Creation

Create an own combination of the available requirements

First extract a term matching table for the used instruments without specifying the origin key.

full_tmt <- create_term_match_table(
  instrument_list = c("Thermo EASY-nLC", "Q Exactive - Orbitrap_MS"))
  # no origin key set

Now it is possible to subset or delete some rows with r tools.

sub_rows <- c(1, 6:8, 10) # wanted rows
subset_tmt <- full_tmt[sub_rows,]

head(subset_tmt)
#>                 term
#> 1    hplc_instrument
#> 6  hplc_samplevolume
#> 7      hplc_gradient
#> 8      ms_instrument
#> 10          ms_model
#>                                                term_verbose
#> 1  High Performance Liquid Chromatography (HPLC) Instrument
#> 6                                    Injected Sample Volume
#> 7                                   Chromatography Gradient
#> 8                                    Mass Spectrometer (MS)
#> 10                                                 MS Model
#>                            origin handle_type
#> 1  author;miape;jpr_guidelines_ms   list_path
#> 6                    author;miape   list_path
#> 7  author;miape;jpr_guidelines_ms    function
#> 8  author;miape;jpr_guidelines_ms   list_path
#> 10 author;miape;jpr_guidelines_ms     literal
#>                                                          handle
#> 1              Instruments.Thermo EASY-nLC.InstrumentFriendName
#> 6  Instruments.Thermo EASY-nLC.Method.Sample pickup.Volume [µl]
#> 7                                    document_easy_nlc_gradient
#> 8     Instruments.Q Exactive - Orbitrap MS.InstrumentFriendName
#> 10                                                    QExactive
#>                     example
#> 1           Thermo EASY-nLC
#> 6                      4.00
#> 7                      <NA>
#> 8  Q Exactive - Orbitrap MS
#> 10                QExactive

New rows can be added. It is mandatory to fill in term_verbose, handle_type and handle in their specific column. term_verbose should be a short desription for the column as it will show up as key in the final table.

If handle contains a string that just needs to be copied to the output table the collumn handle_type should contain "literal".

# create row
new_row <- data.frame(term = "example_line",
                      term_verbose = "Example line",        # Term in the final table
                      origin = "",
                      handle_type = "literal",            
                      handle = "this will be the value",    # Value in the final table
                      example = "")
# add to subset
subset_tmt <- rbind(subset_tmt, new_row)

If the row is meant to show an entry of the json handle_type needs to be "list_path" and handle should contain the path to the information in the flattened json after the group number.

# create the flattened json (explained in using_MARMoSET)
flat_json <- flatten_json(json = MARMoSET::testfile_json)

# choose/search for item of the flattened list, get path without group number.
fj_path <- stringi::stri_subset(names(flat_json), regex = "Flush")  %>% 
stringi::stri_replace_all_regex(pattern = "^Group.[:digit:].", replacement = "")

# create row
new_row <- data.frame(term = "second_example_line",
                      term_verbose = "Second example, Autosampler flush volume",    # Term in the final table
                      origin = "",
                      handle_type = "list_path",            
                      handle = fj_path,                                             # Value in the final table
                      example = "")
# add to subset
subset_tmt <- rbind(subset_tmt, new_row)

This so changed term matching table can be used with the function match_terms().

subset_table <- one_group_match_terms(flat_json = flat_json, 
                                         term_matching_table = subset_tmt, 
                                         group_number = 1)
subset_table[5:7,]
#>                                       Term                  Value
#> 5                                 MS Model              QExactive
#> 6                             Example line this will be the value
#> 7 Second example, Autosampler flush volume                 100.00