Package: trackdem 0.6
Marjolein Bruijning
trackdem: Particle Tracking and Demography
Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.
Authors:
trackdem_0.6.tar.gz
trackdem_0.6.zip(r-4.5)trackdem_0.6.zip(r-4.4)trackdem_0.6.zip(r-4.3)
trackdem_0.6.tgz(r-4.5-x86_64)trackdem_0.6.tgz(r-4.5-arm64)trackdem_0.6.tgz(r-4.4-x86_64)trackdem_0.6.tgz(r-4.4-arm64)trackdem_0.6.tgz(r-4.3-x86_64)trackdem_0.6.tgz(r-4.3-arm64)
trackdem_0.6.tar.gz(r-4.5-noble)trackdem_0.6.tar.gz(r-4.4-noble)
trackdem_0.6.tgz(r-4.4-emscripten)trackdem_0.6.tgz(r-4.3-emscripten)
trackdem.pdf |trackdem.html✨
trackdem/json (API)
| # Install 'trackdem' in R: |
| install.packages('trackdem', repos = c('https://marjoleinbruijning.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/marjoleinbruijning/trackdem/issues
Last updated 4 years agofrom:c74c15724a. Checks:1 OK, 11 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 06 2025 |
| R-4.5-win-x86_64 | NOTE | Mar 06 2025 |
| R-4.5-mac-x86_64 | NOTE | Mar 06 2025 |
| R-4.5-mac-aarch64 | NOTE | Mar 06 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 06 2025 |
| R-4.4-win-x86_64 | NOTE | Mar 06 2025 |
| R-4.4-mac-x86_64 | NOTE | Mar 06 2025 |
| R-4.4-mac-aarch64 | NOTE | Mar 06 2025 |
| R-4.4-linux-x86_64 | NOTE | Mar 06 2025 |
| R-4.3-win-x86_64 | NOTE | Mar 06 2025 |
| R-4.3-mac-x86_64 | NOTE | Mar 06 2025 |
| R-4.3-mac-aarch64 | NOTE | Mar 06 2025 |
Exports:createBackgroundcreateImageSeqfindMaxCostfindPixelRangefindThresholdidentifyParticlesloadImagesmanuallySelectmergeTracksrunBatchsimulTrajecsubtractBackgroundtestNNtrackParticles
Dependencies:base64encbslibcachemclicommonmarkcrayonDerivdigestfastmapfontawesomefsgluehtmltoolshttpuvjquerylibjsonlitelaterlatticelifecyclemagrittrMASSmemoisemimeneuralnetpngpromisesR6rappdirsrasterRcppRcppArmadillorlangsassshinysourcetoolsspterrawithrxtable
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Background detection | createBackground |
| Create image sequence | createImageSeq |
| Find maximum tracking cost | findMaxCost |
| Find pixel range | findPixelRange |
| Find threshold | findThreshold |
| Identify moving particles | identifyParticles |
| Load .png images | loadImages |
| Manually identify true and false positives with a GUI. | manuallySelect |
| Merge track records | mergeTracks |
| 'plot' methods for class 'TrDm'. | plot.TrDm |
| 'print' methods for class 'TrDm'. | print.summaryTrDm |
| 'print' methods for class 'TrDm'. | print.TrDm |
| Batch analysis | runBatch |
| Simulate trajectories and save as png files. | simulTrajec |
| Background subtraction | subtractBackground |
| 'summary' methods for class 'TrDm'. | summary.TrDm |
| Train, validate and test artificial neural networks | testNN |
| trackdem - Particle Tracking and Demography | trackdem |
| Track particles | trackParticles |
| Update identified particles. | update.particles |