Introduction

Isoreader supports several dual inlet IRMS data formats. This vignette shows some of the functionality for dual inlet data files. For additional information on operations more generally (caching, combining read files, data export, etc.), please consult the operations vignette. For details on downstream data processing and visualization, see the isoprocessor package.

# load isoreader package
library(isoreader)

Reading files

Reading dual inlet files is as simple as passing one or multiple file or folder paths to the iso_read_dual_inlet() function. If folders are provided, any files that have a recognized continuous flow file extensions within those folders will be processed (e.g. all .did and .caf). Here we read several files that are bundled with the package as examples (and whose paths can be retrieved using the iso_get_reader_example() function).

# all available examples
iso_get_reader_examples() %>% knitr::kable()

filename	type	software	description
continuous_flow_example.cf	continuous flow	Isodat	Continuous Flow file format (older)
continuous_flow_example.dxf	continuous flow	Isodat	Continuous Flow file format (newer)
continuous_flow_example.iarc	continuous flow	ionOS	Continuous Flow data archive
dual_inlet_example.caf	dual inlet	Isodat	Dual Inlet file format (older)
dual_inlet_example.did	dual inlet	Isodat	Dual Inlet file format (newer)
dual_inlet_nu_example.txt	dual inlet	Nu	Dual Inlet file format
background_scan_example.scn	scan	Isodat	Scan file format
full_scan_example.scn	scan	Isodat	Scan file format
peak_shape_scan_example.scn	scan	Isodat	Scan file format
time_scan_example.scn	scan	Isodat	Scan file format

# read dual inlet examples
di_files <-
  iso_read_dual_inlet(
    iso_get_reader_example("dual_inlet_example.did"),
    iso_get_reader_example("dual_inlet_example.caf"),
    iso_get_reader_example("dual_inlet_nu_example.txt"),
    nu_masses = 49:44
  )
#> Info: preparing to read 3 data files...
#> Info: reading file 'dual_inlet_example.did' with '.did' reader...
#> Info: reading file 'dual_inlet_example.caf' with '.caf' reader...
#> Info: reading file 'dual_inlet_nu_example.txt' with '.txt' reader...
#> Info: finished reading 3 files in 3.95 secs

File summary

The di_files variable now contains a set of isoreader objects, one for each file. Take a look at what information was retrieved from the files using the iso_get_data_summary() function.

di_files %>% iso_get_data_summary() %>% knitr::kable()
#> Info: aggregating data summary from 3 data file(s)

file_id	raw_data	file_info	method_info	vendor_data_table	file_path
dual_inlet_example.did	7 cycles, 6 ions (44,45,46,47,48,49)	16 entries	standards, resistors	7 rows, 8 columns	dual_inlet_example.did
dual_inlet_example.caf	8 cycles, 6 ions (44,45,46,47,48,49)	22 entries	standards, resistors	8 rows, 9 columns	dual_inlet_example.caf
dual_inlet_nu_example.txt	82 cycles, 6 ions (44,45,46,47,48,49)	9 entries	no method info	no vendor data table	dual_inlet_nu_example.txt

Problems

In case there was any trouble with reading any of the files, the following functions provide an overview summary as well as details of all errors and warnings, respectively. The examples here contain no errors but if you run into any unexpected file read problems, please file a bug report in the isoreader issue tracker.

di_files %>% iso_get_problems_summary() %>% knitr::kable()

file_id	error	warning

di_files %>% iso_get_problems() %>% knitr::kable()

file_id	type	func	details

File Information

Detailed file information can be aggregated for all isofiles using the iso_get_file_info() function which supports the full select syntax of the dplyr package to specify which columns are of interest (by default, all file information is retrieved). Additionally, file information from different file formats can be renamed to the same column name for easy of downstream processing. The following provides a few examples for how this can be used (the names of the interesting info columns may vary between different file formats):

