import matplotlib.pyplot as plt
from abapy.postproc import HistoryOutput
time = [[1., 2., 3.], [3., 4., 5.], [5., 6., 7.]]
force = [[2., 2., 2.], [3., 3., 3.], [4., 4., 4.]]
Force = HistoryOutput(time, force)
fig = plt.figure(0, figsize=(8, 4))
plt.clf()
ax = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
x, y = Force[[0, 2]].toArray()
x2, y2 = Force[[0, 2]].plotable()
ax.plot(x, y)
ax2.plot(x2, y2)
ax.set_ylim([1, 5])
ax2.set_ylim([1, 5])
plt.savefig('HistoryOutput-plotable.png')
ax.set_title('HistorytOutput.toArray')
ax2.set_title('HistorytOutput.plotable')
plt.show()
from abapy.postproc import HistoryOutput
from math import sin, pi
N = 100
hist = HistoryOutput()
time = [pi / 2 * float(i) / N for i in range(N + 1)]
data = [sin(t) for t in time]
hist.add_step(time_step=time, data_step=data)
time2 = [10., 11.]
data2 = [1., 1.]
hist.add_step(time_step=time2, data_step=data2)
sol = 2. / pi + 1.
print('Print computed value:', hist.average())
print('Analytic solution:', sol)
print('Relative error: {0:.4}%'.format((hist.average() - sol) / sol * 100.))
from abapy.postproc import HistoryOutput
from math import sin, pi
N = 100
hist = HistoryOutput()
time = [pi / 2 * float(i)/N for i in xrange(N+1)]
data = [sin(t) for t in time]
hist.add_step(time_step = time, data_step = data)
time2 = [10., 11.]
data2 = [1., 1.]
hist.add_step(time_step = time2, data_step = data2)
sol = 2. / pi + 1.
print 'Print computed value:', hist.average()
print 'Analytic solution:', sol
print 'Relative error: {0:.4}%'.format( (hist.average() - sol)/sol * 100.)
from abapy.postproc import HistoryOutput
time = [ [0., 1.], [3., 4.] ]
data = [ [.5, 1.5], [.5, 1.5] ]
hist = HistoryOutput(time = time, data = data)
hist[0].integral()
hist[1].integral()
hist.integral()
N = 10
from math import sin, pi
time = [pi / 2 * float(i)/N for i in xrange(N+1)]
data = [sin(t) for t in time]
hist = HistoryOutput()
hist.add_step(time_step = time, data_step = data)
trap = hist.integral()
simp = hist.integral(method = 'simps')
trap_error = (trap -1.)
simp_error = (simp -1.)
print 'Relative errors:\nTrapezoid rule: {0:.2}%\nSimpson rule: {1:.2}%'.format(trap_error*100, simp_error*100)
from abapy.postproc import HistoryOutput
time = [[0., 1.], [3., 4.]]
data = [[.5, 1.5], [.5, 1.5]]
hist = HistoryOutput(time=time, data=data)
hist[0].integral()
hist[1].integral()
hist.integral()
N = 10
from math import sin, pi
time = [pi / 2 * float(i) / N for i in range(N + 1)]
data = [sin(t) for t in time]
hist = HistoryOutput()
hist.add_step(time_step=time, data_step=data)
trap = hist.integral()
simp = hist.integral(method='simps')
trap_error = (trap - 1.)
simp_error = (simp - 1.)
print('Relative errors:\nTrapezoid rule: {0:.2}%\nSimpson rule: {1:.2}%'.format(
trap_error * 100, simp_error * 100))
from abapy.postproc import HistoryOutput time = [[1., 2., 3.], [3., 4., 5.], [5., 6., 7.]] # Time separated in 3 steps data = [[2., 2., 2.], [3., 3., 3.], [4., 4., 4.]] # Data separated in 3 steps Data = HistoryOutput(time, data) print Data # +, *, **, abs, neg act only on data, not on time print Data + Data + 1. # addition print Data * Data * 2. # multiplication print(Data / Data) / 2. # division print Data**2 print abs(Data) print Data[1] # step 1 print Data[0:2] print Data[0, 2]
