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ParticleData.py
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ParticleData.py
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import taichi as ti
import math
import numpy as np
import taichi as ti
from HashGrid import HashGrid
from MarchingCubeGrid import MCGrid
from kernels.CubicKernel import CubicKernel
@ti.data_oriented
class ParticleData:
def __init__(self, particleR):
self.count = 0
self.liquid_count = 0
self.solid_count = 0
self.rho_L0 = 1000.0
self.rho_S0 = self.rho_L0
self.VL0 = particleR * particleR * particleR * 0.8 * 8.0
self.VS0 = self.VL0
self.liqiudMass = self.VL0 * self.rho_L0
self.hash_grid = HashGrid(particleR*2.0, 64, 2048, self)
#self.mc_grid = MCGrid(particleR*4.0, 64, 2048, self)
self.mc_grid = MCGrid(particleR, 4, 512, self)
self.kernel_c = CubicKernel(self.hash_grid.searchR)
self.pos = ti.Vector.field(3, dtype=ti.f32)
self.normal = ti.Vector.field(3, dtype=ti.f32)
self.color = ti.field( dtype=ti.f32)
self.color_grad = ti.Vector.field(3, dtype=ti.f32)
self.pos_avr = ti.Vector.field(3, dtype=ti.f32)
self.G = ti.Matrix.field(3,3, dtype=ti.f32)
self.vel_guess = ti.Vector.field(3, dtype=ti.f32)
self.vel = ti.Vector.field(3, dtype=ti.f32)
self.omega = ti.Vector.field(3, dtype=ti.f32)
self.vel_max = ti.field( dtype=ti.f32)
self.d_vel = ti.Vector.field(3, dtype=ti.f32)
self.d_omega = ti.Vector.field(3, dtype=ti.f32)
self.pressure = ti.field( dtype=ti.f32)
self.rho = ti.field( dtype=ti.f32)
self.adv_rho = ti.field( dtype=ti.f32)
#viscorcity cg sovler
self.gravity = ti.Vector([0.0, -9.81, 0.0])
self.dim_coff = 10.0
self.viscosity = 10.0
self.viscosity_b = 10.0
self.viscosity_err = 0.05
self.avg_density_err = ti.field( dtype=ti.f32, shape=(1))
self.cg_delta = ti.field( dtype=ti.f32, shape=(1))
self.cg_delta_old = ti.field( dtype=ti.f32, shape=(1))
self.cg_delta_zero = ti.field( dtype=ti.f32, shape=(1))
self.cg_Minv = ti.Matrix.field(3, 3, dtype=ti.f32)
self.cg_r = ti.Vector.field(3, dtype=ti.f32)
self.cg_dir = ti.Vector.field(3, dtype=ti.f32)
self.cg_Ad = ti.Vector.field(3, dtype=ti.f32)
self.cg_s = ti.Vector.field(3, dtype=ti.f32)
#tension
self.tension_coff = 0.0
self.tension_coff_b = 0.0
#vorcity_coff
self.viscosity_omega = 0.1
self.vorticity_coff = 0.01
self.vorticity_init = 0.5
self.point_list = []
self.maxboundarynp = np.ones(shape=(1,3), dtype=np.float32)
self.minboundarynp = np.ones(shape=(1,3), dtype=np.float32)
for j in range(3):
self.maxboundarynp[0, j] = -10000.0
self.minboundarynp[0, j] = 10000.0
def add_liquid_point(self, point):
'''
filename = "liqiud.obj"
if len(self.point_list) == 0:
fo = open(filename, "w")
else:
fo = open(filename, "a+")
print ("v %f %f %f" % (point[0], point[1], point[2]), file = fo)
fo.close()
'''
self.point_list.append(point)
for j in range(3):
self.maxboundarynp[0, j] = max(self.maxboundarynp[0, j], point[j])
self.minboundarynp[0, j] = min(self.minboundarynp[0, j], point[j])
self.count += 1
self.liquid_count += 1
def add_solid_point(self, point):
self.point_list.append(point)
for j in range(3):
self.maxboundarynp[0, j] = max(self.maxboundarynp[0, j], point[j])
self.minboundarynp[0, j] = min(self.minboundarynp[0, j], point[j])
self.count += 1
self.solid_count += 1
def add_obj(self, filename):
for line in open(filename, "r"):
if line.startswith('#'):
continue
values = line.split()
if not values: continue
if values[0] == 'v':
v = list(map(float, values[1:4]))
self.add_solid_point(v)
def setup_data_gpu(self):
ti.root.dense(ti.i, self.count ).place(self.pos)
ti.root.dense(ti.i, self.liquid_count ).place(self.normal)
ti.root.dense(ti.i, self.liquid_count ).place(self.color)
ti.root.dense(ti.i, self.liquid_count ).place(self.color_grad)
ti.root.dense(ti.i, self.liquid_count ).place(self.pos_avr)
ti.root.dense(ti.i, self.liquid_count ).place(self.G)
ti.root.dense(ti.i, self.liquid_count ).place(self.vel_guess)
ti.root.dense(ti.i, self.liquid_count ).place(self.vel )
ti.root.dense(ti.i, self.liquid_count ).place(self.omega )
ti.root.dense(ti.i, self.liquid_count ).place(self.vel_max )
ti.root.dense(ti.i, self.liquid_count ).place(self.d_vel )