# all file information
di_files %>% iso_get_file_info(select = c(-file_root)) %>% knitr::kable()
#> Info: aggregating file info from 3 data file(s), selecting info columns 'c(-file_root)'

file_id	file_path	file_subpath	file_datetime	file_size	Line	Peak Center	Pressadjust	Background	Identifier 1	Identifier 2	Analysis	Method	measurement_info	MS_integration_time.s	Reference Refill	Weight [mg]	Sample	Comment	Preparation	Pre Script	Post Script	Sample Name	Sample Weight	Method File Name
dual_inlet_example.did	dual_inlet_example.did	NA	2014-10-27 05:23:54	134446	158	1	1	1	CIT Carrara	13	49077	CO2_multiply_16V.met	Peak Center found at [61032] , Background: 8.87 mV,11.31 mV,12.98 mV,6.40 mV,1.90 mV,5.88 mV (old253), PressAdjust: L: 15972.5 R: 15971.6 ( Manual Adjustment )	26	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.caf	dual_inlet_example.caf	NA	2017-07-03 16:57:57	651704	1	NA	NA	NA	2H6	CARBO IIIUvU_Clump.met	16068	CARBO IIIUvU_Clump.met	NA	26	NA	113	9	NA	NA	NA	NA	NA	NA	NA
dual_inlet_nu_example.txt	dual_inlet_nu_example.txt	NA	2017-02-21 10:46:17	309491	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	ETH-01	3480	C:Stable2 4-20-8-20.rdf

# select file information
di_files %>%
  iso_get_file_info(
    select = c(
      # rename sample id columns from the different file types to a new ID column
      ID = `Identifier 1`, ID = `Sample Name`,
      # select columns without renaming
      Analysis, Method, `Peak Center`,
      # select the time stamp and rename it to `Date & Time`
      `Date & Time` = file_datetime,
      # rename weight columns from the different file types
      `Sample Weight`, `Sample Weight` = `Weight [mg]`
    ),
    # explicitly allow for file specific rename (for the new ID column)
    file_specific = TRUE
  ) %>% knitr::kable()
#> Info: aggregating file info from 3 data file(s), selecting info columns 'c(ID = `Identifier 1`, ID = `Sample Name`, Analysis, Method, `Peak Center`, `Date & Time` = file_datetime, `Sample Weight`, `Sample Weight` = `Weight [mg]`)'

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight
dual_inlet_example.did	CIT Carrara	49077	CO2_multiply_16V.met	1	2014-10-27 05:23:54	NA
dual_inlet_example.caf	2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113
dual_inlet_nu_example.txt	ETH-01	NA	NA	NA	2017-02-21 10:46:17	3480

Select/Rename

Rather than retrieving specific file info columns using the above example of iso_get_file_info(select = ...), these information can also be modified across an entire collection of isofiles using the iso_select_file_info() and iso_rename_file_info() functions. For example, the above example could be similarly achieved with the following use of iso_select_file_info():

# select + rename specific file info columns
di_files2 <- di_files %>%
  iso_select_file_info(
    ID = `Identifier 1`, ID = `Sample Name`, Analysis, Method,
    `Peak Center`, `Date & Time` = file_datetime,
    `Sample Weight`, `Sample Weight` = `Weight [mg]`,
    file_specific = TRUE
  )
#> Info: selecting/renaming the following file info:
#>  - for 1 file(s): 'file_id', 'Identifier 1'->'ID', 'Analysis', 'Method', 'Peak Center', 'file_datetime'->'Date & Time'
#>  - for 1 file(s): 'file_id', 'Identifier 1'->'ID', 'Analysis', 'Method', 'Peak Center', 'file_datetime'->'Date & Time', 'Weight [mg]'->'Sample Weight'
#>  - for 1 file(s): 'file_id', 'Sample Name'->'ID', 'file_datetime'->'Date & Time', 'Sample Weight'

# fetch all file info
di_files2 %>% iso_get_file_info() %>% knitr::kable()
#> Info: aggregating file info from 3 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight
dual_inlet_example.did	CIT Carrara	49077	CO2_multiply_16V.met	1	2014-10-27 05:23:54	NA
dual_inlet_example.caf	2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113
dual_inlet_nu_example.txt	ETH-01	NA	NA	NA	2017-02-21 10:46:17	3480

Filter

Any collection of isofiles can also be filtered based on the available file information using the function iso_filter_files. This function can operate on any column available in the file information and supports full dplyr syntax.

