mattandClaude Sonnet 5
298724a9d3
CI / test (push) Failing after 45m4s
Implements the package from PLAN.md: config/data loading, the LP-first MILP-fallback rolling-horizon optimiser, battery degradation tracking, independent schedule validation, metrics, plots and the CLI, plus the matching test suite. Adds a Gitea Actions workflow (lint + tests) that posts a pass/fail notification to ntfy on every run, and a .gitignore for build/cache artefacts that had been tracked by mistake. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
"""Shared fixtures: a spec matching Attachment 1 and helpers for tiny markets."""
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from __future__ import annotations
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import numpy as np
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import pandas as pd
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import pytest
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from battery_dispatch.config import BatterySpec, RunConfig
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from battery_dispatch.markets import MARKET_1, MARKET_2, Market
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# Equal to Attachment 1, but stated literally so the tests do not depend on the
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# workbook being present or unchanged.
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SPEC = BatterySpec(
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max_charge_mw=2.0,
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max_discharge_mw=2.0,
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capacity_mwh=4.0,
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charge_efficiency=0.95,
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discharge_efficiency=0.95,
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lifetime_years=10.0,
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lifetime_cycles=5000.0,
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degradation_pct_per_cycle=0.001,
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capex_gbp=500_000.0,
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fixed_opex_gbp_per_year=5_000.0,
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)
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@pytest.fixture
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def spec() -> BatterySpec:
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return SPEC
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@pytest.fixture
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def config() -> RunConfig:
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return RunConfig()
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def markets_from(
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market_1_prices: list[float],
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market_2_prices: list[float] | None = None,
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) -> list[Market]:
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"""Build both markets from a half-hourly Market 1 price list.
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``market_2_prices`` is given per *hour*; when omitted Market 2 is priced so
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low that it never trades, isolating Market 1 behaviour.
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"""
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n = len(market_1_prices)
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if market_2_prices is None:
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broadcast = np.zeros(n)
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else:
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assert n == 2 * len(market_2_prices), "one Market 2 price per hour"
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broadcast = np.repeat(np.asarray(market_2_prices, dtype=float), 2)
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return [
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Market(MARKET_1, 1, np.asarray(market_1_prices, dtype=float)),
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Market(MARKET_2, 2, broadcast),
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]
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def prices_frame(
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market_1_prices: list[float],
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market_2_prices: list[float],
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start: str = "2018-01-01",
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) -> pd.DataFrame:
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"""A price frame shaped like the one ``load_prices`` returns."""
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n = len(market_1_prices)
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index = pd.date_range(start, periods=n, freq="30min")
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return pd.DataFrame(
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{
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"market_1_price": np.asarray(market_1_prices, dtype=float),
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"market_2_price": np.repeat(np.asarray(market_2_prices, dtype=float), 2),
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"hour_index": np.arange(n) // 2,
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},
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index=index,
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)
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