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Process SensorLog Data

Source: R/acti_process_sensorlog.R
acti_process_sensorlog.Rd

Process SensorLog Data

Usage

acti_process_sensorlog(
  data,
  lat = NULL,
  lon = NULL,
  dist_fun = geosphere::distVincentyEllipsoid,
  expected_timezone = NULL,
  check_data = TRUE,
  remove_cols = c("file", "index"),
  verbose = FALSE,
  ...,
  distance_cutoff = 180
)

acti_check_duplicate_times(data, remove_cols = c("file", "index"))

acti_calculate_distance(
  data,
  lat,
  lon,
  distance_cutoff = 180,
  dist_fun = geosphere::distVincentyEllipsoid,
  fast = TRUE
)

Arguments

data

A SensorLog-style data.frame

lat

Latitude of central point (e.g. home) to calculate distance. Set to NULL if distance should not be calculated.

lon

Longitude of central point (e.g. home) to calculate distance Set to NULL if distance should not be calculated.

dist_fun

Distance function to pass to geosphere::distm

expected_timezone

Expected Timezone based on the latitude/longitude of the data based on the lat/lon values from SensorLog ( e.g. "America/New_York"). Set to NULL if not to be checked.

check_data

should acti_check_duplicate_times be run?

remove_cols

columns to remove from duplicate checking in acti_check_duplicate_times. Default is c("file", "index")

verbose

print diagnostic messages. Either logical or integer, where higher values are higher levels of verbosity.

...

additional arguments to pass to acti_sensorlog_process_time, including apply_tz and tz

distance_cutoff

Distance in meters to consider within home, in meters

fast

Calculate distance on the distinct latitude/longitude, not the full data. Should be used unless some precision looks wrong.

Value

A data.frame of transformed data

Note

This calls acti_check_duplicate_times, acti_calculate_distance, and acti_sensorlog_process_time

Examples

sensorlog = suppressMessages(
  actiread::acti_read_sensorlog(actiread::acti_example_sensorlog_file())
)
sensorlog = dplyr::distinct(sensorlog, time, .keep_all = TRUE)
result = acti_process_sensorlog(
  sensorlog,
  lat = 39.3,
  lon = -76.6,
  expected_timezone = "America/New_York",
  check_data = FALSE
)
head(result)
#> # A tibble: 6 × 19
#>   file  time                index timestamp             lat   lon altitude speed
#>   <chr> <dttm>              <dbl> <dttm>              <dbl> <dbl>    <dbl> <dbl>
#> 1 /tmp… 2025-03-11 18:44:11     1 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> 2 /tmp… 2025-03-11 18:44:11     2 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> 3 /tmp… 2025-03-11 18:44:11     3 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> 4 /tmp… 2025-03-11 18:44:12     4 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> 5 /tmp… 2025-03-11 18:44:12     5 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> 6 /tmp… 2025-03-11 18:44:12     6 2025-03-11 18:44:07  39.3 -76.6     46.3    -1
#> # ℹ 11 more variables: speed_accuracy <dbl>, accel_X <dbl>, accel_Y <dbl>,
#> #   accel_Z <dbl>, lat_zero <lgl>, lon_zero <lgl>, distance <dbl>,
#> #   is_within_home <lgl>, distance_traveled <dbl>, timezone_estimated <chr>,
#> #   char_time <chr>
minute = acti_minute_sensorlog(result)
summary = acti_summarize_sensorlog(result)