context("nn2")

test_that("basic use of nn2", {

  res<-structure(list(nn.idx = structure(c(1L, 2L, 2L), 
                                         .Dim = c(3L, 1L)),
                      nn.dists = structure(c(0.01, 1, 2), .Dim = c(3L, 1L))), 
                 .Names = c("nn.idx", "nn.dists"))
  
  res.func<-nn2(rbind(c(1,0),c(2,0)),rbind(c(1.01,0),c(3,0),c(4.0,0)),k=1)
  expect_equal(res,res.func)
  
  a=structure(c(-0.626453810742332, 0.183643324222082, -0.835628612410047, 
                1.59528080213779, 0.329507771815361, -0.820468384118015, 0.487429052428485, 
                0.738324705129217, 0.575781351653492, -0.305388387156356, 1.51178116845085, 
                0.389843236411431, -0.621240580541804, -2.2146998871775, 1.12493091814311, 
                -0.0449336090152309, -0.0161902630989461, 0.94383621068530, 0.821221195098089, 
                0.593901321217509, 0.918977371608218, 0.782136300731067, 0.0745649833651906, 
                -1.98935169586337, 0.61982574789471, -0.0561287395290008, -0.155795506705329, 
                -1.47075238389927, -0.47815005510862, 0.417941560199702), .Dim = c(10L, 
                                                                                   3L))
  
  b=structure(c(1.35867955152904, -0.102787727342996, 0.387671611559369, 
                -0.0538050405829051, -1.37705955682861, -0.41499456329968, -0.394289953710349, 
                -0.0593133967111857, 1.10002537198388, 0.763175748457544, -0.164523596253587, 
                -0.253361680136508, 0.696963375404737, 0.556663198673657, -0.68875569454952, 
                -0.70749515696212, 0.36458196213683, 0.768532924515416, -0.112346212150228, 
                0.881107726454215, 0.398105880367068, -0.612026393250771, 0.341119691424425, 
                -1.12936309608079, 1.43302370170104, 1.98039989850586, -0.367221476466509, 
                -1.04413462631653, 0.569719627442413, -0.135054603880824), .Dim = c(10L, 
                                                                                    3L))
  
  nearest=structure(list(
    nn.idx = structure(c(7L, 7L, 5L, 9L, 3L, 2L, 6L, 
                         9L, 7L, 9L, 2L, 6L, 2L, 8L, 6L, 3L, 10L, 8L, 2L, 5L, 9L, 3L, 
                         10L, 7L, 10L, 10L, 7L, 7L, 5L, 7L, 5L, 9L, 9L, 6L, 2L, 6L, 9L, 
                         6L, 9L, 2L, 10L, 10L, 7L, 10L, 1L, 5L, 3L, 10L, 10L, 10L),
                       .Dim = c(10L, 5L)), 
    nn.dists = structure(c(1.04301819567468, 0.782785251535478, 
                           0.514019762075842, 0.943635726058299, 1.46393847125353, 1.73157573316917, 
                           0.66791447696244, 0.852326186446708, 0.954406845715277, 0.395496580572611, 
                           1.35481071903339, 0.931412898425681, 0.574844301957827, 0.945472961596115, 
                           1.71518967014802, 1.95360681279363, 0.822782991518318, 0.921390522381496, 
                           1.06633538007411, 0.904080753178077, 1.53376883835267, 1.06948509416105, 
                           0.704879811283639, 1.25256907321914, 1.95552547157996, 2.03639936314308, 
                           0.983420985126367, 1.30532148465522, 1.45844529983923, 0.938940949941509, 
                           1.66464626768377, 1.27793083718641, 0.849722423887674, 1.44966319723756, 
                           2.00569777023645, 2.179643484087, 1.07789743302845, 1.4890400761415, 
                           1.49813576432115, 1.19098185772077, 1.82885863701822, 1.3489757618116, 
                           0.874908208472254, 1.56806650285981, 2.38117935086023, 2.40067304459157, 
                           1.16696237017602, 1.49288843286122, 1.58019302443234, 1.23698083599426),
                         .Dim = c(10L, 5L))),
    .Names = c("nn.idx", "nn.dists"))
  
  expect_equal(nn2(a, b, k=5), nearest, tol=1e-6)
})

# NB this fails with the version of ANN distributed with knnFinder v1.0
test_that("nn2 with identical point", {
	res<-structure(list(nn.idx = structure(c(1L, 2L, 2L), .Dim = c(3L, 
	1L)), nn.dists = structure(c(0.00, 1, 2), .Dim = c(3L, 1L))), .Names = c("nn.idx", 
	"nn.dists"))
	
	res.func<-nn2(rbind(c(1,0),c(2,0)),rbind(c(1.0,0),c(3,0),c(4.0,0)),k=1)
	expect_equal(res,res.func)
})


test_that("nn2 with different search / tree types", {
	set.seed(1)
	a=matrix(rnorm(3000),ncol=3)
	b=matrix(rnorm(3000),ncol=3)
	n.standard<-nn2(a,b,k=5,searchtype='standard')
	n.priority<-nn2(a,b,k=5,searchtype='priority')
	n.bd.standard<-nn2(a,b,k=5,searchtype='standard',treetype='bd')
	n.bd.priority<-nn2(a,b,k=5,searchtype='priority',treetype='bd')

	expect_equal(n.standard,n.priority)
	expect_equal(n.standard,n.bd.standard)
	expect_equal(n.standard,n.bd.priority)
})

test_that("nn2 fixed radius with large radius", {
	set.seed(1)
	a=matrix(rnorm(3000),ncol=3)
	b=matrix(rnorm(3000),ncol=3)
	n.standard<-nn2(a,b,k=5,searchtype='standard')
	n.rad<-nn2(a,b,k=5,searchtype='radius',radius=20.0)
	n.bd.rad<-nn2(a,b,k=5,searchtype='radius',radius=20.0,treetype='bd')

	expect_equal(n.standard,n.rad)
	expect_equal(n.standard,n.bd.rad)
})

test_that("matrix with 0 columns", {
  d=matrix(ncol=0,nrow=90)
  expect_error(nn2(d))
})

test_that("all NA", {
  data=matrix(rnorm(10), ncol=2)
  query=matrix(rep(NA_real_,10), ncol=2)
  expect_error(nn2(data = data, query = query, k=1))
})

test_that("mixture of matrix and vector inputs", {
  mat=matrix(rnorm(10), ncol=1)
  vec=as.numeric(mat)
  expect_is(res<-nn2(data = mat, query = vec, k=1), 'list')
  expect_equal(nn2(data = vec, query = mat, k=1), res)
  expect_equal(nn2(data = vec, query = vec, k=1), res)
})

test_that("vector inputs give outputs of appropriate length", {
  expect_is(res<-nn2(data = rnorm(10), query = rnorm(5), k=1), 'list')
  expect_equal(length(res$nn.idx), 5L)
})

test_that("inputs with different dimensions", {
  mat=matrix(rnorm(20), ncol=2)
  vec=as.numeric(mat[,1])
  expect_error(nn2(data = mat, query = vec, k=1), 'same dimensions')
})