# %%
library(profoc)
library(ggplot2)
library(tidyr)
library(dplyr)
library(readr)

# Creating faceted plots for different knot values and mu values
# Create a function to generate the data for a given number of knots and mu value
generate_basis_data <- function(num_knots, mu_value) {
  grid <- seq(0, 1, length.out = 20)
  B <- profoc:::make_basis_matrix(grid,
    profoc::make_knots(
      n = num_knots,
      mu = mu_value,
      sig = 1,
      nonc = 0,
      deg = 1
    ),
    deg = 3
  )
  df <- as.data.frame(as.matrix(B))
  df$x <- grid
  df_long <- pivot_longer(df,
    cols = -x,
    names_to = "b",
    values_to = "y"
  )
  df_long$knots <- num_knots # Store knot count as numeric
  df_long$mu <- mu_value # Add mu parameter information
  return(df_long)
}

# Generate data for each combination of knot value and mu value
knot_values <- 5:10
mu_values <- seq(0.1, 0.9, by = 0.1)

# Create an empty list to store all combinations
all_data <- list()
counter <- 1

# Generate data for all combinations
for (k in knot_values) {
  for (m in mu_values) {
    all_data[[counter]] <- generate_basis_data(k, m)
    counter <- counter + 1
  }
}

# Combine all data frames
all_data <- bind_rows(all_data)

write_csv(all_data, "basis_functions.csv")