Find variable combinations by advanced wildcard/globbing specifications.
Source:R/PatternMatching.R
HierarchicalWildcardGlobbing.RdFind combinations present in an input data frame or, when input is a list, find all possible combinations that meet the requirements.
Usage
HierarchicalWildcardGlobbing(
z,
wg,
useUnique = NULL,
useFactor = FALSE,
makeWarning = TRUE,
printInfo = FALSE,
useMatrixToDataFrame = TRUE
)Arguments
- z
list or data.frame
- wg
data.frame with data globbing and wildcards
- useUnique
Logical variable about recoding within the algorithm. By default (NULL) an automatic decision is made.
- useFactor
When TRUE, internal factor recoding is used.
- makeWarning
When TRUE, warning is made in cases of unused variables. Only variables common to z and wg are used.
- printInfo
When TRUE, information is printed during the process.
- useMatrixToDataFrame
When TRUE, special functions (DataFrameToMatrix/MatrixToDataFrame) for improving speed and memory is utilized.
Details
The final variable combinations must meet the requirements in each positive sign group
and must not match the requirements in the negative sign groups.The function is implemented by
calling WildcardGlobbing several times within an algorithm that uses
hierarchical clustering (hclust).
Examples
# useUnique=NULL betyr valg ut fra antall rader i kombinasjonsfil
data(precip)
data(mtcars)
codes <- as.character(c(100, 200, 300, 600, 700, 101, 102, 103, 104, 134, 647, 783,
13401, 13402, 64701, 64702))
# Create list input
zList <- list(car = rownames(mtcars), wt = as.character(1000 * mtcars$wt),
city = names(precip), code = codes)
# Create data.frame input
m <- cbind(car = rownames(mtcars), wt = as.character(1000 * mtcars$wt))
zFrame <- data.frame(m[rep(1:NROW(m), each = 35), ],
city = names(precip), code = codes, stringsAsFactors = FALSE)
# Create globbing/wildcards input
wg <- data.frame(rbind(c("Merc*", "" , "" , "?00" ),
c("F*" , "" , "" , "?????"),
c("" , "???0", "C*" , "" ),
c("" , "" , "!Co*", "" ),
c("" , "" , "?i*" , "????2"),
c("" , "" , "?h*" , "????1")),
sign = c("+", "+", "+", "+", "-", "-"), stringsAsFactors = FALSE)
names(wg)[1:4] <- names(zList)
# ===================================================================
# Finding unique combinations present in the input data frame
# ===================================================================
# Using first row of wg. Combinations of car starting with Merc
# and three-digit code ending with 00
HierarchicalWildcardGlobbing(zFrame[, c(1, 4)], wg[1, c(1, 4, 5)])
#> car code
#> 1 Merc 240D 100
#> 2 Merc 230 100
#> 3 Merc 280 100
#> 4 Merc 280C 100
#> 5 Merc 450SE 100
#> 6 Merc 450SL 100
#> 7 Merc 450SLC 100
#> 8 Merc 240D 200
#> 9 Merc 230 200
#> 10 Merc 280 200
#> 11 Merc 280C 200
#> 12 Merc 450SE 200
#> 13 Merc 450SL 200
#> 14 Merc 450SLC 200
#> 15 Merc 240D 300
#> 16 Merc 230 300
#> 17 Merc 280 300
#> 18 Merc 280C 300
#> 19 Merc 450SE 300
#> 20 Merc 450SL 300
#> 21 Merc 450SLC 300
#> 22 Merc 240D 600
#> 23 Merc 230 600
#> 24 Merc 280 600
#> 25 Merc 280C 600
#> 26 Merc 450SE 600
