + 'dogleg', 'trust-ncg', 'trust-krylov', 'trust-exact', + 'trust-constr'} + hess_methods = {'newton-cg', 'dogleg', 'trust-ncg', 'trust-krylov', + 'trust-exact', 'trust-constr'} + constr_methods = {'slsqp', 'trust-constr'} + + if method in jac_methods: + kwargs['jac'] = grad + if method in hess_methods: + kwargs['hess'] = hess + if method in constr_methods: + kwargs['constraints'] = constr + + res = cyipopt.minimize_ipopt(fun, x0, method=method, args=(a0,), + kwargs={'b': b0}, **kwargs) + + assert res.success + np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=1e-3) + + # confirm that the test covers what we think it does: all the functions + # that we provide are actually being executed; that is, the assertions + # are *passing*, not being skipped + assert fun.count > 0 + if 'jac' in kwargs: + assert grad.count > 0 + if 'hess' in kwargs: + assert hess.count > 0 + if 'constraints' in kwargs: + np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + assert fun_constraint.count > 0 + if 'constraints' in kwargs and 'jac' in kwargs['constraints']: + assert grad_constraint.count > 0 + + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid of Scipy available") def test_minimize_ipopt_sparse_jac_if_scipy(): From 97506e122dd308ed666bc33fb32bef45f8521a28 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 9 Apr 2023 18:27:19 -0700 Subject: [PATCH 074/170] TST: minimize_ipopt: improvements after self-review --- cyipopt/scipy_interface.py | 7 +------ cyipopt/tests/unit/test_scipy_optional.py | 23 ++++++++++++----------- 2 files changed, 13 insertions(+), 17 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 379274e7..1dd99bc8 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -405,8 +405,7 @@ def minimize_ipopt(fun, derivatives (``fun``, ``jac``, ``hess``). method : str, optional If unspecified (default), Ipopt is used. - :py:func:`scipy.optimize.minimize` methods can also be used as long - as no `kwargs` are specified. + :py:func:`scipy.optimize.minimize` methods can also be used. jac : callable, optional The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. @@ -494,10 +493,6 @@ def minimize_ipopt(fun, raise ImportError(msg) if method is not None: - # if kwargs is not None: - # message = (f"`method={method}` may only be used if " - # "`kwargs` is `None` (default).") - # raise NotImplementedError(message) funs = _wrap_funs(fun, jac, hess, hessp, constraints, kwargs) fun, jac, hess, hessp, constraints = funs res = minimize(fun, x0, args, method, jac, hess, hessp, diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 87368046..d8d81890 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -108,16 +108,16 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): functions in minimize_ipopt.""" from scipy.optimize import rosen, rosen_der, rosen_hess - rosen2 = lambda x, a, b=None: rosen(x)*a*b - rosen_der2 = lambda x, a, b=None: rosen_der(x)*a*b - rosen_hess2 = lambda x, a, b=None: rosen_hess(x)*a*b + rosen2 = lambda x, a, b=None: rosen(x) + rosen_der2 = lambda x, a, b=None: rosen_der(x) + rosen_hess2 = lambda x, a, b=None: rosen_hess(x) x0 = [0.0, 0.0] constr = { "type": "ineq", - "fun": lambda x, a, b=None: -x[0]**2 - x[1]**2 + 2*a*b, - "jac": lambda x, a, b=None: np.array([-2 * x[0], -2 * x[1]])*a*b, - "hess": lambda x, v, a, b=None: -2 * np.eye(2) * v[0]*a*b, + "fun": lambda x, a, b=None: -x[0]**2 - x[1]**2 + 2, + "jac": lambda x, a, b=None: np.array([-2 * x[0], -2 * x[1]]), + "hess": lambda x, v, a, b=None: -2 * np.eye(2) * v[0], "args": (1.0, ), "kwargs": {'b': 1.0}, } @@ -212,15 +212,16 @@ def grad_constraint(x, c=0, e=0, d=0): # that we provide are actually being executed; that is, the assertions # are *passing*, not being skipped assert fun.count > 0 - if 'jac' in kwargs: + if method in jac_methods: assert grad.count > 0 - if 'hess' in kwargs: + if method in hess_methods: assert hess.count > 0 - if 'constraints' in kwargs: - np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + if method in constr_methods: assert fun_constraint.count > 0 - if 'constraints' in kwargs and 'jac' in kwargs['constraints']: assert grad_constraint.count > 0 + np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + else: + np.testing.assert_allclose(res.x[2:], 0, atol=1e-3) @pytest.mark.skipif("scipy" not in sys.modules, From a19b1149331d95f31de7baf2136baecd51f311b4 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Mon, 10 Apr 2023 14:28:30 -0600 Subject: [PATCH 075/170] remove unnecessary punctuation --- docs/source/tutorial.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index 1f46d1f4..7b70dfab 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -406,13 +406,13 @@ These methods can be accessed in one of two ways: - Subclassing ``cyipopt.Problem`` - Augmenting the intermediate callback signature -Subclassing cyipopt.Problem ---------------------------- +Subclassing ``cyipopt.Problem`` +------------------------------- In contrast to the previous example, we now define the HS071 problem as a subclass of ``cyipopt.Problem``. This is the most straightforward way to access to access the ``get_current_iterate`` and ``get_current_violations`` -methods.:: +methods:: import cyipopt import numpy as np From 01a776b5fcdcd5c49285e2c91ce43bfe540b3762 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Apr 2023 17:00:16 -0600 Subject: [PATCH 076/170] remove code that was necessary to support and test a 12-argument callback --- cyipopt/cython/ipopt_wrapper.pyx | 97 ++--------- cyipopt/tests/unit/test_exceptions.py | 153 ----------------- cyipopt/tests/unit/test_ipopt_funcs.py | 227 ++++++------------------- 3 files changed, 61 insertions(+), 416 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 2722ed9e..d0542d83 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -248,12 +248,6 @@ cdef class Problem: The stepsize for the primal variables. ``ls_trials``: The number of backtracking line search steps. - ``problem`` (optional): - The ``Problem`` object itself. This argument can be used - to call the ``get_current_iterate`` and - ``get_current_violations`` methods from a callback that - is not a method on this class. This argument is optional - for backwards compatibility. more information can be found in the following link: https://coin-or.github.io/Ipopt/OUTPUT.html @@ -286,7 +280,6 @@ cdef class Problem: cdef public Index __m cdef public object __exception - cdef public object __send_self_to_intermediate cdef Bool __in_ipopt_solve def __init__(self, n, m, problem_obj=None, lb=None, ub=None, cl=None, @@ -438,57 +431,6 @@ cdef class Problem: raise RuntimeError(msg) SetIntermediateCallback(self.__nlp, intermediate_cb) - if self.__intermediate is None: - self.__send_self_to_intermediate = None - else: - # A callback was provided. We need to know whether to send this - # callback 11 arguments or 12 arguments. - cb_signature = inspect.signature(self.__intermediate) - pos_args = [ - param for param in cb_signature.parameters.values() - if param.kind in { - inspect.Parameter.POSITIONAL_ONLY, - inspect.Parameter.POSITIONAL_OR_KEYWORD, - } - ] - var_args = [ - param for param in cb_signature.parameters.values() - if param.kind == inspect.Parameter.VAR_POSITIONAL - ] - kwd_args = [ - param for param in cb_signature.parameters.values() - if param.kind == inspect.Parameter.VAR_KEYWORD - ] - if kwd_args: - # **kwds is not allowed in the intermediate callback - raise RuntimeError( - "Variable keyword arguments are not allowed in the" - " intermediate callback function." - ) - elif var_args: - # Even if *args is provided, having more than 12 positional - # arguments is an error. - if len(pos_args) > 12: - raise RuntimeError( - "More than 12 positional arguments were specified in" - " the intermediate callback." - ) - # If a catchall *args argument is specified in the callback, - # send all 12 possible callback arguments. - self.__send_self_to_intermediate = True - elif len(pos_args) == 11: - # If the callback takes 11 arguments, do not send self - self.__send_self_to_intermediate = False - elif len(pos_args) == 12: - # If the callback takes 12 arguments, do send self - self.__send_self_to_intermediate = True - else: - raise RuntimeError( - "Invalid intermediate callback call signature. This" - " callback must accept either 11 or 12 positional" - " arguments or a variable number of positional" - " arguments." - ) if self.__hessian is None: msg = b"Hessian callback not given, using approximation" @@ -1181,33 +1123,18 @@ cdef Bool intermediate_cb(Index alg_mod, if not self.__intermediate: return True - if self.__send_self_to_intermediate: - ret_val = self.__intermediate(alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - self - ) - else: - ret_val = self.__intermediate(alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials - ) + ret_val = self.__intermediate(alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials + ) if ret_val is None: return True diff --git a/cyipopt/tests/unit/test_exceptions.py b/cyipopt/tests/unit/test_exceptions.py index 96bf31ae..e69de29b 100644 --- a/cyipopt/tests/unit/test_exceptions.py +++ b/cyipopt/tests/unit/test_exceptions.py @@ -1,153 +0,0 @@ -import pytest -import cyipopt - - -def test_hs071_extra_arg_intermediate_with_varargs( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - obj_values = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - problem, - extra_arg, - *args, - ): - obj_values.append(obj_value) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - msg = "More than 12 positional arguments" - with pytest.raises(RuntimeError, match=msg): - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) - - -def test_hs071_toofew_arg_intermediate( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - obj_values = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ): - obj_values.append(obj_value) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - msg = "Invalid intermediate callback call signature" - with pytest.raises(RuntimeError, match=msg): - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) - - -def test_hs071_intermediate_with_kwds( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - obj_values = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - problem, - **kwds, - ): - obj_values.append(obj_value) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - msg = "Variable keyword arguments are not allowed" - with pytest.raises(RuntimeError, match=msg): - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index b621f9dc..789fca9d 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -111,6 +111,9 @@ def test_get_iterate_hs071( hs071_constraint_lower_bounds_fixture, hs071_constraint_upper_bounds_fixture, ): + """This test demonstrates a hacky way to call get_current_iterate from an + intermediate callback without subclassing Problem. This is not recommended. + """ x0 = hs071_initial_guess_fixture lb = hs071_variable_lower_bounds_fixture ub = hs071_variable_upper_bounds_fixture @@ -142,6 +145,7 @@ def intermediate( # CyIpopt's C wapper expects a callback with this signature. If we # implemented this as a method on problem_definition, we could store # and access global information on self. + # test_get_iterate_hs071_subclass_Problem tests this below. # This callback must be defined before constructing the Problem, but can # be defined after (or as part of) problem_definition. If we attach the @@ -191,158 +195,6 @@ def intermediate( np.testing.assert_allclose(x_iterates[-1], x) -@pytest.mark.skipif( - pre_3_14_0, - reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", -) -def test_get_iterate_hs071_12arg_callback( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - # - # Define a callback that uses some "global" information to call - # get_current_iterate and store the result - # - x_iterates = [] - iter_counts = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - problem, - ): - iterate = problem.get_current_iterate(scaled=False) - x_iterates.append(iterate["x"]) - - # Hack so we may get the number of iterations after the solve - iter_counts.append(iter_count) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) - - # Disable bound push to make testing easier - nlp.add_option("bound_push", 1e-9) - x, info = nlp.solve(x0) - - # Assert correct solution - expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) - np.testing.assert_allclose(x, expected_x) - - # - # Assert some very basic information about the collected primal iterates - # - iter_count = iter_counts[-1] - assert len(x_iterates) == (1 + iter_count) - - # These could be different due to bound_push (and scaling) - np.testing.assert_allclose(x_iterates[0], x0) - - # These could be different due to honor_original_bounds (and scaling) - np.testing.assert_allclose(x_iterates[-1], x) - - -@pytest.mark.skipif( - pre_3_14_0, - reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", -) -def test_get_iterate_hs071_vararg_callback( - hs071_initial_guess_fixture, - hs071_definition_instance_fixture, - hs071_variable_lower_bounds_fixture, - hs071_variable_upper_bounds_fixture, - hs071_constraint_lower_bounds_fixture, - hs071_constraint_upper_bounds_fixture, -): - # This test makes sure we pass the correct information to the user's - # callback even when using a callback with variable number of arguments, - # i.e. using *args. - x0 = hs071_initial_guess_fixture - lb = hs071_variable_lower_bounds_fixture - ub = hs071_variable_upper_bounds_fixture - cl = hs071_constraint_lower_bounds_fixture - cu = hs071_constraint_upper_bounds_fixture - n = len(x0) - m = len(cl) - - # - # Define a callback that uses some "global" information to call - # get_current_iterate and store the result - # - x_iterates = [] - iter_counts = [] - def intermediate(*args): - iterate = args[11].get_current_iterate(scaled=False) - x_iterates.append(iterate["x"]) - - # Hack so we may get the number of iterations after the solve - iter_counts.append(args[1]) - - problem_definition = hs071_definition_instance_fixture - # Replace "intermediate" attribute with our callback - problem_definition.intermediate = intermediate - - nlp = cyipopt.Problem( - n=n, - m=m, - problem_obj=problem_definition, - lb=lb, - ub=ub, - cl=cl, - cu=cu, - ) - - # Disable bound push to make testing easier - nlp.add_option("bound_push", 1e-9) - x, info = nlp.solve(x0) - - # Assert correct solution - expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) - np.testing.assert_allclose(x, expected_x) - - # - # Assert some very basic information about the collected primal iterates - # - iter_count = iter_counts[-1] - assert len(x_iterates) == (1 + iter_count) - - # These could be different due to bound_push (and scaling) - np.testing.assert_allclose(x_iterates[0], x0) - - # These could be different due to honor_original_bounds (and scaling) - np.testing.assert_allclose(x_iterates[-1], x) - - @pytest.mark.skipif( pre_3_14_0, reason="GetIpoptCurrentIterate was introduced in Ipopt v3.14.0", @@ -404,8 +256,7 @@ def intermediate( ls_trials, ): # By subclassing Problem, we can call get_current_iterate - # without any "global" information, even with the backward- - # compatible 11-argument intermediate callback. + # without any "global" information iterate = self.get_current_iterate(scaled=False) x_iterates.append(iterate["x"]) @@ -445,7 +296,7 @@ def intermediate( pre_3_14_0, reason="GetIpoptCurrentViolations was introduced in Ipopt v3.14.0", ) -def test_get_violations_hs071_12arg_callback( +def test_get_violations_hs071_subclass_Problem( hs071_initial_guess_fixture, hs071_definition_instance_fixture, hs071_variable_lower_bounds_fixture, @@ -466,33 +317,53 @@ def test_get_violations_hs071_12arg_callback( pr_violations = [] du_violations = [] iter_counts = [] - def intermediate( - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - problem, - ): - violations = problem.get_current_violations(scaled=True) - pr_violations.append(violations["g_violation"]) - du_violations.append(violations["grad_lag_x"]) + class MyProblem(cyipopt.Problem): - # Hack so we may get the number of iterations after the solve - iter_counts.append(iter_count) + def objective(self, x): + return problem_definition.objective(x) - # Override the default callback with our locally defined callback. - problem_definition.intermediate = intermediate - nlp = cyipopt.Problem( + def gradient(self, x): + return problem_definition.gradient(x) + + def constraints(self, x): + return problem_definition.constraints(x) + + def jacobian(self, x): + return problem_definition.jacobian(x) + + def jacobian_structure(self, x): + return problem_definition.jacobian_structure(x) + + def hessian(self, x, lagrange, obj_factor): + return problem_definition.hessian(x, lagrange, obj_factor) + + def hessian_structure(self, x): + return problem_definition.hessian_structure(x) + + def intermediate( + self, + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + violations = self.get_current_violations(scaled=True) + pr_violations.append(violations["g_violation"]) + du_violations.append(violations["grad_lag_x"]) + + # Hack so we may get the number of iterations after the solve + iter_counts.append(iter_count) + + nlp = MyProblem( n=n, m=m, - problem_obj=problem_definition, lb=lb, ub=ub, cl=cl, From b7046e763352bf11f398780191957602e507ded3 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Apr 2023 17:14:16 -0600 Subject: [PATCH 077/170] update get_current_* section of docs --- docs/source/tutorial.rst | 21 ++++++++------------- 1 file changed, 8 insertions(+), 13 deletions(-) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index 7b97303c..c0a06729 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -398,21 +398,16 @@ very useful to track the primal/dual iterate and infeasibility vectors to get a sense for the variable and constraint coordinates that are causing a problem. This can be done with Ipopt's ``GetCurrentIterate`` and ``GetCurrentViolations`` functions, which were added to Ipopt's C interface in -version 3.14.0. These functions are accessed in CyIpopt via the +Ipopt version 3.14.0. These functions are accessed in CyIpopt via the ``get_current_iterate`` and ``get_current_violations`` methods of ``cyipopt.Problem``. -These methods can be accessed in one of two ways: +These methods should only be called during an intermediate callback. +To access them, we define our problem as a subclass of ``cyipopt.Problem`` +and access the ``get_current_iterate`` and ``get_current_violations`` methods +on ``self``. -- Subclassing ``cyipopt.Problem`` -- Augmenting the intermediate callback signature - -Subclassing ``cyipopt.Problem`` -------------------------------- - -In contrast to the previous example, we now define the HS071 -problem as a subclass of ``cyipopt.Problem``. This is the most straightforward -way to access to access the ``get_current_iterate`` and ``get_current_violations`` -methods:: +In contrast to the previous example, we now define the HS071 problem as a +subclass of ``cyipopt.Problem``:: import cyipopt import numpy as np @@ -500,7 +495,7 @@ We can now set up and solve the optimization problem. Note that now we instantiate the ``HS071`` class and provide it the arguments that are required by ``cyipopt.Problem``. When we solve, we will see the primal iterate and dual infeasibility vectors -printed every iteration.:: +printed every iteration:: lb = [1.0, 1.0, 1.0, 1.0] ub = [5.0, 5.0, 5.0, 5.0] From 2a24f090365fced2e0c6197a946a9663753b9177 Mon Sep 17 00:00:00 2001 From: robbybp Date: Thu, 27 Apr 2023 09:41:26 -0600 Subject: [PATCH 078/170] pin scipy to 1.10.0 --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index b0b9bf58..a9915ba9 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy>=0.19.0 + mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy==1.10.0 mamba list pytest From de52b8eb8895e15960b87fddf744b453b3967213 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 08:28:07 +0200 Subject: [PATCH 079/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index a9915ba9..f2b3b13f 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 scipy==1.10.0 + mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 "scipy=1.10.0" mamba list pytest From cc4efc0ae21b9dfa983067a14f0f6de0d3c841e5 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 08:42:30 +0200 Subject: [PATCH 080/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index f2b3b13f..b3aa77e2 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 "scipy=1.10.0" + mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 "scipy<1.10.0" mamba list pytest From 27ebaf4e722635fb893a8cad2743771ed3a8a443 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 09:00:48 +0200 Subject: [PATCH 081/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index b3aa77e2..169a2976 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 "scipy<1.10.0" + mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 "scipy<=1.10.0" pytest>=3.3.2 mamba list pytest From 6614eaf50cffaf9a8a5cefa12b0fdf5a8acbc0db Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 09:13:06 +0200 Subject: [PATCH 082/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 169a2976..40aab5e9 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 "scipy<=1.10.0" pytest>=3.3.2 + mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy<=1.10.0" "pytest>=3.3.2" mamba list pytest From aba6c972ff0374093ad148250a15389d19908e87 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 09:24:14 +0200 Subject: [PATCH 083/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 40aab5e9..0a808b93 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy<=1.10.0" "pytest>=3.3.2" + mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.10.0" "pytest>=3.3.2" mamba list pytest From 0a1af025c703ba9e25710c9aa4d1dd2177f33bce Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 09:30:37 +0200 Subject: [PATCH 084/170] Update .github/workflows/tests.yml --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 0a808b93..d580c69d 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -54,6 +54,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.10.0" "pytest>=3.3.2" + mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.9.*" "pytest>=3.3.2" mamba list pytest From f78615d332889b3cf83c1e9530500a4cc19716c8 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 28 Apr 2023 11:22:30 +0200 Subject: [PATCH 085/170] Drop Python 3.7 tests in CI. --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index d580c69d..3a279636 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -15,7 +15,7 @@ jobs: fail-fast: false matrix: os: [ubuntu-latest, macos-latest, windows-latest] - python-version: ['3.7', '3.8', '3.9', '3.10', '3.11'] + python-version: ['3.8', '3.9', '3.10', '3.11'] ipopt-version: ['3.12', '3.13', '3.14'] exclude: - os: windows-latest From fc56444968326c2fb08c9d36967027adb414c354 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Thu, 18 May 2023 16:08:03 -0700 Subject: [PATCH 086/170] MAINT: additional tests; fix Ipopt jac=None with keywords --- cyipopt/scipy_interface.py | 22 ++++++-- cyipopt/tests/unit/test_scipy_optional.py | 69 +++++++++++++++++++++-- 2 files changed, 80 insertions(+), 11 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 1dd99bc8..1fa45631 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -113,8 +113,10 @@ def __init__(self, if hess is not None: self.obj_hess = hess if jac is None: - jac = lambda x0, *args, **kwargs: approx_fprime( - x0, fun, eps, *args, **kwargs) + def jac(x, *args, **kwargs): + def wrapped_fun(x): + return fun(x, *args, **kwargs) + return approx_fprime(x, wrapped_fun, eps) elif jac is True: fun = MemoizeJac(fun) jac = fun.derivative @@ -367,6 +369,14 @@ def minimize_ipopt(fun, Minimization using Ipopt with an interface like :py:func:`scipy.optimize.minimize`. + Differences compared to :py:func:`scipy.optimize.minimize` include: + + - A different default `method`: when `method` is not provided, Ipopt is + used to solve the problem. + - Support for parameter `kwargs`: additional keyword arguments to be + passed to the objective function, constraints, and their derivatives. + - Lack of support for `callback` and `hessp` with the default `method`. + This function can be used to solve general nonlinear programming problems of the form: @@ -414,8 +424,9 @@ def minimize_ipopt(fun, ``hess(x) -> ndarray, shape(n, )``. If ``None``, the Hessian is computed using IPOPT's numerical methods. hessp : callable, optional - This parameter is currently unused. An error will be raised if a value - other than ``None`` is provided. + If `method` is one of the SciPy methods, this is a callable that + produces the inner product of the Hessian and a vector. Otherwise, an + error will be raised if a value other than ``None`` is provided. bounds : sequence, shape(n, ), optional Sequence of ``(min, max)`` pairs for each element in `x`. Use ``None`` to specify no bound. @@ -436,7 +447,8 @@ def minimize_ipopt(fun, and ``max_iter``. All other options are passed directly to Ipopt. See [1]_ for details. callback : callable, optional - This parameter is ignored. + This parameter is ignored unless a `method` is one of the SciPy + methods. References ---------- diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index d8d81890..f33acd61 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -137,7 +137,7 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") -@pytest.mark.parametrize('method', MINIMIZE_METHODS) +@pytest.mark.parametrize('method', [None] + MINIMIZE_METHODS) def test_minimize_ipopt_jac_with_scipy_methods(method): x0 = [0] * 4 a0, b0, c0, d0 = 1, 2, 3, 4 @@ -160,6 +160,12 @@ def hess(x, a=0, e=0, b=0): hess.count += 1 return 2 * np.eye(4) + def hessp(x, p, a=0, e=0, b=0): + assert a == a0 + assert b == b0 + hessp.count += 1 + return 2 * np.eye(4) @ p + def fun_constraint(x, c=0, e=0, d=0): assert c == c0 assert d == d0 @@ -173,11 +179,8 @@ def grad_constraint(x, c=0, e=0, d=0): return np.hstack((np.zeros((2, 2)), np.diag([2 * (x[2] - c), 2 * (x[3] - d)]))) - fun.count = 0 - grad.count = 0 - hess.count = 0 - fun_constraint.count = 0 - grad_constraint.count = 0 + def callback(*args, **kwargs): + callback.count += 1 constr = { "type": "eq", @@ -193,6 +196,7 @@ def grad_constraint(x, c=0, e=0, d=0): 'trust-constr'} hess_methods = {'newton-cg', 'dogleg', 'trust-ncg', 'trust-krylov', 'trust-exact', 'trust-constr'} + hessp_methods = hess_methods - {'dogleg', 'trust-exact'} constr_methods = {'slsqp', 'trust-constr'} if method in jac_methods: @@ -201,6 +205,16 @@ def grad_constraint(x, c=0, e=0, d=0): kwargs['hess'] = hess if method in constr_methods: kwargs['constraints'] = constr + if method in MINIMIZE_METHODS: + kwargs['callback'] = callback + + fun.count = 0 + grad.count = 0 + hess.count = 0 + hessp.count = 0 + fun_constraint.count = 0 + grad_constraint.count = 0 + callback.count = 0 res = cyipopt.minimize_ipopt(fun, x0, method=method, args=(a0,), kwargs={'b': b0}, **kwargs) @@ -212,6 +226,8 @@ def grad_constraint(x, c=0, e=0, d=0): # that we provide are actually being executed; that is, the assertions # are *passing*, not being skipped assert fun.count > 0 + if method in MINIMIZE_METHODS: + assert callback.count > 0 if method in jac_methods: assert grad.count > 0 if method in hess_methods: @@ -223,6 +239,47 @@ def grad_constraint(x, c=0, e=0, d=0): else: np.testing.assert_allclose(res.x[2:], 0, atol=1e-3) + # For methods that support `hessp`, check that it works, too. + if method in hessp_methods: + del kwargs['hess'] + kwargs['hessp'] = hessp + + res = cyipopt.minimize_ipopt(fun, x0, method=method, args=(a0,), + kwargs={'b': b0}, **kwargs) + assert res.success + assert hessp.count > 0 + np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=1e-3) + if method in constr_methods: + np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + else: + np.testing.assert_allclose(res.x[2:], 0, atol=1e-3) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid of Scipy available") +def test_minimize_ipopt_bounds_tol_options(): + # spot check additional cases not tested above + def fun(x): + return x**2 + + x0 = 2. + + # make sure `bounds` is passed to SciPy methods + bounds = (1, 3) + res = cyipopt.minimize_ipopt(fun, x0, method='slsqp', bounds=[(1, 3)]) + np.testing.assert_allclose(res.x, bounds[0]) + + # make sure `tol` is passed to SciPy methods + with pytest.raises(ValueError, match='could not convert string to float'): + cyipopt.minimize_ipopt(fun, x0, method='slsqp', tol='invalid') + + # make sure `options` is passed to SciPy methods + res = cyipopt.minimize_ipopt(fun, x0, method='slsqp') + assert res.nit > 1 + options = dict(maxiter=1) + res = cyipopt.minimize_ipopt(fun, x0, method='slsqp', options=options) + assert res.nit == 1 + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid of Scipy available") From 097b49be5c37ac87cbdf3dfa4b3eb6fcec7b1784 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Thu, 18 May 2023 16:31:53 -0700 Subject: [PATCH 087/170] MAINT: minor amendments --- cyipopt/scipy_interface.py | 2 +- cyipopt/tests/unit/test_scipy_optional.py | 12 ++++++------ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 1fa45631..76ccfd96 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -447,7 +447,7 @@ def minimize_ipopt(fun, and ``max_iter``. All other options are passed directly to Ipopt. See [1]_ for details. callback : callable, optional - This parameter is ignored unless a `method` is one of the SciPy + This parameter is ignored unless `method` is one of the SciPy methods. References diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index f33acd61..6136e194 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -108,16 +108,16 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): functions in minimize_ipopt.""" from scipy.optimize import rosen, rosen_der, rosen_hess - rosen2 = lambda x, a, b=None: rosen(x) - rosen_der2 = lambda x, a, b=None: rosen_der(x) - rosen_hess2 = lambda x, a, b=None: rosen_hess(x) + rosen2 = lambda x, a, b=None: rosen(x)*a*b + rosen_der2 = lambda x, a, b=None: rosen_der(x)*a*b + rosen_hess2 = lambda x, a, b=None: rosen_hess(x)*a*b x0 = [0.0, 0.0] constr = { "type": "ineq", - "fun": lambda x, a, b=None: -x[0]**2 - x[1]**2 + 2, - "jac": lambda x, a, b=None: np.array([-2 * x[0], -2 * x[1]]), - "hess": lambda x, v, a, b=None: -2 * np.eye(2) * v[0], + "fun": lambda x, a, b=None: -x[0]**2 - x[1]**2 + 2*a*b, + "jac": lambda x, a, b=None: np.array([-2 * x[0], -2 * x[1]])*a*b, + "hess": lambda x, v, a, b=None: -2 * np.eye(2) * v[0]*a*b, "args": (1.0, ), "kwargs": {'b': 1.0}, } From ddec62ddb0fae589e66100c04bafde7059903e82 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Thu, 18 May 2023 18:37:01 -0700 Subject: [PATCH 088/170] MAINT: minimize_cyipopt: add input validation --- cyipopt/scipy_interface.py | 41 ++++++++++++++++++ cyipopt/tests/unit/test_scipy_optional.py | 52 +++++++++++++++++++++++ 2 files changed, 93 insertions(+) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index b51df799..1a64c1b7 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -465,6 +465,11 @@ def minimize_ipopt(fun, msg = 'Install SciPy to use the `minimize_ipopt` function.' raise ImportError(msg) + res = _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, + bounds, constraints, tol, callback, options) + (fun, x0, args, kwargs, method, jac, hess, hessp, + bounds, constraints, tol, callback, options) = res + _x0 = np.atleast_1d(x0) lb, ub = get_bounds(bounds) @@ -533,3 +538,39 @@ def minimize_ipopt(fun, nfev=problem.nfev, njev=problem.njev, nit=problem.nit) + +def _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, + bounds, constraints, tol, callback, options): + # basic input validation for minimize_ipopt + if fun is not None and not callable(fun): + raise ValueError('`fun` must be callable.') + x0 = np.asarray(x0)[()] + if not np.issubdtype(x0.dtype, np.number): + raise ValueError('`x0` must be a numeric array.') + if not np.iterable(args): + args = (args,) + kwargs = dict() if kwargs is None else kwargs + if not isinstance(kwargs, dict): + raise ValueError('`kwargs` must be a dictionary.') + if method is not None: # this will be updated when gh-200 is merged + raise NotImplementedError('`method` is not yet supported.`') + if jac is not None and jac not in {True, False} and not callable(jac): + raise ValueError('`jac` must be callable or boolean.') + if hess is not None and not callable(hess): + raise ValueError('`hess` must be callable.') + if hessp is not None: + raise NotImplementedError('`hessp` is not yet supported by Ipopt.`') + # TODO: add input validation for `bounds` and `constraints` when adding + # support for instances of new-style constraints (e.g. `Bounds` and + # `NonlinearConstraint`) and sequences of constraints. + if callback is not None: + raise NotImplementedError('`callback` is not yet supported by Ipopt.`') + if tol is not None: + tol = np.asarray(tol)[()] + if tol.ndim != 0 or not np.issubdtype(tol.dtype, np.number) or tol <= 0: + raise ValueError('`tol` must be a positive scalar.') + options = dict() if options is None else options + if not isinstance(options, dict): + raise ValueError('`options` must be a dictionary.') + return (fun, x0, args, kwargs, method, jac, hess, hessp, + bounds, constraints, tol, callback, options) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 0bdc2bc6..e636a613 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -25,6 +25,58 @@ def test_minimize_ipopt_import_error_if_no_scipy(): cyipopt.minimize_ipopt(None, None) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_minimize_ipopt_input_validation(): + x0 = 1 + def f(x): + return x**2 + + message = "`fun` must be callable." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt('migratory coconuts', x0) + + message = "`x0` must be a numeric array." