tests/testthat/_snaps/ord_plot.md

In david-barnett/microViz: Microbiome Data Analysis and Visualization

constrained rda plot gives correct positions

Code
  cat(p$data[1:50, 1, drop = TRUE])
Output
  -2.130476 0.5894143 0.3160391 1.08751 -0.05355557 3.503399 1.203936 0.6234953 5.592124 2.525964 2.730401 1.39254 3.615096 2.609643 0.7825542 0.6269883 -0.3570368 -0.335859 0.5819399 0.4438977 1.663886 0.149256 0.3422652 0.2049955 0.7025216 -0.3234688 0.3380817 2.476972 1.913976 1.312951 1.080631 -1.103206 -1.392823 -0.2848868 1.558326 -1.85179 0.5686295 -2.050395 -1.256443 1.342032 -1.156612 -1.018807 -1.394098 0.1725057 -0.04134601 -0.6274757 -1.368677 -2.246543 -1.530365 1.691596

Code
  cat(p$data[1:50, 2, drop = TRUE])
Output
  2.618072 -2.748471 -3.076232 -1.148784 0.3788259 -0.1015143 -1.35111 -1.367386 -0.5596091 -3.083707 -1.623868 -1.807981 -0.5441718 -0.5529239 0.9604805 -1.28105 -1.098181 -2.594557 -1.21884 -1.861085 -1.052584 -0.4884243 -0.5190012 -2.966743 -2.431879 -2.63563 -1.925107 -1.227659 -0.7474585 -2.331083 -0.1704811 3.099588 3.292661 -1.575772 -1.654633 2.536926 1.863032 -0.03288809 1.431886 -0.3492331 2.171615 2.694277 -1.276792 -1.185101 3.757507 0.6055251 0.3254076 1.146757 -1.454654 -1.136692

Code
  cat(p$layers[[2]]$data[, 1, drop = TRUE])
Output
  -0.3565107 -0.1062509 0.1547571 -0.8509554 -1.899592 -0.2096152 -0.2829297 -1.779616 -0.4937304 0.5586688 0.3846523 0.4645738 -0.059117 -2.16059 -1.011784 -1.82159 -0.9692845 -1.742553 0.6740945 -1.020301 -2.346078 -0.2790361 -0.1204818 -0.5271442 -1.78475 0.6517035 -0.5044418 -0.9840494 -0.07047137 2.96672 0.4707 1.574522 -2.596042 1.221985 0.1057324 -0.902472 1.130822 -0.1781154 -0.159024 0.1011578 -0.02875207 0.8307857 -0.6201586 -0.3972224 -0.04517522 1.492099 0.771006 0.3775464 0.1834584 0.6782735 0.4648295 3.962965 2.859382 0.5720216 0.08039252 0.527929 -0.6067356 -0.6899561 -1.121057 -0.8502372 0.1333341 -0.4010931 0.5326941 1.674685 -0.08324529 1.282892 -0.337443 -1.879871 -0.2650652 0.1850139 0.1382349 0.4058195 0.1380115 -0.2692422 0.1113067 4.776038 3.61217 0.8894821 -0.2152379 -0.414358 -1.159676 -0.8853212 -1.144903 -0.4437925 -1.527541 -1.223474 -0.2949115 -0.3068263 1.469021 -0.6934613 -0.2475891 0.02910698 -0.2801657 -0.2688476 0.2432086 -0.5492048 -0.3459145 0.5510748 -0.03510124 0.02694244 -0.1714998 1.310444 2.871598 -1.903205 -0.09571269 1.979713 2.077833 3.246218 -1.032558 -0.8310774 -0.8383837 -1.479313 -0.6247188 -1.976837 -0.4051784 -0.7227111 1.405419 0.634562 0.2666264 0.3054786 0.00385781 -0.7068847 0.07462064

Code
  cat(p$layers[[3]]$data[, 1, drop = TRUE])
Output
  4.776038 3.962965 2.96672

Code
  cat(p$layers[[3]]$data[, 2, drop = TRUE])
Output
  -0.09814972 0.2533772 -2.395719

partialed bray CAP plot gives correct positions

Code
  cat(p2$data[1:50, 1, drop = TRUE])
Output
  -0.9433384 -0.4360683 0.01614725 -1.363398 1.665281 1.65784 1.362464 1.129672 1.881359 0.3532599 1.631433 1.388797 1.250819 1.72303 0.8478204 -0.8442538 -0.7064204 -1.10628 -0.2730612 0.4129244 -0.7327066 -0.6039317 1.781876 -2.437726 -0.7128981 -0.5591445 -0.5503607 2.121992 -0.7871148 -0.2522774 0.6067446 0.08712734 2.221565 -1.241554 0.6175632 1.628865 2.537898 -0.03497828 -1.09659 3.99456 -0.07894219 2.536319 -0.8418586 -0.2491924 0.2117898 -0.05593509 -1.513947 -1.795448 -2.313529 -0.2527132

