plum is only able to correctly dispatch on keyword arguments if they …

…have a default value. Make the number of modes and the tolerance optional in POD functions

rbnicsx/_backends/proper_orthogonal_decomposition.py

@@ -18,11 +18,14 @@
 from rbnicsx._cpp import cpp_library
 
 
+real_zero = petsc4py.PETSc.RealType(0.0)
+
+
 def proper_orthogonal_decomposition_functions(  # type: ignore[no-any-unimported]
     functions_list: FunctionsList[Function],
     compute_inner_product: typing.Callable[[Function], typing.Callable[[Function], petsc4py.PETSc.RealType]],
     scale: typing.Callable[[Function, petsc4py.PETSc.RealType], None],
-    N: int, tol: petsc4py.PETSc.RealType, normalize: bool = True
+    N: int = -1, tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], FunctionsList[Function], typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -39,9 +42,9 @@ def proper_orthogonal_decomposition_functions(  # type: ignore[no-any-unimported
     scale
         A callable with signature scale(function, factor) to scale any function by a given factor.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected snapshots.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -67,8 +70,8 @@ def proper_orthogonal_decomposition_functions_block(  # type: ignore[no-any-unim
     compute_inner_products: typing.Sequence[
         typing.Callable[[Function], typing.Callable[[Function], petsc4py.PETSc.RealType]]],
     scale: typing.Callable[[Function, petsc4py.PETSc.RealType], None],
-    N: typing.Union[int, typing.List[int]],
-    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]],
+    N: typing.Union[int, typing.List[int]] = -1,
+    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]] = real_zero,
     normalize: bool = True
 ) -> typing.Tuple[
     typing.List[np.typing.NDArray[petsc4py.PETSc.RealType]], typing.List[FunctionsList[Function]],
@@ -92,9 +95,11 @@ def proper_orthogonal_decomposition_functions_block(  # type: ignore[no-any-unim
     N
         Maximum number of modes to be computed. If an integer value is passed then the same maximum number is
         used for each block. To set a different maximum number of modes for each block pass a list of integers.
+        If not provided, it will be set to the number of collected snapshots.
     tol
         Tolerance on the retained energy. If a floating point value is passed then the same tolerance is
         used for each block. To set a different tolerance for each block pass a list of floating point numbers.
+        If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -132,7 +137,7 @@ def proper_orthogonal_decomposition_functions_block(  # type: ignore[no-any-unim
 
 
 def proper_orthogonal_decomposition_tensors(  # type: ignore[no-any-unimported]
-    tensors_list: TensorsList, N: int, tol: petsc4py.PETSc.RealType, normalize: bool = True
+    tensors_list: TensorsList, N: int = -1, tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], TensorsList, typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -144,9 +149,9 @@ def proper_orthogonal_decomposition_tensors(  # type: ignore[no-any-unimported]
     tensors_list
         Collected tensors.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected tensors.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -243,6 +248,10 @@ def _solve_eigenvalue_problem(  # type: ignore[no-any-unimported]
             3. Eigenvectors of the correlation matrix. Only the first few eigenvectors are returned, till
                either the maximum number N is reached or the tolerance on the retained energy is fulfilled.
     """
+    assert N > 0 or N == -1
+    if N == -1:
+        N = len(snapshots)
+
     correlation_matrix = create_online_matrix(len(snapshots), len(snapshots))
     for (j, snapshot_j) in enumerate(snapshots):
         compute_inner_product_partial_j = compute_inner_product(snapshot_j)

rbnicsx/backends/proper_orthogonal_decomposition.py

@@ -16,7 +16,8 @@
 from rbnicsx._backends.proper_orthogonal_decomposition import (
     proper_orthogonal_decomposition_functions as proper_orthogonal_decomposition_functions_super,
     proper_orthogonal_decomposition_functions_block as proper_orthogonal_decomposition_functions_block_super,
-    proper_orthogonal_decomposition_tensors as proper_orthogonal_decomposition_tensors_super)
+    proper_orthogonal_decomposition_tensors as proper_orthogonal_decomposition_tensors_super,
+    real_zero)
 from rbnicsx.backends.functions_list import FunctionsList
 from rbnicsx.backends.tensors_list import TensorsList
 
