Stefano Mangiola
| Snapshot Date: 2024-05-15 14:05:05 -0400 (Wed, 15 May 2024) |
| git_url: https://git.bioconductor.org/packages/sccomp |
| git_branch: devel |
| git_last_commit: 13c5322 |
| git_last_commit_date: 2024-04-30 11:39:15 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2024-05-17 11:38:46 -0400 (Fri, 17 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup" | 4663 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup" | 4398 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4425 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 1823/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| sccomp 1.9.0 (landing page) Stefano Mangiola
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | TIMEOUT | OK | |||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | see weekly results here | ||||||||||||
|
To the developers/maintainers of the sccomp package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/sccomp.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: sccomp |
| Version: 1.9.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:sccomp.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings sccomp_1.9.0.tar.gz |
| StartedAt: 2024-05-16 11:40:48 -0400 (Thu, 16 May 2024) |
| EndedAt: 2024-05-16 12:20:48 -0400 (Thu, 16 May 2024) |
| EllapsedTime: 2400.4 seconds |
| RetCode: None |
| Status: TIMEOUT |
| CheckDir: sccomp.Rcheck |
| Warnings: NA |
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### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:sccomp.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings sccomp_1.9.0.tar.gz
###
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* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/sccomp.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘sccomp/DESCRIPTION’ ... OK
* this is package ‘sccomp’ version ‘1.9.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘sccomp’ can be installed ... OK
* used C++ compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.sdk’
* checking C++ specification ... OK
Not all R platforms support C++17
* checking installed package size ... NOTE
installed size is 7.8Mb
sub-directories of 1Mb or more:
data 1.1Mb
figures 1.2Mb
libs 4.9Mb
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
alpha_to_CI: no visible binding for global variable ‘M’
alpha_to_CI: no visible binding for global variable ‘C_name’
alpha_to_CI: no visible binding for global variable ‘.lower’
alpha_to_CI: no visible binding for global variable ‘.median’
alpha_to_CI: no visible binding for global variable ‘.upper’
as_matrix: no visible binding for global variable ‘variable’
beta_to_CI: no visible binding for global variable ‘M’
beta_to_CI: no visible binding for global variable ‘C_name’
beta_to_CI: no visible binding for global variable ‘.lower’
beta_to_CI: no visible binding for global variable ‘.median’
beta_to_CI: no visible binding for global variable ‘.upper’
check_if_within_posterior: no visible binding for global variable
‘.lower’
check_if_within_posterior: no visible binding for global variable
‘.upper’
check_if_within_posterior: no visible binding for global variable ‘ppc’
check_random_intercept_design: no visible binding for global variable
‘factors’
check_random_intercept_design: no visible binding for global variable
‘groupings’
contrasts_to_enquos: no visible binding for global variable ‘.’
data_simulation_to_model_input: no visible binding for global variable
‘.’
data_simulation_to_model_input : <anonymous>: no visible global
function definition for ‘sd’
data_spread_to_model_input: no visible global function definition for
‘as.formula’
data_spread_to_model_input: no visible binding for global variable
‘exposure’
data_spread_to_model_input: no visible binding for global variable
‘design’
data_spread_to_model_input: no visible binding for global variable
‘mat’
data_spread_to_model_input: no visible binding for global variable
‘factor___numeric’
data_spread_to_model_input: no visible binding for global variable
‘mean_idx’
data_spread_to_model_input: no visible binding for global variable
‘design_matrix’
data_spread_to_model_input: no visible binding for global variable
‘minus_sum’
data_spread_to_model_input: no visible binding for global variable
‘group___numeric’
data_spread_to_model_input: no visible binding for global variable
‘idx’
data_spread_to_model_input: no visible binding for global variable
‘group___label’
data_spread_to_model_input: no visible binding for global variable
‘parameter’
data_spread_to_model_input: no visible binding for global variable
‘group’
data_spread_to_model_input: no visible binding for global variable
‘design_matrix_col’
data_to_spread: no visible binding for global variable ‘exposure’
design_matrix_and_coefficients_to_dir_mult_simulation: no visible
binding for global variable ‘cell_type’
design_matrix_and_coefficients_to_dir_mult_simulation: no visible
binding for global variable ‘generated_counts’
design_matrix_and_coefficients_to_dir_mult_simulation: no visible
binding for global variable ‘factor_1’
design_matrix_and_coefficients_to_simulation: no visible binding for
global variable ‘cell_type’
design_matrix_and_coefficients_to_simulation: no visible binding for
global variable ‘beta_1’
design_matrix_and_coefficients_to_simulation: no visible binding for
global variable ‘beta_2’
dirichlet_multinomial_glm: no visible global function definition for
‘detect_cores’
dirichlet_multinomial_glm: no visible binding for global variable
‘glm_dirichlet_multinomial’
dirichlet_multinomial_glm: no visible binding for global variable
‘censoring_iteration’
dirichlet_multinomial_glm: no visible binding for global variable ‘.’
