R语言三维数组中匹配指定向量的索引获取方法

For a specific given i #

If you have a particular value of i (say i = 42), you can find the matching j by checking each of the 5 slices against V using identical():

# Example: given i = 42
i <- 42
j_match <- which(sapply(1:5, function(j) identical(h[i, j, ], V)))

Since the problem states there's exactly one match per i, j_match will be a single integer between 1 and 5.

Get all (i,j) pairs that match V #

To find every combination of i (1-100) and j (1-5) where the 9-element slice matches V, you can use a straightforward approach with expand.grid and sapply:

# Create all possible (i,j) pairs
all_pairs <- expand.grid(i = 1:100, j = 1:5)

# Filter pairs where the slice matches V exactly
matching_pairs <- all_pairs[
  sapply(1:nrow(all_pairs), function(k) {
    identical(h[all_pairs$i[k], all_pairs$j[k], ], V)
  }),
]

The result matching_pairs is a data frame with columns i and j, containing all index pairs where the slice matches V.

Alternative vectorized approach (better for larger datasets) #

If you ever work with bigger arrays later, reshaping the 3D array into a 2D matrix can speed up the matching process:

# Reshape 3D array into a 2D matrix (each row = a 9-element sequence)
h_matrix <- matrix(h, nrow = 100 * 5, ncol = 9)

# Find rows that match V exactly
matching_rows <- which(apply(h_matrix, 1, function(row) identical(row, V)))

# Convert row indices back to (i,j) pairs
i_vals <- ceiling(matching_rows / 5)
j_vals <- ifelse(matching_rows %% 5 == 0, 5, matching_rows %% 5)

matching_pairs <- data.frame(i = i_vals, j = j_vals)

This works because each i corresponds to 5 consecutive rows in the matrix (j=1 to 5). The modulo operation gives us the j index, with a quick adjustment for when the row number is a multiple of 5 (since 5 mod 5 is 0, we replace that with 5).

All these methods rely on identical(), which ensures an exact match (including data type and structure) just as you specified.

内容的提问来源于stack exchange，提问作者ChuckP