#> 27 Merc 450SL 600
#> 28 Merc 450SLC 600
#> 29 Merc 240D 700
#> 30 Merc 230 700
#> 31 Merc 280 700
#> 32 Merc 280C 700
#> 33 Merc 450SE 700
#> 34 Merc 450SL 700
#> 35 Merc 450SLC 700
# Using first row of wg. Combinations of all four variables
HierarchicalWildcardGlobbing(zFrame, wg[1, ])
#> car code wt city
#> 1 Merc 450SL 700 3730 Mobile
#> 2 Merc 280C 100 3440 Phoenix
#> 3 Merc 280C 200 3440 Little Rock
#> 4 Merc 280C 300 3440 Los Angeles
#> 5 Merc 280C 600 3440 Sacramento
#> 6 Merc 280C 700 3440 San Francisco
#> 7 Merc 230 100 3150 Hartford
#> 8 Merc 230 200 3150 Wilmington
#> 9 Merc 230 300 3150 Washington
#> 10 Merc 230 600 3150 Jacksonville
#> 11 Merc 230 700 3150 Miami
#> 12 Merc 450SL 100 3730 Miami
#> 13 Merc 450SL 200 3730 Atlanta
#> 14 Merc 450SL 300 3730 Honolulu
#> 15 Merc 450SL 600 3730 Boise
#> 16 Merc 450SL 700 3730 Chicago
#> 17 Merc 280C 100 3440 Indianapolis
#> 18 Merc 280C 200 3440 Des Moines
#> 19 Merc 280C 300 3440 Wichita
#> 20 Merc 280C 600 3440 Louisville
#> 21 Merc 280C 700 3440 New Orleans
#> 22 Merc 240D 600 3190 Portland
#> 23 Merc 230 100 3150 Baltimore
#> 24 Merc 230 200 3150 Boston
#> 25 Merc 230 300 3150 Detroit
#> 26 Merc 230 600 3150 Sault Ste. Marie
#> 27 Merc 230 700 3150 Duluth
#> 28 Merc 450SL 100 3730 Duluth
#> 29 Merc 450SL 200 3730 Minneapolis/St Paul
#> 30 Merc 450SL 300 3730 Jackson
#> 31 Merc 450SL 600 3730 Kansas City
#> 32 Merc 450SL 700 3730 St Louis
#> 33 Merc 280C 100 3440 Omaha
#> 34 Merc 450SE 200 4070 Reno
#> 35 Merc 450SE 300 4070 Concord
#> 36 Merc 450SE 600 4070 Atlantic City
#> 37 Merc 450SE 700 4070 Albuquerque
#> 38 Merc 280 100 3440 Buffalo
#> 39 Merc 280 200 3440 New York
#> 40 Merc 280 300 3440 Charlotte
#> 41 Merc 280 600 3440 Raleigh
#> 42 Merc 280 700 3440 Bismark
#> 43 Merc 450SLC 100 3780 Bismark
#> 44 Merc 450SLC 200 3780 Cincinnati
#> 45 Merc 240D 100 3190 Cleveland
#> 46 Merc 450SLC 300 3780 Cleveland
#> 47 Merc 240D 200 3190 Columbus
#> 48 Merc 450SLC 600 3780 Columbus
#> 49 Merc 240D 300 3190 Oklahoma City
#> 50 Merc 450SLC 700 3780 Oklahoma City
#> 51 Merc 240D 700 3190 Philadelphia
#> 52 Merc 450SE 100 4070 Philadelphia
#> 53 Merc 450SE 200 4070 Pittsburg
#> 54 Merc 450SE 300 4070 Providence
#> 55 Merc 450SE 600 4070 Columbia
#> 56 Merc 450SE 700 4070 Sioux Falls
#> 57 Merc 280 100 3440 Nashville
#> 58 Merc 280 200 3440 Dallas
#> 59 Merc 280 300 3440 El Paso
#> 60 Merc 280 600 3440 Houston
#> 61 Merc 280 700 3440 Salt Lake City
#> 62 Merc 450SLC 100 3780 Salt Lake City
#> 63 Merc 450SLC 200 3780 Burlington
#> 64 Merc 240D 100 3190 Norfolk
#> 65 Merc 450SLC 300 3780 Norfolk
#> 66 Merc 240D 200 3190 Richmond
#> 67 Merc 450SLC 600 3780 Richmond
#> 68 Merc 240D 300 3190 Seattle Tacoma
#> 69 Merc 450SLC 700 3780 Seattle Tacoma
#> 70 Merc 240D 600 3190 Spokane
#> 71 Merc 240D 700 3190 Charleston
#> 72 Merc 450SE 100 4070 Charleston
#> 73 Merc 450SE 200 4070 Milwaukee
#> 74 Merc 450SE 300 4070 Cheyenne
#> 75 Merc 450SE 600 4070 San Juan
# More combinations when using second row also
HierarchicalWildcardGlobbing(zFrame, wg[1:2, ])
#> car code wt city
