def __init__( self, jdata ) :
'''
--- property -- unit --
1. Length -- nm -- self.alatt, self.first, self.second
2. Volume -- nm^3 -- self.volume
2. Time -- s --
3. Temperature -- K --
4. Energy -- eV --
5. Pressure -- Gpa --
1 eV = 1.60217663410E-19 J -> 1 J = 1.0 / 1.60217663410 * 1.E+19 eV
shear modulus:
1.0 Gpa = 1.E9 Pa = 1.E9 N / m^2 = 1.e9 J/m^3 = 1.E9 * 1.0 / 1.60217663410 * 1.E+19 eV/(10^9 nm)^3 = 1.0 / 1.60217663410 * 10 eV/nm^3
Boltzmann constant, unit: eV/ K
kb = 1.380649 * 10 ** (-23) J / K = 1.380649 * 10 ** (-23) * 1.0 / 1.60217663410 * 10**( 19 ) eV/K = 1.380649 / 1.60217663410 * 1.E-4 eV/K
'''
'shear modulus, unit: eV/nm^3.'
self.shear_modulus = 161.0 / 1.60217663410 * 10
'poisson ratio'
self.poisson_ratio = 0.28
'lattice constant'
self.alatt = j_must_have( jdata, 'alatt' )
lattice = j_must_have( jdata, 'lattice' )
if lattice == 'bcc' :
'first nearest neighbour'
self.first = math.sqrt( 3.0 ) * 0.5 * self.alatt
'second nearest neighbour'
self.second = self.alatt
'atomic volume'
self.volume = self.alatt * self.alatt * self.alatt * 0.5
elif lattice == 'fcc' :
print( '# should be change for lattice fcc !' )
pass
elif lattice == 'hcp' :
print( '# should be change for lattice hcp !' )
pass
self.kb = 1.380649 / 1.60217663410 * 1.E-4
'prefactor: Hz'
self.prefactor = 10.0 * 10 ** 12
self.u_disk_disk_prefactor = self.shear_modulus / ( 4.0 * math.pi * ( 1.0 - self.poisson_ratio ) )
self.u_sphere_disk_prefactor = 1.0 / ( 3.0 * math.pi ) * ( 1.0 + self.poisson_ratio ) / ( 1.0 - self.poisson_ratio ) * self.shear_modulus
def __init__( self,
jdata,
tmp_defectObject_list ) :
'''
Properties of BoxLinkcell:
No change:
1. self.box
2. self.linkcell_space
3. self.nlc_vector
4. self.fnlc_vector
5. self.nlc
6. self.periodic
7. self.nnbrs
8. self.hmeps
9. self.nix, self.niy, self.niz
Change :
10. self.numb_defectObject
11. self.ltop[ 0 : self.nlc ]
12. self.linkmp[ 0 : self.numb_defectObject ]
'''
self.box = np.array( j_must_have( jdata, 'box' ) )
self.linkcell_space = np.array( j_must_have( jdata, 'linkcell_space' ) )
for item in self.linkcell_space > self.box :
if item : raise RuntimeError( 'linkcell_space > box, wrong !' )
rcutoff_elastic = j_must_have( jdata, 'rcutoff_elastic' )
for item in self.linkcell_space < rcutoff_elastic :
if item : raise RuntimeError( 'linkcell_space < rcutoff_elastic, wrong !' )
'python3 np.divide, / and np.true_divide are same.'
self.fnlc_vector = np.floor_divide( self.box, self.linkcell_space )
self.nlc_vector = convert_int_array( self.fnlc_vector )
self.nlc = self.nlc_vector[ 0 ] * self.nlc_vector[ 1 ] * self.nlc_vector[ 2 ]
self.periodic = j_must_have( jdata, 'periodic' )
self.nnbrs = j_must_have( jdata, 'max_numb_in_27_cells' )
self.hmeps = -1e-9
self.nix = [ 0, -1, -1, -1, 0, 0, -1, 1, -1, 0, 1, -1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, -1, -1, -1 ]
self.niy = [ 0, 0, -1, 1, 1, 0, 0, 0, -1, -1, -1, 1, 1, 1, -1, 0, 1, -1, 1, 0, -1, 0, -1, 1, 0, -1, 1 ]
self.niz = [ 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]
self.linked( tmp_defectObject_list )
def set_min_max_nsize_dict(self, defectsys, jdata):
'set min nsize and max nsize for every defecttype.'
