Package 'isoreader2'

isoreader2: Read Stable Isotope Data Files

Description

Interface to the raw data and metadata stored in the file formats commonly encountered in scientific disciplines that make use of stable isotopes. Supports Isodat (.dxf, .cf, .did, .caf, .scn), IonOS (.iarc), LyticOS (.larc), Callisto (.bch), and Qtegra (.imexp) file formats. Provides a consistent data structure together with tools to aggregate, convert signal units, filter, and visualize the extracted data. The approach is described in Kopf et al. (2021) doi:10.21105/joss.02878.

Details

Resources:

• Website for the isoreader2 package: https://isoreader2.isoverse.org

• Package options: ir_options

Author(s)

Maintainer: Sebastian Kopf [email protected] (ORCID)

Authors:

• Sebastian Kopf [email protected] (ORCID)

See Also

Useful links:

• https://isoreader2.isoverse.org/

• https://github.com/isoverse/isoreader2

• Report bugs at https://github.com/isoverse/isoreader2/issues

---

Automatic / default behavior

Description

A sentinel that requests automatic behavior for an argument (currently the data_type_as_facet argument of the plotting functions ir_plot_continuous_flow(), ir_plot_dual_inlet(), ir_plot_scans()). It is the default for those arguments; pass TRUE/FALSE to override the automatic choice.

Usage

auto()

Value

an opaque sentinel of class ir_auto

---

Combine aggregated isofile data

Description

Combine multiple ir_aggregate_isofiles() results into a single ir_aggregated_data object by row-binding each of the contained datasets (metadata, traces, cycles, scans, resistors, vendor_data_table, problems, ...) with dplyr::bind_rows(). Datasets present in only some of the objects are combined as well (missing columns are filled with NA). The file index uidx is re-numbered across the inputs so each file stays uniquely identified (and its datasets stay correctly linked) in the combined object.

Usage

## S3 method for class 'ir_aggregated_data'
c(...)

Arguments

...	ir_aggregated_data objects to combine

Value

a single combined ir_aggregated_data object

---

Combine isofiles

Description

Combine multiple collections of isofiles (read by ir_read_isofiles()) into a single ir_isofiles object by row-binding them with dplyr::bind_rows(). This preserves the object structure and type.

Usage

## S3 method for class 'ir_isofiles'
c(...)

Arguments

...	ir_isofiles objects to combine

Value

a single combined ir_isofiles object

---

Aggregate data from isofiles

Description

This function allows dynamic aggregation and validation of data read by ir_read_isofiles(). Like ir_read_isofiles(), it is designed to be fail save by safely catching errors and reporting back on them (see ir_get_problems()). This function should work out of the box for most files without additional modification of the aggregator.

Usage

ir_aggregate_isofiles(
  isofiles,
  intensity_units = c("mV", "V", "fA", "pA", "nA", "µA", "mA", "A", "cps"),
  aggregator = "standard",
  show_progress = is_interactive(),
  show_problems = TRUE
)

Arguments

isofiles	the isotope data files/archives read in by ir_read_isofiles()
intensity_units	target intensity unit to convert traces/cycles/scans to before aggregation, one of "mV", "V", "fA", "pA", "nA", "\u00b5A", "mA", "A", "cps". Only applied when the aggregator includes any of those datasets. Default is "mV".
aggregator	typically the name of a registered aggregator (see all with ir_get_option("aggregators")), default is the "standard" aggregator included in the package (ir_get_aggregator("standard")). The other built-in options, from smallest to largest, are "metadata" (ir_get_aggregator("metadata"), metadata only), "minimal" (ir_get_aggregator("minimal"), metadata plus the core data series), and "extended" (ir_get_aggregator("extended"), also resistors and the vendor data table). The aggregator parameter can can also directly be an aggregator tibble (created/modified with ir_start_aggregator() and/or ir_add_to_aggregator()) that defines which data should be aggregated and how.
show_progress	whether to show a progress bar, by default always enabled when running interactively e.g. inside Positron or RStudio (and disabled in a notebook), turn off with show_progress = FALSE
show_problems	whether to show problems encountered along the way (rather than just keeping track of them with ir_get_problems()). Set to show_problems = FALSE to turn off the live printout. Either way, all encountered problems can be retrieved with running ir_get_problems() for the returned list

Value

a list of merged dataframes collected from the isofiles based on the aggregator definitions

---

Calculate isotope ratios

Description

Calculate intensity ratios of each mass relative to a base mass for every measurement in an ir_aggregate_isofiles() result. Ratios are added directly to the traces (continuous flow), cycles (dual inlet), and/or scans data present in the aggregated data as two extra columns: ratio_name (e.g. "29/28") and ratio. The ratio at each time.s/cycle/x position (within every uidx and analysis) is

Usage

ir_calculate_ratios(
  aggregated_data,
  ...,
  num_add.V = 100,
  denom_add.V = num_add.V,
  num_add.nA = 0,
  denom_add.nA = num_add.nA,
  num_add.cps = 0,
  denom_add.cps = num_add.cps,
  normalize_ratios = NULL
)

Arguments

aggregated_data	datasets aggregated from ir_aggregate_isofiles() (must include at least one of traces, cycles, or scans)
...	named base masses for individual species, e.g. ⁠SO2 = 64, N2 = 28⁠. Species not listed here use their numerically lowest measured mass as the base mass.
num_add.V, denom_add.V	additive offset (in volts) for the numerator and denominator intensities of voltage-unit data (V/mV). Applies to traces and scans only, not to cycles (dual inlet). Default num_add.V = 100, denom_add.V = num_add.V.
num_add.nA, denom_add.nA	additive offset (in nanoamperes) for the numerator and denominator intensities of current-unit data (A/mA/µA/nA/pA/fA). Applies to traces and scans only, not to cycles (dual inlet). Default num_add.nA = 0, denom_add.nA = num_add.nA.
num_add.cps, denom_add.cps	additive offset (in cps) for the numerator and denominator intensities of count-unit data (cps). Applies to traces and scans only, not to cycles (dual inlet). Default num_add.cps = 0, denom_add.cps = num_add.cps.
normalize_ratios	NULL (default) for no normalization, or a function (e.g. mean, median, min, max) applied per uidx/analysis/ratio_name group; each ratio is divided by the value the function returns for its group's non-NA ratios.

Details

$ratio = (I_{mass} + num\_add) / (I_{base} + denom\_add)$

i.e. the intensity of the mass divided by the intensity of the base mass of the same species, after adding an additive offset to numerator and denominator (see below). Base mass rows are kept and have NA in both columns. Calling this function again recomputes (overwrites) the ratio_name/ratio columns. The resulting ratios are not constrained in any way (they can be any value).

