80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
#!/usr/bin/env python3
|
||
"""Generate a synthetic nanoparticle image for the demo/ folder.
|
||
|
||
The image simulates an AFM scan of particles on a flat substrate:
|
||
- Slightly noisy background
|
||
- ~20 hemisphere-shaped particles with varying radii and heights
|
||
- Saved as both .npy (calibrated float64) and .png (visual preview)
|
||
|
||
Run from project root:
|
||
python scripts/generate_demo_particles.py
|
||
"""
|
||
|
||
import numpy as np
|
||
from pathlib import Path
|
||
|
||
DEMO_DIR = Path(__file__).resolve().parent.parent / "demo"
|
||
DEMO_DIR.mkdir(exist_ok=True)
|
||
|
||
RNG = np.random.default_rng(2024)
|
||
|
||
# --- Image parameters ---
|
||
N = 256 # pixels
|
||
SCAN_SIZE = 5e-6 # 5 µm scan
|
||
PIXEL_SIZE = SCAN_SIZE / N # metres per pixel
|
||
BG_NOISE_RMS = 0.3e-9 # 0.3 nm background noise
|
||
|
||
# --- Generate particles ---
|
||
particles = []
|
||
# Hand-placed cluster + random scatter to give a realistic spread
|
||
fixed = [
|
||
# (cx_frac, cy_frac, radius_nm, height_nm)
|
||
(0.25, 0.30, 120, 30),
|
||
(0.28, 0.34, 80, 20),
|
||
(0.70, 0.25, 150, 45),
|
||
(0.50, 0.55, 100, 25),
|
||
(0.55, 0.60, 60, 15),
|
||
(0.15, 0.75, 200, 55),
|
||
(0.80, 0.80, 90, 22),
|
||
]
|
||
for cx_f, cy_f, r_nm, h_nm in fixed:
|
||
particles.append((cx_f * N, cy_f * N, r_nm * 1e-9, h_nm * 1e-9))
|
||
|
||
# Random particles
|
||
for _ in range(15):
|
||
cx = RNG.uniform(20, N - 20)
|
||
cy = RNG.uniform(20, N - 20)
|
||
radius = RNG.uniform(30, 180) * 1e-9 # 30–180 nm
|
||
height = RNG.uniform(8, 60) * 1e-9 # 8–60 nm
|
||
particles.append((cx, cy, radius, height))
|
||
|
||
# --- Render height map ---
|
||
image = RNG.normal(0, BG_NOISE_RMS, (N, N))
|
||
|
||
yy, xx = np.mgrid[0:N, 0:N]
|
||
|
||
for cx, cy, radius_m, height_m in particles:
|
||
radius_px = radius_m / PIXEL_SIZE
|
||
dist2 = (xx - cx) ** 2 + (yy - cy) ** 2
|
||
inside = dist2 < radius_px ** 2
|
||
# Hemisphere profile: z = h * sqrt(1 - (r/R)^2)
|
||
z = np.zeros_like(image)
|
||
z[inside] = height_m * np.sqrt(1.0 - dist2[inside] / radius_px ** 2)
|
||
image = np.maximum(image, z) # particles don't subtract from each other
|
||
|
||
# --- Save .npy (float64 metres) ---
|
||
npy_path = DEMO_DIR / "nanoparticles.npy"
|
||
np.save(str(npy_path), image)
|
||
print(f"Saved {npy_path} shape={image.shape} range=[{image.min():.2e}, {image.max():.2e}] m")
|
||
|
||
# --- Save .png (8-bit grayscale for quick visual) ---
|
||
from PIL import Image
|
||
|
||
normed = (image - image.min()) / (image.max() - image.min())
|
||
uint8 = (normed * 255).astype(np.uint8)
|
||
png_path = DEMO_DIR / "nanoparticles.png"
|
||
Image.fromarray(uint8, mode="L").save(str(png_path))
|
||
print(f"Saved {png_path}")
|
||
|
||
print(f"\n{len(particles)} particles generated on a {SCAN_SIZE*1e6:.0f} µm × {SCAN_SIZE*1e6:.0f} µm scan")
|