def get_vtus(fmts, folder='rstf', sync=False):
files = [
glob('../stream/' + folder + '/' + fmt + '_????.vtu') for fmt in fmts
]
inds = [
np.argsort(np.array([float(fn[-8:-4]) for fn in filel]))
for filel in files
]
if not sync:
print('Returning files:')
print([filel[int(ind[-1])] for ind, filel in zip(inds, files)])
vtus = [
fastvtulib.get_structured_vtu(filel[int(ind[-1])])
for ind, filel in zip(inds, files)
]
maxtime = None
return vtus, maxtime
else:
def get_times(fmt):
times = []
out_file = '../stream/' + folder + '/' + fmt + '.result'
with open(out_file) as fout:
for line in fout:
if line[:4] == 'Time':
times.append(float(line.rstrip('\n').split()[-1]))
times = np.array(times)
return np.unique(times - times[0])
n_jobs = len(fmts)
timess = Parallel(n_jobs=n_jobs)(delayed(get_times)(fmt)
for fmt in fmts)
maxtime = np.min([np.max(times) for times in timess])
inds_times = [
int(np.where(times == maxtime)[0][0]) for times in timess
]
vtus = [
fastvtulib.get_structured_vtu(filel[int(ind[ind_t])])
for ind, ind_t, filel in zip(inds, inds_times, files)
]
for vtu in vtus:
vtu.rawdata_dict['vel'] = np.sqrt(
vtu.rawdata_dict['aiflow'][:, 0]**2. +
vtu.rawdata_dict['aiflow'][:, 1]**2.)
return vtus, maxtime
def vtu_to_φ_and_ε(fn,
x,
y_pts,
obs_angles,
E_transmit=np.array([1.0e3, 0]),
scatter_aniso=1.0e-1,
freq=300.0e6):
vtu = fastvtulib.get_structured_vtu(fn)
y = np.linspace(np.min(vtu.coords[:, 1]), np.max(vtu.coords[:, 1]), y_pts)
x = np.ones((y_pts, )) * x
test_p = vtu.get_pts_2d(['fabric 1'], x, y)
y_valid = y[~np.isnan(test_p['fabric 1'])]
y = np.linspace(np.min(y_valid), np.max(y_valid), y_pts)[::-1]
depths = y[0] - y
pts = vtu.get_pts_2d(
['fabric 1', 'fabric 2', 'fabric 3', 'fabric 4', 'fabric 5', 'temp'],
x, y)
A_xy = np.zeros((len(y), 2, 2), dtype=np.complex128)
A_xy[:, 0, 0] = pts['fabric 1']
A_xy[:, 1, 1] = 1.0 - pts['fabric 1'] - pts['fabric 2']
A_xy[:, 1, 0] = pts['fabric 5']
A_xy[:, 0, 1] = pts['fabric 5']
φ, ε = fujita_model.φ_and_ε(A_xy, T=pts['temp'])
if fn == '../stream/rstf/s_ftw_rc2.0e-3_oop0.0_bm0.0_0001.vtu':
with open('deforming_fabric.csv', 'w') as fout:
fout.write('depth[m] epsilon_x epsilon_y\n')
for i in range(len(depths)):
fout.write('{:f} {:f} {:f}\n'.format(depths[i], np.real(ε[i,
0]),
np.real(ε[i, 1])))
# Anisotropic scattering
S_aniso = np.zeros((y.shape[0], 2, 2))
S_aniso[:, 0, 0] = 1.0e0
S_aniso[:, 1, 1] = scatter_aniso
S_aniso = S_aniso * 1.0e-4
return y, fujita_model.fujita_model_εS(E_transmit, depths, obs_angles, ε,
S_aniso, φ, freq)
def idealized_init():
# We want to find the filename for the highest index where we have all 3
files = glob('../stream/rstf/deform2e-3_????.vtu')
inds = np.argsort(np.array([float(fn[-8:-4]) for fn in files]))
files = [files[i] for i in inds]
out_file = '../stream/relaxed_stream_tall_fabric/deform_diffuse.result'
vtu = fastvtulib.get_structured_vtu(files[-1])
vtu.rawdata_dict['vel'] = np.sqrt(vtu.rawdata_dict['aiflow'][:, 0]**2. +
vtu.rawdata_dict['aiflow'][:, 1]**2.)