The base mass for a species is, by default, the numerically lowest mass measured for that species. Override it for individual species via ... (e.g. SO2 = 64, N2 = 28).

Value

the aggregated_data with ratio_name and ratio columns added to each of the traces, cycles, and/or scans datasets that is present. Both columns are NA for base mass rows (and for any species whose requested base mass could not be found).

Additive offsets

The additive offsets apply to continuous-flow (traces) and scans data only. Dual inlet (cycles) data is not offset and always uses the plain ratio I_mass / I_base regardless of the ⁠num_add.*⁠/⁠denom_add.*⁠ settings.

For traces and scans, which pair of additive offsets is used depends on the intensity unit family of the data: voltage (V, mV) uses num_add.V/denom_add.V, current (A, mA, µA, nA, pA, fA) uses num_add.nA/denom_add.nA, and counts (cps) uses num_add.cps/denom_add.cps. The offsets are specified in their family's reference unit (volts, nanoamperes, cps) and are automatically scaled to the data's actual intensity unit before being added. For example, with intensity.mV data the default num_add.V = 100 (volts) is multiplied by 1000 and 100000 mV are added; with intensity.pA data the default num_add.nA = 0 would be multiplied by 1000 (1 nA = 1000 pA).

Normalization

normalize_ratios is NULL by default (no normalization). Pass a function to divide every ratio by the value that function returns for its uidx/analysis/ratio_name group (the function receives the group's non-NA ratios). For example normalize_ratios = mean centers each ratio around 1, while median, min, or max normalize to the group median, minimum, or maximum, respectively.

---

Check for the isoextract executables

Description

By default, these will install the executable if it is missing or outdated. They run automatically when needed and do not usually need to be called directly by the user. In particular, ir_check_isoextract() calls ir_check_isosolfs() automatically (unless check_isosolfs = FALSE), so ir_check_isosolfs() rarely needs to be called on its own.

Usage

ir_check_isoextract(
  install_if_missing = !on_cran(),
  reinstall_if_outdated = !on_cran(),
  reinstall_always = FALSE,
  min_version = "0.3.1",
  show_version = TRUE,
  ask_permission = TRUE,
  source =
    paste0("https://github.com/isoverse/IsofileExtractor/releases/download/isoextract-v",
    min_version),
  check_isosolfs = TRUE,
  ...
)

ir_check_isosolfs(
  install_if_missing = !on_cran(),
  reinstall_if_outdated = !on_cran(),
  reinstall_always = FALSE,
  min_version = "1.0.0",
  show_version = TRUE,
  ask_permission = TRUE,
  source =
    paste0("https://github.com/isoverse/IsofileExtractor/releases/download/isosolfs-v",
    min_version),
  ...
)

Arguments

install_if_missing	install the executable if it's missing
reinstall_if_outdated	install the executable if it's outdated (i.e. not at least min_version)
reinstall_always	whether to (re-)install no matter what
min_version	the minimum version number required
show_version	whether to print the installed version after a successful check (default: TRUE)
ask_permission	whether to ask for the user's permission before downloading a missing or outdated executable (default: TRUE). The prompt only appears in interactive sessions and only when a download is actually needed; if it is declined - or the session is not interactive - no download is attempted and the function aborts with instructions. Set to FALSE to allow the download without prompting (e.g. in scripts). When ir_check_isoextract() downloads isoextract with the user's consent it passes ask_permission = FALSE on to ir_check_isosolfs() so the user is not asked a second time.
source	the URL (or local path) where to find the executable, by default this is the latest release of the executables on github
check_isosolfs	whether to also ensure the isosolfs helper executable is installed (default: TRUE), by calling ir_check_isosolfs(). isosolfs is required to read Qtegra notebooks (.imexp files) and is released alongside isoextract; the same install_if_missing / reinstall_if_outdated / reinstall_always / show_version settings are applied to it.
...	passed on to download.file if (re-) installing the executable(s)

Value

called for its side effect of ensuring a working executable (at least min_version) is installed — and, for ir_check_isoextract() when check_isosolfs = TRUE, isosolfs as well; returns NULL invisibly and aborts if a required executable cannot be made available

Functions

• ir_check_isosolfs(): ensure the isosolfs helper executable (used to read Qtegra .imexp notebooks) is installed. Released alongside isoextract and called automatically by ir_check_isoextract(), so it rarely needs to be called directly.

---

Convert intensity between units

Description

Note: this function is rarely called directly, it's run as part of ir_aggregate_isofiles to standardize the trace/cycle/scan datasets before aggregation.

Usage

ir_convert_intensity(
  dataset,
  resistors = NULL,
  units = c("mV", "V", "fA", "pA", "nA", "µA", "mA", "A", "cps")
)

Arguments

dataset	a data frame with columns species, channel, and an ⁠intensity.<unit>⁠ column (e.g. intensity.mV, intensity.nA).
resistors	a data frame with columns species, channel, and resistance.Ohm. Required when converting between voltage and current/CPS; ignored otherwise. If a config column is present in both dataset and resistors it is included in the join key.
units	target unit, one of "mV", "V", "fA", "pA", "nA", "\u00b5A", "mA", "A", "cps".

Details

Converts the intensity column of a dataset between voltage, current, and count-per-second units using A = CPS * e and V = A * R. Automatically detects the source unit from any ⁠intensity.<unit>⁠ column present in dataset. Joins resistors by species and channel (plus config when present in both) only when the conversion path crosses the A/V boundary. Returns dataset with the source intensity column replaced by ⁠intensity.<units>⁠.

Value

the dataset with its ⁠intensity.*⁠ column converted to the target units and renamed accordingly (e.g. intensity.mV)

---

Default isoreader2 plotting theme

Description

This theme is always applied by the plotting functions (ir_plot_continuous_flow(), ir_plot_dual_inlet(), ir_plot_scans()). To customize a plot, add a ggplot2::theme() on top of the returned plot, e.g. ir_plot_continuous_flow(...) + ggplot2::theme(text = element_text(size = 20)).

Usage

ir_default_theme(text_size = 16)

Arguments

text_size

base font size in points (default: 16)

Value

a ggplot2 theme object

---

Bundled example files

Description

ir_examples_folder() returns the path to the folder with the example isodat files bundled with the package (a convenience wrapper around system.file("extdata", package = "isoreader2")). ir_copy_examples() copies those example files into a local folder so they can be read, re-extracted, or modified without touching the read-only package installation.

