FreeSurfaceSampler
These examples plot the evolution of the liquid-gas interface as a liquid column
collapses and flows into the rest of the domain, and they show the velocity
magnitude (in color) as a function of interface position. At each instant plotted,
the shading of the line color represents the progression of time. Below, the scripts
for processing the data in each available format (native, netcdf, and ascii)
are shown, and these scripts are also available in the tools directory.
Note that the data accesses in the native and ascii examples can be applied to other sampler types because the format is identical. However, the NetCDF format can vary depending on the sampler type, and further detail is provided in that example.
The three examples will generate the same plot, shown here:
Native format: dam break example
To generate the data required to replicate this example, run the simulation contained in test/test_files/dam_break_godunov with the sampling format set to “native” and the sampling frequency (actually an interval) set to 30.
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import sys
AMR_WIND_PATH = '.'
sys.path.append(AMR_WIND_PATH+'/tools/')
import amrex_particle
from amrex_particle import AmrexParticleFile
loc_dir = "."
pp_dir = loc_dir + "/post_processing"
pfile = AmrexParticleFile(loc_dir)
nt = 5 + 1
out_int = 30
plt.figure()
base_color = 0.8
for n in range(nt):
pt = pfile.load(n * out_int, root_dir = pp_dir)
pt.parse_header()
pt.load_binary_data()
data = pt.df
x_oo = data.xco
z_oo = data.zco
u_oo = data.velocityx
v_oo = data.velocityy
w_oo = data.velocityz
# Reorder arrays
ind_0 = np.argsort(x_oo)
x = np.zeros(np.shape(x_oo))
z = np.zeros(np.shape(x_oo))
Vmag = np.zeros(np.shape(x_oo))
flag = np.zeros(np.shape(x_oo))
for i in range(0, len(ind_0)):
x[i]= x_oo[ind_0[i]]
z[i]= z_oo[ind_0[i]]
Vmag[i] = np.sqrt(u_oo[ind_0[i]]**2+v_oo[ind_0[i]]**2+w_oo[ind_0[i]]**2)
# When interface is not present, z location is set to zlo
flag[i] = 1.0 if z[i] > 1e-8 else 0.
# Shorten arrays (exclude points where interface not detected)
nvalid = int(flag.sum())
xshort = x[0:nvalid]
zshort = z[0:nvalid]
vshort = Vmag[0:nvalid]
color = base_color - (base_color) * (n/nt)
cstr = str(color)
plt.plot(xshort,zshort,color=cstr)
plt.scatter(xshort,zshort,c=vshort,cmap="jet",vmin=0.,vmax=2.)
plt.ylabel(r'$z$',fontsize=16)
plt.xlabel(r'$x$',fontsize=16)
plt.colorbar()
plt.savefig('plot_sampling_native.pdf',format='pdf',dpi=300,bbox_inches="tight")
NetCDF format: dam break example
To generate the data required to replicate this example, run the simulation contained in test/test_files/dam_break_godunov with the sampling format set to “netcdf” (AMR-Wind must also be compiled with NetCDF) and the sampling frequency (actually an interval) set to 30.
Because the FreeSurfaceSampler tracks the interface location, the sample points change position with time, and these changing positions are output as the “points” field. However, samplers that do not have moving sample locations do not have the “points” field in the NetCDF dataset. For static samplers, the locations are provided solely through the variable “coordinates”, which represents the initial positions of the sampler points. Otherwise, the data accesses in this example can be applied to other sampler types.
