def plot(self,
ifield=0,
cut=0.5,
levels=12,
cmap='RdYlBu_r',
png=False,
step=1,
normed=False,
dpi=80,
bgcolor=None,
deminc=True,
ic=False):
"""
Plotting function (it can also write the png files)
:param ifield: in case of a multiple-field movie file, you can change
the default field displayed using the parameter ifield
:type ifield: int
:param levels: number of contour levels
:type levels: int
:param cmap: name of the colormap
:type cmap: str
:param cut: adjust the contour extrema to max(abs(data))*cut
:type cut: float
:param png: save the movie as a series of png files when
set to True
:type png: bool
:param dpi: dot per inch when saving PNGs
:type dpi: int
:param bgcolor: background color of the figure
:type bgcolor: str
:param normed: the colormap is rescaled every timestep when set to True,
otherwise it is calculated from the global extrema
:type normed: bool
:param step: the stepping between two timesteps
:type step: int
:param deminc: a logical to indicate if one wants do get rid of the
possible azimuthal symmetry
:type deminc: bool
"""
if png:
plt.ioff()
if not os.path.exists('movie'):
os.mkdir('movie')
else:
plt.ion()
if not normed:
vmin = -max(abs(self.data[ifield, ...].max()),
abs(self.data[ifield, ...].min()))
vmin = cut * vmin
vmax = -vmin
# vmin, vmax = self.data.min(), self.data.max()
cs = np.linspace(vmin, vmax, levels)
if self.surftype == 'phi_constant':
if self.n_theta_plot == self.n_theta_max:
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
fig = plt.figure(figsize=(4, 8))
th0 = th
else:
th0 = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
th1 = np.linspace(np.pi / 2., 3. * np.pi / 2.,
self.n_theta_max)
th = np.concatenate((th0, th1))
fig = plt.figure(figsize=(6.5, 6))
# Plotting trick using th0
th0 = np.linspace(np.pi / 2, np.pi / 2 + 2. * np.pi,
2 * self.n_theta_max)
rr, tth = np.meshgrid(self.radius, th)
xx = rr * np.cos(tth)
yy = rr * np.sin(tth)
xxout = rr.max() * np.cos(th0)
yyout = rr.max() * np.sin(th0)
xxin = rr.min() * np.cos(th0)
yyin = rr.min() * np.sin(th0)
if ic:
rr, tth = np.meshgrid(self.radius_ic, th)
xx_ic = rr * np.cos(tth)
yy_ic = rr * np.sin(tth)
elif self.surftype == 'r_constant':
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
if deminc:
phi = np.linspace(-np.pi, np.pi,
self.n_phi_tot * self.minc + 1)
xxout, yyout = hammer2cart(th, -np.pi)
xxin, yyin = hammer2cart(th, np.pi)
else:
phi = np.linspace(-np.pi / self.minc, np.pi / self.minc,
self.n_phi_tot)
xxout, yyout = hammer2cart(th, -np.pi / self.minc)
xxin, yyin = hammer2cart(th, np.pi / self.minc)
