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#14: Correction fixes #15

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May 12, 2024
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#14: Correction fixes #15

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951dd60
#14: fix k=2 failure
jlmelville May 12, 2024
76abb36
#14: fix metric correction
jlmelville May 12, 2024
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8 changes: 5 additions & 3 deletions R/corrections.R
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Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@
}
}

apply_dense_alt_metric_uncorrection <- function(metric, dist) {

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file=R/corrections.R,line=45,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
if (is.matrix(dist)) {
switch(metric,
cosine = apply(dist, c(1, 2), uncorrect_alternative_cosine),
Expand All @@ -66,7 +66,7 @@
}
}

apply_sparse_alt_metric_uncorrection <- function(metric, dist) {

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file=R/corrections.R,line=69,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
if (is.matrix(dist)) {
switch(metric,
cosine = apply(dist, c(1, 2), uncorrect_alternative_cosine),
Expand All @@ -90,7 +90,7 @@
}
}

apply_dense_alt_metric_correction <- function(metric, dist) {

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file=R/corrections.R,line=93,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
if (is.matrix(dist)) {
switch(metric,
cosine = apply(dist, c(1, 2), correct_alternative_cosine),
Expand All @@ -114,7 +114,7 @@
}
}

apply_sparse_alt_metric_correction <- function(metric, dist) {

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file=R/corrections.R,line=117,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
if (is.matrix(dist)) {
switch(metric,
cosine = apply(dist, c(1, 2), correct_alternative_cosine),
Expand Down Expand Up @@ -208,14 +208,16 @@
-log2(cos(pi * res))
}

float32_max <- 3.4028235e+38

uncorrect_alternative_jaccard <- function(dist) {
ifelse(dist >= (1.0 - 1.e-10), 0.0, -log2(1.0 - dist))
ifelse(dist >= (1.0 - 1.e-10), float32_max, -log2(1.0 - dist))
}

uncorrect_alternative_hellinger <- function(dist) {

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file=R/corrections.R,line=217,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
ifelse(dist >= (1.0 - 1.e-10), 0.0, -log2(1.0 - (dist * dist)))
ifelse(dist >= (1.0 - 1.e-10), float32_max, -log2(1.0 - (dist * dist)))
}

uncorrect_alternative_cosine <- function(dist) {
ifelse(dist >= (1.0 - 1.e-10), 0.0, -log2(1.0 - dist))
ifelse(dist >= (1.0 - 1.e-10), float32_max, -log2(1.0 - dist))
}
4 changes: 2 additions & 2 deletions R/rnndescent.R
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Original file line number Diff line number Diff line change
Expand Up @@ -2359,13 +2359,13 @@ prepare_search_graph <- function(data,
sp <- graph_to_csparse(graph)
}

sp <- preserve_zeros(sp)

if (use_alt_metric) {
sp@x <-
apply_alt_metric_uncorrection(metric, sp@x, is_sparse(data))
}

sp <- preserve_zeros(sp)

data <- x2m(data)
if (obs == "R") {
data <- Matrix::t(data)
Expand Down
42 changes: 42 additions & 0 deletions tests/testthat/test_corrections.R
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@@ -0,0 +1,42 @@
library(rnndescent)
context("Corrections")

# 14: bad uncorrection broke cosine, jaccard, hellinger default search

float32_max <- 3.4028235e+38

test_that("cosine", {
expect_equal(correct_alternative_cosine(0), 0)
expect_equal(correct_alternative_cosine(1), 0.5)
expect_equal(correct_alternative_cosine(float32_max), 1.0)

expect_equal(uncorrect_alternative_cosine(0), 0)
expect_equal(uncorrect_alternative_cosine(0.5), 1.0)
expect_equal(uncorrect_alternative_cosine(1), float32_max)
})

test_that("jaccard", {
expect_equal(correct_alternative_jaccard(0), 0)
expect_equal(correct_alternative_jaccard(1), 0.5)
expect_equal(correct_alternative_jaccard(float32_max), 1.0)

expect_equal(uncorrect_alternative_jaccard(0), 0)
expect_equal(uncorrect_alternative_jaccard(0.5), 1.0)
expect_equal(uncorrect_alternative_jaccard(1), float32_max)
})

test_that("hellinger", {
expect_equal(correct_alternative_hellinger(0), 0)
expect_equal(correct_alternative_hellinger(1), 1 / sqrt(2))
expect_equal(correct_alternative_hellinger(float32_max), 1.0)

expect_equal(uncorrect_alternative_hellinger(0), 0)
expect_equal(uncorrect_alternative_hellinger(1 / sqrt(2)), 1.0)
expect_equal(uncorrect_alternative_hellinger(1), float32_max)
})

test_that("dot", {
expect_equal(correct_alternative_dot(0), 0)
expect_equal(correct_alternative_dot(1), 0.5)
expect_equal(correct_alternative_dot(float32_max), 1.0)
})
197 changes: 197 additions & 0 deletions tests/testthat/test_sparse_search.R
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@@ -0,0 +1,197 @@
library(rnndescent)
context("Sparse search/build")

