R/import_data.R
import_actigraph_count_csv.Rd
import_actigraph_count_csv
imports Actigraph count data stored in
Actigraph summary csv format, which was exported by Actilife.
import_actigraph_count_csv(
filepath,
count_col = 2,
count_per_axis_cols = c(2, 3, 4)
)
string. The filepath of the input data.
number. The index of column of Actigraph count (combined
axes). If it is NULL
, the function will use
count_per_axis_cols
to get the combined Actigraph count values.
numerical vector. The indices of columns of
Actigraph count values per axis. If count_col
is not NULL
,
the argument will be ignored. If it is NULL
, the output dataframe
will only have two columns without Actigraph count values per axis.
dataframe. The imported actigraph count data, with the first column being the timestamps in POSIXct format, and the second column being the combined Actigraph count values, and the rest of columns being the Actigraph cont values per axis if available. Column names:
HEADER_TIME_STAMP
, ACTIGRAPH_COUNT
,
ACTIGRAPH_COUNT_X
....
If both count_col
and count_per_axis_cols
are
NULL
, the function will raise an error.
This function is a File IO function that is used to import Actigraph count data from Actigraph devices during algorithm validation.
Other File I/O functions:
export_to_actilife()
,
import_actigraph_csv_chunked()
,
import_actigraph_csv()
,
import_actigraph_meta()
,
import_activpal3_csv()
,
import_enmo_csv()
,
import_mhealth_csv_chunked()
,
import_mhealth_csv()
# Use the actigraph count csv file shipped with the package
filepath = system.file('extdata', 'actigraph_count.csv', package='MIMSunit')
# Check original data format
readLines(filepath)[1:5]
#> [1] "timestamp,vectormagnitude" "2018-06-14 11:27:00,0"
#> [3] "2018-06-14 11:27:05,0" "2018-06-14 11:27:10,0"
#> [5] "2018-06-14 11:27:15,0"
# Load file, default column for actigraph count values are 2, this file does not have
# axial count values
output = import_actigraph_count_csv(filepath, count_col=2)
# Check output
head(output)
#> HEADER_TIME_STAMP ACTIGRAPH_COUNT
#> 1 2018-06-14 11:27:00 0
#> 2 2018-06-14 11:27:05 0
#> 3 2018-06-14 11:27:10 0
#> 4 2018-06-14 11:27:15 0
#> 5 2018-06-14 11:27:20 0
#> 6 2018-06-14 11:27:25 0