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View Code? Open in Web Editor NEWEmpirically Informed Random Trajectory Generator in 3-D.
Home Page: https://munterfi.github.io/eRTG3D/
License: GNU General Public License v3.0
Empirically Informed Random Trajectory Generator in 3-D.
Home Page: https://munterfi.github.io/eRTG3D/
License: GNU General Public License v3.0
Write roxygen example for every function that is running and illsutrates the capabilites
Hi @nnneogeorge @munterfinger! I stumbled upon this paper which led me to this repository.
Does eRTG3D have a way to generate 2D trajectories? I couldn't find any mention of this in the documentation, but i figured it was worth a shot after reading this part:
The development started from a 2-D version of the eRTG algorithm by Technitis et al. (2016).
Thank you for your time!
By updating to RoxyGen 6.1 also the hidden functions are getting documented.
Use NoRd to avoid documentation for the dot-functions
Create a github page for the eRTG3D package before submission to CRAN.
The pkgdown package should be used to be consistent with other packages.
Extend the parallel calculation capacities of the functions n.sim.cond.3d(), qProb.3d() and n.sim.gliding.soaring.3d() such that they also run in parallel on Windows systems. At the moment only unix-based systems are supported.
Adjust 3D plotting functions (plot3d, plot3d.tldCube) to the new version (4.8.0) of plotly. Now the color of markers and lines has to be set individually.
Add package import :: statement for the stats and utils packages. It is not throwing an ERROR in the R CMD check but a NOTE.
Add the following citation to the eRTG3D package:
Unterfinger, M., 2018. 3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk. Master's thesis. University of Zurich.
citation("eRTG3D")
Implement glidingSoaring3d() also for windows.
Avoid the 3 Notes in R CMD check --as-cran:
Write the DOI in your Description text in the form
doi:10.5167/uzh-130652.
Ensure that passing in a trajectory as input where the z dimension is 0 or constant, no error occurs and the algorithm worsks properly. The 2-D case should also be handled in a 3-D algorithm.
To Do:
-Eliminate minimum Number of bins
-Adjust the tld-Cube
-Check result and ensure all other functions (testing, plotting, ... ) are still working.
Use the internal R function (nclass.FD) for estimating the number of bins in the stepTurnLift histogram. Thereby the previous implantation of the Freedman–Diaconis rule .fd.bw will be removed.
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