This function creates a 1-4 dimensional grid in long format, with the cell
positions encoded in the x, y, z, and t columns. A long_cell object
is the base class for the tidy interface to ambient, and allows a very
flexible approach to pattern generation at the expense of slightly lower
performance than the noise_* functions that maps directly to the underlying
C++ code.
For long_grid() vectors of grid cell positions for each
dimension. The final dimensionality of the object is determined by how many
arguments are given. For slice_at() an integer defining the index at the
given dimension to extract.
A long_grid object
The dimension to get the cell index at, either as an integer or string.
Arguments passed on to methods (ignored)
The unquoted value to use for filling out the array/matrix
grid <- long_grid(1:10, seq(0, 1, length = 6), c(3, 6))
# Get which row each cell belongs to
grid_cell(grid, 2) # equivalent to grid_cell(grid, 'y')
#> [1] 1 1 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1
#> [38] 1 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1 1
#> [75] 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1 1 2 2 3 3 4 4 5 5 6 6 1 1 2
#> [112] 2 3 3 4 4 5 5 6 6
# Convert the long_grid to an array and fill with the x position
as.array(grid, x)
#> , , 1
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 1 1 1 1 1 1
#> [2,] 1 1 1 1 1 1
#>
#> , , 2
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 2 2 2 2 2 2
#> [2,] 2 2 2 2 2 2
#>
#> , , 3
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 3 3 3 3 3 3
#> [2,] 3 3 3 3 3 3
#>
#> , , 4
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 4 4 4 4 4 4
#> [2,] 4 4 4 4 4 4
#>
#> , , 5
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 5 5 5 5 5 5
#> [2,] 5 5 5 5 5 5
#>
#> , , 6
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 6 6 6 6 6 6
#> [2,] 6 6 6 6 6 6
#>
#> , , 7
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 7 7 7 7 7 7
#> [2,] 7 7 7 7 7 7
#>
#> , , 8
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 8 8 8 8 8 8
#> [2,] 8 8 8 8 8 8
#>
#> , , 9
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 9 9 9 9 9 9
#> [2,] 9 9 9 9 9 9
#>
#> , , 10
#>
#> y
#> z [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 10 10 10 10 10 10
#> [2,] 10 10 10 10 10 10
#>
# Extract the first column
slice_at(grid, x = 1)
#> # A tibble: 12 × 3
#> x y z
#> <int> <dbl> <dbl>
#> 1 1 0 3
#> 2 1 0 6
#> 3 1 0.2 3
#> 4 1 0.2 6
#> 5 1 0.4 3
#> 6 1 0.4 6
#> 7 1 0.6 3
#> 8 1 0.6 6
#> 9 1 0.8 3
#> 10 1 0.8 6
#> 11 1 1 3
#> 12 1 1 6
# Convert the first column to a matrix filled with y position
as.matrix(slice_at(grid, x = 1), y)
#> z
#> y [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0 0.2 0.4 0.6 0.8 1
#> [2,] 0 0.2 0.4 0.6 0.8 1