{ "_id": "6a1ef9c6b401979e7341815a", "Package": "glatos", "Type": "Package", "Title": "A package for the Great Lakes Acoustic Telemetry Observation\nSystem", "Description": "Functions useful to members of the Great Lakes Acoustic\nTelemetry Observation System https://glatos.org; many more\nbroadly relevant to simulating, processing, analysing, and\nvisualizing acoustic telemetry data.", "Version": "0.9.8", "Date": "2026-05-18", "URL": "https://github.com/ocean-tracking-network/glatos", "BugReports": "https://github.com/ocean-tracking-network/glatos/issues", "Authors@R": "c(\nperson(\"Christopher\", \"Holbrook\", email = \"cholbrook@glfc.org\",\nrole = c(\"cre\", \"aut\")),\nperson(\"Todd\", \"Hayden\", role = \"aut\"),\nperson(\"Thomas\", \"Binder\", role = \"aut\"),\nperson(\"Jon\", \"Pye\", role = \"aut\"),\nperson(\"Mike\", \"O'Brien\", role = \"ctb\"),\nperson(\"Alex\", \"Nunes\", role = \"ctb\"),\nperson(\"Benjamin\", \"Hlina\", role = \"ctb\"),\nperson(\"Angela\", \"Dini\", role = \"ctb\"),\nperson(\"Ryan\", \"Gosse\", role = \"ctb\"))", "License": "GPL-2", "LazyLoad": "yes", "LazyData": "true", "VignetteBuilder": "knitr", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev\nlibglpk-dev libavfilter-dev libxml2-dev libssl-dev libproj-dev\nlibsqlite3-dev libudunits2-dev", "Repository": "https://benjaminhlina.r-universe.dev", "Date/Publication": "2026-05-18 20:48:08 UTC", "RemoteUrl": "https://github.com/ocean-tracking-network/glatos", "RemoteRef": "dev", "RemoteSha": "a9b2a3b66c5e7a7f1e737ad97b245bdb81a7357e", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 21:24:06 UTC", "User": "root" }, "Author": "Christopher Holbrook [cre, aut],\nTodd Hayden [aut],\nThomas Binder [aut],\nJon Pye [aut],\nMike O'Brien [ctb],\nAlex Nunes [ctb],\nBenjamin Hlina [ctb],\nAngela Dini [ctb],\nRyan Gosse [ctb]", "Maintainer": "Christopher Holbrook ", "MD5sum": "03586861e332c16586d7de45d8f491d3", "_user": "benjaminhlina", "_type": "src", "_file": "glatos_0.9.8.tar.gz", "_fileid": "2347db8137092a1b9d30f18748bba9e3baa06b2653984535d1aa8e0e06cf042d", "_filesize": 19192283, "_sha256": "2347db8137092a1b9d30f18748bba9e3baa06b2653984535d1aa8e0e06cf042d", "_created": "2026-05-18T21:24:06.000Z", "_published": "2026-06-02T15:41:58.197Z", "_distro": "noble", "_jobs": [ { "job": 79110881672, "time": 275, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "ERROR", "artifact": "7069543964" }, { "job": 79110882047, "time": 262, "config": "linux-release-x86_64", "r": "4.6.0", "check": "ERROR", "artifact": "7069539872" }, { "job": 79110882035, "time": 195, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "WARNING", "artifact": "7069519938" }, { "job": 79110881469, "time": 236, "config": "macos-release-arm64", "r": "4.6.0", "check": "WARNING", "artifact": "7069531253" }, { "job": 79110881059, "time": 271, "config": 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"cholbrook@glfc.org", "login": "chrisholbrook", "description": "", "uuid": 9382173 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "av", "role": "Imports" }, { "package": "data.table", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "geodist", "role": "Imports" }, { "package": "gdistance", "role": "Imports" }, { "package": "jsonlite", "role": "Imports" }, { "package": "lubridate", "role": "Imports" }, { "package": "nanoparquet", "role": "Imports" }, { "package": "plotrix", "role": "Imports" }, { "package": "raster", "role": "Imports" }, { "package": "readxl", "role": "Imports" }, { "package": "sf", "role": "Imports" }, { "package": "sp", "role": "Imports" }, { "package": "zip", "role": "Imports" }, { "package": "vdiffr", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "gifski", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "mapview", "role": "Suggests" }, { "package": "methods", "role": "Suggests" }, { "package": "png", "role": "Suggests" }, { "package": "purrr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "terra", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "tint", "role": "Suggests" } ], "_owner": "ocean-tracking-network", "_selfowned": false, "_usedby": 