Usage

ir_examples_folder()

ir_copy_examples(folder = "examples")

Arguments

folder

target directory to copy the example files into (default "examples"); created if it does not exist

Value

ir_examples_folder() returns the path to the example files folder as a single string.

ir_copy_examples() invisibly returns the path to the created examples folder

Functions

• ir_copy_examples(): copy the bundled example files into a local folder, creating it if necessary and only copying files that do not already exist there (existing files are left untouched). Only the original data files are copied, not their bundled .json sidecars, so reading from the copied folder re-extracts them from scratch (requires the isoextract executable).

Examples

ir_examples_folder() |> ir_find_scans()
# copy the bundled examples into a temporary folder and find them
ir_copy_examples(folder = file.path(tempdir(), "examples")) |>
  ir_find_continuous_flow()

---

Export data to Excel

Description

Exports one or more data frames / tibbles (typically retrieved with the ⁠ir_get_*()⁠ functions, e.g. ir_get_metadata(), ir_get_traces()) to an Excel file, one sheet per data frame. Pass the data frames as ...: named arguments use the name as the sheet name, unnamed arguments are placed in a sheet named after their position (e.g. the 3rd unnamed data frame goes into "Sheet3").

Usage

ir_export_to_excel(
  ...,
  file,
  dbl_digits = 2,
  int_format = "0",
  dbl_format = sprintf(sprintf("%%.%sf", dbl_digits), 0),
  show_progress = is_interactive()
)

Arguments

...	one or more data frames / tibbles to export, one per sheet. Named arguments set the sheet name; unnamed arguments use "Sheet{position}".
file	path to the .xlsx file (.xlsx extension added if absent)
dbl_digits	number of decimal places shown for double columns (all digits are stored; this only affects display formatting in Excel)
int_format	Excel number format string for integer columns
dbl_format	Excel number format string for double columns (derived automatically from dbl_digits if not set)
show_progress	whether to show a progress indicator

Details

This function only accepts data frames. To store a complete ir_aggregate_isofiles() result use ir_save_aggregated_data() instead.

Requires the suggested openxlsx package.

Value

the exported data invisibly (the single data frame if one was provided, otherwise the list of data frames), for use in pipes

Examples

if (requireNamespace("openxlsx", quietly = TRUE)) {
  agg <- ir_examples_folder() |>
    ir_find_continuous_flow() |>
    ir_read_isofiles() |>
    ir_aggregate_isofiles()
  ir_export_to_excel(
    metadata = ir_get_metadata(agg),
    traces = ir_get_traces(agg),
    file = file.path(tempdir(), "my_export.xlsx")
  )
}

---

run the isoextract executable on a vector of file paths this is usually not called directly

Description

run the isoextract executable on a vector of file paths this is usually not called directly

Usage

ir_extract_isofiles(
  file_paths,
  pretty_json = FALSE,
  dry_run = FALSE,
  show_progress = is_interactive(),
  show_problems = TRUE
)

ir_get_isoextract_version()

Arguments

file_paths	paths to the isodat file(s), single value or vector of paths. Use ir_find_isofiles() to get files in a folder.
pretty_json	whether to write the JSON output in human-readable pretty-printed format (default: FALSE). Useful for debugging; has no effect on the data read back by ir_read_isofiles(). Note that pretty-printed files are larger than compact ones.
dry_run	whether to run isoextract in "dry run" mode (default: FALSE). In dry run mode the files are parsed to test whether they can be read (a file-compatibility check) but no .json sidecar output is written. Combine with show_problems = TRUE to see which files (if any) cannot be extracted. Note that with dry_run = TRUE, the progress bar does not work as it depends on the JSON output files.
show_progress	whether to show a progress bar, by default always enabled when running interactively e.g. inside Positron or RStudio (and disabled in a notebook), turn off with show_progress = FALSE
show_problems	whether to show problems encountered along the way (rather than just keeping track of them with ir_get_problems()). Set to show_problems = FALSE to turn off the live printout. Either way, all encountered problems can be retrieved with running ir_get_problems() for the returned list

Value

called for its side effect of running isoextract to write a .json sidecar file next to each input file (unless dry_run = TRUE); returns NULL invisibly

Functions

• ir_get_isoextract_version(): return the version of the installed isoextract executable as a numeric_version, or NULL if it is not installed (or does not report a recognizable version)

---

Filter isofiles by measurement type

Description

Convenience wrappers around ir_filter_metadata() that keep only the files of a single measurement type (using the metadata type column): continuous flow ("cf"), dual inlet ("di"), or scan ("scan"). Like ir_filter_metadata() they work on both ir_isofiles (from ir_read_isofiles()) and ir_aggregated_data (from ir_aggregate_isofiles()) objects, cascade to the other datasets, and drop any file whose metadata ends up empty.

Usage

ir_filter_for_continuous_flow(isofiles)

ir_filter_for_dual_inlet(isofiles)

ir_filter_for_scans(isofiles)

Arguments

isofiles

a collection of isofiles from ir_read_isofiles() (ir_isofiles) or datasets aggregated from ir_aggregate_isofiles() (ir_aggregated_data)

Details

Files whose metadata has no type column (e.g. a file that errored during reading) never match and are dropped.

Value

the isofiles object filtered to the requested measurement type

Functions

• ir_filter_for_continuous_flow(): keep only continuous flow files (type == "cf")

• ir_filter_for_dual_inlet(): keep only dual inlet files (type == "di")

• ir_filter_for_scans(): keep only scan files (type == "scan")

---

Find isodat files

Description

Finds isodat files with the specified extensions in one or more folders.

Usage

ir_find_isofiles(
  folder,
  types = c("dxf", "cf", "iarc", "larc", "bch", "imexp", "caf", "did", "scn"),
  pattern = NULL,
  recursive = TRUE
)

ir_find_continuous_flow(folder, pattern = NULL, recursive = TRUE)

ir_find_dual_inlet(folder, pattern = NULL, recursive = TRUE)

ir_find_scans(folder, pattern = NULL, recursive = TRUE)

Arguments

folder	path to a folder with isodat files, or a character vector of folder paths
types	file extensions to include (without leading dot), default is all supported types: c("dxf", "cf", "iarc", "larc", "bch", "imexp", "caf", "did", "scn")
pattern	provide a name pattern to find only specific files
recursive	whether to find files recursively

Value

a sorted character vector of unique paths that correspond to the original data files (without .json suffixes if those are the versions of the files that are present)

Functions

• ir_find_continuous_flow(): finds continuous flow files (.dxf, .cf)

• ir_find_dual_inlet(): finds dual inlet files (.did, .caf)

• ir_find_scans(): finds scan files (.scn)

