phenotypic.measure.MeasureGridSpread

class phenotypic.measure.MeasureGridSpread(*args, **kwargs)

Bases: GridMeasureFeatures

Quantify within-well colony dispersion using pairwise centroid distances.

Compute the sum of squared pairwise Euclidean distances between all colony centroids in each grid section. High values indicate multiple dispersed objects within a single well – a sign of over-segmentation, fragmented growth, or invasive spreading.

Returns:

pd.DataFrame: Section-level statistics sorted by spread (descending) with columns:

• count: number of colonies detected in the section.

• ObjectSpread: sum of squared pairwise Euclidean distances between colony centroids in the section.

Best For:

• Detecting over-segmented wells where multiple objects were found instead of a single cohesive colony.

• Identifying invasive or spreading growth that extends beyond the designated grid position.

• Flagging wells with questionable data quality for manual review or exclusion from downstream analysis.

Consider Also:

• MeasureGridSpatial for between-well neighbor distances rather than within-well dispersion.

• MeasureGridLinRegStats for positional accuracy metrics based on linear regression.

• MeasureBounds for raw centroid positions per colony.

See Also:

Tutorial 7: Measuring and Exporting for a walkthrough of grid-level measurements.

Category: GRID_SPREAD

Name	Description
ObjectSpread	Sum of squared pairwise Euclidean distances between all unique colony pairs within a grid section. Quantifies spatial dispersion of colonies in a grid cell. Higher values indicate greater spread from the section center, suggesting over-segmentation, multi-detections, or colonies growing beyond expected boundaries. Used to identify problematic grid sections requiring refinement or quality review.

Methods

__init__
measure	Compute grid edges and assign each detected object to a grid cell.

__del__()

Automatically stop tracemalloc when the object is deleted.

measure(image)

Compute grid edges and assign each detected object to a grid cell.

Parameters:

image – Image with detected objects.

Returns:

DataFrame with grid assignments (ROW_NUM, COL_NUM, ROW_MAJOR_IDX).