Channels — list view #

URL: /channels

Every channel Litmus has seen — streaming numeric / array signals captured during test runs (scope traces, PSU readback, sensor logs). Each row shows a live sparkline of the last 50 samples and the latest value; values update in place as new samples arrive. Click a row to drill into the single-channel chart.

Table #

Channels — table

A count above the table tells you how many channels are registered.

ColumnWhat it shows
Channel IDThe channel's identifier — typically <instrument-role>.<signal> or <channel-name>
LatestThe most recent sample, with units appended when known. — when no samples yet.
HistoryAn inline sparkline of the last 50 samples (or — for series with fewer than 2 samples).
TypeSample data type (float, array, ...) from the channel descriptor
InstrumentThe instrument role this channel belongs to, when known
Last updatedWhen the most recent sample arrived, in browser-local time

The table is dense — rows are about 30 pixels tall; sparklines render inside the row at 80×24 pixels.

Live updates #

The view watches the event log for instrument.read and instrument.set events and refreshes the table when a new sample arrives — no manual reload needed. Cells re-render in place; unchanged rows don't repaint, so the view stays calm during quiet periods. If the event log isn't running, the page falls back to a 2-second polling loop.

Empty state #

When no channels are registered, the table is replaced with a card explaining how channels get populated: "Channels appear once a test writes to the channel store (e.g. context.observe('scope', value) or instrument observers)."

Underlying data #

Channels live in the channel store — separate from the run / event / measurement stores because the sample shape (numeric streams, arrays, images) doesn't fit the row-per-measurement model the other stores use.

The page reads from the channel store directly. Programmatic access goes through litmus.data.ChannelStore; there is no first-class CLI equivalent today.

Common tasks #

  • Watch a sensor live during a test — open /channels, find the row, watch the Latest column and sparkline update.
  • Drill into one channel's full history — click any row to open the single-channel detail with a full chart + raw data table + session/date filters.

See also #