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@xingzhongyu Please let me know when it is ready review. Thanks! |
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@RemyLau OK. I need to add some comments to review in the transform test part , and the automatic machine learning part needs to be modified |
xingzhongyu
commented
Jan 14, 2024
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| def __call__(self, data: Data) -> Data: | ||
| xy_pixel = data.get_feature(return_type="numpy", channel="spatial_pixel", channel_type="obsm") | ||
| sc.pp.neighbors(data.data, n_neighbors=self.n_neighbors) |
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Neighbors need to be calculated in advance
xingzhongyu
commented
Jan 14, 2024
| sim_matrix_mean = np.mean(sim_matrix_all, axis=0) | ||
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| data.data.uns[self.out] = sim_matrix_mean | ||
| data.data.obsm[self.out] = sim_matrix_mean |
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change to obsm
xingzhongyu
commented
Jan 14, 2024
| data = Data(adata.copy()) | ||
| RESEPTgraph = RESEPTGraph() | ||
| RESEPTgraph(data) | ||
| assert data.data.uns['RESEPTGraph'].shape == (2000, 2000, 3) |
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resize to (2000,2000,3)
xingzhongyu
commented
Jan 14, 2024
| sc3feature = SC3Feature() | ||
| data = sc3feature(data) | ||
| sc3_feature = data.get_feature(return_type="numpy", channel="SC3Feature", channel_type="obsm") | ||
| assert sc3_feature.shape[0] == data.shape[0] |
xingzhongyu
commented
Jan 14, 2024
| tangramFeature = TangramFeature() | ||
| data = tangramFeature(data) | ||
| tangram_feature = data.get_feature(return_type="numpy", channel="TangramFeature", channel_type="obs") | ||
| assert np.sum(tangram_feature) == 1 |
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Make sure the sum is 1 and the test passed
xingzhongyu
commented
Jan 14, 2024
| data = Data(adata.copy()) | ||
| data = CellTypeNums()(data) | ||
| cell_type_nums = data.get_feature(return_type="numpy", channel="CellTypeNums", channel_type="uns") | ||
| return cell_type_nums.shape[0] == len(np.unique(cell_types)) |
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Test passed.Make sure the number of cell types is the same
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
xingzhongyu
commented
Jan 28, 2024
| for i, j in params_dict.items(): | ||
| idx, key = i.split(f"{Pipeline.PIPELINE_KEY}.", 1)[1].split(".", 1) | ||
| idx, key = i.split(f"{Pipeline.PIPELINE_KEY}.", i)[1].split(".", 1) | ||
| idx = int(idx) |
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I guess it should be PARAMS_KEY
xingzhongyu
commented
Jan 29, 2024
dance/pipeline.py
Outdated
| if param_dict is not None: | ||
| for key, val in param_dict.items(): | ||
| search_space[f"{self.PARAMS_KEY}.{i}.{key}"] = val | ||
| if type(val) == DictConfig: |
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
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add CellTypeNums SC3Feature RESEPTGraph TangramFeature test
Changed local github repository. So I will pre-commit install next time
The code of the automl demo is a bit irregular. I will continue to modify it in the future and learn singularity if necessary.
It is ready to review in the transform test part @RemyLau
complete automl in single modality,maybe need to change it.
More information is needed on the inputs, functions, and return values of functions
In general, leave out the outdated comments.They're caused by file moves, which I've pretty much added to the new file.