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Copper alloy classification according to Bayley & Butcher (2004)

Source: R/ASTR_copper_alloy_classification_bb.R
copper_alloy_bb.Rd

Classification of copper alloy artefacts according to Bayley & Butcher (2004) based on Zn, Sn, and Pb concentrations in wt%. Classification uses specific thresholds and ratios to define alloy types.

Usage

copper_alloy_bb(
  df,
  elements = c(Sn = "Sn", Zn = "Zn", Pb = "Pb"),
  id_column = "ID",
  ...
)

Arguments

df

data frame with the data to be classified.

elements

named character vector with column names of Sn, Zn, and Pb concentrations.

id_column

name of the column in df with the identifiers of each row. Default to ID.

...

Additional arguments for unit conversion, see atomic_conversion and oxide_conversion for details.

Value

If df is an ASTR object, the output is an object of the same type including the ID column, the contextual columns, the elements used for classification and the alloy type. In all other cases, the data frame provided as input with the column for the alloy type.

References

Bayley, J. and Butcher, S. (2004). Roman brooches in Britain: a technological and typological study based on the Richborough Collection. London: Society of Antiquaries of London. https://doi.org/10.26530/20.500.12657/50365

See also

Other copper alloy classifications: copper_alloy_pollard(), copper_group_bray()

Examples

sample_df <- data.frame(
  ID = 1:5,
  Sn = c(5, 1, 4, 0.5, 2),
  Zn = c(12, 20, 6, 2, 10),
  Pb = c(1, 0.5, 5, 9, 12)
)
copper_alloy_bb(sample_df)
#>   ID  Sn Zn   Pb   copper_alloy_bb
#> 1  1 5.0 12  1.0          Gunmetal
#> 2  2 1.0 20  0.5             Brass
#> 3  3 4.0  6  5.0 (Leaded) Gunmetal
#> 4  4 0.5  2  9.0     Leaded Copper
#> 5  5 2.0 10 12.0      Leaded Brass

# For ASTR objects, units and oxides are automatically converted
sample_df <- as_ASTR(
  data.frame(
    ID = 1:8,
    SnO_wtP = c(0.5, 0.5, 5, 5, 0.5, 5, 5, 5),
    ZnO_wtP = c(0.5, 0.5, 0.5, 0.5, 5, 5, 0.5, 5),
    PbO_wtP = c(0.5, 5, 0.5, 5, 0.5, 0.5, 5, 5)
  )
)
copper_alloy_bb(sample_df, elements = c(Sn = "SnO", Zn = "ZnO", Pb = "PbO"))
#> ASTR table
#> Analytical columns: Sn, Zn, Pb
#> Contextual columns: copper_alloy_bb 
#> # A data frame: 8 × 5
#>      ID    Sn    Zn    Pb copper_alloy_bb  
#>   <int> [wtP] [wtP] [wtP] <chr>            
#> 1     1 0.441 0.402 0.464 Copper           
#> 2     2 0.441 0.402 4.64  (Leaded) Copper  
#> 3     3 4.41  0.402 0.464 Bronze           
#> 4     4 4.41  0.402 4.64  (Leaded) Bronze  
#> 5     5 0.441 4.02  0.464 Copper/brass     
#> 6     6 4.41  4.02  0.464 Gunmetal         
#> 7     7 4.41  0.402 4.64  (Leaded) Bronze  
#> 8     8 4.41  4.02  4.64  (Leaded) Gunmetal