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LightLogR (version 0.5.3)

import_Dataset: Import a light logger dataset or related data

Description

Imports a dataset and does the necessary transformations to get the right column formats. Unless specified otherwise, the function will set the timezone of the data to UTC. It will also enforce an Id to separate different datasets and will order/arrange the dataset within each Id by Datetime. See the Details and Devices section for more information and the full list of arguments.

Usage

import_Dataset(device, ...)
import

Value

Tibble/Dataframe with a POSIXct column for the datetime

Format

An object of class list of length 18.

Arguments

device

From what device do you want to import? For a few devices, there is a sample data file that you can use to test the function (see the examples). See supported_devices() for a list of supported devices and see below for more information on devices with specific requirements.

...

Parameters that get handed down to the specific import functions

Devices

The set of import functions provide a convenient way to import light logger data that is then perfectly formatted to add metadata, make visualizations and analyses. There are a number of devices supported, where import should just work out of the box. To get an overview, you can simply call the supported_devices() dataset. The list will grow continuously as the package is maintained.

supported_devices()
#>  [1] "ActLumus"              "ActTrust"              "Actiwatch_Spectrum"   
#>  [4] "Actiwatch_Spectrum_de" "Circadian_Eye"         "DeLux"                
#>  [7] "GENEActiv_GGIR"        "Kronowise"             "LIMO"                 
#> [10] "LYS"                   "LiDo"                  "LightWatcher"         
#> [13] "MotionWatch8"          "OcuWEAR"               "Speccy"               
#> [16] "SpectraWear"           "VEET"                  "nanoLambda"

ActLumus

Manufacturer: Condor Instruments

Model: ActLumus

Implemented: Sep 2023

A sample file is provided with the package, it can be accessed through system.file("extdata/205_actlumus_Log_1020_20230904101707532.txt.zip", package = "LightLogR"). It does not need to be unzipped to be imported. This sample file is a good example for a regular dataset without gaps

LYS

Manufacturer: LYS Technologies

Model: LYS Button

Implemented: Sep 2023

A sample file is provided with the package, it can be accessed through system.file("extdata/sample_data_LYS.csv", package = "LightLogR"). This sample file is a good example for an irregular dataset.

Actiwatch_Spectrum & Actiwatch_Spectrum_de

Manufacturer: Philips Respironics

Model: Actiwatch Spectrum

Implemented: Nov 2023 / July 2024

Important note: The Actiwatch_Spectrum function is for an international/english formatting. The Actiwatch_Spectrum_de function is for a german formatting, which slightly differs in the datetime format, the column names, and the decimal separator.

ActTrust

Manufacturer: Condor Instruments

Model: ActTrust1, ActTrust2

Implemented: Mar 2024

This function works for both ActTrust 1 and 2 devices

Speccy

Manufacturer: Monash University

Model: Speccy

Implemented: Feb 2024

DeLux

Manufacturer: Intelligent Automation Inc

Model: DeLux

Implemented: Dec 2023

LiDo

Manufacturer: University of Lucerne

Model: LiDo

Implemented: Nov 2023

SpectraWear

Manufacturer: University of Manchester

Model: SpectraWear

Implemented: May 2024

NanoLambda

Manufacturer: NanoLambda

Model: XL-500 BLE

Implemented: May 2024

LightWatcher

Manufacturer: Object-Tracker

Model: LightWatcher

Implemented: June 2024

VEET

Manufacturer: Meta Reality Labs

Model: VEET

Implemented: July 2024

Required Argument: modality A character scalar describing the modality to be imported from. Can be one of "ALS" (Ambient light sensor), "IMU" (Inertial Measurement Unit), "INF" (Information), "PHO" (Spectral Sensor), "TOF" (Time of Flight)

Circadian_Eye

Manufacturer: Max-Planck-Institute for Biological Cybernetics, Tübingen

Model: melanopiQ Circadian Eye (Prototype)

Implemented: July 2024

Kronowise

Manufacturer: Kronohealth

Model: Kronowise

Implemented: July 2024

GENEActiv with GGIR preprocessing

Manufacturer: Activeinsights

Model: GENEActiv

Note: This import function takes GENEActiv data that was preprocessed through the GGIR package. By default, GGIR aggregates light data into intervals of 15 minutes. This can be set by the windowsizes argument in GGIR, which is a three-value vector, where the second values is set to 900 seconds by default. To import the preprocessed data with LightLogR, the filename argument requires a path to the parent directory of the GGIR output folders, specifically the meta folder, which contains the light exposure data. Multiple filenames can be specified, each of which needs to be a path to a different GGIR parent directory. GGIR exports can contain data from multiple participants, these will always be imported fully by providing the parent directory. Use the pattern argument to extract sensible Ids from the .RData filenames within the meta/basic/ folder. As per the author, Dr. Vincent van Hees, GGIR preprocessed data are always in local time, provided the desiredtz/configtz are properly set in GGIR. LightLogR still requires a timezone to be set, but will not timeshift the import data.

MotionWatch 8

Manufacturer: CamNtech

Implemented: September 2024

LIMO

Manufacturer: ENTPE

Implemented: September 2024

LIMO exports LIGHT data and IMU (inertia measurements, also UV) in separate files. Both can be read in with this function, but not at the same time. Please decide what type of data you need and provide the respective filenames.

OcuWEAR

Manufacturer: Ocutune

Implemented: September 2024

OcuWEAR data contains spectral data. Due to the format of the data file, the spectrum is not directly part of the tibble, but rather a list column of tibbles within the imported data, containing a Wavelength (nm) and Intensity (mW/m^2) column.

