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"""Методика Петербург — лактирующие коровы (NORM_1_2_CALC)."""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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from app.modules.zootech.lab.calc.norms_derived import apply_derived_norms
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from app.modules.zootech.lab.calc.racion.interp import lerp
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from app.modules.zootech.lab.calc.racion.moscow import MoscowDairyParams
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from app.modules.zootech.lab.calc.racion.npitv_map import DAIRY_LACTIR_NPITV, NPITV_TO_INDICATOR
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from app.modules.zootech.lab.calc.racion.piter_prep import PiterPrepError, PiterPrepResult, prepare_piter_calc
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from app.modules.zootech.lab.calc.racion.tables import load_piter_lactir
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@dataclass(frozen=True)
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class PiterDairyParams(MoscowDairyParams):
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konc_oe_sv: float = 10.3
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def _konc_bracket(konc: float, konc_values: list[float]) -> tuple[float, float]:
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sorted_k = sorted(set(konc_values))
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positive = [k for k in sorted_k if k > 0]
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if not positive:
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return konc, konc
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if konc <= positive[0]:
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return positive[0], positive[min(1, len(positive) - 1)]
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for i in range(len(positive) - 1):
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if positive[i] <= konc <= positive[i + 1]:
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return positive[i], positive[i + 1]
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return positive[-2], positive[-1]
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def _udoy_bracket(udoy_jir: float, udoys: list[float]) -> tuple[float, float]:
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sorted_u = sorted(set(udoys))
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if len(sorted_u) < 2:
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return sorted_u[0], sorted_u[0]
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if udoy_jir <= sorted_u[0]:
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return sorted_u[0], sorted_u[1]
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for i in range(len(sorted_u) - 1):
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if sorted_u[i] <= udoy_jir < sorted_u[i + 1]:
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return sorted_u[i], sorted_u[i + 1]
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return sorted_u[-2], sorted_u[-1]
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def _norm_at_mass(
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entry_normy: list[float],
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mass_ind: int,
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wmassa: float,
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m_a: float,
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m_b: float,
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) -> float | None:
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i = mass_ind - 1
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if i < 0 or i + 1 >= len(entry_normy):
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return None
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n_a, n_b = entry_normy[i], entry_normy[i + 1]
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if n_a <= 0 or n_b <= 0:
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return None
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return lerp(wmassa, m_a, n_a, m_b, n_b)
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def _entries_for(data: dict, npitv: int) -> list[dict]:
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npv = 4 if npitv == 5 else npitv
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return [e for e in data.get("entries") or [] if e["npitv"] == npv]
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def _compute_with_konc(
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entries: list[dict],
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npitv: int,
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params: PiterDairyParams,
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prep: PiterPrepResult,
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konc_pred: float,
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konc_sled: float,
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) -> float | None:
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by_konc = {k: [e for e in entries if abs(e["konc"] - k) < 1e-6] for k in (konc_pred, konc_sled)}
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def _at_konc(konc: float) -> float | None:
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rows = by_konc.get(konc) or []
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if not rows:
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return None
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udoys = [e["udoy"] for e in rows]
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ud_pred, ud_sled = _udoy_bracket(prep.udoy_jir, udoys)
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if ud_pred == ud_sled:
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return None
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e_pred = next((e for e in rows if e["udoy"] == ud_pred), None)
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e_sled = next((e for e in rows if e["udoy"] == ud_sled), None)
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if not e_pred or not e_sled:
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return None
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n01 = _norm_at_mass(e_pred["normy"], prep.mass_ind, prep.wmassa, prep.m_a, prep.m_b)
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n02 = _norm_at_mass(e_sled["normy"], prep.mass_ind, prep.wmassa, prep.m_a, prep.m_b)
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if n01 is None or n02 is None:
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return None
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return lerp(prep.udoy_jir, ud_pred, n01, ud_sled, n02)
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norma1 = _at_konc(konc_pred)
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norma2 = _at_konc(konc_sled)
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if norma1 is None or norma2 is None or konc_pred == konc_sled:
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return None
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norma = lerp(params.konc_oe_sv, konc_pred, norma1, konc_sled, norma2)
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if npitv == 5:
