def draw_value_along_curve(t, f, sigma, limits, fname, title, save):
fig = plt.figure()
plt.plot(t / np.max(t), f, color='black')
plt.fill_between(t / np.max(t),
f - sigma,
f + sigma,
color='red',
alpha=0.5,
linewidth=0)
#plt.title(title)
plt.axes().set_ylim(limits)
plt.ylabel(r'$C_l^{||}$')
plt.xlabel(r'$t$')
myplt.set_font_sizes(plt.gca())
myplt.make_grid(plt.gca())
if save:
myplt.save_figure(fig, 3.5, fname)
#fig.savefig(fname, bbox_inches='tight')
plt.close(fig)
else:
plt.show()
def draw_cross_section(alldata,
gpY,
gpZ,
sep,
equilibria,
points,
title,
fname,
save,
rotation=True):
fig = plt.figure()
#plt.title(title)
plt.xlabel('$y / (H/2)$')
plt.ylabel('$z / (H/2)$')
myplt.set_font_sizes(plt.gca())
plt.axes().set_xlim([-0.02, 0.72])
plt.axes().set_ylim([-0.02, 0.72])
plt.axes().set_aspect('equal', 'box', anchor='SW')
norm, cmap = draw_quiver(alldata)
x = np.linspace(0, 0.7, 40)
y = np.linspace(0, 0.7, 40)
X, Y = np.meshgrid(x, y)
grid = np.array([X.flatten(), Y.flatten()]).T
#draw_gp(grid, gpY, gpZ, norm, cmap)
plt.plot(sep[:, 0], sep[:, 1], color='grey', linewidth=2)
if rotation:
plt.scatter(sep[:, 0][0],
sep[:, 1][0],
color='C3',
linewidth=1.5,
s=25.0,
zorder=5)
plt.scatter(sep[:, 0][-1],
sep[:, 1][-1],
facecolors='none',
edgecolors='C3',
linewidth=1.5,
s=25.0,
zorder=5)
# plt.scatter( points[0,:], points[1,:], color='C3', s=5.0, zorder=5)
if save:
myplt.save_figure(fig, 4.5, fname)
#fig.savefig(fname, bbox_inches='tight')
plt.close(fig)
else:
plt.show()
return fig
def dump_plots(alldata, Re, kappa):
fig, axes = plt.subplots(nrows=3, ncols=4, sharex=True, sharey=True, figsize=(60, 40))
#plt.suptitle(r'$Re = ' + str(Re) + r'$, $\kappa = ' + str(kappa) + r'$')
axes = axes.flatten()
i=0
for x, data, err, gp, Y, lbd in alldata:
label = r'$Ca =' + str(Y) + '$, $\lambda = ' + str(lbd) + r'$'
gpx = np.linspace(0.0, np.max(x), 100)
axes[i].errorbar(x, data, yerr=3.0*err, fmt='D',
label=label, color='C2', markeredgewidth=0.75, markeredgecolor='black', ms=3, zorder=5)
# print x
# print data
# print err
# print ""
y_fit, sigma = gp.predict(np.atleast_2d(gpx).T, return_std=True)
axes[i].plot(gpx, y_fit, color='black', zorder=4)
axes[i].fill_between(gpx, y_fit - 2*sigma, y_fit + 2*sigma, color='red', alpha=0.5, linewidth=0, zorder=3)
axes[i].grid()
axes[i].legend(loc=3, fontsize=7)
if i % 4 == 0:
axes[i].set_ylabel(r'$C_{l}$')
if i >= 8:
axes[i].set_xlabel(r'$y/R$')
myplt.set_font_sizes(axes[i])
i=i+1
# plt.xlabel('y/R', fontsize=16)
# plt.ylabel('Cl', fontsize=16)
plt.tight_layout()
plt.subplots_adjust(hspace=0.01, wspace=0.01)
#plt.show()
myplt.save_figure(fig, 7, 'soft_circle/tube_lift_soft__Re_' + str(Re) + '_kappa_' + str(kappa) + '.pdf')
plt.close(fig)
def angle(y, z, fy, fz, wy, wz, save=False, fname='', title=''):
fig = plt.figure()
N = 20
yi = np.linspace(0, 0.8, N)
zi = np.linspace(0, 0.8, N)
Y, Z = np.meshgrid(yi, zi)
ang = np.abs((fy * wy + fz * wz) / (fy * fy + fz * fz)**0.5 /
(wy * wy + wz * wz)**0.5)
# Z is a matrix of x-y values
angi = scinterp.griddata((y, z),
ang, (yi[None, :], zi[:, None]),
method='cubic')
#plt.title(title)
plt.pcolormesh(Y,
Z,
angi.reshape(Y.shape),
shading='gouraud',
cmap=plt.cm.plasma,
vmax=0.12,
vmin=0.0)
cbar = plt.colorbar()
cbar.ax.get_yaxis().labelpad = 20
cbar.ax.set_ylabel(r'$\cos(\bm{F}^{\text{diff}}_l, \bm{\omega})$',
size=9,
rotation=270)
cbar.ax.tick_params(labelsize=8)
plt.xlim(0, 0.65)
plt.ylim(0, 0.65)
plt.xlabel('$y / (H/2)$')
plt.ylabel('$z / (H/2)$')
myplt.set_font_sizes(plt.gca())
if save:
myplt.save_figure(fig, 3, fname, dpi=600)
#plt.close(fig)
else:
plt.show()
err_Cls.append(0)
return Cls, err_Cls
alldata = []
#alldata.append( get_forces("/home/alexeedm/extern/daint/project/alexeedm/focusing_square/case_5_0.08__80_20_1.5__") + ("Present", "o") )
alldata.append( get_forces("/home/alexeedm/extern/daint/project/alexeedm/focusing_square/case_5_0.0788__160_20_3.0__", 2.3) + ("Present", "D") ) # 2244!
