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29 changes: 16 additions & 13 deletions src/imcflibs/imagej/trackmate.py
Original file line number Diff line number Diff line change
Expand Up @@ -236,31 +236,35 @@ def spot_filtering(


def set_spotfilter(settings, filter_key, filter_value):
"""Sets a TrackMate spot filter with specified filter key and values.
"""Set a TrackMate spot filter with specified filter key and values.

Parameters
----------
settings : fiji.plugin.trackmate.Settings
Dictionary containing all the settings to use for TrackMate.
filter_name : str
The name of the filter to be applied. You must use the keys of the features, not their name.
Here is the table of the feature keys and names for the spot features:
https://imagej.net/plugins/trackmate/scripting/trackmate-detectors-trackers-keys
Settings object to use for TrackMate.
filter_key : str
The key-name of the filter to be applied (as opposed to the filter
"name" shown in ImageJ. Refer to the spot features table on the related
ImageJ wiki page:
https://imagej.net/plugins/trackmate/scripting/trackmate-detectors-trackers-keys#the-feature-penalty-map
filter_value : list
A list containing two values for the filter. The first value is
applied as an above-threshold filter, and the second as a below-threshold filter.

A list containing two values for the filter. The first value is applied
as an above-threshold filter, and the second as a below-threshold
filter.

Returns
-------
Settings
The modified TrackMate settings dict with added spot filters

Example
-------
>>> # Set an above-threshold filter value for spot "QUALITY" without a below-threshold value
>>> tm_settings = set_trackmate_spotfilter(tm_settings, 'QUALITY', [120, None])

To set an above-threshold filter value for spot `QUALITY` without a
below-threshold value use:

>>> settings = set_trackmate_spotfilter(tm_settings, 'QUALITY', [120, None])
"""

settings.addAllAnalyzers()
if filter_value[0] != None:
filter_low = FeatureFilter(filter_key, filter_value[0], True)
Expand All @@ -272,7 +276,6 @@ def set_spotfilter(settings, filter_key, filter_value):
return settings



def sparse_lap_tracker(settings):
"""Create a sparse LAP tracker with default settings.

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