ump_spec.rules.ladder

module ump-spec

Fallback ladder (spec §8) and the tier x operation matrix.

Classes

LadderDecision

class

class LadderDecision

Fields

Name	Type	Default
`step`	`str`
`index`	`int`
`warned`	`bool`
`reason`	`str`
`skipped`	`list[str]`	`field(default_factory=list)`
`notes`	`list[Note]`	`field(default_factory=list)`

Methods and properties (1)

init constructor

LadderDecision(
    self,
    step: str,
    index: int,
    warned: bool,
    reason: str,
    skipped: list[str] = list(),
    notes: list[Note] = list(),
) -> None

Source: packages/ump-spec/src/ump_spec/rules/ladder.py, line 39

Functions

tier_supports

function

def tier_supports(tier: str, op: str) -> str

Source: packages/ump-spec/src/ump_spec/rules/ladder.py, line 35

ladder_index

function

def ladder_index(step: str) -> int

Source: packages/ump-spec/src/ump_spec/rules/ladder.py, line 49

choose_ladder_step

function

def choose_ladder_step(
    available: Iterable[str],
    *,
    excluded: Iterable[str] = (),
    benchmarks_available: bool = True,
) -> LadderDecision

Pick the highest rung available. available holds ladder steps or tiers (A/B/C/D/X). excluded removes rungs (e.g. a model that failed the acceptance bar, G-ACC-01).

Source: packages/ump-spec/src/ump_spec/rules/ladder.py, line 53

Constants

Name	Type	Value	Description
`LADDER`	`tuple[str, ...]`	`('full_model', 'curve_params', 'spend_table', 'summary', 'benchmarks', 'not_a...`	1 full model, 2 curve params, 3 spend table, 4 summary (warned), 5 benchmarks (warned), 6 not available.
`WARNED_STEPS`	`frozenset[str]`	`frozenset({'summary', 'benchmarks'})`
`TIER_TO_STEP`	`dict[str, str]`	`{'A': 'full_model', 'X': 'full_model', 'B': 'curve_params', 'C': 'spend_table...`
`TIER_OPS`	`dict[str, dict[str, str]]`	`{'score': {'A': 'yes', 'B': 'yes', 'C': 'inside_grid_else_extrapolated_widene...`	Spec §8 tier x operation matrix.