def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
y = parsed_args.slice_yplus
if y:
print('Hello! ', y)
in_dir = "/home/mknorps/Projects/ForPhD/SPECTRAL_from2011/FRACTAL/"
out_dir = "/home/mknorps/Projects/ForPhD/SPECTRAL_from2011/FRACTAL/slices/"
f_min = 880
f_max = 900
for ptype in range(4):
for i in range(f_min, f_max):
input_file = 'particles_0{}'.format(i)
output_file_core = "slice_FRACTAL_center_{}_{}".format(
p.StList2[ptype], i)
cut_with_halo(in_dir,
out_dir,
input_file,
output_file_core,
ptype,
yplus=145)
def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
y = parsed_args.slice_yplus
if y:
print('Hello! ', y)
s.write_to_file(f.file_path_write)
s.symmetrise(f.file_path_write, f.file_path_symm)
d.draw_diss_tot(f.file_path_symm, f.file_path_main + "diss.pdf")
d.draw_diss_model(f.file_path_symm, f.file_path_main + "diss_model.pdf")
def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
y = parsed_args.slice_yplus
if y:
print('Hello! ', y)
#s.write_to_file(f.file_path_write)
data = d.DrawU2sgs()
data.draw_u2sgs(f.file_path_main + "u2sgs.pdf")
data.draw_ksgs(f.file_path_main + "ksgs.pdf")
data.draw_sigma_check(f.file_path_main + "sigma_check.pdf")
def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
# ct = parsed_args.particle_type
#ts.write_to_file(f.file_path_write, symm=False)
#ts.write_to_file(f.file_path_write_symm)
data = pd.read_csv(f.file_path_write)
data_symm = pd.read_csv(f.file_path_write_symm)
td.draw_tau(data, f.data_path + "test.pdf")
td.draw_tau_symm(data_symm, f.data_path + "model_tausg_symm.pdf")
optimal = ts.optimize_tau_fluid(f.file_path_write_symm)
def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
y = parsed_args.slice_yplus
if y:
print('Hello! ', y)
# for key in f.prange.keys():
# c.write_to_file(f.file_path_write+key+".csv",key)
data = draw.Draw()
# data.draw_ur(f.file_path_main + "ur.pdf")
# data.draw_urnorm2(f.file_path_main + "urnorm2.pdf")
data.draw_alpha(f.file_path_main + "alpha.pdf")
def run_project(args):
opt = options.Options()
parsed_args = opt.parse(args[1:])
y = parsed_args.slice_yplus
d1 = 2**(-1 / 3)
d2 = -2**(-1 / 3)
w3_LES = fractal_interpolation(at.w(Ufx, d1, d2, 3), len(Ufx))
w3_from_resampled = fractal_interpolation(at.w(Ux_resampled, d1, d2, 3),
len(Ufx))
label = {0: '$W^{3}$: filtered DNS', 1: '$W^{3}$: resampled DNS'}
draw_fractal('LES_and_resampled.pdf',
w3_LES,
w3_from_resampled,
label=label)
draw_fractal('LES_and_DNS.pdf')
ek = kinetic_energy(Ux, Ufx, Ux_resampled, w3_LES['y'],
w3_from_resampled['y'])
fft = fourier_transform(Ux, Ufx, Ux_resampled, w3_LES['y'],
w3_from_resampled['y'])
plt.figure(figsize=(8, 4))
sns.violinplot(data=list(fft.values())[:3])
plt.xticks(plt.xticks()[0], fft.keys())
plt.tight_layout()
plt.savefig("fractal_violinplot_ftt.pdf")
for_box = {
'DNS': Ux,
'filtered DNS': Ufx,
'$W^{3}$: filtered': w3_LES['y'],
'resampled DNS': Ux_resampled,
'$W^{3}$: resampled': w3_from_resampled['y']
}
colors = {
i: v
for i, v in enumerate(
['lightgrey', 'lightgrey', 'darkorange', 'lightgrey', 'slateblue'])
}
plt.figure(figsize=(8, 4))
sns.violinplot(data=list(for_box.values()),
orient='v',
palette=colors,
inner='quartile',
bw='silverman')
plt.xticks(plt.xticks()[0], for_box.keys())
plt.tight_layout()
plt.savefig("fractal_violinplot.pdf")
plt.figure(figsize=(8, 4))
sns.boxplot(data=list(for_box.values()))
plt.xticks(plt.xticks()[0], for_box.keys())
plt.tight_layout()
plt.savefig("fractal_boxplot.pdf")