Visualising How Nonlinear Dimension Reduction Warps Your Data

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Documentation for package ‘quollr’ version 0.3.7

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

Help Pages

assign_data	Assign data to hexagons
augment	Augment Data with Predictions and Error Metrics
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
extract_hexbin_centroids	Extract hexagonal bin centroids coordinates and the corresponding standardise counts.
extract_hexbin_mean	Extract hexagonal bin mean coordinates and the corresponding standardize counts.
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 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	Generate evaluation metrics
hex_binning	Hexagonal binning
plot_proj	Plot Projected Data with Axes and Circles
plot_rmse_layouts	Arrange RMSE plot and 2-D layouts
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