def test_sample_timeSeries():
cwd = os.getcwd()
dir_path = os.path.dirname(os.path.realpath(__file__))
os.chdir(dir_path)
solutionDir = "sample1"
file = "centreLine_T.xy"
caseStructure = [['Ux1', 'Ux3'], ['T1'], ['p1'], ['string10']]
baseCase = "Cases"
surf_time = casefoam.posField_to_timeSeries(solutionDir, file,
getFreeSurfaceWallAndCentre,
caseStructure, baseCase)
grouped_df = surf_time.groupby(['var_0', 'var_1', 'var_2', 'var_3'])
assert len(grouped_df.size()) == 2
assert surf_time['min'].max() == 0
assert surf_time['max'].max() == 1
os.chdir(cwd)
baseCase = 'Cases'
solutionDir = 'reconSurfaces'
file = 'alpha.water_freeSurf.raw'
analytical = pd.read_csv("analyticalWave.dat",
delim_whitespace=True,
header=None)
analytical.columns = ['time', "analytical"]
analytical["analytical"] *= 100
postFunction = postFunctions.getFreeSurfaceWallAndCentre
sol = casefoam.posField_to_timeSeries(solutionDir,
file,
postFunction,
cases,
baseCase,
axis=1)
sol = sol.reset_index()
sol.columns = [
'time', 'min', 'mean', 'max', 'interfaceType', 'Method', 'nCells'
]
sol = sol.replace('coarse', 32)
sol = sol.replace('mid', 64)
sol = sol.replace('fine', 128)
sol['max'] /= 3e-5
sol['time'] /= 1.475e-5
ax = analytical.plot(x='time', y='analytical', c='black', marker='o')
sns.set_style("ticks")
plicRDF = sol[sol['interfaceType'] == 'plicRDF']
plicRDF.to_csv("sinwaveTri.csv", index=False)
import casefoam
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
solutionDir = 'surfaces'
filename = 'p_freeSurf.raw'
def centreAndWall(caseComb, time, currentDataFrame):
"""Return the centre and wall pos.
"""
centre = currentDataFrame.iloc[:, 1].min()
wall = currentDataFrame.iloc[:, 1].max()
df = pd.DataFrame(np.array([time, centre, wall], ndmin=2),
columns=['time', 'centre', 'wall'])
print(df)
df = df.set_index('time')
return df
sol = casefoam.posField_to_timeSeries(solutionDir, filename, centreAndWall)
sol.sort_values('time', inplace=True)
sol[['centre', 'wall']].plot()
plt.show()
import casefoam
from casefoam import postFunctions
import seaborn as sns
# output_notebook()
sns.set_style("ticks")
caseStructure = [['isoSurface', 'plicRDF'],
['implicitGrad', 'explicitGrad', 'Schrage'],
['grid1', 'grid2', 'grid3']]
baseCase = 'Cases'
solutionDir = 'surfaces'
file = 'interfaceEnergyFluxLiquid_freeSurf.raw'
postFunction = postFunctions.getRadius
surfPos = casefoam.posField_to_timeSeries(solutionDir, file, postFunction,
caseStructure, baseCase)
surfPos.columns = ['min', 'r', 'max', 'interFaceType', 'Method', 'Resolution']
surfPos = surfPos.sort_index()
surfPos = surfPos.reset_index('time')
surfPos[['min', 'r', 'max']] *= 1000
# plot analytical solution
analytical_data = pd.read_csv('init/data.dat', delim_whitespace=True)
analytical_data['r'] *= 1000
ax = analytical_data.plot(x='t', y='r', label='analytical', color='black')
surfPos_plicRDF = surfPos[surfPos.interFaceType == 'plicRDF']
ax = sns.lineplot(x='time',
y='r',
forcesDir = 'forces/0'
forces = time_series(forcesDir, 'force.dat', caseStructure, baseCase)
forces = forces.reset_index()
plt.figure()
sns.lineplot(x='t', y=1, hue='var_0', style='var_1', data=forces)
plt.xlabel('x [m]')
plt.ylabel('F [N]')
def max_min_Height(caseComb, time, currentDataFrame):
t = time
minimum = currentDataFrame.iloc[:, 1].min()
maximum = currentDataFrame.iloc[:, 1].max()
df = pd.DataFrame(np.array([time, minimum, maximum], ndmin=2),
columns=['time', 'min', 'max'])
df = df.set_index('time')
return df
surf_Heights = casefoam.posField_to_timeSeries(surfaceDir, 'p_freeSurface.raw',
max_min_Height, caseStructure,
baseCase)
surf_Heights = surf_Heights.reset_index()
plt.figure()
sns.lineplot(x='time', y='max', hue='var_0', style='var_1', data=surf_Heights)
plt.xlabel('x [m]')
plt.ylabel('h [m]')
plt.show()