def init_grain_map(self):
""" Read from geom input.
In damask, the microstructure indices ordered with x as fastest and z as slowest varying coordinate
https://damask.mpie.de/Documentation/GeometryFormat
Output:
self.num_grain: 1D int array with size nx * ny * nz
grain ID in each grid
"""
# find the geom file
files = os.listdir(self.idir)
for i in files:
if "input_clean.geom" in i:
geom_file = i
break
with open(self.idir + "/" + geom_file, 'r') as f:
for i, line in enumerate(f):
split_line = line.split()
if i == 0:
# read how many lines before grain ID map
skip_line = int(split_line[0])
# read the 2D grainID map and flatten into 1D
self.grain_map = np.loadtxt(self.idir + "/" + geom_file,
dtype=np.int32,
skiprows=skip_line + 1).flatten()
def init_slip_systems(self):
""" Read from material.config
Read Euler angles of grain orientation defined in material.config and transpose the vectors
(slip direction d, plane normal n and sense vector t) in such grain-orientation coordinate to
reference coordinate.
"""
# transpose of orientation matrix, i.e., Q^T, where Q is defined in
# Li el.al; International Journal of Plasticity 87 (2016) 154-180; Eq. (6)
omt = []
with open(self.idir + "/material.config", "r") as f:
for i, line in enumerate(f):
split_line = line.split()
if len(split_line) > 0 and split_line[0] == "(gauss)":
# a sample line is:
# (gauss) phi1 323.138 Phi 59.7321 phi2 342.952 scatter 0.0 fraction 1.0
euler_angle = [
float(split_line[2]),
float(split_line[4]),
float(split_line[6])
]
o = damask.Rotation.fromEulers(euler_angle, "-d")
omt.append(o.asMatrix())
# number of grains
ngrain = len(omt)
# slip direction, plane normal as a function of 12 slip system and grainID. vector length 3.
nsp = np.zeros((self.nslip, ngrain, 3))
bsp = np.zeros((self.nslip, ngrain, 3))
tsp = np.zeros((self.nslip, ngrain, 3))
# transfer slip system into global coordinate, where vectors in local coordinate are defined in slip_system
# v_global = O^{-1} * v_local = O^T * v_local
for i in range(self.nslip):
for j in range(ngrain):
# slip direction
b = np.dot(omt[j], slip_system[i, 0:3])
b = b / np.linalg.norm(b)
bsp[i, j] = b
# plane normal
n = np.dot(omt[j], slip_system[i, 3:])
n = n / np.linalg.norm(n)
nsp[i, j] = n
# sense vector
# according to line 2169, lattice_slip_transverse function in lattice.f90 in damask
# source code, t = b x n, i.e., cross product.
tsp[i, j] = np.cross(b, n)
return ngrain, bsp, nsp, tsp
def read_column(self, txt, label):
"""Return a column with label from the damask output txt file."""
with open(txt, 'r') as f:
for i, line in enumerate(f):
split_line = line.split()
if split_line[0] == "inc": # the label line
label_line = i
# the label row
for j in range(len(split_line)):
if split_line[j] == label:
colID = j
break
break
data = np.loadtxt(txt, skiprows = label_line + 1, usecols = colID)
return data
def read_column(self, txt, label):
"""Return a column with label from the damask output txt file."""
with open(txt, 'r') as f:
for i, line in enumerate(f):
split_line = line.split()
if split_line[0] == "inc": # the label line
label_line = i
# the label row
for j in range(len(split_line)):
if split_line[j] == label:
colID = j
break
break
print("Located IDs " + label)
start_time = time.time()
data = np.loadtxt(txt, skiprows=label_line + 1, usecols=colID)
print("time used to loadtxt = ", time.time() - start_time)
print("end loadtxt")
return data
def read_txt(self, txt):
""" Read the txt file generated by postResults to get shear rate, resolved shear stress, gradient shear rate."""
with open(txt, 'r') as f:
for i, line in enumerate(f):
split_line = line.split()
if split_line[0] == "inc": # the label line
label_line = i
# the label row
for j in range(len(split_line)):
if split_line[j] == "1_shearrate_slip":
colID = j
break
break
# the column arrangement is 12 shear rate, 12 resolved shear stress, and 36 gradient of shear rate
data = np.loadtxt(txt,
skiprows=label_line + 1,
usecols=range(colID, colID + 12 + 12 + 36))
for i in range(self.nslip):
self.gamma_dot[i] = data[:, i]
self.tau[i] = data[:, i + 12]
for j in range(3):
self.grad_gamma_dot[i, :, j] = data[:, 24 + i * 3 + j]
def init_load(self):
""" Read load file to get dt"""
# find the load file
files = os.listdir(self.idir)
for i in files:
if ".load" in i:
load_file = i
break
load_file = self.idir + "/" + load_file
# at this point, assume just one line in load file
with open(load_file, "r") as f:
for i, line in enumerate(f):
if i == 0:
split_line = line.split()
for j in range(len(split_line)):
if split_line[j] == "time":
time = float(split_line[j + 1])
if split_line[j] == "incs":
incs = float(split_line[j + 1])
self.dt = time / incs
return
def init_nxyz(self):
""" Read number of grids in three axes from the geom file.
Output:
nx, ny, nz: int
number of grids in three axes
"""
# find the geom file
files = os.listdir(self.idir)
for i in files:
if "input_clean.geom" in i:
geom_file = i
break
with open(self.idir + "/" + geom_file, 'r') as f:
for i, line in enumerate(f):
split_line = line.split()
if split_line[0] == "grid":
# read number of grids in thress axes
# format of this line is: grid a NX b NY c NZ
self.nx = int(split_line[2])
self.ny = int(split_line[4])
self.nz = int(split_line[6])
break
def make_dicts(cursor, row):
return dict(
(cursor.description[idx][0], value) for idx, value in enumerate(row))
