Last updated on 2025-06-28 09:49:27 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.0 | 13.52 | 226.09 | 239.61 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.0.0 | 5.97 | 269.11 | 275.08 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.0.0 | 354.09 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.0.0 | 640.15 | ERROR | |||
| r-devel-windows-x86_64 | 1.0.0 | 15.00 | 202.00 | 217.00 | OK | |
| r-patched-linux-x86_64 | OK | |||||
| r-release-linux-x86_64 | 1.0.0 | 10.32 | 214.20 | 224.52 | OK | |
| r-release-macos-arm64 | 1.0.0 | 102.00 | OK | |||
| r-release-macos-x86_64 | 1.0.0 | 219.00 | OK | |||
| r-release-windows-x86_64 | 1.0.0 | 14.00 | 204.00 | 218.00 | OK | |
| r-oldrel-macos-arm64 | 1.0.0 | 108.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.0.0 | 148.00 | OK | |||
| r-oldrel-windows-x86_64 | 1.0.0 | 19.00 | 295.00 | 314.00 | OK |
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘BanffIT_Run_Script.R’ [221s/290s]
Running the tests in ‘tests/BanffIT_Run_Script.R’ failed.
Complete output:
> # # loading dataset
> # library(banffIT)
> # library(fs)
> # library(dplyr)
> # library(rlang)
> # library(tools)
> # library(readr)
> # library(stringr)
> # library(lubridate)
> # library(tidyr)
> # library(fabR)
> # library(madshapR)
> # library(crayon)
> # library(Rmonize)
> # library(janitor)
> #
> # input_file = "tests/CHUQ_for_test_3.csv"
> # output_folder = 'tests'
> # language = 'label:en'
> # option_filter = quote(adequacy == 1)
> # detail = TRUE
> # include_banff_dictionary = TRUE
>
> library(banffIT)
>
> input_file = system.file("extdata", "banff_example.xlsx", package = "banffIT")
>
> banff_launcher(
+ input_file = input_file,
+ output_folder = 'tests',
+ language = 'label:en',
+ option_filter = adequacy == 1,
+ detail = TRUE)
Welcome to the Banff diagnosis helper.
Press [enter] to continue or [esc] to quit.
[1/6] - Import data
[2/6] - Evaluation of 'banff_example'
[3/6] - Add diagnosis to each observation of'banff_example'
[4/6] - Generate labels for each variable of 'banff_example'
Processing of : patient_id
Processing of : center
Processing of : biopsy_id
Processing of : sc_date_bx
Processing of : date_tx
Processing of : type_bx
Processing of : adequacy
Processing of : fixation_ff
Processing of : fixation_paraffin
Processing of : fixation_elec
Processing of : fixation_rna
Processing of : microscopy
Processing of : c4d_if
Processing of : c4d_ihc
Processing of : dsa
Processing of : hist_dsa
Processing of : i_score
Processing of : t_score
Processing of : v_score
Processing of : g_score
Processing of : ptc_score
Processing of : ti_score
Processing of : cg_score
Processing of : mm_score
Processing of : cv_score
Processing of : ci_score
Processing of : ct_score
Processing of : ah_score
Processing of : glomeruli
Processing of : arteries
Processing of : bk
Processing of : gs
Processing of : i_ifta_score
Processing of : atma
Processing of : ctma
Processing of : atn
Processing of : agn
Processing of : cgn
Processing of : infec
Processing of : cni
Processing of : ain
Processing of : ptld
Processing of : sptcbmml
Processing of : leuscint
Processing of : monofibneoint
Processing of : newaif
Processing of : othi_ifta
Processing of : genetx
Processing of : hist_aamr
Processing of : hist_camr
Processing of : hist_tcmr
Processing of : adequacy_calculated
Processing of : c4d
Processing of : nogn
Processing of : ifta
Processing of : aamr11.1
Processing of : aamr11.2
Processing of : aamr12
Processing of : aamr13