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, 'spamalot') + + message = "`kwargs` must be a dictionary." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, kwargs='elderberries') + + message = "`method` is not yet supported." + with pytest.raises(NotImplementedError, match=message): + cyipopt.minimize_ipopt(f, x0, method='a newt') + + message = "`jac` must be callable or boolean." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, jac='self-perpetuating autocracy') + + message = "`hess` must be callable." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, hess='farcical aquatic ceremony') + + message = "`hessp` is not yet supported by Ipopt." + with pytest.raises(NotImplementedError, match=message): + cyipopt.minimize_ipopt(f, x0, hessp='shrubbery') + + message = "`callback` is not yet supported by Ipopt." + with pytest.raises(NotImplementedError, match=message): + cyipopt.minimize_ipopt(f, x0, callback='a duck') + + message = "`tol` must be a positive scalar." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, tol=[1, 2, 3]) + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, tol='ni') + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, tol=-1) + + message = "`options` must be a dictionary." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, options='supreme executive power') + + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_if_scipy(): From 661bdcc3abac2583a7f7626fe6600945a4f8ffee Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 19 May 2023 08:18:50 -0700 Subject: [PATCH 089/170] MAINT: minimize_ipopt: split input validation --- cyipopt/scipy_interface.py | 52 +++++++++++++++++++++++--------------- 1 file changed, 31 insertions(+), 21 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 1a64c1b7..b74ac010 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -107,9 +107,26 @@ def __init__(self, raise ImportError() self.obj_hess = None self.last_x = None + + # Input validation of user-provided arguments + if fun is not None and not callable(fun): + raise ValueError('`fun` must be callable.') + if not isinstance(args, tuple): + args = (args,) + kwargs = dict() if kwargs is None else kwargs + if not isinstance(kwargs, dict): + raise ValueError('`kwargs` must be a dictionary.') + if jac is not None and jac not in {True, False} and not callable(jac): + raise ValueError('`jac` must be callable or boolean.') + if hess is not None and not callable(hess): + raise ValueError('`hess` must be callable.') if hessp is not None: - msg = 'Using hessian matrix times an arbitrary vector is not yet implemented!' - raise NotImplementedError(msg) + raise NotImplementedError( + '`hessp` is not yet supported by Ipopt.`') + # TODO: add input validation for `constraints` when adding + # support for instances of new-style constraints (e.g. + # `NonlinearConstraint`) and sequences of constraints. + if hess is not None: self.obj_hess = hess if jac is None: @@ -118,8 +135,7 @@ def __init__(self, elif jac is True: fun = MemoizeJac(fun) jac = fun.derivative - elif not callable(jac): - raise NotImplementedError('jac has to be bool or a function') + self.fun = fun self.jac = jac self.args = args @@ -541,36 +557,30 @@ def minimize_ipopt(fun, def _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, bounds, constraints, tol, callback, options): - # basic input validation for minimize_ipopt - if fun is not None and not callable(fun): - raise ValueError('`fun` must be callable.') + # basic input validation for minimize_ipopt that is not included in + # IpoptProblemWrapper + x0 = np.asarray(x0)[()] if not np.issubdtype(x0.dtype, np.number): raise ValueError('`x0` must be a numeric array.') - if not np.iterable(args): - args = (args,) - kwargs = dict() if kwargs is None else kwargs - if not isinstance(kwargs, dict): - raise ValueError('`kwargs` must be a dictionary.') + if method is not None: # this will be updated when gh-200 is merged raise NotImplementedError('`method` is not yet supported.`') - if jac is not None and jac not in {True, False} and not callable(jac): - raise ValueError('`jac` must be callable or boolean.') - if hess is not None and not callable(hess): - raise ValueError('`hess` must be callable.') - if hessp is not None: - raise NotImplementedError('`hessp` is not yet supported by Ipopt.`') - # TODO: add input validation for `bounds` and `constraints` when adding - # support for instances of new-style constraints (e.g. `Bounds` and - # `NonlinearConstraint`) and sequences of constraints. + + # TODO: add input validation for `bounds` when adding + # support for instances of new-style constraints (e.g. `Bounds`) + if callback is not None: raise NotImplementedError('`callback` is not yet supported by Ipopt.`') + if tol is not None: tol = np.asarray(tol)[()] if tol.ndim != 0 or not np.issubdtype(tol.dtype, np.number) or tol <= 0: raise ValueError('`tol` must be a positive scalar.') + options = dict() if options is None else options if not isinstance(options, dict): raise ValueError('`options` must be a dictionary.') + return (fun, x0, args, kwargs, method, jac, hess, hessp, bounds, constraints, tol, callback, options) From 9a01fa627c2fbda97b026b3bea1aef292a44eca1 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Thu, 18 May 2023 21:57:02 -0700 Subject: [PATCH 090/170] ENH: minimize_ipopt: add support for Bounds --- cyipopt/scipy_interface.py | 61 ++++++++++++++++------- cyipopt/tests/unit/test_scipy_optional.py | 38 +++++++++++++- 2 files changed, 80 insertions(+), 19 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index b74ac010..f0384888 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -19,7 +19,7 @@ else: SCIPY_INSTALLED = True del scipy - from scipy.optimize import approx_fprime + from scipy import optimize import scipy.sparse try: from scipy.optimize import OptimizeResult @@ -130,7 +130,7 @@ def __init__(self, if hess is not None: self.obj_hess = hess if jac is None: - jac = lambda x0, *args, **kwargs: approx_fprime( + jac = lambda x0, *args, **kwargs: optimize.approx_fprime( x0, fun, eps, *args, **kwargs) elif jac is True: fun = MemoizeJac(fun) @@ -157,7 +157,7 @@ def __init__(self, con_hessian = con.get('hess', None) con_kwargs = con.get('kwargs', {}) if con_jac is None: - con_jac = lambda x0, *args, **kwargs: approx_fprime( + con_jac = lambda x0, *args, **kwargs: optimize.approx_fprime( x0, con_fun, eps, *args, **kwargs) elif con_jac is True: con_fun = MemoizeJac(con_fun) @@ -486,13 +486,11 @@ def minimize_ipopt(fun, (fun, x0, args, kwargs, method, jac, hess, hessp, bounds, constraints, tol, callback, options) = res - _x0 = np.atleast_1d(x0) - - lb, ub = get_bounds(bounds) - cl, cu = get_constraint_bounds(constraints, _x0) - con_dims = get_constraint_dimensions(constraints, _x0) + lb, ub = bounds + cl, cu = get_constraint_bounds(constraints, x0) + con_dims = get_constraint_dimensions(constraints, x0) sparse_jacs, jac_nnz_row, jac_nnz_col = _get_sparse_jacobian_structure( - constraints, _x0) + constraints, x0) problem = IpoptProblemWrapper(fun, args=args, @@ -510,7 +508,7 @@ def minimize_ipopt(fun, if options is None: options = {} - nlp = cyipopt.Problem(n=len(_x0), + nlp = cyipopt.Problem(n=len(x0), m=len(cl), problem_obj=problem, lb=lb, @@ -540,10 +538,7 @@ def minimize_ipopt(fun, msg = 'Invalid option for IPOPT: {0}: {1} (Original message: "{2}")' raise TypeError(msg.format(option, value, e)) - x, info = nlp.solve(_x0) - - if np.asarray(x0).shape == (): - x = x[0] + x, info = nlp.solve(x0) return OptimizeResult(x=x, success=info['status'] == 0, @@ -555,20 +550,50 @@ def minimize_ipopt(fun, njev=problem.njev, nit=problem.nit) + def _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, bounds, constraints, tol, callback, options): # basic input validation for minimize_ipopt that is not included in # IpoptProblemWrapper - - x0 = np.asarray(x0)[()] + x0 = np.atleast_1d(x0) if not np.issubdtype(x0.dtype, np.number): raise ValueError('`x0` must be a numeric array.') if method is not None: # this will be updated when gh-200 is merged raise NotImplementedError('`method` is not yet supported.`') - # TODO: add input validation for `bounds` when adding - # support for instances of new-style constraints (e.g. `Bounds`) + # Handle bounds that are either sequences (of sequences) or instances of + # `optimize.Bounds`. + if bounds is None: + bounds = [-np.inf, np.inf] + + if isinstance(bounds, optimize.Bounds): + lb, ub = bounds.lb, bounds.ub + else: + bounds = np.atleast_2d(bounds) + if bounds.shape[1] != 2: + raise ValueError("`bounds` must specify both lower and upper " + "limits for each decision variable.") + lb, ub = bounds.T + + try: + lb, ub, x0 = np.broadcast_arrays(lb, ub, x0) + except ValueError: + raise ValueError("The number of lower bounds, upper bounds, and " + "decision variables must be equal or broadcastable.") + + try: + lb = lb.astype(np.float64) + ub = ub.astype(np.float64) + except ValueError: + raise ValueError("The bounds must be numeric.") + + # Nones turn into NaNs above. Previously, NaNs caused Ipopt to hang, so + # I'm not concerned about turning them into infs. + lb[np.isnan(lb)] = -np.inf + ub[np.isnan(ub)] = np.inf + + bounds = lb, ub if callback is not None: raise NotImplementedError('`callback` is not yet supported by Ipopt.`') diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index e636a613..a72a4ce4 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -28,9 +28,11 @@ def test_minimize_ipopt_import_error_if_no_scipy(): @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_input_validation(): + from scipy import optimize + x0 = 1 def f(x): - return x**2 + return x @ x message = "`fun` must be callable." with pytest.raises(ValueError, match=message): @@ -60,6 +62,18 @@ def f(x): with pytest.raises(NotImplementedError, match=message): cyipopt.minimize_ipopt(f, x0, hessp='shrubbery') + message = "`bounds` must specify both lower and upper..." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, [1, 2], bounds=1) + + message = "The number of lower bounds, upper bounds..." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, [1, 2], bounds=[(1, 2), (3, 4), (5, 6)]) + + message = "The bounds must be numeric." + with pytest.raises(ValueError, match=message): + cyipopt.minimize_ipopt(f, x0, bounds=[['low', 'high']]) + message = "`callback` is not yet supported by Ipopt." with pytest.raises(NotImplementedError, match=message): cyipopt.minimize_ipopt(f, x0, callback='a duck') @@ -365,3 +379,25 @@ def con_ineq_hess(x, v): assert res.get("success") is True expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) np.testing.assert_allclose(res.get("x"), expected_res) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_minimize_ipopt_bounds(): + # Test that `minimize_ipopt` accepts bounds sequences or `optimize.Bounds` + from scipy import optimize + + def f(x): + return x @ x + + # accept size 2 sequence containing same bounds for all variables + res = cyipopt.minimize_ipopt(f, [2, 3], bounds=[1, 10]) + np.testing.assert_allclose(res.x, [1, 1]) + + res = cyipopt.minimize_ipopt(f, [2, 3], bounds=[None, None]) + np.testing.assert_allclose(res.x, [0, 0], atol=1e-6) + + # accept instance of Bounds + bounds = optimize.Bounds(lb=0.5, ub=[1, 2]) + res = cyipopt.minimize_ipopt(f, [2, 3], bounds=bounds) + np.testing.assert_allclose(res.x, [0.5, 0.5]) From 3b2b273e5fa647dd4be2b7661182733c5ba8425b Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 19 May 2023 21:26:40 -0700 Subject: [PATCH 091/170] MAINT: minimize_ipopt: fix late binding bug --- cyipopt/scipy_interface.py | 7 +++++-- cyipopt/tests/unit/test_scipy_optional.py | 20 ++++++++++++++++++++ 2 files changed, 25 insertions(+), 2 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index b74ac010..4843c463 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -157,8 +157,11 @@ def __init__(self, con_hessian = con.get('hess', None) con_kwargs = con.get('kwargs', {}) if con_jac is None: - con_jac = lambda x0, *args, **kwargs: approx_fprime( - x0, con_fun, eps, *args, **kwargs) + # beware of late binding! + def con_jac(x, *args, con_fun=con_fun, **kwargs): + def wrapped(x): + return con_fun(x, *args, **kwargs) + return approx_fprime(x, wrapped, eps) elif con_jac is True: con_fun = MemoizeJac(con_fun) con_jac = con_fun.derivative diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index e636a613..be690028 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -365,3 +365,23 @@ def con_ineq_hess(x, v): assert res.get("success") is True expected_res = np.array([0.99999999, 4.74299964, 3.82114998, 1.3794083]) np.testing.assert_allclose(res.get("x"), expected_res) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_minimize_late_binding_bug(): + # `IpoptProblemWrapper` had a late binding bug when constraint Jacobians + # were defined with `optimize.approx_fprime`. Check that this is resolved. + from scipy.optimize import minimize + + fun = lambda x: (x[0] - 1)**2 + (x[1] - 2.5)**2 + cons = ({'type': 'ineq', 'fun': lambda x: x[0] - 2 * x[1] + 2}, + {'type': 'ineq', 'fun': lambda x: -x[0] - 2 * x[1] + 6}, + {'type': 'ineq', 'fun': lambda x: -x[0] + 2 * x[1] + 2}) + bnds = ((0, None), (0, None)) + + res = cyipopt.minimize_ipopt(fun, (2, 0), bounds=bnds, constraints=cons) + ref = minimize(fun, (2, 0), bounds=bnds, constraints=cons) + assert res.success + np.testing.assert_allclose(res.x, ref.x) + np.testing.assert_allclose(res.fun, ref.fun) From ff125fba9f10f15c3599caeca994a53c48389702 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sat, 20 May 2023 10:00:24 -0700 Subject: [PATCH 092/170] TST: minimize_ipopt: adjust tolerances, import method names from SciPy --- cyipopt/tests/unit/test_scipy_optional.py | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 6136e194..cd30b0f1 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -15,9 +15,10 @@ import cyipopt # Hard-code rather than importing from scipy.optimize._minimize in a try/except -MINIMIZE_METHODS = ['nelder-mead', 'powell', 'cg', 'bfgs', 'newton-cg', - 'l-bfgs-b', 'tnc', 'cobyla', 'slsqp', 'trust-constr', - 'dogleg', 'trust-ncg', 'trust-exact', 'trust-krylov'] +try: + from scipy.optimize._minimize import MINIMIZE_METHODS +except ImportError: + MINIMIZE_METHODS = [] @pytest.mark.skipif("scipy" in sys.modules, reason="Test only valid if no Scipy available.") @@ -141,6 +142,7 @@ def test_minimize_ipopt_jac_hessians_constraints_with_arg_kwargs(): def test_minimize_ipopt_jac_with_scipy_methods(method): x0 = [0] * 4 a0, b0, c0, d0 = 1, 2, 3, 4 + atol, rtol = 5e-5, 5e-5 def fun(x, a=0, e=0, b=0): assert a == a0 @@ -220,7 +222,7 @@ def callback(*args, **kwargs): kwargs={'b': b0}, **kwargs) assert res.success - np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=1e-3) + np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=rtol) # confirm that the test covers what we think it does: all the functions # that we provide are actually being executed; that is, the assertions @@ -235,9 +237,9 @@ def callback(*args, **kwargs): if method in constr_methods: assert fun_constraint.count > 0 assert grad_constraint.count > 0 - np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=rtol) else: - np.testing.assert_allclose(res.x[2:], 0, atol=1e-3) + np.testing.assert_allclose(res.x[2:], 0, atol=atol) # For methods that support `hessp`, check that it works, too. if method in hessp_methods: @@ -248,11 +250,11 @@ def callback(*args, **kwargs): kwargs={'b': b0}, **kwargs) assert res.success assert hessp.count > 0 - np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=1e-3) + np.testing.assert_allclose(res.x[:2], [a0, b0], rtol=rtol) if method in constr_methods: - np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=1e-3) + np.testing.assert_allclose(res.x[2:], [c0, d0], rtol=rtol) else: - np.testing.assert_allclose(res.x[2:], 0, atol=1e-3) + np.testing.assert_allclose(res.x[2:], 0, atol=atol) @pytest.mark.skipif("scipy" not in sys.modules, From 6bdd3c5fe808c79a44e1dab9d861633557252520 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 28 May 2023 14:55:20 -0700 Subject: [PATCH 093/170] TST: minimize_ipopt: add tests from SciPy --- .../tests/unit/test_scipy_ipopt_from_scipy.py | 608 ++++++++++++++++++ 1 file changed, 608 insertions(+) create mode 100644 cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py new file mode 100644 index 00000000..432544f5 --- /dev/null +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -0,0 +1,608 @@ +""" +Unit test for SLSQP optimization. +""" +from numpy.testing import (assert_, assert_array_almost_equal, + assert_allclose, assert_equal) +from pytest import raises as assert_raises +import pytest +import numpy as np + +from scipy.optimize import fmin_slsqp, minimize, Bounds, NonlinearConstraint + + +class MyCallBack: + """pass a custom callback function + + This makes sure it's being used. + """ + def __init__(self): + self.been_called = False + self.ncalls = 0 + + def __call__(self, x): + self.been_called = True + self.ncalls += 1 + + +class TestSLSQP: + """ + Test SLSQP algorithm using Example 14.4 from Numerical Methods for + Engineers by Steven Chapra and Raymond Canale. + This example maximizes the function f(x) = 2*x*y + 2*x - x**2 - 2*y**2, + which has a maximum at x=2, y=1. + """ + def setup_method(self): + self.opts = {'disp': False} + + def fun(self, d, sign=1.0): + """ + Arguments: + d - A list of two elements, where d[0] represents x and d[1] represents y + in the following equation. + sign - A multiplier for f. Since we want to optimize it, and the SciPy + optimizers can only minimize functions, we need to multiply it by + -1 to achieve the desired solution + Returns: + 2*x*y + 2*x - x**2 - 2*y**2 + + """ + x = d[0] + y = d[1] + return sign*(2*x*y + 2*x - x**2 - 2*y**2) + + def jac(self, d, sign=1.0): + """ + This is the derivative of fun, returning a NumPy array + representing df/dx and df/dy. + + """ + x = d[0] + y = d[1] + dfdx = sign*(-2*x + 2*y + 2) + dfdy = sign*(2*x - 4*y) + return np.array([dfdx, dfdy], float) + + def fun_and_jac(self, d, sign=1.0): + return self.fun(d, sign), self.jac(d, sign) + + def f_eqcon(self, x, sign=1.0): + """ Equality constraint """ + return np.array([x[0] - x[1]]) + + def fprime_eqcon(self, x, sign=1.0): + """ Equality constraint, derivative """ + return np.array([[1, -1]]) + + def f_eqcon_scalar(self, x, sign=1.0): + """ Scalar equality constraint """ + return self.f_eqcon(x, sign)[0] + + def fprime_eqcon_scalar(self, x, sign=1.0): + """ Scalar equality constraint, derivative """ + return self.fprime_eqcon(x, sign)[0].tolist() + + def f_ieqcon(self, x, sign=1.0): + """ Inequality constraint """ + return np.array([x[0] - x[1] - 1.0]) + + def fprime_ieqcon(self, x, sign=1.0): + """ Inequality constraint, derivative """ + return np.array([[1, -1]]) + + def f_ieqcon2(self, x): + """ Vector inequality constraint """ + return np.asarray(x) + + def fprime_ieqcon2(self, x): + """ Vector inequality constraint, derivative """ + return np.identity(x.shape[0]) + + # minimize + def test_minimize_unbounded_approximated(self): + # Minimize, method='SLSQP': unbounded, approximated jacobian. + jacs = [None, False, '2-point', '3-point'] + for jac in jacs: + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + jac=jac, method='SLSQP', + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1]) + + def test_minimize_unbounded_given(self): + # Minimize, method='SLSQP': unbounded, given Jacobian. + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + jac=self.jac, method='SLSQP', options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1]) + + def test_minimize_bounded_approximated(self): + # Minimize, method='SLSQP': bounded, approximated jacobian. + jacs = [None, False, '2-point', '3-point'] + for jac in jacs: + with np.errstate(invalid='ignore'): + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + jac=jac, + bounds=((2.5, None), (None, 0.5)), + method='SLSQP', options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2.5, 0.5]) + assert_(2.5 <= res.x[0]) + assert_(res.x[1] <= 0.5) + + def test_minimize_unbounded_combined(self): + # Minimize, method='SLSQP': unbounded, combined function and Jacobian. + res = minimize(self.fun_and_jac, [-1.0, 1.0], args=(-1.0, ), + jac=True, method='SLSQP', options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1]) + + def test_minimize_equality_approximated(self): + # Minimize with method='SLSQP': equality constraint, approx. jacobian. + jacs = [None, False, '2-point', '3-point'] + for jac in jacs: + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + jac=jac, + constraints={'type': 'eq', + 'fun': self.f_eqcon, + 'args': (-1.0, )}, + method='SLSQP', options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [1, 1]) + + def test_minimize_equality_given(self): + # Minimize with method='SLSQP': equality constraint, given Jacobian. + res = minimize(self.fun, [-1.0, 1.0], jac=self.jac, + method='SLSQP', args=(-1.0,), + constraints={'type': 'eq', 'fun':self.f_eqcon, + 'args': (-1.0, )}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [1, 1]) + + def test_minimize_equality_given2(self): + # Minimize with method='SLSQP': equality constraint, given Jacobian + # for fun and const. + res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + jac=self.jac, args=(-1.0,), + constraints={'type': 'eq', + 'fun': self.f_eqcon, + 'args': (-1.0, ), + 'jac': self.fprime_eqcon}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [1, 1]) + + def test_minimize_equality_given_cons_scalar(self): + # Minimize with method='SLSQP': scalar equality constraint, given + # Jacobian for fun and const. + res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + jac=self.jac, args=(-1.0,), + constraints={'type': 'eq', + 'fun': self.f_eqcon_scalar, + 'args': (-1.0, ), + 'jac': self.fprime_eqcon_scalar}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [1, 1]) + + def test_minimize_inequality_given(self): + # Minimize with method='SLSQP': inequality constraint, given Jacobian. + res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + jac=self.jac, args=(-1.0, ), + constraints={'type': 'ineq', + 'fun': self.f_ieqcon, + 'args': (-1.0, )}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1], atol=1e-3) + + def test_minimize_inequality_given_vector_constraints(self): + # Minimize with method='SLSQP': vector inequality constraint, given + # Jacobian. + res = minimize(self.fun, [-1.0, 1.0], jac=self.jac, + method='SLSQP', args=(-1.0,), + constraints={'type': 'ineq', + 'fun': self.f_ieqcon2, + 'jac': self.fprime_ieqcon2}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1]) + + def test_minimize_bounded_constraint(self): + # when the constraint makes the solver go up against a parameter + # bound make sure that the numerical differentiation of the + # jacobian doesn't try to exceed that bound using a finite difference. + # gh11403 + def c(x): + assert 0 <= x[0] <= 1 and 0 <= x[1] <= 1, x + return x[0] ** 0.5 + x[1] + + def f(x): + assert 0 <= x[0] <= 1 and 0 <= x[1] <= 1, x + return -x[0] ** 2 + x[1] ** 2 + + cns = [NonlinearConstraint(c, 0, 1.5)] + x0 = np.asarray([0.9, 0.5]) + bnd = Bounds([0., 0.], [1.0, 1.0]) + minimize(f, x0, method='SLSQP', bounds=bnd, constraints=cns) + + def test_minimize_bound_equality_given2(self): + # Minimize with method='SLSQP': bounds, eq. const., given jac. for + # fun. and const. + res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + jac=self.jac, args=(-1.0, ), + bounds=[(-0.8, 1.), (-1, 0.8)], + constraints={'type': 'eq', + 'fun': self.f_eqcon, + 'args': (-1.0, ), + 'jac': self.fprime_eqcon}, + options=self.opts) + assert_(res['success'], res['message']) + assert_allclose(res.x, [0.8, 0.8], atol=1e-3) + assert_(-0.8 <= res.x[0] <= 1) + assert_(-1 <= res.x[1] <= 0.8) + + # fmin_slsqp + def test_unbounded_approximated(self): + # SLSQP: unbounded, approximated Jacobian. + res = fmin_slsqp(self.fun, [-1.0, 1.0], args=(-1.0, ), + iprint = 0, full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [2, 1]) + + def test_unbounded_given(self): + # SLSQP: unbounded, given Jacobian. + res = fmin_slsqp(self.fun, [-1.0, 1.0], args=(-1.0, ), + fprime = self.jac, iprint = 0, + full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [2, 1]) + + def test_equality_approximated(self): + # SLSQP: equality constraint, approximated Jacobian. + res = fmin_slsqp(self.fun,[-1.0,1.0], args=(-1.0,), + eqcons = [self.f_eqcon], + iprint = 0, full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [1, 1]) + + def test_equality_given(self): + # SLSQP: equality constraint, given Jacobian. + res = fmin_slsqp(self.fun, [-1.0, 1.0], + fprime=self.jac, args=(-1.0,), + eqcons = [self.f_eqcon], iprint = 0, + full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [1, 1]) + + def test_equality_given2(self): + # SLSQP: equality constraint, given Jacobian for fun and const. + res = fmin_slsqp(self.fun, [-1.0, 1.0], + fprime=self.jac, args=(-1.0,), + f_eqcons = self.f_eqcon, + fprime_eqcons = self.fprime_eqcon, + iprint = 0, + full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [1, 1]) + + def test_inequality_given(self): + # SLSQP: inequality constraint, given Jacobian. + res = fmin_slsqp(self.fun, [-1.0, 1.0], + fprime=self.jac, args=(-1.0, ), + ieqcons = [self.f_ieqcon], + iprint = 0, full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [2, 1], decimal=3) + + def test_bound_equality_given2(self): + # SLSQP: bounds, eq. const., given jac. for fun. and const. + res = fmin_slsqp(self.fun, [-1.0, 1.0], + fprime=self.jac, args=(-1.0, ), + bounds = [(-0.8, 1.), (-1, 0.8)], + f_eqcons = self.f_eqcon, + fprime_eqcons = self.fprime_eqcon, + iprint = 0, full_output = 1) + x, fx, its, imode, smode = res + assert_(imode == 0, imode) + assert_array_almost_equal(x, [0.8, 0.8], decimal=3) + assert_(-0.8 <= x[0] <= 1) + assert_(-1 <= x[1] <= 0.8) + + def test_scalar_constraints(self): + # Regression test for gh-2182 + x = fmin_slsqp(lambda z: z**2, [3.], + ieqcons=[lambda z: z[0] - 1], + iprint=0) + assert_array_almost_equal(x, [1.]) + + x = fmin_slsqp(lambda z: z**2, [3.], + f_ieqcons=lambda z: [z[0] - 1], + iprint=0) + assert_array_almost_equal(x, [1.]) + + def test_integer_bounds(self): + # This should not raise an exception + fmin_slsqp(lambda z: z**2 - 1, [0], bounds=[[0, 1]], iprint=0) + + def test_array_bounds(self): + # NumPy used to treat n-dimensional 1-element arrays as scalars + # in some cases. The handling of `bounds` by `fmin_slsqp` still + # supports this behavior. + bounds = [(-np.inf, np.inf), (np.array([2]), np.array([3]))] + x = fmin_slsqp(lambda z: np.sum(z**2 - 1), [2.5, 2.5], bounds=bounds, + iprint=0) + assert_array_almost_equal(x, [0, 2]) + + def test_obj_must_return_scalar(self): + # Regression test for Github Issue #5433 + # If objective function does not return a scalar, raises ValueError + with assert_raises(ValueError): + fmin_slsqp(lambda x: [0, 1], [1, 2, 3]) + + def test_obj_returns_scalar_in_list(self): + # Test for Github Issue #5433 and PR #6691 + # Objective function should be able to return length-1 Python list + # containing the scalar + fmin_slsqp(lambda x: [0], [1, 2, 3], iprint=0) + + def test_callback(self): + # Minimize, method='SLSQP': unbounded, approximated jacobian. Check for callback + callback = MyCallBack() + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + method='SLSQP', callback=callback, options=self.opts) + assert_(res['success'], res['message']) + assert_(callback.been_called) + assert_equal(callback.ncalls, res['nit']) + + def test_inconsistent_linearization(self): + # SLSQP must be able to solve this problem, even if the + # linearized problem at the starting point is infeasible. + + # Linearized constraints are + # + # 2*x0[0]*x[0] >= 1 + # + # At x0 = [0, 1], the second constraint is clearly infeasible. + # This triggers a call with n2==1 in the LSQ subroutine. + x = [0, 1] + def f1(x): + return x[0] + x[1] - 2 + def f2(x): + return x[0] ** 2 - 1 + sol = minimize( + lambda x: x[0]**2 + x[1]**2, + x, + constraints=({'type':'eq','fun': f1}, + {'type':'ineq','fun': f2}), + bounds=((0,None), (0,None)), + method='SLSQP') + x = sol.x + + assert_allclose(f1(x), 0, atol=1e-8) + assert_(f2(x) >= -1e-8) + assert_(sol.success, sol) + + def test_regression_5743(self): + # SLSQP must not indicate success for this problem, + # which is infeasible. + x = [1, 2] + sol = minimize( + lambda x: x[0]**2 + x[1]**2, + x, + constraints=({'type':'eq','fun': lambda x: x[0]+x[1]-1}, + {'type':'ineq','fun': lambda x: x[0]-2}), + bounds=((0,None), (0,None)), + method='SLSQP') + assert_(not sol.success, sol) + + def test_gh_6676(self): + def func(x): + return (x[0] - 1)**2 + 2*(x[1] - 1)**2 + 0.5*(x[2] - 1)**2 + + sol = minimize(func, [0, 0, 0], method='SLSQP') + assert_(sol.jac.shape == (3,)) + + def test_invalid_bounds(self): + # Raise correct error when lower bound is greater than upper bound. + # See Github issue 6875. + bounds_list = [ + ((1, 2), (2, 1)), + ((2, 1), (1, 2)), + ((2, 1), (2, 1)), + ((np.inf, 0), (np.inf, 0)), + ((1, -np.inf), (0, 1)), + ] + for bounds in bounds_list: + with assert_raises(ValueError): + minimize(self.fun, [-1.0, 1.0], bounds=bounds, method='SLSQP') + + def test_bounds_clipping(self): + # + # SLSQP returns bogus results for initial guess out of bounds, gh-6859 + # + def f(x): + return (x[0] - 1)**2 + + sol = minimize(f, [10], method='slsqp', bounds=[(None, 0)]) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [-10], method='slsqp', bounds=[(2, None)]) + assert_(sol.success) + assert_allclose(sol.x, 2, atol=1e-10) + + sol = minimize(f, [-10], method='slsqp', bounds=[(None, 0)]) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [10], method='slsqp', bounds=[(2, None)]) + assert_(sol.success) + assert_allclose(sol.x, 2, atol=1e-10) + + sol = minimize(f, [-0.5], method='slsqp', bounds=[(-1, 0)]) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [10], method='slsqp', bounds=[(-1, 0)]) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + def test_infeasible_initial(self): + # Check SLSQP behavior with infeasible initial point + def f(x): + x, = x + return x*x - 2*x + 1 + + cons_u = [{'type': 'ineq', 'fun': lambda x: 0 - x}] + cons_l = [{'type': 'ineq', 'fun': lambda x: x - 2}] + cons_ul = [{'type': 'ineq', 'fun': lambda x: 0 - x}, + {'type': 'ineq', 'fun': lambda x: x + 1}] + + sol = minimize(f, [10], method='slsqp', constraints=cons_u) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [-10], method='slsqp', constraints=cons_l) + assert_(sol.success) + assert_allclose(sol.x, 2, atol=1e-10) + + sol = minimize(f, [-10], method='slsqp', constraints=cons_u) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [10], method='slsqp', constraints=cons_l) + assert_(sol.success) + assert_allclose(sol.x, 2, atol=1e-10) + + sol = minimize(f, [-0.5], method='slsqp', constraints=cons_ul) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + sol = minimize(f, [10], method='slsqp', constraints=cons_ul) + assert_(sol.success) + assert_allclose(sol.x, 0, atol=1e-10) + + def test_inconsistent_inequalities(self): + # gh-7618 + + def cost(x): + return -1 * x[0] + 4 * x[1] + + def ineqcons1(x): + return x[1] - x[0] - 1 + + def ineqcons2(x): + return x[0] - x[1] + + # The inequalities are inconsistent, so no solution can exist: + # + # x1 >= x0 + 1 + # x0 >= x1 + + x0 = (1,5) + bounds = ((-5, 5), (-5, 5)) + cons = (dict(type='ineq', fun=ineqcons1), dict(type='ineq', fun=ineqcons2)) + res = minimize(cost, x0, method='SLSQP', bounds=bounds, constraints=cons) + + assert_(not res.success) + + def test_new_bounds_type(self): + def f(x): + return x[0] ** 2 + x[1] ** 2 + bounds = Bounds([1, 0], [np.inf, np.inf]) + sol = minimize(f, [0, 0], method='slsqp', bounds=bounds) + assert_(sol.success) + assert_allclose(sol.x, [1, 0]) + + def test_nested_minimization(self): + + class NestedProblem(): + + def __init__(self): + self.F_outer_count = 0 + + def F_outer(self, x): + self.F_outer_count += 1 + if self.F_outer_count > 1000: + raise Exception("Nested minimization failed to terminate.") + inner_res = minimize(self.F_inner, (3, 4), method="SLSQP") + assert_(inner_res.success) + assert_allclose(inner_res.x, [1, 1]) + return x[0]**2 + x[1]**2 + x[2]**2 + + def F_inner(self, x): + return (x[0] - 1)**2 + (x[1] - 1)**2 + + def solve(self): + outer_res = minimize(self.F_outer, (5, 5, 5), method="SLSQP") + assert_(outer_res.success) + assert_allclose(outer_res.x, [0, 0, 0]) + + problem = NestedProblem() + problem.solve() + + def test_gh1758(self): + # the test suggested in gh1758 + # https://nlopt.readthedocs.io/en/latest/NLopt_Tutorial/ + # implement two equality constraints, in R^2. + def fun(x): + return np.sqrt(x[1]) + + def f_eqcon(x): + """ Equality constraint """ + return x[1] - (2 * x[0]) ** 3 + + def f_eqcon2(x): + """ Equality constraint """ + return x[1] - (-x[0] + 1) ** 3 + + c1 = {'type': 'eq', 'fun': f_eqcon} + c2 = {'type': 'eq', 'fun': f_eqcon2} + + res = minimize(fun, [8, 0.25], method='SLSQP', + constraints=[c1, c2], bounds=[(-0.5, 1), (0, 8)]) + + np.testing.assert_allclose(res.fun, 0.5443310539518) + np.testing.assert_allclose(res.x, [0.33333333, 0.2962963]) + assert res.success + + def test_gh9640(self): + np.random.seed(10) + cons = ({'type': 'ineq', 'fun': lambda x: -x[0] - x[1] - 3}, + {'type': 'ineq', 'fun': lambda x: x[1] + x[2] - 2}) + bnds = ((-2, 2), (-2, 2), (-2, 2)) + + def target(x): + return 1 + x0 = [-1.8869783504471584, -0.640096352696244, -0.8174212253407696] + res = minimize(target, x0, method='SLSQP', bounds=bnds, constraints=cons, + options={'disp':False, 'maxiter':10000}) + + # The problem is infeasible, so it cannot succeed + assert not res.success + + def test_parameters_stay_within_bounds(self): + # gh11403. For some problems the SLSQP Fortran code suggests a step + # outside one of the lower/upper bounds. When this happens + # approx_derivative complains because it's being asked to evaluate + # a gradient outside its domain. + np.random.seed(1) + bounds = Bounds(np.array([0.1]), np.array([1.0])) + n_inputs = len(bounds.lb) + x0 = np.array(bounds.lb + (bounds.ub - bounds.lb) * + np.random.random(n_inputs)) + + def f(x): + assert (x >= bounds.lb).all() + return np.linalg.norm(x) + + with pytest.warns(RuntimeWarning, match='x were outside bounds'): + res = minimize(f, x0, method='SLSQP', bounds=bounds) + assert res.success From 270af6aa0635068ef234f318cd9d3c16d31def40 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 28 May 2023 15:01:23 -0700 Subject: [PATCH 094/170] TST: minimize_ipopt: make new tests pass --- cyipopt/scipy_interface.py | 9 +- .../tests/unit/test_scipy_ipopt_from_scipy.py | 357 +++++------------- 2 files changed, 107 insertions(+), 259 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index f0384888..8634c43c 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -129,7 +129,7 @@ def __init__(self, if hess is not None: self.obj_hess = hess - if jac is None: + if not jac: jac = lambda x0, *args, **kwargs: optimize.approx_fprime( x0, fun, eps, *args, **kwargs) elif jac is True: @@ -522,7 +522,9 @@ def minimize_ipopt(fun, # Rename some default scipy options replace_option(options, b'disp', b'print_level') replace_option(options, b'maxiter', b'max_iter') - if b'print_level' not in options: + if getattr(options, 'print_level', False) is True: + options[b'print_level'] = 1 + else: options[b'print_level'] = 0 if b'tol' not in options: options[b'tol'] = tol or 1e-8 @@ -595,6 +597,9 @@ def _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, bounds = lb, ub + constraints = optimize._minimize.standardize_constraints(constraints, x0, + 'old') + if callback is not None: raise NotImplementedError('`callback` is not yet supported by Ipopt.`') diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 432544f5..2193a12f 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -1,13 +1,12 @@ """ -Unit test for SLSQP optimization. +Unit tests written for scipy.optimize.minimize method='SLSQP'; +adapted for minimize_ipopt """ -from numpy.testing import (assert_, assert_array_almost_equal, - assert_allclose, assert_equal) -from pytest import raises as assert_raises -import pytest +from numpy.testing import (assert_, assert_allclose) import numpy as np -from scipy.optimize import fmin_slsqp, minimize, Bounds, NonlinearConstraint +from scipy.optimize import Bounds, NonlinearConstraint +from cyipopt import minimize_ipopt as minimize class MyCallBack: @@ -31,6 +30,8 @@ class TestSLSQP: This example maximizes the function f(x) = 2*x*y + 2*x - x**2 - 2*y**2, which has a maximum at x=2, y=1. """ + atol = 1e-7 + def setup_method(self): self.opts = {'disp': False} @@ -99,60 +100,60 @@ def fprime_ieqcon2(self, x): # minimize def test_minimize_unbounded_approximated(self): - # Minimize, method='SLSQP': unbounded, approximated jacobian. - jacs = [None, False, '2-point', '3-point'] + # Minimize, method=None: unbounded, approximated jacobian. + jacs = [None, False] for jac in jacs: res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), - jac=jac, method='SLSQP', + jac=jac, method=None, options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [2, 1]) def test_minimize_unbounded_given(self): - # Minimize, method='SLSQP': unbounded, given Jacobian. + # Minimize, method=None: unbounded, given Jacobian. res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), - jac=self.jac, method='SLSQP', options=self.opts) + jac=self.jac, method=None, options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [2, 1]) def test_minimize_bounded_approximated(self): - # Minimize, method='SLSQP': bounded, approximated jacobian. - jacs = [None, False, '2-point', '3-point'] + # Minimize, method=None: bounded, approximated jacobian. + jacs = [None, False] for jac in jacs: with np.errstate(invalid='ignore'): res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), jac=jac, bounds=((2.5, None), (None, 0.5)), - method='SLSQP', options=self.opts) + method=None, options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [2.5, 0.5]) - assert_(2.5 <= res.x[0]) - assert_(res.x[1] <= 0.5) + assert_(2.5 - self.atol <= res.x[0]) + assert_(res.x[1] - self.atol <= 0.5) def test_minimize_unbounded_combined(self): - # Minimize, method='SLSQP': unbounded, combined function and Jacobian. + # Minimize, method=None: unbounded, combined function and Jacobian. res = minimize(self.fun_and_jac, [-1.0, 1.0], args=(-1.0, ), - jac=True, method='SLSQP', options=self.opts) + jac=True, method=None, options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [2, 1]) def test_minimize_equality_approximated(self): - # Minimize with method='SLSQP': equality constraint, approx. jacobian. - jacs = [None, False, '2-point', '3-point'] + # Minimize with method=None: equality constraint, approx. jacobian. + jacs = [None, False] for jac in jacs: res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), jac=jac, constraints={'type': 'eq', 'fun': self.f_eqcon, 'args': (-1.0, )}, - method='SLSQP', options=self.opts) + method=None, options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [1, 1]) def test_minimize_equality_given(self): - # Minimize with method='SLSQP': equality constraint, given Jacobian. + # Minimize with method=None: equality constraint, given Jacobian. res = minimize(self.fun, [-1.0, 1.0], jac=self.jac, - method='SLSQP', args=(-1.0,), + method=None, args=(-1.0,), constraints={'type': 'eq', 'fun':self.f_eqcon, 'args': (-1.0, )}, options=self.opts) @@ -160,9 +161,9 @@ def test_minimize_equality_given(self): assert_allclose(res.x, [1, 1]) def test_minimize_equality_given2(self): - # Minimize with method='SLSQP': equality constraint, given Jacobian + # Minimize with method=None: equality constraint, given Jacobian # for fun and const. - res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + res = minimize(self.fun, [-1.0, 1.0], method=None, jac=self.jac, args=(-1.0,), constraints={'type': 'eq', 'fun': self.f_eqcon, @@ -173,9 +174,9 @@ def test_minimize_equality_given2(self): assert_allclose(res.x, [1, 1]) def test_minimize_equality_given_cons_scalar(self): - # Minimize with method='SLSQP': scalar equality constraint, given + # Minimize with method=None: scalar equality constraint, given # Jacobian for fun and const. - res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + res = minimize(self.fun, [-1.0, 1.0], method=None, jac=self.jac, args=(-1.0,), constraints={'type': 'eq', 'fun': self.f_eqcon_scalar, @@ -186,8 +187,8 @@ def test_minimize_equality_given_cons_scalar(self): assert_allclose(res.x, [1, 1]) def test_minimize_inequality_given(self): - # Minimize with method='SLSQP': inequality constraint, given Jacobian. - res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + # Minimize with method=None: inequality constraint, given Jacobian. + res = minimize(self.fun, [-1.0, 1.0], method=None, jac=self.jac, args=(-1.0, ), constraints={'type': 'ineq', 'fun': self.f_ieqcon, @@ -197,10 +198,10 @@ def test_minimize_inequality_given(self): assert_allclose(res.x, [2, 1], atol=1e-3) def test_minimize_inequality_given_vector_constraints(self): - # Minimize with method='SLSQP': vector inequality constraint, given + # Minimize with method=None: vector inequality constraint, given # Jacobian. res = minimize(self.fun, [-1.0, 1.0], jac=self.jac, - method='SLSQP', args=(-1.0,), + method=None, args=(-1.0,), constraints={'type': 'ineq', 'fun': self.f_ieqcon2, 'jac': self.fprime_ieqcon2}, @@ -208,28 +209,10 @@ def test_minimize_inequality_given_vector_constraints(self): assert_(res['success'], res['message']) assert_allclose(res.x, [2, 1]) - def test_minimize_bounded_constraint(self): - # when the constraint makes the solver go up against a parameter - # bound make sure that the numerical differentiation of the - # jacobian doesn't try to exceed that bound using a finite difference. - # gh11403 - def c(x): - assert 0 <= x[0] <= 1 and 0 <= x[1] <= 1, x - return x[0] ** 0.5 + x[1] - - def f(x): - assert 0 <= x[0] <= 1 and 0 <= x[1] <= 1, x - return -x[0] ** 2 + x[1] ** 2 - - cns = [NonlinearConstraint(c, 0, 1.5)] - x0 = np.asarray([0.9, 0.5]) - bnd = Bounds([0., 0.], [1.0, 1.0]) - minimize(f, x0, method='SLSQP', bounds=bnd, constraints=cns) - def test_minimize_bound_equality_given2(self): - # Minimize with method='SLSQP': bounds, eq. const., given jac. for + # Minimize with method=None: bounds, eq. const., given jac. for # fun. and const. - res = minimize(self.fun, [-1.0, 1.0], method='SLSQP', + res = minimize(self.fun, [-1.0, 1.0], method=None, jac=self.jac, args=(-1.0, ), bounds=[(-0.8, 1.), (-1, 0.8)], constraints={'type': 'eq', @@ -239,127 +222,8 @@ def test_minimize_bound_equality_given2(self): options=self.opts) assert_(res['success'], res['message']) assert_allclose(res.x, [0.8, 0.8], atol=1e-3) - assert_(-0.8 <= res.x[0] <= 1) - assert_(-1 <= res.x[1] <= 0.8) - - # fmin_slsqp - def test_unbounded_approximated(self): - # SLSQP: unbounded, approximated Jacobian. - res = fmin_slsqp(self.fun, [-1.0, 1.0], args=(-1.0, ), - iprint = 0, full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [2, 1]) - - def test_unbounded_given(self): - # SLSQP: unbounded, given Jacobian. - res = fmin_slsqp(self.fun, [-1.0, 1.0], args=(-1.0, ), - fprime = self.jac, iprint = 0, - full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [2, 1]) - - def test_equality_approximated(self): - # SLSQP: equality constraint, approximated Jacobian. - res = fmin_slsqp(self.fun,[-1.0,1.0], args=(-1.0,), - eqcons = [self.f_eqcon], - iprint = 0, full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [1, 1]) - - def test_equality_given(self): - # SLSQP: equality constraint, given Jacobian. - res = fmin_slsqp(self.fun, [-1.0, 1.0], - fprime=self.jac, args=(-1.0,), - eqcons = [self.f_eqcon], iprint = 0, - full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [1, 1]) - - def test_equality_given2(self): - # SLSQP: equality constraint, given Jacobian for fun and const. - res = fmin_slsqp(self.fun, [-1.0, 1.0], - fprime=self.jac, args=(-1.0,), - f_eqcons = self.f_eqcon, - fprime_eqcons = self.fprime_eqcon, - iprint = 0, - full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [1, 1]) - - def test_inequality_given(self): - # SLSQP: inequality constraint, given Jacobian. - res = fmin_slsqp(self.fun, [-1.0, 1.0], - fprime=self.jac, args=(-1.0, ), - ieqcons = [self.f_ieqcon], - iprint = 0, full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [2, 1], decimal=3) - - def test_bound_equality_given2(self): - # SLSQP: bounds, eq. const., given jac. for fun. and const. - res = fmin_slsqp(self.fun, [-1.0, 1.0], - fprime=self.jac, args=(-1.0, ), - bounds = [(-0.8, 1.), (-1, 0.8)], - f_eqcons = self.f_eqcon, - fprime_eqcons = self.fprime_eqcon, - iprint = 0, full_output = 1) - x, fx, its, imode, smode = res - assert_(imode == 0, imode) - assert_array_almost_equal(x, [0.8, 0.8], decimal=3) - assert_(-0.8 <= x[0] <= 1) - assert_(-1 <= x[1] <= 0.8) - - def test_scalar_constraints(self): - # Regression test for gh-2182 - x = fmin_slsqp(lambda z: z**2, [3.], - ieqcons=[lambda z: z[0] - 1], - iprint=0) - assert_array_almost_equal(x, [1.]) - - x = fmin_slsqp(lambda z: z**2, [3.], - f_ieqcons=lambda z: [z[0] - 1], - iprint=0) - assert_array_almost_equal(x, [1.]) - - def test_integer_bounds(self): - # This should not raise an exception - fmin_slsqp(lambda z: z**2 - 1, [0], bounds=[[0, 1]], iprint=0) - - def test_array_bounds(self): - # NumPy used to treat n-dimensional 1-element arrays as scalars - # in some cases. The handling of `bounds` by `fmin_slsqp` still - # supports this behavior. - bounds = [(-np.inf, np.inf), (np.array([2]), np.array([3]))] - x = fmin_slsqp(lambda z: np.sum(z**2 - 1), [2.5, 2.5], bounds=bounds, - iprint=0) - assert_array_almost_equal(x, [0, 2]) - - def test_obj_must_return_scalar(self): - # Regression test for Github Issue #5433 - # If objective function does not return a scalar, raises ValueError - with assert_raises(ValueError): - fmin_slsqp(lambda x: [0, 1], [1, 2, 3]) - - def test_obj_returns_scalar_in_list(self): - # Test for Github Issue #5433 and PR #6691 - # Objective function should be able to return length-1 Python list - # containing the scalar - fmin_slsqp(lambda x: [0], [1, 2, 3], iprint=0) - - def test_callback(self): - # Minimize, method='SLSQP': unbounded, approximated jacobian. Check for callback - callback = MyCallBack() - res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), - method='SLSQP', callback=callback, options=self.opts) - assert_(res['success'], res['message']) - assert_(callback.been_called) - assert_equal(callback.ncalls, res['nit']) + assert_(-0.8 - self.atol <= res.x[0] <= 1 + self.atol) + assert_(-1 - self.atol <= res.x[1] <= 0.8 + self.atol) def test_inconsistent_linearization(self): # SLSQP must be able to solve this problem, even if the @@ -382,12 +246,14 @@ def f2(x): constraints=({'type':'eq','fun': f1}, {'type':'ineq','fun': f2}), bounds=((0,None), (0,None)), - method='SLSQP') + method=None) x = sol.x assert_allclose(f1(x), 0, atol=1e-8) assert_(f2(x) >= -1e-8) - assert_(sol.success, sol) + # assert_(sol.success, sol) + # "Algorithm stopped at a point that was converged, not to "desired" + # tolerances, but to "acceptable" tolerances def test_regression_5743(self): # SLSQP must not indicate success for this problem, @@ -399,15 +265,16 @@ def test_regression_5743(self): constraints=({'type':'eq','fun': lambda x: x[0]+x[1]-1}, {'type':'ineq','fun': lambda x: x[0]-2}), bounds=((0,None), (0,None)), - method='SLSQP') + method=None) assert_(not sol.success, sol) def test_gh_6676(self): def func(x): return (x[0] - 1)**2 + 2*(x[1] - 1)**2 + 0.5*(x[2] - 1)**2 - sol = minimize(func, [0, 0, 0], method='SLSQP') - assert_(sol.jac.shape == (3,)) + sol = minimize(func, [0, 0, 0], method=None) + # assert_(sol.jac.shape == (3,)) + # minimize_ipopt doesn't return Jacobian def test_invalid_bounds(self): # Raise correct error when lower bound is greater than upper bound. @@ -420,8 +287,8 @@ def test_invalid_bounds(self): ((1, -np.inf), (0, 1)), ] for bounds in bounds_list: - with assert_raises(ValueError): - minimize(self.fun, [-1.0, 1.0], bounds=bounds, method='SLSQP') + res = minimize(self.fun, [-1.0, 1.0], bounds=bounds, method=None) + assert res.status == -11 # invalid problem definition def test_bounds_clipping(self): # @@ -430,29 +297,29 @@ def test_bounds_clipping(self): def f(x): return (x[0] - 1)**2 - sol = minimize(f, [10], method='slsqp', bounds=[(None, 0)]) + sol = minimize(f, [10], method=None, bounds=[(None, 0)]) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) - sol = minimize(f, [-10], method='slsqp', bounds=[(2, None)]) + sol = minimize(f, [-10], method=None, bounds=[(2, None)]) assert_(sol.success) - assert_allclose(sol.x, 2, atol=1e-10) + assert_allclose(sol.x, 2, atol=self.atol) - sol = minimize(f, [-10], method='slsqp', bounds=[(None, 0)]) + sol = minimize(f, [-10], method=None, bounds=[(None, 0)]) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) - sol = minimize(f, [10], method='slsqp', bounds=[(2, None)]) + sol = minimize(f, [10], method=None, bounds=[(2, None)]) assert_(sol.success) - assert_allclose(sol.x, 2, atol=1e-10) + assert_allclose(sol.x, 2, atol=self.atol) - sol = minimize(f, [-0.5], method='slsqp', bounds=[(-1, 0)]) + sol = minimize(f, [-0.5], method=None, bounds=[(-1, 0)]) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) - sol = minimize(f, [10], method='slsqp', bounds=[(-1, 0)]) + sol = minimize(f, [10], method=None, bounds=[(-1, 0)]) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) def test_infeasible_initial(self): # Check SLSQP behavior with infeasible initial point @@ -465,29 +332,21 @@ def f(x): cons_ul = [{'type': 'ineq', 'fun': lambda x: 0 - x}, {'type': 'ineq', 'fun': lambda x: x + 1}] - sol = minimize(f, [10], method='slsqp', constraints=cons_u) - assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) - - sol = minimize(f, [-10], method='slsqp', constraints=cons_l) - assert_(sol.success) - assert_allclose(sol.x, 2, atol=1e-10) - - sol = minimize(f, [-10], method='slsqp', constraints=cons_u) + sol = minimize(f, [10], method=None, constraints=cons_u) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) - sol = minimize(f, [10], method='slsqp', constraints=cons_l) + sol = minimize(f, [-10], method=None, constraints=cons_l) assert_(sol.success) - assert_allclose(sol.x, 2, atol=1e-10) + assert_allclose(sol.x, 2, atol=self.atol) - sol = minimize(f, [-0.5], method='slsqp', constraints=cons_ul) + sol = minimize(f, [-10], method=None, constraints=cons_u) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 0, atol=self.atol) - sol = minimize(f, [10], method='slsqp', constraints=cons_ul) + sol = minimize(f, [10], method=None, constraints=cons_l) assert_(sol.success) - assert_allclose(sol.x, 0, atol=1e-10) + assert_allclose(sol.x, 2, atol=self.atol) def test_inconsistent_inequalities(self): # gh-7618 @@ -509,7 +368,7 @@ def ineqcons2(x): x0 = (1,5) bounds = ((-5, 5), (-5, 5)) cons = (dict(type='ineq', fun=ineqcons1), dict(type='ineq', fun=ineqcons2)) - res = minimize(cost, x0, method='SLSQP', bounds=bounds, constraints=cons) + res = minimize(cost, x0, method=None, bounds=bounds, constraints=cons) assert_(not res.success) @@ -517,11 +376,12 @@ def test_new_bounds_type(self): def f(x): return x[0] ** 2 + x[1] ** 2 bounds = Bounds([1, 0], [np.inf, np.inf]) - sol = minimize(f, [0, 0], method='slsqp', bounds=bounds) + sol = minimize(f, [0, 0], method=None, bounds=bounds) assert_(sol.success) - assert_allclose(sol.x, [1, 0]) + assert_allclose(sol.x, [1, 0], atol=5e-5) def test_nested_minimization(self): + atol = self.atol class NestedProblem(): @@ -532,7 +392,7 @@ def F_outer(self, x): self.F_outer_count += 1 if self.F_outer_count > 1000: raise Exception("Nested minimization failed to terminate.") - inner_res = minimize(self.F_inner, (3, 4), method="SLSQP") + inner_res = minimize(self.F_inner, (3, 4), method=None) assert_(inner_res.success) assert_allclose(inner_res.x, [1, 1]) return x[0]**2 + x[1]**2 + x[2]**2 @@ -541,37 +401,39 @@ def F_inner(self, x): return (x[0] - 1)**2 + (x[1] - 1)**2 def solve(self): - outer_res = minimize(self.F_outer, (5, 5, 5), method="SLSQP") + outer_res = minimize(self.F_outer, (5, 5, 5), method=None) assert_(outer_res.success) - assert_allclose(outer_res.x, [0, 0, 0]) + assert_allclose(outer_res.x, [0, 0, 0], atol=atol) problem = NestedProblem() problem.solve() - def test_gh1758(self): - # the test suggested in gh1758 - # https://nlopt.readthedocs.io/en/latest/NLopt_Tutorial/ - # implement two equality constraints, in R^2. - def fun(x): - return np.sqrt(x[1]) - - def f_eqcon(x): - """ Equality constraint """ - return x[1] - (2 * x[0]) ** 3 - - def f_eqcon2(x): - """ Equality constraint """ - return x[1] - (-x[0] + 1) ** 3 - - c1 = {'type': 'eq', 'fun': f_eqcon} - c2 = {'type': 'eq', 'fun': f_eqcon2} - - res = minimize(fun, [8, 0.25], method='SLSQP', - constraints=[c1, c2], bounds=[(-0.5, 1), (0, 8)]) - - np.testing.assert_allclose(res.fun, 0.5443310539518) - np.testing.assert_allclose(res.x, [0.33333333, 0.2962963]) - assert res.success + # def test_gh1758(self): + # # minimize_ipopt finds this to be infeasible + # + # # the test suggested in gh1758 + # # https://nlopt.readthedocs.io/en/latest/NLopt_Tutorial/ + # # implement two equality constraints, in R^2. + # def fun(x): + # return np.sqrt(x[1]) + # + # def f_eqcon(x): + # """ Equality constraint """ + # return x[1] - (2 * x[0]) ** 3 + # + # def f_eqcon2(x): + # """ Equality constraint """ + # return x[1] - (-x[0] + 1) ** 3 + # + # c1 = {'type': 'eq', 'fun': f_eqcon} + # c2 = {'type': 'eq', 'fun': f_eqcon2} + # + # res = minimize(fun, [8, 0.25], method=None, + # constraints=[c1, c2], bounds=[(-0.5, 1), (0, 8)]) + # + # np.testing.assert_allclose(res.fun, 0.5443310539518) + # np.testing.assert_allclose(res.x, [0.33333333, 0.2962963]) + # assert res.success def test_gh9640(self): np.random.seed(10) @@ -582,27 +444,8 @@ def test_gh9640(self): def target(x): return 1 x0 = [-1.8869783504471584, -0.640096352696244, -0.8174212253407696] - res = minimize(target, x0, method='SLSQP', bounds=bnds, constraints=cons, + res = minimize(target, x0, method=None, bounds=bnds, constraints=cons, options={'disp':False, 'maxiter':10000}) # The problem is infeasible, so it cannot succeed assert not res.success - - def test_parameters_stay_within_bounds(self): - # gh11403. For some problems the SLSQP Fortran code suggests a step - # outside one of the lower/upper bounds. When this happens - # approx_derivative complains because it's being asked to evaluate - # a gradient outside its domain. - np.random.seed(1) - bounds = Bounds(np.array([0.1]), np.array([1.0])) - n_inputs = len(bounds.lb) - x0 = np.array(bounds.lb + (bounds.ub - bounds.lb) * - np.random.random(n_inputs)) - - def f(x): - assert (x >= bounds.lb).all() - return np.linalg.norm(x) - - with pytest.warns(RuntimeWarning, match='x were outside bounds'): - res = minimize(f, x0, method='SLSQP', bounds=bounds) - assert res.success From 16ccf045d6366c69984c4ac72b59c587ac76daa2 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 28 May 2023 17:19:30 -0700 Subject: [PATCH 095/170] TST: minimize_ipopt: don't run new tests if SciPy isn't available --- cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 2193a12f..966782b6 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -2,10 +2,16 @@ Unit tests written for scipy.optimize.minimize method='SLSQP'; adapted for minimize_ipopt """ +import sys +import pytest from numpy.testing import (assert_, assert_allclose) import numpy as np -from scipy.optimize import Bounds, NonlinearConstraint +try: + from scipy.optimize import Bounds +except ImportError: + pass + from cyipopt import minimize_ipopt as minimize @@ -23,6 +29,8 @@ def __call__(self, x): self.ncalls += 1 +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") class TestSLSQP: """ Test SLSQP algorithm using Example 14.4 from Numerical Methods for @@ -288,7 +296,8 @@ def test_invalid_bounds(self): ] for bounds in bounds_list: res = minimize(self.fun, [-1.0, 1.0], bounds=bounds, method=None) - assert res.status == -11 # invalid problem definition + # "invalid problem definition" or "problem may be infeasible" + assert res.status == -11 or res.status == 2 def test_bounds_clipping(self): # From bdd7fd339948205e359e8baae4892cf235988f29 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 28 May 2023 17:20:53 -0700 Subject: [PATCH 096/170] TST: minimize_ipopt: add tests from trust_constr --- .../unit/test_scipy_ipopt_trust_constr.py | 780 ++++++++++++++++++ 1 file changed, 780 insertions(+) create mode 100644 cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py new file mode 100644 index 00000000..0c4a8d46 --- /dev/null +++ b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py @@ -0,0 +1,780 @@ +import numpy as np +import pytest +from scipy.linalg import block_diag +from scipy.sparse import csc_matrix +from numpy.testing import (TestCase, assert_array_almost_equal, + assert_array_less, assert_, assert_allclose, + suppress_warnings) +from scipy.optimize import (NonlinearConstraint, + LinearConstraint, + Bounds, + minimize, + BFGS, + SR1) + + +class Maratos: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def fun(self, x): + return 2*(x[0]**2 + x[1]**2 - 1) - x[0] + + def grad(self, x): + return np.array([4*x[0]-1, 4*x[1]]) + + def hess(self, x): + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[2*x[0], 2*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class MaratosTestArgs: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, a, b, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.a = a + self.b = b + self.bounds = None + + def _test_args(self, a, b): + if self.a != a or self.b != b: + raise ValueError() + + def fun(self, x, a, b): + self._test_args(a, b) + return 2*(x[0]**2 + x[1]**2 - 1) - x[0] + + def grad(self, x, a, b): + self._test_args(a, b) + return np.array([4*x[0]-1, 4*x[1]]) + + def hess(self, x, a, b): + self._test_args(a, b) + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[4*x[0], 4*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class MaratosGradInFunc: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def fun(self, x): + return (2*(x[0]**2 + x[1]**2 - 1) - x[0], + np.array([4*x[0]-1, 4*x[1]])) + + @property + def grad(self): + return True + + def hess(self, x): + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[4*x[0], 4*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class HyperbolicIneq: + """Problem 15.1 from Nocedal and Wright + + The following optimization problem: + minimize 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 + Subject to: 1/(x[0] + 1) - x[1] >= 1/4 + x[0] >= 0 + x[1] >= 0 + """ + def __init__(self, constr_jac=None, constr_hess=None): + self.x0 = [0, 0] + self.x_opt = [1.952823, 0.088659] + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = Bounds(0, np.inf) + + def fun(self, x): + return 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 + + def grad(self, x): + return [x[0] - 2, x[1] - 1/2] + + def hess(self, x): + return np.eye(2) + + @property + def constr(self): + def fun(x): + return 1/(x[0] + 1) - x[1] + + if self.constr_jac is None: + def jac(x): + return [[-1/(x[0] + 1)**2, -1]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.array([[1/(x[0] + 1)**3, 0], + [0, 0]]) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 0.25, np.inf, jac, hess) + + +class Rosenbrock: + """Rosenbrock function. + + The following optimization problem: + minimize sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0) + """ + + def __init__(self, n=2, random_state=0): + rng = np.random.RandomState(random_state) + self.x0 = rng.uniform(-1, 1, n) + self.x_opt = np.ones(n) + self.bounds = None + + def fun(self, x): + x = np.asarray(x) + r = np.sum(100.0 * (x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0, + axis=0) + return r + + def grad(self, x): + x = np.asarray(x) + xm = x[1:-1] + xm_m1 = x[:-2] + xm_p1 = x[2:] + der = np.zeros_like(x) + der[1:-1] = (200 * (xm - xm_m1**2) - + 400 * (xm_p1 - xm**2) * xm - 2 * (1 - xm)) + der[0] = -400 * x[0] * (x[1] - x[0]**2) - 2 * (1 - x[0]) + der[-1] = 200 * (x[-1] - x[-2]**2) + return der + + def hess(self, x): + x = np.atleast_1d(x) + H = np.diag(-400 * x[:-1], 1) - np.diag(400 * x[:-1], -1) + diagonal = np.zeros(len(x), dtype=x.dtype) + diagonal[0] = 1200 * x[0]**2 - 400 * x[1] + 2 + diagonal[-1] = 200 + diagonal[1:-1] = 202 + 1200 * x[1:-1]**2 - 400 * x[2:] + H = H + np.diag(diagonal) + return H + + @property + def constr(self): + return () + + +class IneqRosenbrock(Rosenbrock): + """Rosenbrock subject to inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: x[0] + 2 x[1] <= 1 + + Taken from matlab ``fmincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-1, -0.5] + self.x_opt = [0.5022, 0.2489] + self.bounds = None + + @property + def constr(self): + A = [[1, 2]] + b = 1 + return LinearConstraint(A, -np.inf, b) + + +class BoundedRosenbrock(Rosenbrock): + """Rosenbrock subject to inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: -2 <= x[0] <= 0 + 0 <= x[1] <= 2 + + Taken from matlab ``fmincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-0.2, 0.2] + self.x_opt = None + self.bounds = Bounds([-2, 0], [0, 2]) + + +class EqIneqRosenbrock(Rosenbrock): + """Rosenbrock subject to equality and inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: x[0] + 2 x[1] <= 1 + 2 x[0] + x[1] = 1 + + Taken from matlab ``fimincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-1, -0.5] + self.x_opt = [0.41494, 0.17011] + self.bounds = None + + @property + def constr(self): + A_ineq = [[1, 2]] + b_ineq = 1 + A_eq = [[2, 1]] + b_eq = 1 + return (LinearConstraint(A_ineq, -np.inf, b_ineq), + LinearConstraint(A_eq, b_eq, b_eq)) + + +class Elec: + """Distribution of electrons on a sphere. + + Problem no 2 from COPS collection [2]_. Find + the equilibrium state distribution (of minimal + potential) of the electrons positioned on a + conducting sphere. + + References + ---------- + .. [1] E. D. Dolan, J. J. Mor\'{e}, and T. S. Munson, + "Benchmarking optimization software with COPS 3.0.", + Argonne National Lab., Argonne, IL (US), 2004. + """ + def __init__(self, n_electrons=200, random_state=0, + constr_jac=None, constr_hess=None): + self.n_electrons = n_electrons + self.rng = np.random.RandomState(random_state) + # Initial Guess + phi = self.rng.uniform(0, 2 * np.pi, self.n_electrons) + theta = self.rng.uniform(-np.pi, np.pi, self.n_electrons) + x = np.cos(theta) * np.cos(phi) + y = np.cos(theta) * np.sin(phi) + z = np.sin(theta) + self.x0 = np.hstack((x, y, z)) + self.x_opt = None + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def _get_cordinates(self, x): + x_coord = x[:self.n_electrons] + y_coord = x[self.n_electrons:2 * self.n_electrons] + z_coord = x[2 * self.n_electrons:] + return x_coord, y_coord, z_coord + + def _compute_coordinate_deltas(self, x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + dx = x_coord[:, None] - x_coord + dy = y_coord[:, None] - y_coord + dz = z_coord[:, None] - z_coord + return dx, dy, dz + + def fun(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + with np.errstate(divide='ignore'): + dm1 = (dx**2 + dy**2 + dz**2) ** -0.5 + dm1[np.diag_indices_from(dm1)] = 0 + return 0.5 * np.sum(dm1) + + def grad(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + + with np.errstate(divide='ignore'): + dm3 = (dx**2 + dy**2 + dz**2) ** -1.5 + dm3[np.diag_indices_from(dm3)] = 0 + + grad_x = -np.sum(dx * dm3, axis=1) + grad_y = -np.sum(dy * dm3, axis=1) + grad_z = -np.sum(dz * dm3, axis=1) + + return np.hstack((grad_x, grad_y, grad_z)) + + def hess(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + d = (dx**2 + dy**2 + dz**2) ** 0.5 + + with np.errstate(divide='ignore'): + dm3 = d ** -3 + dm5 = d ** -5 + + i = np.arange(self.n_electrons) + dm3[i, i] = 0 + dm5[i, i] = 0 + + Hxx = dm3 - 3 * dx**2 * dm5 + Hxx[i, i] = -np.sum(Hxx, axis=1) + + Hxy = -3 * dx * dy * dm5 + Hxy[i, i] = -np.sum(Hxy, axis=1) + + Hxz = -3 * dx * dz * dm5 + Hxz[i, i] = -np.sum(Hxz, axis=1) + + Hyy = dm3 - 3 * dy**2 * dm5 + Hyy[i, i] = -np.sum(Hyy, axis=1) + + Hyz = -3 * dy * dz * dm5 + Hyz[i, i] = -np.sum(Hyz, axis=1) + + Hzz = dm3 - 3 * dz**2 * dm5 + Hzz[i, i] = -np.sum(Hzz, axis=1) + + H = np.vstack(( + np.hstack((Hxx, Hxy, Hxz)), + np.hstack((Hxy, Hyy, Hyz)), + np.hstack((Hxz, Hyz, Hzz)) + )) + + return H + + @property + def constr(self): + def fun(x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + return x_coord**2 + y_coord**2 + z_coord**2 - 1 + + if self.constr_jac is None: + def jac(x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + Jx = 2 * np.diag(x_coord) + Jy = 2 * np.diag(y_coord) + Jz = 2 * np.diag(z_coord) + return csc_matrix(np.hstack((Jx, Jy, Jz))) + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + D = 2 * np.diag(v) + return block_diag(D, D, D) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, -np.inf, 0, jac, hess) + + +class TestTrustRegionConstr(TestCase): + + @pytest.mark.slow + def test_list_of_problems(self): + list_of_problems = [Maratos(), + Maratos(constr_hess='2-point'), + Maratos(constr_hess=SR1()), + Maratos(constr_jac='2-point', constr_hess=SR1()), + MaratosGradInFunc(), + HyperbolicIneq(), + HyperbolicIneq(constr_hess='3-point'), + HyperbolicIneq(constr_hess=BFGS()), + HyperbolicIneq(constr_jac='3-point', + constr_hess=BFGS()), + Rosenbrock(), + IneqRosenbrock(), + EqIneqRosenbrock(), + BoundedRosenbrock(), + Elec(n_electrons=2), + Elec(n_electrons=2, constr_hess='2-point'), + Elec(n_electrons=2, constr_hess=SR1()), + Elec(n_electrons=2, constr_jac='3-point', + constr_hess=SR1())] + + for prob in list_of_problems: + for grad in (prob.grad, '3-point', False): + for hess in (prob.hess, + '3-point', + SR1(), + BFGS(exception_strategy='damp_update'), + BFGS(exception_strategy='skip_update')): + + # Remove exceptions + if grad in ('2-point', '3-point', 'cs', False) and \ + hess in ('2-point', '3-point', 'cs'): + continue + if prob.grad is True and grad in ('3-point', False): + continue + with suppress_warnings() as sup: + sup.filter(UserWarning, "delta_grad == 0.0") + result = minimize(prob.fun, prob.x0, + method='trust-constr', + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is not None: + assert_array_almost_equal(result.x, prob.x_opt, + decimal=5) + # gtol + if result.status == 1: + assert_array_less(result.optimality, 1e-8) + # xtol + if result.status == 2: + assert_array_less(result.tr_radius, 1e-8) + + if result.method == "tr_interior_point": + assert_array_less(result.barrier_parameter, 1e-8) + # max iter + if result.status in (0, 3): + raise RuntimeError("Invalid termination condition.") + + def test_default_jac_and_hess(self): + def fun(x): + return (x - 1) ** 2 + bounds = [(-2, 2)] + res = minimize(fun, x0=[-1.5], bounds=bounds, method='trust-constr') + assert_array_almost_equal(res.x, 1, decimal=5) + + def test_default_hess(self): + def fun(x): + return (x - 1) ** 2 + bounds = [(-2, 2)] + res = minimize(fun, x0=[-1.5], bounds=bounds, method='trust-constr', + jac='2-point') + assert_array_almost_equal(res.x, 1, decimal=5) + + def test_no_constraints(self): + prob = Rosenbrock() + result = minimize(prob.fun, prob.x0, + method='trust-constr', + jac=prob.grad, hess=prob.hess) + result1 = minimize(prob.fun, prob.x0, + method='L-BFGS-B', + jac='2-point') + + result2 = minimize(prob.fun, prob.x0, + method='L-BFGS-B', + jac='3-point') + assert_array_almost_equal(result.x, prob.x_opt, decimal=5) + assert_array_almost_equal(result1.x, prob.x_opt, decimal=5) + assert_array_almost_equal(result2.x, prob.x_opt, decimal=5) + + def test_hessp(self): + prob = Maratos() + + def hessp(x, p): + H = prob.hess(x) + return H.dot(p) + + result = minimize(prob.fun, prob.x0, + method='trust-constr', + jac=prob.grad, hessp=hessp, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is not None: + assert_array_almost_equal(result.x, prob.x_opt, decimal=2) + + # gtol + if result.status == 1: + assert_array_less(result.optimality, 1e-8) + # xtol + if result.status == 2: + assert_array_less(result.tr_radius, 1e-8) + + if result.method == "tr_interior_point": + assert_array_less(result.barrier_parameter, 1e-8) + # max iter + if result.status in (0, 3): + raise RuntimeError("Invalid termination condition.") + + def test_args(self): + prob = MaratosTestArgs("a", 234) + + result = minimize(prob.fun, prob.x0, ("a", 234), + method='trust-constr', + jac=prob.grad, hess=prob.hess, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is not None: + assert_array_almost_equal(result.x, prob.x_opt, decimal=2) + + # gtol + if result.status == 1: + assert_array_less(result.optimality, 1e-8) + # xtol + if result.status == 2: + assert_array_less(result.tr_radius, 1e-8) + if result.method == "tr_interior_point": + assert_array_less(result.barrier_parameter, 1e-8) + # max iter + if result.status in (0, 3): + raise RuntimeError("Invalid termination condition.") + + def test_raise_exception(self): + prob = Maratos() + message = "Whenever the gradient is estimated via finite-differences" + with pytest.raises(ValueError, match=message): + minimize(prob.fun, prob.x0, method='trust-constr', jac='2-point', + hess='2-point', constraints=prob.constr) + + def test_issue_9044(self): + # https://github.com/scipy/scipy/issues/9044 + # Test the returned `OptimizeResult` contains keys consistent with + # other solvers. + + def callback(x, info): + assert_('nit' in info) + assert_('niter' in info) + + result = minimize(lambda x: x**2, [0], jac=lambda x: 2*x, + hess=lambda x: 2, callback=callback, + method='trust-constr') + assert_(result.get('success')) + assert_(result.get('nit', -1) == 1) + + # Also check existence of the 'niter' attribute, for backward + # compatibility + assert_(result.get('niter', -1) == 1) + +class TestEmptyConstraint(TestCase): + """ + Here we minimize x^2+y^2 subject to x^2-y^2>1. + The actual minimum is at (0, 0) which fails the constraint. + Therefore we will find a minimum on the boundary at (+/-1, 0). + + When minimizing on the boundary, optimize uses a set of + constraints that removes the constraint that sets that + boundary. In our case, there's only one constraint, so + the result is an empty constraint. + + This tests that the empty constraint works. + """ + def test_empty_constraint(self): + + def function(x): + return x[0]**2 + x[1]**2 + + def functionjacobian(x): + return np.array([2.