4d — Library

Browsing & selecting datasets · 4d User Manual

← Back to the Library tab

The Library — browse and select your datasets

The Library is the table of every dataset in the project. It is where you browse, sort, flag, and select datasets, launch batch processing, and preview a dataset's overview images. A toolbar sits along the top; below it a splitter divides the dataset table (left) from a preview panel (right).

The numbered markers on the screenshot below point to each region; the legend that follows explains them. The small ? button at the far right of the toolbar (just past the selection summary) opens this page.

The Library tab with numbered regions 1 2 3 4 5 6 7 8 9 10 11
#RegionWhat it is and does
1Process SelectedAdds the checked datasets to the parallel AutoProcess batch queue for processing.
2Selection toolsShow selected only, Select All, Deselect All, Invert selection, and Select / Remove the highlighted rows from the checked set.
3Flag toolsSet the flag colour (none / red / green / blue / gold) on the currently highlighted rows.
4Group & file operationsAdd and rename image groups, move highlighted datasets to another group, trash them, copy to a second project, save/load a selection list, and empty the trash.
5Auto Selection ToolOpens a bar that auto-checks the datasets whose chosen parameter falls in a numeric range (optionally filtered by flag colour).
6Selection summaryA live count — "N datasets: X selected and Y highlighted". The ? help button sits just to its right.
7Select columnThe check-box for each dataset. The set of checked boxes is the selected set that Process Selected acts on.
8Flag columnShows each dataset's flag colour (a coloured marker), set with the flag tools (3).
9Column headersEvery other column (Directory, specimen number, last processed, drift, raw stack, …). Click a header to sort by it (click again to reverse); drag headers to reorder them; the toggle at the far right switches column widths between fitting the values and fitting the full names; right-click a header to show/hide individual columns.
10Highlighted row(s)The rows currently selected in the view (shown in blue). The flag, move and trash actions operate on these highlighted rows.
11Preview panelThe overview images of the current dataset (dark-field, bright-field, parallax, shadow, PSF, average pattern, histograms, …), each with an Inspect button. Arrows step to the previous/next dataset, and the buttons below adjust contrast, overlay, and show the file header.

Working with the table

Sorting and arranging columns

The table can be sorted by any column — click the column header to sort ascending, click again to reverse. Rows stay grouped by their image group. You can drag column headers to reorder the columns, right-click a header to show or hide individual columns, and use the toggle at the right end of the header row to switch each column's width between "fit the values" and "fit the full parameter name". Which columns appear (and their order) is remembered per program mode and can also be configured in Preferences ▸ LibraryTable.

Highlighted vs. selected — two different things

4d distinguishes two independent notions, and the toolbar summary (6) shows both counts:

In short: highlighting is what you are looking at; selecting (checking) is what you will process.

Submitting datasets for batch processing

Tick the datasets you want in the Select column, then press Process Selected (1). The checked datasets are handed to the parallel AutoProcess queue, which runs the configured scripts on them concurrently. While the queue runs, the matching rows animate through their queued and processing states.

Opening a dataset

Double-click a dataset to open it in the Manual Processing tab, where you can run individual scripts on it interactively and inspect its parameters, logs and result images. Single-clicking only highlights the row and updates the preview panel (11).

Flags (3, 8) are a free-form way to triage datasets — for example red for "reject", green for "good", gold for "check later" — and the Auto Selection Tool (5) can then select by flag colour and parameter range, so you can, say, check every good dataset whose drift is below a threshold and send just those to processing.