dirichlet_multinomial_glm: no visible binding for global variable
‘chains’
dirichlet_multinomial_glm: no visible binding for global variable
‘precision’
dirichlet_multinomial_glm: no visible binding for global variable ‘M’
do_inference_imputation: no visible binding for global variable
‘glm_dirichlet_multinomial_imputation’
draws_to_statistics: no visible binding for global variable ‘M’
draws_to_statistics: no visible binding for global variable ‘parameter’
draws_to_statistics: no visible binding for global variable
‘bigger_zero’
draws_to_statistics: no visible binding for global variable
‘smaller_zero’
draws_to_statistics: no visible binding for global variable ‘lower’
draws_to_statistics: no visible binding for global variable ‘effect’
draws_to_statistics: no visible binding for global variable ‘upper’
draws_to_statistics: no visible binding for global variable ‘pH0’
draws_to_statistics: no visible binding for global variable ‘FDR’
draws_to_statistics: no visible binding for global variable ‘n_eff’
draws_to_statistics: no visible binding for global variable ‘R_k_hat’
draws_to_tibble_x: no visible binding for global variable ‘.’
draws_to_tibble_x: no visible binding for global variable ‘dummy’
draws_to_tibble_x: no visible binding for global variable ‘.variable’
draws_to_tibble_x: no visible binding for global variable ‘.chain’
draws_to_tibble_x: no visible binding for global variable ‘.iteration’
draws_to_tibble_x: no visible binding for global variable ‘.draw’
draws_to_tibble_x: no visible binding for global variable ‘.value’
draws_to_tibble_x_y: no visible binding for global variable ‘.’
draws_to_tibble_x_y: no visible binding for global variable ‘dummy’
draws_to_tibble_x_y: no visible binding for global variable ‘.variable’
draws_to_tibble_x_y: no visible binding for global variable ‘.chain’
draws_to_tibble_x_y: no visible binding for global variable
‘.iteration’
draws_to_tibble_x_y: no visible binding for global variable ‘.draw’
draws_to_tibble_x_y: no visible binding for global variable ‘.value’
find_optimal_number_of_chains: no visible binding for global variable
‘chains’
find_optimal_number_of_chains: no visible binding for global variable
‘.’
fit_and_generate_quantities: no visible binding for global variable ‘N’
fit_and_generate_quantities: no visible binding for global variable ‘M’
fit_and_generate_quantities: no visible binding for global variable
‘precision’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘N’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘M’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘cores’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘additional_parameters_to_save’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘pass_fit’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘tol_rel_obj’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘glm_dirichlet_multinomial_generate_quantities’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.draw’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.chain’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.iteration’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.draw_imputation’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.variable’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘fit_list’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘n_eff’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘se_mean’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘sd’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘C_name’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.lower’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.median’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘.upper’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘5%’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘95%’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘50%’
fit_model_and_parse_out_missing_data: no visible binding for global
variable ‘precision’
fit_model_and_parse_out_no_missing_data: no visible binding for global
variable ‘glm_dirichlet_multinomial_generate_quantities’
fit_to_counts_rng: no visible binding for global variable ‘.variable’
fit_to_counts_rng: no visible binding for global variable ‘S’
fit_to_counts_rng: no visible binding for global variable ‘G’
fit_to_counts_rng: no visible binding for global variable ‘.’
formula_to_random_effect_formulae: no visible binding for global
variable ‘formula’
generate_quantities: no visible binding for global variable ‘N_M’
generate_quantities: no visible binding for global variable
‘generated_quantity’
generate_quantities: no visible binding for global variable ‘draw’
generate_quantities: no visible binding for global variable ‘N’
generate_quantities: no visible binding for global variable ‘M’
get_FDR: no visible binding for global variable ‘value’
get_FDR: no visible binding for global variable ‘name’
get_FDR: no visible binding for global variable ‘FDR’
get_abundance_contrast_draws: no visible binding for global variable
‘X’
get_abundance_contrast_draws: no visible binding for global variable
‘.value’
get_abundance_contrast_draws: no visible binding for global variable
‘.’
get_abundance_contrast_draws: no visible binding for global variable
‘N_random_intercepts’
get_abundance_contrast_draws: no visible binding for global variable
‘X_random_intercept’
get_abundance_contrast_draws: no visible binding for global variable
‘.variable’
get_abundance_contrast_draws: no visible binding for global variable
‘y’
get_abundance_contrast_draws: no visible binding for global variable
‘M’
get_abundance_contrast_draws: no visible binding for global variable
‘khat’
get_abundance_contrast_draws: no visible binding for global variable
‘parameter’
get_abundance_contrast_draws: no visible binding for global variable
‘n_eff’
get_abundance_contrast_draws: no visible binding for global variable
‘R_k_hat’
get_mean_precision: no visible binding for global variable ‘M’
get_mean_precision: no visible binding for global variable ‘2.5%’
get_mean_precision: no visible binding for global variable ‘97.5%’
get_mean_precision_association: no visible binding for global variable
‘.’
get_probability_non_zero: no visible binding for global variable ‘M’
get_probability_non_zero: no visible binding for global variable
‘C_name’
get_probability_non_zero: no visible binding for global variable
‘bigger_zero’
get_probability_non_zero: no visible binding for global variable
‘smaller_zero’
get_probability_non_zero_OLD: no visible binding for global variable
‘.’