1, "_updates": [ { "week": "2025-37", "n": 5 }, { "week": "2025-39", "n": 2 }, { "week": "2026-04", "n": 2 }, { "week": "2026-07", "n": 10 }, { "week": "2026-13", "n": 3 }, { "week": "2026-14", "n": 2 }, { "week": "2026-20", "n": 2 }, { "week": "2026-21", "n": 1 } ], "_tags": [ { "name": "v0.8.1", "date": "2025-09-09" }, { "name": "v0.9.0", "date": "2026-01-20" }, { "name": "v0.9.2", "date": "2026-02-11" }, { "name": "v0.9.3", "date": "2026-02-12" }, { "name": "v0.9.4", "date": "2026-02-13" }, { "name": "v0.9.5", "date": "2026-03-25" }, { "name": 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Ontario and Huron." }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/glatos" }, "_devurl": "https://github.com/ocean-tracking-network/glatos", "_searchresults": 152, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/glatos.html", "extra/NEWS.html", "extra/NEWS.txt", "manual.pdf" ], "_cranurl": false, "_exports": [ "abacus_plot", "adjust_playback_time", "as_glatos_animals", "as_glatos_detections", "as_glatos_receivers", "calc_collision_prob", "cast", "check_dependencies", "check_vdat", "check_vue", "convert_glatos_to_att", "convert_otn_erddap_to_att", "convert_otn_to_att", "crw", "crw_in_polygon", "detect_transmissions", "detection_bubble_plot", "detection_events", "detection_range_model", "false_detections", "format_POSIXt", "get_local_vdat_template", "get_local_vdat_version", "get_local_vue_version", "glatos_animals", "glatos_check_col_classes", "glatos_check_col_names", "glatos_detections", "glatos_receivers", "identify_workbook_version", "install_ffmpeg", "interpolate_path", "is_glatos_animals", "is_glatos_detections", "is_glatos_receivers", "jarasterize", "kml_to_csv", "kml_workbook", "make_frames", "make_transition", "make_video", "make_video_ffmpeg", "min_lag", "point_offset", "position_heat_map", "prepare_deploy_sheet", "prepare_tag_sheet", "read_glatos_detections", "read_glatos_receivers", "read_glatos_workbook", "read_otn_deployments", "read_otn_detections", "read_vdat_csv", "read_vemco_tag_specs", "read_vue_detection_csv", "read_vue_event_csv", "read_workbook_project", "real_sensor_values", "receiver_line_det_sim", "REI", "residence_index", "rotate_points", "scale_meters_to_degrees", "summarize_detections", "transmit_along_path", "validate_glatos_animals", "validate_glatos_detections", "validate_glatos_receivers", "vdat_convert", "vector_heading", "vrl2csv", "vue_convert", "write_vdat_csv" ], "_datasets": [ { "name": "flynn_island_polygon", "title": "An sf POLYGON object with coastline of Flynn Island", "object": "flynn_island_polygon", "class": [ "sf", "data.frame" ], "fields": [ "value", "geometry" ], "rows": 1, "table": false, "tojson": true }, { "name": "great_lakes_polygon", "title": "An sf POLYGON object with Great Lakes coastline", "object": "great_lakes_polygon", "class": [ "sf", "data.frame" ], "fields": [ "id", "geometry" ], "rows": 1, "table": false, "tojson": true }, { "name": "greatLakesPoly", "title": "Deprecated A SpatialPolygonDataFrame with Great Lakes coastline and some major tributaries.", "object": "greatLakesPoly", "class": [ "SpatialPolygonsDataFrame" ], "fields": [], "table": false, "tojson": false }, { "name": "greatLakesTrLayer", "title": "A 'TransitionLayer' of the Great Lakes that only prevents transition over land", "object": "greatLakesTrLayer", "class": [ "TransitionLayer" ], "fields": [], "table": false, "tojson": false }, { "name": "higgins_lake_polygon", "title": "An sf POLYGON object with coastline of Higgins Lake", "object": "higgins_lake_polygon", "class": [ "sf", "data.frame" ], "fields": [ "value", "geometry" ], "rows": 1, "table": false, "tojson": true }, { "name": "lamprey_tracks", "title": "Sea Lamprey positions from Lake George, St. Marys River, 2012", "object": "lamprey_tracks", "class": [ "data.frame" ], "fields": [ "DETECTEDID", "DATETIME", "X", "Y", "D", "LAT", "LON", "n", "HPE", "HPEm", "TEMP", "DEPTH", "ACCEL", "DRX" ], "rows": 21043, "table": true, "tojson": true }, { "name": "range_detection", "title": "Detection range data