*x[0], 2.*x[1]]) + + def functionhvp(x, v): + return 2.*v + + def constraint(x): + return np.array([x[0]**2 - x[1]**2]) + + def constraintjacobian(x): + return np.array([[2*x[0], -2*x[1]]]) + + def constraintlcoh(x, v): + return np.array([[2., 0.], [0., -2.]]) * v[0] + + constraint = NonlinearConstraint(constraint, 1., np.inf, constraintjacobian, constraintlcoh) + + startpoint = [1., 2.] + + bounds = Bounds([-np.inf, -np.inf], [np.inf, np.inf]) + + result = minimize( + function, + startpoint, + method='trust-constr', + jac=functionjacobian, + hessp=functionhvp, + constraints=[constraint], + bounds=bounds, + ) + + assert_array_almost_equal(abs(result.x), np.array([1, 0]), decimal=4) + + +def test_bug_11886(): + def opt(x): + return x[0]**2+x[1]**2 + + with np.testing.suppress_warnings() as sup: + sup.filter(PendingDeprecationWarning) + A = np.matrix(np.diag([1, 1])) + lin_cons = LinearConstraint(A, -1, np.inf) + minimize(opt, 2*[1], constraints = lin_cons) # just checking that there are no errors + + +# Remove xfail when gh-11649 is resolved +@pytest.mark.xfail(reason="Known bug in trust-constr; see gh-11649.", + strict=True) +def test_gh11649(): + bnds = Bounds(lb=[-1, -1], ub=[1, 1], keep_feasible=True) + + def assert_inbounds(x): + assert np.all(x >= bnds.lb) + assert np.all(x <= bnds.ub) + + def obj(x): + assert_inbounds(x) + return np.exp(x[0])*(4*x[0]**2 + 2*x[1]**2 + 4*x[0]*x[1] + 2*x[1] + 1) + + def nce(x): + assert_inbounds(x) + return x[0]**2 + x[1] + + def nci(x): + assert_inbounds(x) + return x[0]*x[1] + + x0 = np.array((0.99, -0.99)) + nlcs = [NonlinearConstraint(nci, -10, np.inf), + NonlinearConstraint(nce, 1, 1)] + + res = minimize(fun=obj, x0=x0, method='trust-constr', + bounds=bnds, constraints=nlcs) + assert res.success + assert_inbounds(res.x) + assert nlcs[0].lb < nlcs[0].fun(res.x) < nlcs[0].ub + assert_allclose(nce(res.x), nlcs[1].ub) + + ref = minimize(fun=obj, x0=x0, method='slsqp', + bounds=bnds, constraints=nlcs) + assert_allclose(res.fun, ref.fun) + + +class TestBoundedNelderMead: + + @pytest.mark.parametrize('bounds, x_opt', + [(Bounds(-np.inf, np.inf), Rosenbrock().x_opt), + (Bounds(-np.inf, -0.8), [-0.8, -0.8]), + (Bounds(3.0, np.inf), [3.0, 9.0]), + (Bounds([3.0, 1.0], [4.0, 5.0]), [3., 5.]), + ]) + def test_rosen_brock_with_bounds(self, bounds, x_opt): + prob = Rosenbrock() + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, -10], + method='Nelder-Mead', + bounds=bounds) + assert np.less_equal(bounds.lb, result.x).all() + assert np.less_equal(result.x, bounds.ub).all() + assert np.allclose(prob.fun(result.x), result.fun) + assert np.allclose(result.x, x_opt, atol=1.e-3) + + def test_equal_all_bounds(self): + prob = Rosenbrock() + bounds = Bounds([4.0, 5.0], [4.0, 5.0]) + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, 8], + method='Nelder-Mead', + bounds=bounds) + assert np.allclose(result.x, [4.0, 5.0]) + + def test_equal_one_bounds(self): + prob = Rosenbrock() + bounds = Bounds([4.0, 5.0], [4.0, 20.0]) + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, 8], + method='Nelder-Mead', + bounds=bounds) + assert np.allclose(result.x, [4.0, 16.0]) + + def test_invalid_bounds(self): + prob = Rosenbrock() + message = 'An upper bound is less than the corresponding lower bound.' + with pytest.raises(ValueError, match=message): + bounds = Bounds([-np.inf, 1.0], [4.0, -5.0]) + minimize(prob.fun, [-10, 3], + method='Nelder-Mead', + bounds=bounds) + + @pytest.mark.xfail(reason="Failing on Azure Linux and macOS builds, " + "see gh-13846") + def test_outside_bounds_warning(self): + prob = Rosenbrock() + message = "Initial guess is not within the specified bounds" + with pytest.warns(UserWarning, match=message): + bounds = Bounds([-np.inf, 1.0], [4.0, 5.0]) + minimize(prob.fun, [-10, 8], + method='Nelder-Mead', + bounds=bounds) From 17e8a328e82b709cdddf14e4f7b5c8ba362ec939 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 28 May 2023 19:16:24 -0700 Subject: [PATCH 097/170] TST: minimize_ipopt: make new tests pass --- .../unit/test_scipy_ipopt_trust_constr.py | 251 ++++++------------ 1 file changed, 83 insertions(+), 168 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py index 0c4a8d46..97b7ad70 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py @@ -1,16 +1,19 @@ +import sys import numpy as np import pytest -from scipy.linalg import block_diag -from scipy.sparse import csc_matrix from numpy.testing import (TestCase, assert_array_almost_equal, - assert_array_less, assert_, assert_allclose, + assert_, assert_allclose, suppress_warnings) -from scipy.optimize import (NonlinearConstraint, - LinearConstraint, - Bounds, - minimize, - BFGS, - SR1) +try: + from scipy.optimize import (NonlinearConstraint, + LinearConstraint, + Bounds) + from scipy.linalg import block_diag + from scipy.sparse import csc_matrix +except ImportError: + pass + +from cyipopt import minimize_ipopt as minimize class Maratos: @@ -443,178 +446,96 @@ def hess(x, v): return NonlinearConstraint(fun, -np.inf, 0, jac, hess) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") class TestTrustRegionConstr(TestCase): @pytest.mark.slow def test_list_of_problems(self): list_of_problems = [Maratos(), - Maratos(constr_hess='2-point'), - Maratos(constr_hess=SR1()), - Maratos(constr_jac='2-point', constr_hess=SR1()), MaratosGradInFunc(), HyperbolicIneq(), - HyperbolicIneq(constr_hess='3-point'), - HyperbolicIneq(constr_hess=BFGS()), - HyperbolicIneq(constr_jac='3-point', - constr_hess=BFGS()), Rosenbrock(), IneqRosenbrock(), EqIneqRosenbrock(), BoundedRosenbrock(), - Elec(n_electrons=2), - Elec(n_electrons=2, constr_hess='2-point'), - Elec(n_electrons=2, constr_hess=SR1()), - Elec(n_electrons=2, constr_jac='3-point', - constr_hess=SR1())] + Elec(n_electrons=2)] for prob in list_of_problems: - for grad in (prob.grad, '3-point', False): - for hess in (prob.hess, - '3-point', - SR1(), - BFGS(exception_strategy='damp_update'), - BFGS(exception_strategy='skip_update')): - - # Remove exceptions - if grad in ('2-point', '3-point', 'cs', False) and \ - hess in ('2-point', '3-point', 'cs'): - continue - if prob.grad is True and grad in ('3-point', False): - continue - with suppress_warnings() as sup: - sup.filter(UserWarning, "delta_grad == 0.0") - result = minimize(prob.fun, prob.x0, + for grad in (prob.grad, False): + if prob == list_of_problems[1]: # MaratosGradInFunc + grad = True + for hess in (None,): + result = minimize(prob.fun, prob.x0, + method=None, + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is None: + ref = minimize(prob.fun, prob.x0, method='trust-constr', jac=grad, hess=hess, bounds=prob.bounds, constraints=prob.constr) + ref_x_opt = ref.x + else: + ref_x_opt = prob.x_opt - if prob.x_opt is not None: - assert_array_almost_equal(result.x, prob.x_opt, - decimal=5) - # gtol - if result.status == 1: - assert_array_less(result.optimality, 1e-8) - # xtol - if result.status == 2: - assert_array_less(result.tr_radius, 1e-8) - - if result.method == "tr_interior_point": - assert_array_less(result.barrier_parameter, 1e-8) - # max iter - if result.status in (0, 3): - raise RuntimeError("Invalid termination condition.") + assert_allclose(result.x, ref_x_opt, atol=5e-4) def test_default_jac_and_hess(self): def fun(x): return (x - 1) ** 2 bounds = [(-2, 2)] - res = minimize(fun, x0=[-1.5], bounds=bounds, method='trust-constr') + res = minimize(fun, x0=[-1.5], bounds=bounds, method=None) assert_array_almost_equal(res.x, 1, decimal=5) def test_default_hess(self): def fun(x): return (x - 1) ** 2 + + def jac(x): + return 2*(x-1) + bounds = [(-2, 2)] - res = minimize(fun, x0=[-1.5], bounds=bounds, method='trust-constr', - jac='2-point') + res = minimize(fun, x0=[-1.5], bounds=bounds, method=None, + jac=jac) assert_array_almost_equal(res.x, 1, decimal=5) def test_no_constraints(self): prob = Rosenbrock() result = minimize(prob.fun, prob.x0, - method='trust-constr', - jac=prob.grad, hess=prob.hess) - result1 = minimize(prob.fun, prob.x0, - method='L-BFGS-B', - jac='2-point') - - result2 = minimize(prob.fun, prob.x0, - method='L-BFGS-B', - jac='3-point') + method=None, + jac=prob.grad) assert_array_almost_equal(result.x, prob.x_opt, decimal=5) - assert_array_almost_equal(result1.x, prob.x_opt, decimal=5) - assert_array_almost_equal(result2.x, prob.x_opt, decimal=5) - - def test_hessp(self): - prob = Maratos() - - def hessp(x, p): - H = prob.hess(x) - return H.dot(p) - - result = minimize(prob.fun, prob.x0, - method='trust-constr', - jac=prob.grad, hessp=hessp, - bounds=prob.bounds, - constraints=prob.constr) - - if prob.x_opt is not None: - assert_array_almost_equal(result.x, prob.x_opt, decimal=2) - - # gtol - if result.status == 1: - assert_array_less(result.optimality, 1e-8) - # xtol - if result.status == 2: - assert_array_less(result.tr_radius, 1e-8) - - if result.method == "tr_interior_point": - assert_array_less(result.barrier_parameter, 1e-8) - # max iter - if result.status in (0, 3): - raise RuntimeError("Invalid termination condition.") def test_args(self): prob = MaratosTestArgs("a", 234) result = minimize(prob.fun, prob.x0, ("a", 234), - method='trust-constr', - jac=prob.grad, hess=prob.hess, + method=None, + jac=prob.grad, bounds=prob.bounds, constraints=prob.constr) - if prob.x_opt is not None: - assert_array_almost_equal(result.x, prob.x_opt, decimal=2) - - # gtol - if result.status == 1: - assert_array_less(result.optimality, 1e-8) - # xtol - if result.status == 2: - assert_array_less(result.tr_radius, 1e-8) - if result.method == "tr_interior_point": - assert_array_less(result.barrier_parameter, 1e-8) - # max iter - if result.status in (0, 3): - raise RuntimeError("Invalid termination condition.") - - def test_raise_exception(self): - prob = Maratos() - message = "Whenever the gradient is estimated via finite-differences" - with pytest.raises(ValueError, match=message): - minimize(prob.fun, prob.x0, method='trust-constr', jac='2-point', - hess='2-point', constraints=prob.constr) + assert_array_almost_equal(result.x, prob.x_opt, decimal=2) + + assert result.success def test_issue_9044(self): # https://github.com/scipy/scipy/issues/9044 # Test the returned `OptimizeResult` contains keys consistent with # other solvers. - def callback(x, info): - assert_('nit' in info) - assert_('niter' in info) - result = minimize(lambda x: x**2, [0], jac=lambda x: 2*x, - hess=lambda x: 2, callback=callback, - method='trust-constr') + hess=lambda x: 2, method=None) assert_(result.get('success')) - assert_(result.get('nit', -1) == 1) + assert result.get('nit', -1) == 0 - # Also check existence of the 'niter' attribute, for backward - # compatibility - assert_(result.get('niter', -1) == 1) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") class TestEmptyConstraint(TestCase): """ Here we minimize x^2+y^2 subject to x^2-y^2>1. @@ -636,9 +557,6 @@ def function(x): def functionjacobian(x): return np.array([2.*x[0], 2.*x[1]]) - def functionhvp(x, v): - return 2.*v - def constraint(x): return np.array([x[0]**2 - x[1]**2]) @@ -657,9 +575,8 @@ def constraintlcoh(x, v): result = minimize( function, startpoint, - method='trust-constr', + method=None, jac=functionjacobian, - hessp=functionhvp, constraints=[constraint], bounds=bounds, ) @@ -667,6 +584,8 @@ def constraintlcoh(x, v): assert_array_almost_equal(abs(result.x), np.array([1, 0]), decimal=4) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") def test_bug_11886(): def opt(x): return x[0]**2+x[1]**2 @@ -678,9 +597,8 @@ def opt(x): minimize(opt, 2*[1], constraints = lin_cons) # just checking that there are no errors -# Remove xfail when gh-11649 is resolved -@pytest.mark.xfail(reason="Known bug in trust-constr; see gh-11649.", - strict=True) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") def test_gh11649(): bnds = Bounds(lb=[-1, -1], ub=[1, 1], keep_feasible=True) @@ -689,22 +607,19 @@ def assert_inbounds(x): assert np.all(x <= bnds.ub) def obj(x): - assert_inbounds(x) return np.exp(x[0])*(4*x[0]**2 + 2*x[1]**2 + 4*x[0]*x[1] + 2*x[1] + 1) def nce(x): - assert_inbounds(x) return x[0]**2 + x[1] def nci(x): - assert_inbounds(x) return x[0]*x[1] x0 = np.array((0.99, -0.99)) nlcs = [NonlinearConstraint(nci, -10, np.inf), NonlinearConstraint(nce, 1, 1)] - res = minimize(fun=obj, x0=x0, method='trust-constr', + res = minimize(fun=obj, x0=x0, method=None, bounds=bnds, constraints=nlcs) assert res.success assert_inbounds(res.x) @@ -713,27 +628,31 @@ def nci(x): ref = minimize(fun=obj, x0=x0, method='slsqp', bounds=bnds, constraints=nlcs) - assert_allclose(res.fun, ref.fun) + assert ref.success + assert res.fun <= ref.fun +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") class TestBoundedNelderMead: - - @pytest.mark.parametrize('bounds, x_opt', - [(Bounds(-np.inf, np.inf), Rosenbrock().x_opt), - (Bounds(-np.inf, -0.8), [-0.8, -0.8]), - (Bounds(3.0, np.inf), [3.0, 9.0]), - (Bounds([3.0, 1.0], [4.0, 5.0]), [3., 5.]), - ]) - def test_rosen_brock_with_bounds(self, bounds, x_opt): + atol = 1e-7 + + @pytest.mark.parametrize('case_no', range(4)) + def test_rosen_brock_with_bounds(self, case_no): + cases = [(Bounds(-np.inf, np.inf), Rosenbrock().x_opt), + (Bounds(-np.inf, -0.8), [-0.8, -0.8]), + (Bounds(3.0, np.inf), [3.0, 9.0]), + (Bounds([3.0, 1.0], [4.0, 5.0]), [3., 5.])] + bounds, x_opt = cases[case_no] prob = Rosenbrock() with suppress_warnings() as sup: sup.filter(UserWarning, "Initial guess is not within " "the specified bounds") result = minimize(prob.fun, [-10, -10], - method='Nelder-Mead', + method=None, bounds=bounds) - assert np.less_equal(bounds.lb, result.x).all() - assert np.less_equal(result.x, bounds.ub).all() + assert np.less_equal(bounds.lb - self.atol, result.x).all() + assert np.less_equal(result.x, bounds.ub + self.atol).all() assert np.allclose(prob.fun(result.x), result.fun) assert np.allclose(result.x, x_opt, atol=1.e-3) @@ -744,7 +663,7 @@ def test_equal_all_bounds(self): sup.filter(UserWarning, "Initial guess is not within " "the specified bounds") result = minimize(prob.fun, [-10, 8], - method='Nelder-Mead', + method=None, bounds=bounds) assert np.allclose(result.x, [4.0, 5.0]) @@ -755,26 +674,22 @@ def test_equal_one_bounds(self): sup.filter(UserWarning, "Initial guess is not within " "the specified bounds") result = minimize(prob.fun, [-10, 8], - method='Nelder-Mead', + method=None, bounds=bounds) assert np.allclose(result.x, [4.0, 16.0]) def test_invalid_bounds(self): prob = Rosenbrock() message = 'An upper bound is less than the corresponding lower bound.' - with pytest.raises(ValueError, match=message): - bounds = Bounds([-np.inf, 1.0], [4.0, -5.0]) - minimize(prob.fun, [-10, 3], - method='Nelder-Mead', - bounds=bounds) - - @pytest.mark.xfail(reason="Failing on Azure Linux and macOS builds, " - "see gh-13846") + bounds = Bounds([-np.inf, 1.0], [4.0, -5.0]) + res = minimize(prob.fun, [-10, 3], method=None, bounds=bounds) + assert res.status == -11 or res.status == 2 + def test_outside_bounds_warning(self): prob = Rosenbrock() - message = "Initial guess is not within the specified bounds" - with pytest.warns(UserWarning, match=message): - bounds = Bounds([-np.inf, 1.0], [4.0, 5.0]) - minimize(prob.fun, [-10, 8], - method='Nelder-Mead', - bounds=bounds) + bounds = Bounds([-np.inf, 1.0], [4.0, 5.0]) + res = minimize(prob.fun, [-10, 8], + method=None, + bounds=bounds) + assert res.success + assert_allclose(res.x, prob.x_opt, rtol=5e-4) From 5262ce8f1b68829952114d83deaea3a70e78d4ec Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Fri, 7 Jul 2023 18:46:39 -0600 Subject: [PATCH 098/170] add custom exception and start using --- cyipopt/cython/ipopt_wrapper.pyx | 7 +++++++ cyipopt/exceptions.py | 10 ++++++++++ 2 files changed, 17 insertions(+) create mode 100644 cyipopt/exceptions.py diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index d0542d83..b471c768 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -17,6 +17,7 @@ import inspect import numpy as np cimport numpy as np +from cyipopt.exceptions import CyIpoptEvaluationError from cyipopt.utils import deprecated_warning, generate_deprecation_warning_msg from ipopt cimport * @@ -868,6 +869,8 @@ cdef Bool objective_cb(Index n, _x[i] = x[i] try: obj_value[0] = self.__objective(_x) + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True @@ -980,6 +983,8 @@ cdef Bool jacobian_cb(Index n, # try: ret_val = self.__jacobianstructure() + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True @@ -1002,6 +1007,8 @@ cdef Bool jacobian_cb(Index n, try: ret_val = self.__jacobian(_x) + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True diff --git a/cyipopt/exceptions.py b/cyipopt/exceptions.py new file mode 100644 index 00000000..9f8efb1d --- /dev/null +++ b/cyipopt/exceptions.py @@ -0,0 +1,10 @@ +class CyIpoptEvaluationError(ArithmeticError): + """An exception that should be raised in evaluation callbacks to signal + to CyIpopt that a numerical error occured during function evaluation. + Whereas most exceptions that occur in callbacks are re-raised, exceptions + of this type are ignored other than communicating to Ipopt that an error + occurred. + + """ + + pass From 11480cf006917c09719aae174ec162121b038165 Mon Sep 17 00:00:00 2001 From: "Benjamin A. Beasley" Date: Thu, 20 Jul 2023 13:30:45 -0400 Subject: [PATCH 099/170] Pin Cython<3 until compatibility can be fixed --- requirements.txt | 2 +- setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index fd07a964..93395a98 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,4 @@ -cython>=0.26 +cython>=0.26,<3 ipopt>=3.12 numpy>=1.15 pkg-config>=0.29.2 diff --git a/setup.py b/setup.py index da14bebf..e7a34baa 100644 --- a/setup.py +++ b/setup.py @@ -21,7 +21,7 @@ # install requirements before import from setuptools import dist SETUP_REQUIRES = [ - "cython >= 0.26", + "cython >= 0.26,<3", "numpy >= 1.15", ] dist.Distribution().fetch_build_eggs(SETUP_REQUIRES) From 236dbe1be72b52c7948af1b3bfd937ea314abf00 Mon Sep 17 00:00:00 2001 From: "Benjamin A. Beasley" Date: Thu, 20 Jul 2023 13:32:33 -0400 Subject: [PATCH 100/170] Remove Cython from install_requires MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit It’s not actually needed at runtime. --- setup.py | 1 - 1 file changed, 1 deletion(-) diff --git a/setup.py b/setup.py index e7a34baa..29aecf5a 100644 --- a/setup.py +++ b/setup.py @@ -49,7 +49,6 @@ EMAIL = "moorepants@gmail.com" URL = "https://github.com/mechmotum/cyipopt" INSTALL_REQUIRES = [ - "cython>=0.26", "numpy>=1.15", "setuptools>=39.0", ] From 5088cfc081ecf2da73fbf6ab8b64e4bfc3e68d3d Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 21 Jul 2023 08:19:37 +0200 Subject: [PATCH 101/170] Add back cython to INSTALL_REQUIRES. --- setup.py | 1 + 1 file changed, 1 insertion(+) diff --git a/setup.py b/setup.py index a2159731..50d47953 100644 --- a/setup.py +++ b/setup.py @@ -48,6 +48,7 @@ EMAIL = "moorepants@gmail.com" URL = "https://github.com/mechmotum/cyipopt" INSTALL_REQUIRES = [ + "cython >= 0.26,<3", "numpy>=1.15", "setuptools>=39.0", ] From de409177506876346f4c465202ad6cf128449a04 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Mon, 24 Jul 2023 09:05:59 -0600 Subject: [PATCH 102/170] import exceptions into cyipopt module --- cyipopt/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/cyipopt/__init__.py b/cyipopt/__init__.py index f116f35e..015dbde3 100644 --- a/cyipopt/__init__.py +++ b/cyipopt/__init__.py @@ -13,3 +13,4 @@ from .ipopt_wrapper import * from .scipy_interface import * from .version import __version__ +from .exceptions import * From 62aa8784e3e1fe69b3b6111f6053eb4fa6408b83 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Mon, 24 Jul 2023 09:06:26 -0600 Subject: [PATCH 103/170] catch CyIpoptEvaluationError in all callbacks --- cyipopt/cython/ipopt_wrapper.pyx | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index b471c768..2c859c40 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -895,6 +895,8 @@ cdef Bool gradient_cb(Index n, try: ret_val = self.__gradient(_x) + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True @@ -931,6 +933,8 @@ cdef Bool constraints_cb(Index n, try: ret_val = self.__constraints(_x) + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True @@ -1069,6 +1073,8 @@ cdef Bool hessian_cb(Index n, # try: ret_val = self.__hessianstructure() + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True @@ -1094,6 +1100,8 @@ cdef Bool hessian_cb(Index n, try: ret_val = self.__hessian(_x, _lambda, obj_factor) + except CyIpoptEvaluationError: + return False except: self.__exception = sys.exc_info() return True From 968e6cbf9d545b83b490ebcfd246ce6c5a9d7746 Mon Sep 17 00:00:00 2001 From: Polina Lakrisenko Date: Tue, 25 Jul 2023 13:29:27 +0200 Subject: [PATCH 104/170] pin cython < 3 --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index c8e60ea0..dc7728c7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,3 +1,3 @@ [build-system] -requires = ["cython >= 0.26", "oldest-supported-numpy", "setuptools>=39.0"] +requires = ["cython >= 0.26, < 3", "oldest-supported-numpy", "setuptools>=39.0"] build-backend = "setuptools.build_meta" From f3d4344d3469ccb34b19fedd9bd35151515d9609 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Jul 2023 07:15:42 -0600 Subject: [PATCH 105/170] add tests for evaluation errors in objective and its gradient --- cyipopt/tests/integration/test_hs071.py | 101 ++++++++++++++++++++++++ 1 file changed, 101 insertions(+) diff --git a/cyipopt/tests/integration/test_hs071.py b/cyipopt/tests/integration/test_hs071.py index aac10ec2..a7a9ab6c 100644 --- a/cyipopt/tests/integration/test_hs071.py +++ b/cyipopt/tests/integration/test_hs071.py @@ -15,3 +15,104 @@ def test_hs071_solve(hs071_initial_guess_fixture, hs071_problem_instance_fixture expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) np.testing.assert_allclose(x, expected_x) + + +def _make_problem(definition, lb, ub, cl, cu): + n = len(lb) + m = len(cl) + return cyipopt.Problem( + n=n, m=m, problem_obj=definition, lb=lb, ub=ub, cl=cl, cu=cu + ) + + +def _solve_and_assert_correct(problem, x0): + x, info = problem.solve(x0) + expected_x = np.array([1.0, 4.74299964, 3.82114998, 1.37940829]) + assert info["status"] == 0 + np.testing.assert_allclose(x, expected_x) + + +def _assert_solve_fails(problem, x0): + x, info = problem.solve(x0) + # The current (Ipopt 3.14.11) return status is "Invalid number". + assert info["status"] < 0 + + +def test_hs071_objective_eval_error( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + class ObjectiveWithError: + def __init__(self): + self.n_eval_error = 0 + + def __call__(self, x): + if x[0] > 1.1: + self.n_eval_error += 1 + raise cyipopt.CyIpoptEvaluationError() + return x[0] * x[3] * np.sum(x[0:3]) + x[2] + + objective_with_error = ObjectiveWithError() + + x0 = hs071_initial_guess_fixture + definition = hs071_definition_instance_fixture + definition.objective = objective_with_error + definition.intermediate = None + + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + + problem = _make_problem(definition, lb, ub, cl, cu) + _solve_and_assert_correct(problem, x0) + + assert objective_with_error.n_eval_error > 0 + + +def test_hs071_grad_obj_eval_error( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + class GradObjWithError: + def __init__(self): + self.n_eval_error = 0 + + def __call__(self, x): + if x[0] > 1.1: + self.n_eval_error += 1 + raise cyipopt.CyIpoptEvaluationError() + return np.array([ + x[0] * x[3] + x[3] * np.sum(x[0:3]), + x[0] * x[3], + x[0] * x[3] + 1.0, + x[0] * np.sum(x[0:3]), + ]) + + gradient_with_error = GradObjWithError() + + x0 = hs071_initial_guess_fixture + definition = hs071_definition_instance_fixture + definition.gradient = gradient_with_error + definition.intermediate = None + + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + + problem = _make_problem(definition, lb, ub, cl, cu) + _assert_solve_fails(problem, x0) + + # Since we fail at the first evaluation error, we know we only encountered one. + assert gradient_with_error.n_eval_error == 1 From 2eea9256a27a238c6fe3b0d93670d87515e3b995 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Jul 2023 09:03:23 -0600 Subject: [PATCH 106/170] test when evaluation error raised by constraint, Jacobian, and Hessian --- cyipopt/tests/integration/test_hs071.py | 132 ++++++++++++++++++++++++ 1 file changed, 132 insertions(+) diff --git a/cyipopt/tests/integration/test_hs071.py b/cyipopt/tests/integration/test_hs071.py index a7a9ab6c..f5c8353a 100644 --- a/cyipopt/tests/integration/test_hs071.py +++ b/cyipopt/tests/integration/test_hs071.py @@ -112,7 +112,139 @@ def __call__(self, x): cu = hs071_constraint_upper_bounds_fixture problem = _make_problem(definition, lb, ub, cl, cu) + # Solve fails when the evaluation error occurs in objective + # gradient evaluation. _assert_solve_fails(problem, x0) # Since we fail at the first evaluation error, we know we only encountered one. assert gradient_with_error.n_eval_error == 1 + + +def test_hs071_constraints_eval_error( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + class ConstraintsWithError: + def __init__(self): + self.n_eval_error = 0 + + def __call__(self, x): + if x[0] > 1.1: + self.n_eval_error += 1 + raise cyipopt.CyIpoptEvaluationError() + return np.array((np.prod(x), np.dot(x, x))) + + constraints_with_error = ConstraintsWithError() + + x0 = hs071_initial_guess_fixture + definition = hs071_definition_instance_fixture + definition.constraints = constraints_with_error + definition.intermediate = None + + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + + problem = _make_problem(definition, lb, ub, cl, cu) + _solve_and_assert_correct(problem, x0) + + assert constraints_with_error.n_eval_error > 0 + + +def test_hs071_jacobian_eval_error( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + class JacobianWithError: + def __init__(self): + self.n_eval_error = 0 + + def __call__(self, x): + if x[0] > 1.1: + self.n_eval_error += 1 + raise cyipopt.CyIpoptEvaluationError() + return np.concatenate((np.prod(x) / x, 2 * x)) + + jacobian_with_error = JacobianWithError() + + x0 = hs071_initial_guess_fixture + definition = hs071_definition_instance_fixture + definition.jacobian = jacobian_with_error + definition.intermediate = None + + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + + problem = _make_problem(definition, lb, ub, cl, cu) + # Solve fails when the evaluation error occurs in constraint + # Jacobian evaluation. + _assert_solve_fails(problem, x0) + + assert jacobian_with_error.n_eval_error == 1 + + +def test_hs071_hessian_eval_error( + hs071_initial_guess_fixture, + hs071_problem_instance_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + class HessianWithError: + def __init__(self): + self.n_eval_error = 0 + + def __call__(self, x, lagrange, obj_factor): + if x[0] > 1.1: + self.n_eval_error += 1 + raise cyipopt.CyIpoptEvaluationError() + + H = obj_factor * np.array([ + (2 * x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (2 * x[0] + x[1] + x[2], x[0], x[0], 0), + ]) + H += lagrange[0] * np.array([ + (0, 0, 0, 0), + (x[2] * x[3], 0, 0, 0), + (x[1] * x[3], x[0] * x[3], 0, 0), + (x[1] * x[2], x[0] * x[2], x[0] * x[1], 0), + ]) + H += lagrange[1] * 2 * np.eye(4) + row, col = np.nonzero(np.tril(np.ones((4, 4)))) + return H[row, col] + + hessian_with_error = HessianWithError() + + x0 = hs071_initial_guess_fixture + definition = hs071_definition_instance_fixture + definition.hessian = hessian_with_error + definition.intermediate = None + + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + + problem = _make_problem(definition, lb, ub, cl, cu) + # Solve fails when the evaluation error occurs in Lagrangian + # Hessian evaluation. + _assert_solve_fails(problem, x0) + + assert hessian_with_error.n_eval_error == 1 From 17eb332b19fdde1033c621c671bed70f0e306d7d Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Jul 2023 09:05:20 -0600 Subject: [PATCH 107/170] add copyright --- cyipopt/exceptions.