Fast Row/Column Arithmetic for Matrix-Like Objects

Description

Fast operators to perform row- or column-wise replacing and sweeping operations of vectors on matrices, data frames, lists.

Usage

## Perform the operation with v and each row of X

X %rr% v    # Replace rows of X with v
X %r+% v    # Add v to each row of X
X %r-% v    # Subtract v from each row of X
X %r*% v    # Multiply each row of X with v
X %r/% v    # Divide each row of X by v

## Perform a column-wise operation between V and X

X %cr% V    # Replace columns of X with V
X %c+% V    # Add V to columns of X
X %c-% V    # Subtract V from columns of X
X %c*% V    # Multiply columns of X with V
X %c/% V    # Divide columns of X by V

Arguments

Details

With a matrix or data frame X, the default behavior of R when calling X op v (such as multiplication X * v) is to perform the operation of v with each column of X. The equivalent operation is performed by X %cop% V, with the difference that it computes significantly faster if X/V is a data frame / list. A more complex but frequently required task is to perform an operation with v on each row of X. This is provided based on efficient C++ code by the %rop% set of functions, e.g. X %r*% v efficiently multiplies v to each row of X.

Value

X where the operation with v / V was performed on each row or column. All attributes of X are preserved.

Note

Computations and Output: These functions are all quite simple, they only work with X on the LHS i.e. v %op% X will likely fail. The row operations are simple wrappers around TRA which provides more operations including grouped replacing and sweeping (where v would be a matrix or data frame with less rows than X being mapped to the rows of X by grouping vectors). One consequence is that just like TRA, row-wise mathematical operations (+, -, *, /) always yield numeric output, even if both X and v may be integer. This is different for column- operations which depend on base R and may also preserve integer data.

Rules of Arithmetic: Since these operators are defined as simple infix functions, the normal rules of arithmetic are not respected. So a %c+% b %c*% c evaluates as (a %c+% b) %c*% c. As with all chained infix operations, they are just evaluated sequentially from left to right.

Performance Notes: The function setop and a related set of %op=% operators can be used to perform these operations by reference, and are faster if copies of the output are not required!! Furthermore, for Fast Statistical Functions, using fmedian(X, TRA = "-") will be a tiny bit faster than X %r-% fmedian(X). Also use fwithin(X) for fast centering using the mean, and fscale(X) for fast scaling and centering or mean-preserving scaling.

See Also

setop, TRA, dapply, Efficient Programming, Data Transformations, Collapse Overview

Examples

## Using data frame's / lists
v <- mtcars$cyl
mtcars %cr% v
mtcars %c-% v
mtcars %r-% seq_col(mtcars)
mtcars %r-% lapply(mtcars, quantile, 0.28)

mtcars %c*% 5       # Significantly faster than mtcars * 5
mtcars %c*% mtcars  # Significantly faster than mtcars * mtcars

## Using matrices
X <- qM(mtcars)
X %cr% v
X %c-% v
X %r-% dapply(X, quantile, 0.28)

## Chained Operations
library(magrittr) # Note: Used because |> is not available on older R versions
mtcars %>% fwithin() %r-% rnorm(11) %c*% 5 %>%
    tfm(mpg = fsum(mpg)) %>% qsu()