ICluster_lower = 2
ICluster_upper = j_must_have(jdata, 'ICluster_upper')
VCluster_lower = 2
VCluster_upper = VCluster_lower #
ILoop100_lower = ICluster_upper + 1
ILoop100_upper = ILoop100_lower #
ILoop111_lower = ICluster_upper + 1
ILoop111_upper = ILoop111_lower #
VLoop100_lower = j_must_have(jdata, 'VLoop_lower')
VLoop100_upper = VLoop100_lower #
VLoop111_lower = VLoop100_lower
VLoop111_upper = VLoop111_lower #
self.min_nsize_dict = {
'I': 1,
'V': 1,
'ICluster': ICluster_lower,
'VCluster': VCluster_lower,
'ILoop100': ILoop100_lower,
'VLoop100': VLoop100_lower,
'ILoop111': ILoop111_lower,
'VLoop111': VLoop111_lower
}
self.max_nsize_dict = {
'I': 1,
'V': 1,
'ICluster': ICluster_upper,
'VCluster': VCluster_upper,
'ILoop100': ILoop100_upper,
'VLoop100': VLoop100_upper,
'ILoop111': ILoop111_upper,
'VLoop111': VLoop111_upper
}
for item in defectsys.defectObject_list:
tmp_defecttype = item.defecttype
tmp_nsize = item.nsize
if self.max_nsize_dict[tmp_defecttype] < tmp_nsize:
self.max_nsize_dict[tmp_defecttype] = tmp_nsize
self.max_nsize = max(item for item in self.max_nsize_dict.values())
def output_points(self, defectsys, jdata):
''' format:
I 1 10.0 10.0 10.0
V 1 10.0 10.0 10.0
'''
box = np.array(j_must_have(jdata, 'box'))
total_point_defects_str_list = self._return_points(defectsys, jdata)
new_total_point_defects_str_list = [
to_str(box) + ' # b011, b022, b033\n'
]
for item in total_point_defects_str_list:
defectStr = item.lstrip().rstrip()
defectStr_list = defectStr.split()
position = np.array(
[np.float64(item2) for item2 in defectStr_list[0:3]]) * box
if defectStr_list[3] == '0':
new_defectStr = 'V ' + ' 1 ' + to_str(position) + '\n'
else:
new_defectStr = 'I ' + ' 1 ' + to_str(position) + '\n'
new_total_point_defects_str_list.append(new_defectStr)
self.file_out_points.writelines(new_total_point_defects_str_list)
def output_area_density(self, jdata):
''' format:
I 1 1.0
V 1 1.0
ICluster nsize 1.0
VCluster nsize 1.0
ILoop100 nsize 1.0
ILoop111 nsize 1.0
VLoop100 nsize 1.0
VLoop111 nsize 1.0
'''
box = j_must_have(jdata, 'box')
area = box[0] * box[1]
density_str_list = [
'#--(1) Dtype--(2) nsize--(3) density( nm^-2 )---\n'
]
for item in self.sum_numb_nsize_dict.keys():
min_size = self.min_nsize_dict[item]
max_size = self.max_nsize_dict[item]
for i in range(self.sum_numb_nsize_dict[item].size):
if i >= min_size and i <= max_size:
density_str = item + ' ' + str(i) + ' ' + str(
self.sum_numb_nsize_dict[item][i] / area) + '\n'
density_str_list.append(density_str)
self.file_out_area_density.writelines(density_str_list)
def set_sum_numb_nsize_dict(self, defectsys, jdata):
defecttypes = j_must_have(jdata, 'defecttype')
self.sum_numb_nsize_dict = {}
for item in defecttypes:
self.sum_numb_nsize_dict[item] = np.zeros(self.max_nsize + 1)
for item in defectsys.defectObject_list:
tmp_defecttype = item.defecttype
tmp_nsize = item.nsize
self.sum_numb_nsize_dict[tmp_defecttype][tmp_nsize] += 1.0
def multi_cascade_annealing(jdata, cascade):
tmp_ConstNumber = ConstNumber(jdata)
box = j_must_have(jdata, 'box')
trap = False
trapSys = None
if j_have(jdata, 'trap'): trap = jdata['trap']
if trap: trapSys = TrapSystem(jdata)
total_cascade_numb = int(jdata['fluence'] * box[0] * box[1])
position_random = jdata['position_random']
cascade_numb = cascade.return_cascade_numb()
i_select = np.random.randint(0, cascade_numb)
'build a defectSys of Class DefectSystem for okmc simulation.'
