def setUp(self):
self.filename_prefix = os.path.join(os.path.dirname(__file__), 'test_data_miranda/plot.mir')
self.reader = mir.MirandaReader(self.filename_prefix, periodic_dimensions=(False,True,True))
self.lo = (0, 0, 0)
self.hi = (319, 63, 0)
self.reader.sub_domain = (self.lo, self.hi)
self.reader.step = 0
def setUp(self):
self.filename_prefix = os.path.join(os.path.dirname(__file__),
'test_data_miranda/plot.mir')
self.serial_reader = mir.MirandaReader(self.filename_prefix,
periodic_dimensions=(False,
True,
True))
self.serial_reader.step = 0
self.comm = MPI.COMM_WORLD
self.num_ghosts = (1, 1, 1)
self.reader = pdr.ParallelDataReader(
MPI.COMM_WORLD,
mir.MirandaReader(self.filename_prefix,
periodic_dimensions=(False, True, True)),
num_ghosts=self.num_ghosts)
self.reader.step = 0
self.lo, self.hi = self.reader.interior_chunk
def plot_set2(tsteps, tvec, path):
reader = mir.MirandaReader(path,
periodic_dimensions=(False, True, True),
verbose=True)
print("Domain Size: {} ".format(reader._domain_size))
print("Variables available: {}".format(reader.varNames))
Nx, Ny, Nz = reader._domain_size
W = np.zeros(len(tsteps))
t_legend = []
for tind, step in enumerate(tsteps):
##################################
#Reading in full fields to figure out where subdomain and interface are
reader.setStep(step)
reader.setSubDomain(((0, 0, 0), (Nx - 1, Ny - 1, Nz - 1)))
print("Figuring out subdomain at step {}".format(step))
YN2 = np.squeeze(np.array(reader.readData('Ideal1_01')))
YO2 = np.squeeze(np.array(reader.readData('Ideal1_02')))
YSF6 = np.squeeze(np.array(reader.readData('Ideal1_03')))
YAc = np.squeeze(np.array(reader.readData('Ideal1_04')))
YHeavy = YSF6 + YAc
M = (YN2 / M_N2 + YO2 / M_O2 + YSF6 / M_SF6 + YAc / M_Ac)**(-1)
#Find inner mixing zone (IMZ)
IMZ_thresh = 0.9
XHeavy = M / M_Heavy * YHeavy
XHeavy_bar = np.mean(np.mean(XHeavy, axis=2), axis=1)
IMZ_crit = 4 * XHeavy_bar * (1 - XHeavy_bar) - IMZ_thresh
for ind in range(len(IMZ_crit)):
if IMZ_crit[ind] >= 0:
IMZ_lo = ind
break
for ind in range(len(IMZ_crit)):
ind2 = Nx - ind - 1
if IMZ_crit[ind2] >= 0:
IMZ_hi = ind2
break
IMZ_mid = np.argmax(IMZ_crit)
middle_selection = 0.20 #select middle 20% of domain in x
x1 = IMZ_mid - int(middle_selection / 2 * Nx)
x2 = min(IMZ_mid + int(middle_selection / 2 * Nx), Nx - 1)
reader.setSubDomain(((x1, 0, 0), (x2, Ny - 1, Nz - 1)))
# Get coordinates based on subdomain
x, y, z = reader.readCoordinates()
x = x / 100.0 #convert from cm-> m
y = y / 100.0
z = z / 100.0
nx = reader.chunk[0][1] - reader.chunk[0][0]
ny = reader.chunk[1][1] - reader.chunk[1][0]
nz = reader.chunk[2][1] - reader.chunk[2][0]
##################################
# Reading in on subdomain
reader.setStep(step)
print("reading in Mass Fraction at step {}.".format(step))
YN2 = np.squeeze(np.array(reader.readData('Ideal1_01')))
YO2 = np.squeeze(np.array(reader.readData('Ideal1_02')))
YSF6 = np.squeeze(np.array(reader.readData('Ideal1_03')))
YAc = np.squeeze(np.array(reader.readData('Ideal1_04')))
