Package 'otndo' reference manual

Title:	Understand your OTN data
Description:	This package provides functions to summarize the various type of OTN-style data.
Authors:	Michael O'Brien [aut, cre]
Maintainer:	Michael O'Brien <[email protected]>
License:	CC BY 4.0
Version:	0.2.3
Built:	2024-09-09 05:43:11 UTC
Source:	https://github.com/mhpob/otndo

Create a Gantt-like chart of receiver deployments and recoveries

Description

Create a Gantt-like chart of receiver deployments and recoveries

Usage

deployment_gantt(deployment)
deployment_gantt(deployment)

Arguments

deployment

Cleaned deployment metadata sheet(s). Assumes it was cleaned with the internal otndo:::clean_otn_deployment function, read in, and converted to a data.table.

Examples

## Not run: 
# Download a deployment metadata file
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "data-and-metadata/2018/pbsm-instrument-deployment-short-form-2018.xls/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  mode = "wb"
)

# Use internal function to clean
deployment_filepath <- otndo:::write_to_tempdir(
  type = "deployment",
  files = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  temp_dir = td
)

# Make the Gantt chart
deployment_gantt(
  data.table::fread(deployment_filepath)
)

## End(Not run)

## Not run: 
# Download a deployment metadata file
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "data-and-metadata/2018/pbsm-instrument-deployment-short-form-2018.xls/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  mode = "wb"
)

# Use internal function to clean
deployment_filepath <- otndo:::write_to_tempdir(
  type = "deployment",
  files = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  temp_dir = td
)

# Make the Gantt chart
deployment_gantt(
  data.table::fread(deployment_filepath)
)

## End(Not run)

Create summary reports of receiver project data from the OTN data push

Description

Create summary reports of receiver project data from the OTN data push

Usage

make_receiver_push_summary(
  qualified = NULL,
  unqualified = NULL,
  update_push_log = FALSE,
  deployment = NULL,
  out_dir = getwd(),
  since = NULL,
  rmd = FALSE
)
make_receiver_push_summary(
  qualified = NULL,
  unqualified = NULL,
  update_push_log = FALSE,
  deployment = NULL,
  out_dir = getwd(),
  since = NULL,
  rmd = FALSE
)

Arguments

`qualified`, `unqualified`	Default is NULL: a character vector of file paths of your qualified/unqualified detections. These can be CSVs or zipped folders.
`update_push_log`	Do you wish to use an updated push log? Default is FALSE, but switch to TRUE if you haven't updated this package since the push occurred.
`deployment`	File path of user-supplied master OTN receiver deployment metadata.
`out_dir`	Defaults to working directory. In which directory would you like to save the report?
`since`	Date in YYYY-MM-DD format. Summarizes what's new since the provided date.
`rmd`	Logical. Compile via RMarkdown rather than Quarto?

Push log

To keep track of when ACT data pushes occur, a log is kept on the package's GitHub page. This is automatically downloaded every time you download or update the package, but you can avoid re-downloading the package by changing update_push_log to TRUE.

You can get similar behavior by providing a date to the since argument.

Output

This function creates an HTML report that can be viewed in your web browser.

Examples

## Not run: 
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "data-and-metadata/archived-records/2018/",
    "pbsm-instrument-deployment-short-form-2018.xls/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  mode = "wb"
)


download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_unqualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_unqualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_unqualified_detections_2018.zip"),
  exdir = td
)

qualified_files <- file.path(td, "pbsm_qualified_detections_2018.csv")
unqualified_files <- file.path(td, "pbsm_unqualified_detections_2018.csv")
deployment_files <- file.path(td, "pbsm-instrument-deployment-short-form-2018.xls")


make_receiver_push_summary(
  qualified = qualified_files,
  unqualified = unqualified_files,
  deployment = deployment_files,
  since = "2018-11-01"
)

