def dump_step(self,status):
"""
Overwrite standard dump per step
Args:
status: status object per step
"""
super(particles_output,self).dump_step(status)
# some abbreviations
L = self.level
u = L.uend
R = np.linalg.norm(u.pos.values)
H = 1/2*np.dot(u.vel.values,u.vel.values)+0.02/R
stats.add_to_stats(step=status.step, time=status.time, type='energy', value=H)
oldcol = self.sframe
# self.sframe = self.ax.scatter(L.uend.pos.values[0],L.uend.pos.values[1],L.uend.pos.values[2])
self.sframe = self.ax.scatter(L.uend.pos.values[0],L.uend.pos.values[1])
# Remove old line collection before drawing
if oldcol is not None:
self.ax.collections.remove(oldcol)
plt.pause(0.00001)
return None
def dump_step(self, status):
"""
Overwrite standard dump per step
Args:
status: status object per step
"""
super(particles_output, self).dump_step(status)
# some abbreviations
L = self.level
u = L.uend
R = np.linalg.norm(u.pos.values)
H = 1 / 2 * np.dot(u.vel.values, u.vel.values) + 0.02 / R
stats.add_to_stats(step=status.step,
time=status.time,
type='energy',
value=H)
oldcol = self.sframe
# self.sframe = self.ax.scatter(L.uend.pos.values[0],L.uend.pos.values[1],L.uend.pos.values[2])
self.sframe = self.ax.scatter(L.uend.pos.values[0],
L.uend.pos.values[1])
# Remove old line collection before drawing
if oldcol is not None:
self.ax.collections.remove(oldcol)
plt.pause(0.00001)
return None
def dump_iteration(self,status):
"""
Default routine called after each iteration
"""
L = self.level
stats.add_to_stats(step=status.step, time=status.time, iter=status.iter, type='residual',
value=L.status.residual)
pass
def dump_iteration(self, status):
"""
Default routine called after each iteration
"""
L = self.level
stats.add_to_stats(step=status.step,
time=status.time,
iter=status.iter,
type='residual',
value=L.status.residual)
pass
def dump_sweep(self,status):
"""
Default routine called after each sweep
"""
L = self.level
logger = logging.getLogger('root')
logger.info('Process %2i on time %8.6f at stage %15s: Level: %s -- Iteration: %2i -- Residual: %12.8e',
status.slot,status.time,status.stage,L.id,status.iter,L.status.residual)
stats.add_to_stats(step=status.step, time=status.time, level=L.id, iter=status.iter,
type='residual', value=L.status.residual)
pass
def dump_step(self,status):
"""
Overwrite standard dump per step
Args:
status: status object per step
"""
super(particles_output,self).dump_step(status)
# some abbreviations
L = self.level
part = L.uend
N = L.prob.nparts
w = np.array([1,1,-2])
# compute (slowly..) the potential at uend
fpot = np.zeros(N)
for i in range(N):
# inner loop, omit ith particle
for j in range(0,i):
dist2 = np.linalg.norm(part.pos.values[3*i:3*i+3]-part.pos.values[3*j:3*j+3],2)**2+L.prob.sig**2
fpot[i] += part.q[j]/np.sqrt(dist2)
for j in range(i+1,N):
dist2 = np.linalg.norm(part.pos.values[3*i:3*i+3]-part.pos.values[3*j:3*j+3],2)**2+L.prob.sig**2
fpot[i] += part.q[j]/np.sqrt(dist2)
fpot[i] -= L.prob.omega_E**2 * part.m[i]/part.q[i]/2.0 \
* np.dot(w,part.pos.values[3*i:3*i+3]*part.pos.values[3*i:3*i+3])
# add up kinetic and potntial contributions to total energy
epot = 0
ekin = 0
for n in range(N):
epot += part.q[n]*fpot[n]
ekin += part.m[n]/2.0*np.dot(part.vel.values[3*n:3*n+3],part.vel.values[3*n:3*n+3])
print('Energy (pot/kin/tot) at step %i: %12.4f / %12.4f / %12.4f' %(status.step,epot,ekin,epot+ekin))
stats.add_to_stats(step=status.step, time=status.time, type='etot', value=epot+ekin)