set", "object": "range_detection", "class": [ "glatos_detections", "data.frame" ], "fields": [ "animal_id", "detection_timestamp_utc", "glatos_array", "station_no", "transmitter_codespace", "transmitter_id", "sensor_value", "sensor_unit", "deploy_lat", "deploy_long", "receiver_sn", "tag_type", "tag_model", "tag_serial_number", "common_name_e", "capture_location", "length", "weight", "sex", "release_group", "release_location", "release_latitude", "release_longitude", "utc_release_date_time", "glatos_project_transmitter", "glatos_project_receiver", "glatos_tag_recovered", "glatos_caught_date", "station", "min_lag" ], "rows": 58309, "table": true, "tojson": true }, { "name": "sample_detection_efficiency", "title": "Detection Efficiency data set", "object": "sample_detection_efficiency", "class": [ "spec_tbl_df", "tbl_df", "tbl", "data.frame" ], "fields": [ "distance_m", "avg_percent", "std_dev", "avg_percent_d", "intercept" ], "rows": 7, "table": true, "tojson": true }, { "name": "vdat_csv_schema", "title": "A schema for Innovasea Fathom (VDAT) CSV files", "object": "vdat_csv_schema", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "sub-.vdat_list", "title": "Subset method for vdat_list that retains attributes", "topics": [ "[.vdat_list" ] }, { "page": "abacus_plot", "title": "Plot detection locations of acoustic transmitters over time", "topics": [ "abacus_plot" ] }, { "page": "adjust_playback_time", "title": "Modify playback time of video", "topics": [ "adjust_playback_time" ] }, { "page": "aggregate_total_no_overlap", "title": "The function below aggregates timedelta of first_detection and last_detection, excluding overlap between detections. Any overlap between two detections is converted to a new detection using the earlier first_detection and the latest last_detection. If the first_detection and last_detection are the same, a timedelta of one second is assumed.", "topics": [ "aggregate_total_no_overlap" ] }, { "page": "aggregate_total_with_overlap", "title": "The function below aggregates timedelta of first_detection and last_detection of each detection into a final timedelta then returns a float of the number of days. If the first_detection and last_detection are the same, a timedelta of one second is assumed.", "topics": [ "aggregate_total_with_overlap" ] }, { "page": "calc_collision_prob", "title": "Estimate probability of collision for telemetry transmitters", "topics": [ "calc_collision_prob" ] }, { "page": "cast", "title": "Cast a list of scalars to a new class", "topics": [ "cast" ] }, { "page": "check_vdat", "title": "Check path to Innovasea program 'vdat.exe'", "topics": [ "check_vdat" ] }, { "page": "check_vue", "title": "Check path to Innovasea program VUE.exe", "topics": [ "check_vue" ] }, { "page": "convert_glatos_to_att", "title": "Convert detections and receiver metadata to a format that ATT accepts.", "topics": [ "convert_glatos_to_att" ] }, { "page": "convert_otn_erddap_to_att", "title": "Convert detections, transmitter, receiver, and animal metadata to a format that ATT accepts.", "topics": [ "convert_otn_erddap_to_att" ] }, { "page": "convert_otn_to_att", "title": "Convert detections, tagging metadata, and deployment metadata to a format that ATT accepts.", "topics": [ "convert_otn_to_att" ] }, { "page": "crw", "title": "Simulate a correlated random walk", "topics": [ "crw" ] }, { "page": "crw_in_polygon", "title": "Simulate a correlated random walk inside a polygon", "topics": [ "crw_in_polygon" ] }, { "page": "detect_transmissions", "title": "Simulate detection of transmitter signals in a receiver network", "topics": [ "detect_transmissions" ] }, { "page": "detection_bubble_plot", "title": "Make bubble plots showing the number of fish detected across a defined set of receiver locations.", "topics": [ "detection_bubble_plot" ] }, { "page": "detection_events", "title": "Classify discrete events in detection data", "topics": [ "detection_events" ] }, { "page": "detection_range_model", "title": "Detection Range Probability Model", "topics": [ "detection_range_model" ] }, { "page": "false_detections", "title": "False