"""Shared helpers for the example solvers: load the challenge, write wavs, write submission JSON."""
from __future__ import annotations

import json
import platform
from pathlib import Path

import numpy as np
from scipy.io import wavfile


def load_challenge(path: Path) -> dict:
    with open(path) as f:
        return json.load(f)


def write_wav(path: Path, samples_si: np.ndarray, challenge: dict) -> None:
    """Write pointwise samples of the SI signal, divided by signal_scale, as float32."""
    out = challenge["output"]
    scaled = np.asarray(samples_si, dtype=np.float64) / float(out["signal_scale"])
    path.parent.mkdir(parents=True, exist_ok=True)
    wavfile.write(path, int(out["sample_rate_hz"]), scaled.astype(np.float32))


def hardware_string() -> str:
    cpu = platform.processor() or platform.machine()
    try:
        with open("/proc/cpuinfo") as f:
            for line in f:
                if line.startswith("model name"):
                    cpu = line.split(":", 1)[1].strip()
                    break
    except OSError:
        pass
    return f"{cpu}, single thread, Python {platform.python_version()} + numpy {np.__version__}"


def initial_shape(x: np.ndarray, p: dict) -> np.ndarray:
    """Raised-cosine pluck u_0(x) from the challenge spec."""
    d = x - p["x_p"]
    u = np.zeros_like(x)
    m = np.abs(d) <= p["w"]
    u[m] = 0.5 * p["h"] * (1.0 + np.cos(np.pi * d[m] / p["w"]))
    return u