# print('plotting particles...')
# oldcol = self.sframe
# # self.sframe = self.ax.scatter(L.uend.pos.values[0],L.uend.pos.values[1],L.uend.pos.values[2])
self.sframe = self.ax.scatter(L.uend.pos.values[0::3],L.uend.pos.values[1::3],L.uend.pos.values[2::3])
# # Remove old line collection before drawing
# if oldcol is not None:
# self.ax.collections.remove(oldcol)
# plt.pause(0.001)
return None
def dump_iteration(self,status):
super(error_output,self).dump_iteration(status)
L = self.level
P = L.prob
L.sweep.compute_end_point()
uend = L.uend
uex = P.u_exact(status.time+status.dt)
err = np.linalg.norm(uex.values-uend.values,np.inf)/np.linalg.norm(uex.values,np.inf)
# print('error at time %s, iteration %s: %s' %(status.time,status.iter,err))
stats.add_to_stats(step=status.step, time=status.time, iter=status.iter, type='error', value=err)
def dump_sweep(self, status):
"""
Default routine called after each sweep
"""
L = self.level
logger = logging.getLogger('root')
logger.info(
'Process %2i at stage %15s: Level: %s -- Iteration: %2i -- Residual: %12.8e',
status.slot, status.stage, L.id, status.iter, L.status.residual)
stats.add_to_stats(step=status.step,
time=status.time,
level=L.id,
iter=status.iter,
type='residual',
value=L.status.residual)
pass
def dump_pre(self, status):
"""
Overwrite standard dump at the beginning
Args:
status: status object per step
"""
super(particles_output, self).dump_pre(status)
# some abbreviations
L = self.level
part = L.u[0]
N = L.prob.nparts
w = np.array([1, 1, -2])
# compute (slowly..) the potential at u0
fpot = np.zeros(N)
for i in range(N):
# inner loop, omit ith particle
for j in range(0, i):
dist2 = np.linalg.norm(
part.pos.values[3 * i:3 * i + 3] -
part.pos.values[3 * j:3 * j + 3], 2)**2 + L.prob.sig**2
fpot[i] += part.q[j] / np.sqrt(dist2)
for j in range(i + 1, N):
dist2 = np.linalg.norm(
part.pos.values[3 * i:3 * i + 3] -
part.pos.values[3 * j:3 * j + 3], 2)**2 + L.prob.sig**2
fpot[i] += part.q[j] / np.sqrt(dist2)
fpot[i] -= L.prob.omega_E**2 * part.m[i]/part.q[i]/2.0 \
* np.dot(w,part.pos.values[3*i:3*i+3]*part.pos.values[3*i:3*i+3])
# add up kinetic and potntial contributions to total energy
epot = 0
ekin = 0
for n in range(N):
epot += part.q[n] * fpot[n]
ekin += part.m[n] / 2.0 * np.dot(part.vel.values[3 * n:3 * n + 3],
part.vel.values[3 * n:3 * n + 3])
print('Energy (pot/kin/tot): %12.4f / %12.4f / %12.4f' %
(epot, ekin, epot + ekin))
stats.add_to_stats(type='etot', value=epot + ekin)
def dump_pre(self,status):
"""
Overwrite standard dump at the beginning
Args:
status: status object per step
"""
super(particles_output,self).dump_pre(status)
# some abbreviations
L = self.level
part = L.u[0]
N = L.prob.nparts
w = np.array([1,1,-2])
# compute (slowly..) the potential at u0
fpot = np.zeros(N)
for i in range(N):
# inner loop, omit ith particle
for j in range(0,i):
dist2 = np.linalg.norm(part.pos.values[3*i:3*i+3]-part.pos.values[3*j:3*j+3],2)**2+L.prob.sig**2
fpot[i] += part.q[j]/np.sqrt(dist2)
for j in range(i+1,N):