defectSys = DefectSystem(jdata,
cascade.return_defectStr_list(jdata, i_select))
outputFile = OutputFile(defectSys, jdata)
print('# %d cascades in database, total %d cascades annealing' %
(cascade_numb, total_cascade_numb))
for i in range(total_cascade_numb):
start_time = time.time()
'reset trap for all defectObject in model of Class DefectSystem.'
if trap: defectSys.reset_trap_defectSystem(jdata, trapSys)
defectSys.evolution(jdata, outputFile, trapSys)
i_select = np.random.randint(0, cascade_numb)
add_defectStr_list = cascade.return_defectStr_list(jdata, i_select)
defectSys.add_defectObject(jdata, add_defectStr_list, position_random)
defectSys.set_initial_recombine_and_related_properties(
jdata, tmp_ConstNumber)
defectSys.set_zero_c_time()
end_time = time.time()
print('# cascade %d running time: %.3f s' % (i, end_time - start_time))
print('# ')
print('# All cascades annealing done !')
return None
def load_point_defects_uniform_distribution(self, jdata, seed=None):
'''
self.defectStr_list, format:
'I 1 10.0 10.0 10.0\n'
'V 1 10.0 10.0 10.0\n'
len( ) == 5
'''
if seed != None: np.random.seed(seed)
tmp_box = np.array(j_must_have(jdata, 'box'))
self.defectStr_list = []
for i in range(self.I_total):
position = np.random.random(3) * tmp_box
defectStr = 'I 1 ' + to_str(position) + '\n'
self.defectStr_list.append(defectStr)
for i in range(self.I_total):
position = np.random.random(3) * tmp_box
defectStr = 'V 1 ' + to_str(position) + '\n'
self.defectStr_list.append(defectStr)
def output_cfg(self, defectsys, jdata):
'''
output configuration file with format *.cfg:
Number of particles = 10000
A = 1 Angstrom (basic length-scale)
H0(1,1) = 760.164 A
H0(1,2) = 0 A
H0(1,3) = 0 A
H0(2,1) = 0 A
H0(2,2) = 760.164 A
H0(2,3) = 0 A
H0(3,1) = 0 A
H0(3,2) = 0 A
H0(3,3) = 760.164 A
.NO_VELOCITY.
entry_count = 4
auxiliary[0] = IV
183.839996
W
0 0 0 1
183.839996
W
0.00208333 0.00208333 0.00208 0
'''
box = j_must_have(jdata, 'box')
mass = j_must_have(jdata, 'mass')
symbol = j_must_have(jdata, 'symbol')
total_point_defects_str_list = self._return_points(defectsys, jdata)
numb_point_defects = len(total_point_defects_str_list)
head_str_list = []
head_str_list.append('Number of particles = ' +
str(numb_point_defects) + '\n')
head_str_list.append('A = 1 Angstrom (basic length-scale)' + '\n')
head_str_list.append('H0(1,1) = ' + str(box[0] * 10.0) + ' ' + 'A' +
'\n')
head_str_list.append('H0(1,2) = 0 A' + '\n')
head_str_list.append('H0(1,3) = 0 A' + '\n')
head_str_list.append('H0(2,1) = 0 A' + '\n')
head_str_list.append('H0(2,2) = ' + str(box[1] * 10.0) + ' ' + 'A' +
'\n')
head_str_list.append('H0(2,3) = 0 A' + '\n')
head_str_list.append('H0(3,1) = 0 A' + '\n')
head_str_list.append('H0(3,2) = 0 A' + '\n')
head_str_list.append('H0(3,3) = ' + str(box[2] * 10.0) + ' ' + 'A' +
'\n')
head_str_list.append('.NO_VELOCITY.' + '\n')
head_str_list.append('entry_count = 4' + '\n')
head_str_list.append('auxiliary[0] = IV' + '\n')
self.file_out_cfg.writelines(head_str_list)
new_total_point_defects_str_list = []
for item in total_point_defects_str_list:
new_total_point_defects_str_list.append(str(mass) + '\n')
new_total_point_defects_str_list.append(symbol + '\n')
new_total_point_defects_str_list.append(item)
self.file_out_cfg.writelines(new_total_point_defects_str_list)
def __init__(self, defectsys, jdata, index=None):
'property'
self.out_dir = os.path.join(j_must_have(jdata, 'out_dir'), 'output')
if index == None or index == 0:
