# People.py

from gpanel import *
from operator import itemgetter

datafile = "swisspeople.dat"
bgImage = "swissmap.png"
k = 5 # number of nearest neighbors
fLong = 60 # scale factor for longitude (km / degree)
fLatt = 80 # scale factor for lattitue (km / degree)

def euklidian(pt1, pt2):
    return math.sqrt(fLong * (pt1[0] - pt2[0]) * fLong * (pt1[0] - pt2[0]) + \
                     fLatt * (pt1[1] - pt2[1]) * fLatt * (pt1[1] - pt2[1]))
                     
def onMousePressed(x, y):
    global color
    global cx, cy, xorMode
    # erase 
    if xorMode:
        pos(cx, cy)
        fillCircle(0.03)  # erase test person
        for pair in pairs: # erase proximity lines
            line(pair[0], pair[1], pair[2], pair[3])
        setPaintMode()
        xorMode = False
        setColor(color)
    if isLeftMouseButton():
        if x < 5.34 and y > 47.24: # color choice
            if y < 47.44:
                color = "Blue"
            elif y > 47.44 and y < 47.66:
                color = "Green"
            elif y > 47.66:
                color = "Red"
            setColor(color)
            title(color + " color selected")
        else: # draw people
            pos(x, y)    
            fillCircle(0.05)
            saveSample(x, y, color)
    else: # right button -> make prediction
        setXORMode("white")
        xorMode = True
        pos(x, y)
        cx = x
        cy = y    
        setColor("lightgreen")
        fillCircle(0.03) # show test person
        predict(x, y)

def loadData(fileName):
    try:    
        fData = open(fileName, 'r')
    except:
        return []
    out = []
    for line in fData:
        line = line[:-1]  # remove \n
        li = [i for i in line.split(";")]
        out.append(li)
    fData.close()
    return out

def predict(x0, y0):
    global pairs
    X = loadData(datafile)
    if len(X) < k:  # not enough people for prediction
        return
    distances = []
    for i in range(len(X)):
        pt0 = [x0, y0]
        pt = [float(X[i][0]), float(X[i][1])]
        distance = euklidian(pt0, pt)
        distances.append([i, distance])
    sorted_distances = sorted(distances, key = itemgetter(1))
    nearestPeople = []
    for i in range(k):
        nearestPeople.append(sorted_distances[i][0])
    pairs = [] 
    votes = [0, 0, 0]
    for i in range(k):
        x = float(X[nearestPeople[i]][0])
        y = float(X[nearestPeople[i]][1])
        pairs.append([x0, y0, x, y])
        line(x0, y0, x, y)  # draw proximity lines
        # get votes
        if X[nearestPeople[i]][2] == "Red":
            votes[0] += 1
        elif X[nearestPeople[i]][2] == "Green":
            votes[1] += 1
        elif X[nearestPeople[i]][2] == "Blue":
            votes[2] += 1
    max_value = max(votes)
    max_indices = []
    for i in range(3):
        if votes[i] == max_value:
            max_indices.append(i)  # all indices with max
    prediction = "Prediction: "
    for index in max_indices:        
        if index == 0:
            prediction += "Red "
        elif index == 1:
           prediction += "Green "
        elif index == 2:
            prediction += "Blue "
    title(prediction)
                 
def saveSample(x, y, kind):
    fOut = open(datafile, "a")
    fOut.write(str(x) + ";" + str(y) +  ";" + kind + "\n")
    fOut.close()
           
xmin = 5
xmax = 11
ymin = 45.8
ymax = 47.9
cx = -1
cy = -1
xorMode = False
pairs = []

makeGPanel(Size(594, 306), mousePressed = onMousePressed)
color = "Red"
title(color + " color selected")
setColor(color)
image(bgImage, 0, 0)
window(xmin, xmax, ymin, ymax)
# draw people already present
X = loadData(datafile)
for person in X:
    pos(float(person[0]), float(person[1]))    
    setColor(person[2])
    fillCircle(0.05)
keep()