# find files that have 'CIT' in the new ID field
di_files2 %>% iso_filter_files(grepl("CIT", ID)) %>%
  iso_get_file_info() %>%
  knitr::kable()
#> Info: applying file filter, keeping 1 of 3 files
#> Info: aggregating file info from 1 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time
dual_inlet_example.did	CIT Carrara	49077	CO2_multiply_16V.met	1	2014-10-27 05:23:54


# find files that were run in 2017
di_files2 %>%
  iso_filter_files(`Date & Time` > "2017-01-01" & `Date & Time` < "2018-01-01") %>%
  iso_get_file_info() %>%
  knitr::kable()
#> Info: applying file filter, keeping 2 of 3 files
#> Info: aggregating file info from 2 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight
dual_inlet_example.caf	2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113
dual_inlet_nu_example.txt	ETH-01	NA	NA	NA	2017-02-21 10:46:17	3480

Mutate

The file information in any collection of isofiles can also be mutated using the function iso_mutate_file_info. This function can introduce new columns and operate on/overwrite any existing columns available in the file information (even if it does not exist in all files) and supports full dplyr syntax. It can also be used in conjunction with iso_with_unit to generate values with implicit units.

di_files3 <- di_files2 %>%
  iso_mutate_file_info(
    # update existing column
    ID = paste("ID:", ID),
    # introduce new column
    `Run in 2017?` = `Date & Time` > "2017-01-01" & `Date & Time` < "2018-01-01",
    # parse weight as a number and turn into a column with units
    `Sample Weight` = `Sample Weight` %>% parse_number() %>% iso_with_units("mg")
  )
#> Info: mutating file info for 3 data file(s)

di_files3 %>%
  iso_get_file_info() %>%
  iso_make_units_explicit() %>%
  knitr::kable()
#> Info: aggregating file info from 3 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight [mg]	Run in 2017?
dual_inlet_example.did	ID: CIT Carrara	49077	CO2_multiply_16V.met	1	2014-10-27 05:23:54	NA	FALSE
dual_inlet_example.caf	ID: 2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113	TRUE
dual_inlet_nu_example.txt	ID: ETH-01	NA	NA	NA	2017-02-21 10:46:17	3480	TRUE

Add

Additionally, a wide range of new file information can be added in the form of a data frame with any number of columns (usually read from a comma-separated-value/csv file or an Excel/xlsx file) using the function iso_add_file_info and specifying which existing file information should be used to merge in the new information. It is similar to dplyr’s left_join but with additional safety checks and the possibility to join the new information sequentially as illustrated below.

# this kind of information data frame is frequently read in from a csv or xlsx file
new_info <-
  dplyr::bind_rows(
    # new information based on new vs. old samples
    dplyr::tribble(
      ~Analysis, ~`Run in 2017?`,  ~process,  ~info,
       NA,       TRUE,              "yes",     "2017 runs",
       NA,       FALSE,             "yes",     "other runs"
    ),
    # new information for a single specific file
    dplyr::tribble(
      ~Analysis, ~process,  ~note,
       "16068",   "no",      "did not inject properly"
    )
  )
new_info %>% knitr::kable()

Analysis	Run in 2017?	process	info	note
NA	TRUE	yes	2017 runs	NA
NA	FALSE	yes	other runs	NA
16068	NA	no	NA	did not inject properly


# adding it to the isofiles
di_files3 %>%
  iso_add_file_info(new_info, by1 = "Run in 2017?", by2 = "Analysis") %>%
  iso_get_file_info(select = !!names(new_info)) %>%
  knitr::kable()
#> Info: adding new file information ('process', 'info', 'note') to 3 data file(s), joining by 'Run in 2017?' then 'Analysis'...
#>  - 'Run in 2017?' join: 2/2 new info rows matched 3/3 data files - 1 of these was/were also matched by subsequent joins which took precedence
#>  - 'Analysis' join: 1/1 new info rows matched 1/3 data files
#> Info: aggregating file info from 3 data file(s), selecting info columns 'Analysis', 'Run in 2017?', 'process', 'info', 'note'

file_id	Analysis	Run in 2017?	process	info	note
dual_inlet_example.did	49077	FALSE	yes	other runs	NA
dual_inlet_example.caf	16068	TRUE	no	NA	did not inject properly
dual_inlet_nu_example.txt	NA	TRUE	yes	2017 runs	NA

