This function fits a high-dimensional model using hexagonal bins and provides options to customize the modeling process, including the choice of bin centroids or bin means, removal of low-density hexagons, and averaging of high-dimensional data.
Arguments
- highd_data
A tibble that contains the high-dimensional data with a unique identifier.
- nldr_data
A tibble that contains the embedding with a unique identifier.
- b1
(default: 4) A numeric value representing the number of bins along the x axis.
- q
(default: 0.1) A numeric value representing the buffer amount as proportion of data range.
- benchmark_highdens
(default: 5) A numeric value using to filter high-density hexagons.
Value
A list containing a list of a tibble contains scaled first and second columns
of NLDR data, and numeric vectors representing the limits of the original NLDR data (nldr_obj),
a object that contains hexagonal binning information (hb_obj),
a tibble with high-dimensional model (model_highd) and a tibble containing
hexagonal bin centroids in 2-D (model_2d), and
a tibble that contains the edge information (trimesh_data).
Examples
fit_highd_model(highd_data = scurve, nldr_data = scurve_umap, b1 = 4,
q = 0.1, benchmark_highdens = 5)
#> ✔ Model generated successfully!!!
#> $nldr_obj
#> $nldr_obj$scaled_nldr
#> # A tibble: 1,000 × 3
#> emb1 emb2 ID
#> <dbl> <dbl> <int>
#> 1 0.277 0.913 1
#> 2 0.697 0.538 2
#> 3 0.779 0.399 3
#> 4 0.173 0.953 4
#> 5 0.218 0.983 5
#> 6 0.593 1.05 6
#> 7 0.180 0.210 7
#> 8 0.976 0.571 8
#> 9 0.803 0.829 9
#> 10 0.932 0.410 10
#> # ℹ 990 more rows
#>
#> $nldr_obj$lim1
#> [1] -9.146398 8.552211
#>
#> $nldr_obj$lim2
#> [1] -10.36686 10.10691
#>
#>
#> $hb_obj
#> $a1
#> [1] 0.3962013
#>
#> $a2
#> [1] 0.3431204
#>
#> $bins
#> [1] 4 5
#>
#> $start_point
#> [1] -0.1000000 -0.1156801
#>
#> $centroids
#> # A tibble: 20 × 3
#> h c_x c_y
#> <int> <dbl> <dbl>
#> 1 1 -0.1 -0.116
#> 2 2 0.296 -0.116
#> 3 3 0.692 -0.116
#> 4 4 1.09 -0.116
#> 5 5 0.0981 0.227
#> 6 6 0.494 0.227
#> 7 7 0.891 0.227
#> 8 8 1.29 0.227
#> 9 9 -0.1 0.571
#> 10 10 0.296 0.571
#> 11 11 0.692 0.571
#> 12 12 1.09 0.571
#> 13 13 0.0981 0.914
#> 14 14 0.494 0.914
#> 15 15 0.891 0.914
#> 16 16 1.29 0.914
#> 17 17 -0.1 1.26
#> 18 18 0.296 1.26
#> 19 19 0.692 1.26
#> 20 20 1.09 1.26
#>
#> $hex_poly
#> h x y
#> 1 1 -0.10000000 0.113066785
#> 2 1 -0.29810065 -0.001306679
#> 3 1 -0.29810065 -0.230053606
#> 4 1 -0.10000000 -0.344427070
#> 5 1 0.09810065 -0.230053606
#> 6 1 0.09810065 -0.001306679
#> 7 2 0.29620130 0.113066785
#> 8 2 0.09810065 -0.001306679
#> 9 2 0.09810065 -0.230053606
#> 10 2 0.29620130 -0.344427070
#> 11 2 0.49430195 -0.230053606
#> 12 2 0.49430195 -0.001306679
#> 13 3 0.69240260 0.113066785
#> 14 3 0.49430195 -0.001306679
#> 15 3 0.49430195 -0.230053606
#> 16 3 0.69240260 -0.344427070
#> 17 3 0.89050325 -0.230053606
#> 18 3 0.89050325 -0.001306679
#> 19 4 1.08860390 0.113066785
#> 20 4 0.89050325 -0.001306679
#> 21 4 0.89050325 -0.230053606
#> 22 4 1.08860390 -0.344427070
#> 23 4 1.28670455 -0.230053606
