//print tree (for testing wether we make is correctly)
private void PrintTheTree_helper()
{
if (this.root.GetChildsNode().Count == 0)
{
this.path.ForEach(Console.Write);
Console.WriteLine();
AugmentedTrie.total_printing_row++; // counting how many row were printed
}
else
{
foreach (TreeNode node_child in this.root.GetChildsNode())
{
List <char> path_child = new List <char>(this.path);
path_child.Add(node_child.GetKeyNode());
AugmentedTrie tree_child = new AugmentedTrie(node_child, path_child);
tree_child.PrintTheTree_helper();
}
}
}
public void PrintTheTree_WithData()
{
if (this.root.GetChildsNode().Count == 0)
{
this.path.ForEach(Console.Write);
Console.Write("\t" + "data:");
foreach (int index_data in this.root.GetDataNode())
{
Console.Write(index_data + " ");
}
Console.WriteLine();
}
else
{
foreach (TreeNode node_child in this.root.GetChildsNode())
{
List <char> path_child = new List <char>(this.path);
path_child.Add(node_child.GetKeyNode());
AugmentedTrie tree_child = new AugmentedTrie(node_child, path_child);
tree_child.PrintTheTree_WithData();
}
}
}
}//end OuterArrangement
// inner loop
private static List <int> InnerArrangement(Dictionary <int, string> total_table, Dictionary <string, int> count_table, AugmentedTrie tree, string word)
{
TreeNode the_leaf = tree.FindtheLeaf(word);
List <int> inner_list = new List <int>(the_leaf.GetDataNode());//go through the data first
bool[] over_arr = new bool[total_table.Count];
for (int i = 0; i < total_table.Count; i++)
{
over_arr[i] = false;
}
foreach (int element in inner_list)
{
over_arr[element] = true;
}
List <int> inner_random = new List <int>();
for (int i = 0; i < total_table.Count; i++)
{
if (over_arr[i] == false)
{
inner_random.Add(i);
}
}
//make random_inner randomly
inner_random.Shuffle();
inner_list = inner_list.Concat(inner_random).ToList();
return(inner_list);
}//end innerArrangement
static private Random random_obj = new Random();// helping for making a random order
// Make the tree and tables function
static public void MakeTree_And_Table_Function(List <double> data, int N_LENGTH, out AugmentedTrie tree, out Dictionary <string, int> count_table, out Dictionary <int, string> total_table)
{
double min = data.Min();
double max = data.Max();
count_table = new Dictionary <string, int>();
total_table = new Dictionary <int, string>();
List <double> C_n;
List <double> C_w = new List <double>();// w dimension
//convert time series C of length into a w dimensional, then transform to SAX word:
for (int start_point_subtimeseries = 0; start_point_subtimeseries + N_LENGTH - 1 <= data.Count - 1; start_point_subtimeseries++) //go through timeseries by the window "N_LENGTH"
{
C_n = data.GetRange(start_point_subtimeseries, N_LENGTH); //get the sub_timeseries
C_w.Clear(); // reset C_w
string s = String.Empty; //initialize the SAX word
//if N_LENGTH % Constants.W_DIMENSION != 0, then we do PAA as the formala (quite complex and take time):
if (N_LENGTH % Constants.W_DIMENSION != 0)
{
for (int i = 0; i < Constants.W_DIMENSION; i++)
{
C_w.Add(0); //set initial value for C_w
}
for (int i = 0; i < N_LENGTH * Constants.W_DIMENSION; i++)
{
C_w[i / N_LENGTH] += C_n[i / Constants.W_DIMENSION];
}
for (int i = 0; i < Constants.W_DIMENSION; i++)
{
C_w[i] = MathFunctions.MinMax_Normalization(C_w[i], min, max);
//Convert c_i to SAX
if (C_w[i] <= Constants.GAUSS_1)
{
s += "a";
}
else if (C_w[i] >= Constants.GAUSS_2)
{
s += "c";
}
else
{
s += "b";
}
}
}
else //else, we can simple split it into the same size, this help to reduce the execution time*/
{
double c_i;
int from_index, to_index;
//Calculate C_w
for (int start_point_w = 0; start_point_w < Constants.W_DIMENSION; start_point_w++)
{
from_index = (N_LENGTH / Constants.W_DIMENSION) * start_point_w;
to_index = (N_LENGTH / Constants.W_DIMENSION) * (start_point_w + 1) - 1;
c_i = 0;
for (int i = from_index; i <= to_index; i++)
{
c_i += C_n.ElementAt(i);
}
c_i = c_i * (Constants.W_DIMENSION / (double)(N_LENGTH));
c_i = MathFunctions.MinMax_Normalization(c_i, min, max);
//Convert c_i to SAX
if (c_i <= Constants.GAUSS_1)
{
s += "a";
}
else if (c_i >= Constants.GAUSS_2)
{
s += "c";
}
else
{
s += "b";
}
C_w.Add(c_i);
} //end for loop-calc SAX word
} //end else
total_table.Add(start_point_subtimeseries, s);
if (count_table.ContainsKey(s))
{
count_table[s]++;//if it did have, just plus 1 to 'count_table'
}
else
{
count_table.Add(s, 1);// else, we make a new one
}
}// end for _ go through time series by the window
//Making the root node:
TreeNode root = new TreeNode('R');
//init the path (to print the tree later)
List <char> path = new List <char>();
// Making the augmented tree:
tree = new AugmentedTrie(root, path);
tree.CreateTheAugmentedTrie();
// appending the indice to the tree.
foreach (KeyValuePair <int, string> pair in total_table)
{
tree.AddTheDataToLeaf(pair.Value, pair.Key);
}
} //end MakeTree_AND_Table function
