Volume slicing refactoring #630
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| // and then selects slices corresponding to Z=60, X=135, and Y=160. | ||
| // Close other open images | ||
| run("Close All"); | ||
| // open image stack |
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not sure "stack" is the best word...
maybe "open volumetric image" or "open 3D image" ?
| # !First start Napari and drag and drop the image (https://github.com/NEUBIAS/training-resources/raw/master/image_data/xyz_16bit_calibrated__dna_metaphase.tif) in the Napari viewer. | ||
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| # Access the 3D array in the image layer | ||
| d = viewer.layers[0].data # assuming the image is in the first layer |
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maybe better image instead of d?
| shape = d.shape | ||
| print("Image shape:", shape) | ||
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| # Compare the non-scaled non-scaled image to the scaled image. You can also use the 3D view to better appreciate the dimensions. |
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| # Compare the non-scaled non-scaled image to the scaled image. You can also use the 3D view to better appreciate the dimensions. | ||
| voxel_dims = (0.300, 0.1377745, 0.1377745) # original voxel dimensions in µm, in order ZYX | ||
| scaled_voxel_dims = [1 / voxel_dims[0] * v for v in voxel_dims] # rescaling the voxel dimensions to maintain proportions but display with a z-step of 1. |
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We try to avoid fancy python such as list comprehension...
Would that also work?
scaled_voxel_dims = voxel_dims / voxel_dims[0]
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This gives an error: "unsupported operand type(s) for /: 'tuple' and 'float'" (also with list), but we could do this instead:
scale_factor = 1 / voxel_dims[0]
scaled_voxel_dims = [voxel_dims[0] * scale_factor, voxel_dims[1] * scale_factor, voxel_dims[2] * scale_factor]
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Then the latter would be the best, imho.
| viewer.add_image(d, name="Scaled to physical world dimensions", scale=scaled_voxel_dims) # Note that the scaled image layer contains the exact same data as the non-scaled image, but is only visualized differently to show the correct proportions. | ||
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| # Create 2D slices (YX, ZX, and ZY) | ||
| mid_z_slice_ind = shape[0] // 2 |
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while // 2 is cool maybe doing a floating point division and then casting to integer could be more explicit for beginners?
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Thanks for your comments @tischi! I have incorporated them. |
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Hi @AnniekStok, somehow I can't see the new changes...maybe due to the above "conflicts"? |
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Yes I think I had a small unpulled change in my local version. I resolved the conflicts now. |
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Thanks so much! |
Proposal for refactoring the Volume Slicing module based on discussion in #613, replacing the ImageJ macro 'head' example with the metaphase image, removing the Jython exercise and adding a python-napari example.