Adding functionalities#2
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getStepsizes is a method for the msdanalyzer object that returns a cell array with the step sizes, either in x and y or absolute distance, for each step in each track. Inspecting the distribution of step sizes can be useful to show the precision (lower step size), find different diffusion speeds (multiple peaks), comparing between experiments with different time steps (do step sizes get bigger, or are they limited by precision) Code is based on "getVelocities".
getSDdt is a method for the msdanalyzer object that returns a cell array with, for each step in each track, the squared displacement for that step divided by the time step. This complements the "getStepsizes" function: the distribution of the square displacement per time should be the same between experiments with different time steps. Different peaks can indicate different diffusive states of the tracked particles. Code is based on "getVelocities" and "getStepsizes".
to plotMSD, added the option to hide the (0,0) points on the MSDplot. The line between (0,0) and the first point would often obscure other data, in the case of big pooled datasets with different time steps.
Suppresses command line output. Main reason is that the progress counter does not work when used in Jupyter Notebook leading to output spam.
fixed a bug where time delays would be interpreted as different when they differ very slightly due to limited precision
silent option: no progress printed in command line
See Backlund et al. 2015 "Chromosomal locus tracking with proper accounting of static and dynamic errors"
- use parallel computing - increased upper bound for D (ub(1)) - initial guess for D is now based on MSD closest to t=1s. (p0)
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Dear Jean-Yves Tinevez,
I found your msdanalyzer code very useful for my research. I am examining tracks from different experiments with different time steps. One of the questions is whether we can see different diffusion states for our particles. However, there were a few functionalities that I missed in msdanalyzer, and wrote myself, included in this pull request:
All the best,
Aster
P.S.: this is my first pull request, so let me know if I did anything wrong.