if os.path.exists(self.out_dir): shutil.rmtree(self.out_dir)
os.mkdir(self.out_dir)
if index != None:
self.out_dir = os.path.join(self.out_dir, str(index))
if os.path.exists(self.out_dir): shutil.rmtree(self.out_dir)
os.mkdir(self.out_dir)
self.step = defectsys.c_step
self.time = defectsys.c_time
self.out_style_freq = j_must_have(jdata, 'out_style_freq')
self.out_cfg = False
if j_have(jdata, 'out_cfg_dir_name'):
'0. self.out_cfg, 1. self.cfg_path, 2. self.cfg_name, 3. self.target_cfg'
self.out_cfg = True
out_cfg_dir_name = jdata['out_cfg_dir_name']
self.cfg_path = os.path.join(self.out_dir, out_cfg_dir_name[0])
os.mkdir(self.cfg_path)
self.cfg_name = out_cfg_dir_name[1]
self.target_cfg = os.path.join(
self.cfg_path, self.cfg_name + '.' + str(self.step) + '.cfg')
self.out_defectStr = False
if j_have(jdata, 'out_defectStr_dir_name'):
'0. self.out_defectStr, 1. self.defectStr_path, 2. self.defectStr_name, 3. self.target_defectStr'
self.out_defectStr = True
out_defectStr_dir_name = jdata['out_defectStr_dir_name']
self.defectStr_path = os.path.join(self.out_dir,
out_defectStr_dir_name[0])
os.mkdir(self.defectStr_path)
self.defectStr_name = out_defectStr_dir_name[1]
self.target_defectStr = os.path.join(
self.defectStr_path,
self.defectStr_name + '.' + str(self.step))
self.out_volume_density = False
if j_have(jdata, 'out_volume_density_dir_name'):
'0. self.out_volume_density, 1. self.volume_density_path, 2. self.volume_density_name, 3. self.target_volume_density'
self.out_volume_density = True
out_volume_density_dir_name = jdata['out_volume_density_dir_name']
self.volume_density_path = os.path.join(
self.out_dir, out_volume_density_dir_name[0])
os.mkdir(self.volume_density_path)
self.volume_density_name = out_volume_density_dir_name[1]
self.target_volume_density = os.path.join(
self.volume_density_path,
self.volume_density_name + '.' + str(self.step))
self.out_area_density = False
if j_have(jdata, 'out_area_density_dir_name'):
'0. self.out_area_density, 1. self.area_density_path, 2. self.area_density_name, 3. self.target_area_density'
self.out_area_density = True
out_area_density_dir_name = jdata['out_area_density_dir_name']
self.area_density_path = os.path.join(self.out_dir,
out_area_density_dir_name[0])
os.mkdir(self.area_density_path)
self.area_density_name = out_area_density_dir_name[1]
self.target_area_density = os.path.join(
self.area_density_path,
self.area_density_name + '.' + str(self.step))
self.out_points = False
if j_have(jdata, 'out_point_defects_dir_name'):
'0. self.out_points, 1. self.points_path, 2. self.points_name, 3. self.target_points'
self.out_points = True
out_points_dir_name = jdata['out_point_defects_dir_name']
self.points_path = os.path.join(self.out_dir,
out_points_dir_name[0])
os.mkdir(self.points_path)
self.points_name = out_points_dir_name[1]
self.target_points = os.path.join(
self.points_path, self.points_name + '.' + str(self.step))
self.out_size_distri = False
if j_have(jdata, 'out_size_distri_dir_name'):
'0. self.out_size_distri, 1. self.size_distri_path, 2. self.size_distri_name, 3. self.target_size_distri.'
self.out_size_distri = True
out_size_distri_dir_name = jdata['out_size_distri_dir_name']
self.size_distri_path = os.path.join(self.out_dir,
out_size_distri_dir_name)
os.mkdir(self.size_distri_path)
self.out_size_distri_defecttype = jdata[
'out_size_distri_defecttype']
for item in self.out_size_distri_defecttype:
os.mkdir(os.path.join(self.size_distri_path, item))
'1. self.target_steptime.'
