This function read one or more CSV/TXT files or directories of identical,
pre-defined logger type (format) see mc_DataFormat and mc_data_formats.
This function does not support loading locality or sensor metadata while reading.
Metadata can be loaded through mc_read_data() or
can be provided later with function mc_prep_meta_locality()
mc_read_files(
paths,
dataformat_name,
logger_type = NA_character_,
recursive = TRUE,
date_format = NA_character_,
tz_offset = NA_integer_,
step = NA_integer_,
clean = TRUE,
silent = FALSE,
user_data_formats = NULL
)vector of paths to files or directories
data format of logger; one of names(mc_data_formats)
type of logger (default NA), can be one of
pre-defined see mc_read_data() or any custom string
recursive search in sub-directories (default TRUE)
format of date in your hobo files e.g. "%d.%m.%y %H:%M:%S" (default NA). Required for HOBO files. For TMS files ignored, there is known, stable date format. see mc_data_formats
timezone offset in minutes; It is required only for non-UTC data (custom settings in HOBO). Not used in TMS (default NA)
time step of microclimatic time-series in seconds. When provided, then is used in mc_prep_clean instead of automatic step detection. See details. If not provided (NA), is automatically detected in mc_prep_clean. (default NA)
if TRUE, then mc_prep_clean is called automatically while reading (default TRUE)
if TRUE, then any information is not printed in console (default FALSE)
custom data formats; use in case you have your own logger files not pre-defined in myClim - list(key=mc_DataFormat) mc_DataFormat (default NULL)
If custom data format is defined the key can be used in data_format parameter in mc_read_files()
and mc_read_data(). Custom data format must be defined first, and then an be used for reading.
myClim object in Raw-format see myClim-package
If file is not in expected format, then file is skipped and warning printed in console. CSV/TXT files (loggers raw data) are in resulting myClim object placed to separate localities with empty metadata. Localities are named after serial_number of logger. Pre-defined logger types are ("Dendro","HOBO","Thermo","TMS","TMS_L45")
By default, data are cleaned with the function mc_prep_clean see function description.
mc_prep_clean detects gaps in time-series data,
duplicated records, or records in the wrong order. Importantly, mc_prep_clean
also applies a step parameter if provided. The step parameter can be used either
instead of automatic step detection which can sometime failed, or to prune
microclimatic data. For example, if you have a 15-minute time series but you wish to
keep only one record per hour (without aggregating), you can use step parameter.
However, if a step is provided and clean = FALSE, then the step is only stored in the
metadata of myClim, and the time-series data is not cleaned, and the step is not applied.
files <- c(system.file("extdata", "data_91184101_0.csv", package = "myClim"),
system.file("extdata", "data_94184102_0.csv", package = "myClim"))
tomst_data <- mc_read_files(files, "TOMST")
#> 2 loggers
#> datetime range: 2020-10-06 09:00:00 - 2020-10-29 09:45:00
#> detected steps: (900s = 15min)
#> locality_id serial_number start_date end_date
#> 91184101 91184101 91184101 2020-10-28 08:45:00 2020-10-29 09:45:00
#> 94184102 94184102 94184102 2020-10-06 09:00:00 2020-10-07 10:00:00
#> step_seconds count_duplicities count_missing count_disordered rounded
#> 91184101 900 0 0 0 FALSE
#> 94184102 900 0 0 0 FALSE
# user_data_formats
files <- system.file("extdata", "TMS94184102.csv", package = "myClim")
user_data_formats <- list(my_logger=new("mc_DataFormat"))
user_data_formats$my_logger@date_column <- 2
user_data_formats$my_logger@date_format <- "%Y-%m-%d %H:%M:%S"
user_data_formats$my_logger@tz_offset <- 0
user_data_formats$my_logger@columns[[mc_const_SENSOR_T_C]] <- c(3, 4, 5)
user_data_formats$my_logger@columns[[mc_const_SENSOR_real]] <- 6
my_data <- mc_read_files(files, "my_logger", silent=TRUE, user_data_formats=user_data_formats)