# Harbinger Package
# version 1.0.777

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

#loading Harbinger
load_library("daltoolbox") 
load_library("harbinger") 

#loading the example database
data(examples_anomalies)

#Using the simple time series
dataset <- examples_anomalies$simple
head(dataset)

#ploting the time series
plot_ts(x = 1:length(dataset$serie), y = dataset$serie)

# establishing conv1d method 
  model <- hanr_ml(ts_conv1d(ts_norm_gminmax(), input_size=4, epochs=10000))

# fitting the model
  model <- fit(model, dataset$serie)

# making detections
  detection <- detect(model, dataset$serie)

# filtering detected events
  print(detection |> dplyr::filter(event==TRUE))

# evaluating the detections
  evaluation <- evaluate(model, detection$event, dataset$event)
  print(evaluation$confMatrix)

# ploting the results
  grf <- har_plot(model, dataset$serie, detection, dataset$event)
  plot(grf)