Examples

Imports made easy

To import a file, simple specify the filename (and path) and feed it to the import_Dataset function. There are sample datasets for all devices.

The import functions provide a basic overview of the data after import, such as the intervals between measurements or the start and end dates.

filepath <- system.file("extdata/sample_data_LYS.csv", package = "LightLogR")
dataset <- import_Dataset("LYS", filepath, auto.plot = FALSE)
#> 
#> Successfully read in 11'422 observations across 1 Ids from 1 LYS-file(s).
#> Timezone set is UTC.
#> The system timezone is Europe/Berlin. Please correct if necessary!
#> 
#> First Observation: 2023-06-21 00:00:12
#> Last Observation: 2023-06-22 23:59:48
#> Timespan: 2 days
#> 
#> Observation intervals: 
#>   Id              interval.time     n pct    
#> 1 sample_data_LYS 15s           10015 87.689%
#> 2 sample_data_LYS 16s            1367 11.969%
#> 3 sample_data_LYS 17s              23 0.201% 
#> 4 sample_data_LYS 18s              16 0.140%

Import functions can also be called directly:

filepath <- system.file("extdata/205_actlumus_Log_1020_20230904101707532.txt.zip", package = "LightLogR")
dataset <- import$ActLumus(filepath, auto.plot = FALSE)
#> 
#> Successfully read in 61'016 observations across 1 Ids from 1 ActLumus-file(s).
#> Timezone set is UTC.
#> The system timezone is Europe/Berlin. Please correct if necessary!
#> 
#> First Observation: 2023-08-28 08:47:54
#> Last Observation: 2023-09-04 10:17:04
#> Timespan: 7.1 days
#> 
#> Observation intervals: 
#>   Id                                          interval.time     n pct  
#> 1 205_actlumus_Log_1020_20230904101707532.txt 10s           61015 100%
dataset %>% gg_days()


dataset %>%
dplyr::select(Datetime, TEMPERATURE, LIGHT, MEDI, Id) %>%
dplyr::slice(1500:1505)
#> # A tibble: 6 x 5
#> # Groups:   Id [1]
#>   Datetime            TEMPERATURE LIGHT  MEDI Id                                
#>   <dttm>                    <dbl> <dbl> <dbl> <fct>                             
#> 1 2023-08-28 12:57:44        26.9  212.  202. 205_actlumus_Log_1020_20230904101~
#> 2 2023-08-28 12:57:54        26.9  208.  199. 205_actlumus_Log_1020_20230904101~
#> 3 2023-08-28 12:58:04        26.9  205.  196. 205_actlumus_Log_1020_20230904101~
#> 4 2023-08-28 12:58:14        26.8  204.  194. 205_actlumus_Log_1020_20230904101~
#> 5 2023-08-28 12:58:24        26.9  203.  194. 205_actlumus_Log_1020_20230904101~
#> 6 2023-08-28 12:58:34        26.8  204.  195. 205_actlumus_Log_1020_20230904101~

Details

There are specific and a general import function. The general import function is described below, whereas the specific import functions take the form of import$device(). The general import function is a thin wrapper around the specific import functions. The specific import functions take the following arguments:

  • filename: Filename(s) for the Dataset. Can also contain the filepath, but path must then be NULL. Expects a character. If the vector is longer than 1, multiple files will be read in into one Tibble.

  • path: Optional path for the dataset(s). NULL is the default. Expects a character.

  • n_max: maximum number of lines to read. Default is Inf.

  • tz: Timezone of the data. "UTC" is the default. Expects a character. You can look up the supported timezones with OlsonNames().

  • Id.colname: Lets you specify a column for the id of a dataset. Expects a symbol (Default is Id). This column will be used for grouping (dplyr::group_by()).

  • auto.id: If the Id.colname column is not part of the dataset, the Id can be automatically extracted from the filename. The argument expects a regular expression regex and will by default just give the whole filename without file extension.

  • manual.id: If this argument is not NULL, and no Id column is part of the dataset, this character scalar will be used. We discourage the use of this arguments when importing more than one file

  • silent: If set to TRUE, the function will not print a summary message of the import or plot the overview. Default is FALSE.

  • locale: The locale controls defaults that vary from place to place.

  • dst_adjustment: If a file crosses daylight savings time, but the device does not adjust time stamps accordingly, you can set this argument to TRUE, to apply this shift manually. It is selective, so it will only be done in files that cross between DST and standard time. Default is FALSE. Uses dst_change_handler() to do the adjustment. Look there for more infos. It is not equipped to handle two jumps in one file (so back and forth between DST and standard time), but will work fine if jums occur in separate files.

  • auto.plot: a logical on whether to call gg_overview() after import. Default is TRUE. But is set to FALSE if the argument silent is set to TRUE.

  • ...: supply additional arguments to the readr import functions, like na. Might also be used to supply arguments to the specific import functions, like column_names for Actiwatch_Spectrum devices. Those devices will always throw a helpful error message if you forget to supply the necessary arguments. If the Id column is already part of the dataset it will just use this column. If the column is not present it will add this column and fill it with the filename of the importfile (see param auto.id).

  • print_n can be used if you want to see more rows from the observation intervals

  • remove_duplicates can be used if identical observations are present within or across multiple files. The default is FALSE. The function keeps only unique observations (=rows) if set to' TRUE'. This is a convenience implementation of dplyr::distinct().

See Also

supported_devices