Add discrete variable support#58
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Implement discrete variable handling across the full stack: - Discipline base class: add_discrete_input/add_discrete_output methods with VariableMetaData using kDiscreteInput/kDiscreteOutput types - Server: process_inputs demuxes VariableMessage oneof into continuous and discrete dicts; yields VariableMessage wrappers on output - Client: _assemble_input_messages wraps both Array and DiscreteVariable in VariableMessage; _recover_outputs handles discrete responses - OpenMDAO bindings: auto-discover discrete vars from server metadata, declare them via add_discrete_input/output, and forward through compute/apply_nonlinear/linearize calls Discrete values use google.protobuf.Value for language-interoperable serialization of scalars, lists, and nested structures. Updates proto submodule to feature/discrete_vars (DiscreteVariable message, VariableMessage wrapper, stream VariableMessage RPCs). Refs: #54
Wrap all raw data.Array messages in data.VariableMessage in test fixtures to match the new streaming protocol. Update OpenMDAO test assertions to include discrete_inputs parameters in expected calls.
Codecov Report✅ All modified and coverable lines are covered by tests. 📢 Thoughts on this report? Let us know! |
Add comprehensive test suite covering all new discrete variable code paths: value conversion helpers, discipline base class, server/client discrete message handling, explicit/implicit server discrete dispatch, client discrete assembly/recovery, and OpenMDAO bindings. Coverage restored to 99% (remaining misses are import guards and an unreachable defensive branch).
Add codecov.yml requiring 95% coverage on both project total and patch (new/changed lines). Add fail_under = 95 to .coveragerc for local enforcement via coverage report.
Add coverage exclusion pragmas to three unreachable code paths: - _value_to_python else fallback (all protobuf Value kinds handled) - openmdao/__init__.py ImportError guard (requires uninstalling OpenMDAO) - examples/__init__.py ImportError guard (same) Also fixes bare except to except ImportError in examples/__init__.py.
Add end-to-end integration tests using a ScaledParaboloid discipline that uses a discrete input (mode) to switch scaling behavior and a discrete output (label) to report the mode used. Tests cover: - Raw ExplicitClient compute with discrete inputs/outputs - Raw ExplicitClient compute_partials with discrete inputs - OpenMDAO RemoteExplicitComponent auto-discovery and forwarding of discrete variables through a real gRPC server
Add entries for coverage enforcement, pragma no cover annotations, and the bare except fix under the appropriate sections.
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Summary
add_discrete_input/add_discrete_outputto the discipline base class for declaring discrete variablesprocess_inputsdemuxes the newVariableMessagewrapper, routing continuous chunks to numpy arrays and discrete values to plain Python dicts_assemble_input_messagesand all_recover_*methods handle theVariableMessageoneofenvelopeRemoteExplicitComponent,RemoteImplicitComponent) auto-discover discrete variable metadata from the server and forwarddiscrete_inputs/discrete_outputsthroughcompute,apply_nonlinear,linearize, etc.feature/discrete_vars)google.protobuf.Value, supporting scalars, lists, and nested structuresTest plan
apply_linearsignature failure is unrelated)Closes #54
Depends on MDO-Standards/Philote-MDO#15