out_steptime_dir_name = j_must_have(jdata, 'out_steptime_dir_name')
steptime_path = os.path.join(self.out_dir, out_steptime_dir_name[0])
os.mkdir(steptime_path)
self.target_steptime = os.path.join(steptime_path,
out_steptime_dir_name[1])
self.file_out_steptime = open(self.target_steptime, 'w')
self.file_out_steptime.writelines([
'# step, c_time(s), total_defects_I, total_defects_V, numb_defectObject'
+ '\n'
])
self.file_out_steptime.close()
self.set_min_max_nsize_dict(defectsys, jdata)
self.set_sum_numb_nsize_dict(defectsys, jdata)
def load_cascade_from_file(self, jdata, serial_numb):
'''
1. self.cluster == True, cascade file format:
100.0 100.0 100.0 # b011, b022, b033, units: nm
I 1 10.0 10.0 10.0
V 1 10.0 10.0 10.0
...
reading defects and convert clusters
2. self.cluster == False, cascade file format:
100.0 100.0 100.0 # b011, b022, b033, units: nm
(1): ILoop100 13 10.0 10.0 10.0
(2): ILoop111 13 10.0 10.0 10.0 0.5 0.5 0.5
...
reading defects directly
'''
if serial_numb > self.cascade_numb:
raise RuntimeError('serial_numb %d not in range [ 0, %d ]' %
(serial_numb, self.cascade_numb))
file_in = open(self.cascade_file[serial_numb], 'r')
alatt = j_must_have(jdata, 'alatt')
burgers_vector_unit_array = np.array(
j_must_have(jdata, 'burgers_vector_unit'))
burgers_vector_scale_length_array = np.array(
j_must_have(jdata, 'burgers_vector_scale_length'))
'set d_probability = 1.0 / burgers_vector_scale_length_array.size + 0.037142857 formatly.'
d_probability = 0.037142857 + 1.0 / burgers_vector_scale_length_array.size
if j_have(jdata, 'probability'): d_probability = jdata['probability']
if self.cluster:
# test_cgzhang
print('defect cluster algorithm is done!')
I_position_list = []
V_position_list = []
s = file_in.readline()
defectStr = s.lstrip().rstrip()
defectStr_list = defectStr.split()
tmp_box = np.array(
[np.float64(item) for item in defectStr_list[0:3]])
while True:
s = file_in.readline()
if s == '':
break
defectStr = s.lstrip().rstrip()
defectStr_list = defectStr.split()
position = [np.float64(item) for item in defectStr_list[2:5]]
if defectStr_list[0] == 'I':
I_position_list.append(position)
else:
V_position_list.append(position)
I_position_array = np.array(I_position_list)
V_position_array = np.array(V_position_list)
clusterSys = ClusterSystem(alatt, self.ICluster_upper,
self.VLoop_lower, 'I',
self.IC_VC_rcut[0], I_position_array,
tmp_box, burgers_vector_unit_array,
burgers_vector_scale_length_array,
d_probability)
clusterSys.add_clusters(alatt, self.ICluster_upper,
self.VLoop_lower, 'V', self.IC_VC_rcut[1],
V_position_array, tmp_box)
self.defectStr_list = clusterSys.return_defectStr_list()
else:
self.defectStr_list = []
s = file_in.readline()
while True:
s = file_in.readline()
if s == '':
break
self.defectStr_list.append(s)
def load_cascade_from_formula(self, jdata, seed=None):
'''
self.defectStr_list, defectStr format:
'I 1 10.0 10.0 10.0\n'
'ICluster 7 10.0 10.0 10.0\n'
'ILoop111 13 10.0 10.0 10.0\n'
'ILoop100 13 10.0 10.0 10.0\n'
'V 1 10.0 10.0 10.0\n'
'VCluster 7 10.0 10.0 10.0\n'
'VLoop111 13 10.0 10.0 10.0\n'
'VLoop100 13 10.0 10.0 10.0\n'
'''
if seed != None: np.random.seed(seed)
tmp_box = np.array(j_must_have(jdata, 'box'))
self.create_defects_formula_distribution()
self.defectStr_list = []
for item in self.int_defect_size_R:
if item[0] == 1:
defecttype = 'I'
elif item[0] >= 2 and item[0] <= self.ICluster_upper:
defecttype = 'ICluster'
elif item[0] > self.ICluster_upper:
