This function computes weights for hexagonal binning based on the average values of each bin and the distances from these averages.
Arguments
- nldr_df
A data frame containing 2D embeddings without a unique identifier column (ID).
- hb_object
A hexbin object containing the hexagonal binning information.
Examples
num_bins_x <- 4
shape_value <- 1.833091
hexbin_data_object <- extract_hexbin_centroids(nldr_df = s_curve_noise_umap,
num_bins = num_bins_x, shape_val = shape_value)
hexdf_data <- hexbin_data_object$hexdf_data
hb_obj <- hexbin_data_object$hb_data
compute_weights(nldr_df = s_curve_noise_umap |> dplyr::select(-ID), hb_object = hb_obj)
#> # A tibble: 75 × 6
#> hb_id avg_umap1 avg_umap2 UMAP1 UMAP2 distance
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 -2.71 -5.38 -2.73 -5.35 0.0332
#> 2 1 -2.71 -5.38 -2.69 -5.40 0.0332
#> 3 2 -2.21 -5.52 -2.31 -5.50 0.107
#> 4 2 -2.21 -5.52 -2.35 -5.68 0.209
#> 5 2 -2.21 -5.52 -2.50 -5.74 0.367
#> 6 2 -2.21 -5.52 -1.95 -5.34 0.321
#> 7 2 -2.21 -5.52 -1.81 -5.32 0.442
#> 8 2 -2.21 -5.52 -2.34 -5.54 0.130
#> 9 6 -2.82 -4.20 -2.81 -3.91 0.293
#> 10 6 -2.82 -4.20 -2.86 -4.28 0.0893
#> # ℹ 65 more rows