def test_parabolic_mor_results():
from pymordemos import parabolic_mor
args = ["pymor", "greedy", 5, 20, 3]
results = _test_demo(lambda: parabolic_mor.main(*args))
check_results(
"test_parabolic_mor_results",
args,
results,
(1e-13, 1e-7),
"basis_sizes",
"norms",
"max_norms",
(1e-13, 4.0),
"errors",
"max_errors",
"rel_errors",
"max_rel_errors",
"estimates",
"max_estimates",
"effectivities",
"min_effectivities",
"max_effectivities",
"errors",
)
def test_thermalblock_results(thermalblock_args):
from pymordemos import thermalblock
results = _test_demo(lambda: thermalblock.main(list(map(str, thermalblock_args[1]))))
# due to the symmetry of the problem and the random test parameters, the estimated
# error may change a lot
# fenics varies more than others between MPI/serial
first_tolerance = (1e-13, 3.5e-6) if "--fenics" in thermalblock_args[1] else (1e-13, 1e-7)
check_results(
"test_thermalblock_results",
thermalblock_args[1],
results,
first_tolerance,
"basis_sizes",
"norms",
"max_norms",
(1e-13, 4.0),
"errors",
"max_errors",
"rel_errors",
"max_rel_errors",
"estimates",
"max_estimates",
"effectivities",
"min_effectivities",
"max_effectivities",
"errors",
)
def test_burgers_ei_results():
from pymordemos import burgers_ei
args = list(map(str, [1, 2, 10, 100, 10, 30]))
ei_results, greedy_results = _test_demo(lambda: burgers_ei.main(args))
ei_results['greedy_max_errs'] = greedy_results['max_errs']
check_results('test_burgers_ei_results', args, ei_results,
(1e-13, 1e-7), 'errors', 'triangularity_errors', 'greedy_max_errs')
def test_burgers_ei_results():
from pymordemos import burgers_ei
args = list(map(str, [1, 2, 10, 100, 10, 30]))
ei_results, greedy_results = _test_demo(lambda: burgers_ei.main(args))
ei_results['greedy_max_errs'] = greedy_results['max_errs']
check_results('test_burgers_ei_results', args, ei_results,
(1e-13, 1e-7), 'errors', 'triangularity_errors', 'greedy_max_errs')
def test_parabolic_mor_results():
from pymordemos import parabolic_mor
args = ['pymor', 'greedy', 5, 20, 3]
results = _test_demo(lambda: parabolic_mor.main(*args))
check_results('test_parabolic_mor_results', args, results,
(1e-13, 1e-7), 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors', 'max_rel_errors',
'estimates', 'max_estimates', 'effectivities', 'min_effectivities', 'max_effectivities', 'errors')
def test_parabolic_mor_results():
from pymordemos import parabolic_mor
args = ['pymor', 'greedy', 5, 20, 3]
results = _test_demo(lambda: parabolic_mor.main(*args))
check_results('test_parabolic_mor_results', args, results,
(1e-13, 1e-7), 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors', 'max_rel_errors',
'estimates', 'max_estimates', 'effectivities', 'min_effectivities', 'max_effectivities', 'errors')
def test_burgers_ei_results():
from pymordemos import burgers_ei
args = list(map(str, [1, 2, 10, 100, 10, 30]))
ei_results, greedy_results = _test_demo(lambda: burgers_ei.main(args))
ei_results["greedy_max_errs"] = greedy_results["max_errs"]
check_results(
"test_burgers_ei_results", args, ei_results, (1e-13, 1e-7), "errors", "triangularity_errors", "greedy_max_errs"
)
def test_thermalblock_results(thermalblock_args):
from pymordemos import thermalblock
results = _test_demo(lambda: thermalblock.main(list(map(str, thermalblock_args[1]))))
# due to the symmetry of the problem and the random test parameters, the estimated
# error may change a lot
check_results('test_thermalblock_results', thermalblock_args[1], results,
(1e-13, 1e-7), 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors', 'max_rel_errors',
'estimates', 'max_estimates', 'effectivities', 'min_effectivities', 'max_effectivities', 'errors')
def test_burgers_ei_results():
from pymordemos import burgers_ei
app = Typer()
app.command()(burgers_ei.main)
args = list(map(str, [1, 2, 10, 100, 10, 30]))
_test_demo(lambda: runner.invoke(app, args, catch_exceptions=False))
ei_results, greedy_results = burgers_ei.test_results
ei_results['greedy_max_errs'] = greedy_results['max_errs']
check_results('test_burgers_ei_results', args, ei_results, (1e-13, 1e-7),
'errors', 'triangularity_errors', 'greedy_max_errs')
def test_thermalblock_results(thermalblock_args):
from pymordemos import thermalblock
results = _test_demo(lambda: thermalblock.main(list(map(str, thermalblock_args[1]))))
# due to the symmetry of the problem and the random test parameters, the estimated
# error may change a lot
# fenics varies more than others between MPI/serial
first_tolerance = (1e-13, 3.5e-6) if '--fenics' in thermalblock_args[1] else (1e-13, 1e-7)
check_results('test_thermalblock_results', thermalblock_args[1], results,
first_tolerance, 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors', 'max_rel_errors',
'estimates', 'max_estimates', 'effectivities', 'min_effectivities', 'max_effectivities', 'errors')
def test_thermalblock_results(thermalblock_args):
from pymordemos import thermalblock
results = _test_demo(
lambda: thermalblock.main(list(map(str, thermalblock_args[1]))))
# due to the symmetry of the problem and the random test parameters, the estimated
# error may change a lot
check_results('test_thermalblock_results', thermalblock_args[1], results,
(1e-13, 1e-7), 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors',
'max_rel_errors', 'estimates', 'max_estimates',
'effectivities', 'min_effectivities', 'max_effectivities',
'errors')
def test_thermalblock_results(thermalblock_args):
from pymordemos import thermalblock
app = Typer()
app.command()(thermalblock.main)
args = [str(arg) for arg in thermalblock_args[1]]
_test_demo(lambda: runner.invoke(app, args, catch_exceptions=False))
results = thermalblock.test_results
# due to the symmetry of the problem and the random test parameters, the estimated
# error may change a lot
# fenics varies more than others between MPI/serial
first_tolerance = (
1e-13, 3.5e-6) if '--fenics' in thermalblock_args[1] else (1e-13, 1e-7)
check_results('test_thermalblock_results', thermalblock_args[1], results,
first_tolerance, 'basis_sizes', 'norms', 'max_norms',
(1e-13, 4.), 'errors', 'max_errors', 'rel_errors',
'max_rel_errors', 'error_estimates', 'max_error_estimates',
'effectivities', 'min_effectivities', 'max_effectivities',
'errors')