Examples

ir_find_continuous_flow(system.file("extdata", package = "isoreader2"))
ir_find_dual_inlet(system.file("extdata", package = "isoreader2"))
ir_find_scans(system.file("extdata", package = "isoreader2"))

---

Generate the tibble used by the plotting functions

Description

These helpers build the exact flat tibble that ir_plot_continuous_flow() (ir_generate_traces_tibble()), ir_plot_dual_inlet() (ir_generate_cycles_tibble()), and ir_plot_scans() (ir_generate_scans_tibble()) plot, so it can be inspected or used independently of producing a plot. The dataset is prepared exactly as for the plotting functions (an ir_aggregated_data object has its traces / cycles / scans dataset inner-joined with ⁠$metadata⁠; a plain data frame is used as is), filtered by species, and then split into intensity rows and (optionally) ratio rows, each augmented with three columns:

• trace - the identifier "<species>: <mass>" for intensity rows (e.g. "CO2: 44") or "<species>: <ratio_name>" for ratio rows (e.g. "CO2: 45/44"), always (re)generated and returned as a factor sorted by species and numerical (numerator) mass.

• data_type - "intensity [UNITS]" (e.g. "intensity [mV]") for the intensity rows, or "ratios" for ratio rows.

• value - the value to plot: the intensity for intensity rows, or the (optionally fold-clamped) ratio for ratio rows.

Usage

ir_generate_traces_tibble(dataset, species = NULL, mass = NULL, ratio = NULL)

ir_generate_cycles_tibble(dataset, species = NULL, mass = NULL, ratio = NULL)

ir_generate_scans_tibble(dataset, species = NULL, mass = NULL, ratio = NULL)

Arguments

dataset	an ir_aggregated_data object from ir_aggregate_isofiles() or a plain data frame with the required columns (see the matching plotting function)
species	optional vector to filter to specific species (e.g. "CO2" or c("N2", "CO2")); default NULL keeps all species.
mass	which masses to include as intensity traces: NULL (default) for all masses, a vector (e.g. 44 or c(44, 45)) for specific masses, or a zero-length vector (numeric(0)/character(0)) for none. Note that c() is NULL in R, i.e. all masses.
ratio	which ratios to include (computed with ir_calculate_ratios()): NULL (default) for all available ratios, a character vector of ratio names (e.g. c("45/44", "46/44")) for specific ones, or character(0) for none. Requesting specific ratio names when ratios have not been calculated is an error pointing to ir_calculate_ratios(); with ratio = NULL and no ratios present none are simply added.

Value

a tibble with the prepared data plus the trace, data_type, and value columns described above.

---

Get data frame from aggregated data

Description

Retrieve a specific subset of the aggregated data into a single data frame by specifying which columns to take from each dataset (metadata, traces, cycles, scans, resistors, vendor_data_table) using dplyr::select() syntax. If data from more than one dataset is selected (e.g. some columns from traces AND some from resistors), the datasets are combined with an dplyr::inner_join() using the columns listed in by (only the ones actually in the datasets). Joins that would lead to duplicated data entries (i.e. many-to-many joins) are not allowed and will throw an error to avoid unexpected replications of individual datapoints. If you really want to do such a join, you'll have to do it manually.

Usage

ir_get_data(
  aggregated_data,
  metadata = c("file_name"),
  traces = NULL,
  cycles = NULL,
  scans = NULL,
  resistors = NULL,
  vendor_data_table = NULL,
  by = c("uidx", "analysis", "config", "species", "channel", "mass")
)

ir_get_metadata(aggregated_data, metadata = everything())

ir_get_resistors(
  aggregated_data,
  metadata = c("file_name"),
  by = c("uidx", "analysis")
)

ir_get_traces(
  aggregated_data,
  metadata = c("file_name"),
  by = c("uidx", "analysis")
)

ir_get_cycles(
  aggregated_data,
  metadata = c("file_name"),
  by = c("uidx", "analysis")
)

ir_get_scans(
  aggregated_data,
  metadata = c("file_name"),
  by = c("uidx", "config")
)

ir_get_vendor_data_table(
  aggregated_data,
  metadata = c("file_name"),
  by = c("uidx", "analysis")
)

Arguments

aggregated_data	datasets aggregated from ir_aggregate_isofiles()
metadata	columns to get from the aggregated metadata, all dplyr::select() syntax is supported
traces	columns to get from the aggregated traces, all dplyr::select() syntax is supported
cycles	columns to get from the aggregated cycles, all dplyr::select() syntax is supported
scans	columns to get from the aggregated scans, all dplyr::select() syntax is supported
resistors	columns to get from the aggregated resistors, all dplyr::select() syntax is supported
vendor_data_table	columns to get from the aggregated vendor_data_table, all dplyr::select() syntax is supported
by	character vector of column names used as join keys when combining data from more than one dataset (default covers the standard linking columns; only keys actually present in both datasets are used)

Value

a tibble

Functions

• ir_get_metadata(): shortcut for retrieving all metadata columns (i.e. metadata = dplyr::everything())

• ir_get_resistors(): shortcut for retrieving all resistors columns (i.e. resistors = dplyr::everything()), keyed by the selected metadata

• ir_get_traces(): shortcut for retrieving all traces columns (i.e. traces = dplyr::everything()), keyed by the selected metadata

• ir_get_cycles(): shortcut for retrieving all cycles columns (i.e. cycles = dplyr::everything()), keyed by the selected metadata

• ir_get_scans(): shortcut for retrieving all scans columns (i.e. scans = dplyr::everything()), keyed by the selected metadata

• ir_get_vendor_data_table(): shortcut for retrieving all vendor_data_table columns (i.e. vendor_data_table = dplyr::everything()), keyed by the selected metadata. Only available when aggregated with the "extended" aggregator.

---

Retrieve parsing problems

Description

This function retrieves parsing problems encountered during the reading and processing of files.

This function prints out parsing problems encountered during the reading and processing of files.

Usage

ir_get_problems(obj, strip_ansi = TRUE)

ir_show_problems(obj)

Arguments

obj	data object that holds problems information
strip_ansi	whether to remove ansi characters from the message, yes by default

Value

tibble data frame with a list of problems encountered during processing

---

Get supported file types

Description

Get supported file types

Usage

ir_get_supported_file_types()

Value

a tibble of the file types supported by this package

Examples

ir_get_supported_file_types()

---

Save and load isofiles

Description

ir_save_isofiles() serializes a collection of isofiles read with ir_read_isofiles() to an RDS file using readr::write_rds(), storing the whole ir_isofiles object as-is (including all nested datasets and condition objects) without any changes. ir_load_isofiles() reads the file back with readr::read_rds() and returns the ir_isofiles object exactly as it was saved.

