def do_plot(self, input_file, num_refinements, cli_args, figure, label, mpi=1):
cli_args = " ".join(cli_args + self.function_args)
df = mms.run_spatial(input_file,
num_refinements,
cli_args,
x_pp='h',
y_pp=['L2u', 'L2lambda'],
mpi=mpi)
figure.plot(df,
label=['u_' + label, 'lm_' + label],
num_fitted_points=3,
slope_precision=1,
marker='o')
def test(self):
df1 = mms.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):
df1 = mms.run_spatial('steady-adapt.i', 8, "--error", 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 key, value in fig.label_to_slope.items():
print("%s slope, %f" % (key, value))
self.assertTrue(fuzzyEqual(value, 1., .05))
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 = 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):
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))
def test(self):
labels = ['L2u', 'L2v', 'L2p']
df1 = mms.run_spatial('plane-poiseuille-flow.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('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 = ['L2u', 'L2v', 'L2p']
df1 = mms.run_spatial('plane-poiseuille-flow.i',
7,
"velocity_interp_method='average'",
'two_term_boundary_expansion=false',
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))
#!/usr/bin/env python3
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgpl-2.1.html
import mms
df1 = mms.run_spatial('ex14.i', 4, executable='./ex14-opt')
df2 = mms.run_spatial('ex14.i',
4,
'Mesh/second_order=true',
'Variables/forced/order=SECOND',
executable='./ex14-opt')
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.plot(df2, label='2nd Order', marker='o', markersize=8)
fig.save('ex14_mms.png')
#!/usr/bin/env python3
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgpl-2.1.html
import mms
df1 = mms.run_spatial(
'3d_mes.i',
3,
executable=
'/home/alexander/Development/moose_projects/hammerhead/hammerhead-opt',
file_base='3d_strip_out_{}')
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.save('bean_mms.png')
#!/usr/bin/env python3
#* This file is part of MOOSETOOLS repository
#* https://www.github.com/idaholab/moosetools
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moosetools/blob/main/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgpl-2.1.html
import mms
df1 = mms.run_spatial('mms_spatial.i',
4,
console=False,
executable='../../../test')
df2 = mms.run_spatial('mms_spatial.i',
4,
'Mesh/second_order=true',
'Variables/u/order=SECOND',
console=False,
executable='../../../test')
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.plot(df2, label='2nd Order', marker='o', markersize=8)
fig.save('mms_spatial.png')
#TESTING (leave this comment, it is used in doco to remove the following from a demo)
df1.to_csv('mms_spatial_first.csv')
df2.to_csv('mms_spatial_second.csv')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('cartesian.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='cartesian',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('cartesian.png')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('advection-diffusion.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='adv-diff',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('advection-diffusion.png')
#!/usr/bin/env python3
# MooseDocs:start:spatial
import mms
df = mms.run_spatial('1d_analytical.i', 6, 'Mesh/gen/nx=10', console=False)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df, label='1st Order', marker='o', markersize=8)
fig.save('1d_analytical_spatial.png')
# MooseDocs:end:spatial
# MooseDocs:start:temporal
import mms
df = mms.run_temporal('1d_analytical.i', 6, dt=0.5, console=False)
fig = mms.ConvergencePlot(xlabel='$\Delta t$', ylabel='$L_2$ Error')
fig.plot(df, label='2nd Order (Backward Difference)', marker='o', markersize=8)
fig.save('1d_analytical_temporal.png')
# MooseDocs:end:temporal
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('advection-diffusion-flux-bcs.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='adv-diff-flux-bcs',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('advection-diffusion-flux-bcs.png')
#!/usr/bin/env python
import mms
df1 = mms.run_spatial('mms_spatial.i', 4, console=False)
df2 = mms.run_spatial('mms_spatial.i', 4, 'Mesh/second_order=true', 'Variables/u/order=SECOND', console=False)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.plot(df2, label='2nd Order', marker='o', markersize=8)
fig.save('mms_spatial.png')
#TESTING (leave this comment, it is used in doco to remove the following from a demo)
df1.to_csv('mms_spatial_first.csv')
df2.to_csv('mms_spatial_second.csv')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('diffusion.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='diff',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('diffusion.png')
#!/usr/bin/env python3
# MooseDocs:start:spatial
import mms
df1 = mms.run_spatial(['2d_main.i', '2d_mms_spatial.i'], 4, console=False)
df2 = mms.run_spatial(['2d_main.i', '2d_mms_spatial.i'],
4,
'Mesh/second_order=true',
'Variables/T/order=SECOND',
console=False)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.plot(df2, label='2nd Order', marker='o', markersize=8)
fig.save('2d_mms_spatial.png')
# MooseDocs:end:spatial
# MooseDocs:start:temporal
import mms
df1 = mms.run_temporal(['2d_main.i', '2d_mms_temporal.i'],
4,
dt=1200,
mpi=4,
console=False)
df2 = mms.run_temporal(['2d_main.i', '2d_mms_temporal.i'],
4,
'Executioner/scheme=bdf2',
dt=1200,
mpi=4,
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('rz.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='rz', marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('rz.png')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('advection.i', 7)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='adv',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('advection.png')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('extended-cartesian.i', 7, mpi=2)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='extended-cartesian', marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('extended-cartesian.png')
#!/usr/bin/env python
#* This file is part of the MOOSE framework
#* https://www.mooseframework.org
#*
#* All rights reserved, see COPYRIGHT for full restrictions
#* https://github.com/idaholab/moose/blob/master/COPYRIGHT
#*
#* Licensed under LGPL 2.1, please see LICENSE for details
#* https://www.gnu.org/licenses/lgpl-2.1.html
import mms
df1 = mms.run_spatial('mms_spatial.i', 4, console=False)
df2 = mms.run_spatial('mms_spatial.i', 4, 'Mesh/second_order=true', 'Variables/u/order=SECOND', console=False)
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label='1st Order', marker='o', markersize=8)
fig.plot(df2, label='2nd Order', marker='o', markersize=8)
fig.save('mms_spatial.png')
#TESTING (leave this comment, it is used in doco to remove the following from a demo)
df1.to_csv('mms_spatial_first.csv')
df2.to_csv('mms_spatial_second.csv')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('advection-diffusion.i', 7,
"GlobalParams/advected_interp_method='upwind'")
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1,
label='upwind-adv-diff',
marker='o',
markersize=8,
num_fitted_points=3,
slope_precision=1)
fig.save('upwind-advection-diffusion.png')
#!/usr/bin/env python3
import mms
df1 = mms.run_spatial('input.i', 7, y_pp=['l2_rho', 'l2_vel'])
fig = mms.ConvergencePlot(xlabel='Element Size ($h$)', ylabel='$L_2$ Error')
fig.plot(df1, label=['rho', 'vel'], marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
fig.save('mass-mom-mat-advection-diffusion.png')
