data(mushroom)
head(mushroom)
#> Species Pileus.Cap.Width_min Pileus.Cap.Width_max Stipe.Length_min
#> 1 arorae 3 8 4
#> 2 arvenis 6 21 4
#> 3 benesi 4 8 5
#> 4 bernardii 7 6 4
#> 5 bisporus 5 12 2
#> 6 bitorquis 5 15 4
#> Stipe.Length_max Stipe.Thickness_min Stipe.Thickness_max Edibility
#> 1 9 0.5 2.5 U
#> 2 14 1.0 3.5 Y
#> 3 11 1.0 2.0 Y
#> 4 7 3.0 4.5 Y
#> 5 5 1.5 2.5 Y
#> 6 10 2.0 4.0 YChanges the format of the set variables in the data to conform to the RSDA format.
data = the conventional dataframelocation = the location of the set variable in the
datavar = the name of the set variable in the datamushroom.set <- set_variable_format(data = mushroom, location = 8, var = "Species")
head(mushroom.set)
#> Species arorae arvenis benesi bernardii bisporus bitorquis califorinus
#> 1 23 1 0 0 0 0 0 0
#> 2 23 0 1 0 0 0 0 0
#> 3 23 0 0 1 0 0 0 0
#> 4 23 0 0 0 1 0 0 0
#> 5 23 0 0 0 0 1 0 0
#> 6 23 0 0 0 0 0 1 0
#> campestris comtulus cupreo-brunneus diminutives fuseo-fibrillosus
#> 1 0 0 0 0 0
#> 2 0 0 0 0 0
#> 3 0 0 0 0 0
#> 4 0 0 0 0 0
#> 5 0 0 0 0 0
#> 6 0 0 0 0 0
#> fuscovelatus hondensis lilaceps micromegathus praeclaresquamosus pattersonae
#> 1 0 0 0 0 0 0
#> 2 0 0 0 0 0 0
#> 3 0 0 0 0 0 0
#> 4 0 0 0 0 0 0
#> 5 0 0 0 0 0 0
#> 6 0 0 0 0 0 0
#> perobscurus semotus silvicola subrutilescens xanthodermus
#> 1 0 0 0 0 0
#> 2 0 0 0 0 0
#> 3 0 0 0 0 0
#> 4 0 0 0 0 0
#> 5 0 0 0 0 0
#> 6 0 0 0 0 0
#> Pileus.Cap.Width_min Pileus.Cap.Width_max Stipe.Length_min Stipe.Length_max
#> 1 3 8 4 9
#> 2 6 21 4 14
#> 3 4 8 5 11
#> 4 7 6 4 7
#> 5 5 12 2 5
#> 6 5 15 4 10
#> Stipe.Thickness_min Stipe.Thickness_max Edibility U Y T
#> 1 0.5 2.5 3 1 0 0
#> 2 1.0 3.5 3 0 1 0
#> 3 1.0 2.0 3 0 1 0
#> 4 3.0 4.5 3 0 1 0
#> 5 1.5 2.5 3 0 1 0
#> 6 2.0 4.0 3 0 1 0Changes the format of the data to conform to RSDA format.
