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Reverse Dependency Checks for package lhs 2024-06-23 15:42:47.829123

Old Results

Check results for packages in dir '/home/docker/revdep/old':

Check status summary: ERROR WARNING NOTE OK Source packages 0 0 1 0 Reverse depends 13 1 31 14

Check results summary: lhs ... NOTE

  • checking C++ specification ... NOTE
  • checking installed package size ... NOTE rdepends_acebayes ... NOTE
  • checking C++ specification ... NOTE
  • checking Rd files ... NOTE rdepends_activegp ... NOTE
  • checking dependencies in R code ... NOTE rdepends_BayesianPlatformDesignTimeTrend ... NOTE
  • checking installed package size ... NOTE
  • checking for GNU extensions in Makefiles ... NOTE rdepends_BayesianTools ... NOTE
  • checking Rd files ... NOTE rdepends_binaryGP ... NOTE
  • checking LazyData ... NOTE rdepends_ChemoSpec2D ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE
  • checking examples ... ERROR rdepends_comparer ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_ContourFunctions ... NOTE
  • checking Rd files ... NOTE rdepends_dgpsi ... WARNING
  • checking package dependencies ... NOTE
  • checking running R code from vignettes ... WARNING rdepends_DoE.wrapper ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE rdepends_DSAIDE ... NOTE
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE rdepends_DSAIRM ... NOTE
  • checking package dependencies ... NOTE rdepends_DynamicGP ... OK rdepends_dynparam ... NOTE
  • checking LazyData ... NOTE rdepends_EasyABC ... OK rdepends_ENMTools ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_flacco ... ERROR
  • checking package dependencies ... WARNING
  • checking Rd files ... NOTE
  • checking examples ... ERROR
  • checking package vignettes ... NOTE rdepends_GAparsimony ... NOTE
  • checking package dependencies ... NOTE rdepends_GauPro ... ERROR
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE
  • checking tests ... ERROR rdepends_ggDoE ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR rdepends_GPfit ... OK rdepends_GPM ... NOTE
  • checking C++ specification ... NOTE
  • checking Rd files ... NOTE rdepends_grapherator ... NOTE
  • checking dependencies in R code ... NOTE
  • checking LazyData ... NOTE rdepends_hetGP ... ERROR
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE
  • checking running R code from vignettes ... ERROR rdepends_hmer ... NOTE
  • checking package dependencies ... NOTE rdepends_imabc ... NOTE
  • checking Rd files ... NOTE rdepends_inaparc ... NOTE
  • checking Rd files ... NOTE rdepends_laGP ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_LVGP ... NOTE
  • checking Rd files ... NOTE rdepends_MaOEA ... NOTE
  • checking LazyData ... NOTE rdepends_maximin ... OK rdepends_mixopt ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_mlr3mbo ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE
  • checking tests ... ERROR
  • checking running R code from vignettes ... WARNING rdepends_mlrintermbo ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_mlrMBO ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE
  • checking tests ... ERROR rdepends_nlrx ... ERROR
  • checking package dependencies ... NOTE
  • checking tests ... ERROR rdepends_nls2 ... NOTE
  • checking package dependencies ... NOTE rdepends_optim.functions ... NOTE
  • checking LazyData ... NOTE rdepends_OptimaRegion ... OK rdepends_OSFD ... OK rdepends_OUwie ... OK rdepends_paradox ... ERROR
  • checking package dependencies ... NOTE
  • checking running R code from vignettes ... ERROR rdepends_ParamHelpers ... NOTE
  • checking Rd files ... NOTE rdepends_ParBayesianOptimization ... NOTE
  • checking package dependencies ... NOTE rdepends_profExtrema ... NOTE
  • checking Rd files ... NOTE rdepends_RKHSMetaMod ... NOTE
  • checking installed package size ... NOTE rdepends_RNAmf ... OK rdepends_rrepast ... OK rdepends_sensobol ... OK rdepends_SOAs ... OK rdepends_spsh ... NOTE
  • checking Rd files ... NOTE rdepends_TestFunctions ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking running R code from vignettes ... WARNING rdepends_tools4uplift ... OK rdepends_tramnet ... NOTE
  • checking package dependencies ... NOTE rdepends_tuneRanger ... NOTE
  • checking Rd cross-references ... NOTE rdepends_varycoef ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_vdg ... OK rdepends_VeccTMVN ... OK rdepends_yager ... NOTE
  • checking LazyData ... NOTE

