Command-line tools

Thalamus ships several command-line modules. Each is run with python -m.

registry — live state editing

The registry tool reads and edits the configuration of a running Thalamus pipeline over gRPC, using JSONPath to address any part of the state tree. This lets you inspect or change node parameters (thresholds, addresses, task settings, …) live, without restarting. Reach for it to tune a parameter mid-experiment, or to script changes to a running pipeline.

python -m thalamus.registry -a ADDRESS -p JSONPATH [-s VALUE] [-d]

  • -a, --address – the pipeline address (default localhost:50050).

  • -p, --path – a JSONPath expression selecting the element(s) to act on.

  • -s, --set – a JSON value to assign to the selected element(s).

  • -d, --delete – delete the selected element(s).

With neither --set nor --delete, the tool prints the current value.

Examples:

# Print the whole node list
python -m thalamus.registry -p '$.nodes'

# Read one node's Running flag (assuming a node named "wave")
python -m thalamus.registry -p "$.nodes[?(@.name=='wave')].Running"

# Start that node
python -m thalamus.registry -p "$.nodes[?(@.name=='wave')].Running" -s true

Because the pipeline state is observable, assignments propagate to every connected client immediately.

Data tools

These convert and inspect .tha capture files (see Concepts and Architecture and Examples):

  • python -m thalamus.record_reader2 FILE – print the records in a capture file.

  • python -m thalamus.dataframe -n NODE -i FILE – export a node’s analog or text channels to CSV, Parquet, and other tabular formats.

  • python -m thalamus.hydrate FILE – convert an entire capture into a single HDF5 file (per-channel data plus received timing).

Applications

  • python -m thalamus.pipeline – the data pipeline (no task controller).

  • python -m thalamus.task_controller – the pipeline plus the behavioral Task Controller.

  • python -m thalamus.eye_calibration – the interactive Eye Calibration tool.