Processing of : aamr14
Processing of : aamr1
Processing of : aamr21
Processing of : aamr22.1
Processing of : aamr22.2
Processing of : aamr22.3
Processing of : aamr2
Processing of : aamr
Processing of : susp_aamr
Processing of : c4dneg_aamr
Processing of : susp_c4dneg_aamr
Processing of : dsaneg_aamr
Processing of : susp_activeaamr
Processing of : hist_dsa1
Processing of : hist_dsa2
Processing of : hist_dsa_calculated
Processing of : hist_tcmr1
Processing of : hist_tcmr2
Processing of : hist_tcmr3
Processing of : hist_tcmr_calculated
Processing of : camr11
Processing of : camr12
Processing of : camr13
Processing of : camr1
Processing of : activeabmr
Processing of : camr
Processing of : susp_camr
Processing of : c4dneg_camr
Processing of : susp_c4dneg_camr
Processing of : dsaneg_camr
Processing of : chractabmr
Processing of : susp_chractabmr
Processing of : hist_camr1
Processing of : hist_camr2
Processing of : hist_camr_calculated
Processing of : hist_aamr1
Processing of : hist_aamr2
Processing of : hist_aamr_calculated
Processing of : chrabmr3
Processing of : chrabmr
Processing of : c4d_only
Processing of : final_abmr
Processing of : final_susp_abmr
Processing of : final_abmr_verified
Processing of : diag_code_1
Processing of : diag_code_2
Processing of : diag_code_2_final_abmr
Processing of : diag_code_2_final_susp_abmr
Processing of : diag_code_3
Processing of : diag_code_4_active
Processing of : diag_code_4_chronic
Processing of : diag_code_5
Processing of : diag_code_bk
Processing of : diag_code_ptld
Processing of : diag_code_cni
Processing of : diag_code_atn
Processing of : diag_code_cgn
Processing of : diag_code_agn
Processing of : diag_code_infec
Processing of : diag_code_ain
[5/6] - Assessment of the the annotated 'banff_example'
- DATA DICTIONARY ASSESSMENT: data_dict --------------
Assess the standard adequacy of naming
Assess the uniqueness and presence of variable names
Assess the presence of possible duplicated columns
Assess the presence of duplicated rows
Assess the presence of empty rows in the data dictionary
Assess the presence of empty column in the data dictionary
Assess the presence of categories not in the data dictionary
Assess the `valueType` column in 'Variables'
Assess the completion of `label` column in 'Variables'
Assess presence and completion of `label` column in 'Categories'
Assess the logical values of missing column in Categories
Generate report
- WARNING MESSAGES (if any): --------------------------------------------
- DATASET ASSESSMENT: banff_example --------------------------
Assess the standard adequacy of naming
Assess the presence of variable names both in dataset and data dictionary
Assess the presence of possible duplicated variable in the dataset
Assess the presence of possible duplicated participants
Assess the presence of unique value columns in dataset
Assess the presence of empty rows in the dataset
Assess the presence all empty variable in the dataset
Assess the Categories comparison in dataset and data dictionary
Assess the `valueType` comparison in dataset and data dictionary
Generate report
- WARNING MESSAGES (if any): -------------------------------------------------
Error: The dataset and/or the data dictionary contain errors.
Useful tip: Use dataset_evaluate(dataset, data_dict) to get a full assessment of
your dataset
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘BanffIT_Run_Script.R’ [253s/255s]
Running the tests in ‘tests/BanffIT_Run_Script.R’ failed.
