ivvv
The image voxel volume viewer (pronounced ivy).
Wat?
ivvv is an attmept to provide a lightweight, minimal volume viewer for interactive data exploration in jupyter. (This is a jupyter widget that provide volumetric rendering given a multiple channel zstack as a numpy array.)
Why?
We wanna look at stuff in notebooks
Most 3D viewers are far too heavyweight to use for quick visualization tasks when experimenting with tractably-sized (analyzing, checking, ...) 3D volumetric datasets.
Who?
Envisioned user group is anyone who wants a robust and quick way to interactively interrogate volumetric data as part of their workflows; domain which motivated development is multi-channel volumetric light/fluorescence microscopy datasets.
Stripped down version of 3D renderes used 3D cell viewer. Standard scientific python toolkit.
How?
We've used a stripped down version of 3D rendering provided by the Allen Cell Explorer's 3D Cell Viewer.
Install
pip install ivvv <- would be nice if it worked
jupyter nbextension install --py ivvv
jupyter nbextension enable ivvv --py
Detailed docs
Schema
{
"$schema": "http://json-schema.org/draft-06/schema#",
"title": "Allen Volume Format image",
"description": "An image from e.g. the Allen Cell Explorer Collection defined for render by 3D Cell Viewer (ACE)",
"type": "object",
"properties": {
"width": {
"description": "Width of original volumetric data prior to downsampling.",
"type": "integer"
},
"height": {
"description": "Height of original volumetric data prior to downsampling.",
"type": "integer"
},
"channels": {
"description": "Specifies number of channels.",
"type": "integer",
},
"channel_names": {
"description": "Names of each of the channels to be rendered, in order. Unique identifier expected.",
"type": "array",
"items": {
"type": "string"
},
"minItems": 1,
"uniqueItems": true
}
"rows": {
"description": "Number of rows in tile array in each image.",
"type": "integer"
},
"cols": {
"description": "Number of columns in tile array in each image.",
"type": "integer"
},
"tiles": {
"description": "Number of tiles, which must be equal to the number of z-slices in original volumetric data.",
"type": "integer"
},
"tile_width": {
"description": "Width of each tile in volumetric dataset to be rendered, in pixels.",
"type": "integer"
},
"tile_height": {
"description": "Height of each tile in volumetric dataset to be rendered, in pixels.",
"type": "integer"
},
"atlas_width": {
"description": "Total width of volumetric object containing all the tiles, in pixels.",
"type": "integer"
},
"atlas_height": {
"description": "Total height of volumetric object containing all the tiles, in pixels.",
"type": "integer"
},
"pixel_size_x": {
"description": "Size of pixels in volumetric data to be rendered, in x-dimension, unitless.",
"type": "float"
},
"pixel_size_y": {
"description": "Size of pixels in volumetric data to be rendered, in y-dimension, unitless.",
"type": "float"
},
"pixel_size_z": {
"description": "Size of pixels in volumetric data to be rendered, in z-dimension, unitless.",
"type": "float"
},
"name": {
"description": "Base name of images.",
"type": "string"
},
"images": {
"description": "List of images as defined by name and channel array; should correspond to *name*.",
"type": "array",
"items": {
"name": {
"description": "Name of single image item.",
"type": "string",
},
"channels": {
"description": "Channels to be rendered. Unique identifiers expected.",
"type": "array",
"items": {
"type": "integer"
},
"minItems": 1,
"uniqueItems": true
}
"minItems": 1,
"uniqueItems": true
}
}
"version": {
"description": "Current version of the schema.",
"type": "string"
},
"aicsImageVersion": {
"description": "Version of aicsImage python library that generated the employed texture map.",
"type": "string"
},
},
"required": ["width", "height", "channels", "channel_names", "rows", "cols", "tiles", "tile_width", "tile_height", "atlas_width", "atlas_height", "pixel_size_x", "pixel_size_y", "pixel_size_z", "name", "images", "version"]
}Nice example
AICS-10_5_5.ome.tif_atlas.json
{
"width":306,
"height":494,
"channels":9,
"channel_names":["DRAQ5","EGFP","Hoechst 33258","TL Brightfield","SEG_STRUCT","SEG_Memb","SEG_DNA","CON_Memb","CON_DNA"],
"rows":7,
"cols":10,
"tiles":65,
"tile_width":204,
"tile_height":292,
"atlas_width":2040,
"atlas_height":2044,
"pixel_size_x":0.065,
"pixel_size_y":0.065,
"pixel_size_z":0.29,
"images":[{"name":"AICS-10_5_5.ome.tif_atlas_0.png","channels":[0,1,2]},{"name":"AICS-10_5_5.ome.tif_atlas_1.png","channels":[3,4,5]},{"name":"AICS-10_5_5.ome.tif_atlas_2.png","channels":[6,7,8]}],
"name":"AICS-10_5_5",
"version":"0.0.0",
"aicsImageVersion":"0.3.0"
}
