Compute Projection for High-Dimensional Data
Arguments
- projection
A matrix or data frame representing the projection.
- proj_scale
Scaling factor for the projection.
- highd_data
A data frame or matrix of high-dimensional data.
- model_highd
A model object or function used for high-dimensional transformation.
- tr_from_to_df
A data frame defining transformation from one space to another.
- axis_param
A list of parameters for axis configuration.
Examples
projection_df <- cbind(
c(-0.17353,-0.02906,0.19857,0.00037,0.00131,-0.05019,0.03371),
c(-0.10551,0.14829,-0.02063,0.02658,-0.03150,0.19698,0.00044))
df_bin <- s_curve_obj$s_curve_umap_model_obj$df_bin
edge_data <- s_curve_obj$s_curve_umap_model_tr_from_to_df
get_projection(projection = projection_df, proj_scale = 1,
highd_data = s_curve_noise_training, model_highd = df_bin,
tr_from_to_df = edge_data,
axis_param = list(limits = 1, axis_scaled = 1, axis_pos_x = -0.72,
axis_pos_y = -0.72,threshold = 0))
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
#> $projected_df
#> # A tibble: 3,750 × 3
#> proj1 proj2 ID
#> <dbl> <dbl> <int>
#> 1 -0.427 0.315 1
#> 2 -0.0334 0.221 2
#> 3 0.174 0.248 3
#> 4 -0.295 0.112 4
#> 5 -0.486 0.103 5
#> 6 0.0863 0.0694 6
#> 7 -0.292 0.154 7
#> 8 0.145 0.295 8
#> 9 -0.0326 0.201 9
#> 10 0.183 -0.0528 10
#> # ℹ 3,740 more rows
#>
#> $model_df
#> # A tibble: 313 × 10
#> from to x_from y_from x_to y_to proj1_from proj2_from proj1_to
#> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 0.107 -0.0169 0.189 -0.0169 0.0286 -0.114 0.0922
#> 2 4 5 0.148 0.0546 0.231 0.0546 0.0652 -0.0752 0.161
#> 3 4 13 0.148 0.0546 0.189 0.126 0.0652 -0.0752 0.111
#> 4 12 13 0.107 0.126 0.189 0.126 0.0275 -0.0125 0.111
#> 5 2 3 0.189 -0.0169 0.272 -0.0169 0.0922 -0.105 0.215
#> 6 12 22 0.107 0.126 0.148 0.198 0.0275 -0.0125 0.0543
#> 7 3 5 0.272 -0.0169 0.231 0.0546 0.215 -0.104 0.161
#> 8 13 23 0.189 0.126 0.231 0.198 0.111 -0.0146 0.172
#> 9 13 14 0.189 0.126 0.272 0.126 0.111 -0.0146 0.220
#> 10 5 14 0.231 0.0546 0.272 0.126 0.161 -0.0733 0.220
#> # ℹ 303 more rows
#> # ℹ 1 more variable: proj2_to <dbl>
#>
#> $axes
#> x1 y1 x2 y2 distance
#> x1 -0.72 -0.72 -0.7489217 -0.7375850 0.033848117
#> x2 -0.72 -0.72 -0.7248433 -0.6952850 0.025185097
#> x3 -0.72 -0.72 -0.6869050 -0.7234383 0.033273130
#> x4 -0.72 -0.72 -0.7199383 -0.7155700 0.004430429
#> x5 -0.72 -0.72 -0.7197817 -0.7252500 0.005254538
#> x6 -0.72 -0.72 -0.7283650 -0.6871700 0.033878933
#> x7 -0.72 -0.72 -0.7143817 -0.7199267 0.005618812
#>
#> $circle
#> c1 c2
#> 1 -0.5533333 -0.7200000
#> 2 -0.5547017 -0.6986871
#> 3 -0.5587842 -0.6777242
#> 4 -0.5655139 -0.6574555
#> 5 -0.5747802 -0.6382137
#> 6 -0.5864311 -0.6203149
#> 7 -0.6002751 -0.6040529
#> 8 -0.6160850 -0.5896948
#> 9 -0.6336012 -0.5774762
#> 10 -0.6525361 -0.5675979
#> 11 -0.6725787 -0.5602220
#> 12 -0.6934000 -0.5554697
#> 13 -0.7146581 -0.5534190
#> 14 -0.7360038 -0.5541035
#> 15 -0.7570868 -0.5575120
#> 16 -0.7775608 -0.5635886
#> 17 -0.7970897 -0.5722334
#> 18 -0.8153528 -0.5833046
#> 19 -0.8320501 -0.5966203
#> 20 -0.8469077 -0.6119619
#> 21 -0.8596814 -0.6290775
#> 22 -0.8701615 -0.6476860
#> 23 -0.8781760 -0.6674820
#> 24 -0.8835932 -0.6881402
#> 25 -0.8863242 -0.7093216
#> 26 -0.8863242 -0.7306784
#> 27 -0.8835932 -0.7518598
#> 28 -0.8781760 -0.7725180
#> 29 -0.8701615 -0.7923140
#> 30 -0.8596814 -0.8109225
#> 31 -0.8469077 -0.8280381
#> 32 -0.8320501 -0.8433797
#> 33 -0.8153528 -0.8566954
#> 34 -0.7970897 -0.8677666
#> 35 -0.7775608 -0.8764114
#> 36 -0.7570868 -0.8824880
#> 37 -0.7360038 -0.8858965
#> 38 -0.7146581 -0.8865810
#> 39 -0.6934000 -0.8845303
#> 40 -0.6725787 -0.8797780
#> 41 -0.6525361 -0.8724021
#> 42 -0.6336012 -0.8625238
#> 43 -0.6160850 -0.8503052
#> 44 -0.6002751 -0.8359471
#> 45 -0.5864311 -0.8196851
#> 46 -0.5747802 -0.8017863
#> 47 -0.5655139 -0.7825445
#> 48 -0.5587842 -0.7622758
#> 49 -0.5547017 -0.7413129
#> 50 -0.5533333 -0.7200000
#>