fields testing scripts {fields}R Documentation

Testing fields functions

Description

Some of the basic methods in fields can be tested by directly implementing the linear algebra using matrix expressions and other functions can be cross checked within fields. These comparisons are done in the the R source code test files in the tests subdirectory of fields. The function test.for.zero is useful for comparing the tests in a meaninful and documented way.

Usage

test.for.zero( xtest,xtrue,  tol= 1.0e-8, relative=TRUE, tag=NULL)

Arguments

xtest Vector of target values
xtrue Vector of reference values
tol Tolerance to judge whether the test passes.
relative If true a relative error comparison is used. (See details below.)
tag A text string to be printed out with the test results as a reference

Details

The scripts in the tests subdirectory are

Krig.test.R:
Tests basic parts of the Krig and Tps functions including replicated and weighted observations.
Krig.se.test.R:
Tests computations of standard errors for the Kriging estimate.
Krig.se.grid.test.R
Tests approximate standard errors for the Krig function found by Monte Carlo conditional simulation.

Krig.test.W.R
Tests predictions and A matrix when an off diagonal observation weight matrix is used.
Krig.se.W.R
Tests standard errors when an off diagonal observation weight matrix is used.
spam.test.R
Tests sparse matrix formats and linear algebra.
Wend.test.R
Tests form for Wendland covariance family and its use of sparse matrix formats.
diag.multiply.test.R
Tests special (efficient) version of matrix multiply for diagonal matrices.
evlpoly.test.R
Tests evaluation of univariate and multivariate polynomial evaluation.
mKrig.test.R
Tests the micro Krig function with and without sparse matrix methods.

To run the tests just attach the fields library and source the testing file. In the the fields source code these are in a subdirectory "tests". Compare the output to the "XXX.Rout.save" text file. Keeping in mind that no test messages should print if all is well, this is really a formality. The main reason these comparisions are provided is for matching the conventions of the R package checking utilities.

test.for.zero is used to print out the result for each individual comparison. Failed tests are potentially very bad and are reported with a string beginning

"FAILED test value = ... "

If the object test.for.zero.flag exists (it can have any value), all the tests that pass print text beginning,

" PASSED test at tolerance ..."

This startegy means that if all tests succeed nothing and the object test.for.zero.flag does not exist then nothing is printed in the test scripts. This is option simplifies the output scripts for running through the tests – no news is good news.

FORM OF COMPARISON: The actual test done is the sum of absolute differnces:

test value = sum( abs(c(xtest) - c( xtrue) ) ) /denom

Where demon is either mean( abs(c(xtrue))) for relative error or 1.0 otherwise.

Note the use of "c" here to stack any structure in xtest and xtrue into a vector.

[Package fields version 5.02 Index]