trackpy.linking.find_link

trackpy.linking.find_link(reader, search_range, separation, diameter=None, memory=0, minmass=0, noise_size=1, smoothing_size=None, threshold=None, percentile=64, preprocess=True, before_link=None, after_link=None, refine=False, **kwargs)

Find and link features, using image data to re-find lost features.

Parameters:

readerpims.FramesSequence

search_rangenumber or tuple

maximum displacement of features between subsequent frames

separationnumber or tuple

minimum separation distance between features

diameternumber or tuple, optional

feature diameter, used for characterization only. Also determines the margin (margin = diameter // 2). Default: separation.

memorynumber, optional

number of frames that features are allowed to disappear. Experimental. Default 0.

minmassnumber, optional

minimum integrated intensity (in masked image). Default 0.

noise_sizenumber or tuple, optional

Size of Gaussian kernel with which the image is convoluted for noise reduction. Default 1.

smoothing_sizenumber or tuple, optional

Size of rolling average box for background subtraction. By default, equals separation. This may introduce bias when refined on the background subtracted image!

thresholdnumber, optional

Threshold value for image. Default None.

percentilenumber, optional

The upper percentile of intensities in the image are considered as feature locations. Default 64.

preprocessboolean

Set to False to turn off bandpass preprocessing.

before_linkfunction, optional

This function is executed after the initial find of each frame, but but before the linking and relocating. It should take the following arguments (or **kwargs):

• coords: `ndarray``containing the initially found feature coordinates

• reader: unprocessed reader (for access to other frames)

• image: unprocessed image

• image_proc: the processed image

• diameter

• separation

• search_range

• margin

• minmass

It should return an ndarray of the same shape as coords.

after_linkfunction, optional

This function is executed after the find and link of each frame. It should not change the number of features. It should take the following arguments (or **kwargs):

• features: a DataFrame containing the feature coordinates and characterization.

• reader: unprocessed reader (for access to other frames)

• image: unprocessed image

• image_proc: the processed image

• diameter

• separation

• search_range

• margin

• minmass

It should return a DataFrame like features.

refineboolean, optional

Convenience parameter to do center-of-mass refinement. Cannot be used combined with an after_link function. Default False.

Notes

This feature is a recent addition to trackpy that is still in its experimental phase. Please report any issues you encounter on Github.

If you use this specific algorithm for your scientific publications, please mention the accompanying publication [1]

References

[1]

van der Wel C., Kraft D.J. Automated tracking of colloidal clusters

with sub-pixel accuracy and precision. J. Phys. Condens. Mat. 29:44001 (2017) DOI: http://dx.doi.org/10.1088/1361-648X/29/4/044001