data = the conventional dataframesym_type1 = the labels I means an interval variable,
and S means set variable in locationlocation = the location of the sym_type in the
datasym_type2 = the labels I means an interval variable,
and S means set variable in varvar = the name of the symbolic variable in the
datamushroom.tmp <- RSDA_format(data = mushroom.set, sym_type1 = c("I", "S"),
location = c(25, 31), sym_type2 = c("S", "I", "I"),
var = c("Species", "Stipe.Length_min", "Stipe.Thickness_min"))
head(mushroom.tmp)
#> $S Species arorae arvenis benesi bernardii bisporus bitorquis califorinus
#> 1 $S 23 1 0 0 0 0 0 0
#> 2 $S 23 0 1 0 0 0 0 0
#> 3 $S 23 0 0 1 0 0 0 0
#> 4 $S 23 0 0 0 1 0 0 0
#> 5 $S 23 0 0 0 0 1 0 0
#> 6 $S 23 0 0 0 0 0 1 0
#> campestris comtulus cupreo-brunneus diminutives fuseo-fibrillosus
#> 1 0 0 0 0 0
#> 2 0 0 0 0 0
#> 3 0 0 0 0 0
#> 4 0 0 0 0 0
#> 5 0 0 0 0 0
#> 6 0 0 0 0 0
#> fuscovelatus hondensis lilaceps micromegathus praeclaresquamosus pattersonae
#> 1 0 0 0 0 0 0
#> 2 0 0 0 0 0 0
#> 3 0 0 0 0 0 0
#> 4 0 0 0 0 0 0
#> 5 0 0 0 0 0 0
#> 6 0 0 0 0 0 0
#> perobscurus semotus silvicola subrutilescens xanthodermus $I
#> 1 0 0 0 0 0 $I
#> 2 0 0 0 0 0 $I
#> 3 0 0 0 0 0 $I
#> 4 0 0 0 0 0 $I
#> 5 0 0 0 0 0 $I
#> 6 0 0 0 0 0 $I
#> Pileus.Cap.Width_min Pileus.Cap.Width_max $I Stipe.Length_min
#> 1 3 8 $I 4
#> 2 6 21 $I 4
#> 3 4 8 $I 5
#> 4 7 6 $I 4
#> 5 5 12 $I 2
#> 6 5 15 $I 4
#> Stipe.Length_max $I Stipe.Thickness_min Stipe.Thickness_max $S Edibility U Y
#> 1 9 $I 0.5 2.5 $S 3 1 0
#> 2 14 $I 1.0 3.5 $S 3 0 1
#> 3 11 $I 1.0 2.0 $S 3 0 1
#> 4 7 $I 3.0 4.5 $S 3 0 1
#> 5 5 $I 1.5 2.5 $S 3 0 1
#> 6 10 $I 2.0 4.0 $S 3 0 1
#> T
#> 1 0
#> 2 0
#> 3 0
#> 4 0
#> 5 0
#> 6 0Clean up variable names to conform to the RSDA format.
data = the conventional dataframemushroom.clean <- clean_colnames(data = mushroom.tmp)
head(mushroom.clean)
#> $S Species arorae arvenis benesi bernardii bisporus bitorquis califorinus
#> 1 $S 23 1 0 0 0 0 0 0
#> 2 $S 23 0 1 0 0 0 0 0
#> 3 $S 23 0 0 1 0 0 0 0
#> 4 $S 23 0 0 0 1 0 0 0
#> 5 $S 23 0 0 0 0 1 0 0
#> 6 $S 23 0 0 0 0 0 1 0
#> campestris comtulus cupreo-brunneus dutives fuseo-fibrillosus fuscovelatus
#> 1 0 0 0 0 0 0
#> 2 0 0 0 0 0 0
#> 3 0 0 0 0 0 0
#> 4 0 0 0 0 0 0
#> 5 0 0 0 0 0 0
#> 6 0 0 0 0 0 0
#> hondensis lilaceps micromegathus praeclaresquamosus pattersonae perobscurus
#> 1 0 0 0 0 0 0
#> 2 0 0 0 0 0 0
#> 3 0 0 0 0 0 0
#> 4 0 0 0 0 0 0
#> 5 0 0 0 0 0 0
#> 6 0 0 0 0 0 0
#> semotus silvicola subrutilescens xanthodermus $I Pileus.Cap.Width
#> 1 0 0 0 0 $I 3
#> 2 0 0 0 0 $I 6
#> 3 0 0 0 0 $I 4
#> 4 0 0 0 0 $I 7
#> 5 0 0 0 0 $I 5
#> 6 0 0 0 0 $I 5
#> Pileus.Cap.Width $I Stipe.Length Stipe.Length $I Stipe.Thickness
#> 1 8 $I 4 9 $I 0.5
#> 2 21 $I 4 14 $I 1.0
#> 3 8 $I 5 11 $I 1.0
#> 4 6 $I 4 7 $I 3.0
#> 5 12 $I 2 5 $I 1.5
#> 6 15 $I 4 10 $I 2.0