## End(Not run)
## Not run: 
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "data-and-metadata/archived-records/2018/",
    "pbsm-instrument-deployment-short-form-2018.xls/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm-instrument-deployment-short-form-2018.xls"),
  mode = "wb"
)


download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_unqualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_unqualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_unqualified_detections_2018.zip"),
  exdir = td
)

qualified_files <- file.path(td, "pbsm_qualified_detections_2018.csv")
unqualified_files <- file.path(td, "pbsm_unqualified_detections_2018.csv")
deployment_files <- file.path(td, "pbsm-instrument-deployment-short-form-2018.xls")


make_receiver_push_summary(
  qualified = qualified_files,
  unqualified = unqualified_files,
  deployment = deployment_files,
  since = "2018-11-01"
)

## End(Not run)

Create summary reports of receiver project data from the OTN data push

Description

Create summary reports of receiver project data from the OTN data push

Usage

make_tag_push_summary(
  matched = NULL,
  update_push_log = FALSE,
  since = NULL,
  sensor_decoding = NULL,
  out_dir = getwd(),
  rmd = FALSE
)
make_tag_push_summary(
  matched = NULL,
  update_push_log = FALSE,
  since = NULL,
  sensor_decoding = NULL,
  out_dir = getwd(),
  rmd = FALSE
)

Arguments

`matched`	This argument also accepts a character vector of file paths of your matched detections. These can be CSVs or zipped folders.
`update_push_log`	Do you wish to use an updated push log? Default is FALSE, but switch to TRUE if you haven't updated this package since the push occurred.
`since`	date in YYYY-MM-DD format. Provides a summary of detections that were matched/edited since that date.
`sensor_decoding`	Not yet implemented. Will be a place to provide information to decode and summarize sensor data,
`out_dir`	Defaults to working directory. In which directory would you like to save the report?
`rmd`	Logical. Compile via RMarkdown rather than Quarto?

Examples

## Not run: 
# The code below downloads some matched detections from OTN, then calls the function.
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

# Provide the detection file(s) to the \code{matched} argument, with an
# optional date to the \code{since} argument to summarize what was new since
# that date.
make_tag_push_summary(
  matched = file.path(
    td,
    "pbsm_matched_detections_2018.csv"
  ),
  since = "2018-11-01"
)

## End(Not run)
## Not run: 
# The code below downloads some matched detections from OTN, then calls the function.
td <- file.path(tempdir(), "matos_test_files")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

# Provide the detection file(s) to the \code{matched} argument, with an
# optional date to the \code{since} argument to summarize what was new since
# that date.
make_tag_push_summary(
  matched = file.path(
    td,
    "pbsm_matched_detections_2018.csv"
  ),
  since = "2018-11-01"
)

## End(Not run)

Plot the geographic extent of OTN projects

Description

Plot the geographic extent of OTN projects

Usage

match_map(otn_tables)
match_map(otn_tables)

Arguments

otn_tables

A list containing OTN's otn_resources_metadata_points GeoServer layer. Usually created using otn_query.

Examples

match_map(
  otn_query("MDWEA")
)

match_map(
  otn_query("MDWEA")
)

Create a reactable table of matched detections

Description

Create a reactable table of matched detections

Usage

match_table(extract, type = c("tag", "receiver"))
match_table(extract, type = c("tag", "receiver"))

Arguments

`extract`	matched (transmitter) or qualified (receiver) OTN detections
`type`	Tag or receiver data? Takes values of "tag" and "receiver"; defaults to "tag".

Examples

## Not run: 
# Receiver
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

qualified_dets <- data.table::fread(
  file.path(td, "pbsm_qualified_detections_2018.csv")
)

match_table(
  extract = qualified_dets,
  type = "receiver"
)

# Transmitters
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)

match_table(
  extract = matched_dets,
  type = "tag"
)

## End(Not run)

## Not run: 
# Receiver
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

qualified_dets <- data.table::fread(
  file.path(td, "pbsm_qualified_detections_2018.csv")
)

match_table(
  extract = qualified_dets,
  type = "receiver"
)

# Transmitters
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)

match_table(
  extract = matched_dets,
  type = "tag"
)