Parse

Most file information is initially read as text to avoid cumbersome specifications during the read process and compatibility issues between different IRMS file formats. However, many file info columns are not easily processed as text. The isoreader package therefore provides several parsing and data extraction functions to facilitate processing the text-based data (some via functionality implemented by the readr package). See code block below for examples. For a complete overview, see the ?extract_data and ?iso_parse_file_info documentation.

# use parsing and extraction in iso_mutate_file_info
di_files2 %>%
  iso_mutate_file_info(
    # change type of Peak Center to logical
    `Peak Center` = parse_logical(`Peak Center`),
    # retrieve first word of Method column
    Method_1st = extract_word(Method),
    # retrieve second word of Method column
    Method_2nd = extract_word(Method, 2),
    # retrieve file extension from the file_id using regular expression
    extension = extract_substring(file_id, "\\.(\\w+)$", capture_bracket = 1)
  ) %>%
  iso_get_file_info(select = c(extension, `Peak Center`, matches("Method"))) %>%
  knitr::kable()
#> Info: mutating file info for 3 data file(s)
#> Info: aggregating file info from 3 data file(s), selecting info columns 'c(extension, `Peak Center`, matches("Method"))'

file_id	extension	Peak Center	Method	Method_1st	Method_2nd
dual_inlet_example.did	did	TRUE	CO2_multiply_16V.met	CO2	multiply
dual_inlet_example.caf	caf	NA	CARBO IIIUvU_Clump.met	CARBO	IIIUvU
dual_inlet_nu_example.txt	txt	NA	NA	NA	NA


# use parsing in iso_filter_file_info
di_files2 %>%
  iso_filter_files(parse_integer(Analysis) > 1500) %>%
  iso_get_file_info() %>%
  knitr::kable()
#> Info: applying file filter, keeping 2 of 3 files
#> Info: aggregating file info from 2 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight
dual_inlet_example.did	CIT Carrara	49077	CO2_multiply_16V.met	1	2014-10-27 05:23:54	NA
dual_inlet_example.caf	2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113


# use iso_parse_file_info for simplified parsing of column data types
di_files2 %>%
  iso_parse_file_info(
    integer = Analysis,
    number = `Sample Weight`,
    logical = `Peak Center`
  ) %>%
  iso_get_file_info() %>%
  knitr::kable()
#> Info: parsing 3 file info columns for 3 data file(s):
#>  - to integer: 'Analysis'
#>  - to logical: 'Peak Center'
#>  - to number: 'Sample Weight'
#> Info: aggregating file info from 3 data file(s)

file_id	ID	Analysis	Method	Peak Center	Date & Time	Sample Weight
dual_inlet_example.did	CIT Carrara	49077	CO2_multiply_16V.met	TRUE	2014-10-27 05:23:54	NA
dual_inlet_example.caf	2H6	16068	CARBO IIIUvU_Clump.met	NA	2017-07-03 16:57:57	113
dual_inlet_nu_example.txt	ETH-01	NA	NA	NA	2017-02-21 10:46:17	3480

Resistors

Additionally, some IRMS data files contain resistor information that are useful for downstream calculations (see e.g. section on signal conversion later in this vignette):

di_files %>% iso_get_resistors() %>% knitr::kable()
#> Info: aggregating resistors info from 3 data file(s)

file_id	cup	R.Ohm	mass
dual_inlet_example.did	1	3.000000e+08	44
dual_inlet_example.did	2	3.000000e+10	45
dual_inlet_example.did	3	1.000000e+11	46
dual_inlet_example.did	4	1.000000e+12	47
dual_inlet_example.did	5	5.000000e+11	48
dual_inlet_example.did	6	1.000000e+12	49
dual_inlet_example.caf	1	2.970297e+08	44
dual_inlet_example.caf	2	1.500000e+10	45
dual_inlet_example.caf	3	5.000000e+10	46
dual_inlet_example.caf	4	5.000000e+11	47
dual_inlet_example.caf	5	9.900990e+09	48
dual_inlet_example.caf	6	5.000000e+11	49

