show_langevitour {quollr} | R Documentation |
Visualize the model overlaid on high-dimensional data
Description
This function generates a LangeviTour visualization based on different conditions and input parameters.
Usage
show_langevitour(
df,
df_b,
df_b_with_center_data,
benchmark_value = NA,
distance_df,
distance_col,
use_default_benchmark_val = FALSE,
col_start
)
Arguments
df |
A data frame containing the high-dimensional data. |
df_b |
A data frame containing the high-dimensional coordinates of bin centroids. |
df_b_with_center_data |
The dataset with hexbin centroids. |
benchmark_value |
The benchmark value used to remove long edges (optional). |
distance_df |
The distance dataframe. |
distance_col |
The name of the distance column. |
use_default_benchmark_val |
Logical, indicating whether to use default benchmark value to remove long edges (default is FALSE). |
col_start |
The text that begin the column name of the high-dimensional data. |
Value
A langevitour object with the model and the high-dimensional data.
Examples
num_bins_list <- calc_bins(data = s_curve_noise_umap_scaled, x = "UMAP1",
y = "UMAP2", hex_size = NA, buffer_x = NA, buffer_y = NA)
num_bins_x <- num_bins_list$num_x
num_bins_y <- num_bins_list$num_y
hb_obj <- hex_binning(data = s_curve_noise_umap_scaled,
x = "UMAP1", y = "UMAP2", num_bins_x = num_bins_x,
num_bins_y = num_bins_y, x_start = NA, y_start = NA, buffer_x = NA,
buffer_y = NA, hex_size = NA, col_start = "UMAP")
all_centroids_df <- as.data.frame(do.call(cbind, hb_obj$centroids))
counts_df <- as.data.frame(do.call(cbind, hb_obj$std_cts))
umap_data_with_hb_id <- as.data.frame(do.call(cbind, hb_obj$data_hb_id))
df_all <- dplyr::bind_cols(s_curve_noise_training |> dplyr::select(-ID), umap_data_with_hb_id)
df_bin <- avg_highd_data(data = df_all, col_start = "x")
df_bin_centroids <- extract_hexbin_centroids(centroids_df = all_centroids_df,
counts_df = counts_df)
tr1_object <- tri_bin_centroids(hex_df = df_bin_centroids, x = "c_x", y = "c_y")
tr_from_to_df <- gen_edges(tri_object = tr1_object)
distance_df <- cal_2d_dist(tr_coord_df = tr_from_to_df, start_x = "x_from",
start_y = "y_from", end_x = "x_to", end_y = "y_to",
select_vars = c("from", "to", "distance"))
show_langevitour(df = df_all, df_b = df_bin, df_b_with_center_data = df_bin_centroids,
benchmark_value = 0.75, distance = distance_df, distance_col = "distance",
use_default_benchmark_val = FALSE, col_start = "x")
[Package quollr version 0.1.1 Index]