pymixef.model module

Public model builders, dry-run compilation, and backend dispatch.

class pymixef.model.ExecutionPlan(model, matrices, model_ir, source_data, engine, method, settings, validation)[source]

Bases: object

Deterministic compiled model, data audit, and engine settings.

Parameters:
model: Model
matrices: DesignMatrices
model_ir: ModelIR
source_data: Any
engine: str
method: str
settings: Mapping[str, Any]
validation: ValidationReport
validate()[source]
Return type:

ValidationReport

explain()[source]
Return type:

str

to_backend_data()[source]
Return type:

dict[str, Any]

fit()[source]
Return type:

FitResult

class pymixef.model.Fixed(expression)[source]

Bases: object

Fixed-effects expression in the safe formula grammar.

Parameters:

expression (str)

expression: str
class pymixef.model.Model(response=None, fixed=None, random=(), family=<factory>, residual=None, formula=None, zero_inflation=None, dispersion=None, shape=None, priors=<factory>, metadata=<factory>)[source]

Bases: object

Backend-neutral scientific model.

Construct with a formula through from_formula(), or provide Response, Fixed, and Random declarations directly.

Parameters:

  • response (Response | str | None)

  • fixed (Fixed | str | None)

  • random (Sequence[Random])

  • family (Family)

  • residual (Any)

  • formula (str | None)

  • zero_inflation (str | None)

  • dispersion (str | None)

  • shape (str | None)

  • priors (Mapping[str, Any])

  • metadata (Mapping[str, Any])

response: Response | str | None
fixed: Fixed | str | None
random: Sequence[Random]
family: Family
residual: Any
formula: str | None
zero_inflation: str | None
dispersion: str | None
shape: str | None
priors: Mapping[str, Any]
metadata: Mapping[str, Any]
classmethod from_formula(formula, *, family=None, residual=None, zero_inflation=None, dispersion=None, shape=None, priors=None, metadata=None)[source]
Parameters:

  • formula (str)

  • family (Family | None)

  • residual (Any)

  • zero_inflation (str | None)

  • dispersion (str | None)

  • shape (str | None)

  • priors (Mapping[str, Any] | None)

  • metadata (Mapping[str, Any] | None)

Return type:

Model

formula_text()[source]
Return type:

str

property specification: FormulaSpec
to_ir(*, engine=None, method=None)[source]

Compile data-independent semantics into the shared versioned IR.

Parameters:

  • engine (str | None)

  • method (str | None)

Return type:

ModelIR

validate(*, engine=None, method=None)[source]
Parameters:

  • engine (str | None)

  • method (str | None)

Return type:

ValidationReport

explain(data=None, *, engine=None, method=None, missing='drop')[source]
Parameters:

  • data (Any | None)

  • engine (str | None)

  • method (str | None)

  • missing (str)

Return type:

str

compile(data, *, engine=None, method=None, missing='drop', **settings)[source]
Parameters:

  • data (Any)

  • engine (str | None)

  • method (str | None)

  • missing (str)

  • settings (Any)

Return type:

ExecutionPlan

fit(data, *, engine=None, method=None, missing='drop', **settings)[source]
Parameters:

  • data (Any)

  • engine (str | None)

  • method (str | None)

  • missing (str)

  • settings (Any)

Return type:

FitResult

class pymixef.model.Random(expression, group, covariance='unstructured', correlated=None)[source]

Bases: object

One structured random-effects declaration.

Parameters:

  • expression (str)

  • group (str)

  • covariance (str)

  • correlated (bool | None)

expression: str
group: str
covariance: str
correlated: bool | None
class pymixef.model.Response(name, unit=None)[source]

Bases: object

Explicit response declaration for the structured builder.

Parameters:

  • name (str)

  • unit (str | None)

name: str
unit: str | None
class pymixef.model.ValidationFinding(code, severity, message, component=None, suggested_engines=())[source]

Bases: object

One deterministic model or engine compatibility finding.

Parameters:

  • code (str)

  • severity (str)

  • message (str)

  • component (str | None)

  • suggested_engines (tuple[str, ...])

code: str
severity: str
message: str
component: str | None
suggested_engines: tuple[str, ...]
to_dict()[source]
Return type:

dict[str, Any]

class pymixef.model.ValidationReport(findings, engine, method, compatible_engines)[source]

Bases: object

Dry-run semantic and estimator compatibility result.

Parameters:

  • findings (tuple[ValidationFinding, ...])

  • engine (str)

  • method (str)

  • compatible_engines (tuple[str, ...])

findings: tuple[ValidationFinding, ...]
engine: str
method: str
compatible_engines: tuple[str, ...]
property valid: bool
raise_for_errors()[source]
Return type:

None

to_dict()[source]
Return type:

dict[str, Any]

pymixef.model.fit(formula, *, data, family=None, residual=None, method=None, engine=None, inference=None, zero_inflation=None, dispersion=None, shape=None, missing='drop', **settings)[source]

Fit a formula or prebuilt model through static compatibility dispatch.

Parameters:

  • formula (str | Model)

  • data (Any)

  • family (Family | None)

  • residual (Any)

  • method (str | None)

  • engine (str | None)

  • inference (str | None)

  • zero_inflation (str | None)

  • dispersion (str | None)

  • shape (str | None)

  • missing (str)

  • settings (Any)

Return type:

FitResult