greta (version 0.4.1)

functions: functions for greta arrays

Description

This is a list of functions (mostly from base R) that are currently implemented to transform greta arrays. Also see operators and transforms.

Usage

# logarithms and exponentials
 log(x)
 exp(x)
 log1p(x)
 expm1(x)
# miscellaneous mathematics
 abs(x)
 mean(x)
 sqrt(x)
 sign(x)
# rounding of numbers
 ceiling(x)
 floor(x)
 round(x, digits = 0)
# trigonometry
 cos(x)
 sin(x)
 tan(x)
 acos(x)
 asin(x)
 atan(x)
 cosh(x)
 sinh(x)
 tanh(x)
 acosh(x)
 asinh(x)
 atanh(x)
 cospi(x)
 sinpi(x)
 tanpi(x)
# special mathematical functions
 lgamma(x)
 digamma(x)
 trigamma(x)
 choose(n, k)
 lchoose(n, k)
# matrix operations
 t(x)
 chol(x, ...)
 chol2inv(x, ...)
 cov2cor(V)
 solve(a, b, ...)
 kronecker(X, Y, FUN = c('*', '/', '+', '-'))
# reducing operations
 sum(..., na.rm = TRUE)
 prod(..., na.rm = TRUE)
 min(..., na.rm = TRUE)
 max(..., na.rm = TRUE)
# cumulative operations
 cumsum(x)
 cumprod(x)
 cummax(x)
 cummin(x)
# solve an upper or lower triangular system
 backsolve(r, x, k = ncol(r), upper.tri = TRUE,
           transpose = FALSE)
 forwardsolve(l, x, k = ncol(l), upper.tri = FALSE,
              transpose = FALSE)
# miscellaneous operations
 aperm(x, perm)
 apply(x, MARGIN, FUN = c("sum", "max", "mean", "min",
                          "prod", "cumsum", "cumprod"))
 sweep(x, MARGIN, STATS, FUN = c('-', '+', '/', '*'))
 tapply(X, INDEX, FUN = c("sum", "max", "mean", "min", "prod"), ...)

Details

TensorFlow only enables rounding to integers, so round() will error if digits is set to anything other than 0.

Any additional arguments to chol(), chol2inv, and solve() will be ignored, see the TensorFlow documentation for details of these routines.

sweep() only works on two-dimensional greta arrays (so MARGIN can only be either 1 or 2), and only for subtraction, addition, division and multiplication.

tapply() works on column vectors (2D greta arrays with one column), and INDEX cannot be a greta array. Currently five functions are available, and arguments passed to … are ignored.

cospi(), sinpi(), and tanpi() do not use the computationally more stable routines to compute cos(x * pi) etc. that are available in R under some operating systems. Similarly trigamma() uses TensorFlow's polygamma function, resulting in lower precision than R's equivalent.

Examples

# NOT RUN {
x <- as_data(matrix(1:9, nrow = 3, ncol = 3))
a <- log(exp(x))
b <- log1p(expm1(x))
c <- sign(x - 5)
d <- abs(x - 5)

z <- t(a)

y <- sweep(x, 1, e, "-")
# }