def load_field_3d(datadir, config, time, name):
# Set parameters.
time *= config.T # convert to dimensional time
timestep = int(time / config.dt) # time-step index
# Load gridline coordinates from file.
filepath = datadir / 'grid.h5'
x, y, z = petibmpy.read_grid_hdf5(filepath, name)
# Shift z locations to match figures of Li & Dong (2016).
z -= config.S / 2
# Load 3D field solution from file.
filepath = datadir / f'{timestep:0>7}.h5'
field = petibmpy.read_field_hdf5(filepath, name)
# Return grid and streamwise vorticity.
return (x, y, z), field
def petibm_load_grid_and_field(datadir, timestep, name):
"""Load the gridlines and values of a field at a given time step.
Parameters
----------
datadir : pathlib.Path
Directory with the data to load.
timestep : int
Time-step index.
name : str
Name of the field to read, e.g. 'u', 'v', or 'p'.
Returns
-------
tuple
Gridline locations in each direction as a tuple of 1D arrays of floats.
numpy.ndarray
Field values at given time step.
"""
grid = petibmpy.read_grid_hdf5(datadir / 'grid.h5', name)
field = petibmpy.read_field_hdf5(datadir / f'{timestep:0>7}.h5', name)
return grid, field
# Create data type to store information about annotation.
Annotation = collections.namedtuple('Annotation',
['text', 'xytext', 'xyarrow'])
# ----------------------------------------------------------------------------
# Plot the 2D slice of the streamwise vorticity in the y/z plane at x/c = 0.3.
# ----------------------------------------------------------------------------
# Load the gridline coordinates from file.
filepath = datadir / 'grid.h5'
x, y, z = petibmpy.read_grid_hdf5(filepath, 'wx')
# Load the field solution from file.
filepath = datadir / '{:0>7}.h5'.format(timestep)
wx = petibmpy.read_field_hdf5(filepath, 'wx')
# Interpolate the vorticity component in the y/z plane in the near wake.
xloc = 0.3 # location along the x direction (near wake)
wx_tmp = numpy.swapaxes(wx, -1, 0)
wx_xloc = petibmpy.linear_interpolation(wx_tmp, x, xloc)
# Create the Matplotlib figure.
fig, ax = pyplot.subplots(figsize=(4.0, 4.0))
ax.set_xlabel('z/c')
ax.set_ylabel('y/c')
# Add wing to the plot.
ax.add_patch(
patches.Ellipse((0.0, 0.0),
config.S,
name = 'wz' # name of the vorticity variable
timestep = 20000 # final time-step index
show_figure = True # if True, display the figure
# Set the simulation and data directories.
simudir = pathlib.Path(__file__).absolute().parents[1]
datadir = simudir / 'output'
# Load the gridlines from file.
filepath = datadir / 'grid.h5'
x, y = petibmpy.read_grid_hdf5(filepath, name)
# Load the vorticity field from file.
filepath = datadir / f'{timestep:0>7}.h5'
wz = petibmpy.read_field_hdf5(filepath, name)
# Load the boundary coordinates from file.
filepath = simudir / 'cylinder.body'
xb, yb = petibmpy.read_body(filepath, skiprows=1)
# Plot the contours of the vorticity field.
pyplot.rc('font', family='serif', size=16)
fig, ax = pyplot.subplots(figsize=(6.0, 6.0))
ax.set_xlabel('x / D')
ax.set_ylabel('y / D')
levels = numpy.arange(-3.0, 3.0 + 0.4 / 2, 0.4)
ax.contour(x, y, wz, levels=levels, colors='black')
ax.plot(xb, yb, color='red')
ax.axis('scaled', adjustable='box')
ax.set_xlim(-1.0, 5.0)
ax.set_ylim(-2.0, 2.0)
ax2.set_ylabel('v')
for Re, timestep in zip(Res, timesteps):
# Load data from Ghia et al. (1982).
adir = rootdir / 'data'
filepath = adir / 'ghia_et_al_1982_lid_driven_cavity.dat'
yu_g, uc_g, xv_g, vc_g = load_data_ghia_et_al_1982(filepath, str(Re))
# Load gridlines and velocity fields.
simudir = maindir / f'liddrivencavity2dRe{Re}'
datadir = simudir / 'output'
filepath = datadir / 'grid.h5'
xu, yu = petibmpy.read_grid_hdf5(filepath, 'u')
xv, yv = petibmpy.read_grid_hdf5(filepath, 'v')
filepath = datadir / f'{timestep:0>7}.h5'
u = petibmpy.read_field_hdf5(filepath, 'u')
v = petibmpy.read_field_hdf5(filepath, 'v')
# Interpolate solution at centerlines of the cavity.
uc = petibmpy.linear_interpolation(u.T, xu, 0.5)
vc = petibmpy.linear_interpolation(v, yv, 0.5)
# Plot the velocity profiles.
ax1.plot(yu, uc, label=f'Re = {Re}')
label = ('Ghia et al. (1982)' if Re == Res[-1] else None)
ax1.plot(yu_g,
uc_g,
label=label,
linewidth=0,
color='black',
marker='o',
import petibmpy
show_figure = True # if True, display the figure(s)
simudir = pathlib.Path(__file__).absolute().parents[1]
datadir = simudir / 'output'
# Load the grid from file.
name = 'wz' # name of the vorticity variable
filepath = datadir / 'grid.h5'
x, y = petibmpy.read_grid_hdf5(filepath, name)
# Load the vorticity at phase angles 0 deg during the last period.
timestep = 7500
filepath = datadir / '{:0>7}.h5'.format(timestep)
wz1 = petibmpy.read_field_hdf5(filepath, name)
# Load the body coordinates at the same time.
filepath = datadir / 'circle_{:0>7}.2D'.format(timestep)
body1 = petibmpy.read_body(filepath)
# Load the vorticity at phase angles 288 deg during the last period.
timestep = 9500
filepath = datadir / '{:0>7}.h5'.format(timestep)
wz2 = petibmpy.read_field_hdf5(filepath, name)
# Load the body coordinates at the same time.
filepath = datadir / 'circle_{:0>7}.2D'.format(timestep)
body2 = petibmpy.read_body(filepath)
# Plot the contours of the vorticity at the two time steps.
pyplot.rc('font', family='serif', size=12)
fig, (ax1, ax2) = pyplot.subplots(ncols=2, figsize=(8.0, 4.0))
def test_read_write_field_hdf5(self):
"""Test the I/O functions."""
petibmpy.write_field_hdf5(self.filepath, self.name, self.values)
values = petibmpy.read_field_hdf5(self.filepath, self.name)
self.assertTrue(numpy.allclose(values, self.values))
self.filepath.unlink()
