This is file examples.txt 11/26/19 => 3/8/20 Contents: Auto-executable Dataplot tutorial examples. To auto-execute an example, enter the example ID which resides at the beginning of the example's line; thus, e.g., to do a Comparative analysis of the classic Wright Brothers first-plane pressure dat, enter 3.3 and 3 files will be automatically produced: the graphics output will be placed in dataplot_out.pdf the datalot script will be placdd in dataplot_out.dp the input data will be placed in dataplot_out.dat To edit/tweak/customize the code (in examples.dp) to apply to your data: 1. Execute: Run the example as is by entering the example #: for example, 3.3 for the Wright Brothers' analysis. 2. Edit: With your editor-of-choice, edit/customize the dataplot script file dataplot_out.dp to suit your problem (e.g., edit/change dataplot's READ command, titles, labels, etc.) 3. Re-Execute: Re-enter dataplot and enter call dataplot_out.dp to execute the just-edited script file dtaplot_out.dp . 4. View: view the new graphics results which will reside/overwrite dataplot_out.pdf . Index Code Data Output ----------------------------------------------------------------------------------------------------------------------- 0. General Enter 0.1 for: histogram wright8.dp wright11.dat [3-page output] Enter 0.2 for: scatter plot wright9.dp wright11.dat [2-page output] Enter 0.3 for: Plot functions minitest_menu.dp junk1. and junk2. [13] Enter 0.4 for: 2-Level Exp. Designs 2_level_designs.xlsx none [excel sheet with ~ 15 tabs] Enter 0.5 for: Random Permutations random_permutations.xlsx none [excel sheet with ~ 10 tabs] Enter 0.6 for: Binomial Confidence Lim. binomial_acceptance_sampling.xlsx none [excel sheet with 1 tab ] Enter 0.7 for: Bin. Conf. Lim (large n) binomial_acceptance_sampling_large_n.xlsx none [excel sheet with 1 tab ] 1. Univariate 1.1 : (k=0 factors) Test stat control lew_menu.dp lew.dat [1 page pdf file] 1.2 : (k=0 factors) Test stat control mavro.dp mavro.dat [1] 1.3 : (k=0) Test stat control zarr.dp zarr.dat [1] 1.4 : (k=0) Test stat control univariate_classics.dp 10 files [10] 1.5 : (k=0) Test best-fit dist. simiu.dp simiu.dat [1] 1.6 : (k=0) SRM Certif. Value cline153.dp cline153.dat 1.7 : (k=0) SRM Certif. Value funnel__0_10.dp funnel_0_10.dat [x] 1.8 : (k=0) SRM Certif. Value funnel_0_10_clipboard.dp clipboard [1] 1.9 : (k=0) SRM Certif. Value funnel_1_60_4plot.dp funnel_1_60_matrix.dat [7] 2. Interlab Consensus Value 2.1 : (k=1 factor) (24 students) youden_1_96.dp youden_1962_paper_thickness.dat 2.2 : (k=1) ( 9 tables) funnel_1_90.dp funnel_1_90_matrix.dat 2.3 : (k=1) ( 8 vials) dasilva141_menu.dp dasilva141.dat 2.4 : (k=1) (20 vials) dasilva143.dp dasilva143.dat 2.5 : (k=1) (18 labs ) fletcher446.dp fletcher446.dat 2.6 : (k=1) (35 devices,7 loops) gates12.dp gates12.dat 2.7 : (k=1) ( 6 tables, Boulder) funnel_1_60.dp funnel_1_60_matrix.dat (DEX Class 2020) 2.8 : (k=1) ( 6 tables, Boulder) funnel_1_60_clipboard.dp clipboard 2.9 : (k=2) (112 vials) dasilva192.dp (SRM 9-step) dasilva175_coulter_yeast_all_seasons.dat [9] 3. Comparative 3.1 : (k=1 factor) draft69.dp FIX THIS FIX THIS draft69.dat 3.2 : (k=1) funnel_1_6.dp funnel_1_6.dat 3.3 : (k=2) wright11.dp wright11.dat 3.4 : (k=2) boxshoes_2_20_block_plot.dp boxshoes_2_20.dat 3.5 : (k=3) funnel_3_12_block_plot.dp funnel_3_12.dat 3.6 : (k=4) sheesley_4_24_block_plot.dp sheesley_4_24.dat 3.7 : (k=5) boxreactor_5_32_block_plot.dp boxreactor_5_32.dat 3.8 : (k=3) funnel_3_12_block_plot_clipboard.dp clipboard 3.9 : (k=2) corona_virus_2_n_block_plot.dp corona_virus_2_n_matrix.dat 3.10: (k=2) corona_virus_2_n_block_plot_clipboard.dp clipboard 4. Sensitivity Analysis (DEX 10-step) 4.1 : (k=3 factors) boxsprings_3_8.dp (full) boxsprings_3_8.dat [10] 4.2 : (k=3) funnel_3_8.dp (full) funnel_3_8.dat [10] 4.3 : (k=3) bowen_3_8.dp (full) bowen_3_8.dat [10] 4.4 : (k=4) boxconverter_4_16.dp (full) boxconverter_4_16.dat [10] 4.5 : (k=4) boxcleanser_4_8.dp (fractional) boxcleanser_4_8.dat [10] 4.6 : (k=5) krasny_5_32.dp (full) krasny_5_32.dat [10] 4.7 : (k=5) boxreactor_5_32.dp (full) boxreactor_5_32.dat [10] 4.8 : (k=5) boxreactor_5_16.dp (fractional) boxreactor_5_16.dat [10] 4.9 : (k=5) boxreactor_5_8.dp (fractional) boxreactor_5_8.dat [10] 4.10 : (k=5) tang_5_16.dp (fractional) tang_5_16.dat [10] 4.11 : (k=6) zarr_6_16.dp (fractional) zarr_6_16.dat [10] 4.12 : (k=7) kneifel_7_128.dp (full) kneifel_7_128.dat [10] 4.13 : (k=7) fontana_7_128.dp (full) fontana_7_128.dat [10] 4.14 : (k=7) fong_7_16.dp (fractional) fong_7_16.dat [10] 4.15 : (k=8) scott_8_16.dp (fractional) scott_8_16.dat [10] 4.16 : (k=8) inn_8_16.dp (fractional) inn_8_16.dat [10] 4.17 : (k=9) hecht_9_64.dp (fractional) hecht_9_64.dat [10] 4.18 : (k=10) ma_10_16.dp (fractional) ma_10_16.dat [10] 4.19 : (k=13) wtc_13_16.dp (fractional) wtc_13_16.dat [10] 4.20 : (k=13) fontana_15_256.dp (fractional) fontana_15_256.dat [10] 4.21 : (k=20) mills_20_256.dp (fractional) mills_20_256.dat [10] 4.22 : (k=k) generic_k_n.dp (full or fractional) generic_2_4.dat=>your choice[10] 5. Modeling/regression 5.1 : (k=1 factor) berger.dp berger.dat 5.2 : (k=1) fletcher306.dp fletcher306.dat 6. Optimization (Local & Global Opt.) 6.1 : (k=2 factors) wright11.dp wright11.dat 6.2 : (k=8) sarkar71_menu.dp sarkar71_allresponses_040219.dat 6.3 : (k=2) boxchemyield1.dp boxchemyield1.dat 6.4 : (k=2) boxchemyield2.dp boxchemyield2.dat 6.5 : (k=2) boxchemyield3.dp boxchemyield3.dat 7. Classification (Supervised ML) 7.1 : (4 features) classification_iris.dp iris.dat [7 page pdf file] 7.2 : (6 features) classification_flury.dp flury5.dat 7.3 : (8=>64 feat.) sarkar80_menu.dp sarkar71_allresponses_040219.dat 8. Clustering (Unsupervised ML) 8.1 : (18 resp.) mills47b.dp mills28responses2.dat 9. Time series 9.1 : 1 Series: lew_timeseries_menu.dp lew.dat 9.2 : 1 Series: luther_menu.dp luther.dat 9.3 : 2 Series: runbinson23_menu.dp rubinson23.dat Note : To auto-run any example: enter the example's id # (0.1, 0.2, 1.1, 1.2, 2.1, . . ., 9.1, 9.2) at the prompt (e.g., to run the boxreactor_5_32 example, enter 4.2). Output: pdf graphics file: dataplot_out.pdf ps graphics file: dataplot_out.ps txt program file: dataplot_out.dp txt data file: dataplot_out.dat