Get data for acoustic detections, with options to filter results. Use
limit to limit the number of returned records.
Usage
get_acoustic_detections(
connection,
start_date = NULL,
end_date = NULL,
tag_serial_number = NULL,
acoustic_tag_id = NULL,
animal_project_code = NULL,
scientific_name = NULL,
acoustic_project_code = NULL,
receiver_id = NULL,
station_name = NULL,
limit = FALSE,
progress = TRUE
)Arguments
- connection
![[Deprecated]](figures/lifecycle-deprecated.svg)
A connection to the ETN
database. This argument is no longer used. You will be prompted for
credentials instead.- start_date
Character. Start date (inclusive) in ISO 8601 format (
yyyy-mm-dd,yyyy-mmoryyyy).- end_date
Character. End date (exclusive) in ISO 8601 format (
yyyy-mm-dd,yyyy-mmoryyyy).- tag_serial_number
Character (vector). One or more acoustic tag serial numbers.
- acoustic_tag_id
Character (vector). One or more acoustic tag ids.
- animal_project_code
Character (vector). One or more animal project codes. Case-insensitive.
- scientific_name
Character (vector). One or more scientific names.
- acoustic_project_code
Character (vector). One or more acoustic project codes. Case-insensitive.
- receiver_id
Character (vector). One or more receiver identifiers.
- station_name
Character (vector). One or more deployment station names.
- limit
Logical. Limit the number of returned records to 100 (useful for testing purposes). Defaults to
FALSE.- progress
Logical. Show a progress bar while fetching data. Defaults to
TRUE.
Value
A tibble with acoustic detections data, sorted by acoustic_tag_id
and date_time. See also
field definitions.
Examples
# Get limited sample of acoustic detections
get_acoustic_detections(limit = TRUE)
#> ℹ Preparing
#> ✔ Preparing : will fetch 100 detections [12ms]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [112ms]
#>
#> # A tibble: 100 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 18895442 2010-09-14 09:38:36 1097345 A69-1303-65302
#> 2 18895443 2010-09-14 09:58:44 1097345 A69-1303-65302
#> 3 18895444 2010-09-14 10:18:52 1097345 A69-1303-65302
#> 4 18895445 2010-09-14 10:28:56 1097345 A69-1303-65302
#> 5 18895447 2010-09-14 10:59:07 1097345 A69-1303-65302
#> 6 18895448 2010-09-14 11:09:11 1097345 A69-1303-65302
#> 7 18895449 2010-09-14 11:19:15 1097345 A69-1303-65302
#> 8 18895450 2010-09-14 12:09:35 1097345 A69-1303-65302
#> 9 18895451 2010-09-14 12:19:39 1097345 A69-1303-65302
#> 10 18895452 2010-09-14 13:20:02 1097345 A69-1303-65302
#> # ℹ 90 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get all acoustic detections from a specific animal project
get_acoustic_detections(animal_project_code = "2014_demer")
#> ℹ Preparing
#> ✔ Preparing : will fetch 235.81 k detections [6.3s]
#>
#> Getting detections. ■■■■■■■■■■■ 33% [7.1s] | ETA: 14s
#> Getting detections. ■■■■■■■■■■■■■■■■■■■■■ 67% [14.6s] | ETA: 7s
#> ℹ Wrapping up
#> ✔ Wrapping up [383ms]
#>
#> # A tibble: 235,809 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 20582652 2014-04-18 15:52:33 1187449 A69-1601-16129
#> 2 20627256 2014-04-18 15:51:11 1187449 A69-1601-16129
#> 3 20734006 2014-04-18 15:50:03 1187449 A69-1601-16129
#> 4 20744955 2014-04-18 16:01:00 1187449 A69-1601-16129
#> 5 20777048 2014-04-18 15:55:00 1187449 A69-1601-16129
#> 6 20834951 2014-04-18 15:52:00 1187449 A69-1601-16129
#> 7 20923248 2014-04-18 15:56:25 1187449 A69-1601-16129
#> 8 21655610 2014-04-18 16:02:26 1187449 A69-1601-16129
#> 9 21676626 2014-04-18 15:45:00 1187449 A69-1601-16129
#> 10 21745679 2014-04-18 15:47:45 1187449 A69-1601-16129
#> # ℹ 235,799 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get 2015 acoustic detections from that animal project
get_acoustic_detections(
animal_project_code = "2014_demer",
start_date = "2015",
end_date = "2016",
)
#> ℹ Preparing
#> ✔ Preparing : will fetch 23.70 k detections [2.6s]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [126ms]
#>
#> # A tibble: 23,695 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 23629467 2015-05-06 04:11:52 1187468 A69-1601-16148
#> 2 23630262 2015-05-07 15:59:24 1187468 A69-1601-16148
#> 3 23630263 2015-05-07 16:45:38 1187468 A69-1601-16148
#> 4 23630265 2015-05-07 16:56:22 1187468 A69-1601-16148
#> 5 23630267 2015-05-07 17:00:18 1187468 A69-1601-16148
#> 6 23630274 2015-05-07 17:06:13 1187468 A69-1601-16148
#> 7 23630278 2015-05-07 17:08:54 1187468 A69-1601-16148
#> 8 23630285 2015-05-07 17:15:07 1187468 A69-1601-16148
#> 9 23630294 2015-05-07 17:23:21 1187468 A69-1601-16148
#> 10 23630300 2015-05-07 17:27:27 1187468 A69-1601-16148
#> # ℹ 23,685 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get April 2015 acoustic detections from that animal project
get_acoustic_detections(
animal_project_code = "2014_demer",
start_date = "2015-04",
end_date = "2015-05",
)
#> ℹ Preparing
#> ✔ Preparing : will fetch 442 detections [2.7s]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [63ms]
#>
#> # A tibble: 442 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 23863772 2015-04-20 17:18:27 1171781 A69-1601-26535
#> 2 23863773 2015-04-20 17:20:27 1171781 A69-1601-26535
#> 3 23863774 2015-04-20 17:23:03 1171781 A69-1601-26535
#> 4 23863775 2015-04-20 17:44:07 1171781 A69-1601-26535
#> 5 23863776 2015-04-20 17:58:38 1171781 A69-1601-26535
#> 6 23863777 2015-04-20 18:00:52 1171781 A69-1601-26535
#> 7 23863778 2015-04-20 18:02:37 1171781 A69-1601-26535
#> 8 23863779 2015-04-20 18:04:44 1171781 A69-1601-26535
#> 9 23863780 2015-04-20 18:06:13 1171781 A69-1601-26535
#> 10 23863781 2015-04-20 18:07:47 1171781 A69-1601-26535
#> # ℹ 432 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get April 24, 2015 acoustic detections from that animal project
get_acoustic_detections(
animal_project_code = "2014_demer",
start_date = "2015-04-24",
end_date = "2015-04-25",
)
#> ℹ Preparing
#> ✔ Preparing : will fetch 2 detections [2.5s]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [59ms]
#>
#> # A tibble: 2 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 23053006 2015-04-24 07:54:12 1171781 A69-1601-26535
#> 2 23053007 2015-04-24 07:56:29 1171781 A69-1601-26535
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get acoustic detections for a specific tag at two specific stations
get_acoustic_detections(
acoustic_tag_id = "A69-1601-16130",
station_name = c("de-9", "de-10")
)
#> ℹ Preparing
#> ✔ Preparing : will fetch 50 detections [2.5s]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [59ms]
#>
#> # A tibble: 50 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 20638636 2014-04-26 12:46:40 1187450 A69-1601-16130
#> 2 20641245 2014-04-26 13:18:00 1187450 A69-1601-16130
#> 3 20701797 2014-04-26 13:12:00 1187450 A69-1601-16130
#> 4 20904420 2014-04-26 12:51:00 1187450 A69-1601-16130
#> 5 20951670 2014-04-28 18:34:00 1187450 A69-1601-16130
#> 6 21107986 2014-04-28 18:37:07 1187450 A69-1601-16130
#> 7 21159804 2014-04-26 12:49:22 1187450 A69-1601-16130
#> 8 21193066 2014-04-26 12:49:00 1187450 A69-1601-16130
#> 9 21198095 2014-04-28 18:32:53 1187450 A69-1601-16130
#> 10 21387447 2014-04-26 12:51:23 1187450 A69-1601-16130
#> # ℹ 40 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>
# Get acoustic detections for a specific species, receiver and acoustic project
get_acoustic_detections(
scientific_name = "Rutilus rutilus",
receiver_id = "VR2W-124070",
acoustic_project_code = "demer"
)
#> ℹ Preparing
#> ✔ Preparing : will fetch 38 detections [3.9s]
#>
#> ℹ Wrapping up
#> ✔ Wrapping up [61ms]
#>
#> # A tibble: 38 × 20
#> detection_id date_time tag_serial_number acoustic_tag_id
#> <int> <dttm> <chr> <chr>
#> 1 20962095 2014-04-18 16:12:26 1187449 A69-1601-16129
#> 2 21250456 2014-04-18 16:10:52 1187449 A69-1601-16129
#> 3 21261941 2014-04-18 16:17:05 1187449 A69-1601-16129
#> 4 21697884 2014-04-18 16:12:00 1187449 A69-1601-16129
#> 5 21863649 2014-04-18 16:17:00 1187449 A69-1601-16129
#> 6 22013363 2014-04-18 16:15:00 1187449 A69-1601-16129
#> 7 22153161 2014-04-18 16:15:32 1187449 A69-1601-16129
#> 8 22437907 2014-04-18 16:10:00 1187449 A69-1601-16129
#> 9 20621280 2014-04-26 11:22:25 1187450 A69-1601-16130
#> 10 20667884 2014-04-26 10:23:51 1187450 A69-1601-16130
#> # ℹ 28 more rows
#> # ℹ 16 more variables: animal_project_code <chr>, animal_id <int>,
#> # scientific_name <chr>, acoustic_project_code <chr>, receiver_id <chr>,
#> # station_name <chr>, deploy_latitude <dbl>, deploy_longitude <dbl>,
#> # sensor_value <dbl>, sensor_unit <chr>, sensor2_value <dbl>,
#> # sensor2_unit <chr>, signal_to_noise_ratio <int>, source_file <chr>,
#> # qc_flag <lgl>, deployment_id <int>