"""Synthesize a clean microscopy-like image and a degraded (blurred + noisy) version."""
from __future__ import annotations

import numpy as np


def clean_image(h: int = 256, w: int = 256, seed: int = 0) -> np.ndarray:
    """A microscopy-style scene: blobs (cells) + filaments, values in [0, 1]."""
    rng = np.random.default_rng(seed)
    img = np.zeros((h, w), np.float32)
    yy, xx = np.mgrid[0:h, 0:w]
    for _ in range(35):                                   # blobs
        cy, cx = rng.uniform(0, h), rng.uniform(0, w)
        r = rng.uniform(3, 9)
        img += rng.uniform(0.4, 1.0) * np.exp(-(((yy - cy) ** 2 + (xx - cx) ** 2) / (2 * r ** 2)))
    for _ in range(12):                                   # filaments
        y0, x0 = rng.uniform(0, h), rng.uniform(0, w)
        ang = rng.uniform(0, np.pi)
        for t in np.linspace(0, rng.uniform(20, 60), 200):
            y, x = int(y0 + t * np.sin(ang)), int(x0 + t * np.cos(ang))
            if 0 <= y < h and 0 <= x < w:
                img[max(0, y - 1):y + 1, max(0, x - 1):x + 1] += 0.5
    return np.clip(img / max(img.max(), 1e-6), 0, 1)


def degrade(clean: np.ndarray, psf_sigma: float = 2.0, peak: float = 40.0,
            read_sigma: float = 0.03, seed: int = 1) -> np.ndarray:
    """Blur with a Gaussian PSF, then add Poisson (shot) + Gaussian (read) noise."""
    from scipy.ndimage import gaussian_filter
    rng = np.random.default_rng(seed)
    blurred = gaussian_filter(clean, sigma=psf_sigma)
    shot = rng.poisson(np.clip(blurred, 0, None) * peak) / peak     # photon noise
    noisy = shot + rng.normal(0, read_sigma, clean.shape)           # read noise
    return np.clip(noisy, 0, 1).astype(np.float32)