Code
  cat(p2$data[1:50, 2, drop = TRUE])
Output
  -0.777159 0.319758 0.6808594 -0.3605004 0.7990729 0.9501213 -0.2204894 0.7256214 -0.2381873 0.3182067 0.7976874 0.6710309 -0.007768279 -0.3096304 0.9760564 0.2008539 0.3406989 -0.5329119 -0.3638514 0.7576985 -0.1883829 -0.3308651 0.7528426 0.05331558 0.06812347 -0.5354913 0.0230663 0.8174722 -0.331778 -0.3277457 0.8594061 -0.8416075 -0.7947944 -0.4042679 0.1839848 -0.7063301 -0.6911026 0.6860141 -0.6901189 -0.3483738 -0.7896026 -0.690313 -0.05402992 0.6581042 -0.7226321 0.4378195 0.06440707 -0.8558818 0.4833695 0.7706338

Code
  cat(p2$layers[[2]]$data[, 1, drop = TRUE])
Output
  2.686247

aitchison plot hasn't changed

Code
  cat(abs(p3$data[1:50, 1, drop = TRUE]))
Output
  1.106491 0.8693114 0.7769138 0.1722429 0.5494207 1.342983 0.6422256 0.6158025 1.381771 1.076831 1.047452 0.9241626 1.112544 0.6735143 0.9536031 0.7115146 0.4646272 0.09576095 0.1244906 0.7623212 0.6518461 0.09280437 0.7242988 0.5598014 0.8549104 0.2034272 0.2821326 1.169105 0.3978237 0.5269234 0.8514695 1.310387 1.287183 0.0458201 0.5668595 1.1262 0.6357289 0.044228 0.9423226 0.0271642 1.315038 1.145424 0.1641273 0.2225042 0.8148921 0.1271763 0.3235937 0.8928878 0.0088699 0.9016179

Code
  cat(abs(p3$data[1:50, 2, drop = TRUE]))
Output
  0.5787119 1.110654 1.004009 1.55686 0.476133 0.3927158 1.640435 0.4383189 0.3547506 1.092631 0.5076862 1.161595 1.458424 2.499746 0.4842615 0.7047841 0.3034085 1.131942 1.505218 0.7052604 1.343786 1.922793 0.1882586 0.7064074 1.607724 1.576125 0.8710285 0.9390623 1.286664 2.279908 0.4152985 0.2621039 0.2757177 0.1157476 0.2378094 0.2285831 0.1264438 0.9902263 0.1533971 1.291777 0.08253041 0.191776 0.2938356 0.6350377 1.308276 1.170076 1.064223 0.4547523 0.06588292 0.6282335

Code
  p3$layers
Output
  [[1]]
  mapping: colour = ~.data$bmi_group 
  geom_point: na.rm = FALSE
  stat_identity: na.rm = FALSE
  position_identity

clr PCA plot hasn't changed

Code
  cat(p4$data[1:50, 1, drop = TRUE])
Output
  -1.106491 0.8693114 0.7769138 0.1722429 0.5494207 1.342983 0.6422256 0.6158025 1.381771 1.076831 1.047452 0.9241626 1.112544 0.6735143 0.9536031 0.7115146 0.4646272 -0.09576095 0.1244906 0.7623212 0.6518461 0.09280437 0.7242988 0.5598014 0.8549104 -0.2034272 0.2821326 1.169105 0.3978237 0.5269234 0.8514695 -1.310387 -1.287183 -0.0458201 0.5668595 -1.1262 -0.6357289 -0.044228 -0.9423226 -0.0271642 -1.315038 -1.145424 -0.1641273 0.2225042 -0.8148921 -0.1271763 -0.3235937 -0.8928878 0.0088699 0.9016179

Code
  cat(p4$data[1:50, 2, drop = TRUE])
Output
  -0.5787119 1.110654 1.004009 1.55686 -0.476133 -0.3927158 1.640435 0.4383189 0.3547506 1.092631 0.5076862 1.161595 1.458424 2.499746 -0.4842615 0.7047841 0.3034085 1.131942 1.505218 0.7052604 1.343786 1.922793 0.1882586 0.7064074 1.607724 1.576125 0.8710285 0.9390623 1.286664 2.279908 -0.4152985 -0.2621039 0.2757177 0.1157476 -0.2378094 0.2285831 -0.1264438 -0.9902263 0.1533971 1.291777 -0.08253041 0.191776 -0.2938356 -0.6350377 -1.308276 -1.170076 -1.064223 -0.4547523 0.06588292 -0.6282335

Code
  p4$layers
Output
  [[1]]
  mapping: colour = ~.data$bmi_group 
  geom_point: na.rm = FALSE
  stat_identity: na.rm = FALSE
  position_identity

david-barnett/microViz documentation built on April 17, 2025, 4:25 a.m.