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norma *= 0.65
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return round(norma, 3)
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def _compute_konc_independent(
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entries: list[dict],
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params: PiterDairyParams,
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prep: PiterPrepResult,
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) -> float | None:
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rows = [e for e in entries if e["konc"] == -10]
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if not rows:
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return None
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udoys = [e["udoy"] for e in rows]
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ud_pred, ud_sled = _udoy_bracket(prep.udoy_jir, udoys)
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if ud_pred == ud_sled:
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return None
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e_pred = next((e for e in rows if e["udoy"] == ud_pred), None)
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e_sled = next((e for e in rows if e["udoy"] == ud_sled), None)
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if not e_pred or not e_sled:
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return None
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n01 = _norm_at_mass(e_pred["normy"], prep.mass_ind, prep.wmassa, prep.m_a, prep.m_b)
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n02 = _norm_at_mass(e_sled["normy"], prep.mass_ind, prep.wmassa, prep.m_a, prep.m_b)
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if n01 is None or n02 is None:
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return None
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norma = lerp(prep.udoy_jir, ud_pred, n01, ud_sled, n02)
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if params.housing_system == 2:
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norma *= 1.1
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return round(norma, 3)
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def compute_piter_norm(npitv: int, params: PiterDairyParams, prep: PiterPrepResult | None = None) -> float | None:
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data = load_piter_lactir()
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entries = _entries_for(data, npitv)
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if not entries:
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return None
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if prep is None:
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prep = prepare_piter_calc(
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mass_kg=params.mass_kg,
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milk_yield_kg=params.milk_yield_kg,
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milk_fat_pct=params.milk_fat_pct,
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konc_oe_sv=params.konc_oe_sv,
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body_condition=params.body_condition,
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)
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konc_vals = sorted({e["konc"] for e in entries if e["konc"] > 0})
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if konc_vals:
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min_k = min(konc_vals)
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if min_k > 0:
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konc_pred, konc_sled = _konc_bracket(params.konc_oe_sv, konc_vals)
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return _compute_with_konc(entries, npitv, params, prep, konc_pred, konc_sled)
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return _compute_konc_independent(entries, params, prep)
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def resolve_piter_dairy_norms(params: PiterDairyParams) -> tuple[dict[str, dict[str, float | None]], dict[str, Any]]:
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prep = prepare_piter_calc(
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mass_kg=params.mass_kg,
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milk_yield_kg=params.milk_yield_kg,
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milk_fat_pct=params.milk_fat_pct,
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konc_oe_sv=params.konc_oe_sv,
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body_condition=params.body_condition,
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)
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resolved: dict[str, dict[str, float | None]] = {}
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dynamic: dict[str, Any] = {}
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for npitv in DAIRY_LACTIR_NPITV:
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value = compute_piter_norm(npitv, params, prep=prep)
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if value is None:
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continue
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key = NPITV_TO_INDICATOR.get(npitv)
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if not key:
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continue
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resolved[key] = {"min": value, "max": None}
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dynamic[key] = {"min": value, "npitv": npitv, "method": "racion_piter", "source": "racion"}
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resolved, derived_dyn = apply_derived_norms(resolved, mass_kg=params.mass_kg)
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for k, v in derived_dyn.items():
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dynamic[k] = {**v, "method": "racion_piter", "source": "derived"}
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meta = {
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"method": "racion_piter",
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"massKg": params.mass_kg,
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"milkYieldKg": params.milk_yield_kg,
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"koncOeSv": params.konc_oe_sv,
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"prep": {
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"massInd": prep.mass_ind,
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"mA": prep.m_a,
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"mB": prep.m_b,
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"koncPred": prep.konc_pred,
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"koncSled": prep.konc_sled,
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},
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}
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return resolved, {"meta": meta, "dynamic": dynamic}
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__all__ = ["PiterDairyParams", "PiterPrepError", "compute_piter_norm", "resolve_piter_dairy_norms"]
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