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/cyipopt/exceptions.py b/cyipopt/exceptions.py index 9f8efb1d..7f85cedd 100644 --- a/cyipopt/exceptions.py +++ b/cyipopt/exceptions.py @@ -1,3 +1,14 @@ +# -*- coding: utf-8 -*- +""" +cyipopt: Python wrapper for the Ipopt optimization package, written in Cython. + +Copyright (C) 2012-2015 Amit Aides +Copyright (C) 2015-2017 Matthias Kümmerer +Copyright (C) 2017-2023 cyipopt developers + +License: EPL 2.0 +""" + class CyIpoptEvaluationError(ArithmeticError): """An exception that should be raised in evaluation callbacks to signal to CyIpopt that a numerical error occured during function evaluation. From c94fd4275f393dfa69a7da8b44bd20985aa6aaf7 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Jul 2023 09:36:30 -0600 Subject: [PATCH 108/170] update documentation and add comment to test --- cyipopt/exceptions.py | 26 ++++++++++++++++++++++++- cyipopt/tests/integration/test_hs071.py | 7 +++++++ 2 files changed, 32 insertions(+), 1 deletion(-) diff --git a/cyipopt/exceptions.py b/cyipopt/exceptions.py index 7f85cedd..b75f36cd 100644 --- a/cyipopt/exceptions.py +++ b/cyipopt/exceptions.py @@ -12,10 +12,34 @@ class CyIpoptEvaluationError(ArithmeticError): """An exception that should be raised in evaluation callbacks to signal to CyIpopt that a numerical error occured during function evaluation. + Whereas most exceptions that occur in callbacks are re-raised, exceptions - of this type are ignored other than communicating to Ipopt that an error + of this type are ignored other than to communicate to Ipopt that an error occurred. + Ipopt handles evaluation errors differently depending on where they are + raised (which evaluation callback returns ``false`` to Ipopt). + When evaluation errors are raised in the following callbacks, Ipopt + attempts to recover by cutting the step size. This is usually the desired + behavior when an undefined value is encountered. + + - ``objective`` + - ``constraints`` + + When raised in the following callbacks, Ipopt fails with an "Invalid number" + return status. + + - ``gradient`` + - ``jacobian`` + - ``hessian`` + + Raising an evaluation error in the following callbacks results is not + supported. + + - ``jacobianstructure`` + - ``hessianstructure`` + - ``intermediate`` + """ pass diff --git a/cyipopt/tests/integration/test_hs071.py b/cyipopt/tests/integration/test_hs071.py index f5c8353a..bc64d005 100644 --- a/cyipopt/tests/integration/test_hs071.py +++ b/cyipopt/tests/integration/test_hs071.py @@ -70,6 +70,13 @@ def __call__(self, x): cu = hs071_constraint_upper_bounds_fixture problem = _make_problem(definition, lb, ub, cl, cu) + # Note that the behavior tested here (success or failure of the solve when + # an evaluation error is raised in each callback) is documented in the + # CyIpoptEvaluationError class. If this behavior changes (e.g. Ipopt starts + # handling evaluation errors in the Jacobian), these tests will start to + # fail. We will need to (a) update these tests and (b) update the + # CyIpoptEvaluationError documentation, possibly with Ipopt version-specific + # behavior. _solve_and_assert_correct(problem, x0) assert objective_with_error.n_eval_error > 0 From 8ec983642c8d699e35da338f398d6c9b8813d1bf Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 25 Jul 2023 09:36:47 -0600 Subject: [PATCH 109/170] add reference documentation for CyIpoptEvaluationError --- docs/source/reference.rst | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/source/reference.rst b/docs/source/reference.rst index abac52a6..190c9d4a 100644 --- a/docs/source/reference.rst +++ b/docs/source/reference.rst @@ -17,3 +17,5 @@ specifications may not be enough to give full guidelines on their uses. .. autofunction:: cyipopt.set_logging_level .. autofunction:: cyipopt.setLoggingLevel + +.. autoclass:: cyipopt.CyIpoptEvaluationError From 79051c0d48d71a206d4fa505f6078008a3ec2630 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 28 Jul 2023 12:50:54 -0700 Subject: [PATCH 110/170] TST: address failing tests --- .../unit/test_scipy_ipopt_trust_constr.py | 77 +++++++++++-------- 1 file changed, 43 insertions(+), 34 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py index 97b7ad70..7bfbbfdf 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py @@ -448,41 +448,49 @@ def hess(x, v): @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") -class TestTrustRegionConstr(TestCase): - +class TestTrustRegionConstr(): + list_of_problems = [Maratos(), + MaratosGradInFunc(), + HyperbolicIneq(), + Rosenbrock(), + IneqRosenbrock(), + EqIneqRosenbrock(), + BoundedRosenbrock(), + Elec(n_electrons=2)] @pytest.mark.slow - def test_list_of_problems(self): - list_of_problems = [Maratos(), - MaratosGradInFunc(), - HyperbolicIneq(), - Rosenbrock(), - IneqRosenbrock(), - EqIneqRosenbrock(), - BoundedRosenbrock(), - Elec(n_electrons=2)] - - for prob in list_of_problems: - for grad in (prob.grad, False): - if prob == list_of_problems[1]: # MaratosGradInFunc - grad = True - for hess in (None,): - result = minimize(prob.fun, prob.x0, - method=None, - jac=grad, hess=hess, - bounds=prob.bounds, - constraints=prob.constr) - - if prob.x_opt is None: - ref = minimize(prob.fun, prob.x0, - method='trust-constr', - jac=grad, hess=hess, - bounds=prob.bounds, - constraints=prob.constr) - ref_x_opt = ref.x - else: - ref_x_opt = prob.x_opt - - assert_allclose(result.x, ref_x_opt, atol=5e-4) + @pytest.mark.parametrize("prob", list_of_problems) + def test_list_of_problems(self, prob): + + for grad in (prob.grad, False): + if prob == self.list_of_problems[1]: # MaratosGradInFunc + grad = True + for hess in (None,): + result = minimize(prob.fun, prob.x0, + method=None, + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is None: + ref = minimize(prob.fun, prob.x0, + method='trust-constr', + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + ref_x_opt = ref.x + else: + ref_x_opt = prob.x_opt + + try: # figure out how to clean this up + res_f_opt = prob.fun(result.x)[0] + ref_f_opt = prob.fun(ref_x_opt)[0] + except IndexError: + res_f_opt = prob.fun(result.x) + ref_f_opt = prob.fun(ref_x_opt) + ref_f_opt = ref_f_opt if np.size(ref_f_opt) == 1 else ref_f_opt[0] + pass1 = np.allclose(result.x, ref_x_opt, atol=5e-4) + pass2 = res_f_opt < ref_f_opt + 1e-6 + assert pass1 or pass2 def test_default_jac_and_hess(self): def fun(x): @@ -656,6 +664,7 @@ def test_rosen_brock_with_bounds(self, case_no): assert np.allclose(prob.fun(result.x), result.fun) assert np.allclose(result.x, x_opt, atol=1.e-3) + @pytest.mark.xfail def test_equal_all_bounds(self): prob = Rosenbrock() bounds = Bounds([4.0, 5.0], [4.0, 5.0]) From 6732afbd2083ef9b8bde5d920a85b7a5f877016c Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 28 Jul 2023 15:29:14 -0700 Subject: [PATCH 111/170] TST: try-except use of Bounds --- cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py index 7bfbbfdf..305469d5 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py @@ -176,7 +176,10 @@ def __init__(self, constr_jac=None, constr_hess=None): self.x_opt = [1.952823, 0.088659] self.constr_jac = constr_jac self.constr_hess = constr_hess - self.bounds = Bounds(0, np.inf) + try: + self.bounds = Bounds(0, np.inf) + except ImportError: + pass def fun(self, x): return 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 @@ -290,7 +293,10 @@ def __init__(self, random_state=0): Rosenbrock.__init__(self, 2, random_state) self.x0 = [-0.2, 0.2] self.x_opt = None - self.bounds = Bounds([-2, 0], [0, 2]) + try: + self.bounds = Bounds([-2, 0], [0, 2]) + except ImportError: + pass class EqIneqRosenbrock(Rosenbrock): From 8610389a222aa9521ca5b27906412bd3a555b226 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Fri, 28 Jul 2023 15:34:34 -0700 Subject: [PATCH 112/170] TST: turn eliminate use of Bounds in __init__ methods --- cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py index 305469d5..db859f83 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py @@ -176,10 +176,7 @@ def __init__(self, constr_jac=None, constr_hess=None): self.x_opt = [1.952823, 0.088659] self.constr_jac = constr_jac self.constr_hess = constr_hess - try: - self.bounds = Bounds(0, np.inf) - except ImportError: - pass + self.bounds = (0, np.inf) def fun(self, x): return 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 @@ -293,10 +290,7 @@ def __init__(self, random_state=0): Rosenbrock.__init__(self, 2, random_state) self.x0 = [-0.2, 0.2] self.x_opt = None - try: - self.bounds = Bounds([-2, 0], [0, 2]) - except ImportError: - pass + self.bounds = [(-2, 0), (0, 2)] class EqIneqRosenbrock(Rosenbrock): From 7918b0f5c5ce6ea9023e5b43a65559b2f77574b7 Mon Sep 17 00:00:00 2001 From: Robert Parker Date: Tue, 29 Aug 2023 09:16:05 -0600 Subject: [PATCH 113/170] dont catch evaluation errors when evaluating jacobian/hessian structure --- cyipopt/cython/ipopt_wrapper.pyx | 4 ---- 1 file changed, 4 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 2c859c40..76b7fa1b 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -987,8 +987,6 @@ cdef Bool jacobian_cb(Index n, # try: ret_val = self.__jacobianstructure() - except CyIpoptEvaluationError: - return False except: self.__exception = sys.exc_info() return True @@ -1073,8 +1071,6 @@ cdef Bool hessian_cb(Index n, # try: ret_val = self.__hessianstructure() - except CyIpoptEvaluationError: - return False except: self.__exception = sys.exc_info() return True From 394665d27f8c99af5537dc5bcf3baf291227744f Mon Sep 17 00:00:00 2001 From: Christoph Hansknecht Date: Wed, 26 Jul 2023 20:12:55 +0200 Subject: [PATCH 114/170] Add sanity checks to Jacobian / Hessian indices --- cyipopt/cython/ipopt_wrapper.pyx | 35 ++++++++++++++++++++++++++++++++ 1 file changed, 35 insertions(+) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 76b7fa1b..43ffb556 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -994,6 +994,21 @@ cdef Bool jacobian_cb(Index n, np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() + if (np_iRow.size != nele_jac) or (np_jCol.size != nele_jac): + msg = b"Invalid number of indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + + if (np_iRow < 0).any() or (np_iRow >= m).any(): + msg = b"Invalid row indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + + if (np_jCol < 0).any() or (np_jCol >= n).any(): + msg = b"Invalid column indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + for i in range(nele_jac): iRow[i] = np_iRow[i] jCol[i] = np_jCol[i] @@ -1078,6 +1093,26 @@ cdef Bool hessian_cb(Index n, np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() + if (np_iRow.size != nele_hess) or (np_jCol.size != nele_hess): + msg = b"Invalid number of indices returned from hessianstructure" + log(msg, logging.ERROR) + return False + + if not(np_iRow >= np_jCol).all(): + msg = b"Indices are not lower triangular in hessianstructure" + log(msg, logging.ERROR) + return False + + if (np_jCol < 0).any(): + msg = b"Invalid column indices returned from hessianstructure" + log(msg, logging.ERROR) + return False + + if (np_iRow >= n).any(): + msg = b"Invalid row indices returned from hessianstructure" + log(msg, logging.ERROR) + return False + for i in range(nele_hess): iRow[i] = np_iRow[i] jCol[i] = np_jCol[i] From 999f0c330dd71331c655f32b3b56a70f21676e05 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 16 Sep 2023 07:24:32 +0200 Subject: [PATCH 115/170] Now picks up Windows Ipopt binary files that are adjacent to setup.py (restores regression) (#220) * Adds a Github action to build against the Ipopt Windows binaries. * Update windows.yml * Update windows.yml * Add back option for loading Ipopt dlls adjacent to the setup.py on Windows. * Use Cython <3 in CI. * Try to fix parsing error. * Try without quotes. * Try quoting all deps. * Fix typo. * Try tilde instead of <. * Try cython 0.29. * Run h2071 after install with windows binaries. * Try ipopt <3.14.12. * Set the IPOPTWINDIR, not sure why it wasn't set before. * Corrected env var. * Print some info about where ipopt is found. * Back to ipopt 3.14. * Run env var before install command. * Improved print statements in setup.py. --- .github/workflows/docs.yml | 2 +- .github/workflows/tests.yml | 7 ++++--- .github/workflows/windows.yml | 26 ++++++++++++++++++++++++++ setup.py | 8 ++++++++ 4 files changed, 39 insertions(+), 4 deletions(-) create mode 100644 .github/workflows/windows.yml diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index f453bbd3..161a4ff6 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -30,7 +30,7 @@ jobs: channels: conda-forge miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -y -v lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt + run: mamba install -y -v lapack "libblas=*=*netlib" "cython>=0.26,<3" "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt - name: Install CyIpopt run: | rm pyproject.toml diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 3a279636..dae49dcd 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -35,7 +35,8 @@ jobs: miniforge-variant: Mambaforge - name: Install basic dependencies run: | - mamba install -q -y lapack "libblas=*=*netlib" cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 + mamba install -q -y lapack "libblas=*=*netlib" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "cython=0.29.*" + - run: echo "IPOPTWINDIR=USECONDAFORGEIPOPT" >> $GITHUB_ENV - name: Install CyIpopt run: | rm pyproject.toml @@ -45,7 +46,7 @@ jobs: run: | python -c "import cyipopt" mamba remove lapack - mamba install -q -y cython>=0.26 "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 pytest>=3.3.2 + mamba install -q -y "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "pytest>=3.3.2" "cython=0.29.*" mamba list pytest - name: Test with pytest and scipy, new ipopt @@ -54,6 +55,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "cython>=0.26" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.9.*" "pytest>=3.3.2" + mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.9.*" "pytest>=3.3.2" "cython=0.29.*" mamba list pytest diff --git a/.github/workflows/windows.yml b/.github/workflows/windows.yml new file mode 100644 index 00000000..97f00633 --- /dev/null +++ b/.github/workflows/windows.yml @@ -0,0 +1,26 @@ +name: windows + +on: [push, pull_request] + +# cancels prior builds for this workflow when new commit is pushed +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +jobs: + build: + name: Manually install on Windows with Ipopt binaries + runs-on: windows-latest + strategy: + fail-fast: false + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.10' + - run: python -m pip install numpy "cython<3" setuptools + - run: Invoke-WebRequest -Uri "https://github.com/coin-or/Ipopt/releases/download/releases%2F3.13.3/Ipopt-3.13.3-win64-msvs2019-md.zip" -OutFile "Ipopt-3.13.3-win64-msvs2019-md.zip" + - run: 7z x Ipopt-3.13.3-win64-msvs2019-md.zip + - run: mv Ipopt-3.13.3-win64-msvs2019-md/* . + - run: python setup.py install + - run: python examples/hs071.py diff --git a/setup.py b/setup.py index 50d47953..28a29049 100644 --- a/setup.py +++ b/setup.py @@ -185,10 +185,18 @@ def handle_ext_modules_general_os(): # environment variable is set to USECONDAFORGEIPOPT then this setup will be # run. if sys.platform == "win32" and ipoptdir == "USECONDAFORGEIPOPT": + print('Using Conda Forge Ipopt on Windows.') ext_module_data = handle_ext_modules_win_32_conda_forge_ipopt() elif sys.platform == "win32" and ipoptdir: + print('Using Ipopt in {} directory on Windows.'.format(ipoptdir)) + ext_module_data = handle_ext_modules_win_32_other_ipopt() + elif sys.platform == "win32" and not ipoptdir: + ipoptdir = os.path.abspath(os.path.dirname(__file__)) + msg = 'Using Ipopt adjacent to setup.py in {} on Windows.' + print(msg.format(ipoptdir)) ext_module_data = handle_ext_modules_win_32_other_ipopt() else: + print('Using Ipopt found with pkg-config.') ext_module_data = handle_ext_modules_general_os() EXT_MODULES, DATA_FILES, include_package_data = ext_module_data # NOTE : The `name` kwarg here is the distribution name, i.e. the name that From 230a9e6772fb24e5ac61e05ab17fba011918ceaa Mon Sep 17 00:00:00 2001 From: Christoph Hansknecht Date: Fri, 15 Sep 2023 22:03:49 +0200 Subject: [PATCH 116/170] Add derivative checks to unit tests --- cyipopt/cython/ipopt_wrapper.pyx | 10 + cyipopt/tests/unit/test_deriv_errors.py | 238 ++++++++++++++++++++++++ 2 files changed, 248 insertions(+) create mode 100644 cyipopt/tests/unit/test_deriv_errors.py diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 43ffb556..e0737f28 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -1032,6 +1032,11 @@ cdef Bool jacobian_cb(Index n, np_jac_g = np.array(ret_val, dtype=DTYPEd).flatten() + if (np_jac_g.size != nele_jac): + msg = b"Invalid number of indices returned from jacobian" + log(msg, logging.ERROR) + return False + for i in range(nele_jac): values[i] = np_jac_g[i] @@ -1139,6 +1144,11 @@ cdef Bool hessian_cb(Index n, np_h = np.array(ret_val, dtype=DTYPEd).flatten() + if (np_h.size != nele_hess): + msg = b"Invalid number of indices returned from hessian" + log(msg, logging.ERROR) + return False + for i in range(nele_hess): values[i] = np_h[i] diff --git a/cyipopt/tests/unit/test_deriv_errors.py b/cyipopt/tests/unit/test_deriv_errors.py new file mode 100644 index 00000000..1ab9d87f --- /dev/null +++ b/cyipopt/tests/unit/test_deriv_errors.py @@ -0,0 +1,238 @@ +import numpy as np + +import cyipopt + +import pytest + + +def full_indices(shape): + def indices(): + r, c = np.indices(shape) + return r.flatten(), c.flatten() + + return indices + + +def tril_indices(size): + def indices(): + return np.tril_indices(size) + + return indices + + +def flatten(func): + def _func(*args): + return func(*args).flatten() + + return _func + + +@pytest.fixture +def hs071_sparse_definition_fixture(hs071_variable_lower_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_definition_instance_fixture): + problem = hs071_definition_instance_fixture + n = len(hs071_variable_lower_bounds_fixture) + m = len(hs071_constraint_lower_bounds_fixture) + + problem.jacobianstructure = full_indices((m, n)) + problem.hessianstructure = tril_indices(n) + + problem.jacobian = flatten(problem.jacobian) + problem.hessian = flatten(problem.hessian) + + return problem + + +@pytest.fixture +def hs071_sparse_instance(hs071_initial_guess_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, + hs071_sparse_definition_fixture): + + class Instance: + pass + + instance = Instance() + instance.problem_definition = hs071_sparse_definition_fixture + instance.x0 = hs071_initial_guess_fixture + instance.lb = hs071_variable_lower_bounds_fixture + instance.ub = hs071_variable_upper_bounds_fixture + instance.cl = hs071_constraint_lower_bounds_fixture + instance.cu = hs071_constraint_upper_bounds_fixture + instance.n = len(instance.x0) + instance.m = len(instance.cl) + + return instance + + +def problem_for_instance(instance): + return cyipopt.Problem(n=instance.n, + m=instance.m, + problem_obj=instance.problem_definition, + lb=instance.lb, + ub=instance.ub, + cl=instance.cl, + cu=instance.cu) + + +def test_solve_sparse(hs071_sparse_instance): + instance = hs071_sparse_instance + problem = problem_for_instance(instance) + + x, info = problem.solve(instance.x0) + + assert info['status'] == 0 + + +def ensure_solve_status(instance, status): + problem = problem_for_instance(instance) + + problem.add_option('max_iter', 50) + x, info = problem.solve(instance.x0) + + assert info['status'] == status + + +def ensure_invalid_option(instance): + # -12: Invalid option + # Thrown in invalid Hessian because "hessian_approximation" + # is not chosen as "limited-memory" + ensure_solve_status(instance, -12) + + +def ensure_invalid_number(instance): + # -13: Invalid Number Detected + ensure_solve_status(instance, -13) + + +def ensure_unrecoverable_exception(instance): + # -100: Unrecoverable Exception + # *Should* be returned from errors in initialization + ensure_solve_status(instance, -100) + + +@pytest.mark.skip(reason="Not caught in Ipopt") +def test_solve_neg_jac(hs071_sparse_instance): + n = hs071_sparse_instance.n + m = hs071_sparse_instance.m + problem_definition = hs071_sparse_instance.problem_definition + + def jacobianstructure(): + r = np.full((m*n,), fill_value=-1, dtype=int) + c = np.full((m*n,), fill_value=-1, dtype=int) + return r, c + + problem_definition.jacobianstructure = jacobianstructure + + ensure_unrecoverable_exception(hs071_sparse_instance) + + +@pytest.mark.skip(reason="Not caught in Ipopt") +def test_solve_large_jac(hs071_sparse_instance): + n = hs071_sparse_instance.n + m = hs071_sparse_instance.m + problem_definition = hs071_sparse_instance.problem_definition + + import logging + logging.basicConfig(level=logging.DEBUG) + + def jacobianstructure(): + r = np.full((m*n,), fill_value=(m + n + 100), dtype=int) + c = np.full((m*n,), fill_value=(m + n + 100), dtype=int) + return r, c + + problem_definition.jacobianstructure = jacobianstructure + + ensure_unrecoverable_exception(hs071_sparse_instance) + + +@pytest.mark.skip(reason="Not caught in Ipopt") +def test_solve_wrong_jac_structure_size(hs071_sparse_instance): + n = hs071_sparse_instance.n + m = hs071_sparse_instance.m + + problem_definition = hs071_sparse_instance.problem_definition + + problem_definition.jacobianstructure = full_indices((m+1, n+1)) + + ensure_unrecoverable_exception(hs071_sparse_instance) + + +@pytest.mark.skip(reason="Not caught in Ipopt") +def test_solve_wrong_jac_value_size(hs071_sparse_instance): + n = hs071_sparse_instance.n + m = hs071_sparse_instance.m + + problem_definition = hs071_sparse_instance.problem_definition + + def jacobian(x): + return np.zeros((m*n + 10,)) + + problem_definition.jacobian = jacobian + + ensure_invalid_number(hs071_sparse_instance) + + +def test_solve_triu_hess(hs071_sparse_instance): + n = hs071_sparse_instance.n + problem_definition = hs071_sparse_instance.problem_definition + problem_definition.hessianstructure = lambda: np.triu_indices(n) + + ensure_invalid_option(hs071_sparse_instance) + + +def test_solve_neg_hess_entries(hs071_sparse_instance): + n = hs071_sparse_instance.n + problem_definition = hs071_sparse_instance.problem_definition + + def hessianstructure(): + r, c = np.tril_indices(n) + rneg = np.full_like(r, -1, dtype=int) + cneg = np.full_like(c, -1, dtype=int) + return rneg, cneg + + problem_definition.hessianstructure = hessianstructure + + ensure_invalid_option(hs071_sparse_instance) + + +def test_solve_large_hess_entries(hs071_sparse_instance): + n = hs071_sparse_instance.n + problem_definition = hs071_sparse_instance.problem_definition + + def hessianstructure(): + r, c = np.tril_indices(n) + rlarge = np.full_like(r, n + 100, dtype=int) + clarge = np.full_like(c, n + 100, dtype=int) + return rlarge, clarge + + problem_definition.hessianstructure = hessianstructure + + ensure_invalid_option(hs071_sparse_instance) + + +def test_solve_wrong_hess_struct_size(hs071_sparse_instance): + n = hs071_sparse_instance.n + problem_definition = hs071_sparse_instance.problem_definition + + def hessianstructure(): + return np.tril_indices(n + 10) + + problem_definition.hessianstructure = hessianstructure + + ensure_invalid_option(hs071_sparse_instance) + + +def test_solve_wrong_hess_value_size(hs071_sparse_instance): + n = hs071_sparse_instance.n + problem_definition = hs071_sparse_instance.problem_definition + + def hessian(x, lag, obj_factor): + return np.zeros((n*n + 10,)) + + problem_definition.hessian = hessian + + ensure_invalid_number(hs071_sparse_instance) From 7d55881aaf7d0e33a871689c45e38fee23afc125 Mon Sep 17 00:00:00 2001 From: Christoph Hansknecht Date: Sat, 16 Sep 2023 20:13:53 +0200 Subject: [PATCH 117/170] Add conditional skipping to Hessian-related tests --- cyipopt/tests/unit/test_deriv_errors.py | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/cyipopt/tests/unit/test_deriv_errors.py b/cyipopt/tests/unit/test_deriv_errors.py index 1ab9d87f..350c22c0 100644 --- a/cyipopt/tests/unit/test_deriv_errors.py +++ b/cyipopt/tests/unit/test_deriv_errors.py @@ -5,6 +5,11 @@ import pytest +pre_3_14_13 = ( + cyipopt.IPOPT_VERSION < (3, 14, 13) +) + + def full_indices(shape): def indices(): r, c = np.indices(shape) @@ -114,7 +119,7 @@ def ensure_unrecoverable_exception(instance): ensure_solve_status(instance, -100) -@pytest.mark.skip(reason="Not caught in Ipopt") +@pytest.mark.skipif(pre_3_14_13, reason="Not caught in Ipopt < (3,14,13)") def test_solve_neg_jac(hs071_sparse_instance): n = hs071_sparse_instance.n m = hs071_sparse_instance.m @@ -130,7 +135,7 @@ def jacobianstructure(): ensure_unrecoverable_exception(hs071_sparse_instance) -@pytest.mark.skip(reason="Not caught in Ipopt") +@pytest.mark.skipif(pre_3_14_13, reason="Not caught in Ipopt < (3,14,13)") def test_solve_large_jac(hs071_sparse_instance): n = hs071_sparse_instance.n m = hs071_sparse_instance.m @@ -149,7 +154,7 @@ def jacobianstructure(): ensure_unrecoverable_exception(hs071_sparse_instance) -@pytest.mark.skip(reason="Not caught in Ipopt") +@pytest.mark.skipif(pre_3_14_13, reason="Not caught in Ipopt < (3,14,13)") def test_solve_wrong_jac_structure_size(hs071_sparse_instance): n = hs071_sparse_instance.n m = hs071_sparse_instance.m @@ -161,7 +166,7 @@ def test_solve_wrong_jac_structure_size(hs071_sparse_instance): ensure_unrecoverable_exception(hs071_sparse_instance) -@pytest.mark.skip(reason="Not caught in Ipopt") +@pytest.mark.skipif(pre_3_14_13, reason="Not caught in Ipopt < (3,14,13)") def test_solve_wrong_jac_value_size(hs071_sparse_instance): n = hs071_sparse_instance.n m = hs071_sparse_instance.m From c4adc479a3d0c2f35ed8be688e9494a4c15ef5b3 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Mon, 18 Sep 2023 19:27:29 -0700 Subject: [PATCH 118/170] DOC: minimize_ipopt: note that Bounds and Constraint objects are accepted --- cyipopt/scipy_interface.py | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 682608c9..069fa3d7 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -159,8 +159,6 @@ def wrapped_fun(x): con_hessian = con.get('hess', None) con_kwargs = con.get('kwargs', {}) if con_jac is None: - con_jac = lambda x0, *args, **kwargs: optimize.approx_fprime( - x0, con_fun, eps, *args, **kwargs) # beware of late binding! def con_jac(x, *args, con_fun=con_fun, **kwargs): def wrapped(x): @@ -448,10 +446,18 @@ def minimize_ipopt(fun, If `method` is one of the SciPy methods, this is a callable that produces the inner product of the Hessian and a vector. Otherwise, an error will be raised if a value other than ``None`` is provided. - bounds : sequence, shape(n, ), optional - Sequence of ``(min, max)`` pairs for each element in `x`. Use ``None`` - to specify no bound. + bounds : sequence of shape(n, ) or :py:class:`scipy.optimize.Bounds`, optional + Simple bounds on decision variables. There are two ways to specify the + bounds: + + 1. Instance of :py:class:`scipy.optimize.Bounds` class. + 2. Sequence of ``(min, max)`` pairs for each element in `x`. Use + ``None`` to specify an infinite bound (i.e., no bound). + constraints : {Constraint, dict}, optional + Linear or nonlinear constraint specified by a dictionary, + :py:class:`scipy.optimize.LinearConstraint`, or + :py:class:`scipy.optimize.NonlinearConstraint`. See :py:func:`scipy.optimize.minimize` for more information. Note that the Jacobian of each constraint corresponds to the ``'jac'`` key and must be a callable function with signature ``jac(x) -> {ndarray, From d3b43d6fcdfdbcb94f82ed975ac0090e7066f3f8 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Mon, 18 Sep 2023 19:39:33 -0700 Subject: [PATCH 119/170] TST: minimize_ipopt: combined tests from SciPy, added license --- .../tests/unit/test_scipy_ipopt_from_scipy.py | 740 +++++++++++++++++- .../unit/test_scipy_ipopt_trust_constr.py | 704 ----------------- 2 files changed, 736 insertions(+), 708 deletions(-) delete mode 100644 cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 966782b6..9e23ddab 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -1,19 +1,60 @@ """ -Unit tests written for scipy.optimize.minimize method='SLSQP'; -adapted for minimize_ipopt +Unit tests written for scipy.optimize.minimize method='SLSQP' and +'method='trust-constr'; adapted for `minimize_ipopt`. Original license +from scipy/LICENSE.txt, 79f5cd1ec0a1ba37ad4c295dedb5543d368be438: + +Copyright (c) 2001-2002 Enthought, Inc. 2003-2023, SciPy Developers. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + +3. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + """ import sys import pytest -from numpy.testing import (assert_, assert_allclose) import numpy as np +from numpy.testing import (TestCase, assert_array_almost_equal, + assert_, assert_allclose, + suppress_warnings) try: - from scipy.optimize import Bounds + from scipy.optimize import (NonlinearConstraint, + LinearConstraint, + Bounds) + from scipy.linalg import block_diag + from scipy.sparse import csc_matrix except ImportError: pass from cyipopt import minimize_ipopt as minimize +### Adapted from scipy/scipy/optimize/tests/test_slsqp.py, +### 6c4a3f3551f9ee52a75c8c3999a57bed8ea67deb class MyCallBack: """pass a custom callback function @@ -458,3 +499,694 @@ def target(x): # The problem is infeasible, so it cannot succeed assert not res.success + + +### Adapted from scipy/scipy/optimize/tests/test_minimize_constrained.py, +### 79f5cd1ec0a1ba37ad4c295dedb5543d368be438 + +class Maratos: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def fun(self, x): + return 2*(x[0]**2 + x[1]**2 - 1) - x[0] + + def grad(self, x): + return np.array([4*x[0]-1, 4*x[1]]) + + def hess(self, x): + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[2*x[0], 2*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class MaratosTestArgs: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, a, b, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.a = a + self.b = b + self.bounds = None + + def _test_args(self, a, b): + if self.a != a or self.b != b: + raise ValueError() + + def fun(self, x, a, b): + self._test_args(a, b) + return 2*(x[0]**2 + x[1]**2 - 1) - x[0] + + def grad(self, x, a, b): + self._test_args(a, b) + return np.array([4*x[0]-1, 4*x[1]]) + + def hess(self, x, a, b): + self._test_args(a, b) + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[4*x[0], 4*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class MaratosGradInFunc: + """Problem 15.4 from Nocedal and Wright + + The following optimization problem: + minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] + Subject to: x[0]**2 + x[1]**2 - 1 = 0 + """ + + def __init__(self, degrees=60, constr_jac=None, constr_hess=None): + rads = degrees/180*np.pi + self.x0 = [np.cos(rads), np.sin(rads)] + self.x_opt = np.array([1.0, 0.0]) + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def fun(self, x): + return (2*(x[0]**2 + x[1]**2 - 1) - x[0], + np.array([4*x[0]-1, 4*x[1]])) + + @property + def grad(self): + return True + + def hess(self, x): + return 4*np.eye(2) + + @property + def constr(self): + def fun(x): + return x[0]**2 + x[1]**2 + + if self.constr_jac is None: + def jac(x): + return [[4*x[0], 4*x[1]]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.eye(2) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 1, 1, jac, hess) + + +class HyperbolicIneq: + """Problem 15.1 from Nocedal and Wright + + The following optimization problem: + minimize 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 + Subject to: 1/(x[0] + 1) - x[1] >= 1/4 + x[0] >= 0 + x[1] >= 0 + """ + def __init__(self, constr_jac=None, constr_hess=None): + self.x0 = [0, 0] + self.x_opt = [1.952823, 0.088659] + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = (0, np.inf) + + def fun(self, x): + return 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 + + def grad(self, x): + return [x[0] - 2, x[1] - 1/2] + + def hess(self, x): + return np.eye(2) + + @property + def constr(self): + def fun(x): + return 1/(x[0] + 1) - x[1] + + if self.constr_jac is None: + def jac(x): + return [[-1/(x[0] + 1)**2, -1]] + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + return 2*v[0]*np.array([[1/(x[0] + 1)**3, 0], + [0, 0]]) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, 0.25, np.inf, jac, hess) + + +class Rosenbrock: + """Rosenbrock function. + + The following optimization problem: + minimize sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0) + """ + + def __init__(self, n=2, random_state=0): + rng = np.random.RandomState(random_state) + self.x0 = rng.uniform(-1, 1, n) + self.x_opt = np.ones(n) + self.bounds = None + + def fun(self, x): + x = np.asarray(x) + r = np.sum(100.0 * (x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0, + axis=0) + return r + + def grad(self, x): + x = np.asarray(x) + xm = x[1:-1] + xm_m1 = x[:-2] + xm_p1 = x[2:] + der = np.zeros_like(x) + der[1:-1] = (200 * (xm - xm_m1**2) - + 400 * (xm_p1 - xm**2) * xm - 2 * (1 - xm)) + der[0] = -400 * x[0] * (x[1] - x[0]**2) - 2 * (1 - x[0]) + der[-1] = 200 * (x[-1] - x[-2]**2) + return der + + def hess(self, x): + x = np.atleast_1d(x) + H = np.diag(-400 * x[:-1], 1) - np.diag(400 * x[:-1], -1) + diagonal = np.zeros(len(x), dtype=x.dtype) + diagonal[0] = 1200 * x[0]**2 - 400 * x[1] + 2 + diagonal[-1] = 200 + diagonal[1:-1] = 202 + 1200 * x[1:-1]**2 - 400 * x[2:] + H = H + np.diag(diagonal) + return H + + @property + def constr(self): + return () + + +class IneqRosenbrock(Rosenbrock): + """Rosenbrock subject to inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: x[0] + 2 x[1] <= 1 + + Taken from matlab ``fmincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-1, -0.5] + self.x_opt = [0.5022, 0.2489] + self.bounds = None + + @property + def constr(self): + A = [[1, 2]] + b = 1 + return LinearConstraint(A, -np.inf, b) + + +class BoundedRosenbrock(Rosenbrock): + """Rosenbrock subject to inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: -2 <= x[0] <= 0 + 0 <= x[1] <= 2 + + Taken from matlab ``fmincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-0.2, 0.2] + self.x_opt = None + self.bounds = [(-2, 0), (0, 2)] + + +class EqIneqRosenbrock(Rosenbrock): + """Rosenbrock subject to equality and inequality constraints. + + The following optimization problem: + minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) + subject to: x[0] + 2 x[1] <= 1 + 2 x[0] + x[1] = 1 + + Taken from matlab ``fimincon`` documentation. + """ + def __init__(self, random_state=0): + Rosenbrock.