Function reference • quollr

All functions

GeomTrimesh: GeomTrimesh: A Custom ggplot2 Geom for Triangular Meshes

avg_highD_data(): Average High-Dimensional Data

cal_2d_dist(): Calculate 2D Distances Between Points

calculate_effective_shape_value(): Calculate effective shape parameter value

calculate_effective_x_bins(): Calculate the effective number of bins along x-axis

colour_long_edges(): Color Long Edges

compute_aic(): Compute the Akaike Information Criterion (AIC) for a given model.

compute_mean_density_hex(): Compute Mean Density of Hexagonal Bins

compute_weights(): Compute Weights for Hexagonal Binning

extract_coord_of_shifted_hex_grid(): Extract Coordinates of Shifted Hexagonal Grid

extract_hexbin_centroids(): Extract hexagonal bin centroids and related information from non-linear dimensionality reduction data.

extract_hexbin_mean(): Extract hexagonal bin mean and related information from non-linear dimensionality reduction data.

find_benchmark_value(): Find Benchmark Value To Remove Long Edges

find_low_density_hexagons(): Find Low-Density Hexagons

find_non_empty_bins(): Find the Number of Non-Empty Bins Required

find_pts_in_hexbins(): Find Points in Hexagonal Bins

fit_high_d_model(): Construct the 2D model and lift into high-D

full_hex_grid(): Generate Hexagonal Coordinates

generate_edge_info(): Generate Edge Information

generate_eval_df(): Generate Evaluation Data Frame

generate_full_grid_centroids(): Generate Full Grid Centroids

generate_full_grid_info(): Generate Full Grid Information Data Frame

geom_trimesh(): Create a trimesh plot

map_hexbin_id(): Map Hexagon IDs to Centroids in the Full Grid

map_polygon_id(): Map Polygon ID to Hexagon Coordinates

predict_2d_embeddings(): Predict 2D Embeddings

predict_hex_id(): Predict Hexagonal IDs

remove_long_edges(): Remove Long Edges from a Triangular Mesh 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

show_langevitour(): Show LangeviTour Visualization

stat_trimesh(): stat_trimesh Custom Stat for trimesh plot

triangulate_bin_centroids(): Triangulate Bin Centroids

weighted_highD_data(): Compute Weighted Mean for High-Dimensional Data