get_probability_non_zero_OLD: no visible binding for global variable
‘.draw’
get_probability_non_zero_OLD: no visible binding for global variable
‘M’
get_probability_non_zero_OLD: no visible binding for global variable
‘C_name’
get_probability_non_zero_OLD: no visible binding for global variable
‘bigger_zero’
get_probability_non_zero_OLD: no visible binding for global variable
‘smaller_zero’
get_random_intercept_design: no visible binding for global variable
‘is_factor_continuous’
get_random_intercept_design: no visible binding for global variable
‘design’
get_random_intercept_design: no visible binding for global variable
‘max_mean_idx’
get_random_intercept_design: no visible binding for global variable
‘max_minus_sum’
get_random_intercept_design: no visible binding for global variable
‘max_factor_numeric’
get_random_intercept_design: no visible binding for global variable
‘max_group_numeric’
get_random_intercept_design: no visible binding for global variable
‘min_mean_idx’
get_random_intercept_design: no visible binding for global variable
‘min_minus_sum’
get_random_intercept_design2: no visible binding for global variable
‘formula’
get_variability_contrast_draws: no visible binding for global variable
‘XA’
get_variability_contrast_draws: no visible binding for global variable
‘.value’
get_variability_contrast_draws: no visible binding for global variable
‘.’
get_variability_contrast_draws: no visible binding for global variable
‘.variable’
get_variability_contrast_draws: no visible binding for global variable
‘y’
get_variability_contrast_draws: no visible binding for global variable
‘M’
get_variability_contrast_draws: no visible binding for global variable
‘khat’
get_variability_contrast_draws: no visible binding for global variable
‘parameter’
get_variability_contrast_draws: no visible binding for global variable
‘n_eff’
get_variability_contrast_draws: no visible binding for global variable
‘R_k_hat’
glm_multi_beta: no visible binding for global variable ‘.’
label_deleterious_outliers: no visible binding for global variable
‘.count’
label_deleterious_outliers: no visible binding for global variable
‘95%’
label_deleterious_outliers: no visible binding for global variable ‘5%’
label_deleterious_outliers: no visible binding for global variable ‘X’
label_deleterious_outliers: no visible binding for global variable
‘iteration’
label_deleterious_outliers: no visible binding for global variable
‘outlier_above’
label_deleterious_outliers: no visible binding for global variable
‘slope’
label_deleterious_outliers: no visible binding for global variable
‘is_group_right’
label_deleterious_outliers: no visible binding for global variable
‘outlier_below’
multi_beta_glm: no visible global function definition for
‘detect_cores’
parse_fit: no visible binding for global variable ‘M’
parse_formula: no visible binding for global variable ‘.’
parse_formula_random_intercept: no visible binding for global variable
‘formula’
parse_generated_quantities: no visible binding for global variable
‘.draw’
parse_generated_quantities: no visible binding for global variable ‘N’
parse_generated_quantities: no visible binding for global variable
‘.value’
parse_generated_quantities: no visible binding for global variable
‘generated_counts’
parse_generated_quantities: no visible binding for global variable ‘M’
parse_generated_quantities: no visible binding for global variable
‘generated_proportions’
plot.sccomp_tbl: no visible binding for global variable ‘parameter’
plot.sccomp_tbl: no visible binding for global variable ‘count_data’
plot.sccomp_tbl: no visible binding for global variable
‘multipanel_theme’
plot.sccomp_tbl: no visible binding for global variable ‘v_effect’
plot_1d_intervals: no visible binding for global variable ‘parameter’
plot_1d_intervals: no visible binding for global variable ‘estimate’
plot_1d_intervals: no visible binding for global variable ‘value’
plot_2d_intervals: no visible binding for global variable ‘v_effect’
plot_2d_intervals: no visible binding for global variable ‘parameter’
plot_2d_intervals: no visible binding for global variable ‘.’
plot_2d_intervals: no visible binding for global variable ‘c_effect’
plot_2d_intervals: no visible binding for global variable ‘c_lower’
plot_2d_intervals: no visible binding for global variable ‘c_upper’
plot_2d_intervals: no visible binding for global variable ‘c_FDR’
plot_2d_intervals: no visible binding for global variable ‘v_lower’
plot_2d_intervals: no visible binding for global variable ‘v_upper’
plot_2d_intervals: no visible binding for global variable ‘v_FDR’
plot_2d_intervals: no visible binding for global variable
‘cell_type_label’
plot_boxplot: no visible binding for global variable ‘stats_name’
plot_boxplot: no visible binding for global variable ‘parameter’
plot_boxplot: no visible binding for global variable ‘stats_value’
plot_boxplot: no visible binding for global variable ‘count_data’
plot_boxplot: no visible binding for global variable
‘generated_proportions’
plot_boxplot: no visible binding for global variable ‘proportion’
plot_boxplot: no visible binding for global variable ‘name’
plot_boxplot: no visible binding for global variable ‘outlier’
plot_scatterplot: no visible binding for global variable ‘stats_name’
plot_scatterplot: no visible binding for global variable ‘parameter’
plot_scatterplot: no visible binding for global variable ‘stats_value’
plot_scatterplot: no visible binding for global variable ‘count_data’
plot_scatterplot: no visible binding for global variable
‘generated_proportions’
plot_scatterplot: no visible binding for global variable ‘proportion’
plot_scatterplot: no visible binding for global variable ‘name’
plot_scatterplot: no visible binding for global variable ‘outlier’
replicate_data: no visible binding for global variable
‘glm_dirichlet_multinomial_generate_quantities’
replicate_data: no visible binding for global variable ‘count_data’
replicate_data: no visible binding for global variable ‘exposure’
replicate_data: no visible binding for global variable ‘dummy’
replicate_data: no visible global function definition for ‘tail’
replicate_data: no visible global function definition for ‘as.formula’
replicate_data: no visible binding for global variable ‘.’
