DOI: 10.5281/zenodo.14875771
title: Data for paper "Quantitative and Qualitative Evaluation of IES TM-30 Indices for the Color Preference of Landscape Oil Paintings" published in LEUKOS

description: General Explanation

This doi is reserved to store the data from a journal paper "Quantitative and Qualitative Evaluation of IES TM-30 Indices for the Color Preference of Landscape Oil Paintings" published in LEUKOSCurrently, I think a dataset with a published doi cannot be further updated even if I noticed an error after the publishing. In case if there is a necessary correction or new information should be added by a new version, the new doi of the new version will be offered in this description.

 

Software used in this experiment:

All analyses using Python were performed using Spyder with Python 3All analyses using MATLAB  were performed using MATLAB 2020bAll analyses using R were performed using R Studio Statistical Software (v4.1.2; R Core Team 2021)

 

Files Explaining the data:







Explanation_of_the_Deposition_when_publishing.txt: same information as this Description until the time of publishing. But it is in a txt form and therefore without the format (such as bold or Header setting).



 







Explanation_of_the_Deposition_when_publishing.docx: same information as this Description until the time of publishing. With the format that can be kept in a docx file.







_README_to_explain_the_folders_after_unzip.txt: after unzipped all the zip file (except for code_Python3_module.zip) into the same folder. This file is the README file of this folder. As a result of unzipping files into one folder, this folder contains a file observer_order_paint_Ross_Munsell_20220520.xlsx (from observers_orders.zip) and these subfolders:

- answer_sheets_from_observers: from answer_sheets_from_observers.zip- answer_sheets_researcher_summary_Excel: from answer_sheets_researcher_summary_Excel.zip- answer_sheets_researcher_summary_notes: from answer_sheets_researcher_summary_notes.zip- data_calibration: from analyzed_data_physical.zip + converted_raw_XYZ_pcf_to_img.zip + converted_raw_XYZ_pcf_to_mat.zip + raw_data_determine_spectra.zip + raw_data_physical.zip- data_visual: from raw_data_visual_perception.zip- instructions_and_answer_sheet: from instructions_and_answer_sheet.zip- literature: from literature.zip- Matlab: from code_MATLAB_and_output_results.zip- moo_fast2d: from spectra_moo_determine_the_intensity_of_each_channel.zip- moo_fast10d: from spectra_moo_determine_the_intensity_of_each_channel.zip- moo_res10d: from spectra_moo_determine_the_intensity_of_each_channel.zip- moo_result: from spectra_moo_determine_the_intensity_of_each_channel.zip- optm_brute_force: from spectra_simulation_determine_the_angle.zip + spectra_simulation_determine_the_angle_readme.zip- Python3_all: from code_Python3_all.zip- Python3_preliminary:  from code_Python3_preliminary_test_lamp_decide_spd.zip- Python3_execute_exp: from code_Python3_execute_exp.zip- Python3_analyse: from from code_Python3_analyse_and_plot.zip- R: from code_R_and_output_results.zip- real_paintings: from real_paintings.zip- result_to_intens: from spectra_moo_determine_the_intensity_of_each_channel.zip- setup: from setup.zip








 



 



Files of all README files in each folder after upzipped





all_final_README_files_in_each_folder.zip: After correctly unzipped the file and correctly put into the folder structure, the unzipped file should follow the structure of this folder. (Except for the file code_Python3_module.zip). The latest README files in each unzipped folder is here. During unzipped process, if there is also a README in other zip file and conflicts with the files in this zip file, please use the README file in this zip file instead of those from other zip files because this is the latest one.



 

Files related to the experimental design, the setup, the procedures:

 





raw_data_physical.zip: all physical measurement raw data except for data included in raw_data_determine_spectra.zip  * All the measured physical raw data. These files are independent of the analysis and any other process. Thus, they will never be changed in the future.  = subfolders are: LMK, luxmeter, spd_lamp_monitor, spd_primaries, spd_white_tile, warmup    - LMK:       - raw_data: the LMK measurement raw_data          - 20220330_CRend_3H          - 20220415_CRend_FR_1H          - 20220421_CRend_BM_KM          - 20220511_CRend_RM_CT          - 202204_CRend_FR_1H          - 20240308_Paint_withWhiteTile          - 20240318_LandsMCCTile_3000KRf95          - 20240318_Paint_3000KRf95withMCCTile   - luxmeter: the illuminance measurement results      including a csv file 20220331 that shows the measured results   - spd_lamp_monitor:     including a _README file and csv files generated, with three subfolders        - quickCheck_before_removeCloth        - raw_jeti        - while_testcode   - spd_primaries:     including a _README file and the following subfolders      - l1_2109      - l1_2109_testcode      - l1_210910      - l1_210910_testcode      - l1_211110gray      - l1_21110gray_testcode      - lamp_folder_template      - lamp1- spd_white_tile:  including files:  Convert to csv.xlsx,  SpecimIQWhite - comma.txt,  SpecimIQWhite.csv,  SpecimIQWhite.png, SpecimIQWhite.txt, SpecimIQWhite_wo_UVF.csv- warmup:   including many csv file generated during the measurements and two subfolders  - raw  - when testing code