#> 1 Merc 450SL 700 3730 Mobile
#> 2 Merc 280C 100 3440 Phoenix
#> 3 Merc 280C 200 3440 Little Rock
#> 4 Merc 280C 300 3440 Los Angeles
#> 5 Merc 280C 600 3440 Sacramento
#> 6 Merc 280C 700 3440 San Francisco
#> 7 Merc 230 100 3150 Hartford
#> 8 Ford Pantera L 13401 3170 Hartford
#> 9 Merc 230 200 3150 Wilmington
#> 10 Ford Pantera L 13402 3170 Wilmington
#> 11 Merc 230 300 3150 Washington
#> 12 Ford Pantera L 64701 3170 Washington
#> 13 Merc 230 600 3150 Jacksonville
#> 14 Ford Pantera L 64702 3170 Jacksonville
#> 15 Merc 230 700 3150 Miami
#> 16 Merc 450SL 100 3730 Miami
#> 17 Merc 450SL 200 3730 Atlanta
#> 18 Merc 450SL 300 3730 Honolulu
#> 19 Merc 450SL 600 3730 Boise
#> 20 Merc 450SL 700 3730 Chicago
#> 21 Merc 280C 100 3440 Indianapolis
#> 22 Merc 280C 200 3440 Des Moines
#> 23 Merc 280C 300 3440 Wichita
#> 24 Merc 280C 600 3440 Louisville
#> 25 Merc 280C 700 3440 New Orleans
#> 26 Merc 240D 600 3190 Portland
#> 27 Merc 230 100 3150 Baltimore
#> 28 Ford Pantera L 13401 3170 Baltimore
#> 29 Merc 230 200 3150 Boston
#> 30 Ford Pantera L 13402 3170 Boston
#> 31 Merc 230 300 3150 Detroit
#> 32 Ford Pantera L 64701 3170 Detroit
#> 33 Merc 230 600 3150 Sault Ste. Marie
#> 34 Ford Pantera L 64702 3170 Sault Ste. Marie
#> 35 Merc 230 700 3150 Duluth
#> 36 Merc 450SL 100 3730 Duluth
#> 37 Merc 450SL 200 3730 Minneapolis/St Paul
#> 38 Merc 450SL 300 3730 Jackson
#> 39 Merc 450SL 600 3730 Kansas City
#> 40 Merc 450SL 700 3730 St Louis
#> 41 Merc 280C 100 3440 Omaha
#> 42 Merc 450SE 200 4070 Reno
#> 43 Merc 450SE 300 4070 Concord
#> 44 Fiat X1-9 13401 1935 Concord
#> 45 Merc 450SE 600 4070 Atlantic City
#> 46 Fiat X1-9 13402 1935 Atlantic City
#> 47 Merc 450SE 700 4070 Albuquerque
#> 48 Fiat X1-9 64701 1935 Albuquerque
#> 49 Fiat X1-9 64702 1935 Albany
#> 50 Merc 280 100 3440 Buffalo
#> 51 Ferrari Dino 13401 2770 Buffalo
#> 52 Merc 280 200 3440 New York
#> 53 Ferrari Dino 13402 2770 New York
#> 54 Merc 280 300 3440 Charlotte
#> 55 Ferrari Dino 64701 2770 Charlotte
#> 56 Merc 280 600 3440 Raleigh
#> 57 Ferrari Dino 64702 2770 Raleigh
#> 58 Merc 280 700 3440 Bismark
#> 59 Merc 450SLC 100 3780 Bismark
#> 60 Fiat 128 13401 2200 Bismark
#> 61 Merc 450SLC 200 3780 Cincinnati
#> 62 Fiat 128 13402 2200 Cincinnati
#> 63 Merc 240D 100 3190 Cleveland
#> 64 Merc 450SLC 300 3780 Cleveland
#> 65 Fiat 128 64701 2200 Cleveland
#> 66 Merc 240D 200 3190 Columbus
#> 67 Merc 450SLC 600 3780 Columbus
#> 68 Fiat 128 64702 2200 Columbus
#> 69 Merc 240D 300 3190 Oklahoma City
#> 70 Merc 450SLC 700 3780 Oklahoma City
#> 71 Merc 240D 700 3190 Philadelphia
#> 72 Merc 450SE 100 4070 Philadelphia
#> 73 Merc 450SE 200 4070 Pittsburg
#> 74 Merc 450SE 300 4070 Providence
#> 75 Fiat X1-9 13401 1935 Providence
#> 76 Merc 450SE 600 4070 Columbia
#> 77 Fiat X1-9 13402 1935 Columbia
#> 78 Merc 450SE 700 4070 Sioux Falls
#> 79 Fiat X1-9 64701 1935 Sioux Falls
#> 80 Fiat X1-9 64702 1935 Memphis
#> 81 Merc 280 100 3440 Nashville
#> 82 Ferrari Dino 13401 2770 Nashville
#> 83 Merc 280 200 3440 Dallas
#> 84 Ferrari Dino 13402 2770 Dallas
