from dataclasses import dataclass
from scipy.optimize import basinhopping
import numpy as np

import math
from random import randrange

@dataclass
class Vertexer:
	nodes: np.ndarray
	c: float

	def reconstruct(self, times):
		def ssr_error(point):
			return np.sum(((np.linalg.norm(self.nodes - point, axis=1) / self.c)
                                   - times)**2)

		result = basinhopping(ssr_error, np.array([0,0]), niter=10000)
		print(result)

# Simulate sources to test code
x_1 = randrange(10); y_1 = randrange(10)
x_2 = randrange(10); y_2 = randrange(10)
x_3 = randrange(10); y_3 = randrange(10)

# Pick source to be at random location
x = randrange(10); y = randrange(10);

# Set velocity
c = 299792 # km/ns

# Generate simulated source
t_1 = math.sqrt( (x - x_1)**2 + (y - y_1)**2 ) / c
t_2 = math.sqrt( (x - x_2)**2 + (y - y_2)**2 ) / c
t_3 = math.sqrt( (x - x_3)**2 + (y - y_3)**2 ) / c

t_1 = np.random.normal(t_1, 0.001)
t_2 = np.random.normal(t_2, 0.001)
t_3 = np.random.normal(t_3, 0.001)

print(x,y)
myVertexer = Vertexer(np.array([[x_1, y_1],[x_2, y_2],[x_3, y_3]]), c)
print(myVertexer.reconstruct(np.array([t_1, t_2, t_3])))