#alldata.append( get_forces_cubism("/home/alexeedm/extern/daint/scratch/cubism-square-lift-2d/case_4_0_") + ("Present", "o") )
#alldata.append( get_forces_cubism("/home/alexeedm/extern/daint/scratch/cubism-square-lift-2d/case_4_0_") + ("Present", "o") )
#alldata.append( get_forces_cubism("/home/alexeedm/extern/daint/project/alexeedm/cubism-square-lift-2d/case_yetwider_8_0_") + ("Present", "o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/project/alexeedm/focusing_square/case_5_0.02144__80_10_1.5__", 1.1704) + ("Present", "o") )
print(alldata)
#print Cls
#print err_Cls
myplt.set_pgf_backend()
fig = plt.figure()
positions = np.linspace(0.0, 0.72, 19)
#positions = np.arange(0.0, 0.8, 0.1)
dump_plots(positions, alldata, nakagawa, dicarlo)
myplt.save_figure(fig, 3, 'duct_lift_coefficients.pdf')
plt.close()
if kappa == 0.15:
fmt = 'o'
if kappa == 0.22:
fmt = 's'
if kappa == 0.3:
fmt = 'D'
#plt.plot(data[0,:], data[2,:], 'o', label=r'$Re = ' + str(Re) + r', \kappa = ' + str(kappa) + r'$')
plt.errorbar(data[0,:], transform(data[0,:], data[1,:], Re, kappa, res.x), yerr=transform(data[0,:], data[2,:], Re, kappa, res.x),
fmt=fmt, color=c, ms=3, linewidth=1, label=r'$Re = ' + str(Re) + r', \kappa = ' + str(kappa) + r'$')
plt.legend()
ax = plt.gca()
ax.set_ylabel(r'$ \dfrac{C_{l}}{y} \times Re^{1/3} \left( 1 + \dfrac{7.894}{Re \left( 1 - \kappa - y \right)} \right)$')
ax.set_xlabel(r'$y$')
myplt.set_font_sizes(ax)
myplt.save_figure(fig, 4.1, 'tube_lift_collapse.pdf')
err = 0.5 * (np.abs(data[:, 4] - data[:, 3]) +
np.abs(data[:, 5] - data[:, 3]))
#plt.errorbar(data[:,0], data[:,3], yerr=err, fmt=fmt, color=c, ms=3, linewidth=1, label=r'$Ca = ' + str(Ca) + r', \lambda = ' + str(lbd) + r'$')
plt.plot(data[:, 0],
-data[:, 3],
fmt,
color=c,
ms=4,
linewidth=1,
label=r'$ \begin{aligned}Ca &= ' + str(Ca) +
r',\\ \lambda &= ' + str(lbd) + r'\end{aligned}')
# print(data)
# print("")
plt.legend(ncol=3, handletextpad=0.01)
ax = plt.gca()
ax.set_ylabel(r'$W = \int_{\bm S} C^{||}_l \, ds$')
ax.set_xlabel(r'$Re$')
myplt.set_font_sizes(ax)
myplt.set_figure_size(fig, 4.5)
y = plt.ylim()
plt.ylim(-0.018, y[1])
#plt.show()
myplt.save_figure(fig, 4.5, 'tube_soft_lift_work.pdf')
draw_value_along_curve(t, f, fsigma, '-')
# modified
moddata = pickle.load(
open(folder + 'modrotation' + str(int(Re)) + '.pckl', 'rb'))
#print(moddata)
coo = moddata[:, 0:2]
idx = np.argsort(np.arctan2(coo[:, 1], coo[:, 0]))
coo = coo[idx, :]
fym, eym, fzm, ezm = [moddata[idx, i] for i in [4, 5, 6, 7]]
gpym = gaussian_fit(coo, fym, eym)
gpzm = gaussian_fit(coo, fzm, ezm)
fmod, mods = val_along_curve(gpym, gpzm, coo)
lengths = np.empty(coo.shape[0])
lengths[0] = 0.0
for i in range(1, coo.shape[0]):
lengths[i] = lengths[i - 1] + np.sqrt(
np.dot(coo[i - 1] - coo[i], coo[i - 1] - coo[i]))
print(lengths)
draw_value_along_curve(lengths, fmod, mods, ':')
myplt.save_figure(fig, 3.5, 'square/mod_rotation_Re_100.pdf')
def plot_equilibrium(rot, suffix):
# x is kappa, free rotation
fig = plt.figure()
for Re, style in [(50, '--D'), (100, '--o'), (200, '--s')]:
