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| parameter_tolerance=(0.01, 0.01), coarse_binning=None, final_binning = None, | ||
| angle_binning = None, reduced_volume = None): | ||
| """ | ||
| Initialize a LaminographyCorrector processor to optimize tilt and center-of-rotation for |
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| Initialize a LaminographyCorrector processor to optimize tilt and center-of-rotation for | |
| Initialize a LaminographyCorrector processor to fit your geometry to find tilt and center-of-rotation for |
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| Parameters | ||
| ---------- | ||
| initial_parameters : tuple of float, optional |
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Maybe get this from geometry instead
| Initial guess for the geometry parameters (tilt_angle_deg, center_of_rotation_pix). | ||
| Defaults to (0.0, 0.0). | ||
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| parameter_bounds : list of tuple of float, optional |
| Bounds for the parameters [(tilt_min, tilt_max), (CoR_min, CoR_max)]. | ||
| Defaults to [(-10, 10), (-20, 20)]. | ||
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| parameter_tolerance : tuple of float, optional |
| Final binning factor applied for fine optimisation. | ||
| If None, no binning is applied in the fine optimisation step. | ||
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| angle_binning : float, optional |
| Subsampling factor for the angle dimension during optimisation. | ||
| If None, automatically determined based on input dataset. | ||
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| reduced_volume : ImageGeometry, optional |
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| reduced_volume : ImageGeometry, optional | |
| image_geometry: ImageGeometry, optional |
| If None, automatically determined based on input dataset. | ||
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| reduced_volume : ImageGeometry, optional | ||
| A reduced-dimension volume to be used for optimisation, e.g. obtained using |
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| A reduced-dimension volume to be used for optimisation, e.g. obtained using | |
| Pass a reduced-dimension ImageGeometry to speed up the fit, e.g. obtained using |
| losses = [t[2] for t in eval['evaluations']] | ||
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| ax = axs[i] | ||
| scatter = ax.scatter(tilts, cors, c=losses, cmap='viridis', s=100, edgecolors='k') |
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| scatter = ax.scatter(tilts, cors, c=losses, cmap='viridis', s=100, edgecolors='k') | |
| scatter = ax.scatter(tilts, cors, c=losses, cmap='viridis_r', s=100, edgecolors='k') |
| # Test with 180 degree tilt | ||
| ag_updated_180 = processor.update_geometry(ag, 180.0, 0.0) | ||
| self.assertEqual(ag_updated_180.config.panel.num_pixels[0], original_panel[0]) | ||
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Add a tilted dataset from the cil data simulated spheres data forward projected
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| class LaminographyCorrector(Processor): |
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| class LaminographyCorrector(Processor): | |
| class LaminographyGeometryCorrector(Processor): |
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Changes
Add automatic laminography alignment tool.
Projection matching method to optimise laminography reconstruction by searching tilt and centre of rotation offset
coarse_binningandfinal_binningangle_binningparameter_boundsstarting with an initial guessinitial_parameters.reduced_volumeTesting you performed
New demo script: TomographicImaging/CIL-Demos#280
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