detection filter", "topics": [ "false_detections" ] }, { "page": "flynn_island_polygon", "title": "An sf POLYGON object with coastline of Flynn Island", "topics": [ "flynn_island_polygon" ] }, { "page": "flynn_island_transition", "title": "A transition object for Flynn Island for testing make_transition", "topics": [ "flynn_island_transition" ] }, { "page": "format_POSIXt", "title": "Round timestamp by fractional second and coerce to character", "topics": [ "format_POSIXt" ] }, { "page": "get_days", "title": "Determines which calculation method to use for the residency index.", "topics": [ "get_days" ] }, { "page": "get_local_vdat_template", "title": "Get schema from local installation of Innovasea program 'vdat.exe'", "topics": [ "get_local_vdat_template" ] }, { "page": "get_local_vdat_version", "title": "Get version of local installation of Innovasea program vdat.exe", "topics": [ "get_local_vdat_version" ] }, { "page": "get_local_vue_version", "title": "Get version of local installation of Innovasea program VUE.exe", "topics": [ "get_local_vue_version" ] }, { "page": "glatos", "title": "glatos: An R package for the Great Lakes Acoustic Telemetry Observation System: glatos is an R package with functions useful to members of the Great Lakes Acoustic Telemetry Observation System https://glatos.org. Functions may be generally useful for processing, analyzing, simulating, and visualizing acoustic telemetry data, but are not strictly limited to acoustic telemetry applications. Package status: glatos is hosted by the Ocean Tracking Network on github. • For recent changes, see NEWS. • To report a bug, ask a question, or propose something new, submit an Issue or email the maintainer (Chris Holbrook): cholbrook@glfc.org. Installation: To install the latest release (0.9.8 'pretty-fragrant-rye'): library(remotes) # for install_github install_github('ocean-tracking-network/glatos', build_vignettes = TRUE) To install the development version, an earlier version, or to see frequently asked questions about installation, see https://github.com/ocean-tracking-network/glatos/wiki/installation-instructions. Contents: Data loading and processing: 1. 'read_glatos_detections' and 'read_otn_detections' provide fast data loading from standard GLATOS and OTN data files to a single structure that is compatible with other glatos functions. 2. 'read_glatos_receivers' and 'read_otn_deployments' reads receiver location histories from standard GLATOS and OTN data files to a single structure that is compatible with other glatos functions. 3. 'read_glatos_workbook' reads project-specific receiver history and fish taggging and release data from a standard glatos workbook file. 4. 'read_vemco_tag_specs' reads transmitter (tag) specifications and operating schedule. 5. 'real_sensor_values' converts 'raw' transmitter sensor (e.g., depth, temperature) to 'real'-scale values (e.g., depth in meters) using transmitter specification data (e.g., from read_vemco_tag_specs). 6. 'prepare_tag_sheet' and 'prepare_deploy_sheet' load OTN metadata sheets for Tagging and Deployment of Receivers and formats them for converting to ATT Data. 7. 'vue_convert' and 'vdat_convert' extracts data from proprietary receiver files (.vrl, .vdat) using Innovasea's VUE and VDAT software (packaged with Fathom Connect software). 8. 'read_vdat_csv' reads data from a CSV file produced by Innovasea's Fathom Connect or VDAT software (or with 'vdat_convert()'). Data from an \"interleaved\" (not \"split\") Fathom CSV format are read into R as a 'vdat_list' object. 9. 'read_vue_detection_csv', and 'read_vue_event_csv' read data from a CSV file exported from Innovasea's VUE software. Filtering and summarizing: 1. 'min_lag' facilitates identification and removal of false positive detections by calculating the minimum time interval (min_lag) between successive detections. 2. 'false_detections' removes potential false positive detections using \"short interval\" criteria (see _min_lag_). 3. 