def numpyArray(self):
import tempfile
import os
from scipy.io import mmio
from fipy.tools import parallelComm
if parallelComm.procID == 0:
(_, mtxName) = tempfile.mkstemp(suffix='.mtx')
else:
mtxName = None
mtxName = parallelComm.bcast(mtxName)
self.exportMmf(mtxName)
parallelComm.Barrier()
mtx = mmio.mmread(mtxName)
parallelComm.Barrier()
if parallelComm.procID == 0:
os.remove(mtxName)
coo = mtx.tocoo()
trilinosMatrix = self.matrix
numpyArray = numerix.zeros(
(trilinosMatrix.NumGlobalRows(), trilinosMatrix.NumGlobalCols()),
'd')
numpyArray[coo.row, coo.col] = coo.data
return numpyArray
def savePhi(elapsed):
if parallelComm.procID == 0:
fname = data["t={}.tar.gz".format(elapsed)].make().abspath
else:
fname = None
fname = parallelComm.bcast(fname)
fp.tools.dump.write((phi,), filename=fname)
def savePhi(elapsed, data_dir):
if parallelComm.procID == 0:
fname = data_dir / "t={}.tar.gz".format(elapsed)
fname.touch()
else:
fname = None
fname_bcast = parallelComm.bcast(fname)
fp.tools.dump.write((phi, ), filename=fname_bcast)
def _calcValue(self):
from fipy.tools import parallelComm
rnd = self.parallelRandom()
if parallelComm.Nproc > 1:
rnd = parallelComm.bcast(rnd, root=0)
return rnd[self.mesh._globalOverlappingCellIDs]
else:
return rnd
def _calcValue(self):
from fipy.tools import parallelComm
rnd = self.parallelRandom()
if parallelComm.Nproc > 1:
rnd = parallelComm.bcast(rnd, root=0)
return rnd[self.mesh._globalOverlappingCellIDs]
else:
return rnd
eta.constrain(1., where=YY == 0.)
eta.constrain(0., where=YY == 0.5)
eta.value = eta_fp(xx, yy, 0.)
eq = (fp.TransientTerm() == -4 * eta * (eta - 1) * (eta - 0.5) +
fp.DiffusionTerm(coeff=kappa_fp) + eq_fp(xx, yy, elapsed))
start = time.time()
while elapsed.value <= totaltime:
eta.updateOld()
eq.solve(var=eta, dt=dt)
elapsed.value = elapsed() + dt
end = time.time()
data.categories["solvetime"] = end - start
error = eta - eta_fp(xx, yy, elapsed - dt)
error.name = r"$\Delta\eta$"
if parallelComm.procID == 0:
fname = data["eta.tar.gz"].make().abspath
else:
fname = None
fname = parallelComm.bcast(fname)
fp.tools.dump.write((eta, error), filename=fname)
data = dtr.Treant(output)
else:
class dummyTreant(object):
categories = dict()
data = dummyTreant()
if parallelComm.procID == 0:
eq_str = data.categories["eq"]
eta_str = data.categories["eta"]
kappa_fp = data.categories["kappa"]
else:
eq_str = eta_str = kappa_fp = None
eq_str, eta_str, kappa_fp = parallelComm.bcast((eq_str, eta_str, kappa_fp))
from fipy.tools.numerix import tanh, sqrt, sin, cos, pi
eq_fp = eval(eq_str)
eta_fp = eval(eta_str)
# load checkpoint
if parallelComm.procID == 0:
fname = data["step{}.tar.gz".format(startfrom)].make().abspath
else:
fname = None
fname = parallelComm.bcast(fname)
eta, _ = fp.tools.dump.read(filename=fname)
def nucleus(x0, y0, r0):
r = fp.numerix.sqrt((x - x0)**2 + (y - y0)**2)
return (1 - fp.numerix.tanh((r - r0) / fp.numerix.sqrt(2.))) / 2
# > Generate random positions with uniform distribution for 25 supercritical seeds with $r_0 = 1.1r_c$.
# In[12]:
if not params['restart']:
if parallelComm.procID == 0:
seeds = fp.numerix.random.random(size=(25, 2))
else:
seeds = None
seeds = parallelComm.bcast(seeds)
for fx, fy in seeds:
phi.setValue(phi +
nucleus(x0=fx * Lx, y0=fy * Ly, r0=params['factor'] * rc))
phi.setValue(1., where=phi > 1.)
# ## Setup output
# ### Setup ouput storage
# In[13]:
try:
from sumatra.projects import load_project
project = load_project(os.getcwd())
# In[ ]:
if parallelComm.procID == 0:
if params['restart']:
fname = os.path.join(os.path.dirname(params['restart']), "nucleii.txt")
nucleii = fp.numerix.loadtxt(fnamem, skiprows=1)
else:
times = fp.numerix.random.random(params['numnuclei']) * totaltime
times.sort()
nucleii = fp.numerix.concatenate((times[..., fp.numerix.newaxis],
fp.numerix.random.random(
(params['numnuclei'], 2))),
axis=-1)
else:
nucleii = None
nucleii = parallelComm.bcast(nucleii, root=0)
# ## Setup output
# ### Setup ouput storage
# In[ ]:
try:
from sumatra.projects import load_project
project = load_project(os.getcwd())
record = project.get_record(params["sumatra_label"])
output = record.datastore.root
except:
# either there's no sumatra, no sumatra project, or no sumatra_label
# this will be the case if this script is run directly