idxs = np.where((intersections[:, 4] == rot)
& (intersections[:, 2] == Re))
plt.errorbar(intersections[idxs, 3],
intersections[idxs, 0],
yerr=intersections[idxs, 1],
label=r'$Re = ' + str(Re) + r'$',
fmt=style,
markeredgewidth=0.75,
markeredgecolor='black',
ms=3,
zorder=2,
linewidth=1.0)
plt.legend(labelspacing=0.2)
#plt.xscale('log')
plt.xlabel(r'$\kappa$')
plt.ylabel(r'$Eq/y$')
myplt.set_font_sizes(plt.gca())
myplt.make_grid(plt.gca())
if rot == 1:
y = plt.ylim()
plt.ylim(y[0], 0.46)
plt.tight_layout()
myplt.save_figure(fig, 3, 'tube_lift_rigid_' + suffix + '_kappa.pdf')
plt.close(fig)
# x is Re, no rotation
fig = plt.figure()
for kappa, style in [(0.3, '--D'), (0.22, '--o'), (0.15, '--s')]:
idxs = np.where((intersections[:, 4] == rot)
& (intersections[:, 3] == kappa))
plt.errorbar(intersections[idxs, 2],
intersections[idxs, 0],
yerr=intersections[idxs, 1],
label=r'$\kappa = ' + str(kappa) + r'$',
fmt=style,
markeredgewidth=0.75,
markeredgecolor='black',
ms=3,
zorder=2,
linewidth=1.0)
plt.legend(labelspacing=0.2)
#plt.xscale('log')
plt.xlabel(r'$Re$')
plt.ylabel(r'$Eq/R$')
myplt.set_font_sizes(plt.gca())
myplt.make_grid(plt.gca())
if rot == 0:
y = plt.ylim()
plt.ylim(y[0], 0.75)
plt.tight_layout()
myplt.save_figure(fig, 3, 'tube_lift_rigid_' + suffix + '_re.pdf')
plt.close(fig)
def dump_plots(alldata):
fig, axes = plt.subplots(nrows=3,
ncols=3,
sharex=True,
sharey='row',
figsize=(50, 38))
#plt.suptitle(r'$Re = ' + str(Re) + r'$, $\kappa = ' + str(kappa) + r'$')
axes = axes.flatten()
i = 0
for x, data, err, gp, Re, kappa, rot, w, errw in alldata:
label = (r'$Re = ' + str(Re) + r', \kappa = ' + str(kappa) +
r'$') if rot == 0.0 else ''
fmt = 'D' if rot == 0.0 else 'o'
gpx = np.linspace(0.0, np.max(x), 100)
axes[i].errorbar(x,
data,
yerr=3.0 * err,
fmt=fmt,
label=label,
color='C2',
markeredgewidth=0.75,
markeredgecolor='black',
ms=3,
zorder=3)
# print x
# print data
# print err
# print ""
y_fit, sigma = gp.predict(np.atleast_2d(gpx).T, return_std=True)
axes[i].plot(gpx, y_fit, linewidth=0.75, color='black')
axes[i].fill_between(gpx,
y_fit - sigma,
y_fit + sigma,
color='red',
alpha=0.5,
linewidth=0,
zorder=2)
axes[i].grid()
leg = axes[i].legend(loc=3,
fontsize=7,
handlelength=0,
handletextpad=0,
markerscale=0)
for item in leg.legendHandles:
item.set_visible(False)
if i % 3 == 0:
axes[i].set_ylabel(r'$C_{l}$')
if i >= 6:
axes[i].set_xlabel(r'$y/R$')
myplt.set_font_sizes(axes[i])
myplt.make_grid(axes[i])
if rot == 1.0:
i = i + 1
# plt.xlabel('y/R', fontsize=16)
# plt.ylabel('Cl', fontsize=16)
plt.tight_layout()
plt.subplots_adjust(hspace=0.01, wspace=0.01)
#plt.show()
myplt.save_figure(fig, 6.5, 'tube_lift_rigid.pdf')
plt.close(fig)
