def read_and_calc(self, target, c_strain):
uobj = UDFManager(target)
time = []
temp = []
stress = []
strain = []
# データ読み込み
prev_stress = 0.
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
time.append(uobj.get("Time"))
temp.append(uobj.get('Statistics_Data.Temperature.Batch_Average'))
#
if self.mode == 'elong':
strs = uobj.get("Statistics_Data.Stress.Total.Batch_Average")
tmp_stress = strs[2] - (strs[0] + strs[1]) / 2.
elif self.mode == 'shear':
tmp_stress = uobj.get(
'Statistics_Data.Stress.Total.Batch_Average.xy'
) #- self.ave_xy
if tmp_stress <= 0:
tmp_stress = prev_stress
#
stress.append(tmp_stress)
strain.append(c_strain)
prev_stress = tmp_stress
#
stress_part = np.stack([time, stress, temp], 1)
strain_part = np.stack([time, strain, temp], 1)
return stress_part, strain_part
def read_and_calc(area_init, z_init, target):
uobj = UDFManager(target)
data = []
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
cell = uobj.get("Structure.Unit_Cell.Cell_Size")
#
stress = uobj.get("Statistics_Data.Stress.Total.Batch_Average")
t_stress = calc_stress(cell, stress, area_init)
#
bond_stress = uobj.get("Statistics_Data.Stress.Bond.Batch_Average")
bond = calc_stress(cell, bond_stress, area_init)
#
non_bond_stress = uobj.get(
"Statistics_Data.Stress.Non_Bond.Batch_Average")
non_bond = calc_stress(cell, non_bond_stress, area_init)
#
strain = uobj.get("Structure.Unit_Cell.Cell_Size.c") / z_init
#
temp = uobj.get("Statistics_Data.Temperature.Batch_Average")
#
data.append([strain, t_stress, non_bond, bond, temp])
return data
def read_and_calc(self, target):
uobj = UDFManager(target)
time = []
g = []
temp = []
# データ読み込み
prev_g = 0.
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
time.append(uobj.get("Time"))
temp.append(uobj.get('Statistics_Data.Temperature.Batch_Average'))
#
if self.mode == 'elong':
stress = uobj.get("Statistics_Data.Stress.Total.Batch_Average")
tmp_g = (stress[2] -
(stress[0] + stress[1]) / 2.) / (self.deform**2 -
1 / self.deform)
elif self.mode == 'shear':
tmp_stress = uobj.get(
'Statistics_Data.Stress.Total.Batch_Average.xy'
) - self.ave_xy
tmp_g = tmp_stress / self.deform
if tmp_g <= 0:
tmp_g = prev_g
g.append(tmp_g)
prev_g = tmp_g
# smoothing
mod_g = signal.savgol_filter(g, 11, 3)
# pack up
data = np.stack([time, g, temp], 1)
data_mod = np.stack([time, mod_g, temp], 1)
return data, data_mod
def read_step_stress(self, t_udf):
print("Readin file = ", t_udf)
area_init, z_init = self.calc_init(t_udf)
uobj = UDFManager(t_udf)
time = []
strain = []
stress = []
temp = []
# データ読み込み
prev_stress = 0.
for rec in range(uobj.totalRecord()):
print("Reading Rec.=", rec)
uobj.jump(rec)
#
time.append(uobj.get("Time"))
if self.mode == 'elong':
tmp_strain = uobj.get(
"Structure.Unit_Cell.Cell_Size.c") / z_init
elif self.mode == 'shear':
tmp_strain = uobj.get('Structure.Unit_Cell.Shear_Strain')
strain.append(tmp_strain)
#
if rec == 0:
tmp_stress = prev_stress
temp.append(1.)
else:
temp.append(
uobj.get('Statistics_Data.Temperature.Batch_Average'))
if self.mode == 'elong':
stress_list = uobj.get(
"Statistics_Data.Stress.Total.Batch_Average")
tmp_stress = stress_list[2] - (stress_list[0] +
stress_list[1]) / 2.