Usage

ir_save_isofiles(isofiles, file)

ir_load_isofiles(file)

Arguments

isofiles	a collection of isofiles from ir_read_isofiles()
file	path to the RDS file (.rds extension added if absent)

Details

This operates at the unaggregated ir_isofiles level. To store an aggregated result instead, use ir_save_aggregated_data() / ir_load_aggregated_data().

Value

ir_save_isofiles() returns isofiles invisibly; ir_load_isofiles() returns an ir_isofiles object.

Functions

• ir_save_isofiles(): save isofiles to an RDS file

• ir_load_isofiles(): load isofiles from an RDS file

---

Filter, mutate, or join the metadata of isofiles

Description

These functions modify the metadata of either an ir_aggregate_isofiles() result (ir_aggregated_data) or a collection of isofiles read with ir_read_isofiles() (ir_isofiles).

Usage

ir_filter_metadata(isofiles, ...)

ir_mutate_metadata(isofiles, ...)

ir_join_metadata(isofiles, y, by)

Arguments

isofiles	datasets aggregated from ir_aggregate_isofiles() (ir_aggregated_data) or a collection of isofiles from ir_read_isofiles() (ir_isofiles)
...	passed to dplyr::filter(), dplyr::mutate(), or dplyr::left_join() respectively
y	data frame to join to the metadata
by	character vector of columns to join by (passed to dplyr::left_join())

Details

For ir_aggregated_data, the operation is applied once to the combined ⁠$metadata⁠ data frame. For ir_filter_metadata(), the filter then cascades to all other datasets: traces, cycles, and scans are filtered by the remaining uidx + analysis combinations; resistors and problems are filtered by the remaining uidx values.

For ir_isofiles, the same operation is instead applied individually to each row (i.e. to each file's own nested datasets), since an ir_isofiles object has no combined metadata to operate on. Within each row, the filter cascade uses whichever linking columns are present (typically analysis). For ir_filter_metadata(), any file whose metadata ends up with 0 rows after the filter is removed from the ir_isofiles collection entirely.

Operating on an unaggregated ir_isofiles object is supported for convenience, but is significantly slower than operating on an ir_aggregated_data result, because the operation has to be carried out separately on every file rather than once on the combined metadata. For anything beyond small collections, prefer aggregating first with ir_aggregate_isofiles() and then applying these functions to the result.

After filtering, columns that are entirely NA across all remaining rows are dropped from every (non-empty) dataset. All three functions also clear the not-aggregated column information (columns present in the source files but not included in the aggregator) from every dataset, since that information is no longer meaningful after the metadata has been modified.

Value

the isofiles object (of the same type as the input) with updated metadata

Functions

• ir_filter_metadata(): filter rows of the metadata (and cascade to the other datasets)

• ir_mutate_metadata(): add or modify columns in the metadata

• ir_join_metadata(): left-join additional columns into the metadata

---

Package options

Description

These options are best set via ir_options() and queried via ir_get_option(). However, the base functions options() and getOption() work as well but require an isoreader2. prefix (the package name and a dot) for the option name. Setting an option to a value of NULL means that the default is used. ir_get_options() is available as an additional convenience function to retrieve a subset of options with a regular expression pattern.

Usage

ir_options(...)

ir_get_options(pattern = NULL)

ir_get_option(x)

Arguments

...	set package options, syntax identical to options()
pattern	to retrieve multiple options (as a list) with a shared pattern
x	name of the specific option to retrieve

Value

ir_options() and ir_get_options() return a named list of option values; ir_get_option() returns the value of the single requested option.

Functions

• ir_options(): set/get option values

• ir_get_options(): get a subset of option values that fit a pattern

• ir_get_option(): retrieve the current value of one option (option must be defined for the package)

Options for the isoreader2 package

• aggregators: data aggregators for pulling data out of raw files. The list of available aggregators is accessible via ir_get_option("aggregators"). Individual aggregators are available via the shortcut helper function ir_get_aggregator("standard"). Register new/overwrite existing aggregators via ir_register_aggregator().

• debug: turn on debug mode

• auto_use_ansi: whether to automatically enable correct rendering of stylized (ansi) output in HTML reports from notebooks that call library(isoir). Can be turned off by calling isoir::ir_options(auto_use_ansi = FALSE) before call library(isoir).

Examples

# All default options
ir_get_options()

---

Plot continuous flow data

Description

Plots chromatographic trace data from an ir_aggregate_isofiles() result or a plain data frame. The data is prepared with ir_generate_traces_tibble() (which, for an ir_aggregated_data object, inner-joins the ⁠$traces⁠ dataset with ⁠$metadata⁠). The plot data must contain species, time.s, mass, and an ⁠intensity.*⁠ column — an error is thrown if any are missing. A trace identifier ("<species>: <mass>") is always regenerated and the plotted value together with a data_type label ("intensity [UNITS]", or "ratios" for ratio rows) are added.

Usage

ir_plot_continuous_flow(
  dataset,
  species = NULL,
  mass = NULL,
  ratio = NULL,
  facet = NULL,
  data_type_as_facet = auto(),
  scales = "free",
  nrow = NULL,
  ncol = 1,
  color = trace,
  linetype = NULL,
  color_values = palette.colors(),
  drop_unused_levels = FALSE,
  scientific = FALSE,
  time_window.s = if (is.null(time_window.min)) NULL else 60 * time_window.min,
  time_window.min = NULL,
  short_time_labels = FALSE,
  n_time_breaks = 5,
  n_y_breaks = 5,
  ...
)

