132 lines
3.3 KiB
Markdown
132 lines
3.3 KiB
Markdown
```python
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import imageio.v2 as imageio
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import matplotlib.pyplot as plt
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import numpy as np
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from scipy import ndimage
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# sensor horizontal size
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sensor_width = 7.75
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# image file
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laser = imageio.imread("laser-img/2025-09-07-012621-2mm-aperture.jpg")
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```
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```python
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dimensions = np.array([sensor_width * laser.shape[0] / laser.shape[1], sensor_width])
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half_size = dimensions / 2
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# Mean of all color channels as an approximation of the monochrome image
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laser_monochrome = np.mean(laser, axis=2)
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# Normalized intensity map
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intensity_map = laser_monochrome / np.max(laser_monochrome)
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# Summed intensity in each axis
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intensity_x = np.sum(laser_monochrome, axis=0)
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intensity_y = np.sum(laser_monochrome, axis=1)
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# Center of mass of the laser beam
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center = (
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(ndimage.center_of_mass(laser_monochrome) / np.array(laser_monochrome.shape) - 0.5)
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* dimensions
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* [-1, 1]
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)
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print(f"Center of the beam is at {center[0]:.3f}/{center[1]:.3f}")
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# Calculate FWHM in each axis
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def fwhm(curve, width):
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assert curve.ndim == 1
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half_max = (np.max(curve) + np.min(curve)) / 2
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diff = curve - half_max
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indices = np.where(diff > 0)[0]
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return (indices[-1] - indices[0]) / curve.size * width
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fwhm_y = fwhm(intensity_y, dimensions[0])
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fwhm_x = fwhm(intensity_x, dimensions[1])
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print(f"FWHM in X/Y: {fwhm_x:.2f}/{fwhm_y:.2f}")
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eccentricity = np.sqrt(1 - (min(fwhm_y, fwhm_x) ** 2 / max(fwhm_y, fwhm_x) ** 2))
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print(f"Eccentricity (along cartesian axes): {eccentricity:.5f}")
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```
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Center of the beam is at -0.088/0.238
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FWHM in X/Y: 2.16/1.46
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Eccentricity (along cartesian axes): 0.73687
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```python
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with plt.style.context("dark_background"):
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fig, ax = plt.subplots(figsize=(14, 14))
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im = ax.imshow(
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intensity_map,
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cmap="magma",
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extent=(-half_size[1], half_size[1], -half_size[0], half_size[0]),
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interpolation="none",
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vmin=0,
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)
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ax.set_xlim(-np.max(half_size), np.max(half_size))
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ax.set_ylim(-np.max(half_size), np.max(half_size))
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xy_scale = max(np.max(intensity_x), np.max(intensity_y))
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ax.plot(
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np.linspace(-half_size[1], half_size[1], intensity_x.size),
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intensity_x / xy_scale - np.max(half_size),
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color="red",
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)
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ax.plot(
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intensity_y / xy_scale - np.max(half_size),
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np.linspace(half_size[0], -half_size[0], intensity_y.size),
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color="red",
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)
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# reticle
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ax.axvline(x=center[1], color="white", linestyle=":")
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ax.axhline(y=center[0], color="white", linestyle=":")
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ax.axvline(x=center[1] - fwhm_x / 2, color="gray", linestyle=":")
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ax.axvline(x=center[1] + fwhm_x / 2, color="gray", linestyle=":")
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ax.axhline(y=center[0] - fwhm_y / 2, color="gray", linestyle=":")
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ax.axhline(y=center[0] + fwhm_y / 2, color="gray", linestyle=":")
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cax = fig.add_axes(
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[
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ax.get_position().x1 + 0.01,
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ax.get_position().y0,
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0.02,
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ax.get_position().height,
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]
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)
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fig.colorbar(im, cax=cax)
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text = (
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f"FWHM X/Y: {fwhm_x:.2f} mm/{fwhm_y:.2f} mm\n"
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f"Eccentricity: {eccentricity:.5f}\n"
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f"Offset X/Y: {center[1]:+.3f} mm/{center[0]:+.3f} mm"
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)
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fig.text(0.5, 0.05, text, ha="center")
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fig
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```
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```python
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```
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