def solve(self, dt=0.01, tol=0.001, maxiter=50, t_max=2., t_load=1., node_to_plot=None, verbose=False,
savefile='', savetextfile='', show=True, timelog=None, output_freq=1):
headers = ['u_x', 'u_y', 'v_x', 'v_y', 'a_x', 'a_y', '||a||', 'time', 'loadfunc']
table = {key:[] for key in headers}
if timelog:
tlog = open(timelog, 'w')
else:
tlog = None
dt = t_max / float(maxiter)
t1 = time.clock()
if timelog: tlog.write('Commencing initializing calculation\n')
# Initialize local values
els = self.elements
nds = self.nodes
for el in els:
el.set_matrices()
el.calc_normal_vectors()
for nd in nds:
nd.init_vals(maxiter)
t2 = time.clock()
if timelog: tlog.write('Initializing calculation total time = %g\n' % (t2 - t1))
# Iterate until convergence is reached for all elements
itercount = 0
crits = []
node_data = []
while True:
itercount += 1
crit = 0.
if timelog: tlog.write('Starting iteration no. %d\n' % itercount)
t1 = time.clock()
for i, el in enumerate(els):
if timelog: tlog.write('Calculating element no. %d\n' % (i + 1))
crit = max(crit, el.iterate(dt, itercount * dt / t_load, tlog, verbose=verbose))
for i, el in enumerate(els):
if timelog: tlog.write('Writing nodal values element no. %d\n' % (i + 1))
el.write_next_vals()
t2 = time.clock()
if timelog: tlog.write('Iteration no. %d complete, total time taken = %g\n' % (itercount, t2 - t1))
crits.append(crit)
if node_to_plot and ((itercount % output_freq) == 0):
node_data.append((np.array(self.nodes[node_to_plot - 1].v_disp),
np.array(self.nodes[node_to_plot - 1].v_velo),
np.array(self.nodes[node_to_plot - 1].v_acce),
))
table['||a||'].append(np.linalg.norm(np.hstack([nd.v_acce for nd in nds])))
table['loadfunc'].append(load_function(itercount * dt / t_load))
table['time'].append(itercount * dt)
if crit < tol:
if verbose: print 'Convergence reached in step no.%d: maximum criterium = %.10f' % (itercount, crit)
# break
else:
if verbose: print 'Step no.%d: maximum criterium = %.10f' % (itercount, crit)
if itercount == maxiter:
print 'Maximum step count reached: maximum criterium = %.10f' % crit
break
acce_norm = np.linalg.norm(np.hstack([nd.v_acce for nd in nds]))
print 'Acceleration norm upon calculation end = %.6f' % acce_norm
if timelog: tlog.close()
t_vals = np.array(table['time'])
# plt.plot(t_vals, crits, label='Convergence criterium', linewidth=2.)
if node_to_plot:
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(t_vals, [n[0][0] for n in node_data], label='u_x', linewidth=2.)
ax.plot(t_vals, [n[0][1] for n in node_data], label='u_y', linewidth=2.)
ax.plot(t_vals, [n[1][0] for n in node_data], label='v_x', linewidth=2.)
ax.plot(t_vals, [n[1][1] for n in node_data], label='v_y', linewidth=2.)
ax.plot(t_vals, [n[2][0] for n in node_data], label='a_x', linewidth=2.)
ax.plot(t_vals, [n[2][1] for n in node_data], label='a_y', linewidth=2.)
table['u_x'] = [n[0][0] for n in node_data]
table['u_y'] = [n[0][1] for n in node_data]
table['v_x'] = [n[1][0] for n in node_data]
table['v_y'] = [n[1][1] for n in node_data]
table['a_x'] = [n[2][0] for n in node_data]
table['a_y'] = [n[2][1] for n in node_data]
table['time'] = t_vals
ax.legend(loc='lower left')
if savetextfile:
f = open(savetextfile, 'w')
texttable = tbl.tabulate(zip(*[table[col] for col in headers]), headers=headers, tablefmt="orgtbl")
f.write(texttable)
f.close()
if savefile:
fig.savefig(savefile)
if show:
plt.show()
def init_vals(self, maxiter):
# Init for dynamic relaxation
tau = 1 / float(maxiter)
self.F_g = load_function(tau) * np.array([0., -self.mass * GRAVITY])
self.v_acce[self.free_dofs] = load_function(tau) / self.mass * (self.F_ext + self.F_g)