tri = Triangulation(
np.array([rc[0] + 100000. for rc in vtu.raw_coords[:, 0]]) / 1000.,
np.array([rc[1] for rc in vtu.raw_coords[:, 0]]), vtu.simptt)
gs = gridspec.GridSpec(2,
3,
width_ratios=(1., 1., 1.),
height_ratios=(1, 0.1),
hspace=0.55,
wspace=0.1,
left=0.1,
bottom=0.2,
top=0.9,
right=0.98)
fig = plt.figure(figsize=(7.5, 3.0))
axes = [fig.add_subplot(gs[0, i]) for i in range(3)]
cbr_axes = [fig.add_subplot(gs[1, i]) for i in range(3)]
cm1 = axes[0].tricontourf(tri,
vtu.rawdata_dict['aiflow'][:, 0],
cmap='Reds',
levels=np.linspace(0.0, 10., 101),
extend='max')
levels = [1000, 5000, 10000, 50000, 100000]
CS = axes[0].tricontour(tri,
vtu.rawdata_dict['age'],
colors='k',
levels=levels,
linewidths=0.5)
fmt = {level: '{:d} kyr'.format(level // 1000) for level in levels}
axes[0].clabel(CS, CS.levels, inline=True, fmt=fmt, fontsize=8)
for c in cm1.collections:
c.set_edgecolor("face")
# axes[0].set_title('Speed', fontsize=bfs)
# axes[1].set_title('Vertical fabric', fontsize=bfs)
# axes[2].set_title('Woodcock Parameter', fontsize=bfs)
axes[0].set_xlim(0, 175)
axes[0].set_xticks([0., 50., 100., 150.])
cm2 = axes[1].tricontourf(tri,
vtu.rawdata_dict['fabric 2'],
cmap='BrBG',
norm=anisolib.fab_norm,
levels=np.linspace(0, 1, 101),
extend='neither')
for c in cm2.collections:
c.set_edgecolor("face")
axes[1].set_xlim(0, 175)
axes[1].set_xticks([0., 50., 100., 150.])
k = woodcock(vtu.rawdata_dict)
cm3 = axes[2].tricontourf(tri,
k,
cmap='PuOr',
levels=np.linspace(0, 2, 201),
extend='max')
for c in cm3.collections:
c.set_edgecolor("face")
axes[2].set_xlim(0, 175)
axes[2].set_xticks([0., 50., 100., 150.])
cbr = plt.colorbar(cm1,
cax=cbr_axes[0],
orientation='horizontal',
ticks=(0, 5., 10.))
cbr.set_label(label=r'$v_x$ (m a$^{-1})$', size=fs)
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
cbr = plt.colorbar(cm2,
cax=cbr_axes[1],
orientation='horizontal',
ticks=(0, 1. / 3., 2. / 3., 1.0))
cbr.set_label(label=r'$a^{(2)}_{zz}$', size=fs)
cbr.ax.set_xticklabels(['0', r'$\frac{1}{3}$', r'$\frac{2}{3}$', '1'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
cbr = plt.colorbar(cm3,
cax=cbr_axes[2],
orientation='horizontal',
ticks=(0, 1, 2))
cbr.set_label(label=r'Woodcock $k$', size=fs)
cbr.ax.set_xticklabels(['0', '1', '2'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
axes[0].set_ylabel('Height (m)', fontsize=fs)
for ax in axes[1:]:
ax.set_yticklabels(['' for tick in ax.get_yticklabels()])
axes[1].set_xlabel('Distance (km)', fontsize=fs)
for letter, ax in zip('abc', axes):
ax.text(0.05, 0.85, letter, transform=ax.transAxes, fontsize=bfs)
ax.tick_params(axis='both', which='major', labelsize=fs)
ax.set_ylim(0, 2250)
fig.savefig('../plots/idealized_init.png', dpi=300)
fig.savefig('../plots/poster_idealized_init.png',
dpi=300,
transparent=True)
def idealized_init_zoom():
# We want to find the filename for the highest index where we have all 3
files = glob('../stream/rstf/deform2e-5_????.vtu')
inds = np.argsort(np.array([float(fn[-8:-4]) for fn in files]))
files = [files[i] for i in inds]
vtu = fastvtulib.get_structured_vtu(files[-1])
vtu.rawdata_dict['vel'] = np.sqrt(vtu.rawdata_dict['aiflow'][:, 0]**2. +
vtu.rawdata_dict['aiflow'][:, 1]**2.)
