Last updated on 2018-11-14 05:49:41 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.1.3 | 19.19 | 247.38 | 266.57 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.1.3 | 15.61 | 195.11 | 210.72 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.1.3 | 335.08 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.1.3 | 304.16 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.1.3 | 30.00 | 323.00 | 353.00 | ERROR | |
| r-patched-linux-x86_64 | 0.1.3 | 13.03 | 205.09 | 218.12 | ERROR | |
| r-patched-solaris-x86 | 0.1.3 | 338.10 | ERROR | |||
| r-release-linux-x86_64 | 0.1.3 | 16.28 | 211.28 | 227.56 | ERROR | |
| r-release-windows-ix86+x86_64 | 0.1.3 | 43.00 | 218.00 | 261.00 | ERROR | |
| r-release-osx-x86_64 | 0.1.3 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 0.1.3 | 36.00 | 319.00 | 355.00 | ERROR | |
| r-oldrel-osx-x86_64 | 0.1.3 | OK |
Version: 0.1.3
Check: examples
Result: ERROR
Running examples in ‘recipes-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: step_isomap
> ### Title: Isomap Embedding
> ### Aliases: step_isomap tidy.step_isomap
> ### Keywords: datagen
>
> ### ** Examples
>
> data(biomass)
>
> biomass_tr <- biomass[biomass$dataset == "Training",]
> biomass_te <- biomass[biomass$dataset == "Testing",]
>
> rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
+ data = biomass_tr)
>
> im_trans <- rec %>%
+ step_YeoJohnson(all_predictors()) %>%
+ step_center(all_predictors()) %>%
+ step_scale(all_predictors()) %>%
+ step_isomap(all_predictors(),
+ options = list(knn = 100),
+ num = 2)
>
> im_estimates <- prep(im_trans, training = biomass_tr)
Error in chckpkg("RSpectra") :
require 'RSpectra' package, install it using install.packages('RSpectra')
Calls: prep ... embed -> .local -> do.call -> <Anonymous> -> chckpkg
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [34s/35s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1016 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [25s/32s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1016 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.1.3
Check: examples
Result: ERROR
Running examples in ‘recipes-Ex.R’ failed
The error most likely occurred in:
> ### Name: step_isomap
> ### Title: Isomap Embedding
> ### Aliases: step_isomap tidy.step_isomap
> ### Keywords: datagen
>
> ### ** Examples
>
> data(biomass)
>
> biomass_tr <- biomass[biomass$dataset == "Training",]
> biomass_te <- biomass[biomass$dataset == "Testing",]
>
> rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
+ data = biomass_tr)
>
> im_trans <- rec %>%
+ step_YeoJohnson(all_predictors()) %>%
+ step_center(all_predictors()) %>%
+ step_scale(all_predictors()) %>%
+ step_isomap(all_predictors(),
+ options = list(knn = 100),
+ num = 2)
>
> im_estimates <- prep(im_trans, training = biomass_tr)
Error in chckpkg("RSpectra") :
require 'RSpectra' package, install it using install.packages('RSpectra')
Calls: prep ... embed -> .local -> do.call -> <Anonymous> -> chckpkg
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-solaris-x86, r-release-windows-ix86+x86_64
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [43s/105s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1018 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [38s/41s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1016 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.1.3
Check: tests
Result: ERROR
Running 'testthat.R' [37s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
-- 1. Error: printing (@test_isomap.R#47) -------------------------------------
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
== testthat results ===========================================================
OK: 1016 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [33s/34s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1016 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavors: r-patched-linux-x86_64, r-release-linux-x86_64
Version: 0.1.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [47s/48s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
── 1. Error: printing (@test_isomap.R#47) ─────────────────────────────────────
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
══ testthat results ═══════════════════════════════════════════════════════════
OK: 1018 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-patched-solaris-x86
Version: 0.1.3
Check: tests
Result: ERROR
Running 'testthat.R' [32s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
-- 1. Error: printing (@test_isomap.R#47) -------------------------------------
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = new("dimRedData", data = 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), .Dim = c(5L, 3L), .Dimnames = list(
NULL, c("x1", "x2", "x3"))), meta = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")),
keep.org.data = TRUE, pars = list(knn = 3, ndim = 3, get_geod = FALSE))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
== testthat results ===========================================================
OK: 1018 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-release-windows-ix86+x86_64
Version: 0.1.3
Check: examples
Result: ERROR
