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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()