unknowns
Stable function · Variable classification
Tier: stable · Kind: function · Topic: Variable classification
| Julia | TypeScript | Python | Rust | Go |
|---|---|---|---|---|
unknown_names, unknowns | unknowns | unknowns | not exported | not exported |
Note: spelling differs from the §2 rule: julia=unknown_names (expected unknowns); multiple spellings exported by: julia
Julia
Exported as unknown_names and unknowns. Both names refer to the same operation.
unknown_names
unknown_names(model::Model)
unknown_names(model::Model) -> Vector{String}
Deprecated alias of unknowns
(API_SPEC.md §8 item 6). Kept exported —
not merely for one minor — because the bare canonical name collides in Julia’s
flat namespace; both spellings are in the surface manifest.
unknowns
unknowns(model::Model)
unknowns(model::Model) -> Vector{String}
Every unknown declared by model, sorted lexicographically. The union of
ode_states
, observed_unknowns
and
algebraic_unknowns
, which partition it.
This is the canonical cross-binding name (API_SPEC.md §8 item 6): TypeScript
spells it unknowns and Python unknowns. unknown_names
is a
Julia-only alias, kept exported because the
bare name collides badly in Julia’s flat namespace — ModelingToolkit.unknowns
is the obvious clash, and a consumer doing using EarthSciAST, ModelingToolkit
needs a spelling that cannot be ambiguous.
Example (inspect)
model = doc.models["Decay"]
@assert sort(collect(keys(model.variables))) == ["N", "half_life", "lambda"]
# The two declared kinds...
@assert unknowns(model) == ["N", "half_life"]
@assert parameters(model) == ["lambda"]
# ...and what each unknown is, derived from the equations.
@assert ode_states(model) == ["N"] # has a D(N)/dt equation
@assert observed_unknowns(model) == ["half_life"] # defined explicitly
@assert algebraic_unknowns(model) == String[] # none solved implicitly
defs = observed_definitions(model)
@assert to_ascii(defs["half_life"]) == "log(2) / lambda"
TypeScript
function unknowns(model: Model): string[]
Names of every variable declared unknown, sorted.
Example (inspect)
const doc = loadPath(fixture('decay.esm'))
assert.deepEqual(Object.keys(doc.models ?? {}), ['Decay'])
const model = doc.models!.Decay
assert.ok(!('ref' in model)) // narrows away an unresolved `{ ref }` mount
// The document declares only `unknown` and `parameter`; everything else is derived.
assert.deepEqual(Object.keys(model.variables), ['N', 'lambda', 'half_life'])
assert.deepEqual(unknowns(model), ['N', 'half_life'])
assert.deepEqual(parameters(model), ['lambda'])
// N has a time derivative; half_life is defined by an explicit equation.
assert.deepEqual(odeStates(model), ['N'])
assert.deepEqual(observedUnknowns(model), ['half_life'])
assert.deepEqual(algebraicUnknowns(model), [])
assert.equal(isOdeState(model, 'N'), true)
assert.deepEqual(constantParameters(model), ['lambda'])
assert.equal(systemKind(model), 'ode')
// Each observed's defining expression:
const defs = observedDefinitions(model)
assert.equal(toAscii(defs.get('half_life')!), 'log(2) / lambda')
Python
unknowns(model: Any) -> list[str]
Every variable declared type: "unknown", sorted.
Example (inspect)
model = doc.models["Decay"]
for name, var in model.variables.items():
print(f"{name}: {var.type} [{var.units}]")
assert {n: v.type for n, v in model.variables.items()} == {
"N": "unknown",
"lambda": "parameter",
"half_life": "unknown",
}
# The file declares only "unknown" and "parameter"; the finer classes are derived.
assert earthsci_ast.ode_states(model) == ["N"]
assert earthsci_ast.observed_unknowns(model) == ["half_life"]
assert earthsci_ast.algebraic_unknowns(model) == []
assert earthsci_ast.constant_parameters(model) == ["lambda"]
assert earthsci_ast.unknowns(model) == ["N", "half_life"]
Rust
Rust does not export this function.
Go
Go does not export this function.