def test(self):
df1 = mms.run_spatial('steady-adapt.i', 7, mpi=8)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='steady-adapt',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('steady-adapt.png')
for _,value in fig.label_to_slope.items():
self.assertTrue(fuzzyEqual(value, 1., .05))
def test(self):
df1 = mms.run_spatial('advection-diffusion-reaction.i', 7, mpi=2)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='compact-adr',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('compact-adr.png')
for _,value in fig.label_to_slope.items():
self.assertTrue(fuzzyEqual(value, 2., .05))
def test(self):
df1 = mms.run_spatial('skewed.i',
5,
'Variables/v/face_interp_method=average',
mpi=1)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label='average',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('average.png')
for _, value in fig.label_to_slope.items():
self.assertTrue(fuzzyEqual(value, 1., .15))
def test(self):
df1 = mms.run_spatial(
'skewed.i',
5,
'Variables/v/face_interp_method=skewness-corrected FVKernels/advection/advected_interp_method=skewness-corrected',
mpi=1)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)',
ylabel='$L_2$ Error')
fig.plot(df1,
label='corrected-advection',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('corrected-advection.png')
for _, value in fig.label_to_slope.items():
self.assertTrue(fuzzyEqual(value, 2.0, .1))