__init__(self, 2, random_state) + self.x0 = [-1, -0.5] + self.x_opt = [0.41494, 0.17011] + self.bounds = None + + @property + def constr(self): + A_ineq = [[1, 2]] + b_ineq = 1 + A_eq = [[2, 1]] + b_eq = 1 + return (LinearConstraint(A_ineq, -np.inf, b_ineq), + LinearConstraint(A_eq, b_eq, b_eq)) + + +class Elec: + """Distribution of electrons on a sphere. + + Problem no 2 from COPS collection [2]_. Find + the equilibrium state distribution (of minimal + potential) of the electrons positioned on a + conducting sphere. + + References + ---------- + .. [1] E. D. Dolan, J. J. Mor\'{e}, and T. S. Munson, + "Benchmarking optimization software with COPS 3.0.", + Argonne National Lab., Argonne, IL (US), 2004. + """ + def __init__(self, n_electrons=200, random_state=0, + constr_jac=None, constr_hess=None): + self.n_electrons = n_electrons + self.rng = np.random.RandomState(random_state) + # Initial Guess + phi = self.rng.uniform(0, 2 * np.pi, self.n_electrons) + theta = self.rng.uniform(-np.pi, np.pi, self.n_electrons) + x = np.cos(theta) * np.cos(phi) + y = np.cos(theta) * np.sin(phi) + z = np.sin(theta) + self.x0 = np.hstack((x, y, z)) + self.x_opt = None + self.constr_jac = constr_jac + self.constr_hess = constr_hess + self.bounds = None + + def _get_cordinates(self, x): + x_coord = x[:self.n_electrons] + y_coord = x[self.n_electrons:2 * self.n_electrons] + z_coord = x[2 * self.n_electrons:] + return x_coord, y_coord, z_coord + + def _compute_coordinate_deltas(self, x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + dx = x_coord[:, None] - x_coord + dy = y_coord[:, None] - y_coord + dz = z_coord[:, None] - z_coord + return dx, dy, dz + + def fun(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + with np.errstate(divide='ignore'): + dm1 = (dx**2 + dy**2 + dz**2) ** -0.5 + dm1[np.diag_indices_from(dm1)] = 0 + return 0.5 * np.sum(dm1) + + def grad(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + + with np.errstate(divide='ignore'): + dm3 = (dx**2 + dy**2 + dz**2) ** -1.5 + dm3[np.diag_indices_from(dm3)] = 0 + + grad_x = -np.sum(dx * dm3, axis=1) + grad_y = -np.sum(dy * dm3, axis=1) + grad_z = -np.sum(dz * dm3, axis=1) + + return np.hstack((grad_x, grad_y, grad_z)) + + def hess(self, x): + dx, dy, dz = self._compute_coordinate_deltas(x) + d = (dx**2 + dy**2 + dz**2) ** 0.5 + + with np.errstate(divide='ignore'): + dm3 = d ** -3 + dm5 = d ** -5 + + i = np.arange(self.n_electrons) + dm3[i, i] = 0 + dm5[i, i] = 0 + + Hxx = dm3 - 3 * dx**2 * dm5 + Hxx[i, i] = -np.sum(Hxx, axis=1) + + Hxy = -3 * dx * dy * dm5 + Hxy[i, i] = -np.sum(Hxy, axis=1) + + Hxz = -3 * dx * dz * dm5 + Hxz[i, i] = -np.sum(Hxz, axis=1) + + Hyy = dm3 - 3 * dy**2 * dm5 + Hyy[i, i] = -np.sum(Hyy, axis=1) + + Hyz = -3 * dy * dz * dm5 + Hyz[i, i] = -np.sum(Hyz, axis=1) + + Hzz = dm3 - 3 * dz**2 * dm5 + Hzz[i, i] = -np.sum(Hzz, axis=1) + + H = np.vstack(( + np.hstack((Hxx, Hxy, Hxz)), + np.hstack((Hxy, Hyy, Hyz)), + np.hstack((Hxz, Hyz, Hzz)) + )) + + return H + + @property + def constr(self): + def fun(x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + return x_coord**2 + y_coord**2 + z_coord**2 - 1 + + if self.constr_jac is None: + def jac(x): + x_coord, y_coord, z_coord = self._get_cordinates(x) + Jx = 2 * np.diag(x_coord) + Jy = 2 * np.diag(y_coord) + Jz = 2 * np.diag(z_coord) + return csc_matrix(np.hstack((Jx, Jy, Jz))) + else: + jac = self.constr_jac + + if self.constr_hess is None: + def hess(x, v): + D = 2 * np.diag(v) + return block_diag(D, D, D) + else: + hess = self.constr_hess + + return NonlinearConstraint(fun, -np.inf, 0, jac, hess) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +class TestTrustRegionConstr(): + list_of_problems = [Maratos(), + MaratosGradInFunc(), + HyperbolicIneq(), + Rosenbrock(), + IneqRosenbrock(), + EqIneqRosenbrock(), + BoundedRosenbrock(), + Elec(n_electrons=2)] + @pytest.mark.slow + @pytest.mark.parametrize("prob", list_of_problems) + def test_list_of_problems(self, prob): + + for grad in (prob.grad, False): + if prob == self.list_of_problems[1]: # MaratosGradInFunc + grad = True + for hess in (None,): + result = minimize(prob.fun, prob.x0, + method=None, + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + + if prob.x_opt is None: + ref = minimize(prob.fun, prob.x0, + method='trust-constr', + jac=grad, hess=hess, + bounds=prob.bounds, + constraints=prob.constr) + ref_x_opt = ref.x + else: + ref_x_opt = prob.x_opt + + try: # figure out how to clean this up + res_f_opt = prob.fun(result.x)[0] + ref_f_opt = prob.fun(ref_x_opt)[0] + except IndexError: + res_f_opt = prob.fun(result.x) + ref_f_opt = prob.fun(ref_x_opt) + ref_f_opt = ref_f_opt if np.size(ref_f_opt) == 1 else ref_f_opt[0] + pass1 = np.allclose(result.x, ref_x_opt, atol=5e-4) + pass2 = res_f_opt < ref_f_opt + 1e-6 + assert pass1 or pass2 + + def test_default_jac_and_hess(self): + def fun(x): + return (x - 1) ** 2 + bounds = [(-2, 2)] + res = minimize(fun, x0=[-1.5], bounds=bounds, method=None) + assert_array_almost_equal(res.x, 1, decimal=5) + + def test_default_hess(self): + def fun(x): + return (x - 1) ** 2 + + def jac(x): + return 2*(x-1) + + bounds = [(-2, 2)] + res = minimize(fun, x0=[-1.5], bounds=bounds, method=None, + jac=jac) + assert_array_almost_equal(res.x, 1, decimal=5) + + def test_no_constraints(self): + prob = Rosenbrock() + result = minimize(prob.fun, prob.x0, + method=None, + jac=prob.grad) + assert_array_almost_equal(result.x, prob.x_opt, decimal=5) + + def test_args(self): + prob = MaratosTestArgs("a", 234) + + result = minimize(prob.fun, prob.x0, ("a", 234), + method=None, + jac=prob.grad, + bounds=prob.bounds, + constraints=prob.constr) + + assert_array_almost_equal(result.x, prob.x_opt, decimal=2) + + assert result.success + + def test_issue_9044(self): + # https://github.com/scipy/scipy/issues/9044 + # Test the returned `OptimizeResult` contains keys consistent with + # other solvers. + + result = minimize(lambda x: x**2, [0], jac=lambda x: 2*x, + hess=lambda x: 2, method=None) + assert_(result.get('success')) + assert result.get('nit', -1) == 0 + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +class TestEmptyConstraint(TestCase): + """ + Here we minimize x^2+y^2 subject to x^2-y^2>1. + The actual minimum is at (0, 0) which fails the constraint. + Therefore we will find a minimum on the boundary at (+/-1, 0). + + When minimizing on the boundary, optimize uses a set of + constraints that removes the constraint that sets that + boundary. In our case, there's only one constraint, so + the result is an empty constraint. + + This tests that the empty constraint works. + """ + def test_empty_constraint(self): + + def function(x): + return x[0]**2 + x[1]**2 + + def functionjacobian(x): + return np.array([2.*x[0], 2.*x[1]]) + + def constraint(x): + return np.array([x[0]**2 - x[1]**2]) + + def constraintjacobian(x): + return np.array([[2*x[0], -2*x[1]]]) + + def constraintlcoh(x, v): + return np.array([[2., 0.], [0., -2.]]) * v[0] + + constraint = NonlinearConstraint(constraint, 1., np.inf, constraintjacobian, constraintlcoh) + + startpoint = [1., 2.] + + bounds = Bounds([-np.inf, -np.inf], [np.inf, np.inf]) + + result = minimize( + function, + startpoint, + method=None, + jac=functionjacobian, + constraints=[constraint], + bounds=bounds, + ) + + assert_array_almost_equal(abs(result.x), np.array([1, 0]), decimal=4) + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_bug_11886(): + def opt(x): + return x[0]**2+x[1]**2 + + with np.testing.suppress_warnings() as sup: + sup.filter(PendingDeprecationWarning) + A = np.matrix(np.diag([1, 1])) + lin_cons = LinearConstraint(A, -1, np.inf) + minimize(opt, 2*[1], constraints = lin_cons) # just checking that there are no errors + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_gh11649(): + bnds = Bounds(lb=[-1, -1], ub=[1, 1], keep_feasible=True) + + def assert_inbounds(x): + assert np.all(x >= bnds.lb) + assert np.all(x <= bnds.ub) + + def obj(x): + return np.exp(x[0])*(4*x[0]**2 + 2*x[1]**2 + 4*x[0]*x[1] + 2*x[1] + 1) + + def nce(x): + return x[0]**2 + x[1] + + def nci(x): + return x[0]*x[1] + + x0 = np.array((0.99, -0.99)) + nlcs = [NonlinearConstraint(nci, -10, np.inf), + NonlinearConstraint(nce, 1, 1)] + + res = minimize(fun=obj, x0=x0, method=None, + bounds=bnds, constraints=nlcs) + assert res.success + assert_inbounds(res.x) + assert nlcs[0].lb < nlcs[0].fun(res.x) < nlcs[0].ub + assert_allclose(nce(res.x), nlcs[1].ub) + + ref = minimize(fun=obj, x0=x0, method='slsqp', + bounds=bnds, constraints=nlcs) + assert ref.success + assert res.fun <= ref.fun + + +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +class TestBoundedNelderMead: + atol = 1e-7 + + @pytest.mark.parametrize('case_no', range(4)) + def test_rosen_brock_with_bounds(self, case_no): + cases = [(Bounds(-np.inf, np.inf), Rosenbrock().x_opt), + (Bounds(-np.inf, -0.8), [-0.8, -0.8]), + (Bounds(3.0, np.inf), [3.0, 9.0]), + (Bounds([3.0, 1.0], [4.0, 5.0]), [3., 5.])] + bounds, x_opt = cases[case_no] + prob = Rosenbrock() + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, -10], + method=None, + bounds=bounds) + assert np.less_equal(bounds.lb - self.atol, result.x).all() + assert np.less_equal(result.x, bounds.ub + self.atol).all() + assert np.allclose(prob.fun(result.x), result.fun) + assert np.allclose(result.x, x_opt, atol=1.e-3) + + @pytest.mark.xfail + def test_equal_all_bounds(self): + prob = Rosenbrock() + bounds = Bounds([4.0, 5.0], [4.0, 5.0]) + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, 8], + method=None, + bounds=bounds) + assert np.allclose(result.x, [4.0, 5.0]) + + def test_equal_one_bounds(self): + prob = Rosenbrock() + bounds = Bounds([4.0, 5.0], [4.0, 20.0]) + with suppress_warnings() as sup: + sup.filter(UserWarning, "Initial guess is not within " + "the specified bounds") + result = minimize(prob.fun, [-10, 8], + method=None, + bounds=bounds) + assert np.allclose(result.x, [4.0, 16.0]) + + def test_invalid_bounds(self): + prob = Rosenbrock() + message = 'An upper bound is less than the corresponding lower bound.' + bounds = Bounds([-np.inf, 1.0], [4.0, -5.0]) + res = minimize(prob.fun, [-10, 3], method=None, bounds=bounds) + assert res.status == -11 or res.status == 2 + + def test_outside_bounds_warning(self): + prob = Rosenbrock() + bounds = Bounds([-np.inf, 1.0], [4.0, 5.0]) + res = minimize(prob.fun, [-10, 8], + method=None, + bounds=bounds) + assert res.success + assert_allclose(res.x, prob.x_opt, rtol=5e-4) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py b/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py deleted file mode 100644 index db859f83..00000000 --- a/cyipopt/tests/unit/test_scipy_ipopt_trust_constr.py +++ /dev/null @@ -1,704 +0,0 @@ -import sys -import numpy as np -import pytest -from numpy.testing import (TestCase, assert_array_almost_equal, - assert_, assert_allclose, - suppress_warnings) -try: - from scipy.optimize import (NonlinearConstraint, - LinearConstraint, - Bounds) - from scipy.linalg import block_diag - from scipy.sparse import csc_matrix -except ImportError: - pass - -from cyipopt import minimize_ipopt as minimize - - -class Maratos: - """Problem 15.4 from Nocedal and Wright - - The following optimization problem: - minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] - Subject to: x[0]**2 + x[1]**2 - 1 = 0 - """ - - def __init__(self, degrees=60, constr_jac=None, constr_hess=None): - rads = degrees/180*np.pi - self.x0 = [np.cos(rads), np.sin(rads)] - self.x_opt = np.array([1.0, 0.0]) - self.constr_jac = constr_jac - self.constr_hess = constr_hess - self.bounds = None - - def fun(self, x): - return 2*(x[0]**2 + x[1]**2 - 1) - x[0] - - def grad(self, x): - return np.array([4*x[0]-1, 4*x[1]]) - - def hess(self, x): - return 4*np.eye(2) - - @property - def constr(self): - def fun(x): - return x[0]**2 + x[1]**2 - - if self.constr_jac is None: - def jac(x): - return [[2*x[0], 2*x[1]]] - else: - jac = self.constr_jac - - if self.constr_hess is None: - def hess(x, v): - return 2*v[0]*np.eye(2) - else: - hess = self.constr_hess - - return NonlinearConstraint(fun, 1, 1, jac, hess) - - -class MaratosTestArgs: - """Problem 15.4 from Nocedal and Wright - - The following optimization problem: - minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] - Subject to: x[0]**2 + x[1]**2 - 1 = 0 - """ - - def __init__(self, a, b, degrees=60, constr_jac=None, constr_hess=None): - rads = degrees/180*np.pi - self.x0 = [np.cos(rads), np.sin(rads)] - self.x_opt = np.array([1.0, 0.0]) - self.constr_jac = constr_jac - self.constr_hess = constr_hess - self.a = a - self.b = b - self.bounds = None - - def _test_args(self, a, b): - if self.a != a or self.b != b: - raise ValueError() - - def fun(self, x, a, b): - self._test_args(a, b) - return 2*(x[0]**2 + x[1]**2 - 1) - x[0] - - def grad(self, x, a, b): - self._test_args(a, b) - return np.array([4*x[0]-1, 4*x[1]]) - - def hess(self, x, a, b): - self._test_args(a, b) - return 4*np.eye(2) - - @property - def constr(self): - def fun(x): - return x[0]**2 + x[1]**2 - - if self.constr_jac is None: - def jac(x): - return [[4*x[0], 4*x[1]]] - else: - jac = self.constr_jac - - if self.constr_hess is None: - def hess(x, v): - return 2*v[0]*np.eye(2) - else: - hess = self.constr_hess - - return NonlinearConstraint(fun, 1, 1, jac, hess) - - -class MaratosGradInFunc: - """Problem 15.4 from Nocedal and Wright - - The following optimization problem: - minimize 2*(x[0]**2 + x[1]**2 - 1) - x[0] - Subject to: x[0]**2 + x[1]**2 - 1 = 0 - """ - - def __init__(self, degrees=60, constr_jac=None, constr_hess=None): - rads = degrees/180*np.pi - self.x0 = [np.cos(rads), np.sin(rads)] - self.x_opt = np.array([1.0, 0.0]) - self.constr_jac = constr_jac - self.constr_hess = constr_hess - self.bounds = None - - def fun(self, x): - return (2*(x[0]**2 + x[1]**2 - 1) - x[0], - np.array([4*x[0]-1, 4*x[1]])) - - @property - def grad(self): - return True - - def hess(self, x): - return 4*np.eye(2) - - @property - def constr(self): - def fun(x): - return x[0]**2 + x[1]**2 - - if self.constr_jac is None: - def jac(x): - return [[4*x[0], 4*x[1]]] - else: - jac = self.constr_jac - - if self.constr_hess is None: - def hess(x, v): - return 2*v[0]*np.eye(2) - else: - hess = self.constr_hess - - return NonlinearConstraint(fun, 1, 1, jac, hess) - - -class HyperbolicIneq: - """Problem 15.1 from Nocedal and Wright - - The following optimization problem: - minimize 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 - Subject to: 1/(x[0] + 1) - x[1] >= 1/4 - x[0] >= 0 - x[1] >= 0 - """ - def __init__(self, constr_jac=None, constr_hess=None): - self.x0 = [0, 0] - self.x_opt = [1.952823, 0.088659] - self.constr_jac = constr_jac - self.constr_hess = constr_hess - self.bounds = (0, np.inf) - - def fun(self, x): - return 1/2*(x[0] - 2)**2 + 1/2*(x[1] - 1/2)**2 - - def grad(self, x): - return [x[0] - 2, x[1] - 1/2] - - def hess(self, x): - return np.eye(2) - - @property - def constr(self): - def fun(x): - return 1/(x[0] + 1) - x[1] - - if self.constr_jac is None: - def jac(x): - return [[-1/(x[0] + 1)**2, -1]] - else: - jac = self.constr_jac - - if self.constr_hess is None: - def hess(x, v): - return 2*v[0]*np.array([[1/(x[0] + 1)**3, 0], - [0, 0]]) - else: - hess = self.constr_hess - - return NonlinearConstraint(fun, 0.25, np.inf, jac, hess) - - -class Rosenbrock: - """Rosenbrock function. - - The following optimization problem: - minimize sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0) - """ - - def __init__(self, n=2, random_state=0): - rng = np.random.RandomState(random_state) - self.x0 = rng.uniform(-1, 1, n) - self.x_opt = np.ones(n) - self.bounds = None - - def fun(self, x): - x = np.asarray(x) - r = np.sum(100.0 * (x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0, - axis=0) - return r - - def grad(self, x): - x = np.asarray(x) - xm = x[1:-1] - xm_m1 = x[:-2] - xm_p1 = x[2:] - der = np.zeros_like(x) - der[1:-1] = (200 * (xm - xm_m1**2) - - 400 * (xm_p1 - xm**2) * xm - 2 * (1 - xm)) - der[0] = -400 * x[0] * (x[1] - x[0]**2) - 2 * (1 - x[0]) - der[-1] = 200 * (x[-1] - x[-2]**2) - return der - - def hess(self, x): - x = np.atleast_1d(x) - H = np.diag(-400 * x[:-1], 1) - np.diag(400 * x[:-1], -1) - diagonal = np.zeros(len(x), dtype=x.dtype) - diagonal[0] = 1200 * x[0]**2 - 400 * x[1] + 2 - diagonal[-1] = 200 - diagonal[1:-1] = 202 + 1200 * x[1:-1]**2 - 400 * x[2:] - H = H + np.diag(diagonal) - return H - - @property - def constr(self): - return () - - -class IneqRosenbrock(Rosenbrock): - """Rosenbrock subject to inequality constraints. - - The following optimization problem: - minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) - subject to: x[0] + 2 x[1] <= 1 - - Taken from matlab ``fmincon`` documentation. - """ - def __init__(self, random_state=0): - Rosenbrock.__init__(self, 2, random_state) - self.x0 = [-1, -0.5] - self.x_opt = [0.5022, 0.2489] - self.bounds = None - - @property - def constr(self): - A = [[1, 2]] - b = 1 - return LinearConstraint(A, -np.inf, b) - - -class BoundedRosenbrock(Rosenbrock): - """Rosenbrock subject to inequality constraints. - - The following optimization problem: - minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) - subject to: -2 <= x[0] <= 0 - 0 <= x[1] <= 2 - - Taken from matlab ``fmincon`` documentation. - """ - def __init__(self, random_state=0): - Rosenbrock.__init__(self, 2, random_state) - self.x0 = [-0.2, 0.2] - self.x_opt = None - self.bounds = [(-2, 0), (0, 2)] - - -class EqIneqRosenbrock(Rosenbrock): - """Rosenbrock subject to equality and inequality constraints. - - The following optimization problem: - minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2) - subject to: x[0] + 2 x[1] <= 1 - 2 x[0] + x[1] = 1 - - Taken from matlab ``fimincon`` documentation. - """ - def __init__(self, random_state=0): - Rosenbrock.__init__(self, 2, random_state) - self.x0 = [-1, -0.5] - self.x_opt = [0.41494, 0.17011] - self.bounds = None - - @property - def constr(self): - A_ineq = [[1, 2]] - b_ineq = 1 - A_eq = [[2, 1]] - b_eq = 1 - return (LinearConstraint(A_ineq, -np.inf, b_ineq), - LinearConstraint(A_eq, b_eq, b_eq)) - - -class Elec: - """Distribution of electrons on a sphere. - - Problem no 2 from COPS collection [2]_. Find - the equilibrium state distribution (of minimal - potential) of the electrons positioned on a - conducting sphere. - - References - ---------- - .. [1] E. D. Dolan, J. J. Mor\'{e}, and T. S. Munson, - "Benchmarking optimization software with COPS 3.0.", - Argonne National Lab., Argonne, IL (US), 2004. - """ - def __init__(self, n_electrons=200, random_state=0, - constr_jac=None, constr_hess=None): - self.n_electrons = n_electrons - self.rng = np.random.RandomState(random_state) - # Initial Guess - phi = self.rng.uniform(0, 2 * np.pi, self.n_electrons) - theta = self.rng.uniform(-np.pi, np.pi, self.n_electrons) - x = np.cos(theta) * np.cos(phi) - y = np.cos(theta) * np.sin(phi) - z = np.sin(theta) - self.x0 = np.hstack((x, y, z)) - self.x_opt = None - self.constr_jac = constr_jac - self.constr_hess = constr_hess - self.bounds = None - - def _get_cordinates(self, x): - x_coord = x[:self.n_electrons] - y_coord = x[self.n_electrons:2 * self.n_electrons] - z_coord = x[2 * self.n_electrons:] - return x_coord, y_coord, z_coord - - def _compute_coordinate_deltas(self, x): - x_coord, y_coord, z_coord = self._get_cordinates(x) - dx = x_coord[:, None] - x_coord - dy = y_coord[:, None] - y_coord - dz = z_coord[:, None] - z_coord - return dx, dy, dz - - def fun(self, x): - dx, dy, dz = self._compute_coordinate_deltas(x) - with np.errstate(divide='ignore'): - dm1 = (dx**2 + dy**2 + dz**2) ** -0.5 - dm1[np.diag_indices_from(dm1)] = 0 - return 0.5 * np.sum(dm1) - - def grad(self, x): - dx, dy, dz = self._compute_coordinate_deltas(x) - - with np.errstate(divide='ignore'): - dm3 = (dx**2 + dy**2 + dz**2) ** -1.5 - dm3[np.diag_indices_from(dm3)] = 0 - - grad_x = -np.sum(dx * dm3, axis=1) - grad_y = -np.sum(dy * dm3, axis=1) - grad_z = -np.sum(dz * dm3, axis=1) - - return np.hstack((grad_x, grad_y, grad_z)) - - def hess(self, x): - dx, dy, dz = self._compute_coordinate_deltas(x) - d = (dx**2 + dy**2 + dz**2) ** 0.5 - - with np.errstate(divide='ignore'): - dm3 = d ** -3 - dm5 = d ** -5 - - i = np.arange(self.n_electrons) - dm3[i, i] = 0 - dm5[i, i] = 0 - - Hxx = dm3 - 3 * dx**2 * dm5 - Hxx[i, i] = -np.sum(Hxx, axis=1) - - Hxy = -3 * dx * dy * dm5 - Hxy[i, i] = -np.sum(Hxy, axis=1) - - Hxz = -3 * dx * dz * dm5 - Hxz[i, i] = -np.sum(Hxz, axis=1) - - Hyy = dm3 - 3 * dy**2 * dm5 - Hyy[i, i] = -np.sum(Hyy, axis=1) - - Hyz = -3 * dy * dz * dm5 - Hyz[i, i] = -np.sum(Hyz, axis=1) - - Hzz = dm3 - 3 * dz**2 * dm5 - Hzz[i, i] = -np.sum(Hzz, axis=1) - - H = np.vstack(( - np.hstack((Hxx, Hxy, Hxz)), - np.hstack((Hxy, Hyy, Hyz)), - np.hstack((Hxz, Hyz, Hzz)) - )) - - return H - - @property - def constr(self): - def fun(x): - x_coord, y_coord, z_coord = self._get_cordinates(x) - return x_coord**2 + y_coord**2 + z_coord**2 - 1 - - if self.constr_jac is None: - def jac(x): - x_coord, y_coord, z_coord = self._get_cordinates(x) - Jx = 2 * np.diag(x_coord) - Jy = 2 * np.diag(y_coord) - Jz = 2 * np.diag(z_coord) - return csc_matrix(np.hstack((Jx, Jy, Jz))) - else: - jac = self.constr_jac - - if self.constr_hess is None: - def hess(x, v): - D = 2 * np.diag(v) - return block_diag(D, D, D) - else: - hess = self.constr_hess - - return NonlinearConstraint(fun, -np.inf, 0, jac, hess) - - -@pytest.mark.skipif("scipy" not in sys.modules, - reason="Test only valid if Scipy available.") -class TestTrustRegionConstr(): - list_of_problems = [Maratos(), - MaratosGradInFunc(), - HyperbolicIneq(), - Rosenbrock(), - IneqRosenbrock(), - EqIneqRosenbrock(), - BoundedRosenbrock(), - Elec(n_electrons=2)] - @pytest.mark.slow - @pytest.mark.parametrize("prob", list_of_problems) - def test_list_of_problems(self, prob): - - for grad in (prob.grad, False): - if prob == self.list_of_problems[1]: # MaratosGradInFunc - grad = True - for hess in (None,): - result = minimize(prob.fun, prob.x0, - method=None, - jac=grad, hess=hess, - bounds=prob.bounds, - constraints=prob.constr) - - if prob.x_opt is None: - ref = minimize(prob.fun, prob.x0, - method='trust-constr', - jac=grad, hess=hess, - bounds=prob.bounds, - constraints=prob.constr) - ref_x_opt = ref.x - else: - ref_x_opt = prob.x_opt - - try: # figure out how to clean this up - res_f_opt = prob.fun(result.x)[0] - ref_f_opt = prob.fun(ref_x_opt)[0] - except IndexError: - res_f_opt = prob.fun(result.x) - ref_f_opt = prob.fun(ref_x_opt) - ref_f_opt = ref_f_opt if np.size(ref_f_opt) == 1 else ref_f_opt[0] - pass1 = np.allclose(result.x, ref_x_opt, atol=5e-4) - pass2 = res_f_opt < ref_f_opt + 1e-6 - assert pass1 or pass2 - - def test_default_jac_and_hess(self): - def fun(x): - return (x - 1) ** 2 - bounds = [(-2, 2)] - res = minimize(fun, x0=[-1.5], bounds=bounds, method=None) - assert_array_almost_equal(res.x, 1, decimal=5) - - def test_default_hess(self): - def fun(x): - return (x - 1) ** 2 - - def jac(x): - return 2*(x-1) - - bounds = [(-2, 2)] - res = minimize(fun, x0=[-1.5], bounds=bounds, method=None, - jac=jac) - assert_array_almost_equal(res.x, 1, decimal=5) - - def test_no_constraints(self): - prob = Rosenbrock() - result = minimize(prob.fun, prob.x0, - method=None, - jac=prob.grad) - assert_array_almost_equal(result.x, prob.x_opt, decimal=5) - - def test_args(self): - prob = MaratosTestArgs("a", 234) - - result = minimize(prob.fun, prob.x0, ("a", 234), - method=None, - jac=prob.grad, - bounds=prob.bounds, - constraints=prob.constr) - - assert_array_almost_equal(result.x, prob.x_opt, decimal=2) - - assert result.success - - def test_issue_9044(self): - # https://github.com/scipy/scipy/issues/9044 - # Test the returned `OptimizeResult` contains keys consistent with - # other solvers. - - result = minimize(lambda x: x**2, [0], jac=lambda x: 2*x, - hess=lambda x: 2, method=None) - assert_(result.get('success')) - assert result.get('nit', -1) == 0 - - -@pytest.mark.skipif("scipy" not in sys.modules, - reason="Test only valid if Scipy available.") -class TestEmptyConstraint(TestCase): - """ - Here we minimize x^2+y^2 subject to x^2-y^2>1. - The actual minimum is at (0, 0) which fails the constraint. - Therefore we will find a minimum on the boundary at (+/-1, 0). - - When minimizing on the boundary, optimize uses a set of - constraints that removes the constraint that sets that - boundary. In our case, there's only one constraint, so - the result is an empty constraint. - - This tests that the empty constraint works. - """ - def test_empty_constraint(self): - - def function(x): - return x[0]**2 + x[1]**2 - - def functionjacobian(x): - return np.array([2.*x[0], 2.*x[1]]) - - def constraint(x): - return np.array([x[0]**2 - x[1]**2]) - - def constraintjacobian(x): - return np.array([[2*x[0], -2*x[1]]]) - - def constraintlcoh(x, v): - return np.array([[2., 0.], [0., -2.]]) * v[0] - - constraint = NonlinearConstraint(constraint, 1., np.inf, constraintjacobian, constraintlcoh) - - startpoint = [1., 2.] - - bounds = Bounds([-np.inf, -np.inf], [np.inf, np.inf]) - - result = minimize( - function, - startpoint, - method=None, - jac=functionjacobian, - constraints=[constraint], - bounds=bounds, - ) - - assert_array_almost_equal(abs(result.x), np.array([1, 0]), decimal=4) - - -@pytest.mark.skipif("scipy" not in sys.modules, - reason="Test only valid if Scipy available.") -def test_bug_11886(): - def opt(x): - return x[0]**2+x[1]**2 - - with np.testing.suppress_warnings() as sup: - sup.filter(PendingDeprecationWarning) - A = np.matrix(np.diag([1, 1])) - lin_cons = LinearConstraint(A, -1, np.inf) - minimize(opt, 2*[1], constraints = lin_cons) # just checking that there are no errors - - -@pytest.mark.skipif("scipy" not in sys.modules, - reason="Test only valid if Scipy available.") -def test_gh11649(): - bnds = Bounds(lb=[-1, -1], ub=[1, 1], keep_feasible=True) - - def assert_inbounds(x): - assert np.all(x >= bnds.lb) - assert np.all(x <= bnds.ub) - - def obj(x): - return np.exp(x[0])*(4*x[0]**2 + 2*x[1]**2 + 4*x[0]*x[1] + 2*x[1] + 1) - - def nce(x): - return x[0]**2 + x[1] - - def nci(x): - return x[0]*x[1] - - x0 = np.array((0.99, -0.99)) - nlcs = [NonlinearConstraint(nci, -10, np.inf), - NonlinearConstraint(nce, 1, 1)] - - res = minimize(fun=obj, x0=x0, method=None, - bounds=bnds, constraints=nlcs) - assert res.success - assert_inbounds(res.x) - assert nlcs[0].lb < nlcs[0].fun(res.x) < nlcs[0].ub - assert_allclose(nce(res.x), nlcs[1].ub) - - ref = minimize(fun=obj, x0=x0, method='slsqp', - bounds=bnds, constraints=nlcs) - assert ref.success - assert res.fun <= ref.fun - - -@pytest.mark.skipif("scipy" not in sys.modules, - reason="Test only valid if Scipy available.") -class TestBoundedNelderMead: - atol = 1e-7 - - @pytest.mark.parametrize('case_no', range(4)) - def test_rosen_brock_with_bounds(self, case_no): - cases = [(Bounds(-np.inf, np.inf), Rosenbrock().x_opt), - (Bounds(-np.inf, -0.8), [-0.8, -0.8]), - (Bounds(3.0, np.inf), [3.0, 9.0]), - (Bounds([3.0, 1.0], [4.0, 5.0]), [3., 5.])] - bounds, x_opt = cases[case_no] - prob = Rosenbrock() - with suppress_warnings() as sup: - sup.filter(UserWarning, "Initial guess is not within " - "the specified bounds") - result = minimize(prob.fun, [-10, -10], - method=None, - bounds=bounds) - assert np.less_equal(bounds.lb - self.atol, result.x).all() - assert np.less_equal(result.x, bounds.ub + self.atol).all() - assert np.allclose(prob.fun(result.x), result.fun) - assert np.allclose(result.x, x_opt, atol=1.e-3) - - @pytest.mark.xfail - def test_equal_all_bounds(self): - prob = Rosenbrock() - bounds = Bounds([4.0, 5.0], [4.0, 5.0]) - with suppress_warnings() as sup: - sup.filter(UserWarning, "Initial guess is not within " - "the specified bounds") - result = minimize(prob.fun, [-10, 8], - method=None, - bounds=bounds) - assert np.allclose(result.x, [4.0, 5.0]) - - def test_equal_one_bounds(self): - prob = Rosenbrock() - bounds = Bounds([4.0, 5.0], [4.0, 20.0]) - with suppress_warnings() as sup: - sup.filter(UserWarning, "Initial guess is not within " - "the specified bounds") - result = minimize(prob.fun, [-10, 8], - method=None, - bounds=bounds) - assert np.allclose(result.x, [4.0, 16.0]) - - def test_invalid_bounds(self): - prob = Rosenbrock() - message = 'An upper bound is less than the corresponding lower bound.' - bounds = Bounds([-np.inf, 1.0], [4.0, -5.0]) - res = minimize(prob.fun, [-10, 3], method=None, bounds=bounds) - assert res.status == -11 or res.status == 2 - - def test_outside_bounds_warning(self): - prob = Rosenbrock() - bounds = Bounds([-np.inf, 1.0], [4.0, 5.0]) - res = minimize(prob.fun, [-10, 8], - method=None, - bounds=bounds) - assert res.success - assert_allclose(res.x, prob.x_opt, rtol=5e-4) From 943d18bd80c6eec387874df34d1b1800ea649363 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Mon, 18 Sep 2023 19:44:52 -0700 Subject: [PATCH 120/170] Exclude SciPy test file --- MANIFEST.in | 1 + 1 file changed, 1 insertion(+) diff --git a/MANIFEST.in b/MANIFEST.in index 7efc396c..c6c550cc 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -4,6 +4,7 @@ include LICENSE include CHANGELOG.rst include README.rst exclude pyproject.toml +exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py recursive-include tests *.py From 21e3b463bf790f0e83c76def73e170c9b85cdd89 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 09:34:01 +0200 Subject: [PATCH 121/170] Removed requirments.txt: not used and had ipopt incorrectly present. --- requirements.txt | 5 ----- 1 file changed, 5 deletions(-) delete mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 93395a98..00000000 --- a/requirements.txt +++ /dev/null @@ -1,5 +0,0 @@ -cython>=0.26,<3 -ipopt>=3.12 -numpy>=1.15 -pkg-config>=0.29.2 -setuptools>=39.0 From 86c933712dd403b7a2521b41c05e385acf16ea63 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 09:48:00 +0200 Subject: [PATCH 122/170] Bumped minimum dependencies to match those in Ubuntu 22.04. --- .github/workflows/docs.yml | 2 +- .github/workflows/tests.yml | 10 +++++----- docs/requirements.txt | 4 ++-- docs/source/install.rst | 17 +++++++++-------- pyproject.toml | 2 +- setup.py | 10 ++++------ 6 files changed, 22 insertions(+), 23 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 161a4ff6..8f295d13 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -30,7 +30,7 @@ jobs: channels: conda-forge miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -y -v lapack "libblas=*=*netlib" "cython>=0.26,<3" "ipopt=${{ matrix.ipopt-version }}" numpy>=1.15 pkg-config>=0.29.2 setuptools>=39.0 --file docs/requirements.txt + run: mamba install -y -v lapack "libblas=*=*netlib" "cython=0.29.*" "ipopt=${{ matrix.ipopt-version }}" numpy>=1.21.5 pkg-config>=0.29.2 setuptools>=44.1.1 --file docs/requirements.txt - name: Install CyIpopt run: | rm pyproject.toml diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index dae49dcd..53bac79f 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -33,20 +33,20 @@ jobs: python-version: ${{ matrix.python-version }} channels: conda-forge miniforge-variant: Mambaforge - - name: Install basic dependencies + - name: Install basic dependencies against generic blas/lapack run: | - mamba install -q -y lapack "libblas=*=*netlib" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "cython=0.29.*" + mamba install -q -y lapack "libblas=*=*netlib" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "cython=0.29.*" - run: echo "IPOPTWINDIR=USECONDAFORGEIPOPT" >> $GITHUB_ENV - name: Install CyIpopt run: | rm pyproject.toml python -m pip install . mamba list - - name: Test with pytest + - name: Test with pytest using OS specific blas/lapack run: | python -c "import cyipopt" mamba remove lapack - mamba install -q -y "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "pytest>=3.3.2" "cython=0.29.*" + mamba install -q -y "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "pytest>=6.2.5" "cython=0.29.*" mamba list pytest - name: Test with pytest and scipy, new ipopt @@ -55,6 +55,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.15" "pkg-config>=0.29.2" "setuptools>=39.0" "scipy=1.9.*" "pytest>=3.3.2" "cython=0.29.*" + mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0" "pytest>=6.2.5" "cython=0.29.*" mamba list pytest diff --git a/docs/requirements.txt b/docs/requirements.txt index 9b4b2447..e61cb3c4 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,2 +1,2 @@ -numpydoc>=0.7 -sphinx>=1.6.7 +numpydoc>=1.2 +sphinx>=4.3.2 diff --git a/docs/source/install.rst b/docs/source/install.rst index 3fe320ea..d4ec57d2 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -28,12 +28,12 @@ dependencies: * C/C++ compiler * pkg-config [only for Linux and Mac] - * Ipopt [>= 3.13 on Windows] - * Python 3.6+ - * setuptools - * cython - * numpy - * scipy [optional] + * Ipopt >=3.12 [>= 3.13 on Windows] + * Python 3.8+ + * setuptools >=44.1.1 + * cython >=0.29.8,<3 + * NumPy >=1.21.5 + * SciPy >=1.8 [optional] The binaries and header files of the Ipopt package can be obtained from http://www.coin-or.org/download/binary/Ipopt/. These include a version compiled @@ -44,12 +44,13 @@ On Linux and Mac ~~~~~~~~~~~~~~~~ For Linux and Mac, the ``ipopt`` executable should be in your path and -discoverable by pkg-config, i.e. this command should return a valid result:: +discoverable by ``pkg-config``, i.e. this command should return a valid +result:: $ pkg-config --libs --cflags ipopt You will need to install Ipopt in a system location or set ``LD_LIBRARY_PATH`` -if pkg-config does not find the executable. +if ``pkg-config`` does not find the executable. Once all the dependencies are installed, execute:: diff --git a/pyproject.toml b/pyproject.toml index dc7728c7..c85fe423 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,3 +1,3 @@ [build-system] -requires = ["cython >= 0.26, < 3", "oldest-supported-numpy", "setuptools>=39.0"] +requires = ["cython>=0.29.28,<3", "oldest-supported-numpy","setuptools>=44.1.1"] build-backend = "setuptools.build_meta" diff --git a/setup.py b/setup.py index 28a29049..a014d064 100644 --- a/setup.py +++ b/setup.py @@ -20,8 +20,9 @@ # install requirements before import from setuptools import dist SETUP_REQUIRES = [ - "cython >= 0.26,<3", - "numpy >= 1.15", + "cython>=0.29.28,<3", + "numpy>=1.21.5", + "setuptools>=44.1.1", ] dist.Distribution().fetch_build_eggs(SETUP_REQUIRES) @@ -48,9 +49,7 @@ EMAIL = "moorepants@gmail.com" URL = "https://github.com/mechmotum/cyipopt" INSTALL_REQUIRES = [ - "cython >= 0.26,<3", - "numpy>=1.15", - "setuptools>=39.0", + "numpy>=1.21.5", ] LICENSE = "EPL-2.0" CLASSIFIERS = [ @@ -58,7 +57,6 @@ "License :: OSI Approved :: Eclipse Public License 2.0 (EPL-2.0)", "Intended Audience :: Science/Research", "Operating System :: OS Independent", - "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", From 0187e5bc4bee0c616676f934bafd02c901f93ba6 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 09:50:43 +0200 Subject: [PATCH 123/170] Corrected Cython version in docs. --- docs/source/install.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/install.rst b/docs/source/install.rst index d4ec57d2..1d81fb72 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -31,7 +31,7 @@ dependencies: * Ipopt >=3.12 [>= 3.13 on Windows] * Python 3.8+ * setuptools >=44.1.1 - * cython >=0.29.8,<3 + * cython >=0.29.28,<3 * NumPy >=1.21.5 * SciPy >=1.8 [optional] From 667024ea73370f0744f3c2c5ee5587b889a476ea Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 09:52:56 +0200 Subject: [PATCH 124/170] Pin deps in manual windows build. --- .github/workflows/windows.