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menu.py
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import csv
import random
import string
import range_tree as rt
import hospitals_rt as hos
#### Functions ####
#gia tin print tree: pre-order traversal
def pre_order(root, string=""):
if root:
print(string + str(root.coords) + "|Name:" + str(root.name))
pre_order(root.left, "\t" + string + "-left-")
pre_order(root.right, "\t" + string + "-right-")
#gia tin range search: print result
def print_nodes(nodes_list):
for node in nodes_list:
print(str(node.coords) + "\t|\tName:" + str(node.name))
#euclidean distance variation for kNN - xwris riza
def euclidean_dist(pointa, pointb):
return sum((pointa[i] - pointb[i]) ** 2 for i in range(rt.DIMENSIONS))
#kNN
#geitones (+1 gia ton eauto tou), to node, tou opoiou psaxnw tous geitones
#ti riza tou dentrou
def knn_algorithm(k, point, root):
#tyxaia arxikopoihsh toy [[x_min, x_max],[y_min, y_max]] gia range search
my_range = [[point.coords[0]-3, point.coords[0]+3],[point.coords[1]-3, point.coords[1]+3]]
#range search sto arxiko diastima gyrw apo to simeio endiaferontos
temp_nodes = rt.range_search(root, my_range)
#ypologizoume tis apostaseis kathe komvou pou epestrepse to range search
#apo to simeio endiaferontos kai sortaroume
temp_distances = [[euclidean_dist(point.coords, node.coords), node.name, node.coords] for node in temp_nodes]
temp_distances = sorted(temp_distances)
#prosarmozoume to diastima wste na psaxnoume aristera apo to x_min,y_min
#kai deksia apo to x_max, y_max kai epanalamvanoume mexri na vroume k geitones
while len(temp_nodes) < k:
#pairnoume to max giati mporei na exoume vrei mono ton eauto tou
#opote h apostash tha einai 0
my_range[0][1] += max(temp_distances[int(len(temp_distances)/2)][0],1)
my_range[1][1] += max(temp_distances[int(len(temp_distances)/2)][0],1)
my_range[0][0] -= max(temp_distances[int(len(temp_distances)/2)][0],1)
my_range[1][0] -= max(temp_distances[int(len(temp_distances)/2)][0],1)
temp_nodes = rt.range_search(root, my_range)
temp_distances = [[euclidean_dist(point.coords, node.coords), node.name, node.coords] for node in temp_nodes]
temp_distances = sorted(temp_distances)
return temp_distances[0:k]
#### Menu ####
#dialegoume real h simulated data
choose_data = int(input("0 - Real Data\n1 - Simulated Data\n-> "))
my_nodes = []
nodes_counter = 0
if choose_data == 0:
filename = 'data.csv'
#diavazoume to arxeio kai dimiourgoume kateytheian node objects
with open(filename, mode='r', encoding="utf-8") as csv_file:
csv_reader = csv.reader(csv_file, delimiter=';')
for row in csv_reader:
my_nodes.append(rt.Node([float(row[0].replace(',','.')), float(row[1].replace(',','.'))], row[2]))
nodes_counter += 1
print('Number of Nodes: ' + str(nodes_counter))
#gia na mporoume na kanoume search me to name ston knn
with open(filename, mode='r', encoding="utf-8") as csv_file:
csv_reader = csv.reader(csv_file, delimiter=';')
hosp = hos.put_into_list(csv_file)
else:
#tyxaia string gia ta onomata twn simulated data
string_len = 5
chars = string.ascii_lowercase
for j in range(0,int(input("Give the number of Nodes you want to create: "))):
coords = []
name = ''.join((random.sample(chars, string_len)))
for k in range(0, rt.DIMENSIONS):
coords.append(random.randint(0,10))
nodes_counter += 1
my_nodes.append(rt.Node(coords, name))
#sortaroume tis syntetagmenes twn komvwn kai ftiaxnoume to dentro
sorted_nodes = sorted(my_nodes, key=lambda l:(l.coords[0], l.coords[1]))
my_root, _ = rt.create_range_tree(sorted_nodes)
#menu gia tis diadikasies tou dentrou
print("\nMENU")
print("0 - Print Tree")
print("1 - Range Search")
print("2 - Insert Node")
print("3 - Delete Node")
print("4 - Update Node")
print("5 - kNN")
print("-1 - Exit Program\n")
choice = int(input())
while choice != -1:
# Print Tree
if choice == 0:
print('-----------------------')
pre_order(my_root)
print('-----------------------')
# Range Search
elif choice == 1:
my_range = []
for d in range(rt.DIMENSIONS):
d_range = []
print("Give min coordinate for dimension " + str(d))
d_range.append(float(input()))
print("Give max coordinate for dimension " + str(d))
d_range.append(float(input()))
my_range.append(d_range)
print('-----------------------')
res_list = rt.range_search(my_root, my_range)
if len(res_list) == 0:
print('-----------------------')
print("Not Found!")
