def print_rf_dat(rf, name='RF'):
h.hprint('Write output file: {}.dat'.format(name))
file='{}.dat'.format(name)
with open(file, 'w') as f:
f.write('META_START\n'.format(name))
f.write('name:{}\n'.format(name))
for l in rf:
if l in ['sizes', 'parameters', 'nodes']:
for k,v in rf[l].items():
f.write('{l}:{k}:{v}\n'.format(l=l, k=k, v=v))
f.write('META_STOP\n'.format(name))
f.write('\n')
f.write('VALUES_START\n')
for r in rf[1]:
f.write('{}\n'.format(r))
f.write('VALUES_STOP\n')
def simu_rf(rf):
l = rf.l
n = rf.n
h.hprint('Correlated Gaussian Random Field')
for k,v in rf.__dict__.iteritems():
h.hprint('{k}={v}'.format(k=k, v=v), n=2)
importr("RandomFields")
RFsimulate = r('RFsimulate')
options = r('RFoptions(seed=NA, spConform=FALSE)')
if rf.type is "gauss":
model = r('RMgauss(var={var}, scale={scale}) + RMnugget(var={nugget_var}) + RMtrend(mean={mean})'.format(**rf.__dict__))
elif rf.type is "matern":
model = r('RMmatern(nu={nu}, scale={scale}) + RMnugget(var={nugget_var}) + RMtrend(mean={mean})'.format(**rf.__dict__))
x = r('seq(0.0, {}, {})'.format(l['x'], float(l['x'])/(n['x']-1)))
y = r('seq(0.0, {}, {})'.format(l['y'], float(l['y'])/(n['y']-1)))
z = r('seq(0.0, {}, {})'.format(l['z'], float(l['z'])/(n['z']-1)))
grid = r('NULL')
return {1:np.array(RFsimulate(model=model, x=x, y=y, z=z, grid=grid))}
def print_rf_vtk(rf, rea):
c = create_lexico(rf)
h.hprint('Write output file: {}.vtk'.format(rf.name))
file='{}.vtk'.format(rf.name)
with open(file, 'w') as f:
f.write('# vtk DataFile Version 2.0\n')
f.write('{}\n'.format(rf.name))
f.write('ASCII\nDATASET STRUCTURED_GRID\n')
f.write('DIMENSIONS {x} {y} {z}\n\n'.format(**rf.n))
f.write('POINTS {} float\n'.format(np.prod([n for n in rf.n.itervalues()])))
for x, y, z in zip(c['x'], c['y'], c['z']):
f.write('{x} {y} {z}\n'.format(x=x, y=y, z=z))
f.write('\n')
f.write('POINT_DATA {}\n'.format(np.prod([n for n in rf.n.itervalues()])))
f.write('SCALARS {} float 1\n'.format(rf.name))
f.write('LOOKUP_TABLE default\n')
for r in rea[1].flatten(order='F'):
f.write('{}\n'.format(r))
f.write('\n')
def read_rf_dat(f, create_mesh=False):
first_line_printed = '--- Read file: {} ---'.format(f)
print('\n{}'.format(first_line_printed))
h.hprint('Read file')
with open('{}.dat'.format(f)) as content_file:
content = [l.strip() for l in content_file if l.strip()]
h.hprint('Get Metadatas')
try:
meta_start = content.index('META_START')
meta_stop = content.index('META_STOP')
except ValueError as e:
h.hprint('Oups... Could not read meta datas.', n=2)
h.hprint('{}'.format(e), n=3)
return None
rf = dict()
for m in content[meta_start+1:meta_stop]:
sp = m.split(':')
if len(sp) == 2:
if sp[0] in rf:
h.hprint('couple {}:{} not considered (redondant data)'.format(*sp),n=3)
else:
rf.update({sp[0]:sp[1]})
elif len(sp) == 3:
if sp[0] in rf:
rf[sp[0]].update({sp[1]:sp[2]})
else:
rf.update({sp[0]:{sp[1]:sp[2]}})
else:
h.hprint('parameter {m} not considered (to deep)'.format(m=m),n=3)
h.hprint('Get Values')
try:
values_start = content.index('VALUES_START')
values_stop = content.index('VALUES_STOP')
except ValueError as e:
h.hprint('Oups... Could not read values.', n=2)
h.hprint('{}'.format(e), n=3)
return None
rf.update({1:np.array([float(m) for m in content[values_start+1:values_stop]])})
if create_mesh:
if 'sizes' in rf and 'nodes' in rf:
create_lexico(rf['sizes'], rf['nodes'])
print '-'*len(first_line_printed)+'\n'
return rf