YHeavy = YSF6 + YAc
plt.figure()
plt.title("t = {} ms".format(step * 1e-1))
plt.pcolor(1000 * x[:, :, int(Nz / 2)],
1000 * y[:, :, int(Nz / 2)], YHeavy[:, :, int(Nz / 2)])
plt.xlabel('x [mm]')
plt.ylabel('y [mm]')
ax = plt.gca()
ax.set_aspect('equal')
plt.colorbar()
plt.clim([0, 1])
#Format plots
print("Formatting Plots")
for ind in plt.get_fignums():
plt.figure(ind)
plt.tight_layout()
return None
def plot_set2(tsteps, tvec, path):
reader = mir.MirandaReader(path,
periodic_dimensions=(False, True, True),
verbose=True)
print("Domain Size: {} ".format(reader._domain_size))
print("Variables available: {}".format(reader.varNames))
Nx, Ny, Nz = reader._domain_size
W = np.zeros(len(tsteps))
t_legend = []
for tind, step in enumerate(tsteps):
##################################
#Reading in full fields to figure out where subdomain and interface are
reader.setStep(step)
reader.setSubDomain(((0, 0, 0), (Nx - 1, Ny - 1, Nz - 1)))
print("Figuring out subdomain at step {}".format(step))
YN2 = np.squeeze(np.array(reader.readData('Ideal1_01')))
YO2 = np.squeeze(np.array(reader.readData('Ideal1_02')))
YSF6 = np.squeeze(np.array(reader.readData('Ideal1_03')))
YAc = np.squeeze(np.array(reader.readData('Ideal1_04')))
YHeavy = YSF6 + YAc
M = (YN2 / M_N2 + YO2 / M_O2 + YSF6 / M_SF6 + YAc / M_Ac)**(-1)
#Find inner mixing zone (IMZ)
IMZ_thresh = 0.9
XHeavy = M / M_Heavy * YHeavy
XHeavy_bar = np.mean(np.mean(XHeavy, axis=2), axis=1)
IMZ_crit = 4 * XHeavy_bar * (1 - XHeavy_bar) - IMZ_thresh
for ind in range(len(IMZ_crit)):
if IMZ_crit[ind] >= 0:
IMZ_lo = ind
break
for ind in range(len(IMZ_crit)):
ind2 = Nx - ind - 1
if IMZ_crit[ind2] >= 0:
IMZ_hi = ind2
break
IMZ_mid = np.argmax(IMZ_crit)
middle_selection = 0.40 #select middle 20% of domain in x
x1 = IMZ_mid - int(middle_selection / 2 * Nx)
x2 = min(IMZ_mid + int(middle_selection / 2 * Nx), Nx - 1)
reader.setSubDomain(((x1, 0, 0), (x2, Ny - 1, Nz - 1)))
# Get coordinates based on subdomain
x, y, z = reader.readCoordinates()
x = x / 100.0 #convert from cm-> m
y = y / 100.0
z = z / 100.0
nx = reader.chunk[0][1] - reader.chunk[0][0]
ny = reader.chunk[1][1] - reader.chunk[1][0]
nz = reader.chunk[2][1] - reader.chunk[2][0]
##################################
# Reading in on subdomain
reader.setStep(step)
print("reading in Mass Fraction at step {}.".format(step))
YN2 = np.squeeze(np.array(reader.readData('Ideal1_01')))
YO2 = np.squeeze(np.array(reader.readData('Ideal1_02')))
YSF6 = np.squeeze(np.array(reader.readData('Ideal1_03')))
YAc = np.squeeze(np.array(reader.readData('Ideal1_04')))
YHeavy = YSF6 + YAc
print("reading in density at step {}.".format(step))
density = 1e3 * np.squeeze(np.array(reader.readData('density')))
print("reading in pressure at step {}.".format(step))
pressure = 1e-1 * np.squeeze(np.array(reader.readData('pressure')))
#Calculating Stats
print("Computing Diffusion Properties")
rho_bar = np.mean(np.mean(density, axis=2), axis=1)
Cp = YN2 * Cp_N2 + YO2 * Cp_O2 + YSF6 * Cp_SF6 + YAc * Cp_Ac
