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Charts and dashboards

Chart your test data and share it. A chart is a saved query plus how to draw its rows. A dashboard is a grid of charts. Both rerun their query each time you open them, so "the last 30 days" is always current.

Build them by hand, or ask the assistant: "a dashboard of this week's acceptance runs: yield by part number, failures by measurement, and the runs that failed". It writes the queries, checks each chart, and gives you the links.

Where the rows come from

Two sources are always there: what your devices measured, and how your runs went.

SourceWhat it holdsAsk it
Reservoireverything your devices recorded: channels, video, and one row per judged measurement of every run (trellis_measurements)a channel's trend, a measurement's values against its limit, which measurement fails most
Runsone row per run: recipe and version, unit, outcome, verdict counts, and a column for every run field the run started with (field_item, field_batch, …)yield by item, failures per batch, runs per person

Run fields are only in Runs. A measurement row knows its recipe, unit and outcome, but not the item or batch someone entered. To break down by a run field, query Runs.

Any database or sheet your org connected on Connectors is also a source.

Build a chart

  1. Open Dashboards, switch to the Charts tab, and choose New chart.
  2. Pick the source (Reservoir, Runs or a connector) and write the query. Press Run and check the rows.
  3. Choose how to draw it and which columns go where. The preview updates live.
  4. Save.

To combine two sources, add a second Query and a Join. Within one source, join in SQL.

Choose how to draw it

You want to showDraw it as
something over timea line, with a column of times on the x axis
counts per category (per part, per day)bars. Stack them when the parts make a whole (passed and failed per day)
two quantities in different unitssmall multiples: one panel each, one shared time axis
one number (this week's yield)a stat, with the change from last week beside it
the rows themselvesa table
a limita band behind the trace, or a line at the value

Each chart has one y axis. Put quantities with different units in separate panels, never on a second axis.

Queries for test data

Each of these was tested on real data. Swap in your recipe and measurement names. The query editor suggests tables and columns as you type, and Reservoir → Explore lists Reservoir's.

Runs: yield by part number, counting each unit once. A unit retested until it passed has a row per try; latest keeps only the newest:

SELECT field_part AS part,
       count(*) FILTER (WHERE outcome = 'passed') AS passed,
       count(*) FILTER (WHERE outcome = 'failed') AS failed,
       count(*) FILTER (WHERE outcome NOT IN ('passed', 'failed')) AS not_judged
FROM runs
WHERE latest
GROUP BY 1
ORDER BY failed DESC

Runs: runs per day by outcome (stacked bars, day on the x axis):

SELECT start_ms // 86400000 * 86400000 AS day_ms,
       count(*) FILTER (WHERE outcome = 'passed') AS passed,
       count(*) FILTER (WHERE outcome = 'failed') AS failed
FROM runs
GROUP BY 1
ORDER BY 1

Reservoir: one measurement across every run, with its limits:

SELECT started_ms AS t_ms, uut, f64 AS value, bound_lo, bound_hi
FROM trellis_measurements
WHERE recipe = 'unit_accept' AND name = 'output_v' AND f64 IS NOT NULL
ORDER BY started_ms

Reservoir: which measurements fail most:

SELECT name,
       count(*) FILTER (WHERE verdict = 'fail') AS failed,
       count(*) FILTER (WHERE verdict IN ('unavailable', 'error')) AS not_measured
FROM trellis_measurements
WHERE recipe = 'unit_accept'
GROUP BY name
ORDER BY failed DESC
Note

The two sources' SQL differs slightly. In Runs, / divides exactly, so a day bucket uses //. In Reservoir, / between whole numbers already drops the remainder, so the same bucket is started_ms / 86400000 * 86400000.

Yield is passed ÷ (passed + failed). A run that couldn't measure, was aborted, or passed with configuration pending is neither. Show it as its own series.

Build a dashboard

  1. Open Dashboards and choose New dashboard. Name it; it opens ready to edit.
  2. Add Chart for each saved chart, then drag and resize the tiles.
  3. Add Dashboard filters. A filter on a column narrows every chart that has that column. Use the same column name in every query (recipe, field_part, device) and one filter drives them all.
  4. Save.

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