default=script_directory,
help='directory where to save the figures')
args = parser.parse_args()
with open(args.map, 'r') as infile:
dirs = yaml.load(infile)
# Computes the mean coefficients from the PetIBM simulations
# with displaced markers.
# The force coefficients are averaged between 32 and 64 time-units.
cd_displaced, cl_displaced = [], []
for re in ['Re1000', 'Re2000']:
for aoa in ['AoA25', 'AoA30', 'AoA35', 'AoA40']:
simulation_directory = dirs['petibm011_forceCoefficientsVsAoA'][re][aoa]
simulation = PetIBMSimulation(directory=simulation_directory)
simulation.read_forces()
simulation.get_mean_forces(limits=[32.0, 64.0])
cd_displaced.append(2.0*simulation.forces[0].mean['value'])
cl_displaced.append(2.0*simulation.forces[1].mean['value'])
# Computes the mean coefficients from the PetIBM simulations
# with non-displaced (original) markers.
# The force coefficients are averaged between 32 and 64 time-units.
simulation_directory = dirs['petibm011_forceCoefficientsVsAoA']['Re2000']['AoA35original']
simulation = PetIBMSimulation(directory=simulation_directory)
simulation.read_forces()
simulation.get_mean_forces(limits=[32.0, 64.0])
cd_original = 2.0*simulation.forces[0].mean['value']
cl_original = 2.0*simulation.forces[1].mean['value']
# Computes the mean coefficients from the cuIBM simulations
# reported in Krishnan et al. (2014).
import yaml
import argparse
from matplotlib import pyplot
import snake
from snake.petibm.simulation import PetIBMSimulation
if snake.__version__ != '0.1.2':
warnings.warn('The figures were originally created with snake-0.1.2, ' +
'you are using snake-{}'.format(snake.__version__))
directory = os.path.join(os.path.dirname(__file__), 'dt0.0002')
simulation = PetIBMSimulation(description='dt=0.0002', directory=directory)
simulation.read_forces()
simulation.get_mean_forces(limits=[32.0, 64.0])
directory = os.path.join(os.path.dirname(__file__), 'dt0.0004')
loose = PetIBMSimulation(description='dt=0.0004', directory=directory)
loose.read_forces()
loose.get_mean_forces(limits=[32.0, 64.0])
dataframe = simulation.create_dataframe_forces(display_coefficients=True,
coefficient=2.0)
dataframe2 = loose.create_dataframe_forces(display_coefficients=True,
coefficient=2.0)
dataframe = dataframe.append(dataframe2)
print(dataframe)
fig, ax = pyplot.subplots(figsize=(6, 4))
ax.grid(True, zorder=0)
import sys
from matplotlib import pyplot
import snake
from snake.petibm.simulation import PetIBMSimulation
print('\nPython version:\n{}'.format(sys.version))
print('\nsnake version: {}\n'.format(snake.__version__))
simulation = PetIBMSimulation(
description='original markers',
directory=os.path.join(os.environ['HOME'], 'snakeReproducibilityPackages',
'petibm', 'exactMarkers', 'Re2000AoA35'))
simulation.read_forces()
simulation.get_mean_forces(limits=[32.0, 64.0])
simulation.get_strouhal(limits=[32.0, 64.0], order=200)
other = PetIBMSimulation(
description='displaced markers',
directory=os.path.join(os.environ['HOME'], 'snakeReproducibilityPackages',
'petibm', 'shiftedMarkers', 'Re2000AoA35'))
other.read_forces()
other.get_mean_forces(limits=[32.0, 64.0])
other.get_strouhal(limits=[32.0, 64.0], order=200)
dataframe = simulation.create_dataframe_forces(display_strouhal=True,
display_coefficients=True,
coefficient=2.0)
dataframe2 = other.create_dataframe_forces(display_strouhal=True,
display_coefficients=True,
published into Krishnan et al., 2014).
This script reads the forces, computes the mean forces within a given range,
computes the Strouhal number within a range, plots the force coefficients,
saves the figure, and prints a data-frame that contains the mean values.
"""
import os
from snake.petibm.simulation import PetIBMSimulation
from snake.cuibm.simulation import CuIBMSimulation
simulation = PetIBMSimulation(description='PetIBM')
simulation.read_forces()
time_limits = (32.0, 64.0)
simulation.get_mean_forces(limits=time_limits)
simulation.get_strouhal(limits=time_limits, order=200)
krishnan = CuIBMSimulation(description='Krishnan et al. (2014)')
filepath = os.path.join(os.environ['SNAKE'], 'resources',
'flyingSnake2d_cuibm_anush',
'flyingSnake2dRe2000AoA35', 'forces')
krishnan.read_forces(file_path=filepath)
krishnan.get_mean_forces(limits=time_limits)
krishnan.get_strouhal(limits=time_limits, order=200)
simulation.plot_forces(display_coefficients=True,
coefficient=2.0,
display_extrema=True,
order=200,
limits=(0.0, 80.0, 0.0, 3.0),
This script reads the forces, computes the mean forces within a given range,
computes the Strouhal number within a range, plots the force coefficients,
saves the figure, and prints a data-frame that contains the mean values.
"""
import os
from snake.petibm.simulation import PetIBMSimulation
from snake.cuibm.simulation import CuIBMSimulation
simulation = PetIBMSimulation(description='PetIBM')
simulation.read_forces()
time_limits = (32.0, 64.0)
simulation.get_mean_forces(limits=time_limits)
simulation.get_strouhal(limits=time_limits, order=200)
krishnan = CuIBMSimulation(description='Krishnan et al. (2014)')
filepath = os.path.join(os.environ['SNAKE'],
'resources',
'flyingSnake2d_cuibm_anush',
'flyingSnake2dRe2000AoA35',
'forces')
krishnan.read_forces(file_path=filepath)
krishnan.get_mean_forces(limits=time_limits)
krishnan.get_strouhal(limits=time_limits, order=200)
simulation.plot_forces(display_coefficients=True,
coefficient=2.0,
display_extrema=True, order=200,
# Run this script from the simulation directory.
from snake.ibamr.simulation import IBAMRSimulation
from snake.petibm.simulation import PetIBMSimulation
simulation = IBAMRSimulation(description='IBAMR')
simulation.read_forces()
simulation.get_mean_forces(limits=[32.0, 64.0])
simulation.get_strouhal(limits=[32.0, 64.0], order=200)
other = PetIBMSimulation(description='other',
directory='other')
other.read_forces()
other.get_mean_forces(limits=[32.0, 64.0])
other.get_strouhal(limits=[32.0, 64.0], order=200)
simulation.plot_forces(display_coefficients=True,
coefficient=-2.0,
display_extrema=True, order=200,
limits=(0.0, 80.0, 0.0, 3.0),
other_simulations=other,
other_coefficients=2.0,
save_name='forceCoefficientsCompareOther')
dataframe = simulation.create_dataframe_forces(display_strouhal=True,
display_coefficients=True,
coefficient=-2.0)
dataframe2 = other.create_dataframe_forces(display_strouhal=True,
display_coefficients=True,
coefficient=2.0)
