Merge branch 'master' into feature/problemconfig_rng

.gitignore

@@ -14,4 +14,8 @@ env
 docs/_build
 .coverage
 Makefile
-make.bat
+make.bat
+
+build/
+dist/
+*.egg-info

entmoot/__version__.py

@@ -1,4 +1,4 @@
-__version__ = "1.0.4"
+__version__ = "2.0.1"
 __author__ = "Alexander Thebelt"
 __author_email__ = "alexander.thebelt18@imperial.ac.uk"
 __license__ = "BSD 3-Clause License"

entmoot/optimizers/gurobi_opt.py

@@ -68,7 +68,7 @@ def solve(
         model_core: gur.Model = None,
         weights: tuple = None,
         use_env: bool = False,
-    ) -> namedtuple:
+    ) -> OptResult:
         """
         Solves the Gurobi optimization model
         """

setup.py

@@ -17,14 +17,14 @@
     url="https://github.com/cog-imperial/entmoot",
     packages=find_packages(exclude=["tests", "docs"]),
     install_requires=[
-        "numpy",
-        "lightgbm==4.0.0",
+        "numpy<=2.0.0",
+        "lightgbm>=4.0.0",
         "gurobipy",
         "pyomo"
     ],
     setup_requires=[
-        "numpy",
-        "lightgbm==4.0.0",
+        "numpy<=2.0.0",
+        "lightgbm>=4.0.0",
         "gurobipy",
         "pyomo"
     ],

tests/test_curr.py

@@ -10,6 +10,7 @@
 import numpy as np
 import pytest
 import random
+import pyomo.environ # noqa: F401
 
 @pytest.mark.pipeline_test
 def test_core_model_copy():
@@ -32,7 +33,7 @@ def test_core_model_copy():
     assert len(core_model_pyomo._all_feat) == len(core_model_pyomo_copy._all_feat)
 
 
-@pytest.mark.pipeline_test
+# @pytest.mark.pipeline_test
 def test_multiobj_constraints():
     # define problem
     problem_config = ProblemConfig(rnd_seed=73)
@@ -98,7 +99,7 @@ def test_multiobj_constraints():
     assert round(x_opt, 5) == round(y_opt, 5) and round(y_opt, 5) == round(z_opt, 5)
 
 
-@pytest.mark.pipeline_test
+# @pytest.mark.pipeline_test
 def test_simple_test():
     def my_func(x: float) -> float:
         return x**2 + 1 + random.uniform(-0.2, 0.2)
@@ -172,7 +173,7 @@ def test_compare_pyomo_gurobipy_multiobj():
             assert math.isclose(res_gur.opt_val, res_pyo.opt_val, abs_tol=0.01)
 
 
-@pytest.mark.pipeline_test
+# @pytest.mark.pipeline_test
 def test_compare_pyomo_gurobipy_singleobj():
     """
     Ensures for a single objective example with l1  and l2 uncertainty metric and mixed feature types that optimization