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[pre-commit.ci] pre-commit autoupdate #60

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439e3b6
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Oct 5, 2026
9b02864
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Oct 5, 2026
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4 changes: 2 additions & 2 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ repos:

- repo: https://github.com/astral-sh/ruff-pre-commit
# Ruff version.
rev: v0.16.2
rev: v0.16.10
hooks:
# Run the linter.
- id: ruff-check
Expand All @@ -55,7 +55,7 @@ repos:
# - id: codespell

- repo: https://github.com/PyCQA/bandit
rev: 1.7.9
rev: 1.9.4
hooks:
- id: bandit
args: ["-c", "pyproject.toml"]
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50 changes: 26 additions & 24 deletions README.md
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Expand Up @@ -51,36 +51,38 @@ ncols = 500 # Number of spots/cells
counts = np.random.rand(nrows, ncols)

# Create feature annotations
row_data = BiocFrame({
"gene_ids": [f"gene_{i}" for i in range(nrows)],
"gene_names": [f"Gene_{i}" for i in range(nrows)]
})
row_data = BiocFrame(
{"gene_ids": [f"gene_{i}" for i in range(nrows)], "gene_names": [f"Gene_{i}" for i in range(nrows)]}
)

# Create spot/cell annotations
col_data = BiocFrame({
"n_genes": [50, 200] * int(ncols / 2),
"condition": ["healthy", "tumor"] * int(ncols / 2),
"cell_id": [f"spot_{i}" for i in range(ncols)],
"sample_id": ["sample_1"] * int(ncols / 2) + ["sample_2"] * int(ncols / 2),
})
col_data = BiocFrame(
{
"n_genes": [50, 200] * int(ncols / 2),
"condition": ["healthy", "tumor"] * int(ncols / 2),
"cell_id": [f"spot_{i}" for i in range(ncols)],
"sample_id": ["sample_1"] * int(ncols / 2) + ["sample_2"] * int(ncols / 2),
}
)

# Generate spatial coordinates
spatial_coords = BiocFrame({
"x": np.random.uniform(low=0.0, high=100.0, size=ncols),
"y": np.random.uniform(low=0.0, high=100.0, size=ncols)
})
spatial_coords = BiocFrame(
{"x": np.random.uniform(low=0.0, high=100.0, size=ncols), "y": np.random.uniform(low=0.0, high=100.0, size=ncols)}
)

# Create image data
img_data = BiocFrame({
"sample_id": ["sample_1", "sample_1", "sample_2"],
"image_id": ["aurora", "dice", "desert"],
"data": [
construct_spatial_image_class("tests/images/sample_image1.jpg"),
construct_spatial_image_class("tests/images/sample_image2.png"),
construct_spatial_image_class("tests/images/sample_image3.jpg"),
],
"scale_factor": [1, 1, 1],
})
img_data = BiocFrame(
{
"sample_id": ["sample_1", "sample_1", "sample_2"],
"image_id": ["aurora", "dice", "desert"],
"data": [
construct_spatial_image_class("tests/images/sample_image1.jpg"),
construct_spatial_image_class("tests/images/sample_image2.png"),
construct_spatial_image_class("tests/images/sample_image3.jpg"),
],
"scale_factor": [1, 1, 1],
}
)

# Create SpatialExperiment object
spe = SpatialExperiment(
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