lumicks/pylake: v0.13.2

New features Added covariance-based estimator (cve) option to KymoTrack.estimate_diffusion(). See kymotracker documentation for more details. TIFFs exported from Scan and Kymo now contain metadata. The DateTime tag indicates the start/stop timestamp of each frame. The ImageDescription tag contains additional information about the confocal acquisition parameters. Added the Kymo.duration property to provide convenient access to the total scan time in seconds. Added addition operator to KymoTrackGroup. KymoTrackGroups tracked on the same Kymo can be concatenated with the + operator. Added the optional min_length parameter to KymoTrackGroup.estimate_diffusion() to discard tracks shorter than a specified length from the analysis. Added the DwelltimeModel.rate_constants property along with additional documentation explaining the assumptions that underlie using the exponential model. See the dwell time analysis documentation for more information. Ensure same call signature for plot() methods for Scan, Kymo, PointScan and CorrelatedStack: Scan, Kymo and PointScan: Made argument channel optional. Scan and PointScan: Added argument show_title. Kymo: Added arguments image_handle and show_title. CorrelatedStack: See deprecation changelog entry. Introduced lazy loading for TimeSeries data. This means that the data corresponding to a TimeSeries channel is not read from disk until it is used. Bugfixes Added a check which verifies that a Kymo is not downsampled prior to estimating a diffusion constant. Computing diffusion constants from temporally downsampled kymographs is now explicitly disallowed. Fixed a bug in KymoTrack.estimate_diffusion() that could lead to biased estimates obtained with the "ols" estimator. For the diffusion estimate itself to be affected, specific lags have to be missing from the track (for example every second point in a track). This is a regression that was introduced in v0.12.1. Added a warning to KymoTrack.estimate_diffusion() used with the "ols" method when points are missing from a track. In this case the uncertainty estimate is biased. See the section on diffusive processes for more details. Added a warning that estimating the optimal number of points to use when using the "ols" method can be biased if many points are missing. Fixed a bug in KymoTrack.estimate_diffusion() that could lead to biased estimates obtained with the "gls" estimator when gaps occur in the track. Such cases now produce an exception recommending the user to refine the track prior to diffusion estimation. See the section on diffusive processes for more details. Fixed issue where on Jupyter Lab the kymotracker widget would align the Kymograph and track parameters vertically rather than horizontally. Functions that use KymoTrackGroup now gracefully handle the cases where no tracks are available. The refinement functions refine_tracks_centroid() and refine_tracks_gaussian() return an empty list, while KymoTrackGroup.fit_binding_times() and KymoTrackGroup.plot_binding_histogram() raise an exception. lk.track_greedy() now returns an empty KymoTrackGroup instead of an empty list when no coordinates exceed the threshold. lk.track_greedy() now returns an empty KymoTrackGroup instead of an error when an ROI is selected that results in no lines tracked. Fixed a bug where the pixel_threshold could be set to zero for an empty image. Now the minimum pixel_threshold is one. Fixed a bug where single pixel detections in a KymoTrackGroup would contribute values with a dwell time of zero. These are now dropped, the correct minimally observable time is set appropriately and a warning is issued. Fixed slicing of a Kymo where slicing from a time point inside the last line to the end (e.g. kymo["5s":]) resulted in a Kymo which returned errors upon trying to access its contents. Fixed a minor bug in force calibration. In rare cases it was possible that the procedure to generate an initial guess for the power spectral fit failed. This seemed to occur when the spectrum supplied is a mostly flat plateau. After the fix, an alternative method to compute an initial guess is applied in cases where the regular method fails. Note that successful calibrations were not at risk for being incorrect due to this bug since they would have resulted in an exception rather than an invalid result. Deprecations Deprecated property CorrelatedStack.src. In future versions, the contents of src will be considered an implementation detail that is not directly accessible. Data should be accessed through the public API. Reordered the keyword arguments of the method CorrelatedStack.plot() and enforced all parameters after channel to be keyword arguments. For details see the docstring. Enforced the argument axes of the method plot() for Scan, Kymo and PointScan to be a keyword argument. Renamed force distance fitting functions. They are deprecated now and will be removed in the future: inverted_marko_siggia_simplified -> wlc_marko_siggia_distance marko_siggia_simplified -> wlc_marko_siggia_force marko_siggia_ewlc_distance -> ewlc_marko_siggia_distance marko_siggia_ewlc_force -> ewlc_marko_siggia_force odijk -> ewlc_odijk_distance inverted_odijk -> ewlc_odijk_force freely_jointed_chain -> efjc_distance inverted_freely_jointed_chain -> efjc_force twistable_wlc -> twlc_distance inverted_twistable_wlc -> twlc_force Other changes All KymoTrack instances must have the same source Kymo and color channel in order to be in the same KymoTrackGroup instance. While this behavior was required previously for some downstream analyses on the tracks, it is now explicitly enforced upon KymoTrackGroup construction. When calling KymoTrackGroup.estimate_diffusion() without specifying the min_length parameter, tracks which are shorter than the required length for the specified method will be discarded from analysis and a warning emitted. Previously, if any tracks were shorter than required, an error would be raised. Updated benchmark to not use deprecated functions and arguments. Prior to this change, running the benchmark would produce deprecation warnings. Kymo.plot() now returns a handle of the plotted image. PointScan.plot() now returns a list of handles of the plotted lines