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calibrate_anim <- function(border, q, u, p, degree, xmax, ymax, data_matched){
res = NULL
hori_line = NULL
verti_line = NULL
lambda_vec = border[,1]
delta_vec = border[,2]
for (i in 1:length(lambda_vec)) {
# Obtain coefficients of observed coefficients
all_coef = EM_Algorithm(q, u, p, lambda_vec[i], delta_vec[i], data_matched, all_coef = TRUE)
coef_lambda = all_coef[[2]]
coef_delta = all_coef[[1]]
group = rep(i, length(coef_lambda))
points_added = data.frame(abs(coef_lambda), abs(coef_delta), group)
res = rbind(res, points_added)
hori_line = rbind(hori_line, c(lambda_vec[i], delta_vec[i], 0, delta_vec[i]))
verti_line = rbind(verti_line, c(lambda_vec[i], delta_vec[i], lambda_vec[i], 0))
}
res = cbind(res, rownames(res))
colnames(res) <- c('lambda', 'delta', 'curve', 'X_obs')
res$curve = as.factor(res$curve)
points_added_2 <- data.frame(lambda_vec, delta_vec, seq(1,length(lambda_vec)))
colnames(points_added_2) <- c('lambda','delta','curve')
points_added_2$curve = as.factor(points_added_2$curve)
hori_line <- as.data.frame(cbind(hori_line, seq(1,length(lambda_vec))))
colnames(hori_line) <- c('x1','y1', 'x2', 'y2', 'curve')
verti_line <- as.data.frame(cbind(verti_line, seq(1,length(lambda_vec))))
colnames(verti_line) <- c('x1','y1', 'x2', 'y2', 'curve')
sm = smooth.spline(border$lambda_vec, border$delta_vec, df = degree)
border$lambda_vec = sm$x
border$delta_vec = sm$y
p = ggplot(border, aes(lambda_vec, delta_vec)) + geom_line(size = 1) +
xlim(c(0, xmax)) + ylim(c(0, ymax)) +
xlab('lambda') + ylab('delta') +
geom_point(data = res, aes_string(x = 'lambda', y = 'delta', frame = 'curve', ids = 'X_obs'), size = 3, fontface = 'bold') +
geom_point(data = points_added_2, aes_string(x = 'lambda', y = 'delta', frame = 'curve'), color = 'red', shape = 8, size = 3)
p = ggplotly(p)
return(p)
}
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