# Visualising How Nonlinear Dimension Reduction Warps Your Data

## Documentation for package ‘quollr’ version 1.0.6

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

assign_data | Assign data to hexagons
augment | S3 generic for augment
augment.highd_vis_model | Augment Data with Predictions and Error Metrics for NLDR Models
avg_highd_data | Create a tibble with averaged high-dimensional data
calc_2d_dist | Calculate 2-D Euclidean distances between vertices
calc_bins_y | Calculate the effective number of bins along x-axis and y-axis
comb_all_data_model | Create a tibble with averaged high-dimensional data and high-dimensional data, non-linear dimension reduction data
comb_all_data_model_error | Create a tibble with averaged high-dimensional data and high-dimensional data, non-linear dimension reduction data, model error data
comb_data_model | Create a tibble with averaged high-dimensional data and high-dimensional data
compute_mean_density_hex | Compute mean density of hexagonal bins
compute_std_counts | Compute standardise counts in hexagons
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.
fit_highd_model | Construct the 2-D model and lift into high-dimensions
gen_axes | Generate Axes for Projection
gen_centroids | Generate centroid coordinate
gen_design | Generate a design to layout 2-D representations
gen_diffbin1_errors | Generate erros and MSE for different bin widths
gen_edges | Generate edge information
gen_hex_coord | Generate hexagonal polygon coordinates
gen_scaled_data | Scaling the NLDR data
GeomHexgrid | GeomHexgrid: A Custom ggplot2 Geom for Hexagonal Grid
GeomTrimesh | GeomTrimesh: A Custom ggplot2 Geom for Triangular Meshes
geom_hexgrid | Create a hexgrid plot
geom_trimesh | Create a trimesh plot
get_projection | Compute Projection for High-Dimensional Data
glance | S3 generic for glance
glance.highd_vis_model | Generate evaluation metrics for a hex_model object
group_hex_pts | Grouped points in each hexagon
hex_binning | Hexagonal binning
merge_hexbin_centroids | Extract hexagonal bin centroids coordinates and the corresponding standardise counts.
merge_hexbin_mean | Extract hexagonal bin mean coordinates and the corresponding standardize counts.
plot_hbe_layouts | Arrange HBE plot and 2-D layouts
plot_proj | Plot Projected Data with Axes and Circles
predict_emb | Predict 2-D embeddings
quad | Solve Quadratic Equation for Positive Real Roots
scurve | S-curve dataset with noise dimensions
scurve_model_obj | Object for S-curve dataset
scurve_plts | List of plots
scurve_umap | UMAP embedding for 'scurve' with n_neighbors = 15 and min_dist = 0.1
scurve_umap2 | UMAP embedding for 'scurve' with n_neighbors = 10 and min_dist = 0.4
scurve_umap3 | UMAP embedding for 'scurve' with n_neighbors = 62 and min_dist = 0.1
scurve_umap4 | UMAP embedding for 'scurve' with n_neighbors = 30 and min_dist = 0.5
scurve_umap_predict | Predicted UMAP embedding for 'scurve' data
scurve_umap_rmse | Summary with different number of bins for 'scurve_umap'
scurve_umap_rmse2 | Summary with different number of bins for 'scurve_umap2'
scurve_umap_rmse3 | Summary with different number of bins for 'scurve_umap3'
scurve_umap_rmse4 | Summary with different number of bins for 'scurve_umap4'
show_error_link_plots | Visualise the model overlaid on high-dimensional data along with 2-D wireframe model and error.
show_langevitour | Visualise the model overlaid on high-dimensional data
show_link_plots | Visualise the model overlaid on high-dimensional data along with 2-D wireframe model.
stat_hexgrid | stat_hexgrid Custom Stat for hexagonal grid plot
stat_trimesh | stat_trimesh Custom Stat for trimesh plot
tri_bin_centroids | Triangulate bin centroids
update_trimesh_index | Update from and to values in trimesh data