print('-----------------------')
else:
print('-----------------------')
print('Nodes found (' + str(len(res_list)) + ')')
print_nodes(res_list)
print('-----------------------')
# Insert
elif choice == 2:
coords = []
for d in range(rt.DIMENSIONS):
print("Give coordinate for dimension " + str(d))
coords.append(float(input()))
name = input("Give your Hospital's name: ")
print('-----------------------')
my_root = rt.insert(my_root, rt.Node(coords, name))
# Delete
elif choice == 3:
coords = []
for d in range(rt.DIMENSIONS):
print("Give coordinate for dimension " + str(d))
coords.append(float(input()))
print('-----------------------')
my_root = rt.delete(my_root, coords)
# Update
elif choice == 4:
coords = []
new_coords = []
for d in range (rt.DIMENSIONS):
print("Give old coordinate for dimension " + str(d))
coords.append(float(input()))
print('-----------------------')
for d in range (rt.DIMENSIONS):
print("Give new coordinate for dimension " + str(d))
new_coords.append(float(input()))
print('-----------------------')
my_root = rt.update(my_root, coords, new_coords)
#kNN
elif choice == 5:
#real data
if choose_data == 0:
name = input("Give your Hospital's name: ")
#k+1 giati perilamvanei kai ton eauto tou, distance = 0
k = int(input("How many nearby hospitals do you want: ")) + 1
pcoords = [0,0]
flag = 0
#elegxoume an uparxei
for i in range(len(hosp)):
if hosp[i].gaz_name == name:
pcoords[0] = hosp[i].latitude
pcoords[1] = hosp[i].longitude
flag = 1
if flag != 1:
print("Hospital doesn't exist.")
else:
#theloume ton komvo pou zitithike san node object
res = rt.range_search(my_root, [[pcoords[0], pcoords[0]],[pcoords[1], pcoords[1]]])
print('-----------------------')
neighboring_hosp = knn_algorithm(k, res[0], my_root)
for i in range(len(neighboring_hosp)):
print("|Distance:" + str(neighboring_hosp[i][0]) + "\t|\tName:" + str(neighboring_hosp[i][1]) + "\t|\tCoordinates:" + str(neighboring_hosp[i][2]))
print("\n")
print('-----------------------')
else:
pcoords = []
for d in range(rt.DIMENSIONS):
print("Give coordinate for dimension " + str(d))
pcoords.append(int(input()))
k = int(input("How many nearby nodes do you want: ")) + 1 #k+1 giati perilamvanei kai ton eauto tou, distance = 0
if k > nodes_counter/2: #node counter += 1 gia kathe coord
print("Tree nodes = ", int(nodes_counter/2))
k = int(nodes_counter/2)
#theloume ton komvo pou zitithike san node object
res = rt.search(my_root, pcoords)
print('-----------------------')
k_neighbors = knn_algorithm(k, res[0], my_root)
for i in range(len(k_neighbors)):
print("|Distance:" + str(k_neighbors[i][0]) + "\t|\tName:" + str(k_neighbors[i][1]) + "\t|\tCoordinates:" + str(k_neighbors[i][2]))
print('-----------------------')
choice = int(input())