def test(self):
labels = ['L2u', 'L2v', 'L2p']
df1 = run_spatial('plane-poiseuille-flow.i',
7,
"velocity_interp_method='average'",
'two_term_boundary_expansion=false',
"--error",
"--error-unused",
y_pp=labels,
mpi=16)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=labels,
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('plane-poiseuille-average-first.png')
for key, value in fig.label_to_slope.items():
if key == 'L2p':
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .1))
else:
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
def test(self):
labels = ['L2u', 'L2v', 'L2p']
df1 = mms.run_spatial('2d-average.i', 6, y_pp=labels)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=labels, marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('2d-average.png')
for key,value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
if key == 'L2p':
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .1))
else:
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
def test(self):
df1 = mms.run_spatial('advection-outflow.i', 7, y_pp=['L2u', 'L2v'])
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=['L2u', 'L2v'],
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('outflow.png')
for label, value in fig.label_to_slope.items():
if label == 'L2u':
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .05))
else:
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .05))
def test(self):
df1 = run_spatial('2d-rc.i', 6, y_pp=['L2u', 'L2v', 'L2p'], mpi=16)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=['L2u', 'L2v', 'L2p'], marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('rc-2d.png')
for key,value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .15))
def test(self):
labels = ['L2u', 'L2v', 'L2p', 'L2t']
df1 = mms.run_spatial('2d-average-with-temp.i', 7, "velocity_interp_method='rc'", y_pp=labels, mpi=16)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=labels, marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('2d-rc-with-temp.png')
for key,value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
def test(self):
labels = ['L2u', 'L2v', 'L2p']
df1 = run_spatial('rotated-pp-flow.i', 6, "velocity_interp_method='rc'", "--error", y_pp=labels, mpi=8)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=labels, marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('plane-poiseuille-rc.png')
for key,value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
def test(self):
labels = ['L2rho', 'L2rho_u', 'L2rho_et']
df1 = run_spatial('hllc-mms.i', list(range(6,12)), "--allow-test-objects", "--error", y_pp=labels, mpi=6)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=labels, marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('hllc.png')
for key,value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .05))
def test(self):
velocity_labels = ['L2u', 'L2v']
pressure_labels = ['L2p']
labels = velocity_labels + pressure_labels
df1 = run_spatial('skewed-vortex.i', 5, y_pp=labels, mpi=2)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=labels,
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('skewed.png')
for key, value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
if key in velocity_labels:
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .2))
else:
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .2))
def test(self):
df1 = run_spatial('1d-rc-no-diffusion.i',
5,
"--error",
"--error-unused",
"--error-deprecated",
y_pp=['L2u', 'L2p'])
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=['L2u', 'L2p'],
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('1d-rc-no-diffusion.png')
for key, value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
if (key == 'L2u'):
self.assertTrue(fuzzyAbsoluteEqual(value, 1.5, .1))
else:
self.assertTrue(fuzzyAbsoluteEqual(value, 1., .1))
def test(self):
df1 = mms.run_spatial('limited-advection.i',
9,
"FVKernels/advection_u/limiter='vanLeer'",
y_pp=['L2u'])
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=['L2u'],
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('vanLeer-limiter.png')
for label, value in fig.label_to_slope.items():
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .05))
def test(self):
df1 = mms.run_spatial(
'kt-limited-advection.i',
11,
"FVKernels/advection_u/limiter='central_difference'",
y_pp=['L2u'])
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=['L2u'],
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('kt-cd-limiter.png')
for key, value in fig.label_to_slope.items():
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .05))
print("%s slope, %f" % (key, value))
def test(self):
labels = ['L2u', 'L2v', 'L2p']
df1 = run_spatial('2d-rc-rz-symmetry.i',
list(range(1, 6)),
"--error",
y_pp=labels,
mpi=8)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=labels,
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('2d-rc-rz-symmetry.png')
for key, value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
def test(self):
df1 = run_spatial('pressure-interpolation-corrected.i',
7,
"--error",
"--error-unused",
"--error-deprecated",
y_pp=['L2u', 'L2v', 'L2p'],
mpi=8)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label=['L2u', 'L2v', 'L2p'],
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('pressure-interpolation-corrected.png')
for key, value in fig.label_to_slope.items():
print("%s, %f" % (key, value))
self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))