#> 24 4 1.28670455 -0.001306679
#> 25 5 0.09810065 0.456187177
#> 26 5 -0.10000000 0.341813713
#> 27 5 -0.10000000 0.113066785
#> 28 5 0.09810065 -0.001306679
#> 29 5 0.29620130 0.113066785
#> 30 5 0.29620130 0.341813713
#> 31 6 0.49430195 0.456187177
#> 32 6 0.29620130 0.341813713
#> 33 6 0.29620130 0.113066785
#> 34 6 0.49430195 -0.001306679
#> 35 6 0.69240260 0.113066785
#> 36 6 0.69240260 0.341813713
#> 37 7 0.89050325 0.456187177
#> 38 7 0.69240260 0.341813713
#> 39 7 0.69240260 0.113066785
#> 40 7 0.89050325 -0.001306679
#> 41 7 1.08860390 0.113066785
#> 42 7 1.08860390 0.341813713
#> 43 8 1.28670455 0.456187177
#> 44 8 1.08860390 0.341813713
#> 45 8 1.08860390 0.113066785
#> 46 8 1.28670455 -0.001306679
#> 47 8 1.48480520 0.113066785
#> 48 8 1.48480520 0.341813713
#> 49 9 -0.10000000 0.799307568
#> 50 9 -0.29810065 0.684934104
#> 51 9 -0.29810065 0.456187177
#> 52 9 -0.10000000 0.341813713
#> 53 9 0.09810065 0.456187177
#> 54 9 0.09810065 0.684934104
#> 55 10 0.29620130 0.799307568
#> 56 10 0.09810065 0.684934104
#> 57 10 0.09810065 0.456187177
#> 58 10 0.29620130 0.341813713
#> 59 10 0.49430195 0.456187177
#> 60 10 0.49430195 0.684934104
#> 61 11 0.69240260 0.799307568
#> 62 11 0.49430195 0.684934104
#> 63 11 0.49430195 0.456187177
#> 64 11 0.69240260 0.341813713
#> 65 11 0.89050325 0.456187177
#> 66 11 0.89050325 0.684934104
#> 67 12 1.08860390 0.799307568
#> 68 12 0.89050325 0.684934104
#> 69 12 0.89050325 0.456187177
#> 70 12 1.08860390 0.341813713
#> 71 12 1.28670455 0.456187177
#> 72 12 1.28670455 0.684934104
#> 73 13 0.09810065 1.142427959
#> 74 13 -0.10000000 1.028054495
#> 75 13 -0.10000000 0.799307568
#> 76 13 0.09810065 0.684934104
#> 77 13 0.29620130 0.799307568
#> 78 13 0.29620130 1.028054495
#> 79 14 0.49430195 1.142427959
#> 80 14 0.29620130 1.028054495
#> 81 14 0.29620130 0.799307568
#> 82 14 0.49430195 0.684934104
#> 83 14 0.69240260 0.799307568
#> 84 14 0.69240260 1.028054495
#> 85 15 0.89050325 1.142427959
#> 86 15 0.69240260 1.028054495
#> 87 15 0.69240260 0.799307568
#> 88 15 0.89050325 0.684934104
#> 89 15 1.08860390 0.799307568
#> 90 15 1.08860390 1.028054495
#> 91 16 1.28670455 1.142427959
#> 92 16 1.08860390 1.028054495
#> 93 16 1.08860390 0.799307568
#> 94 16 1.28670455 0.684934104
#> 95 16 1.48480520 0.799307568
#> 96 16 1.48480520 1.028054495
#> 97 17 -0.10000000 1.485548350
#> 98 17 -0.29810065 1.371174887
#> 99 17 -0.29810065 1.142427959
#> 100 17 -0.10000000 1.028054495
#> 101 17 0.09810065 1.142427959
#> 102 17 0.09810065 1.371174887
#> 103 18 0.29620130 1.485548350
#> 104 18 0.09810065 1.371174887
#> 105 18 0.09810065 1.142427959
#> 106 18 0.29620130 1.028054495
#> 107 18 0.49430195 1.142427959
#> 108 18 0.49430195 1.371174887
#> 109 19 0.69240260 1.485548350
#> 110 19 0.49430195 1.371174887
#> 111 19 0.49430195 1.142427959
#> 112 19 0.69240260 1.028054495
#> 113 19 0.89050325 1.142427959
#> 114 19 0.89050325 1.371174887
#> 115 20 1.08860390 1.485548350
#> 116 20 0.89050325 1.371174887
#> 117 20 0.89050325 1.142427959