if np.random.rand() < self.ratio_ILoop111_ILoop100[0]:
defecttype = 'ILoop111'
else:
defecttype = 'ILoop100'
position = 0.5 * tmp_box + R_convert_to_position(item[1])
defectStr = defecttype + ' ' + str(
item[0]) + ' ' + to_str(position) + '\n'
self.defectStr_list.append(defectStr)
for item in self.vac_defect_size_R:
if item[0] == 1:
defecttype = 'V'
elif item[0] >= 2 and item[0] < self.VLoop_lower:
defecttype = 'VCluster'
elif item[0] >= self.VLoop_lower:
kesi = np.random.rand()
if kesi < self.ratio_VCluster_VLoop100_VLoop111[0]:
defecttype = 'VCluster'
elif kesi < self.ratio_VCluster_VLoop100_VLoop111[
0] + self.ratio_VCluster_VLoop100_VLoop111[1]:
defecttype = 'VLoop100'
else:
defecttype = 'VLoop111'
position = 0.5 * tmp_box + R_convert_to_position(item[1])
defectStr = defecttype + ' ' + str(
item[0]) + ' ' + to_str(position) + '\n'
self.defectStr_list.append(defectStr)
def __init__(self, jdata):
'''
Class Cascade properties:
1. self.defectStr_list
format:
(1): ILoop100 13 10.0 10.0 10.0
(2): ILoop111 13 10.0 10.0 10.0 0.5 0.5 0.5
mode :
1. cascade from formula
2. cascade from file
a. self.cluster == True, defects of I and V convert into clusters
b. self.cluster == False, defects of I and V does not convert into clusters
3. cascade I and V randomly and uniformly distributed in simulation box, for electron irradiation
'''
self.cascade_from_formula = False
if j_have(jdata, 'cascade_from_formula'):
self.cascade_from_formula = jdata['cascade_from_formula']
if self.cascade_from_formula:
self.cascade_numb = j_must_have(jdata, 'cascade_numb')
self.I_total = j_must_have(jdata, 'I_total')
self.SI = j_must_have(jdata, 'SI')
self.mu = j_must_have(jdata, 'mu')
self.sigma = j_must_have(jdata, 'sigma')
self.SV = j_must_have(jdata, 'SV')
self.ICluster_upper = j_must_have(jdata, 'ICluster_upper')
self.ratio_ILoop111_ILoop100 = j_must_have(
jdata, 'ratio_ILoop111_ILoop100')
self.VLoop_lower = j_must_have(jdata, 'VLoop_lower')
self.ratio_VCluster_VLoop100_VLoop111 = j_must_have(
jdata, 'ratio_VCluster_VLoop100_VLoop111')
self.cascade_from_file = False
if j_have(jdata, 'cascade_from_file'):
self.cascade_from_file = jdata['cascade_from_file']
if self.cascade_from_file:
sys_path = j_must_have(jdata, 'systems')
cascade_prefix = j_must_have(jdata, 'cascade_prefix')
if j_have(jdata, 'sys_defects_cfg'):
sys_defects_cfg = jdata['sys_defects_cfg']
defects_cfg_prefix = j_must_have(jdata, 'defects_cfg_prefix')
self.defects_cfg_file = glob.glob(
os.path.join(sys_defects_cfg, defects_cfg_prefix + '.*'))
self.defects_cfg_file.sort(key=return_serial_numb_in_str)
if os.path.exists(sys_path): shutil.rmtree(sys_path)
os.mkdir(sys_path)
self.cascade_cfg_2_points_defectStr(sys_path, cascade_prefix)
self.cascade_file = glob.glob(
os.path.join(sys_path, cascade_prefix + '.*'))
self.cascade_file.sort(key=return_serial_numb_in_str)
self.cascade_numb = len(self.cascade_file)
self.cluster = j_must_have(jdata, 'cluster')
if self.cluster:
self.IC_VC_rcut = j_must_have(jdata, 'IC_VC_rcut')
self.VLoop_lower = j_must_have(jdata, 'VLoop_lower')
self.ICluster_upper = j_must_have(jdata, 'ICluster_upper')
self.point_defects_uniform_distribution = False
if j_have(jdata, 'point_defects_uniform_distribution'):
self.point_defects_uniform_distribution = jdata[
'point_defects_uniform_distribution']
if self.point_defects_uniform_distribution:
self.cascade_numb = j_must_have(jdata, 'cascade_numb')
self.I_total = j_must_have(jdata, 'I_total')
