highd.md
In quollr: Visualising How Nonlinear Dimension Reduction Warps Your Data

avg_highd_data() works

Code
  avg_highd_data(highd_data = scurve, scaled_nldr_hexid = umap_with_hb_id)
Output
  # A tibble: 137 x 8
         h      x1     x2    x3         x4        x5       x6         x7
     <int>   <dbl>  <dbl> <dbl>      <dbl>     <dbl>    <dbl>      <dbl>
   1    34  0.958  0.0854  1.29  0.00265    0.0171    0.0876  -0.00249  
   2    35  0.818  0.116   1.56  0.00184    0.00361  -0.0318  -0.00377  
   3    36  0.544  0.111   1.83 -0.00341   -0.000303  0.0196   0.0000704
   4    37  0.279  0.128   1.95  0.0000880  0.00104  -0.0276  -0.000227 
   5    38  0.0567 0.119   2.00  0.00733    0.00238   0.0833  -0.00166  
   6    41 -0.375  1.58    1.91 -0.0126     0.000689  0.0295   0.000936 
   7    42 -0.529  1.84    1.83 -0.000870  -0.000312  0.00825  0.00162  
   8    49  0.935  0.364   1.31 -0.00383   -0.00292  -0.00153  0.000860 
   9    50  0.705  0.449   1.70  0.00218   -0.00679  -0.0149   0.00223  
  10    51  0.387  0.371   1.92  0.00876    0.00420   0.0157   0.00230  
  # i 127 more rows

comb_data_model() works

Code
  comb_data_model(highd_data = scurve, model_highd = scurve_model_obj$model_highd,
  model_2d = scurve_model_obj$model_2d)
Output
  # A tibble: 1,026 x 8
           x1    x2    x3        x4        x5       x6        x7 type 
        <dbl> <dbl> <dbl>     <dbl>     <dbl>    <dbl>     <dbl> <chr>
   1 -0.529   1.84   1.83 -0.000870 -0.000312  0.00825  0.00162  model
   2  0.935   0.364  1.31 -0.00383  -0.00292  -0.00153  0.000860 model
   3 -0.00776 0.305  2.00 -0.000357  0.000463  0.00485  0.00122  model
   4 -0.254   0.261  1.96 -0.00457   0.00248  -0.0156   0.000782 model
   5 -0.706   1.38   1.70  0.000786 -0.00266  -0.0132  -0.00169  model
   6 -0.839   1.77   1.54  0.00281   0.000455  0.0260  -0.00147  model
   7  0.182   0.691  1.98 -0.00137   0.00421   0.00362  0.000414 model
   8 -0.567   0.369  1.81 -0.00213  -0.000838 -0.0130   0.000421 model
   9 -0.724   0.698  1.68 -0.000712  0.00110  -0.00523 -0.000711 model
  10 -0.992   0.960  1.07 -0.00316   0.00512  -0.00440  0.00123  model
  # i 1,016 more rows