raw_data_determine_spectra.zip: the data about how the nine spectra were decided.  * This includes a huge amount of spectra generated by the lamp and measured by a JETI spectrometer. These huge amount of spectra were then selected (filter-in) and reached the final nine 3000 K spectra used in this experiment.  = subfolders:     - spd_sol_filt_combined    - spd_sol_filt_combined_v##    ##=00, v02, v03, v05, v07, v08, v09, v10, v12, v12_bgd, v12Cmpns, v12uvTmCmpns, v13bgd, v14bgd, v15, v15bgd    - spd_sol_filt_combined_v##bgd ##=15,16,17,18,19,20,21,22,23,24,25






converted_raw_XYZ_pcf_to_mat.zip: convert the raw data from the colorimeter camera .pcf file to a .mat file by Matlab.  * This contains all the paintings under all spectra in this experiments.







converted_raw_XYZ_pcf_to_img.zip: the data to generate the images of paintings.  * convert the XYZ image captured by a colorimetry camera under the 3000 K lighting condition to a sRGB image showing the color of paintings. A von Kries conversion was applied to let the appearance closer to the appearance under daylight instead of a yellowish image captured under the 3000 K spectra.  = subfolders:    - 20250610_CRend_bmp_devideToMCC_normToD65: with all images in the nine spectra. In fact, only the f95g100 is used in the paper.    - PhotoEdit_202506

spectra_moo_determine_the_intensity_of_each_channel.zip: using a Python tool pymoo (a tool to use multi-objective optimization (MOO)) to decide the luminaire intensity from the spd_primaries.  * There are four folder in the zip files, (1) moo_fast2d (2) moo_fast10d (3) moo_res10d (4) moo_result (5) result_to_intens. To run the python code smoothly, these folder should be in the same folder as Python3_all.  = subfolders:    - moo_fast2d:  moo faster optimization with CIE 1931  2 degree    - moo_fast10d: moo faster optimization with CIE 1976 10 degree    - moo_res10d:  moo normal optimization with CIE 1976 10 degree    - moo_result:  moo normal optimization with CIE 1931  2 degree     - result_to_intens: from the results of pymoo optimization solutions, pick up solutions with the tolerance as Royer (Yuv to CCT based on CIE1931_2) * only used from 2021/05/13 to 2021/07/06. Afterwards, Royer tolerance is applied in pymoo optimization.









spectra_simulation_determine_the_angle.zip: the simuation to determined the angle to be 22.5 degree.  * the results from a brute force simulation according to the primiary of the lamp that detemined the angle of 22.5 for best-fitmaximized the Rf Rg combinations.







spectra_simulation_determine_the_angle_readme.zip: the readme file in the folder explaining the spectra_simulation procedure and results.



setup.zip: information of the setup (lighting spectra, gray cloth, photos and figures of the setup)  = file: RoomSetup250610.pptx (a pptx describing the setup, the Fig, 1 in the published paper)  = subfolders:   - cloth_survey: data to select the cloth material among all available gray cloths in a local shop   - cloth_using: the spectra of the purchased gray cloth after the cloth survey. However, the reflect spectrum is not identical to the cloth during the survey.   - lamp_cond_formal: the lighting spectra of the formal visual experiment measured before the visual experiment started   - lamp_cond_pilot:  the lighting spectra of a pilot experiment to decide a proper experimental procedure.   - photos_of_setup: photos of the setup 




real_paintings.zip: photos from a Canon camera (uncalibrated) to show the paintings with its original frame. The pictures in the questionnaire came from editing these photos. 


observers_orders.zip: an Excel file contain the observer orders, their anonymous information with gender and background.









analyzed_data_physical.zip: all physical measurement raw data  * The results came from analyzing the measured physical raw data. These files are dependent of the analysis and are usually the result from processing the raw data by a MATLAB code, a Python code, a R code, or an Excel file.  * An _README_data_calibration.txt file is included to explain the folder of each subfolder in "data_calibration". All files unzipped from analyzed_data_physical.zip + raw_data_determine_spectra.zip + raw_data_physical.zip = the full data of "data_calibration" folder.  * An Excel file generated the accpet_ind_plot of all results from all sol_filter_v## until 202203. From this result, the best-fit ellipse psi angles was set to 22.5 and -67.5 (112.5).   = subfolders:   - spd_lamp_monitor: contain the Excel file that analyzed the csv files and the subfolders that are color vector graphs generated from the csv data          - cvg_2022-05-11-21-48-09_2s          - ppFig_cvg_2022-05-11-21-48-09_2s   - warmup: a powerpoint file as the report, the following subfolder          - fig: contain figures           and a _README txt filemany csv file generated during the measurements   - LMK: contain a _README_lmk.txt file to explain the files.            - jab_dist2024: analysis the color distribution of the test paintings.                 Two of the results are used in the paper. They are:                 (1) the color distribution of each huebin of each painting. It is located in data_calibration\LMK\jab_dist2024\xyzw_MCCinImg\bar_bin_amount                 (2) the color distribution of M' in cam02ucs of each painting. It is located in data_calibration\LMK\jab_dist2024\xyzw_MCCinImg\cam02uscM                 Other methods that were studied but not in the published article are also included in this zip files such as the color distribution of each pixel captured by LMK for each painting on the CAM02UCS ab plane. 