Reference values

As well as isotopic reference values for the different gases:

# reference delta values without ratio values
di_files %>% iso_get_standards(file_id:reference) %>% knitr::kable()
#> Info: aggregating standards info from 3 data file(s)

file_id	standard	gas	delta_name	delta_value	reference
dual_inlet_example.did	Caltech-1960C	CO2	d 13C/12C	-3.56	VPDB
dual_inlet_example.did	Caltech-1960C	CO2	d 18O/16O	25.01	VSMOW
dual_inlet_example.caf	CO2clump tank	CO2	d 13C/12C	-2.82	VPDB
dual_inlet_example.caf	CO2clump tank	CO2	d 18O/16O	-4.67	VPDB
dual_inlet_example.caf	CO2clump tank	CO2	d 47CO2/44CO2	0.00	None
dual_inlet_example.caf	CO2clump tank	CO2	d 48CO2/44CO2	0.00	None
dual_inlet_example.caf	CO2clump tank	CO2	d 49CO2/44CO2	0.00	None

# reference values with ratios
di_files %>% iso_get_standards() %>% knitr::kable()
#> Info: aggregating standards info from 3 data file(s)

file_id	standard	gas	delta_name	delta_value	reference	element	ratio_name	ratio_value
dual_inlet_example.did	Caltech-1960C	CO2	d 13C/12C	-3.56	VPDB	C	R 13C/12C	0.0111802
dual_inlet_example.did	Caltech-1960C	CO2	d 13C/12C	-3.56	VPDB	O	R 18O/16O	0.0020672
dual_inlet_example.did	Caltech-1960C	CO2	d 13C/12C	-3.56	VPDB	O	R 17O/16O	0.0003860
dual_inlet_example.did	Caltech-1960C	CO2	d 18O/16O	25.01	VSMOW	H	R 2H/1H	0.0001558
dual_inlet_example.did	Caltech-1960C	CO2	d 18O/16O	25.01	VSMOW	O	R 17O/16O	0.0003799
dual_inlet_example.did	Caltech-1960C	CO2	d 18O/16O	25.01	VSMOW	O	R 18O/16O	0.0020052
dual_inlet_example.caf	CO2clump tank	CO2	d 13C/12C	-2.82	VPDB	C	R 13C/12C	0.0111802
dual_inlet_example.caf	CO2clump tank	CO2	d 13C/12C	-2.82	VPDB	O	R 18O/16O	0.0020672
dual_inlet_example.caf	CO2clump tank	CO2	d 13C/12C	-2.82	VPDB	O	R 17O/16O	0.0003860
dual_inlet_example.caf	CO2clump tank	CO2	d 18O/16O	-4.67	VPDB	C	R 13C/12C	0.0111802
dual_inlet_example.caf	CO2clump tank	CO2	d 18O/16O	-4.67	VPDB	O	R 18O/16O	0.0020672
dual_inlet_example.caf	CO2clump tank	CO2	d 18O/16O	-4.67	VPDB	O	R 17O/16O	0.0003860
dual_inlet_example.caf	CO2clump tank	CO2	d 47CO2/44CO2	0.00	None	NA	NA	NA
dual_inlet_example.caf	CO2clump tank	CO2	d 48CO2/44CO2	0.00	None	NA	NA	NA
dual_inlet_example.caf	CO2clump tank	CO2	d 49CO2/44CO2	0.00	None	NA	NA	NA

Raw Data

The raw data read from the IRMS files can be retrieved similarly using the iso_get_raw_data() function. Most data aggregation functions also allow for inclusion of file information using the include_file_info parameter, which functions identically to the select parameter of the iso_get_file_info function discussed earlier.