tri = Triangulation(
np.array([rc[0] + 100000. for rc in vtu.raw_coords[:, 0]]) / 1000.,
np.array([rc[1] for rc in vtu.raw_coords[:, 0]]), vtu.simptt)
gs = gridspec.GridSpec(2,
3,
width_ratios=(1., 1., 1.),
height_ratios=(1, 0.1),
hspace=0.55,
wspace=0.1,
left=0.1,
bottom=0.2,
top=0.9,
right=0.98)
fig = plt.figure(figsize=(7.5, 3.0))
axes = [fig.add_subplot(gs[0, i]) for i in range(3)]
cbr_axes = [fig.add_subplot(gs[1, i]) for i in range(3)]
cm1 = axes[0].tricontourf(tri,
vtu.rawdata_dict['strainrate 4'],
cmap='bwr',
levels=np.linspace(-2.5e-4, 2.5e-4, 101),
extend='both')
levels = [1000, 5000, 10000, 50000, 100000]
axes[0].set_xlim(0, 20)
axes[0].set_ylim(0, 2250)
CS = axes[0].tricontour(tri,
vtu.rawdata_dict['age'],
colors='k',
levels=levels,
linewidths=0.5)
fmt = {level: '{:d} kyr'.format(level // 1000) for level in levels}
axes[0].set_xlim(0, 20)
axes[0].set_ylim(0, 2250)
axes[0].clabel(CS, CS.levels, inline=True, fmt=fmt, fontsize=8)
for c in cm1.collections:
c.set_edgecolor("face")
axes[0].set_title(r'$\dot\varepsilon_{xz}$')
axes[1].set_title('Vertical fabric')
axes[2].set_title('Angle')
axes[0].set_xlim(0, 20)
axes[0].set_xticks([0., 10., 20.])
cm2 = axes[1].tricontourf(tri,
vtu.rawdata_dict['fabric 2'],
cmap='BrBG',
norm=anisolib.fab_norm,
levels=np.linspace(0, 1, 101),
extend='neither')
for c in cm2.collections:
c.set_edgecolor("face")
axes[1].set_xlim(0, 20)
axes[1].set_xticks([0., 10., 20.])
cm3 = axes[2].tricontourf(tri,
vtu.rawdata_dict['eigenv 4'],
cmap='PuOr',
levels=np.linspace(-5, 5, 201),
extend='both')
for c in cm3.collections:
c.set_edgecolor("face")
axes[2].set_xlim(0, 20)
axes[2].set_xticks([0., 10., 20.])
cbr = plt.colorbar(cm1,
cax=cbr_axes[0],
orientation='horizontal',
label=r'$\dot\varepsilon_{xz}$',
ticks=(-2.5e-4, 0, 2.5e-4))
cbr.ax.set_xticklabels(['-2.5e-4', '0', '2.5e-4'])
cbr = plt.colorbar(cm2,
cax=cbr_axes[1],
orientation='horizontal',
ticks=(0, 1. / 3., 2. / 3., 1.0),
label=r'$a^{(2)}_{zz}$')
cbr.ax.set_xticklabels(['0', r'$\frac{1}{3}$', r'$\frac{2}{3}$', '1'])
cbr = plt.colorbar(cm3,
cax=cbr_axes[2],
orientation='horizontal',
ticks=(-5, 0, 5),
label=r'Angle ($^o$)')
axes[0].set_ylabel('Height (m)')
for ax in axes[1:]:
ax.set_yticklabels(['' for tick in ax.get_yticklabels()])
axes[1].set_xlabel('Distance (km)')
for letter, ax in zip('abc', axes):
ax.text(0.05, 0.85, letter, transform=ax.transAxes, fontsize=bfs)
ax.set_ylim(0, 2250)
fig.savefig('../plots/idealized_init_zoom.png', dpi=300)
def idealized_with_cartoon():
# We want to find the filename for the highest index where we have all 3
files = glob('../stream/rstf/deform2e-3_????.vtu')
inds = np.argsort(np.array([float(fn[-8:-4]) for fn in files]))
files = [files[i] for i in inds]
vtu = fastvtulib.get_structured_vtu(files[-1])
vtu.rawdata_dict['vel'] = np.sqrt(vtu.rawdata_dict['aiflow'][:, 0]**2. +
vtu.rawdata_dict['aiflow'][:, 1]**2.)
