Predict 2D embeddings — predict

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

Usage

predict_emb(test_data, df_bin_centroids, df_bin, type_NLDR)

Arguments

test_data: The test dataset containing high-dimensional coordinates and an unique identifier.
df_bin_centroids: Centroid coordinates of hexagonal bins in 2D space.
df_bin: Centroid coordinates of hexagonal bins in high dimensions.
type_NLDR: The type of non-linear dimensionality reduction (NLDR) used.

Value

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

Examples

df_bin_centroids <- s_curve_obj$s_curve_umap_model_distance_df$df_bin_centroids
#> Warning: Unknown or uninitialised column: `df_bin_centroids`.
df_bin <- s_curve_obj$s_curve_umap_model_distance_df$df_bin
#> Warning: Unknown or uninitialised column: `df_bin`.
predict_emb(test_data = s_curve_noise_training, df_bin_centroids = df_bin_centroids,
df_bin = df_bin, type_NLDR = "UMAP")
#> Error in UseMethod("select"): no applicable method for 'select' applied to an object of class "NULL"