elif self.mode == 'shear':
tmp_stress = uobj.get(
'Statistics_Data.Stress.Total.Batch_Average.xy'
) #- self.ave_xy
if tmp_stress <= 0:
tmp_stress = prev_stress
stress.append(tmp_stress)
#
prev_stress = tmp_stress
#
stress_step = np.stack([time, stress, temp], 1)
strain_step = np.stack([time, strain, temp], 1)
ss = np.stack([strain, stress, temp], 1)
self.plot(strain_step, 'strain_step.dat')
self.plot(stress_step, 'stress_step.dat')
self.plot(ss, 'ss.dat')
return stress_step, strain_step
def read_and_calc(target):
uobj = UDFManager(target)
data = []
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
stress = uobj.get('Statistics_Data.Stress.Total.Batch_Average.xy')
#
strain = uobj.get('Structure.Unit_Cell.Shear_Strain')
#
data.append([strain, stress])
return data
def make_base_udf(self, t_udf):
if os.path.exists(self.calc_dir):
print("Use existing dir of ", self.calc_dir)
else:
print("Make new dir of ", self.calc_dir)
os.makedirs(self.calc_dir)
#
base = os.path.join(self.calc_dir, self.base_udf)
print("Readin file = ", t_udf)
u = UDFManager(t_udf)
# u.jump(u.totalRecord() - 1)
# ave_xy = u.get('Statistics_Data.Stress.Total.Total_Average.xy')
u.eraseRecord(0, u.totalRecord() - 2)
u.write(base)
return base
def read_and_calc(target, c_strain, mode):
# low = 1e-5
uobj = UDFManager(target)
time = []
temp = []
stress = []
strain = []
gt = []
# データ読み込み
prev_stress = 0.
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
time.append(uobj.get("Time"))
temp.append(uobj.get('Statistics_Data.Temperature.Batch_Average'))
#
if mode == 'elong':
strs = uobj.get("Statistics_Data.Stress.Total.Batch_Average")
tmp_stress = strs[2] - (strs[0] + strs[1]) / 2.
if tmp_stress <= 0.05 * prev_stress:
tmp_stress = 4 * prev_stress / 5
if tmp_stress < 1e-4:
tmp_stress = 1e-4
tmp_gt = tmp_stress / c_strain / 3.
elif mode == 'shear':
tmp_stress = uobj.get(
'Statistics_Data.Stress.Total.Batch_Average.xy'
) #- self.ave_xy
if tmp_stress <= 0.05 * prev_stress:
tmp_stress = 4 * prev_stress / 5
if tmp_stress < 1e-4:
tmp_stress = 1e-4
tmp_gt = tmp_stress / c_strain
# tmp_stress = low
#
stress.append(tmp_stress)
strain.append(c_strain)
gt.append(tmp_gt)
prev_stress = tmp_stress
#
mod_stress = signal.savgol_filter(stress, 5, 3)
stress_part = np.stack([time, mod_stress, temp], 1)
strain_part = np.stack([time, strain, temp], 1)
gt_part = np.stack([time, gt, temp], 1)
return stress_part, strain_part, gt_part
def read_and_calc(target):
if target.split('_')[0] == 'Cycle':
sim_type = target.split('_')[4]
else:
sim_type = target.split('_')[3]
uobj = UDFManager(target)
if sim_type == 'forward':
uobj.jump(0)
cell = uobj.get("Structure.Unit_Cell.Cell_Size")
area_init = cell[0] * cell[1]
z_init = cell[2]
data = [[1.0, 0, 0, 0]]
elif sim_type == 'backward':
uobj.jump(1)
vol = uobj.get("Statistics_Data.Volume.Batch_Average")
area_init = vol**(2. / 3.)
z_init = vol**(1. / 3.)