'detection_events' distills detection data down to a much smaller number of discrete detection events, defined as a change in location or time gap that exceeds a threshold. 4. 'summarize_detections' calculates number of fish detected, number of detections, first and last detection timestamps, and/or mean location of receivers or groups, depending on specific type of summary requested. 5. 'residence_index' calculates the relative proportion of time spent at each location. 6. 'REI' calculates the relative activity at each receiver based on number of unique species and individual animals. 7. 'detection_range_model' for estimating detection range at which a certain detection efficiency is expected, using output from Innovasea's range testing software. Simulation functions for system design and evaluation: 1. 'calc_collision_prob' estimates the probability of collisions for pulse-position-modulation type co-located telemetry transmitters. This is useful for determining the number of fish to release or tag specifications (e.g., delay). 2. 'receiver_line_det_sim' simulates detection of acoustic-tagged fish crossing a receiver line (or single receiver). This is useful for determining optimal spacing of receviers in a line and tag specifications (e.g., delay). 3. 'crw_in_polygon', 'transmit_along_path', and 'detect_transmissions' individually simulate random fish movement paths within a water body (_crw_in_polygon_: a random walk in a polygon), tag signal transmissions along those paths (_transmit_along_path_: time series and locations of transmissions based on tag specs), and detection of those transmittions by receivers in a user-defined receiver network (_detect_transmissions_: time series and locations of detections based on detection range curve). Collectively, these functions can be used to explore, compare, and contrast theoretical performance of a wide range of transmitter and receiver network designs. Visualization and data exploration: 1. 'abacus_plot' is useful for exploring movement patterns of individual tagged animals through time. 2. 'detection_bubble_plot' is useful for exploring distribution of tagged individuals among receivers. 3. 'interpolate_path', 'make_frames', and 'make_video' Interpolate spatio-temporal movements, between detections, create video frames, and stitch frames together to create animated video file. 4. 'adjust_playback_time' modify playback speed of videos and optionally convert between video file formats. Data Exporting: 1. 'convert_glatos_to_att' converts the glatos detection and receiver objects to a format supported by VTrack/ATT. 2. 'convert_otn_erddap_to_att' converts the OTN detection and ERDDAP csvs of OTN animals, tags and stations to a format supported by VTrack/ATT. 3. 'convert_otn_to_att' converts the OTN detections and metadata sheets to the ATT format. Also accepts deployment metadata from the OTN website in CSV format.", "topics": [ "glatos-package", "glatos" ] }, { "page": "glatos_animals", "title": "Construct, check, and validate a glatos_animals object", "topics": [ "as_glatos_animals", "glatos_animals", "is_glatos_animals", "validate_glatos_animals" ] }, { "page": "glatos_check_col_names", "title": "Check column names and classes of a list or data.frame against requirements", "topics": [ "glatos_check_col_classes", "glatos_check_col_names" ] }, { "page": "glatos_detections", "title": "Construct, check, and validate a glatos_detections object", "topics": [ "as_glatos_detections", "glatos_detections", "is_glatos_detections", "validate_glatos_detections" ] }, { "page": "glatos_receivers", "title": "Construct, check, and validate a glatos_receivers object", "topics": [ "as_glatos_receivers", "glatos_receivers", "is_glatos_receivers", "validate_glatos_receivers" ] }, { "page": "glatos-defunct", "title": "Defunct functions in glatos", "topics": [ "check_dependencies", "glatos-defunct", "install_ffmpeg", "make_video_ffmpeg" ] }, { "page": "glatos-deprecated", "title": "Deprecated functions in package 'glatos'.", "topics": [ "glatos-deprecated", "vrl2csv" ] }, { "page": "great_lakes_polygon", "title": "An sf POLYGON object with Great Lakes