tri = Triangulation(
np.array([rc[0] + 100000. for rc in vtu.raw_coords[:, 0]]) / 1000.,
np.array([rc[1] for rc in vtu.raw_coords[:, 0]]), vtu.simptt)
gs = gridspec.GridSpec(7,
4,
width_ratios=(1., 1., 0.5, 0.035),
height_ratios=(0.4, 0.05, 0.4, 0.05, 0.2, 0.05,
0.15),
hspace=0.00,
wspace=0.1,
left=0.07,
bottom=0.07,
top=0.93,
right=0.92)
fig = plt.figure(figsize=(7.9, 3.1))
axes = [fig.add_subplot(gs[0:4, i]) for i in range(2)]
cbr_axes = [fig.add_subplot(gs[5, i]) for i in range(2)]
ball_cbr_axis = fig.add_subplot(gs[0:5, 3])
cartoon_axes = [
fig.add_subplot(gs[0, 2], projection=fabricplotlib.PRJ),
fig.add_subplot(gs[2, 2], projection=fabricplotlib.PRJ),
fig.add_subplot(gs[4:, 2], projection=fabricplotlib.PRJ)
]
cm1 = axes[0].tricontourf(tri,
vtu.rawdata_dict['aiflow'][:, 0],
cmap='Reds',
levels=np.linspace(0.0, 10., 101),
extend='max')
levels = [1000, 5000, 10000, 50000, 100000]
CS = axes[0].tricontour(tri,
vtu.rawdata_dict['age'],
colors='k',
levels=levels,
linewidths=0.5)
fmt = {level: '{:d} kyr'.format(level // 1000) for level in levels}
axes[0].clabel(CS, CS.levels, inline=True, fmt=fmt, fontsize=8)
for c in cm1.collections:
c.set_edgecolor("face")
# axes[0].set_title('Speed', fontsize=bfs)
# axes[1].set_title('Vertical fabric', fontsize=bfs)
# axes[2].set_title('Woodcock Parameter', fontsize=bfs)
axes[0].set_xlim(0, 175)
axes[0].set_xticks([0., 50., 100., 150.])
# k = woodcock(vtu.rawdata_dict)
vtu.rawdata_dict['eigenv 3'][np.isnan(vtu.rawdata_dict['eigenv 3'])] = 1.0
vtu.rawdata_dict['eigenv 3'][np.isinf(vtu.rawdata_dict['eigenv 3'])] = 1.0
cm3 = axes[1].tricontourf(tri,
vtu.rawdata_dict['eigenv 3'],
cmap='summer',
extend='neither',
levels=np.linspace(0.33333, 1, 101))
for c in cm3.collections:
c.set_edgecolor("face")
axes[1].set_xlim(0, 175)
axes[1].set_xticks([0., 50., 100., 150.])
fabricplotlib.quiver(axes[1], vtu, scale=15, width=0.005)
axes[1].scatter(-1000,
-1000,
marker=r'$\uparrow$',
label='Single max. in x-z',
color='k')
axes[1].legend(loc='lower left',
bbox_to_anchor=(0.15, 0.85),
fontsize=fs,
framealpha=1.0)
cbr = plt.colorbar(cm1,
cax=cbr_axes[0],
orientation='horizontal',
ticks=(0, 5., 10.))
cbr.set_label(label=r'$v_x$ (m a$^{-1})$', size=fs)
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
cbr = plt.colorbar(cm3,
cax=cbr_axes[1],
orientation='horizontal',
ticks=(1. / 3., 2. / 3., 1))
cbr.set_label(label=r'$a_1^{(2)}$', size=fs)
cbr.ax.set_xticklabels([r'$\frac{1}{3}$', r'$\frac{2}{3}$', '1'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
axes[0].set_ylabel('Height (m)', fontsize=fs)
for ax in axes[1:]:
ax.set_yticklabels(['' for tick in ax.get_yticklabels()])
axes[0].set_xlabel('Distance (km)', fontsize=fs)
axes[1].set_xlabel('Distance (km)', fontsize=fs)
for letter, ax in zip('abc', axes):
ax.text(0.05, 0.85, letter, transform=ax.transAxes, fontsize=bfs)
ax.tick_params(axis='both', which='major', labelsize=fs)
ax.set_ylim(0, 2250)
for letter, ax in zip('cde', cartoon_axes):
ax.text(0.00, 0.9, letter, transform=ax.transAxes, fontsize=bfs)
x, y = np.array([70000, 70000, 70000]), np.array([1900, 1200, 200])
