Benchmark 8a.1 Results¶

All result for the 8a.1 benchmark specification.

In [1]:

from pfhub.main import line_plot, levelset_plot, get_table_data_style, plot_order_of_accuracy, get_result_data
from itables import init_notebook_mode
init_notebook_mode(all_interactive=True);

from pathlib import Path

cwd = Path().resolve()
benchmark_path = r'https://raw.githubusercontent.com/usnistgov/pfhub/master/_data/simulation_list.yaml'

from pfhub.main import line_plot, levelset_plot, get_table_data_style, plot_order_of_accuracy, get_result_data from itables import init_notebook_mode init_notebook_mode(all_interactive=True); from pathlib import Path cwd = Path().resolve() benchmark_path = r'https://raw.githubusercontent.com/usnistgov/pfhub/master/_data/simulation_list.yaml'

In [2]:

line_plot(
    data_name='free_energy_1',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Free Energy',
        title="Free Energy, <i>r</i><sub>0</sub>=0.99<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='free_energy_1', benchmark_id='8a.1', layout=dict( x='time (s)', y='Free Energy', title="Free Energy, r₀=0.99r^*" ), benchmark_path=benchmark_path )

In [3]:

line_plot(
    data_name='solid_fraction_1',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Solid Fraction',
        title="Solid Fraction, <i>r</i><sub>0</sub>=0.99<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='solid_fraction_1', benchmark_id='8a.1', layout=dict( x='time (s)', y='Solid Fraction', title="Solid Fraction, r₀=0.99r^*" ), benchmark_path=benchmark_path )

In [4]:

line_plot(
    data_name='free_energy_2',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Free Energy',
        title="Free Energy, <i>r</i><sub>0</sub>=<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='free_energy_2', benchmark_id='8a.1', layout=dict( x='time (s)', y='Free Energy', title="Free Energy, r₀=r^*" ), benchmark_path=benchmark_path )

In [5]:

line_plot(
    data_name='solid_fraction_2',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Solid Fraction',
        title="Solid Fraction, <i>r</i><sub>0</sub>=<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='solid_fraction_2', benchmark_id='8a.1', layout=dict( x='time (s)', y='Solid Fraction', title="Solid Fraction, r₀=r^*" ), benchmark_path=benchmark_path )

In [6]:

line_plot(
    data_name='free_energy_3',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Free Energy',
        title="Free Energy, <i>r</i><sub>0</sub>=1.01<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='free_energy_3', benchmark_id='8a.1', layout=dict( x='time (s)', y='Free Energy', title="Free Energy, r₀=1.01r^*" ), benchmark_path=benchmark_path )

In [7]:

line_plot(
    data_name='solid_fraction_3',
    benchmark_id='8a.1',
    layout=dict(
        x='time (s)',
        y='Solid Fraction',
        title="Solid Fraction, <i>r</i><sub>0</sub>=1.01<i>r</i><sup>*</sup>"
    ),
    benchmark_path=benchmark_path
)

line_plot( data_name='solid_fraction_3', benchmark_id='8a.1', layout=dict( x='time (s)', y='Solid Fraction', title="Solid Fraction, r₀=1.01r^*" ), benchmark_path=benchmark_path )

In [8]:

#PYTEST_VALIDATE_IGNORE_OUTPUT

data = get_result_data(['phase_field_1'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path)

levelset_plot(
    data,
    layout=dict(
        levelset=0.5, 
        range=[-10, 10],
        title="Solid / Liquid Boundary at t=200, <i>r</i><sub>0</sub>=0.99<i>r</i><sup>*</sup>"
    ),
    mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9),
    columns=('x', 'y', 'z')
)

#PYTEST_VALIDATE_IGNORE_OUTPUT data = get_result_data(['phase_field_1'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path) levelset_plot( data, layout=dict( levelset=0.5, range=[-10, 10], title="Solid / Liquid Boundary at t=200, r₀=0.99r^*" ), mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9), columns=('x', 'y', 'z') )

In [9]:

data = get_result_data(['phase_field_2'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path)

levelset_plot(
    data,
    layout=dict(
        levelset=0.5, 
        range=[-10, 10],
        title="Solid / Liquid Boundary at t=200, <i>r</i><sub>0</sub>=<i>r</i><sup>*</sup>"
    ),
    mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9)
)

data = get_result_data(['phase_field_2'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path) levelset_plot( data, layout=dict( levelset=0.5, range=[-10, 10], title="Solid / Liquid Boundary at t=200, r₀=r^*" ), mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9) )

In [10]:

data = get_result_data(['phase_field_3'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path)

levelset_plot(
    data,
    layout=dict(
        levelset=0.5, 
        range=[-10, 10],
        title="Solid / Liquid Boundary at t=200, <i>r</i><sub>0</sub>=1.01<i>r</i><sup>*</sup>"
    ),
    mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9)
)

data = get_result_data(['phase_field_3'], ['8a.1'], ['x', 'y', 'z'], benchmark_path=benchmark_path) levelset_plot( data, layout=dict( levelset=0.5, range=[-10, 10], title="Solid / Liquid Boundary at t=200, r₀=1.01r^*" ), mask_func=lambda df: (0.1 < df.z) & (df.z < 0.9) )

In [11]:

keys = ['x', 'y', 'z']

data_names = ['phase_field_3', 'phase_field_4', 'phase_field_5']
df = get_result_data(data_names, ['8a.1'], keys=keys, benchmark_path=benchmark_path)

plot_order_of_accuracy(
    df,
    keys=keys,
    stepsx=([-50, 50], 1000),
    stepsy=([-50, 50], 1000),
    layout=dict(
        title='Order of Accuracy',
        labels=dict(x=r'Δx', y=r'L<sup>2</sup> Norm')
    )
)

keys = ['x', 'y', 'z'] data_names = ['phase_field_3', 'phase_field_4', 'phase_field_5'] df = get_result_data(data_names, ['8a.1'], keys=keys, benchmark_path=benchmark_path) plot_order_of_accuracy( df, keys=keys, stepsx=([-50, 50], 1000), stepsy=([-50, 50], 1000), layout=dict( title='Order of Accuracy', labels=dict(x=r'Δx', y=r'L² Norm') ) )

Table of Results¶

Table of 8a.1 benchmark result uploads

In [12]:

#PYTEST_VALIDATE_IGNORE_OUTPUT

init_notebook_mode(False)
get_table_data_style('8a.1', benchmark_path=benchmark_path)

#PYTEST_VALIDATE_IGNORE_OUTPUT init_notebook_mode(False) get_table_data_style('8a.1', benchmark_path=benchmark_path)

Out[12]:

Timestamp	Name	Code	Author	GitHub ID
2022-08-31	fipy_8a_10.5281/zenodo.7199253	fipy	Daniel Wheeler	None
2019-10-16	fipy_8a_fake	FiPy	Daniel Wheeler	wd15
2019-10-16	fipy_8a_fake_fake	FiPy	Daniel Wheeler	wd15

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