def test_extend_scalararray(self):
flist = field.fieldlist()
f1 = field.fdata(self.convmodel, self.curmesh, [1.])
flist.append(f1)
f2 = f1.copy()
f2.set_time(10.)
flist.append(f2)
newlist = field.fieldlist()
f3 = f2.copy()
newlist.append(f3)
f3.set_time(20.)
newlist.append(f2)
flist.extend(newlist)
f2.reset(t=100., it=5)
assert len(flist) == 4 # f1, f2, f3, f2
assert flist.time_array() == [0., 100., 20., 100.]
assert flist.it_array() == [-1, 5, -1, 5]
def test_append_scalararray(self):
flist = field.fieldlist()
f1 = field.fdata(self.convmodel, self.curmesh, [1.])
flist.append(f1)
f2 = f1.copy()
f2.set_time(10.)
flist.append(f2)
assert len(flist) == 2
assert flist[0].time == 0.
assert flist[-1].time == 10.
assert flist.time_array() == [0., 10.]
def test_flist_plotxtcontourf(self):
def fn(x, t):
return np.exp(-2 * np.square(x - .5 + .2 * np.sin(10 * t)))
times = np.linspace(0., 5., 11, endpoint=True)
flist = field.fieldlist()
for t in times:
f = field.fdata(self.convmodel, self.curmesh,
[fn(self.curmesh.centers(), t)])
f.set_time(t)
flist.append(f)
fig, ax = plt.subplots(1, 1)
flist.xtcontourf('q')
return fig
def _solve(self, f, condition, tsave, stop, flush, monitors, directives):
"""Solve dQ/dt=RHS(Q,t)
Args:
f: initial field
condition: CFL number
tsave: array/list of time to save
flush: (Default value = None)
Returns:
list of solution fields (size of tsave)
"""
self._time = f.time
# directives
verbose = 'verbose' in directives.keys()
#
self.condition = condition
# default stopping criterion
stopcrit = { 'tottime': tsave[-1] } if len(tsave)>0 else {}
if stop is not None: stopcrit.update(stop)
if not stopcrit:
raise ValueError("missing stopping criteria")
# default monitors
monitors = { **self.monitors, **monitors }
# initialization before loop
self.Qn = f.copy()
if flush:
alldata = [d for d in self.Qn.data]
results = field.fieldlist()
start = myclock()
isave, nsave = 0, len(tsave)
# loop testing all ending criteria
checkend = self._check_end(stopcrit)
self._parse_monitors(monitors)
# find first time to save if exists
while (isave < nsave) and (self.Qn.time > tsave[isave]):
isave += 1
# MAIN LOOP
while not checkend:
dtloc = self.modeldisc.calc_timestep(self.Qn, condition)
mindtloc = min(dtloc)
Qnn = self.Qn.copy()
if isave < nsave: # specific step to save result and go back to Qn
if self.Qn.time+mindtloc >= tsave[isave]:
# compute smaller step with same integrator
self.step(Qnn, tsave[isave]-self.Qn.time)
Qnn.it = self._itstart + self._nit
results.append(Qnn)
if verbose:
print("save state at it {:5d} and time {:6.2e}".format(self._nit, Qnn.time))
isave += 1
# step back to self.Qn
Qnn = self.Qn.copy()
self.step(Qnn, mindtloc)
self.Qn = Qnn
self._nit += 1
self._time = self.Qn.time
self._parse_monitors(monitors)
if flush:
for i, q in zip(range(len(alldata)), self.Qn.data):
alldata[i] = np.vstack((alldata[i], q))
checkend = self._check_end(stopcrit)
# save at least current state
if checkend and len(results)==0:
results.append(self.Qn)
self._cputime = myclock() - start
if flush:
np.save(flush, alldata)
return results