#14: Alt metric gave the wrong results (because of a bad uncorrection)

# [1,] . . 1 . . . . . 1 1 . 1 . 1 . 1 1 2 1
# [2,] 1 1 . 1 1 1 1 1 . . 1 . 1 . 1 . . . .
# [3,] . . . . . . . . . . . . . . . . . . 1

xi <- c(
1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L,
0L, 0L, 0L, 0L, 2L
)
xj <- c(
0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 18L
)
xx <- c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1)
xsp <- Matrix::sparseMatrix(
i = xi + 1,
j = xj + 1,
x = xx,
dims = c(3, 19),
)
xd <- as.matrix(xsp)

# [1,] 1 1 . . 1 1 1 1 . . 1 . 1 . 1 . . . .
# [2,] 1 1 . 1 1 1 1 1 . . 1 . 1 . 1 . . . .
# [3,] 1 1 . . 1 1 1 1 . . 1 . 1 . 1 . . . .
# [4,] 1 1 . . 1 . 1 . . . 1 . . . 1 . . . .
# [5,] . . 1 . . . . . 1 1 . 1 . 1 . 1 1 2 1
# [6,] . . 1 . . . . . 1 1 . 1 . 1 . . 1 2 1
# [7,] . . 1 . . . . . 1 1 . 1 . 1 . 1 1 2 1
# [8,] . . . . . . . . 1 1 . . . 1 . . . 1 .

yi <- c(
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 4L, 5L, 6L, 7L, 4L,
5L, 6L, 7L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 0L, 1L, 2L, 4L, 5L, 6L,
7L, 0L, 1L, 2L, 3L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 7L, 4L, 5L,
6L
)
yj <- c(
0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 4L, 4L, 4L,
4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L,
13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 15L, 15L, 16L, 16L, 16L,
17L, 17L, 17L, 17L, 18L, 18L, 18L
)
yx <- c(
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1,
1, 1
)
ysp <- Matrix::sparseMatrix(
i = yi + 1,
j = yj + 1,
x = yx,
dims = c(8, 19),
)
yd <- as.matrix(ysp)

index_graph_idx <- matrix(c(
1, 3, 2,
2, 3, 1,
3, 1, 2
), nrow = 3, byrow = TRUE)

index_graph_dist <- matrix(c(
0, 0.711325, 1,
0, 1, 1,
0, 0.711325, 1
), nrow = 3, byrow = TRUE)

search_graph <- Matrix::sparseMatrix(
i = c(1L, 2L, 0L, 0L, 1L) + 1,
j = c(0L, 0L, 1L, 2L, 2L) + 1,
x = c(1, 0.7113249, 1, 0.7113249, 1),
dims = c(3, 3),
)

k3_idx <- matrix(c(
2, 1, 3,
2, 1, 3,
2, 1, 3,
2, 1, 3,
1, 3, 2,
1, 3, 2,
1, 3, 2,
1, 2, 3
), nrow = 8, byrow = TRUE)

k3_dist <- matrix(c(
5.131668e-02, 1.0000000, 1,
-1.192093e-07, 1.0000000, 1,
5.131668e-02, 1.0000000, 1,
2.254034e-01, 1.0000000, 1,
1.192093e-07, 0.7113249, 1,
4.257292e-02, 0.6984887, 1,
1.192093e-07, 0.7113249, 1,
2.783122e-01, 1.0000000, 1
), nrow = 8, byrow = TRUE)

test_that("sparse no alt metric", {
set.seed(2024)
nndes_index <- rnnd_build(data = xsp, k = 3, metric = "cosine", use_alt_metric = FALSE)
expect_equal(nndes_index$graph$idx, index_graph_idx)
expect_equal(nndes_index$graph$dist, index_graph_dist, tol = 1e-6)
expect_equal(nndes_index$search_graph, search_graph, tol = 1e-7)

k1_query <- rnnd_query(nndes_index, query = ysp, k = 1)
expect_equal(k1_query$idx, k3_idx[, 1, drop = FALSE])
expect_equal(k1_query$dist, k3_dist[, 1, drop = FALSE], tol = 1e-6)

