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Make curves smoooooooth

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Jonathan Berrisch
2025-05-24 00:06:24 +02:00
parent c96022c7b2
commit 5dec1e78ff
2 changed files with 25 additions and 15 deletions
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2
25_07_phd_defense/app.qmd
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@@ -206,7 +206,7 @@ chart = {
const line = d3.line() const line = d3.line()
.x(d => x(d.x)) .x(d => x(d.x))
.y(d => y(d.y)) .y(d => y(d.y))
.curve(d3.curveLinear); .curve(d3.curveBasis);
// Group to contain the basis function lines // Group to contain the basis function lines
const linesGroup = g.append("g") const linesGroup = g.append("g")

22
25_07_phd_defense/assets/make_knots_data.R
View File

@@ -8,7 +8,7 @@ library(readr)
# Creating faceted plots for different knot values and mu values # 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 # Create a function to generate the data for a given number of knots and mu value
generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tailw_value, deg_value) { generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tailw_value, deg_value) {
grid <- seq(from = 0.01, to = 0.99, length.out = 99) grid <- seq(from = 0.01, to = 0.99, length.out = 50)
# Use provided degree # Use provided degree
B <- profoc:::make_basis_matrix(grid, B <- profoc:::make_basis_matrix(grid,
profoc::make_knots( profoc::make_knots(
@@ -21,9 +21,9 @@ generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tail
), ),
deg = deg_value deg = deg_value
) )
B_mat <- round(as.matrix(B), 2) B_mat <- round(as.matrix(B), 3)
df <- as.data.frame(B_mat) df <- as.data.frame(B_mat)
df$x <- round(grid, 2) df$x <- grid
df_long <- pivot_longer(df, df_long <- pivot_longer(df,
cols = -x, cols = -x,
names_to = "b", names_to = "b",
@@ -39,7 +39,6 @@ generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tail
} }
# Generate data for each combination of knot, mu, sig, nonc, tailw, and deg # Generate data for each combination of knot, mu, sig, nonc, tailw, and deg
knot_values <- c(10)
mu_values <- seq(0.1, 0.9, by = 0.2) mu_values <- seq(0.1, 0.9, by = 0.2)
sig_values <- 2^(-2:2) sig_values <- 2^(-2:2)
nonc_values <- c(-4, -2, 0, 2, 4) nonc_values <- c(-4, -2, 0, 2, 4)
@@ -50,7 +49,6 @@ all_data <- list()
counter <- 1 counter <- 1
# Nested loops to cover all parameter combinations # Nested loops to cover all parameter combinations
for (k in knot_values) {
print(paste("Processing knots:", k)) print(paste("Processing knots:", k))
for (m in mu_values) { for (m in mu_values) {
print(paste("Processing mu:", m)) print(paste("Processing mu:", m))
@@ -63,7 +61,6 @@ for (k in knot_values) {
} }
} }
} }
}
# Combine all data frames # Combine all data frames
all_data <- bind_rows(all_data) all_data <- bind_rows(all_data)
@@ -71,3 +68,16 @@ all_data <- bind_rows(all_data)
write_csv(all_data, "25_07_phd_defense/assets/mcrps_learning/basis_functions.csv") write_csv(all_data, "25_07_phd_defense/assets/mcrps_learning/basis_functions.csv")
# %% # %%
all_data %>%
filter(mu == 0.1) %>%
filter(sig == 0.25) %>%
filter(nonc == -4) %>%
filter(tailw == 0.25) %>%
ggplot(aes(x = x, y = y, col = b)) +
geom_line(size = 2) +
labs(
title = "Basis Functions for Different Knot Values",
x = "x",
y = "y"
) +
theme_minimal()