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      0.234      0.896     1    215
#>  2      0.692      0.534     2    145
#>  3      0.776      0.390     3    116
#>  4      0.192      0.968     4    229
#>  5      0.192      0.968     5    229
#>  6      0.567      1.04      6    249
#>  7      0.192      0.245     7     79
#>  8      0.984      0.607     8    164
#>  9      0.776      0.823     9    206
#> 10      0.943      0.390    10    118
#> # ℹ 990 more rows