New Results

Check results for packages in dir '/home/docker/revdep/new':

Check status summary: ERROR WARNING NOTE OK Source packages 0 0 1 0 Reverse depends 13 1 31 14

Check results summary: lhs ... NOTE

  • checking installed package size ... NOTE rdepends_acebayes ... NOTE
  • checking C++ specification ... NOTE
  • checking Rd files ... NOTE rdepends_activegp ... NOTE
  • checking dependencies in R code ... NOTE rdepends_BayesianPlatformDesignTimeTrend ... NOTE
  • checking installed package size ... NOTE
  • checking for GNU extensions in Makefiles ... NOTE rdepends_BayesianTools ... NOTE
  • checking Rd files ... NOTE rdepends_binaryGP ... NOTE
  • checking LazyData ... NOTE rdepends_ChemoSpec2D ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE
  • checking examples ... ERROR rdepends_comparer ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_ContourFunctions ... NOTE
  • checking Rd files ... NOTE rdepends_dgpsi ... WARNING
  • checking package dependencies ... NOTE
  • checking running R code from vignettes ... WARNING rdepends_DoE.wrapper ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE rdepends_DSAIDE ... NOTE
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE rdepends_DSAIRM ... NOTE
  • checking package dependencies ... NOTE rdepends_DynamicGP ... OK rdepends_dynparam ... NOTE
  • checking LazyData ... NOTE rdepends_EasyABC ... OK rdepends_ENMTools ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_flacco ... ERROR
  • checking package dependencies ... WARNING
  • checking Rd files ... NOTE
  • checking examples ... ERROR
  • checking package vignettes ... NOTE rdepends_GAparsimony ... NOTE
  • checking package dependencies ... NOTE rdepends_GauPro ... ERROR
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE
  • checking tests ... ERROR rdepends_ggDoE ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR rdepends_GPfit ... OK rdepends_GPM ... NOTE
  • checking C++ specification ... NOTE
  • checking Rd files ... NOTE rdepends_grapherator ... NOTE
  • checking dependencies in R code ... NOTE
  • checking LazyData ... NOTE rdepends_hetGP ... ERROR
  • checking package dependencies ... NOTE
  • checking installed package size ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE
  • checking running R code from vignettes ... ERROR rdepends_hmer ... NOTE
  • checking package dependencies ... NOTE rdepends_imabc ... NOTE
  • checking Rd files ... NOTE rdepends_inaparc ... NOTE
  • checking Rd files ... NOTE rdepends_laGP ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_LVGP ... NOTE
  • checking Rd files ... NOTE rdepends_MaOEA ... NOTE
  • checking LazyData ... NOTE rdepends_maximin ... OK rdepends_mixopt ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_mlr3mbo ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE
  • checking tests ... ERROR
  • checking running R code from vignettes ... WARNING rdepends_mlrintermbo ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking tests ... ERROR rdepends_mlrMBO ... ERROR
  • checking package dependencies ... NOTE
  • checking Rd files ... NOTE
  • checking Rd cross-references ... NOTE
  • checking tests ... ERROR rdepends_nlrx ... ERROR
  • checking package dependencies ... NOTE
  • checking tests ... ERROR rdepends_nls2 ... NOTE
  • checking package dependencies ... NOTE rdepends_optim.functions ... NOTE
  • checking LazyData ... NOTE rdepends_OptimaRegion ... OK rdepends_OSFD ... OK rdepends_OUwie ... OK rdepends_paradox ... ERROR
  • checking package dependencies ... NOTE
  • checking running R code from vignettes ... ERROR rdepends_ParamHelpers ... NOTE
  • checking Rd files ... NOTE rdepends_ParBayesianOptimization ... NOTE
  • checking package dependencies ... NOTE rdepends_profExtrema ... NOTE
  • checking Rd files ... NOTE rdepends_RKHSMetaMod ... NOTE
  • checking installed package size ... NOTE rdepends_RNAmf ... OK rdepends_rrepast ... OK rdepends_sensobol ... OK rdepends_SOAs ... OK rdepends_spsh ... NOTE
  • checking Rd files ... NOTE rdepends_TestFunctions ... ERROR
  • checking package dependencies ... NOTE
  • checking examples ... ERROR
  • checking running R code from vignettes ... WARNING rdepends_tools4uplift ... OK rdepends_tramnet ... NOTE
  • checking package dependencies ... NOTE rdepends_tuneRanger ... NOTE
  • checking Rd cross-references ... NOTE rdepends_varycoef ... NOTE
  • checking package dependencies ... NOTE
  • checking Rd cross-references ... NOTE rdepends_vdg ... OK rdepends_VeccTMVN ... OK rdepends_yager ... NOTE
  • checking LazyData ... NOTE