## End(Not run)

Create an abacus plot of matched detections

Description

Create an abacus plot of matched detections

Usage

matched_abacus(temp_dist, release)
matched_abacus(temp_dist, release)

Arguments

`temp_dist`	Data from the output of `temporal_distribution()`
`release`	Data frame of release times/locations; a subset of the matched detections data

Examples

## Not run: 
# Get a detection file
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)


# Run temporal_distribution
temporal <- temporal_distribution(matched_dets, "tag")

# Run matched_abacus
matched_abacus(temporal$data, matched_dets[receiver == "release"])

## End(Not run)

## Not run: 
# Get a detection file
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)


# Run temporal_distribution
temporal <- temporal_distribution(matched_dets, "tag")

# Run matched_abacus
matched_abacus(temporal$data, matched_dets[receiver == "release"])

## End(Not run)

Query the OTN Geoserver

Description

Query the OTN Geoserver

Usage

otn_query(projects)
otn_query(projects)

Arguments

projects

Character vector of OTN project codes for which you'd like project metadata. Prepended networks can be provided, but are not necessary.

Value

list of the "otn_resources_metadata_points" and "project_metadata" for the given projects

Examples

otn_query(c("EST", "FACT.SCDNRDFP", "ACT.MDBSB", "MDBSB"))

otn_query(c("EST", "FACT.SCDNRDFP", "ACT.MDBSB", "MDBSB"))

Prepare the detection match summary data

Description

Prepare the detection match summary data

Usage

prep_match_table(extract, type = c("tag", "receiver"))
prep_match_table(extract, type = c("tag", "receiver"))

Arguments

`extract`	matched (transmitter) or qualified (receiver) OTN detections
`type`	Tag or receiver data? Takes values of "tag" and "receiver"; defaults to "tag".

Summarize OTN extract data by station and convert to a spatial object

Description

Summarize OTN extract data by station and convert to a spatial object

Usage

prep_station_spatial(extract, type = c("tag", "receiver"))
prep_station_spatial(extract, type = c("tag", "receiver"))

Arguments

`extract`	OTN extract data
`type`	type of extract data: "tag" or "receiver"

Examples

## Not run: 
# Get an extract file
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)

# Convert to spatial
prep_station_spatial(matched_dets, "tag")

## End(Not run)

## Not run: 
# Get an extract file
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched_dets <- data.table::fread(
  file.path(td, "pbsm_matched_detections_2018.csv")
)

# Convert to spatial
prep_station_spatial(matched_dets, "tag")

## End(Not run)

Extract and combine the contacts for matched projects

Description

Extract and combine the contacts for matched projects

Usage

project_contacts(extract, type = c("receiver", "tag"))
project_contacts(extract, type = c("receiver", "tag"))

Arguments

`extract`	data.frame of transmitter/receiver detections matched by OTN: matched detections for tags and qualified detections for receivers
`type`	Type of extract data: "tag" or "receiver"

Value

a data.table containing project names, principal investigators (PI), points of contact (POC), and their respective emails. Multiple emails are separated by commas.

Examples

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Actually run the function
project_contacts(matched, type = "tag")

# Clean up
unlink(td, recursive = TRUE)

## End(Not run)

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip"),
  mode = "wb"
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Actually run the function
project_contacts(matched, type = "tag")

# Clean up
unlink(td, recursive = TRUE)

## End(Not run)

Estimate transmitters remaining in the system

Description

This function estimates the transmitters remaining in the system by finding the last date of detection for each transmitter and summing all available transmitters in a given day. This is a very coarse measure and likely to be very inaccurate with sparse data or short time scales.

