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Athena DeepLynx Demo Setup

Jaren Brownlee edited this page Sep 30, 2024 · 17 revisions

Setup

To set up a dockerized DeepLynx instance:

  1. Install the latest version of Docker
  2. Clone the DeepLynx repository
  3. Navigate to the DeepLynx repository in your terminal/command line/Powershell
  4. Type docker compose pull and wait for the process to finish
  5. Type docker compose up --attach deep-lynx and hit enter
  6. To terminate hit Cntrl-C or Cntrl-D

To set up the Athena DeepLynx container:

  1. Download the files found here. The files are as follows:
  • AthenaDT.owl: ontology file
  • Athena DT_Container_Export.json: data source/type mapping file
  • bt_equipment 1.csv: graph data file
  • AMUSE_scenario_0.xlsx, AMUSE_scenario_1.xlsx, and AMUSE_scenario_2.xlsx: amuse output files
  • tag_athena.py: a python file to properly tag the nodes and files for the demo
  1. Create a new DL container with the AthenaDT.owl ontology
  2. Under "Container Administration"/"Import Container", check the "Data Sources" and "Type Mapping and Transformations" box and import the Athena DT_Container_Export.json file
  3. Enable the Data Source ("Data Management"/"Data Sources") and all the mapping checkboxes ("Data Management"/"Type Mappings")
  4. Under the "Data Management"/"Import Data" page, upload bt_equipment 1.csv
  5. Navigate to "Data"/"Data Viewer". You should see a graph like this:
  • image
  1. Under "Data"/"File Viewer", upload each of the AMUSE_scenarion_# files.
  2. In order for the Python script to operate correctly, you will need two pieces of information- an API auth token and a container ID.
    1. To get the API auth token, view this wiki article.
      1. Use method 1 to generate your key/secret
      2. Use steps 1-3 of this section to generate your auth token.
    2. Container ID is visible in the bottom left corner of the UI. For example, the container from the screenshot above is container 2.
  3. Once you have your auth token and container ID, put them into the TODO lines from the Python code:
  • image
  1. Run the Python code. You should see an output like this (there may be some SSL warnings before this output; you can safely ignore those):
  • image

Relevant DeepLynx endpoints (for querying from Unity)

  • List Tags: GET localhost:8090/containers/:container_id/graphs/tags
    • you want to retrieve id (tag_id) for future queries
  • List Files for a tag: GET localhost:8090/containers/:container_id/graphs/tags/:tag_id/files
    • you want to retrieve id (file_id) for future queries
  • Download file (used for AMUSE data): GET localhost:8090/containers/:container_id/files
  • List Nodes for a tag (used for flashing instrumentation): GET localhost:8090/containers/:container_id/graphs/tags/:tag_id/nodes

DeepLynx Wiki

Sections marked with ! are in progress.

Building DeepLynx

DeepLynx Overview

Getting Started

Building From Source

Admin Web App


Deploying DeepLynx


Integrating with DeepLynx


Using DeepLynx

Ontology

Data Ingestion

Timeseries Data

Manual Path
Automated Path
File/Blob Storage

Data Querying

Event System

Data Targets


Developing DeepLynx

Developer Overview

Project Structure and Patterns

Data Access Layer

Development Process

Current Proposals

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