allequal {spam}

Test if Two Sparse Matrices are (Nearly) Equal

Description

Utility to compare two spam objects testing 'near equality'. Depending on the type of difference, comparison is still made to some extent, and a report of the differences is returned.

Usage

## S3 method for class 'spam'
all.equal(target, current, tolerance = .Machine$double.eps^0.5,
    scale = NULL, check.attributes = FALSE,...)

Arguments

target

a spam object.

current

another spam object to be compared with target.

tolerance

numeric >= 0. Differences smaller than tolerance are not considered.

scale

numeric scalar > 0 (or NULL). See ‘Details’.

check.attributes

currently not yet implemented.

...

Further arguments for different methods.

Details

Numerical comparisons for scale = NULL (the default) are typically on a relative difference scale unless the target values are close to zero or infinite. Specifically, the scale is computed as the average absolute value of target. If this scale is finite and exceeds tolerance, differences are expressed relative to it; otherwise, absolute differences are used.

If scale is numeric (and positive), absolute comparisons are made after scaling (dividing) by scale. Note that if all of scale is sufficiently close to 1 (specifically, within tolerance), the difference is still reported as being on an absolute scale.

Do not use all.equal.spam directly in if expressions: either use isTRUE( all.equal.spam(...)) or identical if appropriate.

Cholesky decomposition routines use this function to test for symmetry.

A method for matrix-spam objects is defined as well.

There is the additional catch of a zero matrix being represented by one zero element, see ‘Examples’ below.

Value

Either TRUE or a vector of 'mode' "character" describing the differences between target and current.

Author(s)

Reinhard Furrer

See Also

isSymmetric.spam and cleanup.

Examples

obj <- diag.spam(2)
obj[1,2] <- .Machine$double.eps

all.equal( diag.spam(2), obj)

all.equal( t(obj), obj)

all.equal( t(obj), obj*1.1)

# We can compare a spam to a matrix
all.equal(diag(2),diag.spam(2))

# the opposite does often not make sense,
# hence, it is not implemented.
all.equal(diag.spam(2),diag(2))


# A zero matrix contains one element:
str(spam(0))
# hence
all.equal.spam(spam(0,3,3), diag.spam(0,3) )
norm(spam(0,3,3) - diag.spam(0,3) )