Cv = YN2 * Cv_N2 + YO2 * Cv_O2 + YSF6 * Cv_SF6 + YAc * Cv_Ac
gamma = Cp / Cv
M = (YN2 / M_N2 + YO2 / M_O2 + YSF6 / M_SF6 + YAc / M_Ac)**(-1)
T = M * pressure / (density * Ru)
c = (gamma * pressure / density)**0.5
del YAc, gamma
#Find inner mixing zone (IMZ)
IMZ_thresh = 0.9
XHeavy = M / M_Heavy * YHeavy
XHeavy_bar = np.mean(np.mean(XHeavy, axis=2), axis=1)
IMZ_crit = 4 * XHeavy_bar * (1 - XHeavy_bar) - IMZ_thresh
for ind in range(len(IMZ_crit)):
if IMZ_crit[ind] >= 0:
IMZ_lo = ind
break
for ind in range(len(IMZ_crit)):
ind2 = nx - ind - 1
if IMZ_crit[ind2] >= 0:
IMZ_hi = ind2
break
IMZ_mid = np.argmax(IMZ_crit)
#Mole Fraction Variance
XHeavy_prime = XHeavy - XHeavy_bar.reshape((nx, 1, 1))
XHeavy_variance = np.mean(np.mean(XHeavy_prime**2, axis=2), axis=1)
#Compute Turbulent Mach Number
print("reading in velocity at step {}.".format(step))
velocity = np.zeros((3, nx, ny, nz))
velocity[0, :, :, :] = 1e-2 * np.squeeze(
np.array(reader.readData('velocity-0')))
velocity[1, :, :, :] = 1e-2 * np.squeeze(
np.array(reader.readData('velocity-1')))
velocity[2, :, :, :] = 1e-2 * np.squeeze(
np.array(reader.readData('velocity-2')))
u_tilde = np.mean(np.mean(velocity[0, :, :, :] * density, axis=2),
axis=1) / np.mean(np.mean(density, axis=2), axis=1)
u_doubleprime = velocity[0, :, :, :] - u_tilde.reshape((nx, 1, 1))
#Density Spectra
t_legend.append("t = {} ms".format(step * 1e-1))
k_rad, rho_spec_rad = fh.radial_spectra(
x[:, 0, 0], y[0, :, 0], z[0, 0, :],
density[IMZ_lo:IMZ_hi + 1, :, :])
plt.figure(2)
plt.loglog(k_rad, rho_spec_rad)
plt.xlabel('Radial Wavenumber [m-1]')
plt.ylabel("Density spectra")
#Energy Spectra
energy_for_spectra = density * u_doubleprime / (np.reshape(
rho_bar, (nx, 1, 1)))**0.5
k_rad, rhoU_spec_rad = fh.radial_spectra(
x[:, 0, 0], y[0, :, 0], z[0, 0, :],
energy_for_spectra[IMZ_lo:IMZ_hi + 1, :, :])
plt.figure(3)
plt.loglog(k_rad, rhoU_spec_rad)
plt.xlabel('Radial Wavenumber [m-1]')
plt.ylabel("Energy Spectra")
#Format plots
print("Formatting Plots")
t_legend.append("-3/2 slope")
for ind in plt.get_fignums():
plt.figure(ind)
plt.loglog(k_rad, 1e2 * k_rad**(-1.5), 'k--')
plt.legend(t_legend)
plt.tight_layout()
return None
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable, axes_size
#Local Modules
import floatpy.readers.miranda_reader as mir
# Set up default plotting
params = {'legend.fontsize': 14, 'legend.handlelength': 2, 'font.size': 16}
matplotlib.rcParams.update(params)
if __name__ == '__main__':
#Read in a file and plot something
reader = mir.MirandaReader(
"/home/jrwest/Research/FloATPy_moving_grid/data/Tritschler/RM_CTR_3D_64/plot.mir",
periodic_dimensions=(False, True, True),
verbose=True)
print("Domain Size: {} ".format(reader._domain_size))
x, y, z = reader.readCoordinates()
print("Variables available: {}".format(reader.varNames))
tsteps = (15, 20, 22, 27, 50)
for step in tsteps:
reader.setStep(step)
YN2 = np.array(reader.readData('Ideal1_01'))
YO2 = np.array(reader.readData('Ideal1_02'))
YSF6 = np.array(reader.readData('Ideal1_03'))