@@ -30,7 +31,7 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported]
     functions_list: FunctionsList,
     compute_inner_product: typing.Callable[
         [dolfinx.fem.Function], typing.Callable[[dolfinx.fem.Function], petsc4py.PETSc.RealType]],
-    N: int, tol: petsc4py.PETSc.RealType, normalize: bool = True
+    N: int = -1, tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], FunctionsList, typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -46,9 +47,9 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported]
         The resulting modes will be orthonormal w.r.t. this inner product.
         Use rbnicsx.backends.bilinear_form_action to generate the callable x from a UFL form.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected snapshots.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -68,7 +69,7 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported]
 
 @plum.overload
 def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa: F811
-    tensors_list: TensorsList, N: int, tol: petsc4py.PETSc.RealType, normalize: bool = True
+    tensors_list: TensorsList, N: int = -1, tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], TensorsList, typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -80,9 +81,9 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa:
     tensors_list
         Collected tensors.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected tensors.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -109,8 +110,8 @@ def proper_orthogonal_decomposition_block(  # type: ignore[no-any-unimported]
     functions_lists: typing.Sequence[FunctionsList],
     compute_inner_products: typing.Sequence[
         typing.Callable[[dolfinx.fem.Function], typing.Callable[[dolfinx.fem.Function], petsc4py.PETSc.RealType]]],
-    N: typing.Union[int, typing.List[int]],
-    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]],
+    N: typing.Union[int, typing.List[int]] = -1,
+    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]] = real_zero,
     normalize: bool = True
 ) -> typing.Tuple[
     typing.List[np.typing.NDArray[petsc4py.PETSc.RealType]], typing.List[FunctionsList],
@@ -133,9 +134,11 @@ def proper_orthogonal_decomposition_block(  # type: ignore[no-any-unimported]
     N
         Maximum number of modes to be computed. If an integer value is passed then the same maximum number is
         used for each block. To set a different maximum number of modes for each block pass a list of integers.
+        If not provided, it will be set to the number of collected snapshots.
     tol
         Tolerance on the retained energy. If a floating point value is passed then the same tolerance is
         used for each block. To set a different tolerance for each block pass a list of floating point numbers.
+        If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 

rbnicsx/online/proper_orthogonal_decomposition.py

@@ -15,7 +15,8 @@
 from rbnicsx._backends.proper_orthogonal_decomposition import (
     proper_orthogonal_decomposition_functions as proper_orthogonal_decomposition_functions_super,
     proper_orthogonal_decomposition_functions_block as proper_orthogonal_decomposition_functions_block_super,
-    proper_orthogonal_decomposition_tensors as proper_orthogonal_decomposition_tensors_super)
+    proper_orthogonal_decomposition_tensors as proper_orthogonal_decomposition_tensors_super,
+    real_zero)
 from rbnicsx.online.functions_list import FunctionsList
 from rbnicsx.online.projection import matrix_action
 from rbnicsx.online.tensors_list import TensorsList
@@ -27,8 +28,8 @@
 
 @plum.overload
 def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa: F811
-    functions_list: FunctionsList, inner_product: petsc4py.PETSc.Mat, N: int, tol: petsc4py.PETSc.RealType,
-    normalize: bool = True
+    functions_list: FunctionsList, inner_product: petsc4py.PETSc.Mat, N: int = -1,
+    tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], FunctionsList, typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -43,9 +44,9 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa:
         Online matrix which defines the inner product. The resulting modes will be orthonormal
         w.r.t. this inner product.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected snapshots.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize : bool, optional
         If true (default), the modes are scaled to unit norm.
 
