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Copy pathcreate_example_data.py
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359 lines (342 loc) · 10.3 KB
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import zarr
import numpy as np
# v0.4 reference:
# https://ngff.openmicroscopy.org/0.4/index.html
# v0.4 JSON Schema
# https://github.com/ome/ngff/blob/main/0.4/schemas/image.schema
image = zarr.open_group("data/invalid/image-01.zarr", "w")
image.attrs.put({})
# -> fail
image = zarr.open_group("data/invalid/image-02.zarr", "w")
image.attrs.put({"version": "0.4", "multiscales": []})
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
# -> fail, with no obvious error (hanging, with "loading" message)
image = zarr.open_group("data/invalid/image-03.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0], "type": "scale"}
],
"path": "0",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
# -> fails correctly, because of missing .zarray
# More than one resolution level
image = zarr.open_group("data/invalid/image-04.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "z", "type": "space", "unit": "micrometer"},
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0, 1.0], "type": "scale"}
],
"path": "0",
},
{
"coordinateTransformations": [
{"scale": [1.0, 2.0, 2.0], "type": "scale"}
],
"path": "1",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
array = zarr.open_array(
"data/invalid/image-04.zarr/0",
dimension_separator="/",
shape=(2, 64, 64),
chunks=(1, 32, 32),
)
array = zarr.open_array(
"data/invalid/image-04.zarr/1",
dimension_separator="/",
shape=(32, 32),
chunks=(32, 32),
)
# WARNING for dtype mismatch
image = zarr.open_group("data/warning/image-01.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0], "type": "scale"}
],
"path": "0",
},
{
"coordinateTransformations": [
{"scale": [2.0, 2.0], "type": "scale"}
],
"path": "1",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
array = zarr.open_array(
"data/warning/image-01.zarr/0",
dimension_separator="/",
shape=(64, 64),
chunks=(32, 32),
dtype=int,
)
array = zarr.open_array(
"data/warning/image-01.zarr/1",
dimension_separator="/",
shape=(32, 32),
chunks=(32, 32),
dtype=float,
)
# succeeds
image = zarr.open_group("data/valid/image-01.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0], "type": "scale"}
],
"path": "0",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
zarr.open_array(
"data/valid/image-01.zarr/0",
dimension_separator="/",
shape=(1000, 1000),
chunks=(100, 100),
)
# succeeds
image = zarr.open_group("data/valid/image-02.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0], "type": "scale"}
],
"path": "0",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
array = zarr.open_array(
"data/valid/image-02.zarr/0",
dimension_separator="/",
shape=(200, 200),
chunks=(100, 100),
)
array[:] = np.random.uniform(0, 1000, (200, 200))
# succeeds
image = zarr.open_group("data/valid/image-03.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "z", "type": "space", "unit": "micrometer"},
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0, 1.0], "type": "scale"}
],
"path": "0",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
array = zarr.open_array(
"data/valid/image-03.zarr/0",
dimension_separator="/",
shape=(2, 100, 100),
chunks=(1, 50, 100),
)
array[:] = np.random.uniform(0, 1000, (2, 100, 100))
# succeeds
# More than one resolution level
image = zarr.open_group("data/valid/image-04.zarr", "w")
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "z", "type": "space", "unit": "micrometer"},
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0, 1.0], "type": "scale"}
],
"path": "0",
},
{
"coordinateTransformations": [
{"scale": [1.0, 2.0, 2.0], "type": "scale"}
],
"path": "1",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
array = zarr.open_array(
"data/valid/image-04.zarr/0",
dimension_separator="/",
shape=(2, 64, 64),
chunks=(1, 32, 32),
)
array = zarr.open_array(
"data/valid/image-04.zarr/1",
dimension_separator="/",
shape=(2, 32, 32),
chunks=(1, 32, 32),
)
# succeeds
# PLATE
plate = zarr.open_group("data/valid/plate-01.zarr", "w")
plate.attrs.put(
{
"plate": {
"name": "my_wonderful_plate",
"version": "0.4",
"columns": [{"name": "1"}, {"name": "2"}],
"rows": [{"name": "A"}, {"name": "B"}],
"wells": [
{"path": "A/1", "rowIndex": 0, "columnIndex": 0},
{"path": "A/2", "rowIndex": 1, "columnIndex": 0},
{"path": "B/1", "rowIndex": 0, "columnIndex": 1},
{"path": "B/2", "rowIndex": 1, "columnIndex": 1},
],
}
}
)
row_A = plate.create_group("A")
row_B = plate.create_group("B")
well_A1 = row_A.create_group("1")
well_A2 = row_A.create_group("2")
well_B1 = row_B.create_group("1")
well_B2 = row_B.create_group("2")
image_A1 = well_A1.create_group("0")
image_A2 = well_A2.create_group("0")
image_B1 = well_B1.create_group("0")
image_B2 = well_B2.create_group("0")
for well in [well_A1, well_A2, well_B1, well_B2]:
well.attrs.put(
{"well": {"images": [{"acquisition": 1, "path": "0"}], "version": "0.4"}}
)
for image in [image_A1, image_A2, image_B1, image_B2]:
image.attrs.put(
{
"version": "0.4",
"multiscales": [
{
"axes": [
{"name": "y", "type": "space", "unit": "micrometer"},
{"name": "x", "type": "space", "unit": "micrometer"},
],
"datasets": [
{
"coordinateTransformations": [
{"scale": [1.0, 1.0], "type": "scale"}
],
"path": "0",
},
],
"version": "0.4",
}
],
}
)
labels = image.create_group("labels")
labels.attrs.put({"labels": []})
for col in ["A", "B"]:
for row in ["1", "2"]:
zarr.open_array(
f"data/valid/plate-01.zarr/{col}/{row}/0/0",
dimension_separator="/",
shape=(1000, 1000),
chunks=(100, 100),
)