def f(dm, data, itt, final=False):
if final:
fn = '{:s}_final.2obj'.format(data['prefix'])
else:
fn = '{:s}_{:010d}.2obj'.format(data['prefix'], itt)
vnum = dm.np_get_vertices(verts)
tnum = dm.np_get_triangles_vertices(tris)
meta = '\n# procs {:d}\n'+\
'# vnum {:d}\n'+\
'# tnum {:d}\n'+\
'# time {:f}\n'+\
'# nearl {:f}\n'+\
'# farl {:f}\n'+\
'# attract stp {:f}\n'+\
'# reject stp {:f}\n'+\
'# triangle stp {:f}\n'+\
'# size {:d}\n'
meta = meta.format(data['procs'], vnum, tnum,
time() - t0, data['nearl'], data['farl'],
data['attract_stp'], data['reject_stp'],
data['triangle_stp'], data['size'])
export_obj('mesh',
fn,
verts=verts[:vnum, :],
faces=tris[:tnum, :],
meta=meta)
def f(df, data, itt, final=False):
if final:
fn = '{:s}_final.2obj'.format(data['prefix'])
else:
fn = '{:s}_{:010d}.2obj'.format(data['prefix'],itt)
num = df.np_get_sorted_vert_coordinates(verts)
meta = '\n# procs {:d}\n# vnum {:d}\n# time {:f}\n# nearl {:f}\n# farl {:f}\n# stp {:f}\n size {:d}'.format(
data['procs'],
num,
time()-t_start,
data['nearl'],
data['farl'],
data['stp'],
data['size']
)
export_obj('line',fn, verts[:num,:], meta=meta)
def f(dm, data, itt, final=False):
if final:
fn = '{:s}_final.2obj'.format(data['prefix'])
else:
fn = '{:s}_{:010d}.2obj'.format(data['prefix'],itt)
vnum = dm.np_get_vertices(verts)
tnum = dm.np_get_triangles_vertices(tris)
meta = '\n# procs {:d}\n'+\
'# vnum {:d}\n'+\
'# tnum {:d}\n'+\
'# time {:f}\n'+\
'# nearl {:f}\n'+\
'# farl {:f}\n'+\
'# attract stp {:f}\n'+\
'# reject stp {:f}\n'+\
'# triangle stp {:f}\n'+\
'# size {:d}\n'
meta = meta.format(
data['procs'],
vnum,
tnum,
time()-t0,
data['nearl'],
data['farl'],
data['attract_stp'],
data['reject_stp'],
data['triangle_stp'],
data['size']
)
export_obj(
'mesh',
fn,
verts = verts[:vnum,:],
faces = tris[:tnum,:],
meta = meta
)
def f(dm, data, itt, final=False):
if final:
fn = '{:s}_final.2obj'.format(data['prefix'])
else:
fn = '{:s}_{:010d}.2obj'.format(data['prefix'],itt)
vnum = dm.np_get_vert_coordinates(verts)
enum = dm.np_get_edges(edges)
linenum = dm.np_get_sorted_verts(line)
meta = '\n# procs {:d}\n'+\
'# vnum {:d}\n'+\
'# enum {:d}\n'+\
'# time {:f}\n'+\
'# nearl {:f}\n'+\
'# farl {:f}\n'+\
'# stp {:f}\n'+\
'# size {:d}\n'
meta = meta.format(
data['procs'],
vnum,
enum,
time()-t0,
data['nearl'],
data['farl'],
data['stp'],
data['size']
)
export_obj(
'mesh',
fn,
verts = verts[:vnum,:],
edges = edges[:enum,:],
lines = [line[:linenum]],
meta = meta
)
def main(args):
from differentialCloud import DifferentialCloud
from modules.helpers import print_stats
from modules.helpers import make_info_str
from modules.utils import get_initial_cloud
from dddUtils.ioOBJ import export as export_obj
from numpy.random import random
from numpy import array, zeros
reject = args.reject * args.stp
attract = args.attract * args.stp
stat = args.stat
export = args.export
out = args.out
vnum_max = args.vnum
start_num = args.startNum
start_rad = args.startRad
nearl = args.nearl
midl = args.midl
farl = args.farl
np_verts = zeros((args.nmax, 3), 'float')
DC = DifferentialCloud(nmax=args.nmax,
zonewidth=args.farl,
nearl=nearl,
midl=midl,
farl=farl,
procs=args.procs)
xyz, mode = get_initial_cloud(start_num, start_rad)
DC.init_cloud(xyz, mode)
DC.init_rules(array([[1.0, 1.0], [1.0, -1.0]], 'double'),
array([[nearl, farl], [nearl, farl]], 'double'))
for i in xrange(args.itt):
try:
rnd = (random(size=DC.get_vnum()) < 0.001).nonzero()[0]
if len(rnd) > 0:
DC.spawn(rnd)
DC.optimize_position(reject, attract, nearl * 0.1)
if i % stat == 0:
print_stats(i, DC, meta=None)
if i % export == 0:
vnum = DC.np_get_vertices(np_verts)
export_obj(obj_name='cloud',
fn='{:s}_{:012d}.obj'.format(out, i),
verts=np_verts[:vnum, :],
tris=None,
meta=make_info_str(args))
if DC.get_vnum() > vnum_max:
return
except KeyboardInterrupt:
break
def main(args):
from differentialCloud import DifferentialCloud
from modules.helpers import print_stats
from modules.helpers import make_info_str
from modules.utils import get_initial_cloud
from dddUtils.ioOBJ import export as export_obj
from numpy.random import random
from numpy import array, zeros
reject = args.reject*args.stp
attract = args.attract*args.stp
stat = args.stat
export = args.export
out = args.out
vnum_max = args.vnum
start_num = args.startNum
start_rad = args.startRad
nearl = args.nearl
midl = args.midl
farl = args.farl
np_verts = zeros((args.nmax, 3), 'float')
DC = DifferentialCloud(
nmax = args.nmax,
zonewidth = args.farl,
nearl = nearl,
midl = midl,
farl = farl,
procs = args.procs
)
xyz, mode = get_initial_cloud(start_num, start_rad)
DC.init_cloud(xyz, mode)
DC.init_rules(
array(
[
[1.0,1.0],
[1.0,-1.0]
],
'double'
),
array(
[
[nearl,farl],
[nearl,farl]
],
'double'
)
)
for i in xrange(args.itt):
try:
rnd = (random(size=DC.get_vnum())<0.001).nonzero()[0]
if len(rnd)>0:
DC.spawn(rnd)
DC.optimize_position(
reject,
attract,
nearl*0.1
)
if i%stat==0:
print_stats(i, DC, meta=None)
if i%export==0:
vnum = DC.np_get_vertices(np_verts)
export_obj(
obj_name = 'cloud',
fn = '{:s}_{:012d}.obj'.format(out, i),
verts = np_verts[:vnum,:],
tris = None,
meta = make_info_str(args)
)
if DC.get_vnum()>vnum_max:
return
except KeyboardInterrupt:
break
