Process completed with exit code 1.

1 error

Expression of type "None" cannot be assigned to parameter of type "DTypeLike"   Type "None" is not assignable to type "DTypeLike"     "None" is not assignable to "type[Any]"     "None" is not assignable to "dtype[Any]"     "None" is incompatible with protocol "_HasDType[dtype[Any]]"       "dtype" is not present     "None" is incompatible with protocol "_HasNumPyDType[dtype[Any]]"       "__numpy_dtype__" is not present     "None" is not assignable to "tuple[_DTypeLikeNested, _DTypeLikeNested]" ... (reportArgumentType)

Process completed with exit code 1.

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl9-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl3-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

Process completed with exit code 1.

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl9-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl3-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

Process completed with exit code 1.

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl9-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

test_sumpy_fmm[<PyOpenCLArrayContext for <pyopencl.Device 'cpu-haswell-AMD EPYC 7763 64-Core Processor' on 'Portable Computing Language'>>-knl3-LinearPDEConformingVolumeTaylorLocalExpansion-LinearPDEConformingVolumeTaylorMultipoleExpansion-False-True-True-pyvkfft] AssertionError

Argument type is partially unknown   Argument corresponds to parameter "a" in function "cross"   Argument type is "ndarray[tuple[Any, ...], dtype[Unknown]]" (reportUnknownArgumentType)

Type of "_points_shaped" is partially unknown   Type of "_points_shaped" is "ndarray[tuple[Any, ...], dtype[Any | Unknown]]" (reportUnknownMemberType)

Type of "_points_shaped" is partially unknown   Type of "_points_shaped" is "ndarray[tuple[Any, ...], dtype[Any | Unknown]]" (reportUnknownMemberType)

Type of "diag" is partially unknown   Type of "diag" is "Overload[(v: ndarray[tuple[Unknown] | tuple[Unknown, Unknown], dtype[_ScalarT@diag]] | Sequence[Sequence[_ScalarT@diag]], k: int = 0) -> ndarray[tuple[Any, ...], dtype[_ScalarT@diag]], (v: ndarray[tuple[int, int], dtype[_ScalarT@diag]] | Sequence[Sequence[_ScalarT@diag]], k: int = 0) -> ndarray[tuple[int], dtype[_ScalarT@diag]], (v: ndarray[tuple[int], dtype[_ScalarT@diag]] | Sequence[_ScalarT@diag], k: int = 0) -> ndarray[tuple[int, int], dtype[_ScalarT@diag]], (v: Sequence[Sequence[complex | str | bytes | generic[Any]]], k: int = 0) -> ndarray[tuple[int], dtype[Any]], (v: Sequence[complex | str | bytes | generic[Any]], k: int = 0) -> ndarray[tuple[int, int], dtype[Any]], (v: _SupportsArray[dtype[_ScalarT@diag]] | _NestedSequence[_SupportsArray[dtype[_ScalarT@diag]]], k: int = 0) -> ndarray[tuple[Any, ...], dtype[_ScalarT@diag]], (v: _Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], k: int = 0) -> ndarray[tuple[Any, ...], dtype[Any]]]" (reportUnknownMemberType)

Type of "_points_shaped" is partially unknown   Type of "_points_shaped" is "ndarray[tuple[Any, ...], dtype[Any | Unknown]]" (reportUnknownMemberType)

Type of "_points_shaped" is partially unknown   Type of "_points_shaped" is "ndarray[tuple[Any, ...], dtype[Any | Unknown]]" (reportUnknownMemberType)

Argument type is partially unknown   Argument corresponds to parameter "object" in function "array"   Argument type is "tuple[ndarray[tuple[Any, ...], dtype[Any | Unknown]], ...]" (reportUnknownArgumentType)

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Using the base PyOpenCLArrayContext.transform_loopy_program to transform a translation unit. This is largely a no-op and unlikely to result in fast generated code.Instead, subclass PyOpenCLArrayContext and implement the specific transform logic required to transform the program for your package or application. Check higher-level packages (e.g. meshmode), which may already have subclasses you may want to build on.

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Aff.is_equal with implicit conversion of self to PwAff is deprecated and will stop working in 2026. Explicitly convert to PwAff, using .to_pw_aff().

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.

'bcast_numpy_array=True' is deprecated and will be unsupported from 2025.

Broadcasting array context array types across <class 'meshmode.dof_array.DOFArray'> has been implicitly enabled. As of 2026, this will no longer work. Use arraycontext.Bcast* object wrappers for roughly equivalent functionality. See the discussion in https://github.com/inducer/arraycontext/pull/190. To opt out now (and avoid this warning), pass _bcast_actx_array_type=False.