Differences Checking for Exact Message Matches

flacco

  • Version: 1.8
  • Check: examples
  • Status: ERROR
  • Output: Running examples in ‘flacco-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: FeatureObject

Title: Create a Feature Object

Aliases: FeatureObject createFeatureObject

** Examples

(1a) create a feature object using X and y:

X = createInitialSample(n.obs = 500, dim = 3,

  • control = list(init_sample.lower = -10, init_sample.upper = 10))

y = apply(X, 1, function(x) sum(x^2)) feat.object1 = createFeatureObject(X = X, y = y,

  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1b) create a feature object using X and fun:

feat.object2 = createFeatureObject(X = X,

  • fun = function(x) sum(sin(x) * x^2),
  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1c) create a feature object using a data.frame:

feat.object3 = createFeatureObject(iris[,-5], blocks = 5,

  • objective = "Petal.Length")

(2) have a look at the feature objects:

feat.object1 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object2 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Function to be Optimized: function (x) sum(sin(x) * x^2)
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object3 Feature Object:

  • Number of Observations: 150
  • Number of Variables: 3
  • Lower Boundaries: 4.30e+00, 2.00e+00, 1.00e-01
  • Upper Boundaries: 7.90e+00, 4.40e+00, 2.50e+00
  • Name of Variables: Sepal.Length, Sepal.Width, Petal.Width
  • Optimization Problem: minimize Petal.Length
  • Number of Cells per Dimension: 5, 5, 5
  • Size of Cells per Dimension: 0.72, 0.48, 0.48
  • Number of Cells:
    • total: 125
    • non-empty: 37 (29.60%)
    • empty: 88 (70.40%)
  • Average Number of Observations per Cell:
    • total: 1.20
    • non-empty: 4.05

(3) now, one could calculate features

calculateFeatureSet(feat.object1, "ela_meta") $ela_meta.lin_simple.adj_r2 [1] 0.007611856

$ela_meta.lin_simple.intercept [1] 100.4512

$ela_meta.lin_simple.coef.min [1] 0.1066988

$ela_meta.lin_simple.coef.max [1] 0.8837961

$ela_meta.lin_simple.coef.max_by_min [1] 8.283094

$ela_meta.lin_w_interact.adj_r2 [1] 0.03712366

$ela_meta.quad_simple.adj_r2 [1] 1

$ela_meta.quad_simple.cond [1] 1

$ela_meta.quad_w_interact.adj_r2 [1] 1

$ela_meta.costs_fun_evals [1] 0

$ela_meta.costs_runtime [1] 0.009

calculateFeatureSet(feat.object2, "cm_grad") Error in loadNamespace(x) : there is no package called ‘RANN’ Calls: calculateFeatureSet ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted

  • Flags: --no-manual --no-build-vignettes

GauPro

  • Version: 0.2.12

  • Check: tests

  • Status: ERROR

  • Output: Running ‘testthat.R’ Running the tests in ‘tests/testthat.R’ failed. Last 13 lines of output: Error in loadNamespace(x): there is no package called 'mixopt' Backtrace: ▆

    1. └─base::loadNamespace(x) at test_kernel_model_and_kernels.R:1216:3
    2. └─base::withRestarts(stop(cond), retry_loadNamespace = function() NULL)
    3. └─base (local) withOneRestart(expr, restarts[[1L]])

    4.   └─base (local) doWithOneRestart(return(expr), restart)

    ── Failure ('test_kernel_model_and_kernels.R:1420:3'): Normalize Z ───────────── Expected normEI <- gp$maxEI() to run without any errors. ℹ Actually got a with text: there is no package called 'mixopt'

    [ FAIL 24 | WARN 0 | SKIP 0 | PASS 2252 ] Error: Test failures Execution halted

  • Flags: --no-manual --no-build-vignettes

hetGP

  • Version: 1.1.6
  • Check: running R code from vignettes
  • Status: ERROR
  • Output: Errors in running code in vignettes: when running code in ‘hetGP_vignette.Rnw’ ...

for (i in 1:470) {

  • opt <- crit_optim(mod, crit = "crit_cSUR", h = 5, ncores = ncores)

  • X <- c(X, opt$par)

  • Ynew <- fr(opt$par)

  • .... [TRUNCATED]

Execution halted

... incomplete output. Crash?

‘hetGP_vignette.Rnw’ using ‘UTF-8’... failed to complete the test

  • Flags: --no-manual --no-build-vignettes

mixopt

  • Version: 0.1.2
  • Check: examples
  • Status: ERROR
  • Output: Running examples in ‘mixopt-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: mixopt

Title: Mixed variable optimization using coordinate descent

Aliases: mixopt mixopt_blockcd mixopt_coorddesc mixopt_multistart

** Examples

Simple 1D example

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.003144741 secs

With gradient (isn't faster)

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2},

  •            gr=function(x) {-2*(4.5-x[1])})

$par [1] 4.5

$val [1] 0

$counts function gradient 5 4

$runtime Time difference of 0.002400637 secs

1D discrete ordered

mixopt_blockcd(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.002458811 secs

2D: one continuous, one factor

mixopt_blockcd(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.004085302 secs

Simple 1D example

mixopt_coorddesc(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.0003144741 secs

1D discrete ordered

mixopt_coorddesc(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.0005743504 secs

2D: one continuous, one factor

mixopt_coorddesc(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.0009217262 secs

2D

library(ggplot2) library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

filter, lag

The following objects are masked from ‘package:base’:

intersect, setdiff, setequal, union

f6 <- function(x) {-(-x[1].5sin(.5*x[1])1 - 1e-2x[2]^2 +

  •                    .2*x[1] - .3*x[2])}

ContourFunctions::cf_func(f6, xlim=c(0,100), ylim=c(-100,100)) Error in loadNamespace(x) : there is no package called ‘ContourFunctions’ Calls: loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted

  • Flags: --no-manual --no-build-vignettes

Differences using check_packages_in_dir_changes()

Package: flacco Check: examples Old result: ERROR Running examples in ‘flacco-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: FeatureObject

Title: Create a Feature Object

Aliases: FeatureObject createFeatureObject

** Examples

(1a) create a feature object using X and y:

X = createInitialSample(n.obs = 500, dim = 3,

  • control = list(init_sample.lower = -10, init_sample.upper = 10))

y = apply(X, 1, function(x) sum(x^2)) feat.object1 = createFeatureObject(X = X, y = y,

  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1b) create a feature object using X and fun:

feat.object2 = createFeatureObject(X = X,

  • fun = function(x) sum(sin(x) * x^2),
  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1c) create a feature object using a data.frame:

feat.object3 = createFeatureObject(iris[,-5], blocks = 5,

  • objective = "Petal.Length")