replicate_data: no visible global function definition for ‘na.omit’
replicate_data: no visible binding for global variable ‘Xa’
replicate_data: no visible binding for global variable
‘intercept_in_design’
replicate_data: no visible binding for global variable ‘design’
replicate_data: no visible binding for global variable ‘design_matrix’
replicate_data: no visible binding for global variable
‘X_random_intercept’
sccomp_boxplot: no visible binding for global variable ‘parameter’
sccomp_boxplot: no visible binding for global variable ‘count_data’
sccomp_boxplot: no visible binding for global variable
‘multipanel_theme’
sccomp_glm_data_frame_counts: no visible binding for global variable
‘N’
sccomp_glm_data_frame_counts: no visible binding for global variable
‘M’
sccomp_glm_data_frame_counts: no visible global function definition for
‘na.omit’
sccomp_predict.sccomp_tbl: no visible binding for global variable
‘count_data’
sccomp_predict.sccomp_tbl: no visible binding for global variable ‘M’
sccomp_predict.sccomp_tbl: no visible binding for global variable ‘N’
sccomp_predict.sccomp_tbl: no visible binding for global variable
‘2.5%’
sccomp_predict.sccomp_tbl: no visible binding for global variable
‘97.5%’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘count_data’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘N’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘M’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘5%’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘95%’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘truncation_up’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘truncation_down’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘.lower’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘.’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘50%’
sccomp_remove_outliers.sccomp_tbl: no visible binding for global
variable ‘.upper’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘proportion_mean’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘y’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘observed_proportion’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘logit_residuals’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘exposure’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘adjusted_proportion’
sccomp_remove_unwanted_variation.sccomp_tbl: no visible binding for
global variable ‘adjusted_counts’
sccomp_replicate.sccomp_tbl: no visible binding for global variable ‘N’
sccomp_replicate.sccomp_tbl: no visible binding for global variable ‘M’
sccomp_test.sccomp_tbl: no visible binding for global variable
‘design_matrix_col’
sccomp_test.sccomp_tbl: no visible binding for global variable
‘parameter’
sccomp_test.sccomp_tbl: no visible binding for global variable ‘M’
simulate_data.tbl: no visible binding for global variable
‘glm_dirichlet_multinomial_generate_quantities’
simulate_data.tbl: no visible binding for global variable ‘data___’
simulate_data.tbl: no visible binding for global variable ‘.exposure’
simulate_data.tbl: no visible binding for global variable ‘N’
simulate_data.tbl: no visible binding for global variable ‘M’
simulate_multinomial_logit_linear: no visible global function
definition for ‘rnorm’
summary_to_tibble: no visible binding for global variable ‘.’
summary_to_tibble: no visible binding for global variable ‘.variable’
Undefined global functions or variables:
. .chain .count .draw .draw_imputation .exposure .iteration .lower
.median .upper .value .variable 2.5% 5% 50% 95% 97.5% C_name FDR G M
N N_M N_random_intercepts R_k_hat S X XA X_random_intercept Xa
additional_parameters_to_save adjusted_counts adjusted_proportion
as.formula beta_1 beta_2 bigger_zero c_FDR c_effect c_lower c_upper
cell_type cell_type_label censoring_iteration chains cores count_data
data___ design design_matrix design_matrix_col detect_cores draw
dummy effect estimate exposure factor_1 factor___numeric factors
fit_list formula generated_counts generated_proportions
generated_quantity glm_dirichlet_multinomial
glm_dirichlet_multinomial_generate_quantities
glm_dirichlet_multinomial_imputation group group___label
group___numeric groupings idx intercept_in_design
is_factor_continuous is_group_right iteration khat logit_residuals
lower mat max_factor_numeric max_group_numeric max_mean_idx
max_minus_sum mean_idx min_mean_idx min_minus_sum minus_sum
multipanel_theme n_eff na.omit name observed_proportion outlier
outlier_above outlier_below pH0 parameter pass_fit ppc precision
proportion proportion_mean rnorm sd se_mean slope smaller_zero
stats_name stats_value tail tol_rel_obj truncation_down truncation_up
upper v_FDR v_effect v_lower v_upper value variable y
Consider adding
importFrom("stats", "as.formula", "formula", "na.omit", "rnorm", "sd")
importFrom("utils", "tail")
to your NAMESPACE file.
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in shell scripts ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... NOTE
GNU make is a SystemRequirements.
