phenotypic.refine.ReduceMultipleGridObjects#

class phenotypic.refine.ReduceMultipleGridObjects(*args, **kwargs)[source]

Bases: GridObjectRefiner

Reduce multi-detections per grid cell by keeping the object closest to a linear-regression prediction.

Models expected colony positions along each row and column using linear regression, then iteratively removes objects with the largest positional residuals until each grid cell contains at most one detection. Cells with the most objects are processed first to stabilize the regression fit.

Returns:

Input image with objmap and objmask reduced to at most one object per grid cell based on minimum residual error.

Return type:

Image

Best For:

  • Grid cells with multiple detections from halos, debris, or over-segmentation.

  • Condensation or glare artifacts that create extra detections near true colonies.

  • Pinned arrays where consistent spatial layout makes positional prediction reliable.

Consider Also:

See also

How To: Refine Noisy Detection Boundaries for grid-based refinement workflows. Refinement Strategies for a comparison of grid refinement approaches.

Methods

__init__

apply

Applies the operation to an image, either in-place or on a copy.

widget

Return (and optionally display) the root widget.
__del__()

Automatically stop tracemalloc when the object is deleted.

__getstate__()

Prepare the object for pickling by disposing of any widgets.

This ensures that UI components (which may contain unpickleable objects like input functions or thread locks) are cleaned up before serialization.

Note

This method modifies the object state by calling dispose_widgets(). Any active widgets will be detached from the object.

apply(image, inplace=False)

Applies the operation to an image, either in-place or on a copy.

Parameters:

  • image (Image) – The arr image to apply the operation on.

  • inplace (bool) – If True, modifies the image in place; otherwise, operates on a copy of the image.

Returns:

The modified image after applying the operation.

Return type:

Image

widget(image: Image | None = None, show: bool = False) → Widget

Return (and optionally display) the root widget.

Parameters:

  • image (Image | None) – Optional image to visualize. If provided, visualization controls will be added to the widget.

  • show (bool) – Whether to display the widget immediately. Defaults to False.

Returns:

The root widget.

Return type:

ipywidgets.Widget

Raises:

ImportError – If ipywidgets or IPython are not installed.

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