ttheta, pphi = np.meshgrid(th, phi)
xx, yy = hammer2cart(ttheta, pphi)
fig = plt.figure(figsize=(8, 4))
elif self.surftype == 'theta_constant':
if deminc:
phi = np.linspace(0., 2. * np.pi,
self.n_phi_tot * self.minc + 1)
else:
phi = np.linspace(0., 2. * np.pi / self.minc, self.n_phi_tot)
rr, pphi = np.meshgrid(self.radius, phi)
xx = rr * np.cos(pphi)
yy = rr * np.sin(pphi)
xxout = rr.max() * np.cos(pphi)
yyout = rr.max() * np.sin(pphi)
xxin = rr.min() * np.cos(pphi)
yyin = rr.min() * np.sin(pphi)
if ic:
rr, pphi = np.meshgrid(self.radius_ic, phi)
xx_ic = rr * np.cos(pphi)
yy_ic = rr * np.sin(pphi)
fig = plt.figure(figsize=(6, 6))
elif self.surftype == '3d volume':
self.data = self.data[ifield, ..., 0]
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
phi = np.linspace(-np.pi, np.pi, self.n_phi_tot)
ttheta, pphi = np.meshgrid(th, phi)
xx, yy = hammer2cart(ttheta, pphi)
xxout, yyout = hammer2cart(th, -np.pi)
xxin, yyin = hammer2cart(th, np.pi)
fig = plt.figure(figsize=(8, 4))
fig.subplots_adjust(top=0.99, right=0.99, bottom=0.01, left=0.01)
ax = fig.add_subplot(111, frameon=False)
for k in range(self.nvar):
if k == 0:
if normed:
vmin = -max(abs(self.data[ifield, k, ...].max()),
abs(self.data[ifield, k, ...].min()))
vmin = cut * vmin
vmax = -vmin
cs = np.linspace(vmin, vmax, levels)
if self.surftype in ['r_constant', 'theta_constant']:
if deminc:
dat = symmetrize(self.data[ifield, k, ...], self.minc)
if ic:
datic = symmetrize(self.data_ic[ifield, k, ...],
self.minc)
else:
dat = self.data[ifield, k, ...]
if ic:
datic = self.data_ic[ifield, k, ...]
im = ax.contourf(xx, yy, dat, cs, cmap=cmap, extend='both')
if ic:
ax.contourf(xx_ic,
yy_ic,
datic,
cs,
cmap=cmap,
extend='both')
else:
im = ax.contourf(xx,
yy,
self.data[ifield, k, ...],
cs,
cmap=cmap,
extend='both')
if ic:
im_ic = ax.contourf(xx_ic,
yy_ic,
self.data_ic[ifield, k, ...],
cs,
cmap=cmap,
extend='both')
ax.plot(xxout, yyout, 'k-', lw=1.5)
ax.plot(xxin, yyin, 'k-', lw=1.5)
ax.axis('off')
man = plt.get_current_fig_manager()
man.canvas.draw()
if k != 0 and k % step == 0:
if not png:
print(k + self.var2 - self.nvar)
plt.cla()
if normed:
vmin = -max(abs(self.data[ifield, k, ...].max()),
abs(self.data[ifield, k, ...].min()))
vmin = cut * vmin
vmax = -vmin
cs = np.linspace(vmin, vmax, levels)
if self.surftype in ['r_constant', 'theta_constant']:
if deminc:
dat = symmetrize(self.data[ifield, k, ...], self.minc)
if ic:
datic = symmetrize(self.data_ic[ifield, k, ...],
self.minc)
else:
dat = self.data[ifield, k, ...]
if ic:
datic = self.data_ic[ifield, k, ...]