Arguments

dataset	an ir_aggregated_data object from ir_aggregate_isofiles() or a plain data frame with species, time.s, mass, and an ⁠intensity.*⁠ column
species	optional vector to filter the displayed data to specific species (e.g. "CO2" or c("N2", "CO2")); default NULL shows all species.
mass	which masses to include as intensity traces: NULL (default) shows all masses, a vector (e.g. 44 or c(44, 45)) shows specific masses, and a zero-length vector (numeric(0)/character(0)) shows none. Note that c() is NULL in R (i.e. all masses).
ratio	which ratios to additionally include (computed with ir_calculate_ratios()): NULL (default) shows all available ratios, a character vector of ratio names (e.g. c("45/44", "46/44")) shows specific ones, and character(0) shows none. Requesting specific ratio names when ratios have not been calculated is an error pointing to ir_calculate_ratios() (with ratio = NULL and no ratios present, none are simply added). Ratio rows are plotted on the same value axis with data_type = "ratios"; the default facet = data_type (with free scales) separates them from the intensities.
facet	column or expression to facet by (default: NULL, no extra faceting). When data_type is used as a facet row (see data_type_as_facet), a single facet variable becomes the facet_grid column (data_type ~ facet) and a NULL facet gives data_type ~ .. Otherwise a plain column or expression (e.g. file_name or paste(species, mass)) is faceted with ggplot2::facet_wrap(), and a two-sided formula (e.g. species ~ mass) is faceted with ggplot2::facet_grid(). Set to NULL to suppress faceting.
data_type_as_facet	whether the data_type column (intensities vs ratios) is used as the ggplot2::facet_grid() row variable: auto() (default) uses it only when more than one data type is present; TRUE always uses it; FALSE never does. When used, the y axis label is dropped (the facet strip provides it) and the facet becomes data_type ~ . (a NULL facet) or data_type ~ facet (a single-variable facet). It is ignored when facet is a two-sided formula (a warning is issued if data_type_as_facet = TRUE is combined with a formula facet, since the two are mutually exclusive).
scales	whether facet scales should be "free" (default), "fixed", "free_x", or "free_y"; passed on to ggplot2::facet_wrap() / ggplot2::facet_grid().
nrow, ncol	number of rows and columns of facet panels (nrow default NULL lets ggplot2 choose; ncol default 1 stacks the panels in a single column). Only applies when facet is a single variable or expression (faceted with ggplot2::facet_wrap()); ignored when facet is a formula (faceted with ggplot2::facet_grid()), with a warning if you set them explicitly.
color	column or expression for the colour aesthetic (default: trace, the per-species/mass trace identifier, e.g. "CO2: 44"). When colouring by trace, traces that share the same species and (numerator) mass are given the same colour, so an intensity trace ("N2: 29") and its ratio traces ("N2: 29/28") match.
linetype	column or expression for the linetype aesthetic (default: NULL, i.e. no linetype aesthetic)
color_values	named or unnamed character vector of colours passed to ggplot2::scale_color_manual(), or NULL to use the ggplot2 default colour palette (default: palette.colors())
drop_unused_levels	whether to drop unused trace factor levels (e.g. traces that are absent after zooming to a window) from the colour scale and legend. Default FALSE keeps every level so the colour mapping stays stable across subsets of the same dataset; set to TRUE to show only the levels actually present in the plotted data.
scientific	whether to format y axis labels in scientific notation (default: FALSE)
time_window.s, time_window.min	optional numeric vector of length 2 giving the time axis display window c(min, max), either in seconds (time_window.s) or in minutes (time_window.min, converted to seconds internally — the function always works in seconds). Provide at most one; if both are given, time_window.s is used. Must have min < max. The data point just outside each edge of the window is retained so the clipped lines interpolate correctly across the window boundaries and y autoscales correctly at the edges; ggplot2::coord_cartesian() clips the display. A window that contains no data points of its own is allowed (the line is drawn between the bracketing points). Default NULL (both) shows the full time range.
short_time_labels	whether to use compact time axis labels with no space between value and unit and abbreviated units (hr, m, s) (default: FALSE)
n_time_breaks	desired number of time axis tick marks (default: 5)
n_y_breaks	desired number of y axis tick marks (default: 5)
...	additional arguments passed on to ggplot2::facet_wrap() or ggplot2::facet_grid() (e.g. labeller)

Value

a ggplot object with ir_default_theme() applied. To customize the plot, add ggplot2 layers on top (e.g. + ggplot2::theme(...) or + ggplot2::labs(...)); attach ggplot2 with library(ggplot2) first.

---

Plot dual inlet cycle data

Description

Plots cycle data from an ir_aggregate_isofiles() result or a plain data frame. The data is prepared with ir_generate_cycles_tibble() (which, for an ir_aggregated_data object, inner-joins the ⁠$cycles⁠ dataset with ⁠$metadata⁠). The plot data must contain species, cycle, type, mass, and an ⁠intensity.*⁠ column — an error is thrown if any are missing. A trace identifier ("<species>: <mass>") is always regenerated and the plotted value together with a data_type label ("intensity [UNITS]", or "ratios" for ratio rows) are added.

Usage

ir_plot_dual_inlet(
  dataset,
  species = NULL,
  mass = NULL,
  ratio = NULL,
  facet = NULL,
  data_type_as_facet = auto(),
  scales = "free",
  nrow = NULL,
  ncol = 1,
  color = trace,
  shape = type,
  linetype = NULL,
  color_values = palette.colors(),
  drop_unused_levels = FALSE,
  scientific = FALSE,
  cycle_window = NULL,
  n_y_breaks = 5,
  ...
)