#> 85 Merc 280 300 3440 El Paso
#> 86 Ferrari Dino 64701 2770 El Paso
#> 87 Merc 280 600 3440 Houston
#> 88 Ferrari Dino 64702 2770 Houston
#> 89 Merc 280 700 3440 Salt Lake City
#> 90 Merc 450SLC 100 3780 Salt Lake City
#> 91 Fiat 128 13401 2200 Salt Lake City
#> 92 Merc 450SLC 200 3780 Burlington
#> 93 Fiat 128 13402 2200 Burlington
#> 94 Merc 240D 100 3190 Norfolk
#> 95 Merc 450SLC 300 3780 Norfolk
#> 96 Fiat 128 64701 2200 Norfolk
#> 97 Merc 240D 200 3190 Richmond
#> 98 Merc 450SLC 600 3780 Richmond
#> 99 Fiat 128 64702 2200 Richmond
#> 100 Merc 240D 300 3190 Seattle Tacoma
#> 101 Merc 450SLC 700 3780 Seattle Tacoma
#> 102 Merc 240D 600 3190 Spokane
#> 103 Merc 240D 700 3190 Charleston
#> 104 Merc 450SE 100 4070 Charleston
#> 105 Merc 450SE 200 4070 Milwaukee
#> 106 Merc 450SE 300 4070 Cheyenne
#> 107 Fiat X1-9 13401 1935 Cheyenne
#> 108 Merc 450SE 600 4070 San Juan
#> 109 Fiat X1-9 13402 1935 San Juan
# Less combinations when using third row also
# since last digit of wt must be 0 and only cities starting with C
HierarchicalWildcardGlobbing(zFrame, wg[1:3, ])
#> car code wt city
#> 1 Merc 450SL 700 3730 Chicago
#> 2 Merc 450SE 300 4070 Concord
#> 3 Merc 280 300 3440 Charlotte
#> 4 Ferrari Dino 64701 2770 Charlotte
#> 5 Merc 450SLC 200 3780 Cincinnati
#> 6 Fiat 128 13402 2200 Cincinnati
#> 7 Merc 240D 100 3190 Cleveland
#> 8 Merc 450SLC 300 3780 Cleveland
#> 9 Fiat 128 64701 2200 Cleveland
#> 10 Merc 240D 200 3190 Columbus
#> 11 Merc 450SLC 600 3780 Columbus
#> 12 Fiat 128 64702 2200 Columbus
#> 13 Merc 450SE 600 4070 Columbia
#> 14 Merc 240D 700 3190 Charleston
#> 15 Merc 450SE 100 4070 Charleston
#> 16 Merc 450SE 300 4070 Cheyenne
# Less combinations when using fourth row also since city cannot start with Co
HierarchicalWildcardGlobbing(zFrame, wg[1:4, ])
#> car code wt city
#> 1 Merc 450SL 700 3730 Chicago
#> 2 Merc 280 300 3440 Charlotte
#> 3 Ferrari Dino 64701 2770 Charlotte
#> 4 Merc 450SLC 200 3780 Cincinnati
#> 5 Fiat 128 13402 2200 Cincinnati
#> 6 Merc 240D 100 3190 Cleveland
#> 7 Merc 450SLC 300 3780 Cleveland
#> 8 Fiat 128 64701 2200 Cleveland
#> 9 Merc 240D 700 3190 Charleston
#> 10 Merc 450SE 100 4070 Charleston
#> 11 Merc 450SE 300 4070 Cheyenne
# Less combinations when using fourth row also
# since specific combinations of city and code are removed
HierarchicalWildcardGlobbing(zFrame, wg)
#> car code wt city
#> 1 Merc 450SL 700 3730 Chicago
#> 2 Merc 280 300 3440 Charlotte
#> 3 Merc 450SLC 200 3780 Cincinnati
#> 4 Merc 240D 100 3190 Cleveland
#> 5 Merc 450SLC 300 3780 Cleveland
#> 6 Fiat 128 64701 2200 Cleveland
#> 7 Merc 240D 700 3190 Charleston
#> 8 Merc 450SE 100 4070 Charleston
#> 9 Merc 450SE 300 4070 Cheyenne
# ===================================================================
# Using list input to create all possible combinations
# ===================================================================
dim(HierarchicalWildcardGlobbing(zList, wg))
#> [1] 4788 4
# same result with as.list since same unique values of each variable
dim(HierarchicalWildcardGlobbing(as.list(zFrame), wg))
#> [1] 4788 4