Metric Data Export

The Metric Data (CSV) export extracts any configured metric from the workspace metric library as CSV. It supports both Long (tidy) and Wide layouts, optional temporal filtering, and a sidecar provenance codebook.

AOIs are identified by their displayed name throughout: AOIs sharing a displayed name are merged, within a stimulus and across stimuli, matching the behavior everywhere else in the application. The names No_AOI and Any_Fixation are reserved for the synthetic slots (fixations outside every AOI, and the all-fixations aggregate).

Layout Formats

Long (tidy) Format

Best suited for analysis in modern statistical languages (R, Python Pandas, Julia) and software like JASP or jamovi. Emits one row per observation. Active dimension columns are dynamically included only when needed by the selected metrics:

Scalar metrics: stimulus × participant rows.
AOI-vector metrics: adds the AOI column (stimulus × participant × slot).
AOI-pair-matrix metrics: adds the From_AOI and To_AOI columns (stimulus × participant × cell).
Windowed metrics: adds the Window_Start and Window_End columns (stimulus × participant × window). Windows cover each participant’s own recording, so a participant who stopped recording early has fewer window rows, never padded zeros.
Participant-pair-matrix metrics: adds the Participant_B column (stimulus × unordered pair).

Example CSV Output

Participant_ID,Participant,Stimulus,AOI,Metric,Unit,Value
1,P01,Stimulus1,Logo,Fixation count,,3
1,P01,Stimulus1,No_AOI,Fixation count,,1
1,P01,Stimulus1,,Average fixation duration,ms,250.5

Fields are quoted only when they contain the delimiter, quotes, or line breaks.

Wide Format

Best suited for case-per-row analysis in traditional software like IBM SPSS. Emits one row per participant × stimulus case. Values are expanded into separate columns:

Scalar metrics → <Label> column.
AOI-vector metrics → <Label>_<AOI> column per slot (including No_AOI and Any_Fixation).
AOI-pair-matrix metrics → <Label>_<From>_to_<To> column per cell.
Participant-pair metrics (e.g. scanpath similarity) → <Label>_<Participant> column per participant in the group. Each row holds participant A’s line of the similarity matrix, so the wide file IS the full matrix grid, diagonal included.

Temporal Exclusion: Wide format excludes windowed metrics, as mixed-grain wide tables are statistically unsound. Export time series in the long format instead.

Example CSV Output

Participant_ID,Participant,Stimulus,Fixation_Count_Logo,Fixation_Count_No_AOI,Average_fixation_duration
1,"P01","Stimulus1",3,1,250.5
2,"P02","Stimulus1",5,0,220.1

Missing Values

Missing values (for example, a participant who never fixated on an AOI when computing Time to First Fixation) are exported as empty cells.

No Sentinel Values: Sentinel values like -1 are never used, preventing downstream statistical models (such as group means) from being silently poisoned by negative numbers.

Sidecar Codebook

Checking the Include metric codebook option downloads the export as a ZIP archive containing two files:

GazePlotter-MetricData.csv — The dataset itself.
GazePlotter-MetricData-codebook.csv — A sidecar table detailing the operational parameters and provenance of every exported column.

The codebook contains the following columns:

Column	Description
`Metric`	The column label used in the data CSV
`Base_Metric`	The metric’s original registry name
`Base_Id`	The unique recipe identifier
`Unit`	Measurement units (e.g. `ms`, `%`, or empty for dimensionless)
`Measurement_Class`	Statistical class of the metric: `extensive` (counts, summed durations), `intensive` (rates, averages, latencies), `proportion` (binary indicators), or `relational` (participant-pair)
`Parameters`	Active parameters, as shown in the metric library (e.g. `Fixation pairs, Step 2`)
`Projection`	Selected projection (e.g. `max across AOIs`)
`Window`	Windowing parameters (e.g. `1000 ms window, 100 ms step`)
`Output_Shape`	Reshaped dimension classification
`Time_Range`	Range restriction (e.g. `t ∈ [500, 2000] ms` or `full`)
`Participants`	List of participants included
`Stimuli`	List of stimuli included
`AOI_Missing`	Displays `true` if any stimulus lacked the AOI referenced by a projection

Exporting Data

The modal guides you through four collapsible steps, one open at a time. Every collapsed step shows a one-line summary of its current selection, and its badge turns into a check when the step is complete.

Open the Export menu in the Ribbon and select Metric Data (CSV).
Choose metrics: check the metrics to include. On longer lists a search bar appears; Select Found and Deselect Found apply the current matches to the selection in one click.
Choose stimuli and Choose participants: check items the same way. The group chips above the participant list select or deselect an entire participant group at once; individual checkmarks refine the result.
Configure the file: choose the Format (Long (tidy) or Wide), and the Delimiter and Decimal Separator according to your regional system settings. Optional: enter Time Start (ms) and Time End (ms) boundary limits to crop the evaluation window. The step ends with a preview of the exact columns the file will contain. Switching to Wide deselects time-series metrics and says so.
Click Export Data.

Sliding Windows: Sliding-window metrics evaluate dense overlaps and can generate very large files. Opt-in to windowed metrics explicitly when exporting.