multiscales_strict Examples#
This document contains JSON examples for multiscales_strict metadata layouts.
multiscales_transformations#
1{
2 "zarr_format": 3,
3 "node_type": "group",
4 "attributes": {
5 "ome": {
6 "version": "0.6.dev4",
7 "multiscales": [
8 {
9 "coordinateSystems": [
10 {
11 "name": "physical",
12 "axes": [
13 {
14 "name": "y",
15 "type": "space",
16 "unit": "micrometer"
17 },
18 {
19 "name": "x",
20 "type": "space",
21 "unit": "micrometer"
22 }
23 ]
24 },
25 {
26 "name": "intrinsic",
27 "axes": [
28 {
29 "name": "y",
30 "type": "space",
31 "unit": "micrometer"
32 },
33 {
34 "name": "x",
35 "type": "space",
36 "unit": "micrometer"
37 }
38 ]
39 }
40 ],
41 "datasets": [
42 {
43 "path": "s0",
44 "coordinateTransformations": [
45 {
46 "scale": [1, 1],
47 "type": "scale",
48 "input": {"path": "s0"},
49 "output": {"name": "intrinsic"}
50 }
51 ]
52 }
53 ],
54 "coordinateTransformations": [
55 {
56 "scale": [10, 10],
57 "type": "scale",
58 "input": {"name": "intrinsic"},
59 "output": {"name": "physical"}
60 }
61 ],
62 "name": "image_with_coordinateTransformations",
63 "type": "foo",
64 "metadata": {
65 "key": "value"
66 }
67 }
68 ]
69 }
70 }
71}
multiscales_example#
1{
2 "zarr_format": 3,
3 "node_type": "group",
4 "attributes": {
5 "ome": {
6 "version": "0.6.dev4",
7 "multiscales": [
8 {
9 "name": "example",
10 "coordinateSystems": [
11 {
12 "name": "intrinsic",
13 "axes": [
14 { "name": "t", "type": "time", "unit": "millisecond" },
15 { "name": "c", "type": "channel" },
16 { "name": "z", "type": "space", "unit": "micrometer" },
17 { "name": "y", "type": "space", "unit": "micrometer" },
18 { "name": "x", "type": "space", "unit": "micrometer" }
19 ]
20 }
21 ],
22 "datasets": [
23 {
24 "path": "s0",
25 "coordinateTransformations": [
26 {
27 // the voxel size for the first scale level (0.5 micrometer)
28 // and the time unit (0.1 milliseconds), which is the same for each scale level
29 "type": "scale",
30 "scale": [0.1, 1.0, 0.5, 0.5, 0.5],
31 "input": {"path": "s0"},
32 "output": {"name": "intrinsic"}
33 }
34 ]
35 },
36 {
37 "path": "s1",
38 "coordinateTransformations": [
39 {
40 // the voxel size for the second scale level (downscaled by a factor of 2 -> 1 micrometer)
41 // and the time unit (0.1 milliseconds), which is the same for each scale level
42 "type": "sequence",
43 "input": {"path": "s1"},
44 "output": {"name": "intrinsic"},
45 "transformations": [
46 {
47 "type": "scale",
48 "scale": [0.1, 1.0, 1.0, 1.0, 1.0]
49 },
50 {
51 "type": "translation",
52 "translation": [0, 0, 0.25, 0.25, 0.25]
53 }
54 ]
55 }
56 ]
57 },
58 {
59 "path": "s2",
60 "coordinateTransformations": [
61 {
62 // the voxel size for the third scale level (downscaled by a factor of 4 -> 2 micrometer)
63 // and the time unit (0.1 milliseconds), which is the same for each scale level
64 "type": "sequence",
65 "input": {"path": "s2"},
66 "output": {"name": "intrinsic"},
67 "transformations": [
68 {
69 "type": "scale",
70 "scale": [0.1, 1.0, 2.0, 2.0, 2.0]
71 },
72 {
73 "type": "translation",
74 "translation": [0, 0, 0.75, 0.75, 0.75]
75 }
76 ]
77 }
78 ]
79 }
80 ],
81 "type": "gaussian",
