def method(ts, dt=0, **kwargs):
""" Analyze geometry in time."""
info_cyan("Analyzing the evolution of the geometry through time.")
if not ts.get_parameter("enable_PF"):
print "Phase field not enabled."
return False
f_mask = df.Function(ts.function_space)
f_mask_x = []
f_mask_u = []
for d in range(ts.dim):
f_mask_x.append(df.Function(ts.function_space))
f_mask_u.append(df.Function(ts.function_space))
length = np.zeros(len(ts))
area = np.zeros(len(ts))
com = np.zeros((len(ts), ts.dim))
u = np.zeros((len(ts), ts.dim))
makedirs_safe(os.path.join(ts.analysis_folder, "contour"))
steps = get_steps(ts, dt)
for step in steps:
info("Step " + str(step) + " of " + str(len(ts)))
phi = ts["phi", step][:, 0]
mask = 0.5 * (1. - phi) # 0.5*(1.-np.sign(phi))
ts.set_val(f_mask, mask)
for d in range(ts.dim):
ts.set_val(f_mask_x[d], mask * ts.nodes[:, d])
ts.set_val(f_mask_u[d], mask * ts["u", step][:, d])
contour_file = os.path.join(ts.analysis_folder, "contour",
"contour_{:06d}.dat".format(step))
paths = zero_level_set(ts.nodes, ts.elems, phi, save_file=contour_file)
length[step] = path_length(paths)
area[step] = df.assemble(f_mask * df.dx)
for d in range(ts.dim):
com[step, d] = df.assemble(f_mask_x[d] * df.dx)
u[step, d] = df.assemble(f_mask_u[d] * df.dx)
for d in range(ts.dim):
com[:, d] /= area
u[:, d] /= area
if rank == 0:
np.savetxt(os.path.join(ts.analysis_folder, "time_data.dat"),
np.array(
zip(np.arange(len(ts)), ts.times, length, area,
com[:, 0], com[:, 1], u[:, 0], u[:, 1])),
header=("Timestep\tTime\tLength\tArea\t"
"CoM_x\tCoM_y\tU_x\tU_y"))
def __init__(self, folder, sought_fields=None, get_mesh_from=False,
memory_modest=True):
self.folder = folder
self.settings_folder = os.path.join(folder, "Settings")
self.timeseries_folder = os.path.join(folder, "Timeseries")
self.statistics_folder = os.path.join(folder, "Statistics")
self.analysis_folder = os.path.join(folder, "Analysis")
self.plots_folder = os.path.join(folder, "Plots")
self.tmp_folder = os.path.join(folder, ".tmp")
self.memory_modest = memory_modest
self.params_prefix = os.path.join(self.settings_folder,
"parameters_from_tstep_")
self.params_suffix = ".dat"
self.parameters = dict()
self.nodes = None
self.elems = None
self.times = dict()
self.datasets = dict()
self._load_timeseries(sought_fields)
if len(self.fields) > 0:
self._load_mesh(get_mesh_from)
self.dummy_function = df.Function(self.function_space)
makedirs_safe(self.analysis_folder)
makedirs_safe(self.plots_folder)
makedirs_safe(self.tmp_folder)
def method(ts,
dx=0.1,
line="[0.,0.]--[1.,1.]",
time=None,
dt=None,
skip=0,
**kwargs):
""" Probe along a line. """
info_cyan("Probe along a line.")
try:
x_a, x_b = [tuple(eval(pt)) for pt in line.split("--")]
assert (len(x_a) == ts.dim)
assert (len(x_b) == ts.dim)
assert (all([
bool(isinstance(xd, float) or isinstance(xd, int))
for xd in list(x_a) + list(x_b)
]))
except:
info_on_red("Faulty line format. Use 'line=[x1,y1]--[x2,y2]'.")
exit()
x = np.array(line_points(x_a, x_b, dx))
info("Probes {num} points from {a} to {b}".format(num=len(x), a=x_a,
b=x_b))
if rank == 0:
plot_probes(ts.nodes, ts.elems, x, colorbar=False, title="Probes")
f = ts.functions()
probes = dict()
from fenicstools import Probes
for field, func in f.iteritems():
probes[field] = Probes(x.flatten(), func.function_space())
steps = get_steps(ts, dt, time)
for step in steps:
info("Step " + str(step) + " of " + str(len(ts)))
ts.update_all(f, step)
for field, probe in probes.iteritems():
probe(f[field])
probe_arr = dict()
for field, probe in probes.iteritems():
probe_arr[field] = probe.array()
if rank == 0:
for i, step in enumerate(steps):
chunks = [x]
header_list = [index2letter(d) for d in range(ts.dim)]
for field, chunk in probe_arr.iteritems():
if chunk.ndim == 1:
header_list.append(field)
chunk = chunk[:].reshape(-1, 1)
elif chunk.ndim == 2:
header_list.append(field)
chunk = chunk[:, i].reshape(-1, 1)
elif chunk.ndim > 2:
header_list.extend(
[field + "_" + index2letter(d) for d in range(ts.dim)])
chunk = chunk[:, :, i]
chunks.append(chunk)
data = np.hstack(chunks)
header = "\t".join(header_list)
makedirs_safe(os.path.join(ts.analysis_folder, "probes"))
np.savetxt(os.path.join(ts.analysis_folder, "probes",
"probes_{:06d}.dat".format(step)),
data,
header=header)