 

Files related to the questionaires (data of the qualitative results):





answer_sheets_from_observers.zip: scan of all the answer sheet from observers.







answer_sheets_researcher_summary_Excel.zip: the researcher's summary Excel file from the answer sheet of observers. 









answer_sheets_researcher_summary_notes.zip: the researcher's summary from the answer sheet of observers, the print from the Excel with his written summary. 







instructions_and_answer_sheet.zip: contains the instruction and answering sheet for the visual experiment.



 


 

Files related to the 2AFC answers from participants (data of the quantitative results):





raw_data_visual_perception.zip: all the quantitative visual raw data collected during the experiment and the preliminary/pilot experiments. After unzip it, the folder name is "data_visual". Its subfolder 202203_pairC contains the raw data for the experiment of this published paper



 

 

 

Code used in this study:

Python code (with Python3), MATLAB code, and R code used in this study.To run these code, all folder created from the zipped files should be in the same folder. As a result, that folder contains: data_calibration, data_visual, literature, Matlab, moo_fast2d, moo_fast10d,... Python3_all,... R, referance_white, result_to_intens, setup

The only exception is the zip file:  code_Python3_module.zip The upzipped folder should be located in another folder. The path relationship between the folder "common_py_module" and the folder that contains the other folders should be as show in code_Python3_module.zip: the folder "folder_contains_other_folders" contains the other folders. This is because those Python import functions from code_python3_modules by using code "sys.path.insert(1, '../../../common_py_module/v00')"

The code_MATLAB_and_output_results.zip also contains several files generated from python code in the folder "Matlab\UC_software\pwcmp-master\cwlin_result". That is because these files are csv or png files that are either the input or output of MATLAB code. Details are described in a _README_pwcmp_master_code.txt located in "Matlab\UC_software\pwcmp-master\cwlin_result".

The code_R_and_output_results.zip also contains the input file and otput file of these R code. That is because the R code put all inpit and output in this folder. The input are several files generated from python code. They can be either originally outputed in the folder (such as "raw_score_abc_to_ppABC_v##.py" and "ana_eachObsPScore_v##.py" directly generated some csv files in "R\RProjectDir\ANOVA") or being copied and pasted from the original python output folders (such as jod_P_v10.csv, jod_S_v10.csv, jod_B_v10.csv, jod_N_v10.csv were copied from "Matlab\UC_software\pwcmp-master\cwlin_result\output_v10_allPt\seed9"). Details are described in _README_....txt files in i the folder and subfolders.

 

Python code



code_Python3_module.zip : This is the module Author Ching-Wei Lin create to different research projects. Some of the other python code import functions in this module. To execure the other python code, functions in this module sometimes is necessary. To run the code, the other folder generated from other zip files (such as Python3_all, data_calibration,....) should be the folder "folder_contains_other_folders" in this zip file. This is because those Python import functions from code_python3_modules by using code "sys.path.insert(1, '../../../common_py_module/v00')"

code_Python3_all.zip: all the raw Python codes related to this study, a _README file explain the files. Because the huge amount of files, these python codes are separated in the three zip files (code_Python3_analyse_and_plot.zip, code_Python3_execute_exp.zip, code_Python3_preliminary_test_lamp_decide_spd ) by the functions of these code. Draft for codes are included in Python3_all.zip but excluded from the the three separated zip files.



code_Python3_preliminary_test_lamp_decide_spd.zip: Python code used in the preliminary study. Measuring the performance of the tunable LED lamp (warm up time, spectrum of each channel). A procedure to estimate and decide the final nine spectra including a Multi-objective-optimization simulation and a brute force mixing simulation, turn on the lamp with simulated results and selected the final nine spectra. A Pilot study shows that a step of 5 in Rf and Rg is too small. Another pilot experiment using scales instead of two-alternative-force-choice paired comparison. 

code_Python3_execute_exp.zip: Python code to execute the visual experiment and monitor the lamp spectra performance.

code_Python3_analyse_and_plot.zip: Python code to analyze the data collected during the visual experiment and to generate plots from the collected data or the analyzed results. 




 

MATLAB code



code_MATLAB_and_output_results.zip: MATLAB code and their output files (and output of some python code - remark: they are either the required input of the MATLAB codes or JOD plots generated from the MATLAB output. These python output files are located in "Matlab\UC_software\pwcmp-master\cwlin_result". 


 

R code





code_R_and_output_results: R code, the required input data (such as JOD scores generated from Python code) and the output of these R code. These ouputs include figures and statisitcal test values. The tests are (1) Pearson Correlation (2) Spearman Test (3) repeated measure ANOVA (4) Sinusoidal Regression



 

 

Other files



literature.zip: compare the dEuv, Rf, Rg tolerance to three other articles (Royer 2016, Royer 2017, Houser 2017) at the very beginning of the research.