# get raw data with default selections (all raw data, no additional file info)
di_files %>% iso_get_raw_data() %>% head(n=10) %>% knitr::kable()
#> Info: aggregating raw data from 3 data file(s)

file_id	type	cycle	v44.mV	v45.mV	v46.mV	v47.mV	v48.mV	v49.mV	block	i44.A	i45.A	i46.A	i47.A	i48.A	i49.A
dual_inlet_example.did	standard	0	15946.42	19001.94	21960.62	2513.280	29.78742	-181.2712	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	1	15941.14	18995.66	21954.19	2512.345	29.80048	-180.9752	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	2	15933.54	18986.64	21943.58	2511.280	29.81818	-180.7748	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	3	15916.58	18966.34	21919.97	2508.497	29.78074	-180.4583	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	4	15901.62	18948.60	21899.17	2506.104	29.76304	-180.2311	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	5	15896.00	18941.97	21891.49	2505.600	29.75818	-180.3095	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	6	15884.63	18928.51	21876.19	2503.555	29.72923	-180.2013	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	standard	7	15875.89	18918.12	21863.96	2502.444	29.69513	-180.0340	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	sample	1	15955.18	19122.71	22237.99	2559.245	31.09436	-181.2460	NA	NA	NA	NA	NA	NA	NA
dual_inlet_example.did	sample	2	15945.64	19111.16	22224.65	2557.857	31.09153	-180.9976	NA	NA	NA	NA	NA	NA	NA

# get specific raw data and add some file information
di_files %>%
  iso_get_raw_data(
    # select just time and the two ions
    select = c(type, cycle, v44.mV, v45.mV),
    # include the Analysis number fron the file info and rename it to 'run'
    include_file_info = c(run = Analysis)
  ) %>%
  # look at first few records only
  head(n=10) %>% knitr::kable()
#> Info: aggregating raw data from 3 data file(s), selecting data columns 'c(type, cycle, v44.mV, v45.mV)', including file info 'c(run = Analysis)'

file_id	run	type	cycle	v44.mV	v45.mV
dual_inlet_example.did	49077	standard	0	15946.42	19001.94
dual_inlet_example.did	49077	standard	1	15941.14	18995.66
dual_inlet_example.did	49077	standard	2	15933.54	18986.64
dual_inlet_example.did	49077	standard	3	15916.58	18966.34
dual_inlet_example.did	49077	standard	4	15901.62	18948.60
dual_inlet_example.did	49077	standard	5	15896.00	18941.97
dual_inlet_example.did	49077	standard	6	15884.63	18928.51
dual_inlet_example.did	49077	standard	7	15875.89	18918.12
dual_inlet_example.did	49077	sample	1	15955.18	19122.71
dual_inlet_example.did	49077	sample	2	15945.64	19111.16

Data Processing

The isoreader package is intended to make raw stable isotope data easily accessible. However, as with most analytical data, there is significant downstream processing required to turn these raw signal intensities into properly referenced isotopic measurement. This and similar functionality as well as data visualization is part of the isoprocessor package which takes isotopic data through the various corrections in a transparent, efficient and reproducible manner.

That said, most vendor software also performs some of these calculations and it can be useful to be able to compare new data reduction procedures against those implemented in the vendor software. For this purpose, isoreader retrieves vendor computed data tables whenever possible, as illustrated below.

Vendor Data Table

As with most data retrieval functions, the iso_get_vendor_data_table() function also allows specific column selection (by default, all columns are selected) and easy addition of file information via the include_file_info parameter (by default, none is included).