data = []
for i in range(1, uobj.totalRecord()):
print("Reading Rec.=", i)
uobj.jump(i)
#
cell = uobj.get("Structure.Unit_Cell.Cell_Size")
#
stress = uobj.get("Statistics_Data.Stress.Total.Batch_Average")
t_stress = calc_stress(cell, stress, area_init)
#
bond_stress = uobj.get("Statistics_Data.Stress.Bond.Batch_Average")
bond = calc_stress(cell, bond_stress, area_init)
#
non_bond_stress = uobj.get(
"Statistics_Data.Stress.Non_Bond.Batch_Average")
non_bond = calc_stress(cell, non_bond_stress, area_init)
#
strain = uobj.get("Structure.Unit_Cell.Cell_Size.c") / z_init
#
temp = uobj.get("Statistics_Data.Temperature.Batch_Average")
#
data.append([strain, t_stress, non_bond, bond, temp])
return data
print nnk,mxk
rr=zeros(1001,float64)
hist=zeros(1001,int32)
for kkk in range(1, nnk):
k1 = float(k01[kkk]) * pi2 / float(lx)
k2 = float(k02[kkk]) * pi2 / float(ly)
k3 = float(k03[kkk]) * pi2 / float(lz)
kl = sqrt(k1*k1+k2*k2+k3*k3)
bin = int(kl/delk)
rr[bin] = rr[bin] + kl*dia
hist[bin] = hist[bin] + 1
for ij in range(0, 1000):
if hist[ij]>0:
rr[ij]=rr[ij]/float(hist[ij])
print ij,rr[ij],hist[ij]
nt=uobj.totalRecord()
#print nt
suma=zeros(1001,float64)
for n in range(0,nt):
uobj.jump(n)
x = uobj.get("Particles[].R.x")
y = uobj.get("Particles[].R.y")
z = uobj.get("Particles[].R.z")
for kkk in range(1,nnk):
k1 = float(k01[kkk]) * pi2 / float(lx)
k2 = float(k02[kkk]) * pi2 / float(ly)
k3 = float(k03[kkk]) * pi2 / float(lz)
kl = sqrt(k1*k1+k2*k2+k3*k3)
bin = int(kl/delk)
sa1 = 0.0
sa2 = 0.0
def read_step_stress(self, t_udf):
print("Readin file = ", t_udf)
area_init, z_init = self.calc_init(t_udf)
uobj = UDFManager(t_udf)
time = []
strain = []
g = []
stress = []
temp = []
# データ読み込み
prev_stress = 0.
prev_g = 0.
for rec in range(uobj.totalRecord()):
print("Reading Rec.=", rec)
uobj.jump(rec)
#
time.append(uobj.get("Time"))
if self.mode == 'elong':
tmp_strain = uobj.get(
"Structure.Unit_Cell.Cell_Size.c") / z_init
elif self.mode == 'shear':
tmp_strain = uobj.get('Structure.Unit_Cell.Shear_Strain')
strain.append(tmp_strain)
#
if rec == 0:
tmp_stress = prev_stress
tmp_g = prev_g
temp.append(1.)
else:
temp.append(
uobj.get('Statistics_Data.Temperature.Batch_Average'))
if self.mode == 'elong':
stress_list = uobj.get(
"Statistics_Data.Stress.Total.Batch_Average")
tmp_stress = stress_list[2] - (stress_list[0] +
stress_list[1]) / 2.
tmp_g = tmp_stress / (tmp_strain**2 - 1 / tmp_strain)
elif self.mode == 'shear':
tmp_stress = uobj.get(
'Statistics_Data.Stress.Total.Batch_Average.xy'
) - self.ave_xy
tmp_g = tmp_stress / tmp_strain
if tmp_stress <= 0:
tmp_stress = prev_stress
tmp_g = prev_g
stress.append(tmp_stress)
g.append(tmp_g)
#
prev_stress = tmp_stress
prev_g = tmp_g
#
mod_g = signal.savgol_filter(g, 11, 3)
#
gt_step_mod = np.stack([time, mod_g, temp], 1)
gt_step = np.stack([time, g, temp], 1)
ss_step = np.stack([strain, stress, temp], 1)
self.save_data(ss_step, 'ss_step.dat')
self.save_data(gt_step, 'gt_step.dat')
self.save_data(gt_step_mod, 'gt_step_mod.dat')
return gt_step, gt_step_mod