Create a dataframe with averaged high-dimensional data and high-dimensional data, non-linear dimension reduction data, model error data

This function combine the average values of high-dimensional data within each hexagonal bin and high-dimensional data, non-linear dimension reduction data, model error data.

Usage

comb_all_data_model_error(
  highd_data,
  nldr_data,
  model_highd,
  model_2d,
  error_df
)

Arguments

highd_data

A tibble that contains the high-dimensional data.

nldr_data

A tibble that contains the non-linear dimension reduction data.

model_highd

A tibble that contains the high-dimensional coordinates of bin centroids.

model_2d

The dataset with hexagonal bin centroids.

error_df

A tibble that high-dimesional model error.

Value

A tibble with the average values of the high-dimensional data within each hexagonal bin and high-dimensional data, non-linear dimension reduction data, model error.

Examples

df_bin_centroids <- s_curve_obj$s_curve_umap_model_obj$df_bin_centroids
df_bin <- s_curve_obj$s_curve_umap_model_obj$df_bin
model_error <- augment(model_2d = df_bin_centroids, model_highd = df_bin,
highd_data = s_curve_noise_training)
comb_all_data_model_error(highd_data = s_curve_noise_training, nldr_data = s_curve_obj$s_curve_umap_scaled_obj$scaled_nldr,
model_highd = df_bin, model_2d = df_bin_centroids, error_df = model_error)
#> # A tibble: 3,875 × 12
#>        x1     x2    x3        x4        x5       x6         x7 type   emb1  emb2
#>     <dbl>  <dbl> <dbl>     <dbl>     <dbl>    <dbl>      <dbl> <chr> <dbl> <dbl>
#>  1  0.999 0.0659  1.03 -0.00334   0.00122   0.0155  -0.00137   model    NA    NA
#>  2  0.943 0.0996  1.31  0.00668  -0.00213   0.0333  -0.00127   model    NA    NA
#>  3  0.701 0.0554  1.70  0.00128  -0.000620 -0.0148  -0.00265   model    NA    NA
#>  4  0.967 0.354   1.23 -0.00118   0.00123  -0.00145 -0.000612  model    NA    NA
#>  5  0.815 0.311   1.57 -0.000537 -0.000332 -0.00496  0.00180   model    NA    NA
#>  6  0.519 0.263   1.85  0.000251  0.000248 -0.0158   0.0000603 model    NA    NA
#>  7  0.111 0.274   1.98 -0.000734 -0.00238   0.00918 -0.000181  model    NA    NA
#>  8 -0.307 0.215   1.94 -0.00156  -0.000130 -0.0321   0.0000293 model    NA    NA
#>  9 -0.644 0.217   1.76  0.00175  -0.00177   0.0107  -0.000382  model    NA    NA
#> 10 -0.857 0.164   1.50  0.00213   0.00136  -0.00868  0.000856  model    NA    NA
#> # ℹ 3,865 more rows
#> # ℹ 2 more variables: sqrt_row_wise_total_error <dbl>, density <dbl>