Heuristic.py

import copy


def find_minimum_domain(node):
    minimum = 2
    minimum_index = ()
    dimension = len(node.board)
    for i in range(dimension):
        for j in range(dimension):
            if node.board[i][j] == '-' and len(node.variables_domain[i][j]) <= minimum:
                minimum = len(node.variables_domain[i][j])
                minimum_index = (i, j)
    # print("MRV => index ", minimum_index)
    return minimum_index


# assigns a value to the selected variable and delete that value from variable's domain
# it returns 0 first and then 1 if zero were removed from domain
def assign_value(node):
    x, y = node.assigned_variable
    if len(node.variables_domain[x][y]) == 0:
        # it means it has no values left
        return '-'
    else:
        new_value = node.variables_domain[x][y].pop()
        # print(node.variables_domain[x][y])
        # node.variables_domain[x][y] = new_value
        return new_value


def MRV(node, mode):
    if mode == 'samevar':
        # it means we had conflict in constraint so we need to choose another value for chosen variable
        pass
    else:
        # return variable with the smallest domain
        node.assigned_variable = find_minimum_domain(node)
        if not node.assigned_variable:      # when backtrack and node parent variables is empty
            return False

    # assign a value to this variable
    node.assigned_value = assign_value(node)
    # x, y = node.assigned_variable
    # node.board[x][y] = node.assigned_value
    # if node.assigned_value == "0":
    #     node.variables_domain[x][y] = ["1"]
    # elif node.assigned_value == "1":
    #     node.variables_domain[x][y] == ["0"]
    # else:
    #     print('backtracking')
    #     node.variables_domain[x][y] == []

    # return changed node
    if node.assigned_value != '-':
        return True
    else:
        return False