Add Dimitri's script #42
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| class SagittalInterpolator: |
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I would imagine this one is a just a copy of the logic from CoronalInterpolator.
Possible actions
- No action
- Write a more general linear interpolator and make sure
CoronalInterpolatorandSagittalInterpolatorare special cases - Outsource the interpolation to
atlinter
| class SagittalInterpolator: | ||
| """Interpolator that works pixel by pixel in the coronal dimension.""" | ||
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| def __init__(self, kind="linear", fill_value=0, bounds_error=False): |
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We might as well type annotate the entire script. Should be easy
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| def align_marker( | ||
| dataset_id, nvol, model_gl, header, |
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We should definitely run some linters/ code formatters on it.
scripts/align_ish_data.py
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| from skimage.color import rgb2gray | ||
| from skimage.filters import threshold_otsu | ||
| from skimage.transform import resize | ||
| from atldld.sync import DatasetDownloader |
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Seems like everything related to Allen downloads is outsourced to atldld which is great.
| from atlalign.volume import GappedVolume, CoronalInterpolator | ||
| import scipy | ||
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| warnings.filterwarnings("ignore") |
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IMO we should identify where exactly this warning is raised and do one of the following
- Filter the warning inside of a context manager
- Fix the cause of the warning
| all_dl = np.vstack((all_dl, np.copy(img_mov)[None, :, :])) | ||
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| all_ib = [] | ||
| for i, (img_mov, sn) in tqdm(enumerate(zip(all_dl, all_sn))): |
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Ok, so it seems like we first do deep learning registration followed by intensity based. I guess we don't question it and just assume that is the best setup.
scripts/align_ish_data.py
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| DATA_FOLDER = "../data/" | ||
| CCF_version = args.ccf | ||
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| dl_global_path = join(DATA_FOLDER, "atlalign/global/boring_bear/") |
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I would switch to pathlib
scripts/align_ish_data.py
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| # List of ISH experiment ids according to the AIBS API | ||
| # ish experiments used in Rodarie et al. 2022 | ||
| genelist = [868, 1001, 77371835, 479] |
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This could potentially be passed via the CLI
scripts/align_ish_data.py
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| # List of ISH experiment ids according to the AIBS API | ||
| # ish experiments used in Rodarie et al. 2022 | ||
| genelist = [868, 1001, 77371835, 479] | ||
| namelist = ["pvalb", "SST", "VIP", "gad1"] |
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This should be uniquely implied by the gene_id
scripts/align_ish_data.py
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| # ish experiments used in Rodarie et al. 2022 | ||
| genelist = [868, 1001, 77371835, 479] | ||
| namelist = ["pvalb", "SST", "VIP", "gad1"] | ||
| is_sagittal = [False for _ in range(4)] |
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Again, this should be uniquely implied by the gene_id
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