Ops.tf {tf}

Math, Summary and Ops Methods for tf

Description

These methods and operators mostly work arg-value-wise on tf objects, see ?groupGeneric for implementation details.

Usage

## S3 method for class 'tf'
Ops(e1, e2)

## S3 method for class 'tfd'
e1 == e2

## S3 method for class 'tfd'
e1 != e2

## S3 method for class 'tfb'
e1 == e2

## S3 method for class 'tfb'
e1 != e2

## S3 method for class 'tfd'
Ops(e1, e2)

## S3 method for class 'tfb'
Ops(e1, e2)

## S3 method for class 'tfd'
Math(x, ...)

## S3 method for class 'tfb'
Math(x, ...)

## S3 method for class 'tf'
Summary(...)

## S3 method for class 'tfd'
cummax(...)

## S3 method for class 'tfd'
cummin(...)

## S3 method for class 'tfd'
cumsum(...)

## S3 method for class 'tfd'
cumprod(...)

## S3 method for class 'tfb'
cummax(...)

## S3 method for class 'tfb'
cummin(...)

## S3 method for class 'tfb'
cumsum(...)

## S3 method for class 'tfb'
cumprod(...)

Arguments

e1

an tf or a numeric vector

e2

an tf or a numeric vector

x

an tf

...

tf-objects (not used for Math group generic)

Details

See examples below. Equality checks of functional objects are even more iffy than usual for computer math and not very reliable. Note that max and min are not guaranteed to be maximal/minimal over the entire domain, only on the evaluation grid used for computation. With the exception of addition and multiplication, operations on tfb-objects first evaluate the data on their arg, perform computations on these evaluations and then convert back to an tfb- object, so a loss of precision should be expected – especially so for small spline bases and/or very wiggly data.

Value

a tf- or logical vector with the computed result

See Also

tf_fwise() for scalar summaries of each function in a tf-vector

Examples

set.seed(1859)
f <- tf_rgp(4)
2 * f == f + f
sum(f) == f[1] + f[2] + f[3] + f[4]
log(exp(f)) == f
plot(f, points = FALSE)
lines(range(f), col = 2, lty = 2)

f2 <- tf_rgp(5) |> exp() |> tfb(k = 25)
layout(t(1:3))
plot(f2, col = gray.colors(5))
plot(cummin(f2), col = gray.colors(5))
plot(cumsum(f2), col = gray.colors(5))

# ?tf_integrate for integrals, ?tf_fwise for scalar summaries of each function