@@ -67,7 +68,7 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa:
 
 @plum.overload
 def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa: F811
-    tensors_list: TensorsList, N: int, tol: petsc4py.PETSc.RealType, normalize: bool = True
+    tensors_list: TensorsList, N: int = -1, tol: petsc4py.PETSc.RealType = real_zero, normalize: bool = True
 ) -> typing.Tuple[
     np.typing.NDArray[petsc4py.PETSc.RealType], TensorsList, typing.List[petsc4py.PETSc.Vec]
 ]:
@@ -79,9 +80,9 @@ def proper_orthogonal_decomposition(  # type: ignore[no-any-unimported] # noqa:
     tensors_list
         Collected tensors.
     N
-        Maximum number of modes to be computed.
+        Maximum number of modes to be computed. If not provided, it will be set to the number of collected tensors.
     tol
-        Tolerance on the retained energy.
+        Tolerance on the retained energy. If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 
@@ -106,8 +107,8 @@ def proper_orthogonal_decomposition(*args, **kwargs):  # type: ignore[no-untyped
 
 def proper_orthogonal_decomposition_block(  # type: ignore[no-any-unimported]
     functions_lists: typing.Sequence[FunctionsList], inner_products: typing.List[petsc4py.PETSc.Mat],
-    N: typing.Union[int, typing.List[int]],
-    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]],
+    N: typing.Union[int, typing.List[int]] = -1,
+    tol: typing.Union[petsc4py.PETSc.RealType, typing.List[petsc4py.PETSc.RealType]] = real_zero,
     normalize: bool = True
 ) -> typing.Tuple[
     typing.List[np.typing.NDArray[petsc4py.PETSc.RealType]], typing.List[FunctionsList],
@@ -128,9 +129,11 @@ def proper_orthogonal_decomposition_block(  # type: ignore[no-any-unimported]
     N
         Maximum number of modes to be computed. If an integer value is passed then the same maximum number is
         used for each block. To set a different maximum number of modes for each block pass a list of integers.
+        If not provided, it will be set to the number of collected snapshots.
     tol
         Tolerance on the retained energy. If a floating point value is passed then the same tolerance is
         used for each block. To set a different tolerance for each block pass a list of floating point numbers.
+        If not provided, it will be set to zero.
     normalize
         If true (default), the modes are scaled to unit norm.
 

tests/unit/backends/test_backends_proper_orthogonal_decomposition.py

@@ -13,6 +13,7 @@
 import mpi4py.MPI
 import numpy as np
 import petsc4py.PETSc
+import plum
 import pytest
 import ufl
 
@@ -210,5 +211,6 @@ def test_backends_proper_orthogonal_decomposition_zero(  # type: ignore[no-any-u
 
 def test_backends_proper_orthogonal_decomposition_wrong_iterable() -> None:
     """Check rbnicsx.backends.proper_orthogonal_decomposition raises when providing a plain list."""
-    with pytest.raises(RuntimeError):
+    with pytest.raises(plum.NotFoundLookupError) as excinfo:
         rbnicsx.backends.proper_orthogonal_decomposition(list(), N=0, tol=0.0)  # type: ignore[call-overload]
+    assert str(excinfo.value) == "For function `proper_orthogonal_decomposition`, `([],)` could not be resolved."

tests/unit/online/test_online_proper_orthogonal_decomposition.py

@@ -10,6 +10,7 @@
 import _pytest.fixtures
 import numpy as np
 import petsc4py.PETSc
+import plum
 import pytest
 
 import rbnicsx.online
@@ -281,5 +282,6 @@ def test_online_proper_orthogonal_decomposition_zero(  # type: ignore[no-any-uni
 
 def test_online_proper_orthogonal_decomposition_wrong_iterable() -> None:
     """Check rbnicsx.online.proper_orthogonal_decomposition raises when providing a plain list."""
-    with pytest.raises(RuntimeError):
+    with pytest.raises(plum.NotFoundLookupError) as excinfo:
         rbnicsx.online.proper_orthogonal_decomposition(list(), N=0, tol=0.0)  # type: ignore[call-overload]
+    assert str(excinfo.value) == "For function `proper_orthogonal_decomposition`, `([],)` could not be resolved."