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33e4a86 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | """Ordered values read as a distribution over equally spaced bins."""
from __future__ import annotations
import math
from collections.abc import Callable
from dataclasses import dataclass
from functools import cached_property
from typing import Sequence
@dataclass(frozen=True)
class Grid:
low: float
high: float
size: int = 128
def __post_init__(self):
if self.size < 2 or not self.low < self.high:
raise ValueError("a grid needs two values or more, low to high")
@property
def step(self) -> float:
return (self.high - self.low) / (self.size - 1)
@cached_property
def values(self) -> tuple[float, ...]:
return tuple(self.low + i * self.step for i in range(self.size - 1)) + (self.high,)
def read(self, probabilities: Sequence[float], level: Callable[[float], float] | None = None) -> dict[str, float]:
"""The mean, median and central 80 percent interval, on this grid's values; `level`, the level a quantile is
read at (a calibration's, increasing)."""
total = math.fsum(probabilities)
values = self.values
out = {"mean": math.fsum(v * (p / total) for v, p in zip(values, probabilities))}
at = [(key, level(q) if level else q) for key, q in (("p10", 0.1), ("median", 0.5), ("p90", 0.9))]
mass = 0.0
for value, p in zip(values, probabilities):
mass += p / total
for key, quantile in at:
if key not in out and mass >= quantile:
out[key] = value
for key, _ in at: # a level near 1 the summed mass falls short of by rounding: the last value
out.setdefault(key, values[-1])
return out
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