ramify.R
In ramify: Additional Matrix Functionality

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matrix(c(1, 2, 3, 4, 5, 6, 7, 8), nrow = 2, byrow = TRUE)

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matrix(c(
  1, 2, 3, 4,
  5, 6, 7, 8
), nrow = 2, byrow = TRUE)

## ----eval=FALSE---------------------------------------------------------------
# install.packages("ramify") # latest stable release

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library(ramify) # load package
mat("1, 2, 3, 4; 5, 6, 7, 8")

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mat("1:4; 5:8", rows = FALSE) # ; separates columns

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mat("1 2 3 4; 5 6 7 8", sep = "") # blank spaces separate columns

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options(mat.rows = FALSE, mat.sep = "") # change default behavior

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strsplit("rnorm(10, sd = 3)", split = ",")

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mat("rnorm(5); rnorm(5, mean = 10)", sep = NULL)

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z <- list("a" = 1:10, "b" = 11:20, "c" = 21:30)

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# Approach 1
matrix(unlist(z), nrow = 3, byrow = TRUE)

# Approach 2
do.call(rbind, z)

# Approach 3
t(simplify2array(z))

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mat(z)

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m <- matrix(rnorm(1000000), nrow = 1000)
# head(m)

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m <- randn(1000, 1000) # see Table 2 for a description of randn
pprint(m)

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# List holding individual variables
z1 <- list(
  Height = c(Joe = 6.2, Mary = 5.7, Pete = 6.1),
  Weight = c(Joe = 192.2, Mary = 164.3, Pete = 201.7),
  Gender = c(Joe = 0, Mary = 1, Pete = 0)
)

as.data.frame(z1) # convert z1 to a data frame

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# List holding records (i.e., individual observations)
z2 <- list(
  Joe = c(Height = 6.2, Weight = 192.2, Gender = 0),
  Mary = c(Height = 5.7, Weight = 164.3, Gender = 1),
  Pete = c(Height = 6.1, Weight = 201.7, Gender = 0)
)

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as.data.frame(t(as.data.frame(z2)))

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dmat(z1, rows = FALSE) # treat list elements as columns of a data frame
dmat(z2) # treat list elements as rows of a data frame

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A1 <- matrix(c(1, 2, 5, 6), nrow = 2, byrow = TRUE)
A2 <- matrix(c(3, 4, 7, 8), nrow = 2, byrow = TRUE)
A3 <- matrix(c(9, 10, 11, 12), nrow = 1)
A <- rbind(cbind(A1, A2), A3)

## ----eval=FALSE---------------------------------------------------------------
# A1 <- mat("1, 2; 5, 6")
# A2 <- mat("3, 4; 7, 8")
# A3 <- mat("9, 10, 11, 12")
# A <- bmat("A1, A2; A3")

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m <- rand(10, 10)
sum(diag(m)) # compute the trace in base R
tr(m) # compute the trace using ramify's tr function

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a <- array(runif(20000), c(100, 100, 2)) # base R
a <- rand(100, 100, 2) # ramify
pprint(a[, , 1]) # print the first matrix

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zeros(10) # 10x1 matrix (i.e., column vector) of zeros
ones(10, 10) # 10x10 matrix of ones
# fill(pi, 10, 10, 3)  # 10x10x3 array filled with the constant pi

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zeros(10, atleast_2d = FALSE) # has class "integer", rather than "matrix"

## ----fig.cap='Color image and contour lines for $y$.', fig.width=7, fig.height=5----
x <- meshgrid(linspace(-4 * pi, 4 * pi, 27)) # list of input matrices
y <- cos(x[[1]]^2 + x[[2]]^2) * exp(-sqrt(x[[1]]^2 + x[[2]]^2) / 6)
par(mar = c(0, 0, 0, 0)) # remove margins
image(y, axes = FALSE) # color image
contour(y, add = TRUE, drawlabels = FALSE) # add contour lines