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
test_contrasts 50.234 1.864 75.662
sccomp_glm 50.408 1.664 87.847
sccomp_remove_outliers 35.730 1.526 60.783
sccomp_remove_unwanted_variation 18.896 0.986 32.395
sccomp_predict 13.946 0.711 25.118
simulate_data 10.733 0.614 22.826
plot.sccomp_tbl 10.207 0.585 20.963
sccomp_boxplot 9.618 0.619 20.330
sccomp_test 9.348 0.546 16.629
plot_summary 9.110 0.385 17.636
sccomp_estimate 8.938 0.473 19.055
sccomp_replicate 8.815 0.530 14.443
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘testthat.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ...
sccomp.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL sccomp
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘sccomp’ ...
** using staged installation
** libs
using C++ compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using C++17
using SDK: ‘MacOSX11.3.sdk’
clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I"../inst/include" -I"/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include' -I/opt/R/x86_64/include -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -fPIC -falign-functions=64 -Wall -g -O2 -c RcppExports.cpp -o RcppExports.o
clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I"../inst/include" -I"/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include' -I/opt/R/x86_64/include -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -fPIC -falign-functions=64 -Wall -g -O2 -c stanExports_glm_multi_beta_binomial.cc -o stanExports_glm_multi_beta_binomial.o
In file included from stanExports_glm_multi_beta_binomial.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:47:31: warning: 'rstan::io::r_cout_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:70:31: warning: 'rstan::io::r_cerr_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:35:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/binomial_coefficient_log.hpp:13:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/partials_propagator.hpp:8:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:57:1: warning: 'ops_partials_edge' defined as a struct template here but previously declared as a class template; this is valid, but may result in linker errors under the Microsoft C++ ABI [-Wmismatched-tags]
struct ops_partials_edge<ViewElt, Op, require_st_arithmetic<Op>> {
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:45:1: note: did you mean struct here?
class ops_partials_edge;
^~~~~
struct
In file included from stanExports_glm_multi_beta_binomial.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:1252:9: warning: variable 'ret' set but not used [-Wunused-but-set-variable]
int ret = stan::services::error_codes::CONFIG;
^
In file included from stanExports_glm_multi_beta_binomial.cc:5:
./stanExports_glm_multi_beta_binomial.h:653:9: warning: variable 'rows_X' set but not used [-Wunused-but-set-variable]
int rows_X = std::numeric_limits<int>::min();
^
./stanExports_glm_multi_beta_binomial.h:2724:11: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
int pos__ = std::numeric_limits<int>::min();
^
In file included from stanExports_glm_multi_beta_binomial.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:46:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/binomial.hpp:15:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/beta.hpp:1721:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable 'x_extrema' [-Wunused-variable]
const T x_extrema = 1 / (1 + a);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: note: in instantiation of member function 'boost::math::detail::temme_root_finder<double>::temme_root_finder' requested here
temme_root_finder<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 2);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:20: note: in instantiation of function template specialization 'boost::math::detail::temme_method_2_ibeta_inverse<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:17: note: in instantiation of function template specialization 'boost::math::detail::ibeta_inv_imp<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
rx = detail::ibeta_inv_imp(
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:11: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return ibeta_inv(a, b, p, static_cast<result_type*>(nullptr), pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:23: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return boost::math::ibeta_inv(a, b, p, boost_policy_t<>());
^
7 warnings generated.
clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I"../inst/include" -I"/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include' -I/opt/R/x86_64/include -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -fPIC -falign-functions=64 -Wall -g -O2 -c stanExports_glm_multi_beta_binomial_generate_date.cc -o stanExports_glm_multi_beta_binomial_generate_date.o
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_generate_date.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:47:31: warning: 'rstan::io::r_cout_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_generate_date.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:70:31: warning: 'rstan::io::r_cerr_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_generate_date.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:35:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/binomial_coefficient_log.hpp:13:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/partials_propagator.hpp:8:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:57:1: warning: 'ops_partials_edge' defined as a struct template here but previously declared as a class template; this is valid, but may result in linker errors under the Microsoft C++ ABI [-Wmismatched-tags]
struct ops_partials_edge<ViewElt, Op, require_st_arithmetic<Op>> {
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:45:1: note: did you mean struct here?
class ops_partials_edge;
^~~~~
struct
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_generate_date.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:1252:9: warning: variable 'ret' set but not used [-Wunused-but-set-variable]
int ret = stan::services::error_codes::CONFIG;
^
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
./stanExports_glm_multi_beta_binomial_generate_date.h:567:20: warning: unused variable 'jacobian__' [-Wunused-variable]
constexpr bool jacobian__ = false;
^
./stanExports_glm_multi_beta_binomial_generate_date.h:780:11: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
int pos__ = std::numeric_limits<int>::min();
^
In file included from stanExports_glm_multi_beta_binomial_generate_date.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_generate_date.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:46:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/binomial.hpp:15:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/beta.hpp:1721:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable 'x_extrema' [-Wunused-variable]
const T x_extrema = 1 / (1 + a);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: note: in instantiation of member function 'boost::math::detail::temme_root_finder<double>::temme_root_finder' requested here
temme_root_finder<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 2);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:20: note: in instantiation of function template specialization 'boost::math::detail::temme_method_2_ibeta_inverse<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:17: note: in instantiation of function template specialization 'boost::math::detail::ibeta_inv_imp<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
rx = detail::ibeta_inv_imp(
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:11: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return ibeta_inv(a, b, p, static_cast<result_type*>(nullptr), pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:23: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return boost::math::ibeta_inv(a, b, p, boost_policy_t<>());
^
7 warnings generated.
