#!/usr/bin/python

import numpy as np

from energy import get_energy

from force import get_forces, move_vertices

from transition import T1_transition

from plot import plot_network

def steepest_descent(vertices, edges, polys, parameters, folder):

return

# def steepest_descent(network, vertices, cells, edges, delta_t, epsilon, folder):

# # keep track of time steps

# time = []

# t = 0

# # keep track of energy

# energy = []

# # for T1 transition

# min_dist = 0.2

# L = network.L

# # while forces are greater than epsilon

# forces = epsilon**0.5

# count = 0

# # generate random angle vectors

# for cell in cells:

# cell.theta = rand_angle()

# os.mkdir("noise/hex/%s" % folder)

# # f = open("energy/energy.txt", "w+")

# while count < 50:

# # while np.sum(forces**2)**(0.5) > epsilon:

# # plot_network(vertices, cells, L, "motility/%d.jpg" % count)

# # if count % 200 == 0:

# # for cell in cells:

# # cell.theta = rand_angle()

# # # write cell vertices for MSD

# os.chdir("noise/hex/%s" % folder)

# np.savetxt("%d.txt" % count, vertices)

# os.chdir("..")

# os.chdir("..")

# os.chdir("..")

# # get energy for network

# energy = network.get_energy(vertices, cells, edges)

# # get forces for network

# forces = network.get_forces(vertices, cells, edges)

# # move vertices with forces

# vertices = network.move_vertices(forces, vertices)

# ka = network.parameters['ka']

# A0 = 1.

# print t, energy / (24.*ka*(A0**2)), np.sum(forces**2)**(0.5)

# # norm_energy = np.array(energy / (24.*ka*(A0**2)))

# # f.write("%f\n" % norm_energy)

# # new time step

# t += delta_t

# # # check for T1 transitions

# cells, edges = T1_transition(network, vertices, cells, edges, min_dist)

# count += 1

# # f.close()

# return vertices