(2) have a look at the feature objects:

feat.object1 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object2 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Function to be Optimized: function (x) sum(sin(x) * x^2)
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object3 Feature Object:

  • Number of Observations: 150
  • Number of Variables: 3
  • Lower Boundaries: 4.30e+00, 2.00e+00, 1.00e-01
  • Upper Boundaries: 7.90e+00, 4.40e+00, 2.50e+00
  • Name of Variables: Sepal.Length, Sepal.Width, Petal.Width
  • Optimization Problem: minimize Petal.Length
  • Number of Cells per Dimension: 5, 5, 5
  • Size of Cells per Dimension: 0.72, 0.48, 0.48
  • Number of Cells:
    • total: 125
    • non-empty: 37 (29.60%)
    • empty: 88 (70.40%)
  • Average Number of Observations per Cell:
    • total: 1.20
    • non-empty: 4.05

(3) now, one could calculate features

calculateFeatureSet(feat.object1, "ela_meta") $ela_meta.lin_simple.adj_r2 [1] 0.007611856

$ela_meta.lin_simple.intercept [1] 100.4512

$ela_meta.lin_simple.coef.min [1] 0.1066988

$ela_meta.lin_simple.coef.max [1] 0.8837961

$ela_meta.lin_simple.coef.max_by_min [1] 8.283094

$ela_meta.lin_w_interact.adj_r2 [1] 0.03712366

$ela_meta.quad_simple.adj_r2 [1] 1

$ela_meta.quad_simple.cond [1] 1

$ela_meta.quad_w_interact.adj_r2 [1] 1

$ela_meta.costs_fun_evals [1] 0

$ela_meta.costs_runtime [1] 0.007

calculateFeatureSet(feat.object2, "cm_grad") Error in loadNamespace(x) : there is no package called ‘RANN’ Calls: calculateFeatureSet ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted New result: ERROR Running examples in ‘flacco-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: FeatureObject

Title: Create a Feature Object

Aliases: FeatureObject createFeatureObject

** Examples

(1a) create a feature object using X and y:

X = createInitialSample(n.obs = 500, dim = 3,

  • control = list(init_sample.lower = -10, init_sample.upper = 10))

y = apply(X, 1, function(x) sum(x^2)) feat.object1 = createFeatureObject(X = X, y = y,

  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1b) create a feature object using X and fun:

feat.object2 = createFeatureObject(X = X,

  • fun = function(x) sum(sin(x) * x^2),
  • lower = -10, upper = 10, blocks = c(5, 10, 4))

(1c) create a feature object using a data.frame:

feat.object3 = createFeatureObject(iris[,-5], blocks = 5,

  • objective = "Petal.Length")

(2) have a look at the feature objects:

feat.object1 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object2 Feature Object:

  • Number of Observations: 500
  • Number of Variables: 3
  • Lower Boundaries: -1.00e+01, -1.00e+01, -1.00e+01
  • Upper Boundaries: 1.00e+01, 1.00e+01, 1.00e+01
  • Name of Variables: x1, x2, x3
  • Optimization Problem: minimize y
  • Function to be Optimized: function (x) sum(sin(x) * x^2)
  • Number of Cells per Dimension: 5, 10, 4
  • Size of Cells per Dimension: 4.00, 2.00, 5.00
  • Number of Cells:
    • total: 200
    • non-empty: 182 (91.00%)
    • empty: 18 (9.00%)
  • Average Number of Observations per Cell:
    • total: 2.50
    • non-empty: 2.75

feat.object3 Feature Object:

  • Number of Observations: 150
  • Number of Variables: 3
  • Lower Boundaries: 4.30e+00, 2.00e+00, 1.00e-01
  • Upper Boundaries: 7.90e+00, 4.40e+00, 2.50e+00
  • Name of Variables: Sepal.Length, Sepal.Width, Petal.Width
  • Optimization Problem: minimize Petal.Length
  • Number of Cells per Dimension: 5, 5, 5
  • Size of Cells per Dimension: 0.72, 0.48, 0.48
  • Number of Cells:
    • total: 125
    • non-empty: 37 (29.60%)
    • empty: 88 (70.40%)
  • Average Number of Observations per Cell:
    • total: 1.20
    • non-empty: 4.05

(3) now, one could calculate features

calculateFeatureSet(feat.object1, "ela_meta") $ela_meta.lin_simple.adj_r2 [1] 0.007611856

$ela_meta.lin_simple.intercept [1] 100.4512

$ela_meta.lin_simple.coef.min [1] 0.1066988

$ela_meta.lin_simple.coef.max [1] 0.8837961

$ela_meta.lin_simple.coef.max_by_min [1] 8.283094

$ela_meta.lin_w_interact.adj_r2 [1] 0.03712366

$ela_meta.quad_simple.adj_r2 [1] 1

$ela_meta.quad_simple.cond [1] 1

$ela_meta.quad_w_interact.adj_r2 [1] 1

$ela_meta.costs_fun_evals [1] 0

$ela_meta.costs_runtime [1] 0.009

calculateFeatureSet(feat.object2, "cm_grad") Error in loadNamespace(x) : there is no package called ‘RANN’ Calls: calculateFeatureSet ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted

Package: GauPro Check: tests Old result: ERROR Running ‘testthat.R’ Running the tests in ‘tests/testthat.R’ failed. Last 13 lines of output: Error in loadNamespace(x): there is no package called 'mixopt' Backtrace: ▆ 1. └─base::loadNamespace(x) at test_kernel_model_and_kernels.R:1216:3 2. └─base::withRestarts(stop(cond), retry_loadNamespace = function() NULL) 3. └─base (local) withOneRestart(expr, restarts[[1L]]) 4. └─base (local) doWithOneRestart(return(expr), restart) ── Failure ('test_kernel_model_and_kernels.R:1420:3'): Normalize Z ───────────── Expected normEI <- gp$maxEI() to run without any errors. ℹ Actually got a with text: there is no package called 'mixopt'

[ FAIL 24 | WARN 0 | SKIP 0 | PASS 2263 ]
Error: Test failures
Execution halted

New result: ERROR Running ‘testthat.R’ Running the tests in ‘tests/testthat.R’ failed. Last 13 lines of output: Error in loadNamespace(x): there is no package called 'mixopt' Backtrace: ▆ 1. └─base::loadNamespace(x) at test_kernel_model_and_kernels.R:1216:3 2. └─base::withRestarts(stop(cond), retry_loadNamespace = function() NULL) 3. └─base (local) withOneRestart(expr, restarts[[1L]]) 4. └─base (local) doWithOneRestart(return(expr), restart) ── Failure ('test_kernel_model_and_kernels.R:1420:3'): Normalize Z ───────────── Expected normEI <- gp$maxEI() to run without any errors. ℹ Actually got a with text: there is no package called 'mixopt'

[ FAIL 24 | WARN 0 | SKIP 0 | PASS 2252 ]
Error: Test failures
Execution halted

Package: hetGP Check: running R code from vignettes Old result: ERROR Errors in running code in vignettes: when running code in ‘hetGP_vignette.Rnw’ ...

for (i in 1:490) {

  • h[i] <- horizon(mod.a)

  • opt <- IMSPE_optim(mod.a, h = h[i])

  • X <- c(X, opt$par)

  • Ynew <- fr(opt$par)

  • Y .... [TRUNCATED]

Execution halted

... incomplete output. Crash?

‘hetGP_vignette.Rnw’ using ‘UTF-8’... failed to complete the test

New result: ERROR Errors in running code in vignettes: when running code in ‘hetGP_vignette.Rnw’ ...

for (i in 1:470) {

  • opt <- crit_optim(mod, crit = "crit_cSUR", h = 5, ncores = ncores)

  • X <- c(X, opt$par)

  • Ynew <- fr(opt$par)

  • .... [TRUNCATED]

Execution halted

... incomplete output. Crash?