# entire vendor data table
di_files %>% iso_get_vendor_data_table() %>% knitr::kable()
#> Info: aggregating vendor data table from 3 data file(s)

file_id	cycle	d 45CO2/44CO2	d 46CO2/44CO2	d 13C/12C	d 18O/16O	d 17O/16O	AT% 13C/12C	AT% 18O/16O	d 47CO2/44CO2	d 48CO2/44CO2	d 49CO2/44CO2
dual_inlet_example.did	1	3.3287770	37.330647	2.1929917	37.366456	6.202321	1.108056	0.2075809	NA	NA	NA
dual_inlet_example.did	2	3.3209553	37.311799	2.1852948	37.347605	6.192886	1.108048	0.2075772	NA	NA	NA
dual_inlet_example.did	3	3.3263384	37.317514	2.1908570	37.353314	6.195743	1.108054	0.2075783	NA	NA	NA
dual_inlet_example.did	4	3.3200304	37.317207	2.1841057	37.353021	6.195597	1.108047	0.2075782	NA	NA	NA
dual_inlet_example.did	5	3.3187408	37.329768	2.1822644	37.365600	6.201893	1.108045	0.2075808	NA	NA	NA
dual_inlet_example.did	6	3.3177548	37.322849	2.1814601	37.358675	6.198427	1.108044	0.2075794	NA	NA	NA
dual_inlet_example.did	7	3.3217518	37.318368	2.1859087	37.354180	6.196176	1.108049	0.2075785	NA	NA	NA
dual_inlet_example.caf	1	0.7000753	7.543204	0.4669423	7.550236	6.316518	NA	NA	15.65910	22.50135	-58.12863
dual_inlet_example.caf	2	0.6846506	7.518991	0.4512997	7.526031	6.304043	NA	NA	15.62094	22.59733	-54.25812
dual_inlet_example.caf	3	0.6827013	7.503826	0.4497784	7.510853	6.296221	NA	NA	15.56356	22.81077	-52.21288
dual_inlet_example.caf	4	0.6940694	7.513421	0.4616176	7.520432	6.301158	NA	NA	15.64200	23.18259	-66.43734
dual_inlet_example.caf	5	0.6748151	7.499821	0.4414657	7.506862	6.294164	NA	NA	15.56706	22.81533	-67.80591
dual_inlet_example.caf	6	0.6836593	7.492892	0.4512181	7.499905	6.290578	NA	NA	15.65654	23.33585	-66.66771
dual_inlet_example.caf	7	0.6960376	7.491672	0.4645483	7.498654	6.289934	NA	NA	15.56031	23.89354	-42.32076
dual_inlet_example.caf	8	0.6929899	7.499328	0.4609894	7.506326	6.293888	NA	NA	15.45959	24.43994	-48.39355

# get specific parts and add some file information
di_files %>%
  iso_get_vendor_data_table(
    # select cycle and all carbon columns
    select = c(cycle, matches("C")),
    # include the Identifier 1 fron the file info and rename it to 'id'
    include_file_info = c(id = `Identifier 1`)
  ) %>% knitr::kable()
#> Info: aggregating vendor data table from 3 data file(s), including file info 'c(id = `Identifier 1`)'

file_id	id	cycle	d 45CO2/44CO2	d 46CO2/44CO2	d 13C/12C	AT% 13C/12C	d 47CO2/44CO2	d 48CO2/44CO2	d 49CO2/44CO2
dual_inlet_example.did	CIT Carrara	1	3.3287770	37.330647	2.1929917	1.108056	NA	NA	NA
dual_inlet_example.did	CIT Carrara	2	3.3209553	37.311799	2.1852948	1.108048	NA	NA	NA
dual_inlet_example.did	CIT Carrara	3	3.3263384	37.317514	2.1908570	1.108054	NA	NA	NA
dual_inlet_example.did	CIT Carrara	4	3.3200304	37.317207	2.1841057	1.108047	NA	NA	NA
dual_inlet_example.did	CIT Carrara	5	3.3187408	37.329768	2.1822644	1.108045	NA	NA	NA
dual_inlet_example.did	CIT Carrara	6	3.3177548	37.322849	2.1814601	1.108044	NA	NA	NA
dual_inlet_example.did	CIT Carrara	7	3.3217518	37.318368	2.1859087	1.108049	NA	NA	NA
dual_inlet_example.caf	2H6	1	0.7000753	7.543204	0.4669423	NA	15.65910	22.50135	-58.12863
dual_inlet_example.caf	2H6	2	0.6846506	7.518991	0.4512997	NA	15.62094	22.59733	-54.25812
dual_inlet_example.caf	2H6	3	0.6827013	7.503826	0.4497784	NA	15.56356	22.81077	-52.21288
dual_inlet_example.caf	2H6	4	0.6940694	7.513421	0.4616176	NA	15.64200	23.18259	-66.43734
dual_inlet_example.caf	2H6	5	0.6748151	7.499821	0.4414657	NA	15.56706	22.81533	-67.80591
dual_inlet_example.caf	2H6	6	0.6836593	7.492892	0.4512181	NA	15.65654	23.33585	-66.66771
dual_inlet_example.caf	2H6	7	0.6960376	7.491672	0.4645483	NA	15.56031	23.89354	-42.32076
dual_inlet_example.caf	2H6	8	0.6929899	7.499328	0.4609894	NA	15.45959	24.43994	-48.39355