ti.root.dense(ti.i, self.liquid_count ).place(self.d_omega )
ti.root.dense(ti.i, self.liquid_count ).place(self.pressure)
ti.root.dense(ti.i, self.liquid_count ).place(self.rho )
ti.root.dense(ti.i, self.liquid_count ).place(self.adv_rho )
#viscorcity cg sovler
ti.root.dense(ti.i, self.liquid_count ).place(self.cg_Minv)
ti.root.dense(ti.i, self.liquid_count ).place(self.cg_r )
ti.root.dense(ti.i, self.liquid_count ).place(self.cg_dir )
ti.root.dense(ti.i, self.liquid_count ).place(self.cg_Ad )
ti.root.dense(ti.i, self.liquid_count ).place(self.cg_s )
self.hash_grid.setup_grid_gpu()
self.mc_grid.setup_grid_gpu(self.maxboundarynp + self.mc_grid.searchR, self.minboundarynp- self.mc_grid.searchR)
def setup_data_cpu(self):
self.pos.from_numpy(np.array(self.point_list, dtype = np.float32))
self.hash_grid.setup_grid_cpu(self.maxboundarynp, self.minboundarynp)
self.mc_grid.setup_grid_cpu(self.maxboundarynp + self.mc_grid.searchR, self.minboundarynp- self.mc_grid.searchR)
print( "liqiud particle num:", self.liquid_count, "solid particle num:", self.solid_count)
@ti.kernel
def compute_color_map(self):
for i in self.color:
self.color[i] = self.liqiudMass / self.rho[i] * self.kernel_c.Cubic_W_norm(0.0)
cur_neighbor = self.hash_grid.neighborCount[i]
k=0
while k < cur_neighbor:
j = self.hash_grid.neighbor[i, k]
r = self.pos[i] - self.pos[j]
Wr = self.kernel_c.Cubic_W(r)
if j < self.liquid_count:
self.color[i] += self.liqiudMass / self.rho[j] * Wr
else:
self.color[i] += self.VS0 * Wr
k += 1
for i in self.color_grad:
self.color_grad[i] = ti.Vector([0.0, 0.0, 0.0])
cur_neighbor = self.hash_grid.neighborCount[i]
k=0
while k < cur_neighbor:
j = self.hash_grid.neighbor[i, k]
r = self.pos[i] - self.pos[j]
if j < self.liquid_count:
self.color_grad[i] += self.liqiudMass / self.rho[j] * self.color[j] * self.kernel_c.CubicGradW(r)
k += 1
self.color_grad[i] *= 1.0 / self.color[i]
@ti.kernel
def cal_anistropic_kernel(self):
for i in self.pos_avr:
sum_wij = 0.0
sum_xj = ti.Vector([0.0, 0.0, 0.0])
self.pos_avr[i] = self.pos[i]
cur_neighbor = self.hash_grid.neighborCount[i]
k=0
while k < cur_neighbor:
j = self.hash_grid.neighbor[i, k]
if j < self.liquid_count:
wij = self.weight_func(self.pos[i] , self.pos[j] )
sum_wij += wij
sum_xj += wij*self.pos[j]
k+=1
if sum_wij > 0.0:
self.pos_avr[i] = sum_xj / sum_wij
for i in self.G:
kr = 4.0
ks = 1400.0
kn = 0.5
ne = 25.0
sum_wij = 0.0
self.G[i] = kn*ti.Matrix([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
cur_neighbor = self.hash_grid.neighborCount[i]
if cur_neighbor>ne:
sum_ci = ti.Matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
k=0
while k < cur_neighbor:
j = self.hash_grid.neighbor[i, k]
if j < self.liquid_count:
wij = self.weight_func(self.pos[i] , self.pos[j] )
r = self.pos[j] - self.pos_avr[i]
sum_wij += wij
sum_ci += wij * (r.outer_product(r))
k+=1
C = sum_ci / sum_wij
R, sigma, RT = ti.svd(C, ti.f32)
if sigma[0, 0] > 0.0:
sigmas = ti.Matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
sigmas[0, 0] = ks * sigma[0, 0]
sigmas[1, 1] = ks * ti.max(sigma[1, 1], sigma[0, 0] / kr)
sigmas[2, 2] = ks * ti.max(sigma[2, 2], sigma[0, 0] / kr)
inv_sigmas = sigmas.inverse()
self.G[i] = R @ inv_sigmas @ (RT.transpose())
'''
max_value = ti.max( ti.max(inv_sigmas[2, 2], inv_sigmas[0, 0]),inv_sigmas[1, 1])
self.G[i] = R @ inv_sigmas @ (RT.transpose()) / max_value
'''
#self.color_grad[i] = ti.Vector([self.G[i][0,0], self.G[i][1,1], self.G[i][2,2]])
#if abs(self.pos[i].x) < 0.05 and abs(self.pos[i].z) < 0.05 and ( (self.pos[i].y > 1.1) or (self.pos[i].y < 0.225)):
#if abs(self.pos[i].z) > 0.45:
# print(1, self.pos[i], self.G[i] )
@ti.func
def weight_func(self, xi, xj):
ret = 0.0
r = xi - xj
dis = r.norm()
if dis < self.mc_grid.searchR*2.0:
ret = 1.0 - pow( dis / (self.mc_grid.searchR*2.0), 3.0)
return ret
def export_kernel(self):
pos = self.pos.to_numpy()
color = self.color_grad.to_numpy()
filename = "out/test.obj"
fo = open(filename, "w")
for i in range(self.liquid_count):
print ("v %f %f %f %f %f %f %f %f %f" % (pos[i,0],pos[i,1],pos[i,2], color[i,0]*512.0,color[i,1]*512.0,color[i,2]*512.0,color[i,0],color[i,1],color[i,2]), file = fo)
fo.close()