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/windows.yml b/.github/workflows/windows.yml index 97f00633..d71baf5e 100644 --- a/.github/workflows/windows.yml +++ b/.github/workflows/windows.yml @@ -18,7 +18,7 @@ jobs: - uses: actions/setup-python@v4 with: python-version: '3.10' - - run: python -m pip install numpy "cython<3" setuptools + - run: python -m pip install "numpy>=1.21.5" "cython>=0.29.28,<3" "setuptools>44.1.1" - run: Invoke-WebRequest -Uri "https://github.com/coin-or/Ipopt/releases/download/releases%2F3.13.3/Ipopt-3.13.3-win64-msvs2019-md.zip" -OutFile "Ipopt-3.13.3-win64-msvs2019-md.zip" - run: 7z x Ipopt-3.13.3-win64-msvs2019-md.zip - run: mv Ipopt-3.13.3-win64-msvs2019-md/* . From 3446839b501b35385457b335f67c2e00c06b7f52 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 10:08:50 +0200 Subject: [PATCH 125/170] Add pins to the conda cyipopt-dev file. --- conda/cyipopt-dev.yml | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/conda/cyipopt-dev.yml b/conda/cyipopt-dev.yml index c74002bd..241ea329 100644 --- a/conda/cyipopt-dev.yml +++ b/conda/cyipopt-dev.yml @@ -2,13 +2,14 @@ name: cyipopt-dev channels: - conda-forge dependencies: - - cython - - ipopt + - cython >=0.29.28,<3 + - ipopt >=3.12 - libblas * *netlib - - numpy - - pkg-config - - pytest + - numpy >=1.21.5 + - numpydoc >=1.2 + - pkg-config >=0.29.2 + - pytest >=6.2.5 - python >=3.6 - - scipy - - setuptools - - sphinx + - scipy >=1.8 + - setuptools >=44.1.1 + - sphinx >=4.3.2 From 27aa8bcb2beccdd929102d3097c0f6355a980b32 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:03:36 +0200 Subject: [PATCH 126/170] Updated the changelog for v1.3.0. --- CHANGELOG.rst | 35 +++++++++++++++++++++++++++++++++++ 1 file changed, 35 insertions(+) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 3781bfd3..ad7686d6 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -39,6 +39,41 @@ Version History [1.3.0.dev0] - XXXX-XX-XX ~~~~~~~~~~~~~~~~~~~~~~~~~ +Added ++++++ + +- Added a ``pyproject.toml`` file with build dependencies. #162 +- Added support for sparse Jacobians in the SciPy interface. #170 +- Added ``get_current_iterate`` and ``get_current_violations`` methods to + Problem class. #182 +- Added installation instructions for Ubuntu 22.04 LTS apt dependencies. +- Added a script to build manylinux wheels. #189 +- Improved documentation of ``minimize_ipopt()``. #194 +- Added support for all SciPy ``minimize()`` methods. #200 +- Added support for SciPy style bounds in ``minimize_ipopt()`` and added input + validation. #207 +- Added new ``CyIpoptEvaluationError`` and included it in relevance callbacks. + #215 +- Added dimension checks for Jacobian and Hessian attributes/methods. #216 + +Fixed ++++++ + +- Fixed import of ``MemoizeJac`` from scipy.optimize. #183 +- ``args`` and ``kwargs`` can be passed to all functions used in + ``minimize_ipopt()``. #197 +- Fixed late binding bug in ``minimize_ipopt()`` when defining constraint + Jacobians. #208 +- Pinned build dependency Cython to < 3. #212 #214 #223 +- Fixed installation on Windows for official Ipopt binaries adjacent to + ``setup.py``. #220 + +Changed ++++++++ + +- Changed the license to Eclipse Public 2.0. #185 +- Updated all dependency pins to match those in Ubuntu 22.04 LTS. #223 + [1.2.0] - 2022-11-28 ~~~~~~~~~~~~~~~~~~~~ From c3538cc2b2642b7ca5d43a3526c344b19c27bc41 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:04:19 +0200 Subject: [PATCH 127/170] Include pyproject.toml in the source tarball. --- MANIFEST.in | 1 - 1 file changed, 1 deletion(-) diff --git a/MANIFEST.in b/MANIFEST.in index c6c550cc..a9903d42 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -3,7 +3,6 @@ include AUTHORS include LICENSE include CHANGELOG.rst include README.rst -exclude pyproject.toml exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py From 943698d774fc40dc80ba85bc1dd5f8d997d65b03 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:09:06 +0200 Subject: [PATCH 128/170] Added new authors. --- AUTHORS | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/AUTHORS b/AUTHORS index cd774a85..d2c2a9d8 100644 --- a/AUTHORS +++ b/AUTHORS @@ -14,3 +14,9 @@ Jonathan Helgert Benjamin A. Beasley Tobias Kies John Siirola +Nikitas Rontsis +Robert Parker +Matt Haberland +Benjamin A. Beasley +Polina Lakrisenko +Christoph Hansknecht From 3937de070520c8817aa1061390d57492cd5cf4b5 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:16:41 +0200 Subject: [PATCH 129/170] Update copyright date. --- docs/source/conf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/conf.py b/docs/source/conf.py index 08a9385d..0708bc1c 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -53,7 +53,7 @@ # General information about the project. project = u'cyipopt' -copyright = u'2022, cyipopt developers' +copyright = u'2023, cyipopt developers' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the From c8ba2d04af0fe69fcba516f506ddcbd9839e7509 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:16:47 +0200 Subject: [PATCH 130/170] Spelling. --- licenses_manylinux_bundled_libraries/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/licenses_manylinux_bundled_libraries/README.md b/licenses_manylinux_bundled_libraries/README.md index 68832085..94bd49fd 100644 --- a/licenses_manylinux_bundled_libraries/README.md +++ b/licenses_manylinux_bundled_libraries/README.md @@ -1 +1 @@ -This folder contains licenses for all the libraries that are bundled in the `manylinux` wheels of `cyipopt`. These linceses are appended to `cyipopt`'s `LICENSE` file when building these wheels in `build_manylinux_wheel.sh`. \ No newline at end of file +This folder contains licenses for all the libraries that are bundled in the `manylinux` wheels of `cyipopt`. These licenses are appended to `cyipopt`'s `LICENSE` file when building these wheels in `build_manylinux_wheel.sh`. From 7ac1eec3d999f536574230f09eb4427abb50e3f3 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:21:03 +0200 Subject: [PATCH 131/170] Order matters on excluding files. --- MANIFEST.in | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/MANIFEST.in b/MANIFEST.in index a9903d42..4dc02de4 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -3,10 +3,10 @@ include AUTHORS include LICENSE include CHANGELOG.rst include README.rst -exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py recursive-include tests *.py recursive-include docs Makefile *.bat *.rst *.py +exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py prune include* prune lib* From 2db0a1e2030bff7dbaeec0934d9dda93601389de Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:43:33 +0200 Subject: [PATCH 132/170] Bumped to 1.3.0. --- CHANGELOG.rst | 4 ++-- cyipopt/version.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index ad7686d6..d2e9f9ea 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,8 +36,8 @@ Include sections: Version History --------------- -[1.3.0.dev0] - XXXX-XX-XX -~~~~~~~~~~~~~~~~~~~~~~~~~ +[1.3.0] - 2023-09-23 +~~~~~~~~~~~~~~~~~~~~ Added +++++ diff --git a/cyipopt/version.py b/cyipopt/version.py index bfacf1ab..3e6cdbe5 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.3.0.dev0' +__version__ = '1.3.0' From f68a639eb518210dc82a31e190b87f6cba9dfc20 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sat, 23 Sep 2023 11:49:32 +0200 Subject: [PATCH 133/170] Bump to version 1.4.0.dev0. --- CHANGELOG.rst | 3 +++ cyipopt/version.py | 2 +- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index d2e9f9ea..924fd056 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,6 +36,9 @@ Include sections: Version History --------------- +[1.4.0.dev0] - XXXX-XX-XX +~~~~~~~~~~~~~~~~~~~~~~~~~ + [1.3.0] - 2023-09-23 ~~~~~~~~~~~~~~~~~~~~ diff --git a/cyipopt/version.py b/cyipopt/version.py index 3e6cdbe5..3339e4b6 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.3.0' +__version__ = '1.4.0.dev0' From d4e986af8f4bab6ae64153f5803cdb8c0bd98d9f Mon Sep 17 00:00:00 2001 From: Christoph Hansknecht Date: Sat, 23 Sep 2023 13:25:36 +0200 Subject: [PATCH 134/170] Ensure that all cyipopt callbacks are "noexcept" --- cyipopt/cython/ipopt_wrapper.pyx | 513 ++++++++++++++++++------------- 1 file changed, 298 insertions(+), 215 deletions(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index e0737f28..d1a3e6da 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -858,16 +858,20 @@ cdef Bool objective_cb(Index n, Bool new_x, Number* obj_value, UserDataPtr user_data - ): - - log(b"objective_cb", logging.INFO) - - cdef object self = user_data + ) noexcept: + cdef Problem self cdef Index i - cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) - for i in range(n): - _x[i] = x[i] + cdef np.ndarray[DTYPEd_t, ndim=1] _x + try: + log(b"objective_cb", logging.INFO) + + self = user_data + _x = np.zeros((n,), dtype=DTYPEd) + + for i in range(n): + _x[i] = x[i] + obj_value[0] = self.__objective(_x) except CyIpoptEvaluationError: return False @@ -881,31 +885,35 @@ cdef Bool gradient_cb(Index n, Bool new_x, Number* grad_f, UserDataPtr user_data - ): + ) noexcept: - log(b"gradient_cb", logging.INFO) - - cdef object self = user_data + cdef Problem self cdef Index i - cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) + cdef np.ndarray[DTYPEd_t, ndim=1] _x cdef np.ndarray[DTYPEd_t, ndim=1] np_grad_f - for i in range(n): - _x[i] = x[i] - try: + log(b"gradient_cb", logging.INFO) + + self = user_data + _x = np.zeros((n,), dtype=DTYPEd) + + for i in range(n): + _x[i] = x[i] + ret_val = self.__gradient(_x) + + np_grad_f = np.array(ret_val, dtype=DTYPEd).flatten() + + for i in range(n): + grad_f[i] = np_grad_f[i] + except CyIpoptEvaluationError: return False except: self.__exception = sys.exc_info() return True - np_grad_f = np.array(ret_val, dtype=DTYPEd).flatten() - - for i in range(n): - grad_f[i] = np_grad_f[i] - return True @@ -915,34 +923,125 @@ cdef Bool constraints_cb(Index n, Index m, Number* g, UserDataPtr user_data - ): + ) noexcept: + cdef Problem self + cdef Index i + cdef np.ndarray[DTYPEd_t, ndim=1] _x + cdef np.ndarray[DTYPEd_t, ndim=1] np_g + + try: + log(b"constraints_cb", logging.INFO) + + self = user_data + _x = np.zeros((n,), dtype=DTYPEd) + + if not self.__constraints: + log(b"Constraints callback not defined", logging.DEBUG) + return True + + for i in range(n): + _x[i] = x[i] + + ret_val = self.__constraints(_x) + + np_g = np.array(ret_val, dtype=DTYPEd).flatten() + + for i in range(m): + g[i] = np_g[i] - log(b"constraints_cb", logging.INFO) + except CyIpoptEvaluationError: + return False + except: + self.__exception = sys.exc_info() + return True - cdef object self = user_data + return True + + +cdef Bool jacobian_struct_cb(Index n, + Index m, + Index nele_jac, + Index *iRow, + Index *jCol, + UserDataPtr user_data): + cdef Problem self = user_data + cdef Index i + + if not self.__jacobianstructure: + msg = b"Jacobian callback not defined. assuming a dense jacobian" + log(msg, logging.INFO) + + # + # Assuming a dense Jacobian + # + s = np.unravel_index(np.arange(self.__m * self.__n), + (self.__m, self.__n)) + np_iRow = np.array(s[0], dtype=DTYPEi) + np_jCol = np.array(s[1], dtype=DTYPEi) + else: + # + # Sparse Jacobian + # + ret_val = self.__jacobianstructure() + + np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() + np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() + + if (np_iRow.size != nele_jac) or (np_jCol.size != nele_jac): + msg = b"Invalid number of indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + + if (np_iRow < 0).any() or (np_iRow >= m).any(): + msg = b"Invalid row indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + + if (np_jCol < 0).any() or (np_jCol >= n).any(): + msg = b"Invalid column indices returned from jacobianstructure" + log(msg, logging.ERROR) + return False + + for i in range(nele_jac): + iRow[i] = np_iRow[i] + jCol[i] = np_jCol[i] + + return True + + +cdef Bool jacobian_value_cb(Index n, + Number* x, + Bool new_x, + Index m, + Index nele_jac, + Number *values, + UserDataPtr user_data + ): + cdef Problem self = user_data cdef Index i cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) - cdef np.ndarray[DTYPEd_t, ndim=1] np_g - if not self.__constraints: - log(b"Constraints callback not defined", logging.DEBUG) + if not self.__jacobian: + log(b"Jacobian callback not defined", logging.DEBUG) return True for i in range(n): _x[i] = x[i] try: - ret_val = self.__constraints(_x) + ret_val = self.__jacobian(_x) except CyIpoptEvaluationError: - return False - except: - self.__exception = sys.exc_info() - return True + return False - np_g = np.array(ret_val, dtype=DTYPEd).flatten() + np_jac_g = np.array(ret_val, dtype=DTYPEd).flatten() - for i in range(m): - g[i] = np_g[i] + if (np_jac_g.size != nele_jac): + msg = b"Invalid number of indices returned from jacobian" + log(msg, logging.ERROR) + return False + + for i in range(nele_jac): + values[i] = np_jac_g[i] return True @@ -956,89 +1055,134 @@ cdef Bool jacobian_cb(Index n, Index *jCol, Number *values, UserDataPtr user_data - ): + ) noexcept: + cdef Problem self + cdef object ret_val - log(b"jacobian_cb", logging.INFO) + try: + log(b"jacobian_cb", logging.INFO) + ret_val = True + self = user_data + if values == NULL: + log(b"Querying for iRow/jCol indices of the jacobian", logging.INFO) + ret_val = jacobian_struct_cb(n, m, nele_jac, iRow, jCol, user_data) + else: + log(b"Querying for jacobian", logging.INFO) + ret_val = jacobian_value_cb(n, x, new_x, m, nele_jac, values, user_data) - cdef object self = user_data + except: + self.__exception = sys.exc_info() + finally: + return ret_val + + +cdef Bool hessian_struct_cb(Index n, + Index m, + Index nele_hess, + Index *iRow, + Index *jCol, + UserDataPtr user_data + ): + cdef Problem self = user_data cdef Index i - cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) cdef np.ndarray[DTYPEi_t, ndim=1] np_iRow cdef np.ndarray[DTYPEi_t, ndim=1] np_jCol - cdef np.ndarray[DTYPEd_t, ndim=1] np_jac_g - if values == NULL: - log(b"Querying for iRow/jCol indices of the jacobian", logging.INFO) + msg = b"Querying for iRow/jCol indices of the Hessian" + log(msg, logging.INFO) - if not self.__jacobianstructure: - msg = b"Jacobian callback not defined. assuming a dense jacobian" - log(msg, logging.INFO) + if not self.__hessianstructure: + msg = (b"Hessian callback not defined. assuming a lower triangle " + b"Hessian") + log(msg, logging.INFO) - # - # Assuming a dense Jacobian - # - s = np.unravel_index(np.arange(self.__m * self.__n), - (self.__m, self.__n)) - np_iRow = np.array(s[0], dtype=DTYPEi) - np_jCol = np.array(s[1], dtype=DTYPEi) - else: - # - # Sparse Jacobian - # - try: - ret_val = self.__jacobianstructure() - except: - self.__exception = sys.exc_info() - return True - - np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() - np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() - - if (np_iRow.size != nele_jac) or (np_jCol.size != nele_jac): - msg = b"Invalid number of indices returned from jacobianstructure" - log(msg, logging.ERROR) - return False - - if (np_iRow < 0).any() or (np_iRow >= m).any(): - msg = b"Invalid row indices returned from jacobianstructure" - log(msg, logging.ERROR) - return False - - if (np_jCol < 0).any() or (np_jCol >= n).any(): - msg = b"Invalid column indices returned from jacobianstructure" - log(msg, logging.ERROR) - return False - - for i in range(nele_jac): - iRow[i] = np_iRow[i] - jCol[i] = np_jCol[i] + # + # Assuming a lower triangle Hessian + # Note: + # There is a need to reconvert the s.col and s.row to arrays + # because they have the wrong stride + # + row, col = np.nonzero(np.tril(np.ones((self.__n, self.__n)))) + np_iRow = np.array(col, dtype=DTYPEi) + np_jCol = np.array(row, dtype=DTYPEi) else: - log(b"Querying for jacobian", logging.INFO) + # + # Sparse Hessian + # + ret_val = self.__hessianstructure() - if not self.__jacobian: - log(b"Jacobian callback not defined", logging.DEBUG) - return True + np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() + np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() - for i in range(n): - _x[i] = x[i] + if (np_iRow.size != nele_hess) or (np_jCol.size != nele_hess): + msg = b"Invalid number of indices returned from hessianstructure" + log(msg, logging.ERROR) + return False - try: - ret_val = self.__jacobian(_x) - except CyIpoptEvaluationError: + if not(np_iRow >= np_jCol).all(): + msg = b"Indices are not lower triangular in hessianstructure" + log(msg, logging.ERROR) return False - except: - self.__exception = sys.exc_info() - return True - np_jac_g = np.array(ret_val, dtype=DTYPEd).flatten() + if (np_jCol < 0).any(): + msg = b"Invalid column indices returned from hessianstructure" + log(msg, logging.ERROR) + return False - if (np_jac_g.size != nele_jac): - msg = b"Invalid number of indices returned from jacobian" + if (np_iRow >= n).any(): + msg = b"Invalid row indices returned from hessianstructure" log(msg, logging.ERROR) return False - for i in range(nele_jac): - values[i] = np_jac_g[i] + for i in range(nele_hess): + iRow[i] = np_iRow[i] + jCol[i] = np_jCol[i] + + return True + + +cdef Bool hessian_value_cb(Index n, + Number* x, + Bool new_x, + Number obj_factor, + Index m, + Number *lambd, + Bool new_lambda, + Index nele_hess, + Number *values, + UserDataPtr user_data + ): + cdef Index i + cdef Problem self = user_data + cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) + cdef np.ndarray[DTYPEd_t, ndim=1] _lambda = np.zeros((m,), dtype=DTYPEd) + + if not self.__hessian: + msg = (b"Hessian callback not defined but called by the Ipopt " + b"algorithm") + log(msg, logging.ERROR) + return False + + for i in range(n): + _x[i] = x[i] + + for i in range(m): + _lambda[i] = lambd[i] + + try: + ret_val = self.__hessian(_x, _lambda, obj_factor) + except CyIpoptEvaluationError: + return False + + np_h = np.array(ret_val, dtype=DTYPEd).flatten() + + if (np_h.size != nele_hess): + msg = b"Invalid number of indices returned from hessian" + log(msg, logging.ERROR) + return False + + for i in range(nele_hess): + values[i] = np_h[i] return True @@ -1055,104 +1199,38 @@ cdef Bool hessian_cb(Index n, Index *jCol, Number *values, UserDataPtr user_data - ): + ) noexcept: + cdef object self + cdef object ret_val - log(b"hessian_cb", logging.INFO) - - cdef object self = user_data - cdef Index i - cdef np.ndarray[DTYPEd_t, ndim=1] _x = np.zeros((n,), dtype=DTYPEd) - cdef np.ndarray[DTYPEd_t, ndim=1] _lambda = np.zeros((m,), dtype=DTYPEd) - cdef np.ndarray[DTYPEi_t, ndim=1] np_iRow - cdef np.ndarray[DTYPEi_t, ndim=1] np_jCol - cdef np.ndarray[DTYPEd_t, ndim=1] np_h - - if values == NULL: - msg = b"Querying for iRow/jCol indices of the Hessian" - log(msg, logging.INFO) + try: + log(b"hessian_cb", logging.INFO) + ret_val = True + self = user_data - if not self.__hessianstructure: - msg = (b"Hessian callback not defined. assuming a lower triangle " - b"Hessian") - log(msg, logging.INFO) + if values == NULL: + ret_val = hessian_struct_cb(n, + m, + nele_hess, + iRow, + jCol, + user_data) - # - # Assuming a lower triangle Hessian - # Note: - # There is a need to reconvert the s.col and s.row to arrays - # because they have the wrong stride - # - row, col = np.nonzero(np.tril(np.ones((self.__n, self.__n)))) - np_iRow = np.array(col, dtype=DTYPEi) - np_jCol = np.array(row, dtype=DTYPEi) else: - # - # Sparse Hessian - # - try: - ret_val = self.__hessianstructure() - except: - self.__exception = sys.exc_info() - return True - - np_iRow = np.array(ret_val[0], dtype=DTYPEi).flatten() - np_jCol = np.array(ret_val[1], dtype=DTYPEi).flatten() - - if (np_iRow.size != nele_hess) or (np_jCol.size != nele_hess): - msg = b"Invalid number of indices returned from hessianstructure" - log(msg, logging.ERROR) - return False - - if not(np_iRow >= np_jCol).all(): - msg = b"Indices are not lower triangular in hessianstructure" - log(msg, logging.ERROR) - return False - - if (np_jCol < 0).any(): - msg = b"Invalid column indices returned from hessianstructure" - log(msg, logging.ERROR) - return False - - if (np_iRow >= n).any(): - msg = b"Invalid row indices returned from hessianstructure" - log(msg, logging.ERROR) - return False - - for i in range(nele_hess): - iRow[i] = np_iRow[i] - jCol[i] = np_jCol[i] - else: - if not self.__hessian: - msg = (b"Hessian callback not defined but called by the Ipopt " - b"algorithm") - log(msg, logging.ERROR) - return False - - for i in range(n): - _x[i] = x[i] - - for i in range(m): - _lambda[i] = lambd[i] - - try: - ret_val = self.__hessian(_x, _lambda, obj_factor) - except CyIpoptEvaluationError: - return False - except: - self.__exception = sys.exc_info() - return True - - np_h = np.array(ret_val, dtype=DTYPEd).flatten() - - if (np_h.size != nele_hess): - msg = b"Invalid number of indices returned from hessian" - log(msg, logging.ERROR) - return False - - for i in range(nele_hess): - values[i] = np_h[i] - - return True + ret_val = hessian_value_cb(n, + x, + new_x, + obj_factor, + m, + lambd, + new_lambda, + nele_hess, + values, + user_data) + except: + self.__exception = sys.exc_info() + finally: + return ret_val cdef Bool intermediate_cb(Index alg_mod, @@ -1167,35 +1245,40 @@ cdef Bool intermediate_cb(Index alg_mod, Number alpha_pr, Index ls_trials, UserDataPtr user_data - ): + ) noexcept: + cdef Problem self - log(b"intermediate_cb", logging.INFO) + try: + log(b"intermediate_cb", logging.INFO) - cdef object self = user_data + self = user_data - if self.__exception: - return False + if self.__exception: + return False - if not self.__intermediate: - return True + if not self.__intermediate: + return True - ret_val = self.__intermediate(alg_mod, + ret_val = self.__intermediate(alg_mod, iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials - ) - - if ret_val is None: + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials + ) + + if ret_val is None: + return True + except: + self.__exception = sys.exc_info() return True - return ret_val + return True class problem(Problem): From 9b60806dfb51ca06df076b9e073a42012ee80af6 Mon Sep 17 00:00:00 2001 From: Christoph Hansknecht Date: Sat, 23 Sep 2023 14:06:23 +0200 Subject: [PATCH 135/170] Remove cython version restriction --- pyproject.toml | 2 +- setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index c85fe423..f4ce20a3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,3 +1,3 @@ [build-system] -requires = ["cython>=0.29.28,<3", "oldest-supported-numpy","setuptools>=44.1.1"] +requires = ["cython>=0.29.28", "oldest-supported-numpy","setuptools>=44.1.1"] build-backend = "setuptools.build_meta" diff --git a/setup.py b/setup.py index a014d064..eb6e1f48 100644 --- a/setup.py +++ b/setup.py @@ -20,7 +20,7 @@ # install requirements before import from setuptools import dist SETUP_REQUIRES = [ - "cython>=0.29.28,<3", + "cython>=0.29.28", "numpy>=1.21.5", "setuptools>=44.1.1", ] From 9d3c731de911e582903a6b2a4823d0b3aa000b4e Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 24 Sep 2023 17:09:46 -0700 Subject: [PATCH 136/170] ENH: expose 'eps' option for finite difference step size --- cyipopt/scipy_interface.py | 44 +++++++++++++++-------- cyipopt/tests/unit/test_scipy_optional.py | 20 +++++++++++ 2 files changed, 49 insertions(+), 15 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 069fa3d7..d9a7fd16 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -57,8 +57,9 @@ class IpoptProblemWrapper(object): Extra keyword arguments passed to the objective function and its derivatives (``fun``, ``jac``, ``hess``). jac : callable, optional - The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> - ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. + The Jacobian (gradient) of the objective function: + ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. + If ``None``, SciPy's ``approx_fprime`` is used. hess : callable, optional If ``None``, the Hessian is computed using IPOPT's numerical methods. Explicitly defined Hessians are not yet supported for this class. @@ -74,7 +75,8 @@ class IpoptProblemWrapper(object): `(con_val, con_jac)` consisting of the evaluated constraint `con_val` and the evaluated jacobian `con_jac`. eps : float, optional - Epsilon used in finite differences. + Step size used in finite difference approximations of the objective + function gradient and constraint Jacobian. con_dims : array_like, optional Dimensions p_1, ..., p_m of the m constraint functions g_1, ..., g_m : R^n -> R^(p_i). @@ -436,8 +438,9 @@ def minimize_ipopt(fun, If unspecified (default), Ipopt is used. :py:func:`scipy.optimize.minimize` methods can also be used. jac : callable, optional - The Jacobian of the objective function: ``jac(x, *args, **kwargs) -> - ndarray, shape(n, )``. If ``None``, SciPy's ``approx_fprime`` is used. + The Jacobian (gradient) of the objective function: + ``jac(x, *args, **kwargs) -> ndarray, shape(n, )``. + If ``None``, SciPy's ``approx_fprime`` is used. hess : callable, optional The Hessian of the objective function: ``hess(x) -> ndarray, shape(n, )``. @@ -469,18 +472,28 @@ def minimize_ipopt(fun, The desired relative convergence tolerance, passed as an option to Ipopt. See [1]_ for details. options : dict, optional - A dictionary of solver options. The options ``disp`` and ``maxiter`` - are automatically mapped to their Ipopt equivalents ``print_level`` - and ``max_iter``. All other options are passed directly to Ipopt. See - [1]_ for details. + A dictionary of solver options. + + When `method` is unspecified (default: Ipopt), the options + ``disp`` and ``maxiter`` are automatically mapped to their Ipopt + equivalents ``print_level`` and ``max_iter``, and ``eps`` is used to + control the step size of finite difference gradient and constraint + Jacobian approximations. All other options are passed directly + to Ipopt. See [1]_ for details. + + For other values of `method`, `options` is passed to the SciPy solver. + See [2]_ for details. callback : callable, optional - This parameter is ignored unless `method` is one of the SciPy - methods. + This argument is ignored by the default `method` (Ipopt). + If `method` is one of the SciPy methods, this is a callable that is + called once per iteration. See [2]_ for details. References ---------- .. [1] COIN-OR Project. "Ipopt: Ipopt Options". https://coin-or.github.io/Ipopt/OPTIONS.html + .. [2] The SciPy Developers. "scipy.optimize.minimize". + https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html Examples -------- @@ -552,6 +565,10 @@ def minimize_ipopt(fun, sparse_jacs, jac_nnz_row, jac_nnz_col = _get_sparse_jacobian_structure( constraints, x0) + if options is None: + options = {} + eps = options.pop('eps', 1e-8) + problem = IpoptProblemWrapper(fun, args=args, kwargs=kwargs, @@ -559,15 +576,12 @@ def minimize_ipopt(fun, hess=hess, hessp=hessp, constraints=constraints, - eps=1e-8, + eps=eps, con_dims=con_dims, sparse_jacs=sparse_jacs, jac_nnz_row=jac_nnz_row, jac_nnz_col=jac_nnz_col) - if options is None: - options = {} - nlp = cyipopt.Problem(n=len(x0), m=len(cl), problem_obj=problem, diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index a9b049ce..2880552b 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -575,3 +575,23 @@ def test_minimize_late_binding_bug(): assert res.success np.testing.assert_allclose(res.x, ref.x) np.testing.assert_allclose(res.fun, ref.fun) + + +def test_gh115_eps_option(): + # gh-115 requested that the `eps` argument be exposed as an option. Verify + # that it is working as advertised (at least for the objective function). + def f(x): + if f.x is None: + f.x = x + elif f.dx is None: + f.dx = x - f.x + return x ** 2 + + f.x, f.dx = None, None + cyipopt.minimize_ipopt(f, x0=0) + np.testing.assert_equal(f.dx, 1e-8) + + f.x, f.dx = None, None + eps = 1e-9 + cyipopt.minimize_ipopt(f, x0=0, options={'eps': eps}) + np.testing.assert_equal(f.dx, eps) From cdcfcf13bbefe2338bac906827c315d37101c984 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 24 Sep 2023 17:14:11 -0700 Subject: [PATCH 137/170] TST: minimize_ipopt: add back test_gh1758 --- .../tests/unit/test_scipy_ipopt_from_scipy.py | 52 +++++++++---------- 1 file changed, 26 insertions(+), 26 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 9e23ddab..1913befe 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -458,32 +458,32 @@ def solve(self): problem = NestedProblem() problem.solve() - # def test_gh1758(self): - # # minimize_ipopt finds this to be infeasible - # - # # the test suggested in gh1758 - # # https://nlopt.readthedocs.io/en/latest/NLopt_Tutorial/ - # # implement two equality constraints, in R^2. - # def fun(x): - # return np.sqrt(x[1]) - # - # def f_eqcon(x): - # """ Equality constraint """ - # return x[1] - (2 * x[0]) ** 3 - # - # def f_eqcon2(x): - # """ Equality constraint """ - # return x[1] - (-x[0] + 1) ** 3 - # - # c1 = {'type': 'eq', 'fun': f_eqcon} - # c2 = {'type': 'eq', 'fun': f_eqcon2} - # - # res = minimize(fun, [8, 0.25], method=None, - # constraints=[c1, c2], bounds=[(-0.5, 1), (0, 8)]) - # - # np.testing.assert_allclose(res.fun, 0.5443310539518) - # np.testing.assert_allclose(res.x, [0.33333333, 0.2962963]) - # assert res.success + def test_gh1758(self): + # minimize_ipopt finds this to be infeasible + + # the test suggested in gh1758 + # https://nlopt.readthedocs.io/en/latest/NLopt_Tutorial/ + # implement two equality constraints, in R^2. + def fun(x): + return np.sqrt(x[1]) + + def f_eqcon(x): + """ Equality constraint """ + return x[1] - (2 * x[0]) ** 3 + + def f_eqcon2(x): + """ Equality constraint """ + return x[1] - (-x[0] + 1) ** 3 + + c1 = {'type': 'eq', 'fun': f_eqcon} + c2 = {'type': 'eq', 'fun': f_eqcon2} + + res = minimize(fun, [8, 0.25], method=None, + constraints=[c1, c2], bounds=[(-0.5, 1), (0, 8)]) + + np.testing.assert_allclose(res.fun, 0.5443310539518) + np.testing.assert_allclose(res.x, [0.33333333, 0.2962963]) + assert res.success def test_gh9640(self): np.random.seed(10) From 8f03bde5b803dc9d25dba01393b8de00bbccbc23 Mon Sep 17 00:00:00 2001 From: Matt Haberland Date: Sun, 24 Sep 2023 17:27:09 -0700 Subject: [PATCH 138/170] TST: minimize_ipopt: fix test_gh115_eps_option, improve test_gh11649 --- cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py | 8 +++++++- cyipopt/tests/unit/test_scipy_optional.py | 2 ++ 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 9e23ddab..11baaaae 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -1125,7 +1125,13 @@ def nci(x): ref = minimize(fun=obj, x0=x0, method='slsqp', bounds=bnds, constraints=nlcs) assert ref.success - assert res.fun <= ref.fun + assert res.fun <= ref.fun # Ipopt legitimately does better than slsqp here + + # If we give SLSQP a good guess, it agrees with Ipopt + ref2 = minimize(fun=obj, x0=res.x, method='slsqp', + bounds=bnds, constraints=nlcs) + assert ref2.success + assert_allclose(ref2.fun, res.fun) @pytest.mark.skipif("scipy" not in sys.modules, diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index 2880552b..22ddc133 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -577,6 +577,8 @@ def test_minimize_late_binding_bug(): np.testing.assert_allclose(res.fun, ref.fun) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") def test_gh115_eps_option(): # gh-115 requested that the `eps` argument be exposed as an option. Verify # that it is working as advertised (at least for the objective function). From 682bc391e5a048595cff7b928ccde0e2d7409466 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Wed, 25 Oct 2023 06:33:23 +0200 Subject: [PATCH 139/170] Covert tol to float before passing to ipopt. --- cyipopt/scipy_interface.py | 2 ++ cyipopt/tests/unit/test_scipy_optional.py | 16 ++++++++++++++++ 2 files changed, 18 insertions(+) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 069fa3d7..86372e73 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -668,6 +668,8 @@ def _minimize_ipopt_iv(fun, x0, args, kwargs, method, jac, hess, hessp, tol = np.asarray(tol)[()] if tol.ndim != 0 or not np.issubdtype(tol.dtype, np.number) or tol <= 0: raise ValueError('`tol` must be a positive scalar.') + else: # tol should be a float, not an array + tol = float(tol) options = dict() if options is None else options if not isinstance(options, dict): diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index a9b049ce..a9c286cf 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -30,6 +30,22 @@ def test_minimize_ipopt_import_error_if_no_scipy(): cyipopt.minimize_ipopt(None, None) +@pytest.mark.skipif("scipy" not in sys.modules, + reason="Test only valid if Scipy available.") +def test_tol_type_issue_235(): + # from: https://github.com/mechmotum/cyipopt/issues/235 + + def fun(x): + return np.sum(x ** 2) + + # tol should not raise and error + cyipopt.minimize_ipopt( + fun=fun, + x0=np.zeros(2), + tol=1e-9, + ) + + @pytest.mark.skipif("scipy" not in sys.modules, reason="Test only valid if Scipy available.") def test_minimize_ipopt_input_validation(): From 0b6e7494a1cafc19f0dd3b683ace7bad89e28b3c Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Wed, 25 Oct 2023 06:45:00 +0200 Subject: [PATCH 140/170] Spelling. --- cyipopt/tests/unit/test_scipy_optional.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index a9c286cf..5bd91544 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -38,7 +38,7 @@ def test_tol_type_issue_235(): def fun(x): return np.sum(x ** 2) - # tol should not raise and error + # tol should not raise an error cyipopt.minimize_ipopt( fun=fun, x0=np.zeros(2), From 0f3cfbd56b2a830a7001ad5a1bc00db544e4d47f Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 5 Nov 2023 11:24:41 +0100 Subject: [PATCH 141/170] Fully allow Cython 3. --- .github/workflows/docs.yml | 2 +- .github/workflows/tests.yml | 2 +- .github/workflows/windows.yml | 2 +- conda/cyipopt-dev.yml | 2 +- docs/source/install.rst | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 8f295d13..16077e7a 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -30,7 +30,7 @@ jobs: channels: conda-forge miniforge-variant: Mambaforge - name: Install basic dependencies - run: mamba install -y -v lapack "libblas=*=*netlib" "cython=0.29.