CRAN Package Check Results for Package eyetrackingR

Last updated on 2024-11-03 11:49:22 CET.

Flavor	Version	T_install	T_check	T_total	Status
r-devel-linux-x86_64-debian-clang	0.2.1	8.73	383.67	392.40	OK
r-devel-linux-x86_64-debian-gcc	0.2.1	0.42	1.84	2.26	ERROR
r-devel-linux-x86_64-fedora-clang	0.2.1			628.62	NOTE
r-devel-linux-x86_64-fedora-gcc	0.2.1			599.09	NOTE
r-devel-windows-x86_64	0.2.1	10.00	318.00	328.00	OK
r-patched-linux-x86_64	0.2.1	9.06	357.71	366.77	OK
r-release-linux-x86_64	0.2.1	8.02	107.01	115.03	ERROR
r-release-macos-arm64	0.2.1			165.00	OK
r-release-macos-x86_64	0.2.1			256.00	OK
r-release-windows-x86_64	0.2.1	9.00	321.00	330.00	NOTE
r-oldrel-macos-arm64	0.2.1			171.00	OK
r-oldrel-macos-x86_64	0.2.1			493.00	OK
r-oldrel-windows-x86_64	0.2.1	12.00	441.00	453.00	NOTE

Check Details

Version: 0.2.1
Check: whether package can be installed
Result: ERROR Installation failed. Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.2.1
Check: dependencies in R code
Result: NOTE Namespace in Imports field not imported from: ‘rlang’ All declared Imports should be used. Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.2.1
Check: package dependencies
Result: NOTE Packages suggested but not available for checking: 'lme4', 'glmmTMB' Flavor: r-release-linux-x86_64

Version: 0.2.1
Check: tests
Result: ERROR Running ‘testthat.R’ [21s/30s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(eyetrackingR) 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 > > test_check("eyetrackingR") [ FAIL 2 | WARN 0 | SKIP 0 | PASS 27 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_analyze_time_bins.R:99:1'): (code run outside of `test_that()`) ── Error in `analyze_time_bins.time_sequence_data(df_time_within, predictor_column = "SexM:TargetInanimate", test = "lmer", alpha = 0.05, formula = Prop ~ Sex * Target + (1 | ParticipantName))`: Please install the 'lme4' package to use this method. Backtrace: ▆ 1. ├─eyetrackingR::analyze_time_bins(...) at test_analyze_time_bins.R:99:1 2. └─eyetrackingR:::analyze_time_bins.time_sequence_data(...) ── Error ('test_cluster_analysis.R:88:1'): (code run outside of `test_that()`) ── Error in `analyze_time_bins.time_sequence_data(data = structure(list(ParticipantName = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 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1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Animate", "Inanimate"), class = "factor"), TimeBin = c(155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 155, 156, 157, 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0.0520625508808784, 0.0922640217525345, 0.123853779621514, 0.144813183512336, 0.154003721953353, 0.151163275696463, 0.136859868873768, 0.11240898167157, 0.0797604976021792, 0.0413613584539495, -2.69333186266766e-16, -0.0413613584539502, -0.0797604976021799, -0.11240898167157, -0.136859868873768, -0.151163275696464, -0.154003721953354, -0.144813183512336, -0.123853779621513, -0.0922640217525341, -0.0520625508808775, -0.0061032901225934, 0.0420240603529165, 0.088154259214507, 0.127773563745766, 0.156319646586751, 0.169560462521482, 0.164058138391561, 0.13772395921643, 0.090470523600657, 0.0249671415087258, -0.0524954525122716, -0.131024997581549, -0.194026143124753, -0.217971350824825, -0.171038188803188, -0.0116069449507928, 0.313387513671399)), row.names = c(NA, -6710L), class = c("time_sequence_data", "eyetrackingR_df", "data.frame"), eyetrackingR = list(data_options = list( participant_column = "ParticipantName", trackloss_column = "TrackLoss", time_column = "TimeFromTrialOnset", trial_column = "Trial", item_columns = NULL, aoi_columns = c("Animate", "Inanimate" ), treat_non_aoi_looks_as_missing = TRUE), summarized_by = NULL, time_bin_size = 100)), predictor_column = "Age", test = "lmer", formula = ArcSin ~ Target + Age + (1 | ParticipantName) + (1 | Trial), aoi = "Animate", treatment_level = NULL, quiet = TRUE, threshold = 2)`: Please install the 'lme4' package to use this method. Backtrace: ▆ 1. ├─eyetrackingR::make_time_cluster_data(...) at test_cluster_analysis.R:88:1 2. └─eyetrackingR:::make_time_cluster_data.time_sequence_data(...) 3. ├─base::do.call(analyze_time_bins, the_args) 4. ├─eyetrackingR (local) `<fn>`(...) 5. └─eyetrackingR:::analyze_time_bins.time_sequence_data(...) [ FAIL 2 | WARN 0 | SKIP 0 | PASS 27 ] Error: Test failures Execution halted Flavor: r-release-linux-x86_64

Version: 0.2.1
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘divergence_vignette.Rmd’ using rmarkdown Quitting from lines 26-60 [unnamed-chunk-1] (divergence_vignette.Rmd) Error: processing vignette 'divergence_vignette.Rmd' failed with diagnostics: there is no package called 'lme4' --- failed re-building ‘divergence_vignette.Rmd’ --- re-building ‘growth_curve_analysis_vignette.Rmd’ using rmarkdown Quitting from lines 26-57 [unnamed-chunk-1] (growth_curve_analysis_vignette.Rmd) Error: processing vignette 'growth_curve_analysis_vignette.Rmd' failed with diagnostics: there is no package called 'lme4' --- failed re-building ‘growth_curve_analysis_vignette.Rmd’ --- re-building ‘onset_contingent_analysis_vignette.Rmd’ using rmarkdown Quitting from lines 30-61 [unnamed-chunk-1] (onset_contingent_analysis_vignette.Rmd) Error: processing vignette 'onset_contingent_analysis_vignette.Rmd' failed with diagnostics: there is no package called 'lme4' --- failed re-building ‘onset_contingent_analysis_vignette.Rmd’ --- re-building ‘preparing_your_data_vignette.Rmd’ using rmarkdown Quitting from lines 59-75 [unnamed-chunk-1] (preparing_your_data_vignette.Rmd) Error: processing vignette 'preparing_your_data_vignette.Rmd' failed with diagnostics: there is no package called 'lme4' --- failed re-building ‘preparing_your_data_vignette.Rmd’ --- re-building ‘window_analysis_vignette.Rmd’ using rmarkdown Quitting from lines 26-56 [unnamed-chunk-1] (window_analysis_vignette.Rmd) Error: processing vignette 'window_analysis_vignette.Rmd' failed with diagnostics: there is no package called 'lme4' --- failed re-building ‘window_analysis_vignette.Rmd’ SUMMARY: processing the following files failed: ‘divergence_vignette.Rmd’ ‘growth_curve_analysis_vignette.Rmd’ ‘onset_contingent_analysis_vignette.Rmd’ ‘preparing_your_data_vignette.Rmd’ ‘window_analysis_vignette.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-release-linux-x86_64

Version: 0.2.1
Check: package dependencies
Result: NOTE Package suggested but not available for checking: 'doMC' Flavors: r-release-windows-x86_64, r-oldrel-windows-x86_64