Complete output:
> # # loading dataset
> # library(banffIT)
> # library(fs)
> # library(dplyr)
> # library(rlang)
> # library(tools)
> # library(readr)
> # library(stringr)
> # library(lubridate)
> # library(tidyr)
> # library(fabR)
> # library(madshapR)
> # library(crayon)
> # library(Rmonize)
> # library(janitor)
> #
> # input_file = "tests/CHUQ_for_test_3.csv"
> # output_folder = 'tests'
> # language = 'label:en'
> # option_filter = quote(adequacy == 1)
> # detail = TRUE
> # include_banff_dictionary = TRUE
>
> library(banffIT)
>
> input_file = system.file("extdata", "banff_example.xlsx", package = "banffIT")
>
> banff_launcher(
+ input_file = input_file,
+ output_folder = 'tests',
+ language = 'label:en',
+ option_filter = adequacy == 1,
+ detail = TRUE)
Welcome to the Banff diagnosis helper.
Press [enter] to continue or [esc] to quit.
[1/6] - Import data
[2/6] - Evaluation of 'banff_example'
[3/6] - Add diagnosis to each observation of'banff_example'
[4/6] - Generate labels for each variable of 'banff_example'
Processing of : patient_id
Processing of : center
Processing of : biopsy_id
Processing of : sc_date_bx
Processing of : date_tx
Processing of : type_bx
Processing of : adequacy
Processing of : fixation_ff
Processing of : fixation_paraffin
Processing of : fixation_elec
Processing of : fixation_rna
Processing of : microscopy
Processing of : c4d_if
Processing of : c4d_ihc
Processing of : dsa
Processing of : hist_dsa
Processing of : i_score
Processing of : t_score
Processing of : v_score
Processing of : g_score
Processing of : ptc_score
Processing of : ti_score
Processing of : cg_score
Processing of : mm_score
Processing of : cv_score
Processing of : ci_score
Processing of : ct_score
Processing of : ah_score
Processing of : glomeruli
Processing of : arteries
Processing of : bk
Processing of : gs
Processing of : i_ifta_score
Processing of : atma
Processing of : ctma
Processing of : atn
Processing of : agn
Processing of : cgn
Processing of : infec
Processing of : cni
Processing of : ain
Processing of : ptld
Processing of : sptcbmml
Processing of : leuscint
Processing of : monofibneoint
Processing of : newaif
Processing of : othi_ifta
Processing of : genetx
Processing of : hist_aamr
Processing of : hist_camr
Processing of : hist_tcmr
Processing of : adequacy_calculated
Processing of : c4d
Processing of : nogn
Processing of : ifta
Processing of : aamr11.1
Processing of : aamr11.2
Processing of : aamr12
Processing of : aamr13
Processing of : aamr14
Processing of : aamr1
Processing of : aamr21
Processing of : aamr22.1
Processing of : aamr22.2
Processing of : aamr22.3
Processing of : aamr2
Processing of : aamr
Processing of : susp_aamr
Processing of : c4dneg_aamr
Processing of : susp_c4dneg_aamr
Processing of : dsaneg_aamr
Processing of : susp_activeaamr
Processing of : hist_dsa1
Processing of : hist_dsa2
Processing of : hist_dsa_calculated
Processing of : hist_tcmr1
Processing of : hist_tcmr2
Processing of : hist_tcmr3
Processing of : hist_tcmr_calculated
Processing of : camr11
Processing of : camr12
Processing of : camr13
Processing of : camr1
Processing of : activeabmr
Processing of : camr
Processing of : susp_camr
Processing of : c4dneg_camr
Processing of : susp_c4dneg_camr
Processing of : dsaneg_camr
Processing of : chractabmr
Processing of : susp_chractabmr
Processing of : hist_camr1
Processing of : hist_camr2
Processing of : hist_camr_calculated