k2_query <- rnnd_query(nndes_index, query = ysp, k = 2)
expect_equal(k2_query$idx, k3_idx[, 1:2])
expect_equal(k2_query$dist, k3_dist[, 1:2], tol = 1e-6)

k3_query <- rnnd_query(nndes_index, query = ysp, k = 3)
expect_equal(k3_query$idx, k3_idx)
expect_equal(k3_query$dist, k3_dist, tol = 1e-6)
})

test_that("dense no alt metric", {
set.seed(2024)
nndes_index <- rnnd_build(data = xd, k = 3, metric = "cosine", use_alt_metric = FALSE)
expect_equal(nndes_index$graph$idx, index_graph_idx)
expect_equal(nndes_index$graph$dist, index_graph_dist, tol = 1e-6)
expect_equal(nndes_index$search_graph, search_graph, tol = 1e-7)

k1_query <- rnnd_query(nndes_index, query = yd, k = 1)
expect_equal(k1_query$idx, k3_idx[, 1, drop = FALSE])
expect_equal(k1_query$dist, k3_dist[, 1, drop = FALSE], tol = 1e-6)

k2_query <- rnnd_query(nndes_index, query = yd, k = 2)
expect_equal(k2_query$idx, k3_idx[, 1:2])
expect_equal(k2_query$dist, k3_dist[, 1:2], tol = 1e-6)

k3_query <- rnnd_query(nndes_index, query = yd, k = 3)
expect_equal(k3_query$idx, k3_idx)
expect_equal(k3_query$dist, k3_dist, tol = 1e-6)
})

test_that("sparse alt metric", {
set.seed(2024)
nndes_index <- rnnd_build(data = xsp, k = 3, metric = "cosine", use_alt_metric = TRUE)
expect_equal(nndes_index$graph$idx, index_graph_idx)
expect_equal(nndes_index$graph$dist, index_graph_dist, tol = 1e-6)
expect_equal(nndes_index$search_graph, search_graph, tol = 1e-7)

k1_query <- rnnd_query(nndes_index, query = ysp, k = 1)
expect_equal(k1_query$idx, k3_idx[, 1, drop = FALSE])
expect_equal(k1_query$dist, k3_dist[, 1, drop = FALSE], tol = 1e-6)

k2_query <- rnnd_query(nndes_index, query = ysp, k = 2)
expect_equal(k2_query$idx, k3_idx[, 1:2])
expect_equal(k2_query$dist, k3_dist[, 1:2], tol = 1e-6)

k3_query <- rnnd_query(nndes_index, query = ysp, k = 3)
expect_equal(k3_query$idx, k3_idx)
expect_equal(k3_query$dist, k3_dist, tol = 1e-6)
})

test_that("dense alt metric", {
set.seed(2024)
nndes_index <- rnnd_build(data = xd, k = 3, metric = "cosine", use_alt_metric = TRUE)
expect_equal(nndes_index$graph$idx, index_graph_idx)
expect_equal(nndes_index$graph$dist, index_graph_dist, tol = 1e-6)
expect_equal(nndes_index$search_graph, search_graph, tol = 1e-7)

k1_query <- rnnd_query(nndes_index, query = yd, k = 1)
expect_equal(k1_query$idx, k3_idx[, 1, drop = FALSE])
expect_equal(k1_query$dist, k3_dist[, 1, drop = FALSE], tol = 1e-6)

k2_query <- rnnd_query(nndes_index, query = yd, k = 2)
expect_equal(k2_query$idx, k3_idx[, 1:2])
expect_equal(k2_query$dist, k3_dist[, 1:2], tol = 1e-6)

k3_query <- rnnd_query(nndes_index, query = yd, k = 3)
expect_equal(k3_query$idx, k3_idx)
expect_equal(k3_query$dist, k3_dist, tol = 1e-6)
})

test_that("k=2 builds", {
set.seed(2024)
k2dtg <- rnnd_build(data = xd[1:2, ], k = 2, metric = "cosine", use_alt_metric = TRUE)$graph
k2stg <- rnnd_build(data = xsp[1:2, ], k = 2, metric = "cosine", use_alt_metric = TRUE)$graph
expect_equal(k2dtg$idx, k2stg$idx)
expect_equal(k2dtg$dist, k2stg$dist)

k2dfg <- rnnd_build(data = xd[1:2, ], k = 2, metric = "cosine", use_alt_metric = FALSE)$graph
k2sfg <- rnnd_build(data = xsp[1:2, ], k = 2, metric = "cosine", use_alt_metric = FALSE)$graph
expect_equal(k2dfg$idx, k2sfg$idx)
expect_equal(k2dfg$dist, k2sfg$dist)
expect_equal(k2dfg$idx, k2dtg$idx)
})
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