Arguments

dataset	an ir_aggregated_data object from ir_aggregate_isofiles() or a plain data frame with species, cycle, type, mass, and an ⁠intensity.*⁠ column
species	optional vector to filter the displayed data to specific species (e.g. "CO2" or c("N2", "CO2")); default NULL shows all species.
mass	which masses to include as intensity traces: NULL (default) shows all masses, a vector (e.g. 44 or c(44, 45)) shows specific masses, and a zero-length vector (numeric(0)/character(0)) shows none. Note that c() is NULL in R (i.e. all masses).
ratio	which ratios to additionally include (computed with ir_calculate_ratios()): NULL (default) shows all available ratios, a character vector of ratio names (e.g. c("45/44", "46/44")) shows specific ones, and character(0) shows none. Requesting specific ratio names when ratios have not been calculated is an error pointing to ir_calculate_ratios() (with ratio = NULL and no ratios present, none are simply added). Ratio rows are plotted on the same value axis with data_type = "ratios"; the default facet = data_type (with free scales) separates them from the intensities.
facet	column or expression to facet by (default: NULL, no extra faceting). When data_type is used as a facet row (see data_type_as_facet), a single facet variable becomes the facet_grid column (data_type ~ facet) and a NULL facet gives data_type ~ .. Otherwise a plain column or expression (e.g. file_name or paste(species, mass)) is faceted with ggplot2::facet_wrap(), and a two-sided formula (e.g. species ~ mass) is faceted with ggplot2::facet_grid(). Set to NULL to suppress faceting.
data_type_as_facet	whether the data_type column (intensities vs ratios) is used as the ggplot2::facet_grid() row variable: auto() (default) uses it only when more than one data type is present; TRUE always uses it; FALSE never does. When used, the y axis label is dropped (the facet strip provides it) and the facet becomes data_type ~ . (a NULL facet) or data_type ~ facet (a single-variable facet). It is ignored when facet is a two-sided formula (a warning is issued if data_type_as_facet = TRUE is combined with a formula facet, since the two are mutually exclusive).
scales	whether facet scales should be "free" (default), "fixed", "free_x", or "free_y"; passed on to ggplot2::facet_wrap() / ggplot2::facet_grid().
nrow, ncol	number of rows and columns of facet panels (nrow default NULL lets ggplot2 choose; ncol default 1 stacks the panels in a single column). Only applies when facet is a single variable or expression (faceted with ggplot2::facet_wrap()); ignored when facet is a formula (faceted with ggplot2::facet_grid()), with a warning if you set them explicitly.
color	column or expression for the colour aesthetic (default: trace, the per-species/mass trace identifier, e.g. "CO2: 44"). When colouring by trace, traces that share the same species and (numerator) mass are given the same colour, so an intensity trace ("CO2: 45") and its ratio traces ("CO2: 45/44") match.
shape	column or expression for the point shape aesthetic (default: type, distinguishing "standard" from "sample" cycles)
linetype	column or expression for the linetype aesthetic (default: NULL, i.e. no linetype aesthetic)
color_values	named or unnamed character vector of colours passed to ggplot2::scale_color_manual(), or NULL to use the ggplot2 default colour palette (default: palette.colors())
drop_unused_levels	whether to drop unused trace factor levels (e.g. traces that are absent after zooming to a window) from the colour scale and legend. Default FALSE keeps every level so the colour mapping stays stable across subsets of the same dataset; set to TRUE to show only the levels actually present in the plotted data.
scientific	whether to format y axis labels in scientific notation (default: FALSE)
cycle_window	optional numeric vector of length 2 giving the cycle axis display window c(min, max) (must have min < max). The data point just outside each edge of the window is retained so the clipped lines interpolate correctly across the window boundaries and y autoscales correctly at the edges; ggplot2::coord_cartesian() clips the display. A window that contains no data points of its own is allowed (the line is drawn between the bracketing points). Default NULL shows all cycles.
n_y_breaks	desired number of y axis tick marks (default: 5)
...	additional arguments passed on to ggplot2::facet_wrap() or ggplot2::facet_grid() (e.g. labeller)

Value

a ggplot object with ir_default_theme() applied. To customize the plot, add ggplot2 layers on top (e.g. + ggplot2::theme(...) or + ggplot2::labs(...)); attach ggplot2 with library(ggplot2) first.

---

Plot scan data

Description

Plots scan data from an ir_aggregate_isofiles() result or a plain data frame. The data is prepared with ir_generate_scans_tibble() (which, for an ir_aggregated_data object, inner-joins the ⁠$scans⁠ dataset with ⁠$metadata⁠). The plot data must contain species, x, scan_type, x_units, mass, and an ⁠intensity.*⁠ column — an error is thrown if any are missing. A trace identifier ("<species>: <mass>") is always regenerated and the plotted value together with a data_type label ("intensity [UNITS]", or "ratios" for ratio rows) are added. scan_type and x_units are combined for the x axis label.

Usage

ir_plot_scans(
  dataset,
  scan_type = NULL,
  species = NULL,
  mass = NULL,
  ratio = NULL,
  facet = NULL,
  data_type_as_facet = auto(),
  scales = "free",
  nrow = NULL,
  ncol = 1,
  color = trace,
  linetype = NULL,
  color_values = palette.colors(),
  drop_unused_levels = FALSE,
  scientific = FALSE,
  x_window = NULL,
  n_x_breaks = 5,
  n_y_breaks = 5,
  ...
)

Arguments

dataset	an ir_aggregated_data object from ir_aggregate_isofiles() or a plain data frame with species, x, scan_type, x_units, mass, and an ⁠intensity.*⁠ column
scan_type	which scan type to plot (e.g. "high voltage"). Required when the data contains more than one scan type; an error lists the available types. If the data contains only one scan type, the parameter must either be NULL or match that type exactly.
species	optional vector to filter the displayed data to specific species (e.g. "CO2" or c("N2", "CO2")); default NULL shows all species.
mass	which masses to include as intensity traces: NULL (default) shows all masses, a vector (e.g. 44 or c(44, 45)) shows specific masses, and a zero-length vector (numeric(0)/character(0)) shows none. Note that c() is NULL in R (i.e. all masses).
ratio	which ratios to additionally include (computed with ir_calculate_ratios()): NULL (default) shows all available ratios, a character vector of ratio names (e.g. c("45/44", "46/44")) shows specific ones, and character(0) shows none. Requesting specific ratio names when ratios have not been calculated is an error pointing to ir_calculate_ratios() (with ratio = NULL and no ratios present, none are simply added). Ratio rows are plotted on the same value axis with data_type = "ratios"; the default facet = data_type (with free scales) separates them from the intensities.
facet	column or expression to facet by (default: NULL, no extra faceting). When data_type is used as a facet row (see data_type_as_facet), a single facet variable becomes the facet_grid column (data_type ~ facet) and a NULL facet gives data_type ~ .. Otherwise a plain column or expression (e.g. file_name or paste(species, mass)) is faceted with ggplot2::facet_wrap(), and a two-sided formula (e.g. species ~ mass) is faceted with ggplot2::facet_grid(). Set to NULL to suppress faceting.
data_type_as_facet	whether the data_type column (intensities vs ratios) is used as the ggplot2::facet_grid() row variable: auto() (default) uses it only when more than one data type is present; TRUE always uses it; FALSE never does. When used, the y axis label is dropped (the facet strip provides it) and the facet becomes data_type ~ . (a NULL facet) or data_type ~ facet (a single-variable facet). It is ignored when facet is a two-sided formula (a warning is issued if data_type_as_facet = TRUE is combined with a formula facet, since the two are mutually exclusive).
scales	whether facet scales should be "free" (default), "fixed", "free_x", or "free_y"; passed on to ggplot2::facet_wrap() / ggplot2::facet_grid().
nrow, ncol	number of rows and columns of facet panels (nrow default NULL lets ggplot2 choose; ncol default 1 stacks the panels in a single column). Only applies when facet is a single variable or expression (faceted with ggplot2::facet_wrap()); ignored when facet is a formula (faceted with ggplot2::facet_grid()), with a warning if you set them explicitly.
color	column or expression for the colour aesthetic (default: trace, the per-species/mass trace identifier, e.g. "CO2: 44"). When colouring by trace, traces that share the same species and (numerator) mass are given the same colour, so an intensity trace ("N2: 29") and its ratio traces ("N2: 29/28") match.
linetype	column or expression for the linetype aesthetic (default: NULL, i.e. no linetype aesthetic)
color_values	named or unnamed character vector of colours passed to ggplot2::scale_color_manual(), or NULL to use the ggplot2 default colour palette (default: palette.colors())
drop_unused_levels	whether to drop unused trace factor levels (e.g. traces that are absent after zooming to a window) from the colour scale and legend. Default FALSE keeps every level so the colour mapping stays stable across subsets of the same dataset; set to TRUE to show only the levels actually present in the plotted data.
scientific	whether to format y axis labels in scientific notation (default: FALSE)
x_window	optional numeric vector of length 2 giving the x axis display window c(min, max) (must have min < max). The data point just outside each edge of the window is retained so the clipped lines interpolate correctly across the window boundaries and y autoscales correctly at the edges; ggplot2::coord_cartesian() clips the display. A window that contains no data points of its own is allowed (the line is drawn between the bracketing points). Default NULL shows the full x range.
n_x_breaks	desired number of x axis tick marks (default: 5)
n_y_breaks	desired number of y axis tick marks (default: 5)
...	additional arguments passed on to ggplot2::facet_wrap() or ggplot2::facet_grid() (e.g. labeller)