Processing of : hist_aamr1
Processing of : hist_aamr2
Processing of : hist_aamr_calculated
Processing of : chrabmr3
Processing of : chrabmr
Processing of : c4d_only
Processing of : final_abmr
Processing of : final_susp_abmr
Processing of : final_abmr_verified
Processing of : diag_code_1
Processing of : diag_code_2
Processing of : diag_code_2_final_abmr
Processing of : diag_code_2_final_susp_abmr
Processing of : diag_code_3
Processing of : diag_code_4_active
Processing of : diag_code_4_chronic
Processing of : diag_code_5
Processing of : diag_code_bk
Processing of : diag_code_ptld
Processing of : diag_code_cni
Processing of : diag_code_atn
Processing of : diag_code_cgn
Processing of : diag_code_agn
Processing of : diag_code_infec
Processing of : diag_code_ain
[5/6] - Assessment of the the annotated 'banff_example'
- DATA DICTIONARY ASSESSMENT: data_dict --------------
Assess the standard adequacy of naming
Assess the uniqueness and presence of variable names
Assess the presence of possible duplicated columns
Assess the presence of duplicated rows
Assess the presence of empty rows in the data dictionary
Assess the presence of empty column in the data dictionary
Assess the presence of categories not in the data dictionary
Assess the `valueType` column in 'Variables'
Assess the completion of `label` column in 'Variables'
Assess presence and completion of `label` column in 'Categories'
Assess the logical values of missing column in Categories
Generate report
- WARNING MESSAGES (if any): --------------------------------------------
- DATASET ASSESSMENT: banff_example --------------------------
Assess the standard adequacy of naming
Assess the presence of variable names both in dataset and data dictionary
Assess the presence of possible duplicated variable in the dataset
Assess the presence of possible duplicated participants
Assess the presence of unique value columns in dataset
Assess the presence of empty rows in the dataset
Assess the presence all empty variable in the dataset
Assess the Categories comparison in dataset and data dictionary
Assess the `valueType` comparison in dataset and data dictionary
Generate report
- WARNING MESSAGES (if any): -------------------------------------------------
Error: The dataset and/or the data dictionary contain errors.
Useful tip: Use dataset_evaluate(dataset, data_dict) to get a full assessment of
your dataset
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘BanffIT_Run_Script.R’ [8m/17m]
Running the tests in ‘tests/BanffIT_Run_Script.R’ failed.
Complete output:
> # # loading dataset
> # library(banffIT)
> # library(fs)
> # library(dplyr)
> # library(rlang)
> # library(tools)
> # library(readr)
> # library(stringr)
> # library(lubridate)
> # library(tidyr)
> # library(fabR)
> # library(madshapR)
> # library(crayon)
> # library(Rmonize)
> # library(janitor)
> #
> # input_file = "tests/CHUQ_for_test_3.csv"
> # output_folder = 'tests'
> # language = 'label:en'
> # option_filter = quote(adequacy == 1)
> # detail = TRUE
> # include_banff_dictionary = TRUE
>
> library(banffIT)
>
> input_file = system.file("extdata", "banff_example.xlsx", package = "banffIT")
>
> banff_launcher(
+ input_file = input_file,
+ output_folder = 'tests',
+ language = 'label:en',
+ option_filter = adequacy == 1,
+ detail = TRUE)
Welcome to the Banff diagnosis helper.
Press [enter] to continue or [esc] to quit.
