Camera operation matrix
Damiano Oldoni, Wolf Missotten
2026-09-09
Source:vignettes/camera-operation-matrix.Rmd
camera-operation-matrix.RmdThis functionality is superseded because camtrapR supports reading
Camera Trap Data Packages. Use camtrapR::readCamtrapDP()
and camtrapR::cameraOperation() instead.
This vignette shows how to get a camera operation
matrix from a Camera Trap Data Package dataset, equivalent to
the matrix returned by camtrapR’s function
camtrapR::cameraOperation().
Setup
Load the packages that will be used in this example:
library(camtraptor)
#>
#> Attaching package: 'camtraptor'
#> The following object is masked from 'package:base':
#>
#> contributors
library(lubridate)
#>
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#>
#> date, intersect, setdiff, union
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, unionFor this example the function example_dataset() is used
to load an example Camera Trap Data Package dataset. The dataset is
derived from a study on detecting invasive muskrat and coypu populations
using camera traps.
x <- example_dataset()Generating the camera operation matrix
The camera operation matrix can be generated with
get_cam_op():
cam_op <- get_cam_op(x)For readability, let’s only print the first 45 columns of the camera operation matrix (i.e. the first 45 days) instead of all 324:
cam_op[, 1:45]
#> 2020-05-30 2020-05-31 2020-06-01 2020-06-02
#> B_HS_val 2_processiepark 0.8766551 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-03 2020-06-04 2020-06-05 2020-06-06
#> B_HS_val 2_processiepark 1 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-07 2020-06-08 2020-06-09 2020-06-10
#> B_HS_val 2_processiepark 1 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-11 2020-06-12 2020-06-13 2020-06-14
#> B_HS_val 2_processiepark 1 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-15 2020-06-16 2020-06-17 2020-06-18
#> B_HS_val 2_processiepark 1 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-19 2020-06-20 2020-06-21 2020-06-22
#> B_HS_val 2_processiepark 1.000 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom 0.125 1 1 1
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-23 2020-06-24 2020-06-25 2020-06-26
#> B_HS_val 2_processiepark 1 1 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom 1 1 1 1
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-06-27 2020-06-28 2020-06-29 2020-06-30
#> B_HS_val 2_processiepark 1 1.0000000 1 1
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom 1 0.9815046 NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-07-01 2020-07-02 2020-07-03 2020-07-04
#> B_HS_val 2_processiepark 0.4039468 NA NA NA
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-07-05 2020-07-06 2020-07-07 2020-07-08
#> B_HS_val 2_processiepark NA NA NA NA
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-07-09 2020-07-10 2020-07-11 2020-07-12
#> B_HS_val 2_processiepark NA NA NA NA
#> B_DL_val 5_beek kleine vijver NA NA NA NA
#> B_DL_val 3_dikke boom NA NA NA NA
#> B_DM_val 4_'t WAD NA NA NA NA
#> 2020-07-13
#> B_HS_val 2_processiepark NA
#> B_DL_val 5_beek kleine vijver NA
#> B_DL_val 3_dikke boom NA
#> B_DM_val 4_'t WAD NATo build this matrix, the function reads the deployments
slot of the Camera Trap Data Package. Row names are station names, by
default taken from the locationName column of
deployments. Column names are dates. The matrix values
represent the daily effort:
-
NA: the camera was not set up on that day. -
1: the camera was fully active for the entire day. - A decimal between 0 and 1: the camera was partially active (e.g. on the first or last day of a deployment).
- Greater than
1: multiple deployments at the same location were active on that day.
In the example above, no location has overlapping deployments, so no
values greater than 1 occur in the matrix. To demonstrate the scenario
where values are greater than 1, the example below assigns
all four deployments to the same location
(B_HS_val 2_processiepark):
x1 <- x
# Assigning all four deployments to the first location
deployments(x1)$locationName[] <- deployments(x1)$locationName[1]
deployments(x1)$deploymentStart[] <- deployments(x1)$deploymentStart[1]
deployments(x1)$deploymentEnd[] <- deployments(x1)$deploymentEnd[1]
# Visualize camera operation matrix
get_cam_op(x1)
#> 2020-05-30 2020-05-31 2020-06-01 2020-06-02 2020-06-03
#> B_HS_val 2_processiepark 3.50662 4 4 4 4
#> 2020-06-04 2020-06-05 2020-06-06 2020-06-07 2020-06-08
#> B_HS_val 2_processiepark 4 4 4 4 4
#> 2020-06-09 2020-06-10 2020-06-11 2020-06-12 2020-06-13
#> B_HS_val 2_processiepark 4 4 4 4 4
#> 2020-06-14 2020-06-15 2020-06-16 2020-06-17 2020-06-18
#> B_HS_val 2_processiepark 4 4 4 4 4
#> 2020-06-19 2020-06-20 2020-06-21 2020-06-22 2020-06-23
#> B_HS_val 2_processiepark 4 4 4 4 4
#> 2020-06-24 2020-06-25 2020-06-26 2020-06-27 2020-06-28
#> B_HS_val 2_processiepark 4 4 4 4 4
#> 2020-06-29 2020-06-30 2020-07-01
#> B_HS_val 2_processiepark 4 4 1.615787To demonstrate the scenario where a single location is linked to
multiple (non-overlapping) deployments, the example below assigns
location B_HS_val 2_processiepark to two separate
deployments:
x2 <- x
# Assigning the first location to two separate deployments
deployments(x2)$locationName[2] <- deployments(x2)$locationName[1]
deployments(x2)$deploymentStart[2] <- deployments(x2)$deploymentEnd[1] +
ddays(5)
deployments(x2)$deploymentEnd[2] <- deployments(x2)$deploymentStart[2] +
ddays(5)
# Visualize deployments
deployments(x2) %>% select(locationName, deploymentStart, deploymentEnd)
#> # A tibble: 4 × 3
#> locationName deploymentStart deploymentEnd
#> <chr> <dttm> <dttm>
#> 1 B_HS_val 2_processiepark 2020-05-30 02:57:37 2020-07-01 09:41:41
#> 2 B_HS_val 2_processiepark 2020-07-06 09:41:41 2020-07-11 09:41:41
#> 3 B_DL_val 3_dikke boom 2020-06-19 21:00:00 2020-06-28 23:33:22
#> 4 B_DM_val 4_'t WAD 2021-03-27 20:38:18 2021-04-18 21:25:00
# Visualize camera operation matrix
get_cam_op(x2)[1, 1:45]
#> 2020-05-30 2020-05-31 2020-06-01 2020-06-02 2020-06-03 2020-06-04 2020-06-05
#> 0.8766551 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> 2020-06-06 2020-06-07 2020-06-08 2020-06-09 2020-06-10 2020-06-11 2020-06-12
#> 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> 2020-06-13 2020-06-14 2020-06-15 2020-06-16 2020-06-17 2020-06-18 2020-06-19
#> 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> 2020-06-20 2020-06-21 2020-06-22 2020-06-23 2020-06-24 2020-06-25 2020-06-26
#> 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> 2020-06-27 2020-06-28 2020-06-29 2020-06-30 2020-07-01 2020-07-02 2020-07-03
#> 1.0000000 1.0000000 1.0000000 1.0000000 0.4039468 NA NA
#> 2020-07-04 2020-07-05 2020-07-06 2020-07-07 2020-07-08 2020-07-09 2020-07-10
#> NA NA 0.5960532 1.0000000 1.0000000 1.0000000 1.0000000
#> 2020-07-11 2020-07-12 2020-07-13
#> 0.4039468 NA NAStation names
By default, row names are taken from the locationName
column of deployments. You can specify a different column
of deployments using station_col. The example
below uses locationID:
cam_op_with_locationID <- get_cam_op(
x,
station_col = "locationID"
)
# Since the full matrix would be too wide to display here, we only inspect
# the row names:
row.names(cam_op_with_locationID)
#> [1] "e254a13c" "2df5259b" "ff1535c0" "ce943ced"Session and camera IDs
Let’s first extend the dataset so deployments contains a
column for cameraID and sessionID.
x_extended <- x
deployments(x_extended) <- deployments(x) %>%
mutate(sessionID = c(1, 2, 3, 4)) %>%
mutate(cameraID = c(1, 2, 3, 4))You can specify the column containing the session IDs to be added to
the station names using the session_col argument. The
sessionID will be displayed following camtrapR’s convention:
Station__SESS_sessionID:
cam_op_with_session_ids <- get_cam_op(
x_extended,
session_col = "sessionID"
)
# Since the full matrix would be too wide to display here, we only inspect
# the row names:
row.names(cam_op_with_session_ids)
#> [1] "B_HS_val 2_processiepark__SESS_1"
#> [2] "B_DL_val 5_beek kleine vijver__SESS_2"
#> [3] "B_DL_val 3_dikke boom__SESS_3"
#> [4] "B_DM_val 4_'t WAD__SESS_4"You can also specify the column containing the camera IDs to be added
to the station names following camtrapR’s convention:
Station__CAM_CameraID using the camera_col
argument:
cam_op_with_camera_ids <- get_cam_op(
x_extended,
camera_col = "cameraID"
)
# Since the full matrix would be too wide to display here, we only inspect
# the row names:
row.names(cam_op_with_camera_ids)
#> [1] "B_HS_val 2_processiepark__CAM_1"
#> [2] "B_DL_val 5_beek kleine vijver__CAM_2"
#> [3] "B_DL_val 3_dikke boom__CAM_3"
#> [4] "B_DM_val 4_'t WAD__CAM_4"To use both camera and session IDs, the camtrapR’s convention
Station__SESS_SessionID__CAM_CameraID is followed:
cam_op_with_session_and_camera_ids <- get_cam_op(
x_extended,
camera_col = "cameraID",
session_col = "sessionID"
)
# Since the full matrix would be too wide to display here, we only inspect
# the row names:
row.names(cam_op_with_session_and_camera_ids)
#> [1] "B_HS_val 2_processiepark__SESS_1__CAM_1"
#> [2] "B_DL_val 5_beek kleine vijver__SESS_2__CAM_2"
#> [3] "B_DL_val 3_dikke boom__SESS_3__CAM_3"
#> [4] "B_DM_val 4_'t WAD__SESS_4__CAM_4"You can also use the prefix "Station" in the station
names as done by camtrapR’s cameraOperation() by setting
use_prefix = TRUE:
cam_op_with_session_and_camera_ids_prefix <- get_cam_op(
x_extended,
camera_col = "cameraID",
session_col = "sessionID",
use_prefix = TRUE
)
# Since the full matrix would be too wide to display here, we only inspect
# the row names:
row.names(cam_op_with_session_and_camera_ids_prefix)
#> [1] "StationB_HS_val 2_processiepark__SESS_1__CAM_1"
#> [2] "StationB_DL_val 5_beek kleine vijver__SESS_2__CAM_2"
#> [3] "StationB_DL_val 3_dikke boom__SESS_3__CAM_3"
#> [4] "StationB_DM_val 4_'t WAD__SESS_4__CAM_4"