Usage

Quick start

To run the Volumes & Segmentations toolkit and produce the static files suitable for visualization at the frontend:

1. Build the internal database by adding desired entries using preprocessor (see Documentation for preprocess command of Preprocessor and examples on how to add entries to the internal database)

2. From repository root (molstar-volseg by default) run:

       python --db_path PATH_TO_DB --out OUTPUT_FILE --json-params-path PATH_TO_JSON_WITH_PARAMETERS
   

Arguments description

Argument	Description
--db_path	The --db_path argument is mandatory and dictates the path to the internal database constructed using the Preprocessor
--out	The --out argument is mandatory and specifies the desired name for the output file. This file name must include the mandatory .cvsx extension
--json-params-path	The --json-params-path argument is obligatory and defines the path to the JSON file containing the user-specified query parameters (see table below)

Query parameters

Parameter	Description	Kind	Type	Default
entry_id	ID of entry in internal database (e.g. emd-1832)	mandatory	string	N/A
source_db	Source database (e.g. emdb)	mandatory	string	N/A
segmentation_kind	Kind of segmentation (e.g. lattice)	optional	'mesh', 'lattice', 'geometric-segmentation'	all segmentation kinds
time	Timeframe index	optional	integer	all available time frame indices
channel_id	Volume channel ID	optional	string	all available channel IDs
segmentation_id	Segmentation ID	optional	string	all available segmentation IDs
max_points	Maximum number of points for volume and/or lattice segmentation. Used to determine the most suitable downsampling level	optional	integer	1000000000000

Example

This example shows how produce results.cvsx CVSX file for idr-13457537internal database entry (with the database located in temp/test_db) containing the volume data for channel 2 and timeframe index 4, and segmentation data for all available segmentation kinds and timeframe index 4

First create json_with_query_params.json file with the following content:

{
        "entry_id": "idr-13457537",
        "source_db": "idr",
        "channel_id": "2",
        "time": 4
}

Then use the following command:

python vs_toolkit.py --db_path temp/test_db --out results.cvsx --json-params-path json_with_query_params.json

This will query data for channel 2 and time frame 4 for volume and data for all available segmentation kinds and time frame 4, and pack it into idr-13457537.cvsx file