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