# DAL ToolBox
# version 1.0.777

source("https://raw.githubusercontent.com/cefet-rj-dal/daltoolbox/main/jupyter.R")

#loading DAL
load_library("daltoolbox") 
load_github("cefet-rj-dal/tspredit")

data(sin_data)
ts <- ts_data(sin_data$y, 10)
ts_head(ts, 3)

library(ggplot2)
plot_ts(x=sin_data$x, y=sin_data$y) + theme(text = element_text(size=16))

samp <- ts_sample(ts, test_size = 5)
io_train <- ts_projection(samp$train)
io_test <- ts_projection(samp$test)

preproc <- ts_norm_gminmax()

model <- ts_knn(ts_norm_gminmax(), input_size=4, k=3)
model <- fit(model, x=io_train$input, y=io_train$output)

adjust <- predict(model, io_train$input)
adjust <- as.vector(adjust)
output <- as.vector(io_train$output)
ev_adjust <- evaluate(model, output, adjust)
ev_adjust$mse

prediction <- predict(model, x=io_test$input[1,], steps_ahead=5)
prediction <- as.vector(prediction)
output <- as.vector(io_test$output)
ev_test <- evaluate(model, output, prediction)
ev_test

yvalues <- c(io_train$output, io_test$output)
plot_ts_pred(y=yvalues, yadj=adjust, ypre=prediction) + theme(text = element_text(size=16))