#> Stipe.Thickness $S Edibility U Y T
#> 1 2.5 $S 3 1 0 0
#> 2 3.5 $S 3 0 1 0
#> 3 2.0 $S 3 0 1 0
#> 4 4.5 $S 3 0 1 0
#> 5 2.5 $S 3 0 1 0
#> 6 4.0 $S 3 0 1 0write_csv_table(data = mushroom.clean, file = 'mushroom_interval.csv')mushroom.int <- read.sym.table(file = 'mushroom_interval.csv', header = T, sep = ';', dec = '.', row.names = 1)
head(mushroom.int)
#> # A tibble: 6 × 5
#> Species Pileus.Cap.Width Stipe.Length Stipe.Thickness Edibility
#> <symblc_s> <symblc_n> <symblc_n> <symblc_n> <symblc_s>
#> 1 {arorae} [3.00 : 8.00] [4.00 : 9.00] [0.50 : 2.50] {U}
#> 2 {arvenis} [6.00 : 21.00] [4.00 : 14.00] [1.00 : 3.50] {Y}
#> 3 {benesi} [4.00 : 8.00] [5.00 : 11.00] [1.00 : 2.00] {Y}
#> 4 {bernardii} [7.00 : 6.00] [4.00 : 7.00] [3.00 : 4.50] {Y}
#> 5 {bisporus} [5.00 : 12.00] [2.00 : 5.00] [1.50 : 2.50] {Y}
#> 6 {bitorquis} [5.00 : 15.00] [4.00 : 10.00] [2.00 : 4.00] {Y}data(Abalone.iGAP)
head(Abalone.iGAP)
#> Length Diameter Height Whole
#> F-10-12 0.1275,0.9975 0.075, 0.815 -0.0175, 0.3125 -1.021, 3.883
#> F-13-15 0.1775,1.0275 0.125,0.825 0.025, 0.325 -0.8567, 3.6303
#> F-16-18 0.22,0.92 0.1725, 0.7425 0.0375, 0.3075 -0.5725, 3.1235
#> F-19-21 0.3725, 0.8425 0.2575, 0.6875 0.0825, 0.2525 -0.0368, 2.8443
#> F-23-24 0.275, 0.975 0.255, 0.755 0.09, 0.27 -0.303, 3.469
#> F-25-29 0.475, 0.775 0.405, 0.645 0.1625, 0.2325 0.915, 2.105
#> Shucked Viscera Shell
#> F-10-12 -0.6322, 2.1948 -0.2077, 0.7712 -0.258, 1.054
#> F-13-15 -0.4548, 1.7942 -0.1905, 0.7555 -0.269, 1.153
#> F-16-18 -0.244, 1.206 -0.1037, 0.6752 -0.3233, 1.4477
#> F-19-21 -0.16, 1.14 -0.033, 0.615 -0.1175, 1.1725
#> F-23-24 -0.2295, 1.3205 -0.13, 0.83 0.005, 0.945
#> F-25-29 0.134, 0.896 0.1467, 0.3798 0.45, 0.55To convert iGAP files to CSV files.
data = the conventional dataframe(iGAP format)location = the location of the symbolic variable in the
dataAbalone <- iGAP_to_MM(Abalone.iGAP, c(1, 2, 3, 4, 5, 6, 7))
head(Abalone)
#> Length_min Length_max Diameter_min Diameter_max Height_min Height_max
#> F-10-12 0.1275 0.9975 0.075 0.815 -0.0175 0.3125
#> F-13-15 0.1775 1.0275 0.125 0.825 0.025 0.325
#> F-16-18 0.22 0.92 0.1725 0.7425 0.0375 0.3075
#> F-19-21 0.3725 0.8425 0.2575 0.6875 0.0825 0.2525
#> F-23-24 0.275 0.975 0.255 0.755 0.09 0.27
#> F-25-29 0.475 0.775 0.405 0.645 0.1625 0.2325
#> Whole_min Whole_max Shucked_min Shucked_max Viscera_min Viscera_max
#> F-10-12 -1.021 3.883 -0.6322 2.1948 -0.2077 0.7712
#> F-13-15 -0.8567 3.6303 -0.4548 1.7942 -0.1905 0.7555
#> F-16-18 -0.5725 3.1235 -0.244 1.206 -0.1037 0.6752
#> F-19-21 -0.0368 2.8443 -0.16 1.14 -0.033 0.615
#> F-23-24 -0.303 3.469 -0.2295 1.3205 -0.13 0.83
#> F-25-29 0.915 2.105 0.134 0.896 0.1467 0.3798
#> Shell_min Shell_max
#> F-10-12 -0.258 1.054
#> F-13-15 -0.269 1.153
#> F-16-18 -0.3233 1.4477
#> F-19-21 -0.1175 1.1725
#> F-23-24 0.005 0.945
#> F-25-29 0.45 0.55