predict_emb {quollr}

Predict 2D embeddings

Description

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

Examples

model <- fit_highd_model(training_data = s_curve_noise_training, x = "UMAP1", y = "UMAP2",
nldr_df_with_id = s_curve_noise_umap_scaled, col_start_2d = "UMAP", col_start_highd = "x")
df_bin_centroids <- model$df_bin_centroids
df_bin <- model$df_bin
predict_emb(test_data = s_curve_noise_training, df_bin_centroids = df_bin_centroids,
df_bin = df_bin, type_NLDR = "UMAP")