Release Trackpy Supports and Simple DataFrame Handling, and Some New Functions · hanjinliu/impy

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wiener for deconvolution.
extract for extraction of certain region of image according to labels.
defocus for z-padding, which is very useful for FFT preprocessing.
focus_map to find focal plane of 3D image stack, using variance of Laplacian method.
std_filter, coef_filter are filters based on standard deviation. scipy.ndimage.generic_filter is very slow so I implemented in E[X^2] - E[X]^2 method.
doh_filter (determinant of Hessian), log_filter (Laplacian of Gaussian) are implemented aimed at single molecule detection in microscopic images. They can used in find_sm.

MarkerFrame and TrackFrame, (subclass of pd.DataFrame) are defined. They have simple interface between trackpy. You can track particles with lnk = df.link(...), and return individual MSDs by lnk.imsd(...). They also supports ImgArray-like slicing, like df["t=0;c=1"].

The use of MarkerArray was a little bit confusing so now all the functions that use coordinates supports interface with AxesFrame or its subclasses.
ip.window.add(X) now supports MarkerFrame/TrackFrame for drawing points/tracks.
Automatic color mapping in ip.window.add(X)
filt argument in specify, centroid_sm and gauss_sm, which filters if labels/markers should be added.
reslice returns PropArray instead or ImgArray to enable direct plot and curve_fit.

specify could not draw labels when certain values are set to radius because of my misunderstanding of scikit-image's disk and ball functions. → Now it works for any values.
split did not inherit scales. &rrar; fixed.