[1/6] - Import data
[2/6] - Evaluation of 'banff_example'
[3/6] - Add diagnosis to each observation of'banff_example'
[4/6] - Generate labels for each variable of 'banff_example'
Processing of : patient_id
Processing of : center
Processing of : biopsy_id
Processing of : sc_date_bx
Processing of : date_tx
Processing of : type_bx
Processing of : adequacy
Processing of : fixation_ff
Processing of : fixation_paraffin
Processing of : fixation_elec
Processing of : fixation_rna
Processing of : microscopy
Processing of : c4d_if
Processing of : c4d_ihc
Processing of : dsa
Processing of : hist_dsa
Processing of : i_score
Processing of : t_score
Processing of : v_score
Processing of : g_score
Processing of : ptc_score
Processing of : ti_score
Processing of : cg_score
Processing of : mm_score
Processing of : cv_score
Processing of : ci_score
Processing of : ct_score
Processing of : ah_score
Processing of : glomeruli
Processing of : arteries
Processing of : bk
Processing of : gs
Processing of : i_ifta_score
Processing of : atma
Processing of : ctma
Processing of : atn
Processing of : agn
Processing of : cgn
Processing of : infec
Processing of : cni
Processing of : ain
Processing of : ptld
Processing of : sptcbmml
Processing of : leuscint
Processing of : monofibneoint
Processing of : newaif
Processing of : othi_ifta
Processing of : genetx
Processing of : hist_aamr
Processing of : hist_camr
Processing of : hist_tcmr
Processing of : adequacy_calculated
Processing of : c4d
Processing of : nogn
Processing of : ifta
Processing of : aamr11.1
Processing of : aamr11.2
Processing of : aamr12
Processing of : aamr13
Processing of : aamr14
Processing of : aamr1
Processing of : aamr21
Processing of : aamr22.1
Processing of : aamr22.2
Processing of : aamr22.3
Processing of : aamr2
Processing of : aamr
Processing of : susp_aamr
Processing of : c4dneg_aamr
Processing of : susp_c4dneg_aamr
Processing of : dsaneg_aamr
Processing of : susp_activeaamr
Processing of : hist_dsa1
Processing of : hist_dsa2
Processing of : hist_dsa_calculated
Processing of : hist_tcmr1
Processing of : hist_tcmr2
Processing of : hist_tcmr3
Processing of : hist_tcmr_calculated
Processing of : camr11
Processing of : camr12
Processing of : camr13
Processing of : camr1
Processing of : activeabmr
Processing of : camr
Processing of : susp_camr
Processing of : c4dneg_camr
Processing of : susp_c4dneg_camr
Processing of : dsaneg_camr
Processing of : chractabmr
Processing of : susp_chractabmr
Processing of : hist_camr1
Processing of : hist_camr2
Processing of : hist_camr_calculated
Processing of : hist_aamr1
Processing of : hist_aamr2
Processing of : hist_aamr_calculated
Processing of : chrabmr3
Processing of : chrabmr
Processing of : c4d_only
Processing of : final_abmr
Processing of : final_susp_abmr
Processing of : final_abmr_verified
Processing of : diag_code_1
Processing of : diag_code_2
Processing of : diag_code_2_final_abmr
Processing of : diag_code_2_final_susp_abmr
Processing of : diag_code_3
Processing of : diag_code_4_active
Processing of : diag_code_4_chronic
Processing of : diag_code_5
Processing of : diag_code_bk
Processing of : diag_code_ptld
Processing of : diag_code_cni
Processing of : diag_code_atn
Processing of : diag_code_cgn
Processing of : diag_code_agn
Processing of : diag_code_infec
Processing of : diag_code_ain
[5/6] - Assessment of the the annotated 'banff_example'
- DATA DICTIONARY ASSESSMENT: data_dict --------------
Assess the standard adequacy of naming
Assess the uniqueness and presence of variable names
Assess the presence of possible duplicated columns
Assess the presence of duplicated rows
Assess the presence of empty rows in the data dictionary
Assess the presence of empty column in the data dictionary
Assess the presence of categories not in the data dictionary
Assess the `valueType` column in 'Variables'
Assess the completion of `label` column in 'Variables'
Assess presence and completion of `label` column in 'Categories'
Assess the logical values of missing column in Categories
Generate report
- WARNING MESSAGES (if any): --------------------------------------------
- DATASET ASSESSMENT: banff_example --------------------------
Assess the standard adequacy of naming
Assess the presence of variable names both in dataset and data dictionary
Assess the presence of possible duplicated variable in the dataset
Assess the presence of possible duplicated participants
Assess the presence of unique value columns in dataset
Assess the presence of empty rows in the dataset
Assess the presence all empty variable in the dataset
Assess the Categories comparison in dataset and data dictionary
Assess the `valueType` comparison in dataset and data dictionary
Generate report
- WARNING MESSAGES (if any): -------------------------------------------------
Error: The dataset and/or the data dictionary contain errors.
Useful tip: Use dataset_evaluate(dataset, data_dict) to get a full assessment of
your dataset
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc