Build diagnostic atlas data
Usage
diagnostic_atlas_data(
space = c("cylindrical", "toroidal"),
n = 600,
seed = 20260609
)Value
A data frame with diagnostic scenarios and plotting columns. The
returned object has class diagnostic_atlas_data.
See also
Other directional diagnostics:
autoplot.diagnostic_atlas_data(),
diagnostic_scenarios(),
plot_classical_comparison(),
plot_diagnostic_atlas(),
simulate_cyl_diagnostic(),
simulate_tor_diagnostic()
Examples
diagnostic_atlas_data("cylindrical", n = 20, seed = 1)
#> theta x scenario space theta_plot scenario_label
#> 1 1.16164950 3.313238 independent cylindrical 1.16164950 independent
#> 2 4.41314622 3.736315 independent cylindrical -1.87003908 independent
#> 3 3.60231560 2.705478 independent cylindrical -2.68086970 independent
#> 4 1.05590136 2.220248 independent cylindrical 1.05590136 independent
#> 5 5.93031747 4.336672 independent cylindrical -0.35286784 independent
#> 6 5.92802800 1.266698 independent cylindrical -0.35515731 independent
#> 7 0.81152978 3.658953 independent cylindrical 0.81152978 independent
#> 8 5.23671335 3.026855 independent cylindrical -1.04647195 independent
#> 9 2.94064706 3.759622 independent cylindrical 2.94064706 independent
#> 10 3.45564977 3.324199 independent cylindrical -2.82753554 independent
#> 11 3.47255358 4.568114 independent cylindrical -2.81063173 independent
#> 12 1.50102004 2.100056 independent cylindrical 1.50102004 independent
#> 13 4.77844607 4.192229 independent cylindrical -1.50473923 independent
#> 14 1.13612620 4.465989 independent cylindrical 1.13612620 independent
#> 15 2.54646305 3.003703 independent cylindrical 2.54646305 independent
#> 16 5.36300310 1.161220 independent cylindrical -0.92018221 independent
#> 17 6.13489264 3.357928 independent cylindrical -0.14829266 independent
#> 18 1.41890322 2.552581 independent cylindrical 1.41890322 independent
#> 19 2.79481881 3.594152 independent cylindrical 2.79481881 independent
#> 20 0.47110962 3.217228 independent cylindrical 0.47110962 independent
#> 21 1.05583605 3.691390 smooth cylindrical 1.05583605 smooth mean
#> 22 5.07377517 2.365058 smooth cylindrical -1.20941013 smooth mean
#> 23 2.41866413 2.061894 smooth cylindrical 2.41866413 smooth mean
#> 24 2.05921545 2.591208 smooth cylindrical 2.05921545 smooth mean
#> 25 3.78311011 2.474801 smooth cylindrical -2.50007519 smooth mean
#> 26 3.79751984 2.347847 smooth cylindrical -2.48566547 smooth mean
#> 27 0.78309503 3.903366 smooth cylindrical 0.78309503 smooth mean
#> 28 1.85103220 2.579309 smooth cylindrical 1.85103220 smooth mean
#> 29 3.62923016 2.750197 smooth cylindrical -2.65395515 smooth mean
#> 30 3.96455971 2.503929 smooth cylindrical -2.31862560 smooth mean
#> 31 3.21709076 2.135685 smooth cylindrical -3.06609454 smooth mean
#> 32 3.17315884 2.020758 smooth cylindrical -3.11002647 smooth mean
#> 33 3.35544309 2.281833 smooth cylindrical -2.92774222 smooth mean
#> 34 3.50130147 1.912046 smooth cylindrical -2.78188384 smooth mean
#> 35 5.45329897 2.905482 smooth cylindrical -0.82988633 smooth mean
#> 36 5.21321347 2.586077 smooth cylindrical -1.06997184 smooth mean
#> 37 0.70025568 4.548440 smooth cylindrical 0.70025568 smooth mean
#> 38 4.42140436 2.743950 smooth cylindrical -1.86178095 smooth mean
#> 39 5.63908508 3.249633 smooth cylindrical -0.64410023 smooth mean
#> 40 1.75761147 2.567707 smooth cylindrical 1.75761147 smooth mean
#> 41 3.68069187 3.451882 heteroscedastic cylindrical -2.60249344 variable spread
#> 42 0.05620809 3.005555 heteroscedastic cylindrical 0.05620809 variable spread
#> 43 1.84562041 3.415995 heteroscedastic cylindrical 1.84562041 variable spread
#> 44 1.74279826 2.952183 heteroscedastic cylindrical 1.74279826 variable spread
#> 45 5.11183755 3.008162 heteroscedastic cylindrical -1.17134775 variable spread
#> 46 1.63631595 3.173681 heteroscedastic cylindrical 1.63631595 variable spread
#> 47 4.55157646 3.469383 heteroscedastic cylindrical -1.73160885 variable spread
#> 48 5.69314489 2.990817 heteroscedastic cylindrical -0.59004042 variable spread
#> 49 5.96299557 2.975168 heteroscedastic cylindrical -0.32018973 variable spread
#> 50 0.45958026 2.853628 heteroscedastic cylindrical 0.45958026 variable spread
#> 51 4.74176304 3.514940 heteroscedastic cylindrical -1.54142227 variable spread
#> 52 1.79699490 3.177379 heteroscedastic cylindrical 1.79699490 variable spread
#> 53 0.62865482 3.776739 heteroscedastic cylindrical 0.62865482 variable spread
#> 54 5.99459091 3.327425 heteroscedastic cylindrical -0.28859440 variable spread
#> 55 2.61133654 3.673723 heteroscedastic cylindrical 2.61133654 variable spread
#> 56 2.85949282 2.690347 heteroscedastic cylindrical 2.85949282 variable spread
#> 57 6.10132263 3.351675 heteroscedastic cylindrical -0.18186268 variable spread
#> 58 3.66930469 3.730368 heteroscedastic cylindrical -2.61388061 variable spread
#> 59 6.04570996 2.753176 heteroscedastic cylindrical -0.23747535 variable spread
#> 60 4.78591735 3.396767 heteroscedastic cylindrical -1.49726796 variable spread
#> 61 1.25798451 3.336666 multimodal cylindrical 1.25798451 multiple modes
#> 62 4.30535541 4.508400 multimodal cylindrical -1.97782989 multiple modes
#> 63 5.76090039 3.188535 multimodal cylindrical -0.52228491 multiple modes
#> 64 1.78693449 2.723287 multimodal cylindrical 1.78693449 multiple modes
#> 65 0.65753615 3.212641 multimodal cylindrical 0.65753615 multiple modes
#> 66 4.40487393 2.183217 multimodal cylindrical -1.87831138 multiple modes
#> 67 3.31727042 2.259591 multimodal cylindrical -2.96591489 multiple modes
#> 68 5.07640658 4.361914 multimodal cylindrical -1.20677872 multiple modes
#> 69 6.00986753 2.893784 multimodal cylindrical -0.27331777 multiple modes
#> 70 0.69399678 3.019336 multimodal cylindrical 0.69399678 multiple modes
#> 71 1.71709998 2.691065 multimodal cylindrical 1.71709998 multiple modes
#> 72 3.08198534 2.234926 multimodal cylindrical 3.08198534 multiple modes
#> 73 2.00059145 2.877596 multimodal cylindrical 2.00059145 multiple modes
#> 74 3.51338649 2.220495 multimodal cylindrical -2.76979882 multiple modes
#> 75 1.64992135 2.936756 multimodal cylindrical 1.64992135 multiple modes
#> 76 1.26841936 3.032915 multimodal cylindrical 1.26841936 multiple modes
#> 77 2.43489608 3.504388 multimodal cylindrical 2.43489608 multiple modes
#> 78 5.57865030 3.452522 multimodal cylindrical -0.70453500 multiple modes
#> 79 3.48668124 1.683366 multimodal cylindrical -2.79650407 multiple modes
#> 80 5.29156914 2.675893 multimodal cylindrical -0.99161617 multiple modes
#> 81 3.80929606 2.607455 seam cylindrical -2.47388925 seam crossing
#> 82 5.89137827 3.675782 seam cylindrical -0.39180704 seam crossing
#> 83 1.66097303 3.068744 seam cylindrical 1.66097303 seam crossing
#> 84 2.38820053 2.142017 seam cylindrical 2.38820053 seam crossing
#> 85 5.07356777 3.221157 seam cylindrical -1.20961754 seam crossing
#> 86 6.14543103 4.053705 seam cylindrical -0.13775428 seam crossing
#> 87 6.01887505 4.440456 seam cylindrical -0.26431025 seam crossing
#> 88 4.79238559 2.810314 seam cylindrical -1.49079971 seam crossing
#> 89 3.20221619 1.879608 seam cylindrical -3.08096912 seam crossing
#> 90 0.40511965 4.516861 seam cylindrical 0.40511965 seam crossing
#> 91 4.04368694 2.478721 seam cylindrical -2.23949836 seam crossing
#> 92 5.75482524 3.555587 seam cylindrical -0.52836006 seam crossing
#> 93 0.59836395 4.371287 seam cylindrical 0.59836395 seam crossing
#> 94 1.85588206 2.407659 seam cylindrical 1.85588206 seam crossing
#> 95 4.83762354 3.178748 seam cylindrical -1.44556177 seam crossing
#> 96 1.60782644 2.668693 seam cylindrical 1.60782644 seam crossing
#> 97 3.25403482 1.947110 seam cylindrical -3.02915049 seam crossing
#> 98 4.25905672 3.128689 seam cylindrical -2.02412858 seam crossing
#> 99 0.92505967 3.980233 seam cylindrical 0.92505967 seam crossing
#> 100 4.40153495 2.538751 seam cylindrical -1.88165035 seam crossing