clang++ -arch x86_64 -std=gnu++17 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I"../inst/include" -I"/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include' -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include' -I/opt/R/x86_64/include -I'/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -fPIC -falign-functions=64 -Wall -g -O2 -c stanExports_glm_multi_beta_binomial_simulate_data.cc -o stanExports_glm_multi_beta_binomial_simulate_data.o
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_simulate_data.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:47:31: warning: 'rstan::io::r_cout_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_simulate_data.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:21:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/io/r_ostream.hpp:70:31: warning: 'rstan::io::r_cerr_streambuf::xsputn' hides overloaded virtual function [-Woverloaded-virtual]
virtual std::streamsize xsputn(const char_type* s, int n) {
^
/Library/Developer/CommandLineTools/SDKs/MacOSX11.sdk/usr/include/c++/v1/streambuf:291:24: note: hidden overloaded virtual function 'std::basic_streambuf<char>::xsputn' declared here: type mismatch at 2nd parameter ('std::streamsize' (aka 'long') vs 'int')
virtual streamsize xsputn(const char_type* __s, streamsize __n);
^
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_simulate_data.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:35:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/binomial_coefficient_log.hpp:13:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/partials_propagator.hpp:8:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:57:1: warning: 'ops_partials_edge' defined as a struct template here but previously declared as a class template; this is valid, but may result in linker errors under the Microsoft C++ ABI [-Wmismatched-tags]
struct ops_partials_edge<ViewElt, Op, require_st_arithmetic<Op>> {
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/functor/operands_and_partials.hpp:45:1: note: did you mean struct here?
class ops_partials_edge;
^~~~~
struct
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_simulate_data.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:1252:9: warning: variable 'ret' set but not used [-Wunused-but-set-variable]
int ret = stan::services::error_codes::CONFIG;
^
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
./stanExports_glm_multi_beta_binomial_simulate_data.h:534:11: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
int pos__ = std::numeric_limits<int>::min();
^
./stanExports_glm_multi_beta_binomial_simulate_data.h:568:11: warning: variable 'pos__' set but not used [-Wunused-but-set-variable]
int pos__ = std::numeric_limits<int>::min();
^
In file included from stanExports_glm_multi_beta_binomial_simulate_data.cc:5:
In file included from ./stanExports_glm_multi_beta_binomial_simulate_data.h:23:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/rstaninc.hpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/rstan/include/rstan/stan_fit.hpp:43:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/src/stan/io/dump.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim.hpp:14:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun.hpp:46:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/binomial.hpp:15:
In file included from /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/beta.hpp:1721:
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable 'x_extrema' [-Wunused-variable]
const T x_extrema = 1 / (1 + a);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: note: in instantiation of member function 'boost::math::detail::temme_root_finder<double>::temme_root_finder' requested here
temme_root_finder<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 2);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:20: note: in instantiation of function template specialization 'boost::math::detail::temme_method_2_ibeta_inverse<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:17: note: in instantiation of function template specialization 'boost::math::detail::ibeta_inv_imp<double, boost::math::policies::policy<boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>>>' requested here
rx = detail::ibeta_inv_imp(
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:11: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return ibeta_inv(a, b, p, static_cast<result_type*>(nullptr), pol);
^
/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:23: note: in instantiation of function template specialization 'boost::math::ibeta_inv<double, double, double, boost::math::policies::policy<boost::math::policies::overflow_error<boost::math::policies::errno_on_error>, boost::math::policies::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_double<false>, boost::math::policies::digits2<0>>>' requested here
return boost::math::ibeta_inv(a, b, p, boost_policy_t<>());
^
7 warnings generated.
clang++ -arch x86_64 -std=gnu++17 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o sccomp.so RcppExports.o stanExports_glm_multi_beta_binomial.o stanExports_glm_multi_beta_binomial_generate_date.o stanExports_glm_multi_beta_binomial_simulate_data.o -L/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/lib/ -Wl,-rpath,/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/RcppParallel/lib/ -ltbb -ltbbmalloc -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library/00LOCK-sccomp/00new/sccomp/libs
** R
** data
*** moving datasets to lazyload DB
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (sccomp)
sccomp.Rcheck/tests/testthat.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(testthat)
> library(sccomp)
>
> test_check("sccomp")
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
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: typecancer, typehealthy
sccomp says: the variability design matrix has columns: typecancer, typehealthy
sccomp says: From version 1.7.7 the model by default is fit with the variational inference method (variational_inference = TRUE; much faster). For a full Bayesian inference (HMC method; the gold standard) use variational_inference = FALSE.
This message is displayed once per session.
sccomp says: outlier identification - step 1/2
sccomp says: outlier-free model fitting - step 2/2
sccomp says: the composition design matrix has columns: typecancer, typehealthy
sccomp says: the variability design matrix has columns: typecancer, typehealthy
sccomp says: calculating residuals
sccomp says: regressing out unwanted factors
Joining with `by = join_by(cell_group, sample)`
Joining with `by = join_by(cell_group, type)`
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), continuous_covariate, typehealthy, continuous_covariate:typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000446 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.46 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Iteration: 250 / 250 [100%] (Adaptation)
Chain 1: Success! Found best value [eta = 0.1].
