Usage
make_upper_tri(x, diag = NA)
make_lower_tri(x, diag = NA)
make_lower_upper(lower, upper, diag = NA)
make_sym(x, make = "upper", diag = NA)
tidy_sym(x, keep_diag = TRUE)
Arguments
- x
A matrix to apply the function. It must be a symmetric (square) matrix in
make_upper_tri()
andmake_lower_tri()
or a triangular matrix inmake_sym()
.tidy_sym()
accepts both symmetrical or triangular matrices.- diag
What show in the diagonal of the matrix. Default to
NA
.- lower
A square matrix to fill the lower diagonal of the new matrix.
- upper
A square matrix to fill the upper diagonal of the new matrix.
- make
The triangular to built. Default is
"upper"
. In this case, a symmetric matrix will be built based on the values of a lower triangular matrix.- keep_diag
Keep diagonal values in the tidy data frame? Defaults to
TRUE
.
Details
make_upper_tri()
makes an upper triangular matrix using a symmetric matrix.make_lower_tri()
makes a lower triangular matrix using a symmetric matrix.make_sym()
makes a lower triangular matrix using a symmetric matrix.tidy_sym()
transform a symmetric matrix into tidy data frame.
Author
Tiago Olivoto tiagoolivoto@gmail.com
Examples
# \donttest{
library(metan)
m <- cor(select_cols(data_ge2, 5:10))
make_upper_tri(m)
#> EH EP EL ED CL CD
#> EH NA 0.869546 0.3626537 0.6302561 0.3971935 0.2805118
#> EP NA NA 0.2634237 0.4580196 0.3908239 0.1750448
#> EL NA NA NA 0.3851451 0.2554068 0.9118653
#> ED NA NA NA NA 0.6974629 0.3897128
#> CL NA NA NA NA NA 0.3003636
#> CD NA NA NA NA NA NA
make_lower_tri(m)
#> EH EP EL ED CL CD
#> EH NA NA NA NA NA NA
#> EP 0.8695460 NA NA NA NA NA
#> EL 0.3626537 0.2634237 NA NA NA NA
#> ED 0.6302561 0.4580196 0.3851451 NA NA NA
#> CL 0.3971935 0.3908239 0.2554068 0.6974629 NA NA
#> CD 0.2805118 0.1750448 0.9118653 0.3897128 0.3003636 NA
make_lower_tri(m) %>%
make_sym(diag = 0)
#> EH EP EL ED CL CD
#> EH 0.0000000 0.8695460 0.3626537 0.6302561 0.3971935 0.2805118
#> EP 0.8695460 0.0000000 0.2634237 0.4580196 0.3908239 0.1750448
#> EL 0.3626537 0.2634237 0.0000000 0.3851451 0.2554068 0.9118653
#> ED 0.6302561 0.4580196 0.3851451 0.0000000 0.6974629 0.3897128
#> CL 0.3971935 0.3908239 0.2554068 0.6974629 0.0000000 0.3003636
#> CD 0.2805118 0.1750448 0.9118653 0.3897128 0.3003636 0.0000000
tidy_sym(m)
#> # A tibble: 36 × 3
#> group1 group2 value
#> <chr> <chr> <dbl>
#> 1 CD EH 0.281
#> 2 CD EP 0.175
#> 3 CD EL 0.912
#> 4 CD ED 0.390
#> 5 CD CL 0.300
#> 6 CD CD 1
#> 7 CL EH 0.397
#> 8 CL EP 0.391
#> 9 CL EL 0.255
#> 10 CL ED 0.697
#> # … with 26 more rows
tidy_sym(make_lower_tri(m))
#> # A tibble: 15 × 3
#> group1 group2 value
#> <chr> <chr> <dbl>
#> 1 CD EH 0.281
#> 2 CD EP 0.175
#> 3 CD EL 0.912
#> 4 CD ED 0.390
#> 5 CD CL 0.300
#> 6 CL EH 0.397
#> 7 CL EP 0.391
#> 8 CL EL 0.255
#> 9 CL ED 0.697
#> 10 ED EH 0.630
#> 11 ED EP 0.458
#> 12 ED EL 0.385
#> 13 EL EH 0.363
#> 14 EL EP 0.263
#> 15 EP EH 0.870
# }