test_model_solver_dynamic.py
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	#!/usr/bin/env python3

	# ------------------------------------------------------------------------------
	__author__ = "Nicolas Richart"
	__copyright__ = "Copyright (C) 2016-2018, EPFL (Ecole Polytechnique Fédérale" \
	" de Lausanne) Laboratory (LSMS - Laboratoire de Simulation" \
	" en Mécanique des Solides)"
	__credits__ = ["Nicolas Richart"]
	__license__ = "L-GPLv3"
	__maintainer__ = "Nicolas Richart"
	__email__ = "nicolas.richart@epfl.ch"
	# ------------------------------------------------------------------------------

	import numpy as np
	import python_fe as pfe
	import matplotlib.pyplot as plt
	import matplotlib.animation as animation

	# sim_u = np.genfromtxt("disp.csv", delimiter=",", names=True)

	L = 1.
	Ne = 200 # int(sim_u['node'][-1])
	F = np.zeros(Ne + 1) # sim_u['force']
	F[-1] = - 9.81
	blocked = np.zeros(Ne + 1) # sim_u['blocked']
	blocked[0] = 1
	u = np.zeros(Ne + 1) # sim_u['disp']

	trusses = pfe.TrussFE(Ne=Ne,
	F={f: [np.where(F == f)] for f in np.unique(F)},
	blocked=(np.where(blocked == 1),
	u[blocked == 1]))

	solver = pfe.DynamicSolver(trusses, delta_t=0.001)

	# for s in range(200):
	# solver.solveStep()


	fig, ax = plt.subplots()

	x = np.arange(Ne+1) * L / Ne # x-array
	line, = ax.plot(x, trusses.u)


	def animate(i):
	solver.solveStep()
	line.set_ydata(trusses.u) # update the data
	plt.ylim(np.min(trusses.u), np.max(trusses.u))
	return line,


	ani = animation.FuncAnimation(fig, animate, np.arange(1, 200),
	interval=25, blit=True)

	plt.show()