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -4905.096 1.000 1.000
Chain 1: 200 -4077.463 0.601 1.000
Chain 1: 300 -3745.212 0.431 0.203
Chain 1: 400 -3562.547 0.336 0.203
Chain 1: 500 -3465.209 0.274 0.089
Chain 1: 600 -3399.343 0.232 0.089
Chain 1: 700 -3359.020 0.200 0.051
Chain 1: 800 -3328.728 0.176 0.051
Chain 1: 900 -3311.712 0.157 0.028
Chain 1: 1000 -3284.990 0.142 0.028
Chain 1: 1100 -3271.539 0.043 0.019
Chain 1: 1200 -3264.321 0.023 0.012
Chain 1: 1300 -3256.480 0.014 0.009 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), continuous_covariate, typehealthy, continuous_covariate:typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
SAMPLING FOR MODEL 'glm_multi_beta_binomial' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000468 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.68 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Iteration: 1 / 1300 [ 0%] (Warmup)
Chain 1: Iteration: 301 / 1300 [ 23%] (Sampling)
Chain 1: Iteration: 1300 / 1300 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 10.097 seconds (Warm-up)
Chain 1: 15.372 seconds (Sampling)
Chain 1: 25.469 seconds (Total)
Chain 1:
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: typecancer, typehealthy, continuous_covariate
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000443 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.43 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -3277.756 1.000 1.000
Chain 1: 200 -3196.968 0.513 1.000
Chain 1: 300 -3191.089 0.342 0.025
Chain 1: 400 -3187.829 0.257 0.025
Chain 1: 500 -3191.394 0.206 0.002 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: typecancer, typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
SAMPLING FOR MODEL 'glm_multi_beta_binomial' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000618 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 6.18 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Iteration: 1 / 1300 [ 0%] (Warmup)
Chain 1: Iteration: 301 / 1300 [ 23%] (Sampling)
Chain 1: Iteration: 1300 / 1300 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 12.712 seconds (Warm-up)
Chain 1: 31.785 seconds (Sampling)
Chain 1: 44.497 seconds (Total)
Chain 1:
sccomp says: outlier identification - step 1/2
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.002493 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 24.93 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Iteration: 250 / 250 [100%] (Adaptation)
Chain 1: Success! Found best value [eta = 0.1].
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -4781.171 1.000 1.000
Chain 1: 200 -3971.009 0.602 1.000
Chain 1: 300 -3637.424 0.432 0.204
Chain 1: 400 -3505.688 0.333 0.204
Chain 1: 500 -3389.983 0.273 0.092
Chain 1: 600 -3317.783 0.232 0.092
Chain 1: 700 -3260.582 0.201 0.038
Chain 1: 800 -3226.832 0.177 0.038
Chain 1: 900 -3194.633 0.159 0.034
Chain 1: 1000 -3177.027 0.143 0.034
Chain 1: 1100 -3158.273 0.044 0.022
Chain 1: 1200 -3146.812 0.024 0.018
Chain 1: 1300 -3134.948 0.015 0.010
Chain 1: 1400 -3128.273 0.012 0.010
Chain 1: 1500 -3120.540 0.008 0.006 MEAN ELBO CONVERGED MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: outlier-free model fitting - step 2/2
sccomp says: the composition design matrix has columns: (Intercept), continuous_covariate, typehealthy, continuous_covariate:typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.001015 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 10.15 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Iteration: 250 / 250 [100%] (Adaptation)
Chain 1: Success! Found best value [eta = 0.1].
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -4909.820 1.000 1.000
Chain 1: 200 -4040.130 0.608 1.000
Chain 1: 300 -3717.911 0.434 0.215
Chain 1: 400 -3557.971 0.337 0.215
Chain 1: 500 -3449.401 0.276 0.087
Chain 1: 600 -3374.351 0.233 0.087
Chain 1: 700 -3314.721 0.203 0.045
Chain 1: 800 -3281.373 0.179 0.045
Chain 1: 900 -3253.520 0.160 0.031
Chain 1: 1000 -3230.971 0.144 0.031
Chain 1: 1100 -3208.439 0.045 0.022
Chain 1: 1200 -3201.840 0.024 0.018
Chain 1: 1300 -3189.201 0.016 0.010
Chain 1: 1400 -3177.696 0.011 0.009 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.002405 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 24.05 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -3259.836 1.000 1.000
Chain 1: 200 -3170.846 0.514 1.000
Chain 1: 300 -3163.996 0.343 0.028
Chain 1: 400 -3161.271 0.258 0.028
Chain 1: 500 -3161.564 0.206 0.002 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), continuous_covariate
sccomp says: the variability design matrix has columns: (Intercept)
SAMPLING FOR MODEL 'glm_multi_beta_binomial' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 0.000982 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 9.82 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Iteration: 1 / 1300 [ 0%] (Warmup)
Chain 1: Iteration: 301 / 1300 [ 23%] (Sampling)
Chain 1: Iteration: 1300 / 1300 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 26.847 seconds (Warm-up)
Chain 1: 74.121 seconds (Sampling)
Chain 1: 100.968 seconds (Total)
Chain 1:
Loading required package: ttservice
Attaching package: 'ttservice'
The following objects are masked from 'package:dplyr':
bind_cols, bind_rows
Loading required package: SeuratObject
Loading required package: sp
Attaching package: 'SeuratObject'
The following objects are masked from 'package:base':
intersect, t
========================================
tidyseurat version 0.8.0
If you use TIDYSEURAT in published research, please cite:
Mangiola et al. Interfacing Seurat with the R tidy universe. Bioinformatics 2021.
