Example-scripts that use the camtraptor R-package to check a dataset stored in camtrap-dp format
- Setup a login for posit.cloud -- free option here: https://posit.cloud/plans/free
- Make your own cloud-copy of this repo by clicking here: https://posit.cloud/content/7957756
- See user guide for RStudio (similar/same interface as "posit Cloud") for general help
- See below for how to run scripts from this repo
- Install R & RStudio
- Clone this repo -- Or download it by clicking the green Code button, choosing Download ZIP at the end of the drop-down menu, and unzipping the CamtrapCheck-main.zip file.
- Open the R-project in RStudio. (Go to File --> Open project... --> select the "CamtrapCheck.Rproj" file from the unzipped CamtrapCheck-main folder.)
- Install required packages by entering this in the RStudio Console (lower-left panel):
install.packages(c("ggplot2", "hrbrthemes", "plotly", "readr"))
The camtraptor package is not currently available on CRAN, but it can be installed with devtools::install() as shown below:
install.packages("devtools")
devtools::install_github("inbo/camtraptor")
- input: camtrap-dp dataset datapackage.json file -- e.g. here
- output: summaries & visual-things
Run the camtrapSandbox.R script by entering this in the RStudio console: source("camtrapSandbox.R", verbose = TRUE)
- input: 3 CSVs in input_data/tables
- output:
- map/chart of plants in Wild Mile modules (interactive and screenshot)
- plants_in_modules.csv -- consolidated table of which plants are/were where in the Wild Mile modules
Run the gridSandbox.R script by entering this in the RStudio console: source("gridSandbox.R", verbose = TRUE)
See a demo of the gridSandbox map here
- Which Camera Trap or other Wild Mile data would it help to tie together?
- How / Where / For whom?
In sdUploader / camtrapPackager.py:
- Need to add camtrap-dp 'sources' to datapackage.json
- Post-observations re-form camtrap-dp to parse out taxa
- address sequenceID? (is that column empty)