"""Fur texture and two small "bork"s for the pup plushie (for a friend). Run with local/hear-venv python.
fur.png: tileable soft short fur, neutral light grey so prim colour tints it, 256 px.
bork1.wav / bork2.wav: a small dog's bark, rounded towards "bork": rough glottal pulses ~520-600 Hz that jump up
and fall, /o/-ish formants, a lip-closed "b" start, breath noise, ~0.2 s. 44.1 kHz mono.
Claude Opus 5.5 (Tessel), 2026-10-10."""
import wave
from pathlib import Path

import numpy as np
from PIL import Image, ImageFilter

HERE = Path(__file__).parent
rng = np.random.default_rng(11)

# ---- fur: many short soft strokes, mostly one direction, wrapped so it tiles ----
S = 256
img = np.full((S, S), 0.55, np.float32)
for _ in range(5000):
    x, y = rng.random() * S, rng.random() * S
    ang = np.pi / 2 + rng.normal(0, 0.35)
    L = 4 + rng.random() * 7
    v = rng.random()
    for k in range(int(L * 2)):
        px = int(x + np.cos(ang) * k * 0.5) % S
        py = int(y + np.sin(ang) * k * 0.5) % S
        img[py, px] = img[py, px] * 0.4 + (0.35 + 0.65 * v) * 0.6
img = np.asarray(Image.fromarray((img * 255).astype(np.uint8)).filter(ImageFilter.GaussianBlur(0.7)), np.float32) / 255
img = 0.82 + 0.18 * (img - img.mean()) / (img.std() * 2.5)     # gentle: mostly the prim colour
Image.fromarray((np.clip(img, 0, 1) * 255).astype(np.uint8)).convert("RGB").save(HERE / "fur.png")
print(HERE / "fur.png")

# ---- bork ----
SR = 44100


def formant(x, f, bw):
    r = np.exp(-np.pi * bw / SR)
    a1, a2 = -2 * r * np.cos(2 * np.pi * f / SR), r * r
    y = np.zeros_like(x)
    for i in range(len(x)):
        y[i] = x[i] - a1 * y[i - 1] - a2 * y[i - 2]
    return y


def bork(f_peak, D, seed):
    r = np.random.default_rng(seed)
    t = np.arange(int(SR * D)) / SR
    u = t / D
    # pitch: jumps up fast, then falls: the bark's arc
    f0 = f_peak * (0.75 + 0.25 * np.clip(u / 0.15, 0, 1)) * (1 - 0.35 * np.clip((u - 0.2) / 0.8, 0, 1))
    f0 *= 1 + 0.04 * r.standard_normal(len(t)).cumsum() / np.sqrt(np.arange(1, len(t) + 1))   # jitter: rough voice
    ph = np.cumsum(f0) / SR
    src = (ph % 1.0) ** 4 - 0.2
    src -= src.mean()
    noise = r.standard_normal(len(t)) * 0.15                                   # breathy, a bit growly
    src = src + noise * (0.4 + 0.6 * u)
    open_ = np.clip((t - 0.012) / 0.03, 0, 1)                                  # "b": lips open
    # "o" moving towards "r": formants slide a little
    f1 = 560 - 80 * u
    f2 = 1000 + 200 * u
    vowel = formant(src, float(f1.mean()), 120) + 0.7 * formant(src, float(f2.mean()), 160) \
        + 0.3 * formant(src, 2500, 300)
    closed = formant(src, 300, 90)
    sig = closed * (1 - open_) * 0.5 + vowel * open_
    env = np.clip(t / 0.006, 0, 1) * np.exp(-np.clip(u - 0.25, 0, 1) * 5) * np.clip((D - t) / 0.03, 0, 1)
    sig *= env
    # "k": a tiny click of noise at the end
    k0 = int(SR * (D - 0.035))
    click = formant(r.standard_normal(600), 2200, 900)
    sig[k0:k0 + 600] += click / np.abs(click).max() * np.hanning(600) * 0.12 * np.abs(sig).max()
    return sig / np.abs(sig).max()


for name, fp, D, seed in (("bork1", 560, 0.2, 1), ("bork2", 620, 0.17, 2)):
    sig = bork(fp, D, seed)
    pad = np.zeros(int(SR * 0.02))
    sig = np.concatenate([sig, pad])
    with wave.open(str(HERE / f"{name}.wav"), "wb") as w:
        w.setnchannels(1); w.setsampwidth(2); w.setframerate(SR)
        w.writeframes((sig * 0.7 * 32767).astype("<i2").tobytes())
    print(HERE / f"{name}.wav")