axes[1].text(x[0] / 1000. + 100,
y[0],
'c',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
axes[1].text(x[1] / 1000. + 100,
y[1],
'd',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
axes[1].text(x[2] / 1000. + 100,
y[2],
'e',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
fab_at_pts = vtu.get_pts_2d(anisolib.fabs, x, y)
a2 = anisolib.fabric_dict_to_a2(fab_at_pts)
for i in range(3):
cm = fabricplotlib.a2plot(a2[:, :, i],
ax=cartoon_axes[i],
cbr=False,
show=False,
levels=13)
cbr = plt.colorbar(cm, cax=ball_cbr_axis, orientation='vertical')
cbr.set_label(label=r'ODF($\theta,\phi$)', size=fs)
# cbr.ax.set_xticklabels(['0', '1', '2'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
fig.savefig('../plots/idealized_init_cartoon.png', dpi=300)
fig.savefig('../plots/poster_idealized_init_cartoon.png',
dpi=300,
transparent=True)
def single_plot(fl_n=1,
fps=2,
fn='slide',
panel2='fabric 4',
countby=1,
folder='rstf'):
files = glob('../stream/' + folder + '/' + fn + '????.vtu')
if fn[0] == 'd':
maxn = 2502
else:
maxn = 1002
if len(files) > maxn + 1:
files = files[1:maxn]
else:
files = files[1:]
inds = np.argsort(np.array([float(fn[-8:-4]) for fn in files]))
fns = [files[ind] for ind in inds]
FFMpegWriter = manimation.writers['ffmpeg']
title = '{:s}'.format(fn.title())
metadata = dict(title=title,
artist='Matplotlib',
comment='Elmer/Ice Model Results')
writer = FFMpegWriter(fps=fps,
metadata=metadata,
extra_args=['-vcodec', 'rawvideo'])
times = np.arange(0.0, 10.0 * len(files), 10.0)
lens = [len(fn) for fn in fns if len(fn) > 0]
if len(lens) == 0:
return
steps = min(lens)
vtus = [
fastvtulib.get_structured_vtu(tf) if tf is not None else None
for tf in fns[1::countby]
]
tris = [
Triangulation(
np.array([rc[0] for rc in vtu.raw_coords[:, 0]]) / 1000. +
100, np.array([rc[1] for rc in vtu.raw_coords[:, 0]]), vtu.simptt)
if vtu is not None else None for vtu in vtus
]
fig, ((ax1), (ax2)) = plt.subplots(nrows=2,
ncols=1,
figsize=(8, 6),
sharex=True,
sharey=True)
ax1.set_title(r't={:5.1f}'.format(0.0))
gs = gridspec.GridSpec(7,
4,
width_ratios=(1., 1., 0.5, 0.035),
height_ratios=(0.4, 0.05, 0.4, 0.05, 0.2, 0.05,
0.15),
hspace=0.00,
wspace=0.1,
left=0.07,
bottom=0.07,
top=0.90,
right=0.92)
fig = plt.figure(figsize=(7.9, 3.1))
axes = [None, fig.add_subplot(gs[0:4, 0:2])]
cbr_axes = [None, fig.add_subplot(gs[5, 0])]
ball_cbr_axis = fig.add_subplot(gs[0:5, 3])
cartoon_axes = [
fig.add_subplot(gs[0, 2], projection=fabricplotlib.PRJ),
fig.add_subplot(gs[2, 2], projection=fabricplotlib.PRJ),
fig.add_subplot(gs[4:, 2], projection=fabricplotlib.PRJ)
]
# k = woodcock(vtu.rawdata_dict)
vtus[0].rawdata_dict['eigenv 3'][np.isnan(
vtus[0].rawdata_dict['eigenv 3'])] = 1.0
vtus[0].rawdata_dict['eigenv 3'][np.isinf(
vtus[0].rawdata_dict['eigenv 3'])] = 1.0
cm3 = axes[1].tricontourf(tris[0],
vtus[0].rawdata_dict['eigenv 3'],
cmap='summer',
extend='neither',
levels=np.linspace(0.33333, 1, 101))
for c in cm3.collections:
c.set_edgecolor("face")
axes[1].set_xlim(0, 175)
axes[1].set_xticks([0., 50., 100., 150.])
