Visualising How Nonlinear Dimension Reduction Warps Your Data

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Documentation for package ‘quollr’ version 0.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

assign_data	Assign data to hexagons
avg_highd_data	Create a dataframe with averaged high-dimensional data
calc_bins	Calculate the effective number of bins along x-axis and y-axis
calc_y_max	Compute maximum value of y for scaling
cal_2d_dist	Calculate 2D Euclidean distances between vertices
compute_aic	Compute the Akaike Information Criterion (AIC) for a given model.
compute_mean_density_hex	Compute mean density of hexagonal bins
compute_std_counts	Compute standardize counts in hexagons
extract_hexbin_centroids	Extract hexagonal bin centroids coordinates and the corresponding standardize counts.
find_lg_benchmark	Compute a benchmark value to remove long edges
find_low_dens_hex	Find low-density Hexagons
find_non_empty_bins	Find the number of bins required to achieve required number of non-empty bins.
find_pts	Find points in hexagonal bins
fit_highd_model	Construct the 2D model and lift into high-D
gen_centroids	Generate centroid coordinate
gen_edges	Generate edge information
gen_hex_coord	Generate hexagonal polygon coordinates
gen_scaled_data	Scaling the data
gen_summary	Generate evaluation metrics
GeomTrimesh	GeomTrimesh: A Custom ggplot2 Geom for Triangular Meshes
geom_trimesh	Create a trimesh plot
hex_binning	Hexagonal binning
predict_emb	Predict 2D embeddings
show_langevitour	Visualize the model overlaid on high-dimensional data
stat_trimesh	stat_trimesh Custom Stat for trimesh plot
s_curve_noise	S-curve dataset with noise dimensions
s_curve_noise_test	S-curve dataset with noise dimensions for test
s_curve_noise_training	S-curve dataset with noise dimensions for training
s_curve_noise_umap	UMAP embedding for S-curve dataset which with noise dimensions
s_curve_noise_umap_predict	Predicted UMAP embedding for S-curve dataset which with noise dimensions
s_curve_noise_umap_scaled	Scaled UMAP embedding for S-curve dataset which with noise dimensions
tri_bin_centroids	Triangulate bin centroids
vis_lg_mesh	Visualize triangular mesh with coloured long edges
vis_rmlg_mesh	Visualize triangular mesh after removing the long edges