#> 118 20 1.08860390 1.028054495
#> 119 20 1.28670455 1.142427959
#> 120 20 1.28670455 1.371174887
#>
#> $data_hb_id
#> # A tibble: 1,000 × 4
#> emb1 emb2 ID h
#> <dbl> <dbl> <int> <int>
#> 1 0.277 0.913 1 13
#> 2 0.697 0.538 2 11
#> 3 0.779 0.399 3 11
#> 4 0.173 0.953 4 13
#> 5 0.218 0.983 5 13
#> 6 0.593 1.05 6 14
#> 7 0.180 0.210 7 5
#> 8 0.976 0.571 8 12
#> 9 0.803 0.829 9 15
#> 10 0.932 0.410 10 7
#> # ℹ 990 more rows
#>
#> $std_cts
#> # A tibble: 13 × 3
#> h n_h w_h
#> <int> <int> <dbl>
#> 1 2 30 0.03
#> 2 3 14 0.014
#> 3 5 75 0.075
#> 4 6 137 0.137
#> 5 7 132 0.132
#> 6 10 12 0.012
#> 7 11 132 0.132
#> 8 12 37 0.037
#> 9 13 140 0.14
#> 10 14 176 0.176
#> 11 15 67 0.067
#> 12 17 4 0.004
#> 13 18 44 0.044
#>
#> $b
#> [1] 20
#>
#> $m
#> [1] 13
#>
#> $pts_bins
#> # A tibble: 13 × 2
#> h pts_list
#> <int> <list>
#> 1 2 <int [30]>
#> 2 3 <int [14]>
#> 3 5 <int [75]>
#> 4 6 <int [137]>
#> 5 7 <int [132]>
#> 6 10 <int [12]>
#> 7 11 <int [132]>
#> 8 12 <int [37]>
#> 9 13 <int [140]>
#> 10 14 <int [176]>
#> 11 15 <int [67]>
#> 12 17 <int [4]>
#> 13 18 <int [44]>
#>
#> attr(,"class")
#> [1] "hex_bin_obj"
#>
#> $model_highd
#> # A tibble: 12 × 8
#> h x1 x2 x3 x4 x5 x6 x7
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2 0.621 0.145 1.73 0.000811 0.00129 -0.0148 -0.00142
#> 2 3 -0.472 1.60 1.87 -0.00204 0.00591 0.0136 0.00319
#> 3 5 0.874 1.07 1.42 -0.00307 0.00218 -0.00370 0.000263
#> 4 6 -0.185 0.655 1.82 -0.00151 0.00135 0.00135 0.00123
#> 5 7 -0.890 1.29 1.04 0.000368 0.000266 0.00151 0.000278
#> 6 10 0.279 0.713 -0.722 0.00382 -0.00440 -0.0265 0.00181
#> 7 11 0.145 0.537 -0.0960 -0.000434 0.000514 0.00394 0.000941
#> 8 12 -0.132 1.68 0.0457 0.00109 -0.000500 -0.0108 -0.00110
#> 9 13 -0.686 0.824 -1.57 0.000626 -0.000342 0.00253 0.000273
#> 10 14 0.620 1.02 -1.63 -0.000149 -0.000135 -0.00418 -0.000195
#> 11 15 0.833 1.54 -0.553 0.000130 0.000263 0.00686 0.0000105
#> 12 18 -0.345 1.77 -1.85 0.00135 0.00260 -0.0106 0.000976
#>
#> $model_2d
#> h c_x c_y n_h w_h
#> 1 2 0.29620130 -0.1156801 30 0.030
#> 2 3 0.69240260 -0.1156801 14 0.014
#> 3 5 0.09810065 0.2274402 75 0.075
#> 4 6 0.49430195 0.2274402 137 0.137
#> 5 7 0.89050325 0.2274402 132 0.132
#> 6 10 0.29620130 0.5705606 12 0.012
#> 7 11 0.69240260 0.5705606 132 0.132
#> 8 12 1.08860390 0.5705606 37 0.037
#> 9 13 0.09810065 0.9136810 140 0.140
#> 10 14 0.49430195 0.9136810 176 0.176
#> 11 15 0.89050325 0.9136810 67 0.067
#> 12 18 0.29620130 1.2568014 44 0.044
#>
#> $trimesh_data
#> # A tibble: 23 × 8
#> from to x_from y_from x_to y_to from_count to_count
#> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 3 4 0.0981 0.227 0.494 0.227 75 137
#> 2 3 6 0.0981 0.227 0.296 0.571 75 12
#> 3 2 4 0.692 -0.116 0.494 0.227 14 137
#> 4 4 5 0.494 0.227 0.891 0.227 137 132
#> 5 4 7 0.494 0.227 0.692 0.571 137 132
#> 6 6 10 0.296 0.571 0.494 0.914 12 176
#> 7 6 7 0.296 0.571 0.692 0.571 12 132
#> 8 7 8 0.692 0.571 1.09 0.571 132 37
#> 9 7 11 0.692 0.571 0.891 0.914 132 67
#> 10 9 12 0.0981 0.914 0.296 1.26 140 44
#> # ℹ 13 more rows
#>