fit_highd_model {quollr}

Construct the 2D model and lift into high-D

Description

This function fits a high-dimensional model using hexagonal bins and provides options to customize the modeling process, including the choice of bin centroids or bin means, removal of low-density hexagons, and averaging of high-dimensional data.

Usage

fit_highd_model(
  training_data,
  nldr_df_with_id,
  x,
  y,
  num_bins_x = NA,
  num_bins_y = NA,
  x_start = NA,
  y_start = NA,
  buffer_x = NA,
  buffer_y = NA,
  hex_size = NA,
  is_rm_lwd_hex = FALSE,
  benchmark_to_rm_lwd_hex = NA,
  col_start_2d,
  col_start_highd
)

Arguments

training_data

A data frame containing the training high-dimensional data.

nldr_df_with_id

A data frame containing 2D embeddings with a unique identifier.

x

The name of the column that contains first 2D embeddings component.

y

The name of the column that contains second 2D embeddings component.

num_bins_x

Number of bins along the x-axis.

num_bins_y

Number of bins along the y-axis.

x_start

Starting point along the x-axis for hexagonal binning.

y_start

Starting point along the y-axis for hexagonal binning.

buffer_x

The buffer size along the x-axis.

buffer_y

The buffer size along the y-axis.

hex_size

A numeric value that initializes the radius of the outer circle surrounding the hexagon.

is_rm_lwd_hex

Logical, indicating whether to remove low-density hexagons (default is FALSE).

benchmark_to_rm_lwd_hex

The benchmark value to remove low-density hexagons.

col_start_2d

The text prefix for columns in the 2D embedding data.

col_start_highd

The text prefix for columns in the high-dimensional data.

Value

A list containing the data frame with high-dimensional coordinates for 2D bin centroids (df_bin) and the data frame containing information about hexagonal bin centroids (df_bin_centroids) in 2D.

Examples

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")