Predict 2-D embeddings

Given a test dataset, the centroid coordinates of hexagonal bins in 2-D and high-dimensional space, predict the 2-D embeddings for each data point in the test dataset.

Usage

predict_emb(highd_data, model_2d, model_highd)

Arguments

highd_data

The tibble contains high-dimensional data and an unique identifier.

model_2d

Centroid coordinates of hexagonal bins in 2-D space.

model_highd

Centroid coordinates of hexagonal bins in high dimensions.

Value

A tibble contains predicted 2-D embeddings, ID in the test data, and predicted hexagonal IDs.

Examples

predict_emb(highd_data = scurve, model_highd = scurve_model_obj$model_highd,
model_2d = scurve_model_obj$model_2d)
#> # A tibble: 1,000 × 4
#>    pred_emb_1 pred_emb_2    ID pred_h
#>         <dbl>      <dbl> <int>  <int>
#>  1     0.275       0.823     1    200
#>  2     0.734       0.462     2    131
#>  3     0.734       0.462     3    131
#>  4     0.0251      0.968     4    227
#>  5     0.192       1.11      5    259
#>  6     0.442       0.968     6    232
#>  7     0.150       0.318     7     94
#>  8     0.859       0.679     8    177
#>  9     0.818       0.896     9    222
#> 10     0.901       0.318    10    103
#> # ℹ 990 more rows