dist2 = np.linalg.norm(part.pos.values[3*i:3*i+3]-part.pos.values[3*j:3*j+3],2)**2+L.prob.sig**2
fpot[i] += part.q[j]/np.sqrt(dist2)
fpot[i] -= L.prob.omega_E**2 * part.m[i]/part.q[i]/2.0 \
* np.dot(w,part.pos.values[3*i:3*i+3]*part.pos.values[3*i:3*i+3])
# add up kinetic and potntial contributions to total energy
epot = 0
ekin = 0
for n in range(N):
epot += part.q[n]*fpot[n]
ekin += part.m[n]/2.0*np.dot(part.vel.values[3*n:3*n+3],part.vel.values[3*n:3*n+3])
print('Energy (pot/kin/tot): %12.4f / %12.4f / %12.4f' %(epot,ekin,epot+ekin))
stats.add_to_stats(type='etot', value=epot+ekin)
def dump_step(self,status):
"""
Default routine called after each step
"""
L = self.level
stats.add_to_stats(step=status.step, time=status.time, type='timing_step', value=time.time()-self.t0)
stats.add_to_stats(step=status.step, time=status.time, type='niter', value=status.iter)
stats.add_to_stats(step=status.step, time=status.time, type='residual', value=L.status.residual)
pass
def dump_step(self, status):
"""
Default routine called after each step
"""
L = self.level
stats.add_to_stats(step=status.step,
time=status.time,
type='timing_step',
value=time.time() - self.t0)
stats.add_to_stats(step=status.step,
time=status.time,
type='niter',
value=status.iter)
stats.add_to_stats(step=status.step,
time=status.time,
type='residual',
value=L.status.residual)
pass
def dump_step(self, status):
"""
Overwrite standard dump per step
Args:
status: status object per step
"""
super(particles_output, self).dump_step(status)
# some abbreviations
L = self.level
part = L.uend
N = L.prob.nparts
w = np.array([1, 1, -2])
# compute (slowly..) the potential at uend
fpot = np.zeros(N)
for i in range(N):
# inner loop, omit ith particle
for j in range(0, i):
dist2 = np.linalg.norm(
part.pos.values[3 * i:3 * i + 3] -
part.pos.values[3 * j:3 * j + 3], 2)**2 + L.prob.sig**2
fpot[i] += part.q[j] / np.sqrt(dist2)
for j in range(i + 1, N):
dist2 = np.linalg.norm(
part.pos.values[3 * i:3 * i + 3] -
part.pos.values[3 * j:3 * j + 3], 2)**2 + L.prob.sig**2
fpot[i] += part.q[j] / np.sqrt(dist2)
fpot[i] -= L.prob.omega_E**2 * part.m[i]/part.q[i]/2.0 \
* np.dot(w,part.pos.values[3*i:3*i+3]*part.pos.values[3*i:3*i+3])
# add up kinetic and potntial contributions to total energy
epot = 0
ekin = 0
for n in range(N):
epot += part.q[n] * fpot[n]
ekin += part.m[n] / 2.0 * np.dot(part.vel.values[3 * n:3 * n + 3],
part.vel.values[3 * n:3 * n + 3])
print('Energy (pot/kin/tot) at step %i: %12.4f / %12.4f / %12.4f' %
(status.step, epot, ekin, epot + ekin))
stats.add_to_stats(step=status.step,
time=status.time,
type='etot',
value=epot + ekin)
# print('plotting particles...')
# oldcol = self.sframe
# # self.sframe = self.ax.scatter(L.uend.pos.values[0],L.uend.pos.values[1],L.uend.pos.values[2])
self.sframe = self.ax.scatter(L.uend.pos.values[0::3],
L.uend.pos.values[1::3],
L.uend.pos.values[2::3])
# # Remove old line collection before drawing
# if oldcol is not None:
# self.ax.collections.remove(oldcol)
# plt.pause(0.001)
return None