For expert users: retrieving all data

For users familiar with the nested data frames from the tidyverse (particularly tidyr’s nest and unnest), there is an easy way to retrieve all data from the iso file objects in a single nested data frame:

all_data <- di_files %>% iso_get_all_data()
#> Info: aggregating all data from 3 data file(s)
# not printed out because this data frame is very big

Saving collections

Saving entire collections of isofiles for retrieval at a later point is easily done using the iso_save function which stores collections or individual isoreader file objects in the efficient R data storage format .rds (if not specified, the extension .di.rds will be automatically appended). These saved collections can be conveniently read back using the same iso_read_dual_inlet command used for raw data files.

# export to R data archive
di_files %>% iso_save("di_files_export.di.rds")
#> Info: exporting data from 3 iso_files into R Data Storage 'di_files_export.di.rds'

# read back the exported R data storage
iso_read_dual_inlet("di_files_export.di.rds")
#> Info: preparing to read 1 data files...
#> Info: reading file 'di_files_export.di.rds' with '.di.rds' reader...
#> Info: loaded 3 data files from R Data Storage
#> Info: finished reading 1 files in 0.12 secs
#> Data from 3 dual inlet iso files: 
#> # A tibble: 3 x 6
#>   file_id     raw_data      file_info  method_info  vendor_data_tab… file_path  
#>   <chr>       <glue>        <chr>      <chr>        <chr>            <chr>      
#> 1 dual_inlet… 7 cycles, 6 … 16 entries standards, … 7 rows, 8 colum… dual_inlet…
#> 2 dual_inlet… 8 cycles, 6 … 22 entries standards, … 8 rows, 9 colum… dual_inlet…
#> 3 dual_inlet… 82 cycles, 6… 9 entries  no method i… no vendor data … dual_inlet…

Data Export

At the moment, isoreader supports export of all data to Excel and the Feather file format (a Python/R cross-over format). Note that both export methods have similar syntax and append the appropriate file extension for each type of export file (.di.xlsx and .di.feather, respectively).

# export to excel
di_files %>% iso_export_to_excel("di_files_export")
#> Info: exporting data from 3 iso_files into Excel 'di_files_export.di.xlsx'
#> Info: aggregating all data from 3 data file(s)

# data sheets available in the exported data file:
readxl::excel_sheets("di_files_export.di.xlsx")
#> [1] "file info"         "raw data"          "standards"        
#> [4] "resistors"         "vendor data table" "problems"

# export to feather
di_files %>% iso_export_to_feather("di_files_export")
#> Info: exporting data from 3 iso_files into .di.feather files at 'di_files_export'
#> Info: aggregating all data from 3 data file(s)

# exported feather files
list.files(pattern = ".di.feather")
#> [1] "di_files_export_file_info.di.feather"        
#> [2] "di_files_export_problems.di.feather"         
#> [3] "di_files_export_raw_data.di.feather"         
#> [4] "di_files_export_resistors.di.feather"        
#> [5] "di_files_export_standards.di.feather"        
#> [6] "di_files_export_vendor_data_table.di.feather"

Dual Inlet Examples

2021-02-15