Dev (#28)

.github/workflows/tests_slow.yml

@@ -8,6 +8,8 @@ on:
     branches: [ "main" ]
   pull_request:
     branches: [ "main", "dev" ]
+  schedule:
+    - cron: "21 3 * * 1"
 
 jobs:
   test:

README.md

@@ -37,13 +37,13 @@ The library provides:
 
 First, create a conda environment (skip if you already have one):
 ```
-conda create --name opt python=3.9
+conda create --name opt python=3.11
 conda activate opt
 ```
 
 Then install the package:
 ```
-conda install numpy
+conda install "numpy<2.0"
 pip install sb-arch-opt
 ```
 

docs/index.md

@@ -31,13 +31,13 @@ The library provides:
 
 First, create a conda environment (skip if you already have one):
 ```
-conda create --name opt python=3.9
+conda create --name opt python=3.11
 conda activate opt
 ```
 
 Then install the package:
 ```
-conda install numpy
+conda install "numpy<2.0"
 pip install sb-arch-opt
 ```
 

sb_arch_opt/__init__.py

@@ -1 +1 @@
-__version__ = '1.5.3'
+__version__ = '1.5.4'

sb_arch_opt/algo/arch_sbo/models.py

@@ -43,9 +43,14 @@
     from smt.surrogate_models.krg import KRG, KrgBased
     from smt.surrogate_models.kpls import KPLS
     from smt.surrogate_models.krg_based import MixIntKernelType, MixHrcKernelType
+    from smt.surrogate_models.rbf import RBF
 
-    from smt.utils.design_space import BaseDesignSpace
-    import smt.utils.design_space as ds
+    try:
+        from smt.utils.design_space import BaseDesignSpace
+        import smt.utils.design_space as ds
+    except ModuleNotFoundError:  # Module moved from SMT 2.8
+        from smt.design_space import BaseDesignSpace
+        import smt.design_space as ds
 
     from smt import __version__
 
@@ -59,8 +64,11 @@ class BaseDesignSpace:
     class SurrogateModel:
         pass
 
+    class RBF:
+        pass
+
 __all__ = ['check_dependencies', 'HAS_ARCH_SBO', 'HAS_SMT', 'ModelFactory', 'MixedDiscreteNormalization', 'SBArchOptDesignSpace',
-           'MultiSurrogateModel']
+           'MultiSurrogateModel', 'FixedRBF']
 
 
 def check_dependencies():
@@ -150,8 +158,7 @@ def get_md_normalization(self):
     @staticmethod
     def get_rbf_model():
         check_dependencies()
-        from smt.surrogate_models.rbf import RBF
-        return RBF(print_global=False, d0=1., poly_degree=-1, reg=1e-10)
+        return FixedRBF(print_global=False, d0=1., poly_degree=-1, reg=1e-10)
 
     @staticmethod
     def get_kriging_model(multi=True, kpls_n_comp: int = None, **kwargs):
@@ -425,3 +432,11 @@ def predict_variances(self, x: np.ndarray, is_acting=None) -> np.ndarray:
 
     def _predict_values(self, x: np.ndarray, is_acting=None) -> np.ndarray:
         raise RuntimeError
+
+
+class FixedRBF(RBF):
+    """RBF model that can be deep-copied or pickled before initialization"""
+
+    def __setstate__(self, state):
+        """Override to remove the call to _setup"""
+        self.__dict__.update(state)

sb_arch_opt/tests/algo/test_arch_sbo.py

@@ -313,7 +313,7 @@ def _get_xy_train(self, x: np.ndarray, y: np.ndarray) -> Tuple[np.ndarray, np.nd
 @check_dependency()
 def test_invalid_training_set(problem: ArchOptProblemBase):
     assert HAS_SMT
-    sbo = FailedXYRemovingSBO(RBF(print_global=False), FunctionEstimateInfill(), pop_size=100, termination=100,
+    sbo = FailedXYRemovingSBO(FixedRBF(print_global=False), FunctionEstimateInfill(), pop_size=100, termination=100,
                               repair=ArchOptRepair()).algorithm(infill_size=1, init_size=10)
     sbo.setup(problem)