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and Acoustic Data Analysis","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# wildrtrax \u003cimg src=\"man/figures/logo.png\" width=\"50%\" align=\"right\"/\u003e\n\n\u003c!-- badges: start --\u003e\n\n[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable) [![CRAN status](https://www.r-pkg.org/badges/version/wildrtrax)](https://CRAN.R-project.org/package=wildrtrax) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13952335.svg)](https://doi.org/10.5281/zenodo.13952335) [![Codecov test coverage](https://codecov.io/gh/ABbiodiversity/wildrtrax/graph/badge.svg)](https://app.codecov.io/gh/ABbiodiversity/wildrtrax)\n\n\u003c!-- badges: end --\u003e\n\n## Overview\n\n`wildrtrax` (pronounced *wild-r-tracks*) is an R package containing functions to help manage and analyze environmental sensor data to and from [WildTrax](https://wildtrax.ca/). 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The goal is to follow the work flow of pre-processing, linking with WildTrax, download and analysis.\n\n### Discover Data\n\nExplore data through [Data Discover](https://discover.wildtrax.ca/). No login required to access public data! Use `wt_auth()` to login to see data you have privileges and membership to.\n\n``` r\nlibrary(wildrtrax)\nlibrary(sf)\n\n# Search for public data without a boundary\nwt_dd_summary(sensor = 'ARU', species = 'White-throated Sparrow')\n\n# Apply an area of interest. Define a polygon or use a bbox from sf::st_bbox\nmy_aoi \u003c- list(\n  c(-113.96068, 56.23817),\n  c(-117.06285, 54.87577),\n  c(-112.88035, 54.90431),\n  c(-113.96068, 56.23817)\n)\n\nwt_dd_summary(sensor = 'ARU', species = 'White-throated Sparrow', boundary = my_aoi)\n\n# Alberta bounding box\nabbox \u003c- read_sf(\"...shp\") |\u003e \n  filter(Province == \"Alberta\") |\u003e # A shapefile of Alberta\n  st_transform(crs = 4326) |\u003e \n  st_bbox()\n\nwt_dd_summary(sensor = \"ARU\", species = \"White-throated Sparrow\", boundary = abbox)\n```\n\n### Acoustic work flows\n\nDownload data and run and a single-season single-species occupancy analysis. Consult [APIs](https://abbiodiversity.github.io/wildrtrax/articles/apis.html) and Acoustic data wrangling for more information.\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\n# Login with your OAuth\nSys.setenv(WT_USERNAME = \"*****\", WT_PASSWORD = \"*****\")\n\n# Authenticate to WildTrax\nwt_auth()\n\n# Get a project id\nprojects \u003c- wt_get_projects(\"ARU\") |\u003e\n  filter(project == \"Ecosystem Health 2023\") |\u003e\n  pull(project_id) |\u003e\n  wt_download_report(sensor_id = \"ARU\", reports = \"main\")\n\n# Format to occupancy for OVEN\ndat.occu \u003c- wt_format_occupancy(data = raw_data, species=\"OVEN\", siteCovs=NULL)\n\n# Run the model\nunmarked::occu(~ 1 ~ 1, dat.occu)\n```\n\nConduct some pre-processing on various types of acoustic data. See more in [Acoustic pre-processing](https://abbiodiversity.github.io/wildrtrax/articles/acoustic-pre-processing.html).\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\n# Scan files and filter results\nmy_files \u003c- wt_audio_scanner(path = \".\", file_type = \"wav\", extra_cols = TRUE) |\u003e\n              dplyr::mutate(hour = as.numeric(format(recording_date_time, \"%H\"))) |\u003e\n              dplyr::filter(julian == 176, hour %in% c(4:8))\n              \n# Run acoustic indices and LDFCs\nwt_run_ap(x = my_files, output_dir = paste0(root, 'ap_outputs'), path_to_ap = '/where/you/store/AP')\n\nwt_glean_ap(x = my_files, input_dir = \".../ap_outputs\", purpose = \"biotic\", include_ldfcs = TRUE)\n```\n\nEvaluate the performance of BirdNET on a project, and search for false negatives missed by human taggers. See [Classifiers Tutorial](https://abbiodiversity.github.io/wildrtrax/articles/classifiers-tutorial.html) for more information.