‘hetGP_vignette.Rnw’ using ‘UTF-8’... failed to complete the test

Package: mixopt Check: examples Old result: ERROR Running examples in ‘mixopt-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: mixopt

Title: Mixed variable optimization using coordinate descent

Aliases: mixopt mixopt_blockcd mixopt_coorddesc mixopt_multistart

** Examples

Simple 1D example

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.00287199 secs

With gradient (isn't faster)

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2},

  •            gr=function(x) {-2*(4.5-x[1])})

$par [1] 4.5

$val [1] 0

$counts function gradient 5 4

$runtime Time difference of 0.002382994 secs

1D discrete ordered

mixopt_blockcd(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.002665281 secs

2D: one continuous, one factor

mixopt_blockcd(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.004266262 secs

Simple 1D example

mixopt_coorddesc(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.0002658367 secs

1D discrete ordered

mixopt_coorddesc(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.0005483627 secs

2D: one continuous, one factor

mixopt_coorddesc(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.0008187294 secs

2D

library(ggplot2) library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

  filter, lag

The following objects are masked from ‘package:base’:

  intersect, setdiff, setequal, union

f6 <- function(x) {-(-x[1].5sin(.5*x[1])1 - 1e-2x[2]^2 +

  •                    .2*x[1] - .3*x[2])}

ContourFunctions::cf_func(f6, xlim=c(0,100), ylim=c(-100,100)) Error in loadNamespace(x) : there is no package called ‘ContourFunctions’ Calls: loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted New result: ERROR Running examples in ‘mixopt-Ex.R’ failed The error most likely occurred in:

base::assign(".ptime", proc.time(), pos = "CheckExEnv")

Name: mixopt

Title: Mixed variable optimization using coordinate descent

Aliases: mixopt mixopt_blockcd mixopt_coorddesc mixopt_multistart

** Examples

Simple 1D example

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.003144741 secs

With gradient (isn't faster)

mixopt_blockcd(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2},

  •            gr=function(x) {-2*(4.5-x[1])})

$par [1] 4.5

$val [1] 0

$counts function gradient 5 4

$runtime Time difference of 0.002400637 secs

1D discrete ordered

mixopt_blockcd(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.002458811 secs

2D: one continuous, one factor

mixopt_blockcd(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.004085302 secs

Simple 1D example

mixopt_coorddesc(par=list(mopar_cts(2,8)), fn=function(x) {(4.5-x[1])^2}) $par [1] 4.5

$val [1] 0

$counts function gradient 13 0

$runtime Time difference of 0.0003144741 secs

1D discrete ordered

mixopt_coorddesc(par=list(mopar_ordered(100:10000)),

  •              fn=function(x) {(x[1] - 500.3)^2})

$par [1] 500

$val [1] 0.09

$counts function gradient 42 0

$runtime Time difference of 0.0005743504 secs

2D: one continuous, one factor

mixopt_coorddesc(par=list(mopar_cts(2,8), mopar_unordered(letters[1:6])),

  •              fn=function(x) {ifelse(x[2] == 'b', -1, 0) +

  •                              (4.5-x[1])^2})

$par mixopt_list: [1] 4.5 b

$val [1] -1

$counts function gradient 26 0

$runtime Time difference of 0.0009217262 secs

2D

library(ggplot2) library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

  filter, lag

The following objects are masked from ‘package:base’:

  intersect, setdiff, setequal, union

f6 <- function(x) {-(-x[1].5sin(.5*x[1])1 - 1e-2x[2]^2 +

  •                    .2*x[1] - .3*x[2])}

ContourFunctions::cf_func(f6, xlim=c(0,100), ylim=c(-100,100)) Error in loadNamespace(x) : there is no package called ‘ContourFunctions’ Calls: loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart Execution halted