from PIL import Image

data1 = open('Training_wells.csv').read().split('\n')
data2 = open('Empty_part.csv').read().split('\n')
del data1[-1]
del data2[-1]

n1 = len(data1)
n2 = len(data2)
xs1 = []
ys1 = []
vals1 = []
points1 = []
for i in range(1, n1):
    line = data1[i].split(',')
    x, y, val = line[1], line[2], line[3]
    x, y, val = int(x), int(y), float(val)
    xs1.append(x)
    ys1.append(y)
    vals1.append(val)
    points1.append((x, y, val))

xs2 = []
ys2 = []
vals2 = []
points2 = []
for i in range(1, n2):
    line = data2[i].split(',')
    x, y = line[1], line[2]
    val = 0
    x, y, val = int(x), int(y), float(val)
    xs2.append(x)
    ys2.append(y)
    vals2.append(val)
    points2.append((x, y, val))


min_x, max_x, min_y, max_y = min(min(xs1), min(xs2)), max(max(xs1), max(xs2)), min(min(ys1), min(ys2)), max(max(ys1), max(ys2))

for i in range(len(points1)):
    x, y, val = points1[i]
    x -= min_x
    y -= min_y
    points1[i] = (x, y, val)

for i in range(len(points2)):
    x, y, val = points2[i]
    x -= min_x
    y -= min_y
    points2[i] = (x, y, val)

min_x, max_x, min_y, max_y = min(min(xs1), min(xs2)), max(max(xs1), max(xs2)), min(min(ys1), min(ys2)), max(max(ys1), max(ys2))


n = max_x - min_x + 1
m = max_y - min_y + 1
print(min_x, max_x, min_y, max_y)
print(min(vals1), max(vals1))
image = Image.new('RGB', (n, m))
pixel_map = image.load()
for x in range(n):
    for y in range(m):
        pixel_map[x, y] = (255, 255, 255)

values = [[0 for y in range(m)] for x in range(n)]
for (x, y, val) in points1:
    pixel_map[x, y] = (0, int(255 * val), 0)
    values[x][y] = val

deltas = []
for (x, y, val) in points2:
    pixel_map[x, y] = (255, 0, 0)

k = min(800 // n, 800 // m)
image.resize((n * k, m * k), resample=Image.BOX).show()


# f(x, y) = sum(a[i][j] * x ** i * y ** j for i in range(n) for j in range(m)) = z
# n, m
# 0 <= f(x, y) <= 1
# 1 <= n == m, n + m == 40
# f(x, y) == value 138th times
from random import random
from math import *

def generate(n, m, values):
    N = 4

    a = [[random() for y in range(N)] for x in range(N)]

    def relax(a, x, y, value):

        return a

    for itr in range(50):
        for x, y, value in values:
            a = relax(a, x, y, value)
    result = [[0 for y in range(m)] for x in range(n)]

    for x in range(n):
        for y in range(m):
            for i in range(N):
                for j in range(N):
                    result[x][y] += a[i][j] * x ** i * y ** j
    return result


def apply_to_pixel_map_and_show(res):
    n = len(res)
    m = len(res[0])
    img = Image.new('RGB', (n, m))
    pm = img.load()
    for x in range(n):
        for y in range(m):
            val = int(255 * res[x][y]) & 255
            print(val, end = ' ')
            pm[x, y] = (val, val, 0)
    print()
    img.resize((n * k, m * k), resample=Image.BOX).show()

apply_to_pixel_map_and_show(values)