tests/testthat/test-gmeans.R

In neurodata/knorR: A Parallel Clustering Non-Uniform Memory Access ('NUMA') Optimized Library

# Copyright 2016 neurodata (http://neurodata.io/)
# Written by Disa Mhembere (disa@jhu.edu)
#
# This file is part of knor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#require(clusternor)
#require(testthat)

#fn <- "test.data.bin"
#centroidfn <- "test.centroids.bin"

#kmax <- 8
#nrow <- 50
#ncol <- 5
#nthread <- 2
#mb.size <- 20
#iter.max <- 20

## Data in memory, compute centroids
#test.data.in.mem <- function() {
    #cat("Data ==> memory, centroids ==> compute\n\n")
    #print(Gmeans(test_data, kmax, dist.type="eucl",
                 #iter.max=iter.max, nthread=nthread, strictness=2))
#}

### Data in memory, centroids in memory
#test.data.centroids.in.mem <- function() {
    #cat("Data ==> memory, centroids ==> memory\n\n")
    #print(Gmeans(test_data, kmax, init=test_centroids[3:4,],
           #dist.type="cos", iter.max=iter.max, nthread=nthread))
#}

### Data on disk, compute centroids
#test.data.ex.mem <- function() {
    #cat("Data ==> disk, centroids ==> compute\n\n")
    #print(Gmeans(fn, kmax, nrow, ncol, iter.max=iter.max,
                 #nthread=nthread, init="forgy", strictness=1))
#}

### Data on disk, centroids in memory
#test.centroids.in.mem <- function() {
    #cat("Data ==> disk, centroids ==> memory\n\n")
    #print(Gmeans(fn, kmax,  nrow, ncol, iter.max=iter.max,
                 #init=test_centroids[1:2,], nthread=nthread, strictness=3))
#}

## Main

#test.centroids.in.mem()

#ret1 <- test.data.ex.mem()
#ret2 <- test.data.ex.mem()
#test_that("data EM compared to same", {
              #expect_identical(ret1, ret2)
#})

#ret1 <- test.data.centroids.in.mem()
#ret2 <- test.data.centroids.in.mem()
#test_that("Data in-mem compared to same", {
              #expect_identical(ret1, ret2)})

#ret1 <- test.data.in.mem()
#ret2 <- test.data.in.mem()
#test_that("data IM compared to same", {
              #expect_identical(ret1, ret2)
#})