82 "metadata": {
83 "description": "the fields in metadata depend on the downscaling implementation. Here, the parameters passed to the skimage function are given",
84 "method": "skimage.transform.pyramid_gaussian",
85 "version": "0.16.1",
86 "args": "[true]",
87 "kwargs": { "multichannel": true }
88 }
89 }
90 ]
91 }
92 }
93}
multiscales_example_relative#
1{
2 "multiscales": [
3 {
4 "version": "0.6.dev4",
5 "name": "example",
6 "coordinateSystems" : [
7 {
8 "name" : "world",
9 "axes": {
10 "t": {"type": "time", "unit": "millisecond"},
11 "c": {"type": "channel"},
12 "z": {"type": "space", "unit": "micrometer"},
13 "y": {"type": "space", "unit": "micrometer"},
14 "x": {"type": "space", "unit": "micrometer"}
15 }
16 },
17 {
18 "name" : "intrinsic",
19 "axes": [
20 {"name": "t", "type": "time", "unit": "millisecond"},
21 {"name": "c", "type": "channel"},
22 {"name": "z", "type": "space", "unit": "micrometer"},
23 {"name": "y", "type": "space", "unit": "micrometer"},
24 {"name": "x", "type": "space", "unit": "micrometer"}
25 ]
26 }
27 ],
28 "datasets": [
29 {
30 "path": "s0",
31 // the transformation of other arrays are
32 // defined relative to this, the highest resolution, array
33 "coordinateTransformations": [{
34 "type": "scale",
35 "scale": [1, 1, 1, 1, 1],
36 "input": {"path": "s0"},
37 "output": {"name": "intrinsic"}
38 }]
39 },
40 {
41 "path": "s1",
42 "coordinateTransformations": [
43 {
44 // the second scale level (downscaled by a factor of 2 relative to "s0" in zyx)
45 "type": "sequence",
46 "input" : {"path": "s1"},
47 "output" : {"name": "intrinsic"},
48 "transformations": [
49 {
50 "type": "scale",
51 "scale": [1, 1, 2, 2, 2]
52 },
53 {
54 "type": "translation",
55 "translation": [0, 0, 0.5, 0.5, 0.5]
56 }
57 ]
58 }
59 ]
60 },
61 {
62 "path": "s2",
63 "coordinateTransformations": [{
64 // the third scale level (downscaled by a factor of 4 relative to "s0" in zyx)
65 "type": "sequence",
66 "input" : {"path": "s2"},
67 "output" : {"name": "intrinsic"},
68 "transformations": [
69 {
70 "type": "scale",
71 "scale": [1, 1, 4, 4, 4]
72 },
73 {
74 "type": "translation",
75 "translation": [0, 0, 1.5, 1.5, 1.5]
76 }
77 ]
78 }]
79 }
80 ],
81 "coordinateTransformations": [
82 {
83 "name": "additional_translation",
84 "type": "translation",
85 "translation": [0, 0, 10, 20, 30],
86 "input": {"name": "intrinsic"},
87 "output": {"name": "world"}
88 }
89 ]
90 }
91 ]
92}
multiscales_reference_to_label#
1{
2 "ome": {
3 "version": "0.6.dev4",
4 "multiscales": [
5 {
6 "name": "Image",
7 "datasets": [
8 {
9 "path": "s0",
10 "coordinateTransformations": [
11 {
12 "type": "scale",
13 "scale": [0.5, 0.5, 1],
14 "input": {"path": "s0"},
15 "output": {"name": "physical"}
16 }
17 ]
18 }
19 ],
20 "coordinateSystems": [
21 {
22 "name": "physical",
23 "axes": [
24 {"name": "z", "unit": "micrometer"},
25 {"name": "y", "unit": "micrometer"},
26 {"name": "x", "unit": "micrometer"}
27 ]
28 }
29 ],
30 "coordinateTransformations": [
31 {
32 "type": "identity",
33 "input": {"path": "labels/cell_segmentation","name": "physical"},
34 "output": {"name": "physical"}
35 }
36 ]
37 }
38 ]
39 }
40}