This message can be suppressed by:
suppressPackageStartupMessages(library(tidyseurat))
To restore the Seurat default display use options("restore_Seurat_show" = TRUE)
========================================
Attaching package: 'tidyseurat'
The following object is masked from 'package:ttservice':
plot_ly
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), typehealthy, batch
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000614 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 6.14 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Iteration: 250 / 250 [100%] (Adaptation)
Chain 1: Success! Found best value [eta = 0.1].
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -4522.444 1.000 1.000
Chain 1: 200 -3799.209 0.595 1.000
Chain 1: 300 -3510.725 0.424 0.190
Chain 1: 400 -3386.013 0.327 0.190
Chain 1: 500 -3321.092 0.266 0.082
Chain 1: 600 -3286.420 0.223 0.082
Chain 1: 700 -3258.831 0.193 0.037
Chain 1: 800 -3239.101 0.169 0.037
Chain 1: 900 -3230.705 0.151 0.020
Chain 1: 1000 -3216.965 0.136 0.020
Chain 1: 1100 -3213.073 0.036 0.011
Chain 1: 1200 -3206.270 0.017 0.008 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: calculating residuals
sccomp says: regressing out unwanted factors
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000442 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.42 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -3247.354 1.000 1.000
Chain 1: 200 -3162.277 0.513 1.000
Chain 1: 300 -3151.517 0.343 0.027
Chain 1: 400 -3150.089 0.258 0.027
Chain 1: 500 -3147.767 0.206 0.003 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), typehealthy
sccomp says: the variability design matrix has columns: (Intercept)
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000453 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.53 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -3218.250 1.000 1.000
Chain 1: 200 -3154.922 0.510 1.000
Chain 1: 300 -3153.512 0.340 0.020
Chain 1: 400 -3148.086 0.256 0.020
Chain 1: 500 -3148.325 0.204 0.002 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
sccomp says: count column is an integer. The sum-constrained beta binomial model will be used
sccomp says: estimation
sccomp says: the composition design matrix has columns: (Intercept), typehealthy
sccomp says: the variability design matrix has columns: (Intercept), typehealthy
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000454 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.54 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: 100 -3248.662 1.000 1.000
Chain 1: 200 -3168.815 0.513 1.000
Chain 1: 300 -3164.832 0.342 0.025
Chain 1: 400 -3159.578 0.257 0.025
Chain 1: 500 -3159.231 0.206 0.002 MEDIAN ELBO CONVERGED
Chain 1:
Chain 1: Drawing a sample of size 1000 from the approximate posterior...
Chain 1: COMPLETED.
Joining with `by = join_by(cell_group, sample)`
Joining with `by = join_by(cell_group, sample, continuous_covariate)`
Joining with `by = join_by(cell_group, sample)`
Joining with `by = join_by(cell_group, type)`
Joining with `by = join_by(cell_group, sample)`
Joining with `by = join_by(cell_group, type)`
[ FAIL 0 | WARN 168 | SKIP 8 | PASS 21 ]
══ Skipped tests (8) ═══════════════════════════════════════════════════════════
• empty test (8): 'test-old_framework.R:36:1', 'test-old_framework.R:43:1',
'test-sccomp_.R:148:1', 'test-sccomp_.R:156:1', 'test-sccomp_.R:288:1',
'test-sccomp_.R:317:1', 'test-sccomp_.R:369:1', 'test-sccomp_.R:398:1'
[ FAIL 0 | WARN 168 | SKIP 8 | PASS 21 ]
>
> proc.time()
user system elapsed
422.197 16.187 721.519
sccomp.Rcheck/sccomp-Ex.timings
| name | user | system | elapsed | |
| plot.sccomp_tbl | 10.207 | 0.585 | 20.963 | |
| plot_summary | 9.110 | 0.385 | 17.636 | |
| sccomp_boxplot | 9.618 | 0.619 | 20.330 | |
| sccomp_estimate | 8.938 | 0.473 | 19.055 | |
| sccomp_glm | 50.408 | 1.664 | 87.847 | |
| sccomp_predict | 13.946 | 0.711 | 25.118 | |
| sccomp_remove_outliers | 35.730 | 1.526 | 60.783 | |
| sccomp_remove_unwanted_variation | 18.896 | 0.986 | 32.395 | |
| sccomp_replicate | 8.815 | 0.530 | 14.443 | |
| sccomp_test | 9.348 | 0.546 | 16.629 | |
| simulate_data | 10.733 | 0.614 | 22.826 | |
| test_contrasts | 50.234 | 1.864 | 75.662 | |