cpuref = roofline(68, 998) gpuref = roofline(732, 8524) myplt.set_pgf_backend() fig = plt.figure() draw_one(gpu[0], gpu[1], '-', 'C2', 1.5, 'Nvidia Tesla P100 16GB') draw_one(cpu[0], cpu[1], '-', 'royalblue', 1.5, 'Intel Xeon E5-2690 v3') draw_one(gpuref[0], gpuref[1], ':', 'C2', 0.75, '') draw_one(cpuref[0], cpuref[1], ':', 'royalblue', 0.75, '') prepare_plot(plt.gca()) plt.legend() myplt.save_figure(fig, 3, 'new_roofline.pdf') plt.close(fig) xeon = roofline(402.503e-3 * 72, 2467.047e-3 * 103) amd = roofline(306.105e-3 * 72, 1368.974e-3 * 103) gpu = roofline(1846.646e-3 * 72, 25507.547e-3 * 90) xeonref = roofline(51.2, 332.8) amdref = roofline(51.2, 332.8) # intentionally same gpuref = roofline(250, 3935) myplt.set_pgf_backend() fig = plt.figure() draw_one(gpu[0], gpu[1], '-', 'C2', 1.5, 'Nvidia Tesla K20X') draw_one(xeon[0], xeon[1], '-', 'royalblue', 1.5, 'Intel Xeon E5-2670')
intersections = np.empty((0, 4))
for x, d, err, gp, Y, lbd in processed:
x0, elo, ehi = intersection(gp)
intersections = np.vstack( (intersections, np.array([x0, 0.5*(elo+ehi), Y, lbd])) )
#%%
for lbd, style in [(1.0, '--D'), (5.0, '--o'), (25.0, '--s')]:
idxs = np.where(intersections[:,3] == lbd)
plt.errorbar(intersections[idxs, 2], intersections[idxs, 0], yerr=intersections[idxs, 1], label=r'$\lambda=' + str(lbd) + r'$',
fmt=style, markeredgewidth=0.75, markeredgecolor='black', ms=3, zorder=2, linewidth=1.0)
#TODO: eqiulibrium vs size and vs Reynolds
plt.legend()
plt.xscale('log')
plt.xlabel(r'$Ca$')
plt.ylabel(r'$C_0/R$')
myplt.make_grid(plt.gca())
plt.tight_layout()
myplt.save_figure(fig, 3, 'soft_circle/tube_lift_soft__intersection_' + str(Re) + '_kappa_' + str(kappa) + '.pdf')
plt.close(fig)
a= alsdfkja
#alldata.append( get_forces(folder + "case_newcode_ratio_5_0.05177__110_25_2.0__") + (r'Present', "D", 'C2') )
alldata.append(
get_forces(folder + "case_0.14602_0_0.15__160_43.2253_3.0__") +
(r'Present', "D", 'C2'))
#alldata.append( get_forces(folder + "case_0.14602_1_0.15__160_43.2253_3.0__") + (r'Inhibited rotation', "D", 'C3') )
#alldata.append( get_forces(folder + "case_newcode_ratio_5_0.14516__160_43.0935_3.0__") + (r'$\gamma = 43$', "-o") )
#alldata.append( get_forces(folder + "case_newcode_ratio_5_0.16335__160_45.7969_3.0__") + (r'$\gamma = 45$', "-o") )
#alldata.append( get_forces(folder + "case_newcode_ratio_5_0.22234__160_53.6651_3.0_") + (r'$\gamma = 54$', "-o") )
#alldata.append( get_forces(folder + "case_newcode_ratio_5_0.29040__160_61.4946_3.0__") + (r'$\gamma = 61$', "-o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/scratch/focusing_soft/case_noforce_0.1_0.2__80_20_1.5__") + (r'$\lambda = 0.2$', "-o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/scratch/focusing_soft/case_noforce_0.1_1.0__80_20_1.5__") + (r'$\lambda = 1.0$', "-o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/scratch/focusing_soft/case_noforce_0.1_5.0__80_20_1.5__") + (r'$\lambda = 5.0$', "-o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/scratch/focusing_soft/case_noforce_0.1_20.0__80_20_1.5__") + (r'$\lambda = 20.0$', "-o") )
#alldata.append( get_forces("/home/alexeedm/extern/daint/scratch/focusing_soft/case_noforce_0.1_40.0__80_20_1.5__") + (r'$\lambda = 40.0$', "-o") )
print(alldata)
#print Cls
#print err_Cls
myplt.set_pgf_backend()
fig = plt.figure()
positions = np.linspace(0.0, 0.7, 8)
dump_plots(positions, alldata, ref)
myplt.save_figure(fig, 3, 'tube_lift_coefficients.pdf')
plt.close()