#!/usr/bin/env python3
import numpy as np
import netCDF4 as ncdf
import matplotlib.pyplot as plt
loc_dir = "."
pp_dir = loc_dir + "/post_processing"
nt = 5 + 1
out_int = 30
class SamplingFile(object):
"""Interface to Sampling NetCDF file"""
def __init__(self, sampling_file = "sampling.nc", group_name = "s1"):
"""
Args:
stats_file (path): Absolute path to the NetCDF file
"""
self.sampling_file = sampling_file
self.sampling = ncdf.Dataset(self.sampling_file)
self.fs = self.sampling["/"+group_name]
self._points = self.fs.variables["points"][:,:,:]
self._velocityx = self.fs.variables["velocityx"][:,:]
self._velocityy = self.fs.variables["velocityy"][:,:]
self._velocityz = self.fs.variables["velocityz"][:,:]
@property
def locations(self):
return self._points
@property
def vmag(self):
return np.sqrt(self._velocityx**2+self._velocityy**2+self._velocityz**2)
plt.figure()
base_color = 0.8
sampl = SamplingFile(sampling_file=pp_dir+"/sampling00000.nc", \
group_name = "fs")
for n in range(nt):
x_oo=sampl.locations[n,:,:]
Vmag_oo = sampl.vmag[n,:]
# Reorder arrays
ind_0 = np.argsort(x_oo[:,0])
x = np.zeros(np.shape(x_oo)[0])
z = np.zeros(np.shape(x_oo)[0])
Vmag = np.zeros(np.shape(x_oo)[0])
flag = np.zeros(np.shape(x_oo)[0])
for i in range(0, len(ind_0)):
x[i]= x_oo[ind_0[i],0]
z[i]= x_oo[ind_0[i],2]
Vmag[i] = Vmag_oo[ind_0[i]]
# When interface is not present, z location is set to 0
flag[i] = 1.0 if z[i] > 1e-8 else 0.
# Shorten arrays (exclude points where interface not detected)
nvalid = int(flag.sum())
xshort = x[0:nvalid]
zshort = z[0:nvalid]
vshort = Vmag[0:nvalid]
color = base_color - (base_color) * (n/nt)
cstr = str(color)
plt.plot(xshort,zshort,color=cstr)
plt.scatter(xshort,zshort,c=vshort,cmap="jet",vmin=0.,vmax=2.)
plt.ylabel('$z$',fontsize=16)
plt.xlabel('$x$',fontsize=16)
plt.colorbar()
plt.savefig('plot_sampling_netcdf.pdf',format='pdf',dpi=300,bbox_inches="tight")
ASCII format: dam break example
To generate the data required to replicate this example, run the simulation contained in test/test_files/dam_break_godunov with the sampling format set to “ascii” and the sampling frequency (actually an interval) set to 30.
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
loc_dir = "."
pp_dir = loc_dir + "/post_processing"
nt = 5 + 1
out_int = 30
plt.figure()
base_color = 0.8
for n in range(nt):
x_oo=np.genfromtxt(pp_dir+"/sampling"+str(n*out_int).zfill(5)+".txt",delimiter=' ',skip_header=5)
# Reorder array
ind_0 = np.argsort(x_oo[:,0])
x = np.zeros(np.shape(x_oo))
flag = np.zeros(np.shape(x_oo)[0])
for i in range(0, len(ind_0)):
x[i,:]= x_oo[ind_0[i],:]
# When interface is not present, z location is set to zlo
flag[i] = 1.0 if x[i,2] > 1e-8 else 0.
# Shorten arrays (exclude points where interface not detected)
nvalid = int(flag.sum())
# Columns are position (3), id, cpu, ints of struct (uid, sid, nid), field components
xshort = x[0:nvalid,0]
zshort = x[0:nvalid,2]
vshort = np.sqrt(x[0:nvalid,8]**2+x[0:nvalid,9]**2+x[0:nvalid,10]**2)
color = base_color - (base_color) * (n/nt)
cstr = str(color)
plt.plot(xshort,zshort,color=cstr)
plt.scatter(xshort,zshort,c=vshort,cmap="jet",vmin=0.,vmax=2.)
plt.ylabel('$z$',fontsize=16)
plt.xlabel('$x$',fontsize=16)
plt.colorbar()
plt.savefig('plot_sampling_ascii.pdf',format='pdf',dpi=300,bbox_inches="tight")