coastline", "topics": [ "great_lakes_polygon" ] }, { "page": "greatLakesPoly", "title": "Deprecated A SpatialPolygonDataFrame with Great Lakes coastline and some major tributaries.", "topics": [ "greatLakesPoly" ] }, { "page": "greatLakesTrLayer", "title": "A 'TransitionLayer' of the Great Lakes that only prevents transition over land", "topics": [ "greatLakesTrLayer" ] }, { "page": "higgins_lake_polygon", "title": "An sf POLYGON object with coastline of Higgins Lake", "topics": [ "higgins_lake_polygon" ] }, { "page": "higgins_lake_transition", "title": "A transition object for Higgins Lake for testing make_transition", "topics": [ "higgins_lake_transition" ] }, { "page": "identify_workbook_version", "title": "Identify and check GLATOS workbook file version", "topics": [ "identify_workbook_version" ] }, { "page": "interpolate_path", "title": "Interpolate new positions within a spatiotemporal path data", "topics": [ "interpolate_path" ] }, { "page": "interval_count", "title": "The function below takes a detection events data frame and determines the number of time bins in which detections were observed and returns the cumulative time covered by all bins, in days. Interval (bin) size is determined by the 'time_interval_size' argument.", "topics": [ "interval_count" ] }, { "page": "jarasterize", "title": "Just another rasterizer", "topics": [ "jarasterize" ] }, { "page": "kml_to_csv", "title": "KML To CSV Conversion", "topics": [ "kml_to_csv" ] }, { "page": "kml_workbook", "title": "Make a KML or KMZ file of receiver and animal release locations", "topics": [ "kml_workbook" ] }, { "page": "lamprey_tracks", "title": "Sea Lamprey positions from Lake George, St. Marys River, 2012", "topics": [ "lamprey_tracks" ] }, { "page": "make_frames", "title": "Create an animated video of spatiotemporal path data", "topics": [ "make_frames" ] }, { "page": "make_transition", "title": "Create transition layer from spatial object.", "topics": [ "make_transition" ] }, { "page": "make_video", "title": "Create video from sequence of still images", "topics": [ "make_video" ] }, { "page": "min_lag", "title": "Calculate 'min_lag' for identifying potential false positive detections", "topics": [ "min_lag" ] }, { "page": "otn_aat_animals", "title": "Example animal data from the OTN ERDDAP", "topics": [ "otn_aat_animals" ] }, { "page": "otn_aat_receivers", "title": "Example station data from the OTN ERDDAP", "topics": [ "otn_aat_receivers" ] }, { "page": "otn_aat_tag_releases", "title": "Example tag release data from the OTN ERDDAP", "topics": [ "otn_aat_tag_releases" ] }, { "page": "point_offset", "title": "Identify new location based on distance and bearing from another", "topics": [ "point_offset" ] }, { "page": "position_heat_map", "title": "Position Heat Maps", "topics": [ "position_heat_map" ] }, { "page": "prepare_deploy_sheet", "title": "Loads the OTN receiver deployment metadata sheet to prepare it for use in 'convert_otn_to_att'", "topics": [ "prepare_deploy_sheet" ] }, { "page": "prepare_tag_sheet", "title": "Loads the OTN tagging metadata sheet to prepare it for use in 'convert_otn_to_att'", "topics": [ "prepare_tag_sheet" ] }, { "page": "range_detection", "title": "Detection range data set", "topics": [ "range_detection" ] }, { "page": "raw_lamprey_workbook", "title": "Raw GLATOS Workbook from St. Marys River Sea Lamprey project", "topics": [ "raw_lamprey_workbook" ] }, { "page": "raw_walleye_detections", "title": "Zipped GLATOS detection file from Huron Erie Corridor Walleye project", "topics": [ "raw_walleye_detections" ] }, { "page": "read_glatos_detections", "title": "Read data from a GLATOS detection file", "topics": [ "read_glatos_detections" ] }, { "page": "read_glatos_receivers", "title": "Read data from a GLATOS receiver location file", "topics": [ "read_glatos_receivers" ] }, { "page": "read_glatos_workbook", "title": "Read data from a GLATOS project workbook", "topics": [ "read_glatos_workbook" ] }, { "page": "read_otn_deployments", "title": "Read data from a OTN deployment file", "topics": [ "read_otn_deployments" ] }, { "page": "read_otn_detections", "title": "Read data from a OTN detection file", "topics": [ "read_otn_detections" ] }, { "page": "read_vdat_csv", "title": "Read data from an Innovasea Fathom VDAT CSV file", "topics": [ "read_vdat_csv" ] }, { "page": "read_vemco_tag_specs", "title": "Read telemetry transmitter (tag) specification data from a Vemco file", "topics": [ "read_vemco_tag_specs" ] }, { "page": "read_vue_detection_csv", "title": "Read detection data exported from Innovasea VUE software", "topics": [ "read_vue_detection_csv" ] }, { "page": "read_vue_event_csv", "title": "Read receiver event data exported from Innovasea VUE software", "topics": [ "read_vue_event_csv" ] }, { "page": "read_workbook_project", "title": "Read Project sheet from GLATOS workbook file", "topics": [ "read_workbook_project" ] }, { "page": "real_sensor_values", "title": "Add 'real'-scale sensor values to glatos detetections", "topics": [ "real_sensor_values" ] }, { "page": "receiver_line_det_sim", "title": "Simulate detection of acoustic-tagged fish crossing a receiver line", "topics": [ "receiver_line_det_sim" ] }, { "page": "REI", "title": "Calculates a returns a list of each station and the REI (defined here)", "topics": [ "REI" ] }, { "page": "residence_index", "title": "Generate the residence index from a set of detections", "topics": [ "residence_index" ] }, { "page": "rotate_points", "title": "Rotate points in a 2-d plane", "topics": [ "rotate_points" ] }, { "page": "sample_detection_efficiency", "title": "Detection Efficiency data set", "topics": [ "sample_detection_efficiency" ] }, { "page": "scale_meters_to_degrees", "title": "Get degree-scale equivalent of meter-scale distance on a spatial object", "topics": [ "scale_meters_to_degrees" ] }, { "page": "shoreline", "title": "zipped polygon shapefile of Great Lakes", "topics": [ "shoreline" ] }, { "page": "summarize_detections", "title": "Summarize detections by animal, location, or both", "topics": [ "summarize_detections" ] }, { "page": "total_diff_days", "title": "The function below determines the total days difference.", "topics": [ "total_diff_days" ] }, { "page": "transmit_along_path", "title": "Simulate telemetry transmitter signals along a path", "topics": [ "transmit_along_path" ] }, { "page": "vdat_convert", "title": "Convert an Innovasea VRL or VDAT file to a Fathom CSV file", "topics": [ "vdat_convert" ] }, { "page": "vdat_csv_schema", "title": "A schema for Innovasea Fathom (VDAT) CSV files", "topics": [ "vdat_csv_schema" ] }, { "page": "vector_heading", "title": "Calculate direction (heading) of a vector (in degrees)", "topics": [ "vector_heading" ] }, { "page": "video-images", "title": "Video frames of walleye movements in Lake Huron", "topics": [ "video-images" ] }, { "page": "vue_convert", "title": "Convert an Innovasea Vemco VRL file to a VUE CSV file", "topics": [ "vue_convert" ] }, { "page": "write_vdat_csv", "title": "Write a vdat_list object to disk in Innovasea Fathom VDAT CSV format", "topics": [ "write_vdat_csv" ] } ], "_rundeps": [ "av", "cellranger", "class", "classInt", "cli", "cpp11", "crayon", "data.table", "DBI", "dplyr", "e1071", "gdistance", "generics", "geodist", "glue", "hms", "igraph", "jsonlite", "KernSmooth", "lattice", "lifecycle", "lubridate", "magrittr", "MASS", "Matrix", "nanoparquet", "pillar", "pkgconfig", "plotrix", "prettyunits", "progress", "proxy", "R6", "raster", "Rcpp", "readxl", "rematch", "rlang", "s2", "sf", "sp", "terra", "tibble", "tidyselect", "timechange", "units", "utf8", "vctrs", "withr", "wk", "zip" ], "_score": 5.630240691402541, "_indexed": false, "_nocasepkg": "glatos", "_universes": [ "benjaminhlina" ], "_indexurl": "https://ocean-tracking-network.r-universe.dev/glatos", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.9.8", "date": "2026-05-18T21:27:07.000Z", "distro": "noble", "commit": "a9b2a3b66c5e7a7f1e737ad97b245bdb81a7357e", "fileid": "34b00cb55b9ac049dad63926b7fe06d520f4e8ca1cff285d67dd8fe14bdcc639", "status": "failure", "check": "ERROR", "buildurl": 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