Usage

remaining_transmitters(matched, push_log, release = NULL)
remaining_transmitters(matched, push_log, release = NULL)

Arguments

`matched`	matched OTN transmitter detections
`push_log`	data.frame containing the date of the most-recent data push. This requirement is very likely to change in the future.
`release`	Optional. Data frame of release times/locations; a subset of the matched detections data

Examples

## Not run: 
#' # Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Run remaining_transmitters()
remaining_transmitters(matched_dets, data.frame(date = as.Date("2020-01-01")))

## End(Not run)

## Not run: 
#' # Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Run remaining_transmitters()
remaining_transmitters(matched_dets, data.frame(date = as.Date("2020-01-01")))

## End(Not run)

Create the station summary table

Description

Create the station summary table

Usage

station_table(extract, type = c("tag", "receiver"))
station_table(extract, type = c("tag", "receiver"))

Arguments

`extract`	OTN detections. "Matched" detections for tag data and "qualified" detections for receiver data
`type`	type of data to be summarized.

Value

For tag data, a data.table with the PI, project, station, number of detections, and number of individuals heard. For receiver data, a data.table with the station, number of detections, and number of individuals heard (assuming that the PI and POC is you).

Examples

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Actually run the function
prep_station_table(matched, type = "tag")



# For receiver data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

qualified <- read.csv(file.path(td, "pbsm_qualified_detections_2018.csv"))

# Actually run the function
station_table(qualified, type = "receiver")

# Clean up
unlink(td, recursive = TRUE)

## End(Not run)

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

# Actually run the function
prep_station_table(matched, type = "tag")



# For receiver data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/pbsm/",
    "detection-extracts/pbsm_qualified_detections_2018.zip/",
    "@download/file"
  ),
  destfile = file.path(td, "pbsm_qualified_detections_2018.zip"),
  mode = "wb"
)
unzip(
  file.path(td, "pbsm_qualified_detections_2018.zip"),
  exdir = td
)

qualified <- read.csv(file.path(td, "pbsm_qualified_detections_2018.csv"))

# Actually run the function
station_table(qualified, type = "receiver")

# Clean up
unlink(td, recursive = TRUE)

## End(Not run)

Create an abacus plot of detections by project

Description

Create an abacus plot of detections by project

Usage

temporal_distribution(extract, type = c("tag", "receiver"))
temporal_distribution(extract, type = c("tag", "receiver"))

Arguments

`extract`	OTN data extract file
`type`	Transmitter (tag) or receiver detections?

Examples

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

temporal_distribution(matched, "tag")

## End(Not run)

## Not run: 
# Set up example data
td <- file.path(tempdir(), "otndo_example")
dir.create(td)

# For tag data
download.file(
  paste0(
    "https://members.oceantrack.org/data/repository/",
    "pbsm/detection-extracts/pbsm_matched_detections_2018.zip/@download/file"
  ),
  destfile = file.path(td, "pbsm_matched_detections_2018.zip")
)
unzip(file.path(td, "pbsm_matched_detections_2018.zip"),
  exdir = td
)

matched <- read.csv(file.path(
  td,
  "pbsm_matched_detections_2018.csv"
))

temporal_distribution(matched, "tag")

## End(Not run)

Package 'otndo'

Help Index

Create a Gantt-like chart of receiver deployments and recoveries

Description

Usage

Arguments

Examples

Create summary reports of receiver project data from the OTN data push

Description

Usage

Arguments

Push log

Output

Examples

Create summary reports of receiver project data from the OTN data push

Description

Usage

Arguments

Examples

Plot the geographic extent of OTN projects

Description

Usage

Arguments

Examples

Create a reactable table of matched detections

Description

Usage

Arguments

Examples

Create an abacus plot of matched detections

Description

Usage

Arguments

Examples

Query the OTN Geoserver

Description

Usage

Arguments

Value

Examples

Prepare the detection match summary data

Description

Usage

Arguments

Summarize OTN extract data by station and convert to a spatial object

Description

Usage

Arguments

Examples

Extract and combine the contacts for matched projects

Description

Usage

Arguments

Value

Examples

Estimate transmitters remaining in the system

Description

Usage

Arguments

Examples

Create the station summary table

Description

Usage

Arguments

Value

Examples

Create an abacus plot of detections by project

Description

Usage

Arguments

Examples