\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\n# OAuth logins only. Google OAuth2 will be supported soon.\nSys.setenv(WT_USERNAME = \"*****\", WT_PASSWORD = \"*****\")\n\n# Authenticate to WildTrax\nwt_auth()\n\nmy_reports \u003c- wt_download_report(project_id = 1144, sensor_id = \"ARU\", reports = c(\"main\", \"ai\"))\n                           \neval \u003c- wt_evaluate_classifier(data = my_reports, resolution = \"task\", remove_species = TRUE, thresholds = c(0.01,0.99))\n\ne1 \u003c- wt_classifier_threshold(eval) \n\n# Select the lowest threshold across classifiers and find additional species (false negatives)\nwt_additional_species(my_reports, remove_species = TRUE, threshold = min(e1$threshold), resolution=\"task\")\n```\n\n### Camera work flows\n\nThe ultimate pipeline for your camera data work flows. See [Camera data wrangling](https://abbiodiversity.github.io/wildrtrax/articles/camera-data-wrangling.html) for more information.\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\n# OAuth logins only. Google OAuth2 will be supported soon.\nSys.setenv(WT_USERNAME = \"*****\", WT_PASSWORD = \"*****\")\n\n# Authenticate to WildTrax\nwt_auth()\n\n# Get a camera project\nraw \u003c- wt_get_projects(\"CAM\") |\u003e\n  filter(project == \"ABMI Ecosystem Health 2014\") |\u003e\n  pull(project_id) |\u003e\n  wt_download_report(sensor_id = \"CAM\", reports = \"main\")\n\n# Get individual species detections using various thresholds and time ranges\nindividual_detections \u003c- wt_ind_detect(x = raw, threshold = 30, units = \"minutes\")\n```\n\n### Ultrasonic work flows\n\nFormat tags from [Kaleidoscope](https://www.wildlifeacoustics.com/products/kaleidoscope-pro?token=Sz_0cuFdrlAp3tVX2sJzcZanTHahEguB) for a WildTrax project. Download data from a project into an [NABAT](https://www.nabatmonitoring.org/) acceptable format.\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\ninput \u003c- \".../bat.csv\" # A Kaleidoscope output file\noutput \u003c- \".../bats\" # A folder to store the formatted csv\n\nwt_kaleidoscope_tags(input, output, freq_bump = T)\n\n## Authenticate to WildTrax, then upload the tags to a WildTrax project\nwt_auth()\n\n# Get a project id\nprojects \u003c- wt_get_projects(\"ARU\") |\u003e\n  filter(project == \"A bat project\") |\u003e # Enter your bat project name here\n  pull(project_id) |\u003e\n  wt_download_report(sensor_id = \"ARU\", reports = \"main\")\n```\n\n### Point count work flows\n\nDownload combined and formatted acoustic and point count data sets together.\n\n``` r\nlibrary(wildrtrax)\nlibrary(tidyverse)\n\n# An ARU project\nan_aru_project \u003c- wt_download_report(project_id = 620, sensor_id = 'ARU', reports = \"main\", )\n\n# An ARU project as point count format\naru_as_pc \u003c- wt_download_report(project_id = 620, sensor_id = 'PC', reports = \"main\", )\n```\n\n## Issues\n\nTo report bugs, request additional features, or get help using the package, please file an [issue](https://github.com/ABbiodiversity/wildrtrax/issues).\n\n## Contributors\n\nWe encourage ongoing contributions and collaborations to improve the package into the future. The [Alberta Biodiversity Monitoring Institute](https://abmi.ca) provides ongoing support, development and funding.\n\n## License\n\nThis R package is licensed under [MIT license](https://github.com/ABbiodiversity/wildrtrax/blob/master/LICENSE)©2025 [Alberta Biodiversity Monitoring Institute](https://abmi.ca).\n\n## Code of Conduct\n\nPlease note that `wildrtrax` is released with a [Contributor Code of Conduct](https://github.com/ABbiodiversity/wildRtrax?tab=coc-ov-file). By contributing to this project, you agree to abide by its terms.\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.5281/zenodo.13952335"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["camera-traps"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/47462","html_url":"https://ost.ecosyste.ms/projects/47462"}