ax.contourf(xx, yy, dat, cs, cmap=cmap, extend='both')
if ic:
ax.contourf(xx_ic,
yy_ic,
datic,
cs,
cmap=cmap,
extend='both')
else:
ax.contourf(xx,
yy,
self.data[ifield, k, ...],
cs,
cmap=cmap,
extend='both')
if ic:
ax.contourf(xx_ic,
yy_ic,
self.data_ic[ifield, k, ...],
cs,
cmap=cmap,
extend='both')
ax.plot(xxout, yyout, 'k-', lw=1.5)
ax.plot(xxin, yyin, 'k-', lw=1.5)
ax.axis('off')
man.canvas.draw()
if png:
filename = 'movie/img{:05d}.png'.format(k)
print('write {}'.format(filename))
# st = 'echo {}'.format(ivar) + ' > movie/imgmax'
if bgcolor is not None:
fig.savefig(filename, facecolor=bgcolor, dpi=dpi)
else:
fig.savefig(filename, dpi=dpi)
def avgStd(self,
ifield=0,
std=False,
cut=0.5,
levels=12,
cmap='RdYlBu_r',
ic=False):
"""
Plot time-average or standard deviation
:param ifield: in case of a multiple-field movie file, you can change
the default field displayed using the parameter ifield
:type ifield: int
:param std: the standard deviation is computed instead the average
when std is True
:type std: bool
:param levels: number of contour levels
:type levels: int
:param cmap: name of the colormap
:type cmap: str
:param cut: adjust the contour extrema to max(abs(data))*cut
:type cut: float
"""
if std:
avg = self.data[ifield, ...].std(axis=0)
if ic:
avg_ic = self.data_ic[ifield, ...].std(axis=0)
else:
avg = self.data[ifield, ...].mean(axis=0)
if ic:
avg_ic = self.data_ic[ifield, ...].mean(axis=0)
vmin = -max(abs(avg.max()), abs(avg.min()))
vmin = cut * vmin
vmax = -vmin
cs = np.linspace(vmin, vmax, levels)
if self.surftype == 'phi_constant':
if self.n_theta_plot == self.n_theta_max:
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
fig = plt.figure(figsize=(4, 8))
th0 = th
else:
th0 = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
th1 = np.linspace(np.pi / 2., 3. * np.pi / 2.,
self.n_theta_max)
th = np.concatenate((th0, th1))
fig = plt.figure(figsize=(6.5, 6))
# Plotting trick using th0
th0 = np.linspace(np.pi / 2, np.pi / 2 + 2. * np.pi,
2 * self.n_theta_max)
rr, tth = np.meshgrid(self.radius, th)
xx = rr * np.cos(tth)
yy = rr * np.sin(tth)
xxout = rr.max() * np.cos(th0)
yyout = rr.max() * np.sin(th0)
xxin = rr.min() * np.cos(th0)
yyin = rr.min() * np.sin(th0)
if ic:
rr, tth = np.meshgrid(self.radius_ic, th)
xx_ic = rr * np.cos(tth)
yy_ic = rr * np.sin(tth)
elif self.surftype == 'r_constant':
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
phi = np.linspace(-np.pi, np.pi, self.n_phi_tot)
ttheta, pphi = np.meshgrid(th, phi)
xx, yy = hammer2cart(ttheta, pphi)
xxout, yyout = hammer2cart(th, -np.pi)
xxin, yyin = hammer2cart(th, np.pi)
fig = plt.figure(figsize=(8, 4))
elif self.surftype == 'theta_constant':
phi = np.linspace(0., 2. * np.pi, self.n_phi_tot)
rr, pphi = np.meshgrid(self.radius, phi)
xx = rr * np.cos(pphi)
yy = rr * np.sin(pphi)
xxout = rr.max() * np.cos(pphi)
yyout = rr.max() * np.sin(pphi)
xxin = rr.min() * np.cos(pphi)
yyin = rr.min() * np.sin(pphi)
fig = plt.figure(figsize=(6, 6))
elif self.surftype == '3d volume':
self.data = self.data[ifield, ..., 0]
th = np.linspace(np.pi / 2., -np.pi / 2., self.n_theta_max)
phi = np.linspace(-np.pi, np.pi, self.n_phi_tot)
ttheta, pphi = np.meshgrid(th, phi)
xx, yy = hammer2cart(ttheta, pphi)
xxout, yyout = hammer2cart(th, -np.pi)
xxin, yyin = hammer2cart(th, np.pi)
fig = plt.figure(figsize=(8, 4))
fig.subplots_adjust(top=0.99, right=0.99, bottom=0.01, left=0.01)
ax = fig.add_subplot(111, frameon=False)
ax.contourf(xx, yy, avg, cs, cmap=cmap, extend='both')
if ic:
ax.contourf(xx_ic, yy_ic, avg_ic, cs, cmap=cmap, extend='both')
ax.plot(xxout, yyout, 'k-', lw=1.5)
ax.plot(xxin, yyin, 'k-', lw=1.5)
ax.axis('off')