quiv = fabricplotlib.quiver(axes[1], vtus[0], scale=25, width=0.002)
axes[1].scatter(-1000,
-1000,
marker=r'$\uparrow$',
label='Single max. in x-z',
color='k')
axes[1].legend(loc='lower left',
bbox_to_anchor=(0.15, 0.85),
fontsize=fs,
framealpha=1.0)
cbr = plt.colorbar(cm3,
cax=cbr_axes[1],
orientation='horizontal',
ticks=(1. / 3., 2. / 3., 1))
cbr.set_label(label=r'$a_1^{(2)}$', size=fs)
cbr.ax.set_xticklabels([r'$\frac{1}{3}$', r'$\frac{2}{3}$', '1'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
axes[1].set_xlabel('Distance (km)', fontsize=fs)
axes[1].set_ylabel('Height (m)', fontsize=fs)
axes[1].text(0.05, 0.85, 'a', transform=axes[1].transAxes, fontsize=bfs)
axes[1].tick_params(axis='both', which='major', labelsize=fs)
axes[1].set_ylim(0, 2250)
t = axes[1].text(-5, 2400, 'Time={:d}'.format(0))
for letter, ax in zip('bcde', cartoon_axes):
ax.text(0.00, 0.9, letter, transform=ax.transAxes, fontsize=bfs)
x, y = np.array([70000, 70000, 70000]), np.array([1900, 1200, 200])
axes[1].text(x[0] / 1000. + 100,
y[0],
'b',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
axes[1].text(x[1] / 1000. + 100,
y[1],
'c',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
axes[1].text(x[2] / 1000. + 100,
y[2],
'd',
fontsize=fs,
ha='center',
va='center',
bbox=dict(boxstyle='square,pad=0.1',
facecolor='white',
alpha=0.75))
fab_at_pts = vtus[0].get_pts_2d(anisolib.fabs, x, y)
a2 = anisolib.fabric_dict_to_a2(fab_at_pts)
cms = [None for i in range(3)]
for i in range(3):
cms[i] = fabricplotlib.a2plot(a2[:, :, i],
ax=cartoon_axes[i],
cbr=False,
show=False,
levels=13)
cbr = plt.colorbar(cms[0], cax=ball_cbr_axis, orientation='vertical')
cbr.set_label(label=r'ODF($\theta,\phi$)', size=fs)
# cbr.ax.set_xticklabels(['0', '1', '2'])
cbr.ax.tick_params(axis='both', which='major', labelsize=fs)
if folder == 'rstf':
pref = ''
else:
pref = 'oop'
with writer.saving(fig, '{:s}_fabric_evolution.avi'.format(pref + fn),
150):
for i, (svtu, tri,
time) in enumerate(zip(vtus, tris, times[0::countby])):
ax1.set_title(r't={:5.1f}'.format(time))
if svtu is not None:
# Note that this is not fully accurate since fabric 2 only approximates the maximum eigenvalue
for j in range(3):
for c in cms[j].collections:
c.remove()
for c in cm3.collections:
c.remove()
for p in quiv:
try:
p.remove()
except:
try:
for c in p.collections:
c.remove()
except AttributeError:
# I think this is the dots for OOP
for c in p:
c.remove()
t.set_text('Time={:d}'.format(int(time)))
cm3 = axes[1].tricontourf(tri,
svtu.rawdata_dict['eigenv 3'],
cmap='summer',
extend='neither',
levels=np.linspace(0.33333, 1, 101))
quiv = fabricplotlib.quiver(axes[1],
svtu,
scale=25,
width=0.002)
fab_at_pts = svtu.get_pts_2d(anisolib.fabs, x, y)
a2 = anisolib.fabric_dict_to_a2(fab_at_pts)
for j in range(3):
cms[j] = fabricplotlib.a2plot(a2[:, :, j],
ax=cartoon_axes[j],
cbr=False,
show=False,
levels=13)
writer.grab_frame()
maxtime = np.min([np.max(times) for times in timess[:-3]])
maxtime_oop = np.min([np.max(times) for times in timess])
try:
inds_times = [
int(np.where(times == maxtime)[0][0]) for times in timess[:-3]
]
inds_times_oop = [
int(np.where(timess[-1] == maxtime_oop)[0][0]) for times in timess
]
except:
inds_times = [301 for i in timess[:-3]]
inds_times_oop = [301 for i in timess]
vtus = {
fmt: fastvtulib.get_structured_vtu(filel[int(ind[ind_t])])
for fmt, ind, ind_t, filel in zip(fmts[:-3], inds, inds_times, files)
}
vtus_oop = {
fmt: fastvtulib.get_structured_vtu(filel[int(ind[ind_t])])
for fmt, ind, ind_t, filel in zip(fmts, inds, inds_times_oop, files)
}
print('With OOP:', maxtime_oop)
print('Without OOP:', maxtime)
deform_files = glob('../stream/rstf/deform_diffuse????.vtu')
deform_inds = np.argsort(np.array([float(fn[-8:-4]) for fn in deform_files]))
deform_vtu = fastvtulib.get_structured_vtu(deform_files[deform_inds[-1]])
colors = ['C0', 'C1', 'C2']