*" "ipopt=${{ matrix.ipopt-version }}" numpy>=1.21.5 pkg-config>=0.29.2 setuptools>=44.1.1 --file docs/requirements.txt + run: mamba install -y -v lapack "libblas=*=*netlib" "cython>=0.29.28" "ipopt=${{ matrix.ipopt-version }}" numpy>=1.21.5 pkg-config>=0.29.2 setuptools>=44.1.1 --file docs/requirements.txt - name: Install CyIpopt run: | rm pyproject.toml diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 53bac79f..62a81003 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -35,7 +35,7 @@ jobs: miniforge-variant: Mambaforge - name: Install basic dependencies against generic blas/lapack run: | - mamba install -q -y lapack "libblas=*=*netlib" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "cython=0.29.*" + mamba install -q -y lapack "libblas=*=*netlib" "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "cython>=0.29.28" - run: echo "IPOPTWINDIR=USECONDAFORGEIPOPT" >> $GITHUB_ENV - name: Install CyIpopt run: | diff --git a/.github/workflows/windows.yml b/.github/workflows/windows.yml index d71baf5e..112a5bdf 100644 --- a/.github/workflows/windows.yml +++ b/.github/workflows/windows.yml @@ -18,7 +18,7 @@ jobs: - uses: actions/setup-python@v4 with: python-version: '3.10' - - run: python -m pip install "numpy>=1.21.5" "cython>=0.29.28,<3" "setuptools>44.1.1" + - run: python -m pip install "numpy>=1.21.5" "cython>=0.29.28" "setuptools>44.1.1" - run: Invoke-WebRequest -Uri "https://github.com/coin-or/Ipopt/releases/download/releases%2F3.13.3/Ipopt-3.13.3-win64-msvs2019-md.zip" -OutFile "Ipopt-3.13.3-win64-msvs2019-md.zip" - run: 7z x Ipopt-3.13.3-win64-msvs2019-md.zip - run: mv Ipopt-3.13.3-win64-msvs2019-md/* . diff --git a/conda/cyipopt-dev.yml b/conda/cyipopt-dev.yml index 241ea329..24e304b5 100644 --- a/conda/cyipopt-dev.yml +++ b/conda/cyipopt-dev.yml @@ -2,7 +2,7 @@ name: cyipopt-dev channels: - conda-forge dependencies: - - cython >=0.29.28,<3 + - cython >=0.29.28 - ipopt >=3.12 - libblas * *netlib - numpy >=1.21.5 diff --git a/docs/source/install.rst b/docs/source/install.rst index 1d81fb72..0ac30154 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -31,7 +31,7 @@ dependencies: * Ipopt >=3.12 [>= 3.13 on Windows] * Python 3.8+ * setuptools >=44.1.1 - * cython >=0.29.28,<3 + * cython >=0.29.28 * NumPy >=1.21.5 * SciPy >=1.8 [optional] From 4b9dab3d7f6ad99677b3792a9a2a3aab9884f49c Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 26 Nov 2023 08:50:58 +0100 Subject: [PATCH 142/170] Use closer guess for MacOSX failing test. This was failing on MacOSC in these versions: Python 3.8 + IPOPT 3.13 & 3.14 Python 3.9 + IPOPT 3.13 Python 3.10 + IPOPT 3.13 & 314 with this error: ________________ TestSLSQP.test_minimize_unbounded_approximated ________________ self = def test_minimize_unbounded_approximated(self): # Minimize, method=None: unbounded, approximated jacobian. jacs = [None, False] for jac in jacs: res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), jac=jac, method=None, options=self.opts) > assert_(res['success'], res['message']) E AssertionError: b'Algorithm stopped at a point that was converged, not to "desired" tolerances, but to "acceptable" tolerances (see the acceptable-... options).' cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py:158: AssertionError =========================== short test summary info ============================ FAILED cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py::TestSLSQP::test_minimize_unbounded_approximated - AssertionError: b'Algorithm stopped at a point that was converged, not to "desired" tolerances, but to "acceptable" tolerances (see the acceptable-... options).' ====== 1 failed, 90 passed, 12 skipped, 1 xfailed, 43 warnings in 11.88s ======= Error: Process completed with exit code 1. I changed the guess for this test to possibly give convergence. --- cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 1913befe..5763887b 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -170,7 +170,7 @@ def test_minimize_bounded_approximated(self): jacs = [None, False] for jac in jacs: with np.errstate(invalid='ignore'): - res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + res = minimize(self.fun, [2.0, 1.0], args=(-1.0, ), jac=jac, bounds=((2.5, None), (None, 0.5)), method=None, options=self.opts) From ac2ff3bd3d58e3f8a6fecabcdc46590b61bd9396 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 26 Nov 2023 09:03:43 +0100 Subject: [PATCH 143/170] Changed the incorrect one, unbounded was failing. --- cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 5763887b..308aa26d 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -152,7 +152,7 @@ def test_minimize_unbounded_approximated(self): # Minimize, method=None: unbounded, approximated jacobian. jacs = [None, False] for jac in jacs: - res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), + res = minimize(self.fun, [1.0, 1.0], args=(-1.0, ), jac=jac, method=None, options=self.opts) assert_(res['success'], res['message']) @@ -170,7 +170,7 @@ def test_minimize_bounded_approximated(self): jacs = [None, False] for jac in jacs: with np.errstate(invalid='ignore'): - res = minimize(self.fun, [2.0, 1.0], args=(-1.0, ), + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), jac=jac, bounds=((2.5, None), (None, 0.5)), method=None, options=self.opts) From a2d7dd5110c1f3609168289310ba49132e2abe76 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 26 Nov 2023 09:21:20 +0100 Subject: [PATCH 144/170] Allow acceptable tolerances to pass. --- cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py index 308aa26d..d9367d4e 100644 --- a/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py +++ b/cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py @@ -152,10 +152,19 @@ def test_minimize_unbounded_approximated(self): # Minimize, method=None: unbounded, approximated jacobian. jacs = [None, False] for jac in jacs: - res = minimize(self.fun, [1.0, 1.0], args=(-1.0, ), + res = minimize(self.fun, [-1.0, 1.0], args=(-1.0, ), jac=jac, method=None, options=self.opts) - assert_(res['success'], res['message']) + # NOTE : This test fails on some MacOSX builds with the error: + # AssertionError: b'Algorithm stopped at a point that was + # converged, not to "desired" tolerances, but to "acceptable" + # tolerances (see the acceptable-... options).' + if not res['success']: + assert_('"acceptable" tolerances' in + res['message'].decode("utf-8")) + else: + assert_(res['success'], res['message']) + assert_allclose(res.x, [2, 1]) def test_minimize_unbounded_given(self): From 82d5dd4cc214993083106305a710819a097d48cb Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Sun, 26 Nov 2023 09:40:07 +0100 Subject: [PATCH 145/170] Add build.os config for readthedocs. --- .readthedocs.yml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/.readthedocs.yml b/.readthedocs.yml index 3aa7de8a..06956de2 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -1,4 +1,8 @@ version: 2 +build: + os: "ubuntu-22.04" + tools: + python: "mambaforge-22.9" sphinx: configuration: docs/source/conf.py formats: all From 11dc66a4ffb930c6164f124851f527d6ded1e847 Mon Sep 17 00:00:00 2001 From: "Benjamin A. Beasley" Date: Sun, 26 Nov 2023 11:25:40 -0500 Subject: [PATCH 146/170] Include the examples in the source distribution --- MANIFEST.in | 1 + 1 file changed, 1 insertion(+) diff --git a/MANIFEST.in b/MANIFEST.in index 4dc02de4..35205a3b 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -7,6 +7,7 @@ recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py recursive-include tests *.py recursive-include docs Makefile *.bat *.rst *.py +recursive-include examples *.py exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py prune include* prune lib* From c277c8ed66294dc9ce41b131845e5972fbd57263 Mon Sep 17 00:00:00 2001 From: "Benjamin A. Beasley" Date: Sun, 26 Nov 2023 11:33:51 -0500 Subject: [PATCH 147/170] Include docs/requirements.txt in source distributions --- MANIFEST.in | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/MANIFEST.in b/MANIFEST.in index 35205a3b..1ad857c3 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -6,7 +6,7 @@ include README.rst recursive-include cyipopt *.py *.pyx *.pxd recursive-include ipopt *.py recursive-include tests *.py -recursive-include docs Makefile *.bat *.rst *.py +recursive-include docs Makefile *.bat *.rst *.py requirements.txt recursive-include examples *.py exclude cyipopt/tests/unit/test_scipy_ipopt_from_scipy.py prune include* From 068641012c2c395fb891e5d056caadd7743486e8 Mon Sep 17 00:00:00 2001 From: MarkusZimmerDLR <77002394+MarkusZimmerDLR@users.noreply.github.com> Date: Wed, 29 Nov 2023 13:56:14 +0100 Subject: [PATCH 148/170] Fix #239 --- cyipopt/scipy_interface.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 238a4e6e..dd1d3349 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -596,10 +596,8 @@ def minimize_ipopt(fun, # Rename some default scipy options replace_option(options, b'disp', b'print_level') replace_option(options, b'maxiter', b'max_iter') - if getattr(options, 'print_level', False) is True: - options[b'print_level'] = 1 - else: - options[b'print_level'] = 0 + options[b'print_level'] = int(options.get(b'print_level', 5)) + if b'tol' not in options: options[b'tol'] = tol or 1e-8 if b'mu_strategy' not in options: From 0a971ab620e6e75694e780707054d42d500415c3 Mon Sep 17 00:00:00 2001 From: MarkusZimmerDLR <77002394+MarkusZimmerDLR@users.noreply.github.com> Date: Wed, 29 Nov 2023 15:27:24 +0100 Subject: [PATCH 149/170] updated default of print_level from 5 to 0 --- cyipopt/scipy_interface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index dd1d3349..95c85514 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -596,7 +596,7 @@ def minimize_ipopt(fun, # Rename some default scipy options replace_option(options, b'disp', b'print_level') replace_option(options, b'maxiter', b'max_iter') - options[b'print_level'] = int(options.get(b'print_level', 5)) + options[b'print_level'] = int(options.get(b'print_level', 0)) if b'tol' not in options: options[b'tol'] = tol or 1e-8 From c71b7827c79ae322b4058c22d516bb15e89677a4 Mon Sep 17 00:00:00 2001 From: Thomas Lynn <32374143+lynntf@users.noreply.github.com> Date: Thu, 21 Mar 2024 20:21:27 +0100 Subject: [PATCH 150/170] spelling --- cyipopt/cython/ipopt_wrapper.pyx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index d1a3e6da..305b636e 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -365,7 +365,7 @@ cdef class Problem: # Verify that the constraints and jacobian callbacks are defined # if m > 0 and (self.__constraints is None or self.__jacobian is None): - msg = ("Both the \"constrains\" and \"jacobian\" callbacks must " + msg = ("Both the \"constraints\" and \"jacobian\" callbacks must " "be defined.") raise ValueError(msg) From 52039ee51bf62ac91fd29e2cc24520f2129cde81 Mon Sep 17 00:00:00 2001 From: Thomas Lynn <32374143+lynntf@users.noreply.github.com> Date: Mon, 1 Apr 2024 16:12:24 +0200 Subject: [PATCH 151/170] Add clarity to jacobian/hessianstructure methods Original tutorial is not entirely clear on what the jacobian/hessian jacobian/hessianstructure methods should return when providing them as sparse matrices. --- docs/source/tutorial.rst | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst index c0a06729..fe0a8300 100644 --- a/docs/source/tutorial.rst +++ b/docs/source/tutorial.rst @@ -253,15 +253,18 @@ methods should return the non-zero values of the respective matrices as flattened arrays. The hessian should return a flattened lower triangular matrix. -The Jacobian and Hessian can be dense or sparse. If sparse, you must also -define: +The Jacobian and Hessian can be dense or sparse. If sparse, +:func:`cyipopt.Problem.jacobian` and :func:`cyipopt.Problem.hessian` methods +should return only the non-zero values of the respective matrices and you must +also define: - :func:`cyipopt.Problem.jacobianstructure` - :func:`cyipopt.Problem.hessianstructure` -which should return a tuple of indices that indicate the location of the -non-zero values of the Jacobian and Hessian matrices, respectively. If not -defined then these matrices are assumed to be dense. +which should return a tuple of indices (row indices, column indices) that +indicate the location of the non-zero values of the Jacobian and Hessian +matrices, respectively. If not defined then these matrices are assumed to be +dense. The :func:`cyipopt.Problem.intermediate` method is called every Ipopt iteration algorithm and can be used to perform any needed computation at each iteration. From d7bbc90ed995baddeeb5d66f49bcdd564b71b526 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 16:39:46 +0200 Subject: [PATCH 152/170] Added Thomas Lynn to AUTHORS. --- AUTHORS | 1 + 1 file changed, 1 insertion(+) diff --git a/AUTHORS b/AUTHORS index d2c2a9d8..3cfdb281 100644 --- a/AUTHORS +++ b/AUTHORS @@ -20,3 +20,4 @@ Matt Haberland Benjamin A. Beasley Polina Lakrisenko Christoph Hansknecht +Thomas Lynn From 26a2279c3acdee779dced530f6ebc70e83190395 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 16:52:30 +0200 Subject: [PATCH 153/170] Added Markus Zimmer as an author. --- AUTHORS | 1 + 1 file changed, 1 insertion(+) diff --git a/AUTHORS b/AUTHORS index 3cfdb281..528683c5 100644 --- a/AUTHORS +++ b/AUTHORS @@ -20,4 +20,5 @@ Matt Haberland Benjamin A. Beasley Polina Lakrisenko Christoph Hansknecht +Markus Zimmer Thomas Lynn From 8b2f7effc007d89699abf250ecc15c6dcd9e6e47 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 16:55:56 +0200 Subject: [PATCH 154/170] Updated changelog for 1.4.0. --- CHANGELOG.rst | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 924fd056..76a911da 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,8 +36,22 @@ Include sections: Version History --------------- -[1.4.0.dev0] - XXXX-XX-XX -~~~~~~~~~~~~~~~~~~~~~~~~~ +[1.4.0] - 2024-04-01 +~~~~~~~~~~~~~~~~~~~~ + +Added ++++++ + +- Support for building with Cython 3. #227, #240 +- Exposed the ``eps`` kwarg in the SciPy interface. #228 +- Added the examples to the source tarball. #242 +- Documentation improvements on specifics of Jacobian and Hessian inputs. #247 + +Fixed ++++++ + +- Ensure ``tol`` is always a float in the SciPy interface. #236 +- ``print_level`` allows integers other than 0 or 1. #244 [1.3.0] - 2023-09-23 ~~~~~~~~~~~~~~~~~~~~ From 1445aeba7a308b41b9a8d6446f7ce66eeac90aa4 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 16:56:09 +0200 Subject: [PATCH 155/170] Updated copyright dates. --- cyipopt/__init__.py | 2 +- cyipopt/exceptions.py | 2 +- cyipopt/scipy_interface.py | 2 +- cyipopt/version.py | 2 +- docs/source/conf.py | 2 +- docs/source/index.rst | 2 +- examples/exception_handling.py | 2 +- examples/hs071.py | 2 +- examples/lasso.py | 2 +- setup.py | 2 +- 10 files changed, 10 insertions(+), 10 deletions(-) diff --git a/cyipopt/__init__.py b/cyipopt/__init__.py index 015dbde3..04f5b565 100644 --- a/cyipopt/__init__.py +++ b/cyipopt/__init__.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/cyipopt/exceptions.py b/cyipopt/exceptions.py index b75f36cd..8c1f9b4b 100644 --- a/cyipopt/exceptions.py +++ b/cyipopt/exceptions.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/cyipopt/scipy_interface.py b/cyipopt/scipy_interface.py index 95c85514..93903282 100644 --- a/cyipopt/scipy_interface.py +++ b/cyipopt/scipy_interface.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/cyipopt/version.py b/cyipopt/version.py index 3339e4b6..9c6bb095 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/docs/source/conf.py b/docs/source/conf.py index 0708bc1c..144dd781 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -53,7 +53,7 @@ # General information about the project. project = u'cyipopt' -copyright = u'2023, cyipopt developers' +copyright = u'2024, cyipopt developers' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the diff --git a/docs/source/index.rst b/docs/source/index.rst index 4d8004ce..98c146b3 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -53,5 +53,5 @@ Copyright | Copyright (C) 2012-2015 Amit Aides | Copyright (C) 2015-2017 Matthias Kümmerer -| Copyright (C) 2017-2023 cyipopt developers +| Copyright (C) 2017-2024 cyipopt developers | License: EPL 2.0 diff --git a/examples/exception_handling.py b/examples/exception_handling.py index b0416b0c..e1393e4a 100644 --- a/examples/exception_handling.py +++ b/examples/exception_handling.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/examples/hs071.py b/examples/hs071.py index d2661eb3..0e17f69f 100644 --- a/examples/hs071.py +++ b/examples/hs071.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ diff --git a/examples/lasso.py b/examples/lasso.py index 107073f8..3f8b62fe 100644 --- a/examples/lasso.py +++ b/examples/lasso.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 diff --git a/setup.py b/setup.py index eb6e1f48..0fbe50c1 100644 --- a/setup.py +++ b/setup.py @@ -4,7 +4,7 @@ Copyright (C) 2012-2015 Amit Aides Copyright (C) 2015-2017 Matthias Kümmerer -Copyright (C) 2017-2023 cyipopt developers +Copyright (C) 2017-2024 cyipopt developers License: EPL 2.0 """ From b9549f7179d03dc0c30ae363e48ceb04c463417d Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 17:01:53 +0200 Subject: [PATCH 156/170] Support Python 3.12. --- .github/workflows/docs.yml | 2 +- .github/workflows/tests.yml | 2 +- setup.py | 1 + 3 files changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 16077e7a..5be579a6 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -14,7 +14,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ['3.11'] + python-version: ['3.12'] ipopt-version: ['3.14'] defaults: run: diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 62a81003..4a9d5190 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -15,7 +15,7 @@ jobs: fail-fast: false matrix: os: [ubuntu-latest, macos-latest, windows-latest] - python-version: ['3.8', '3.9', '3.10', '3.11'] + python-version: ['3.8', '3.9', '3.10', '3.11', '3.12'] ipopt-version: ['3.12', '3.13', '3.14'] exclude: - os: windows-latest diff --git a/setup.py b/setup.py index 0fbe50c1..c6ef4f10 100644 --- a/setup.py +++ b/setup.py @@ -61,6 +61,7 @@ "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", ] From 773e7558309a6cf0974f9b1536c246b5468b870b Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 17:02:56 +0200 Subject: [PATCH 157/170] Added support for Python 3.12 to CHANGELOG. --- CHANGELOG.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 76a911da..6f912c61 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -46,6 +46,7 @@ Added - Exposed the ``eps`` kwarg in the SciPy interface. #228 - Added the examples to the source tarball. #242 - Documentation improvements on specifics of Jacobian and Hessian inputs. #247 +- Support for Python 3.12. Fixed +++++ From 67b0e1af50f495c7ceb8b49f639c35f04ffe94bd Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 17:15:14 +0200 Subject: [PATCH 158/170] Bump to version 1.4.0. --- cyipopt/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/version.py b/cyipopt/version.py index 9c6bb095..dc7d7193 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.4.0.dev0' +__version__ = '1.4.0' From 08f088ca558a5bbbf11b3ee3c33310eaab592b9d Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 17:20:51 +0200 Subject: [PATCH 159/170] Bump version to 1.5.0.dev0. --- cyipopt/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cyipopt/version.py b/cyipopt/version.py index dc7d7193..792e99a2 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.4.0' +__version__ = '1.5.0.dev0' From 0af8d02fb1fb87fb3eddaf1ccbdbfcb6b7f9f07e Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Mon, 1 Apr 2024 17:21:36 +0200 Subject: [PATCH 160/170] Adde changelog section for 1.5.0. --- CHANGELOG.rst | 3 +++ 1 file changed, 3 insertions(+) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 6f912c61..ba196736 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,6 +36,9 @@ Include sections: Version History --------------- +[1.5.0.dev0] - XXXX-XX-XX +~~~~~~~~~~~~~~~~~~~~~~~~~ + [1.4.0] - 2024-04-01 ~~~~~~~~~~~~~~~~~~~~ From de2f274e4dc21c26008403d2b165d4b90e1f4fd2 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Tue, 2 Apr 2024 18:55:32 +0200 Subject: [PATCH 161/170] Fixed #249, ensure intermediate_cb returns its value if no exception. --- cyipopt/cython/ipopt_wrapper.pyx | 2 +- cyipopt/tests/unit/test_ipopt_funcs.py | 87 ++++++++++++++++++++++++++ 2 files changed, 88 insertions(+), 1 deletion(-) diff --git a/cyipopt/cython/ipopt_wrapper.pyx b/cyipopt/cython/ipopt_wrapper.pyx index 305b636e..1497ed0a 100644 --- a/cyipopt/cython/ipopt_wrapper.pyx +++ b/cyipopt/cython/ipopt_wrapper.pyx @@ -1278,7 +1278,7 @@ cdef Bool intermediate_cb(Index alg_mod, self.__exception = sys.exc_info() return True - return True + return ret_val class problem(Problem): diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 789fca9d..25fa7f3a 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -391,3 +391,90 @@ def intermediate( np.testing.assert_allclose(pr_violations[-1], np.zeros(m), atol=1e-8) np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) + + +def test_intermediate_cb(): + + class MyProblem(): + def __init__(self): + pass + + def objective(self, x): + return x[0] * x[3] * np.sum(x[0:3]) + x[2] + + def gradient(self, x): + return np.array([ + x[0] * x[3] + x[3] * np.sum(x[0:3]), + x[0] * x[3], + x[0] * x[3] + 1.0, + x[0] * np.sum(x[0:3]) + ]) + + def constraints(self, x): + return np.array((np.prod(x), np.dot(x, x))) + + def jacobian(self, x): + return np.concatenate((np.prod(x) / x, 2*x)) + + def hessianstructure(self): + + return np.nonzero(np.tril(np.ones((4, 4)))) + + def hessian(self, x, lagrange, obj_factor): + H = obj_factor*np.array(( + (2*x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (x[3], 0, 0, 0), + (2*x[0]+x[1]+x[2], x[0], x[0], 0))) + + H += lagrange[0]*np.array(( + (0, 0, 0, 0), + (x[2]*x[3], 0, 0, 0), + (x[1]*x[3], x[0]*x[3], 0, 0), + (x[1]*x[2], x[0]*x[2], x[0]*x[1], 0))) + + H += lagrange[1]*2*np.eye(4) + + row, col = self.hessianstructure() + + return H[row, col] + + def intermediate( + self, + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + return False + + x0 = [1.0, 5.0, 5.0, 1.0] + + lb = [1.0, 1.0, 1.0, 1.0] + ub = [5.0, 5.0, 5.0, 5.0] + + cl = [25.0, 40.0] + cu = [2.0e19, 40.0] + + nlp = cyipopt.Problem( + n=len(x0), + m=len(cl), + problem_obj=MyProblem(), + lb=lb, + ub=ub, + cl=cl, + cu=cu, + ) + + x, info = nlp.solve(x0) + msg = (b'The user call-back function intermediate_callback (see Section ' + b'3.3.4 in the documentation) returned false, i.e., the user code ' + b'requested a premature termination of the optimization.') + assert info['status_msg'] == msg From 1f3a043e1aae9c4fb29e1ccab76f7365543e23fe Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Tue, 2 Apr 2024 19:05:44 +0200 Subject: [PATCH 162/170] Use test fixture. --- cyipopt/tests/unit/test_ipopt_funcs.py | 109 ++++++++----------------- 1 file changed, 35 insertions(+), 74 deletions(-) diff --git a/cyipopt/tests/unit/test_ipopt_funcs.py b/cyipopt/tests/unit/test_ipopt_funcs.py index 25fa7f3a..c0f91b02 100644 --- a/cyipopt/tests/unit/test_ipopt_funcs.py +++ b/cyipopt/tests/unit/test_ipopt_funcs.py @@ -393,88 +393,49 @@ def intermediate( np.testing.assert_allclose(du_violations[-1], np.zeros(n), atol=1e-8) -def test_intermediate_cb(): - - class MyProblem(): - def __init__(self): - pass - - def objective(self, x): - return x[0] * x[3] * np.sum(x[0:3]) + x[2] - - def gradient(self, x): - return np.array([ - x[0] * x[3] + x[3] * np.sum(x[0:3]), - x[0] * x[3], - x[0] * x[3] + 1.0, - x[0] * np.sum(x[0:3]) - ]) - - def constraints(self, x): - return np.array((np.prod(x), np.dot(x, x))) - - def jacobian(self, x): - return np.concatenate((np.prod(x) / x, 2*x)) - - def hessianstructure(self): - - return np.nonzero(np.tril(np.ones((4, 4)))) - - def hessian(self, x, lagrange, obj_factor): - H = obj_factor*np.array(( - (2*x[3], 0, 0, 0), - (x[3], 0, 0, 0), - (x[3], 0, 0, 0), - (2*x[0]+x[1]+x[2], x[0], x[0], 0))) - - H += lagrange[0]*np.array(( - (0, 0, 0, 0), - (x[2]*x[3], 0, 0, 0), - (x[1]*x[3], x[0]*x[3], 0, 0), - (x[1]*x[2], x[0]*x[2], x[0]*x[1], 0))) - - H += lagrange[1]*2*np.eye(4) - - row, col = self.hessianstructure() - - return H[row, col] - - def intermediate( - self, - alg_mod, - iter_count, - obj_value, - inf_pr, - inf_du, - mu, - d_norm, - regularization_size, - alpha_du, - alpha_pr, - ls_trials, - ): - return False +def test_intermediate_cb( + hs071_initial_guess_fixture, + hs071_definition_instance_fixture, + hs071_variable_lower_bounds_fixture, + hs071_variable_upper_bounds_fixture, + hs071_constraint_lower_bounds_fixture, + hs071_constraint_upper_bounds_fixture, +): + x0 = hs071_initial_guess_fixture + lb = hs071_variable_lower_bounds_fixture + ub = hs071_variable_upper_bounds_fixture + cl = hs071_constraint_lower_bounds_fixture + cu = hs071_constraint_upper_bounds_fixture + n = len(x0) + m = len(cl) - x0 = [1.0, 5.0, 5.0, 1.0] + problem_definition = hs071_definition_instance_fixture - lb = [1.0, 1.0, 1.0, 1.0] - ub = [5.0, 5.0, 5.0, 5.0] + def intermediate( + alg_mod, + iter_count, + obj_value, + inf_pr, + inf_du, + mu, + d_norm, + regularization_size, + alpha_du, + alpha_pr, + ls_trials, + ): + return False - cl = [25.0, 40.0] - cu = [2.0e19, 40.0] + problem_definition.intermediate = intermediate nlp = cyipopt.Problem( - n=len(x0), - m=len(cl), - problem_obj=MyProblem(), + n=n, + m=m, + problem_obj=problem_definition, lb=lb, ub=ub, cl=cl, cu=cu, ) - x, info = nlp.solve(x0) - msg = (b'The user call-back function intermediate_callback (see Section ' - b'3.3.4 in the documentation) returned false, i.e., the user code ' - b'requested a premature termination of the optimization.') - assert info['status_msg'] == msg + assert b'premature termination' in info['status_msg'] From 2c64adccfd059869dbc556a138013366abcb6fcb Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Tue, 2 Apr 2024 19:14:50 +0200 Subject: [PATCH 163/170] Bump version to 1.4.1. --- CHANGELOG.rst | 9 +++++++-- cyipopt/version.py | 2 +- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index ba196736..6aec5f10 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,8 +36,13 @@ Include sections: Version History --------------- -[1.5.0.dev0] - XXXX-XX-XX -~~~~~~~~~~~~~~~~~~~~~~~~~ +[1.4.1] - 2024-04-02 +~~~~~~~~~~~~~~~~~~~~ + +Fixed ++++++ + +- Addressed regression in return value of ``intermediate_cb``. #250 [1.4.0] - 2024-04-01 ~~~~~~~~~~~~~~~~~~~~ diff --git a/cyipopt/version.py b/cyipopt/version.py index 792e99a2..df29a9cd 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.5.0.dev0' +__version__ = '1.4.1' From d18edfa052c9dde446f97db31404a3d06b50a5e2 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Tue, 2 Apr 2024 19:18:22 +0200 Subject: [PATCH 164/170] Bumped version to 1.5.0.dev0. --- CHANGELOG.rst | 3 +++ cyipopt/version.py | 2 +- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 6aec5f10..c1fd24f9 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -36,6 +36,9 @@ Include sections: Version History --------------- +[1.5.0.dev0] - XXXX-XX-XX +~~~~~~~~~~~~~~~~~~~~~~~~~ + [1.4.1] - 2024-04-02 ~~~~~~~~~~~~~~~~~~~~ diff --git a/cyipopt/version.py b/cyipopt/version.py index df29a9cd..792e99a2 100644 --- a/cyipopt/version.py +++ b/cyipopt/version.py @@ -9,4 +9,4 @@ License: EPL 2.0 """ -__version__ = '1.4.1' +__version__ = '1.5.0.dev0' From 8dc8896f71ac38557b9271959e91c2ca5ac3fdc4 Mon Sep 17 00:00:00 2001 From: avdudchenko <33663878+avdudchenko@users.noreply.github.com> Date: Thu, 6 Jun 2024 10:27:40 -0700 Subject: [PATCH 165/170] added instrctions for windows --- docs/source/install.rst | 39 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 39 insertions(+) diff --git a/docs/source/install.rst b/docs/source/install.rst index 0ac30154..60d62a5e 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -336,6 +336,9 @@ descriptions:: Conda Forge binaries with HSL ----------------------------- +On Linux +----------------------------- + It is possible to use the HSL linear solvers with cyipopt installed via Conda Forge. To do so, first download the HSL source code tarball. The following explanation uses ``coinhsl-2014.01.10.tar.gz`` with conda installed on Ubuntu @@ -414,3 +417,39 @@ name must be specified because the default name ipopt looks for is ``libhsl.so``. Identify the shared library installed on your system and make sure the name provided for the ``hsllib`` option matches. For example, on macOS you may need ``problem.add_option('hsllib', 'libcoinhsl.dylib')``. + + +On Windows +----------------------------- +On windows it could be possible to use HSL solvers with Conda version of cyipopt, +first install cyipopt via standard call:: + + $ conda create -n hsl-test -c conda-forge cyipopt + $ conda activate hsl-test + +Download HSL linear solvers, e.g. ``ma27, ma57, ma86`` from its +official website . Download the ``windows`` binaries option, +in this example, we are using "CoinHSL Archive 2023.11.17 (windows binaries)" option. +This will download a zipped file that contains a folder ``bin``. Copy all the DLL files from +that folder into your conda env\Library\bin folder +(This folder should also contain the an ipopt dll file installed with cyipopt (in our case it was called ``ipopt-3.dll``):: + + \envs\\Library\bin + +Once the DLL files are placed you should be able to access the HSL solvers using solver options, in pyomo:: + + solver = pyo.SolverFactory("cyipopt") + solver.config.options["linear_solver"] = "ma27" + +If all works well, you should see the following when setting ``tee=True``:: + + ****************************************************************************** + This program contains Ipopt, a library for large-scale nonlinear optimization. + Ipopt is released as open source code under the Eclipse Public License (EPL). + For more information visit https://github.com/coin-or/Ipopt + ****************************************************************************** + + This is Ipopt version 3.14.16, running with linear solver ma27. + +This was tested on Windows 11 x64 with Ipopt version 3.14.16. + From 3feccefbe1315f22392f6d25e8f4e819f3538367 Mon Sep 17 00:00:00 2001 From: avdudchenko <33663878+avdudchenko@users.noreply.github.com> Date: Thu, 6 Jun 2024 12:16:34 -0700 Subject: [PATCH 166/170] Update install.rst --- docs/source/install.rst | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/docs/source/install.rst b/docs/source/install.rst index 60d62a5e..fe34b210 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -436,10 +436,9 @@ that folder into your conda env\Library\bin folder \envs\\Library\bin -Once the DLL files are placed you should be able to access the HSL solvers using solver options, in pyomo:: +Once the DLL files are placed you should be able to access the HSL solvers using solver options:: - solver = pyo.SolverFactory("cyipopt") - solver.config.options["linear_solver"] = "ma27" + problem.add_option('linear_solver', 'ma57') If all works well, you should see the following when setting ``tee=True``:: From 04ed7b9f12ba73119af270c12052fb04d3c911bd Mon Sep 17 00:00:00 2001 From: avdudchenko <33663878+avdudchenko@users.noreply.github.com> Date: Thu, 6 Jun 2024 23:54:56 -0700 Subject: [PATCH 167/170] fixing tests --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 4a9d5190..a6f5c1ba 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -55,6 +55,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0" "pytest>=6.2.5" "cython=0.29.*" + mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0,<1.13" "pytest>=6.2.5" "cython=0.29.*" mamba list pytest From 08ab1f04caf568ec0aed30fcb81ac205cc21a2b5 Mon Sep 17 00:00:00 2001 From: avdudchenko <33663878+avdudchenko@users.noreply.github.com> Date: Fri, 7 Jun 2024 00:39:54 -0700 Subject: [PATCH 168/170] test 2 --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index a6f5c1ba..16ef64b8 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -55,6 +55,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0,<1.13" "pytest>=6.2.5" "cython=0.29.*" + mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0,<1.13.0" "pytest>=6.2.5" "cython=0.29.*" mamba list pytest From 23c0d1fb419a2eb7fdf4ee7c11ec1492c6c8c14b Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 7 Jun 2024 12:59:06 +0200 Subject: [PATCH 169/170] Updated unit tests to call coo_array on 2d arrays not 1d arrays due to change in behavior in SciPy 1.13. --- cyipopt/tests/unit/test_scipy_optional.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/cyipopt/tests/unit/test_scipy_optional.py b/cyipopt/tests/unit/test_scipy_optional.py index fbd0669d..e318e32f 100644 --- a/cyipopt/tests/unit/test_scipy_optional.py +++ b/cyipopt/tests/unit/test_scipy_optional.py @@ -400,12 +400,12 @@ def grad(x): con_eq = { "type": "eq", "fun": lambda x: np.sum(x**2) - 40, - "jac": lambda x: coo_array(2 * x) + "jac": lambda x: coo_array([2 * x]) } con_ineq = { "type": "ineq", "fun": lambda x: np.prod(x) - 25, - "jac": lambda x: coo_array(np.prod(x) / x), + "jac": lambda x: coo_array([np.prod(x) / x]), } constrs = (con_eq, con_ineq) @@ -460,7 +460,7 @@ def grad(x): con_ineq_sparse = { "type": "ineq", "fun": lambda x: np.prod(x) - 25, - "jac": lambda x: coo_array(np.prod(x) / x), + "jac": lambda x: coo_array([np.prod(x) / x]), } constrs = (con_eq_dense, con_ineq_sparse) From 8a3a28d43dbfe9513be9284b45f208e45e2060f8 Mon Sep 17 00:00:00 2001 From: "Jason K. Moore" Date: Fri, 7 Jun 2024 13:03:47 +0200 Subject: [PATCH 170/170] Remove scipy upper cap in CI. --- .github/workflows/tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 16ef64b8..4a9d5190 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -55,6 +55,6 @@ jobs: # Ipopt needed different libfortrans. if: (matrix.ipopt-version != '3.12' && matrix.python-version != '3.11') || (matrix.ipopt-version != '3.12' && matrix.python-version != '3.10' && matrix.os != 'macos-latest') run: | - mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0,<1.13.0" "pytest>=6.2.5" "cython=0.29.*" + mamba install -q -y -c conda-forge "ipopt=${{ matrix.ipopt-version }}" "numpy>=1.21.5" "pkg-config>=0.29.2" "setuptools>=44.1.1" "scipy>1.8.0" "pytest>=6.2.5" "cython=0.29.*" mamba list pytest