Value

a ggplot object with ir_default_theme() applied. To customize the plot, add ggplot2 layers on top (e.g. + ggplot2::theme(...) or + ggplot2::labs(...)); attach ggplot2 with library(ggplot2) first.

---

Read isotope data files

Description

Read isotope data files

Usage

ir_read_isofiles(
  file_paths,
  show_progress = is_interactive(),
  show_problems = TRUE,
  reextract = FALSE
)

Arguments

file_paths	paths to the isodat file(s), single value or vector of paths. Use ir_find_isofiles() to get files in a folder.
show_progress	whether to show a progress bar, by default always enabled when running interactively e.g. inside Positron or RStudio (and disabled in a notebook), turn off with show_progress = FALSE
show_problems	whether to show problems encountered along the way (rather than just keeping track of them with ir_get_problems()). Set to show_problems = FALSE to turn off the live printout. Either way, all encountered problems can be retrieved with running ir_get_problems() for the returned list
reextract	whether to re-extract files (uses isoextract to read files from scratch); if FALSE (default) only files that have not been extracted yet (or whose previous extraction is out of date) are extracted. Use ir_extract_isofiles() directly for finer control over extraction (e.g. pretty_json or dry_run).

Value

a tibble data frame (an ir_isofiles object) where each row holds the file path and nested tibbles of datasets extracted from the isodat files. Use ir_aggregate_isofiles() to aggregate data safely across files. Multiple such collections can be combined into one with a simple c() (see c.ir_isofiles()).

See Also

c.ir_isofiles() to combine collections of isofiles

---

Dynamic data aggregator

Description

These functions allow definition of custom data aggregators for processing data extracted from isofiles. An aggregator is run on each imported file and pulls together the relevant data users are interested in while making sure data formats are correct so that the aggregated data can be merged across several imported files for fast downstream processing.

Usage

ir_start_aggregator(name)

ir_add_to_aggregator(
  aggregator,
  dataset = c("metadata", "traces", "cycles", "scans", "resistors", "vendor_data_table"),
  column,
  source = column,
  default = NA,
  cast = "as.character",
  regexp = FALSE,
  func = NULL,
  args = NULL
)

ir_register_aggregator(aggregator, name = attr(aggregator, "name"))

ir_get_aggregator(name)

Arguments

name	a descriptive name for the aggregator. This name is automatically used as the default name when registering the aggregator via ir_register_aggregator().
aggregator	the aggregator table generated by ir_start_aggregator() or passed from a previous call to ir_add_to_aggregator() for constructing the entire aggregator by piping
dataset	the name of the dataset to aggregate from, by default "metadata" which is by far the most common aggregator to work with
column	the name of the column in which data should be stored
source	single character column name or vector of column names (if alternatives could be the source) where in the dataset to find data for the column. If a vector of multiple column names is provided (e.g. source = c("a1", "a2")), the first column name that's found during processing of a dataset will be used and passed to the function defined in func (if any) and then the one defined in cast. To provide multiple parameters from the data to func, define a list instead of a vector source = list("a", "b", "c") or if multiple alternative columns can be the source for any of the arguments, define as source = list(c("a1", "a2"), "b", c("c1", "c2", "c3"))
default	the default value if no source columns can be found or another error is encountered during aggregation. Note that the default value will also be processed with the function in cast to make sure it has the correct data type.
cast	what to cast the values of the resulting column to, most commonly "as.character", "as.integer", "as.numeric", or "as.factor". This is required to ensure all aggregated values have the correct data type.
regexp	whether source column names should be interpreted as a regular expressions for the purpose of finding the relevant column(s). Note if regexp = TRUE, the search for the source column always becomes case-insensitive so this can also be used for a direct match of a source column whose upper/lower casing can be unreliable. If a column is matched by a regexp and also by a direct aggregator rule, the direct aggregator rule takes precedence.
func	name of a processing function to apply before casting the value with the cast function. This is optional and can be used to conduct more elaborate preprocessing of a data or combining data from multiple source columns in the correct way (e.g. pasting together from multiple columns).
args	an optional list of arguments to pass to the func in addition to the values coming from the source column(s)

Value

an aggregator tibble

Functions

• ir_start_aggregator(): starts the aggregator

• ir_add_to_aggregator(): add additional column to aggregate data for. Overwrites an existing aggregator entry for the same dataset and column if it already exists.

• ir_register_aggregator(): register an aggregator in the isoreader2 options so it can be retrieved with ir_get_aggregator()

• ir_get_aggregator(): retrieve a registered aggregator (get all aggregators with ir_get_option("aggregators"))

---

Save and load aggregated isofile data

Description

ir_save_aggregated_data() serializes an ir_aggregate_isofiles() result to a parquet file. Empty datasets (no columns) are dropped. The condition column of problems is set to NULL per row because R condition objects cannot be stored in parquet. ir_load_aggregated_data() reads the file back and returns an ir_aggregated_data object.

Usage

ir_save_aggregated_data(aggregated_data, file)

ir_load_aggregated_data(file)

Arguments

aggregated_data	datasets aggregated from ir_aggregate_isofiles()
file	path to the parquet file (.parquet extension added if absent)

Details

Requires the suggested arrow package.

Value

ir_save_aggregated_data() returns aggregated_data invisibly; ir_load_aggregated_data() returns an ir_aggregated_data object.

Functions

• ir_save_aggregated_data(): save aggregated data to a parquet file

• ir_load_aggregated_data(): load aggregated data from a parquet file

---