Running examples in 'recipes-Ex.R' failed
The error most likely occurred in:
> ### Name: step_isomap
> ### Title: Isomap Embedding
> ### Aliases: step_isomap tidy.step_isomap
> ### Keywords: datagen
>
> ### ** Examples
>
> data(biomass)
>
> biomass_tr <- biomass[biomass$dataset == "Training",]
> biomass_te <- biomass[biomass$dataset == "Testing",]
>
> rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
+ data = biomass_tr)
>
> im_trans <- rec %>%
+ step_YeoJohnson(all_predictors()) %>%
+ step_center(all_predictors()) %>%
+ step_scale(all_predictors()) %>%
+ step_isomap(all_predictors(),
+ options = list(knn = 100),
+ num = 2)
>
> im_estimates <- prep(im_trans, training = biomass_tr)
Error in dimRedMethodList() : could not find function "dimRedMethodList"
Calls: prep ... embed -> embed -> .local -> match.arg -> eval -> eval
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 0.1.3
Check: tests
Result: ERROR
Running 'testthat.R' [45s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(recipes)
Loading required package: dplyr
Attaching package: 'dplyr'
The following object is masked from 'package:testthat':
matches
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: broom
Attaching package: 'recipes'
The following object is masked from 'package:stats':
step
>
> test_check(package = "recipes")
-- 1. Error: printing (@test_isomap.R#47) -------------------------------------
require 'RSpectra' package, install it using install.packages('RSpectra')
1: expect_output(prep(im_rec, training = dat1, verbose = TRUE)) at testthat/test_isomap.R:47
2: quasi_capture(enquo(object), capture_output, label = label)
3: capture(act$val <- eval_bare(get_expr(quo), get_env(quo)))
4: capture_output_lines(code, print, width = width)
5: eval_with_output(code, print = print, width = width)
6: withr::with_output_sink(temp, withVisible(code))
7: force(code)
8: withVisible(code)
9: eval_bare(get_expr(quo), get_env(quo))
10: prep(im_rec, training = dat1, verbose = TRUE)
11: prep.recipe(im_rec, training = dat1, verbose = TRUE)
12: prep(x$steps[[i]], training = training, info = x$term_info)
13: prep.step_isomap(x$steps[[i]], training = training, info = x$term_info)
14: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
15: embed(dimRedData(as.data.frame(training[, col_names, drop = FALSE])), "Isomap", knn = x$options$knn,
ndim = x$num, .mute = x$options$.mute)
16: .local(.data, ...)
17: do.call(methodObject@fun, args)
18: (function (data, pars, keep.org.data = TRUE)
{
chckpkg("RSpectra")
chckpkg("igraph")
chckpkg("RANN")
message(Sys.time(), ": Isomap START")
meta <- data@meta
orgdata <- if (keep.org.data)
data@data
else NULL
indata <- data@data
if (is.null(pars$eps))
pars$eps <- 0
if (is.null(pars$get_geod))
pars$get_geod <- FALSE
message(Sys.time(), ": constructing knn graph")
knng <- makeKNNgraph(x = indata, k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
geodist <- igraph::distances(knng, algorithm = "dijkstra")
message(Sys.time(), ": Classical Scaling")
k <- geodist^2
k <- .Call(stats:::C_DoubleCentre, k)
k <- -k/2
e <- RSpectra::eigs_sym(k, pars$ndim, which = "LA", opts = list(retvec = TRUE))
e_values <- e$values
e_vectors <- e$vectors
neig <- sum(e_values > 0)
if (neig < pars$ndim) {
warning("Isomap: eigenvalues < 0, returning less dimensions!")
e_values <- e_values[seq_len(neig)]
e_vectors <- e_vectors[, seq_len(neig), drop = FALSE]
}
e_vectors <- e_vectors * rep(sqrt(e_values), each = nrow(e_vectors))
colnames(e_vectors) <- paste("iso", seq_len(neig))
appl <- function(x) {
message(Sys.time(), ": L-Isomap embed START")
appl.meta <- if (inherits(x, "dimRedData"))
x@meta
else data.frame()
indata <- if (inherits(x, "dimRedData"))
x@data
else x
if (ncol(indata) != ncol(data@data))
stop("x must have the same number of dimensions as the original data")
nindata <- nrow(indata)
norg <- nrow(orgdata)
message(Sys.time(), ": constructing knn graph")
lknng <- makeKNNgraph(rbind(indata, orgdata), k = pars$knn, eps = pars$eps)
message(Sys.time(), ": calculating geodesic distances")
lgeodist <- igraph::distances(lknng, seq_len(nindata), nindata + seq_len(norg))
message(Sys.time(), ": embedding")
dammu <- sweep(lgeodist^2, 2, colMeans(geodist^2), "-")
Lsharp <- sweep(e_vectors, 2, e_values, "/")
out <- -0.5 * (dammu %*% Lsharp)
message(Sys.time(), ": DONE")
return(new("dimRedData", data = out, meta = appl.meta))
}
return(new("dimRedResult", data = new("dimRedData", data = e_vectors, meta = meta),
org.data = orgdata, has.org.data = keep.org.data, apply = appl, has.apply = TRUE,
method = "Isomap", pars = pars, other.data = if (pars$get_geod) list(geod = as.dist(geodist)) else list()))
})(data = <S4 object of class structure("dimRedData", package = "dimRed")>, keep.org.data = TRUE,
pars = structure(list(knn = 3, ndim = 3, get_geod = FALSE), .Names = c("knn",
"ndim", "get_geod")))
19: chckpkg("RSpectra")
20: stop(paste0("require '", pkg, "' package, install it using install.packages('", pkg,
"')"))
== testthat results ===========================================================
OK: 1017 SKIPPED: 3 FAILED: 1
1. Error: printing (@test_isomap.R#47)
Error: testthat unit tests failed
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64