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Notebooks

A notebook is the plot-and-notes view of one or more measurements. It is the thing the project page shows first.

Auto-created vs extra notebooks

Creating a dataset creates a notebook for that dataset. Add extra notebooks when you want a review board: several lots on one plot, a golden vs. a failure, or “all S21 in this project that still need sign-off.”

Give extra notebooks a title people can find (Lot 15 review, not Notebook 4).

Traces, not whole datasets

You add traces to a notebook (commonly S21). A dataset can contribute more than one trace; a notebook can mix traces from many datasets.

After you bulk-add traces, snapshot the notebook if you need a frozen copy of the curves and the parameters as they were at review time. Live traces keep following the dataset; a snapshot does not.

Typical review flow

  1. Filter datasets in the project (lot=15, tag needs-review).
  2. Create a notebook titled for that filter.
  3. Add the S21 (or other) traces you care about.
  4. Snapshot when the overlay is the record you will discuss.
  5. Tag the underlying datasets when the review decision is made — the tag lives on the dataset, not only in notebook notes.

SDK sketch

project = cs.projects["cable-qual"]
lot15 = list(project.datasets.filter(cs.params.lot == "15"))

nb = project.create_notebook(title="Lot 15 review")
nb.add_traces(*lot15)   # traces from those datasets join the plot
nb.snapshot()           # freeze the overlay for review

Full signatures: create_notebook, add_traces, snapshot.

When creating a notebook, do not set a primary dataset just to “include everything.” That path can dump every S-parameter from that dataset onto the plot. Add the traces you mean.