def test_IPF(self, lattice):
direction = np.random.random(3) * 2.0 - 1
for rot in [Rotation.from_random() for r in range(n // 100)]:
R = damask.Orientation(rot, lattice)
color = R.IPFcolor(direction)
for equivalent in R.equivalentOrientations():
assert np.allclose(color, R.IPFcolor(direction))
def test_add_IPFcolor(self, default, d):
default.add_IPFcolor('orientation', d)
loc = {
'orientation': default.get_dataset_location('orientation'),
'color':
default.get_dataset_location('IPFcolor_[{} {} {}]'.format(*d))
}
qu = default.read_dataset(loc['orientation']).view(np.double).reshape(
-1, 4)
crystal_structure = default.get_crystal_structure()
in_memory = np.empty((qu.shape[0], 3), np.uint8)
for i, q in enumerate(qu):
o = damask.Orientation(q, crystal_structure).reduced()
in_memory[i] = np.uint8(o.IPFcolor(np.array(d)) * 255)
in_file = default.read_dataset(loc['color'])
assert np.allclose(in_memory, in_file)
def test_IPF_cubic(self, color, lattice):
cube = damask.Orientation(damask.Rotation(), lattice)
for direction in set(permutations(np.array(color['direction']))):
assert np.allclose(cube.IPFcolor(np.array(direction)),
np.array(color['RGB']))
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# ------------------------------------------ assemble header ---------------------------------------
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
table.labels_append(['{}_pole_{}{}{}'.format(i+1,*options.pole) for i in xrange(2)])
table.head_write()
# ------------------------------------------ process data ------------------------------------------
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
if inputtype == 'eulers':
o = damask.Orientation(Eulers = np.array(map(float,table.data[column:column+3]))*toRadians)
elif inputtype == 'matrix':
o = damask.Orientation(matrix = np.array(map(float,table.data[column:column+9])).reshape(3,3).transpose())
elif inputtype == 'frame':
o = damask.Orientation(matrix = np.array(map(float,table.data[column[0]:column[0]+3] + \
table.data[column[1]:column[1]+3] + \
table.data[column[2]:column[2]+3])).reshape(3,3))
elif inputtype == 'quaternion':
o = damask.Orientation(quaternion = np.array(map(float,table.data[column:column+4])))
rotatedPole = o.quaternion*pole # rotate pole according to crystal orientation
(x,y) = rotatedPole[0:2]/(1.+abs(pole[2])) # stereographic projection
table.data_append([np.sqrt(x*x+y*y),np.arctan2(y,x)] if options.polar else [x,y]) # cartesian coordinates
outputAlive = table.data_write() # output processed line
])
if output == 'eulers':
table.labels_append([
'{}_eulers({})'.format(i + 1, options.symmetry)
for i in xrange(3)
])
table.head_write()
# ------------------------------------------ process data ------------------------------------------
outputAlive = True
while outputAlive and table.data_read(
): # read next data line of ASCII table
if inputtype == 'eulers':
o = damask.Orientation(
Eulers=np.array(map(float, table.data[column:column + 3])) *
toRadians,
symmetry=options.symmetry).reduced()
elif inputtype == 'matrix':
o = damask.Orientation(matrix=np.array(
map(float,
table.data[column:column + 9])).reshape(3, 3).transpose(),
symmetry=options.symmetry).reduced()
elif inputtype == 'frame':
o = damask.Orientation(matrix = np.array(map(float,table.data[column[0]:column[0]+3] + \
table.data[column[1]:column[1]+3] + \
table.data[column[2]:column[2]+3])).reshape(3,3),
symmetry = options.symmetry).reduced()
elif inputtype == 'quaternion':
o = damask.Orientation(quaternion=np.array(
map(float, table.data[column:column + 4])),
symmetry=options.symmetry).reduced()
column = table.label_index(label)
# ------------------------------------------ assemble header ---------------------------------------
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
table.labels_append(['{}_SphericalEulers'.format(1 + i) for i in range(3)])
table.head_write()
# ------------------------------------------ process data ------------------------------------------
outputAlive = True
while outputAlive and table.data_read(
): # read next data line of ASCII table
if inputtype == 'eulers':
o = damask.Orientation(Eulers=np.array(
list(map(float, table.data[column:column + 3]))) * toRadians,
symmetry=options.symmetry).reduced()
elif inputtype == 'matrix':
o = damask.Orientation(matrix=np.array(
list(map(float, table.data[column:column + 9]))).reshape(
3, 3).transpose(),
symmetry=options.symmetry).reduced()
elif inputtype == 'frame':
o = damask.Orientation(matrix = np.array(list(map(float,table.data[column[0]:column[0]+3] + \
table.data[column[1]:column[1]+3] + \
table.data[column[2]:column[2]+3]))).reshape(3,3),
symmetry = options.symmetry).reduced()
elif inputtype == 'quaternion':
o = damask.Orientation(quaternion=np.array(
list(map(float, table.data[column:column + 4]))),
symmetry=options.symmetry).reduced()
# o = damask.Orientation(random=True, symmetry='tetragonal')
# vector,sym_op = o.inversePole([0,0,1],SST=True)
# q = o.equivalentQuaternions()[sym_op]
# angles = np.array(q.asEulers(degrees=True))
# vector = vector/np.linalg.norm(vector)
# X = vector[0]/(1 + abs(vector[2]))
# Y = vector[1]/(1 + abs(vector[2]))
# zeta = 0.0 if vector[0] == 0. and vector[1] == 0. else math.degrees(math.atan2(vector[1],vector[0]))
# eta = math.degrees(math.acos(vector[2]))
# o_convention = damask.Orientation(Eulers=np.radians(np.array([270. + zeta,eta,90.-zeta])))
# angle_conv = np.array([270. + zeta,eta,90.-zeta])
# angle_mis,axis = (o_convention.quaternion * q.conjugated()).asAngleAxis(degrees=True)
# # print angle_mis,axis[2]
# angle_mis = angle_mis * axis[2]
o = damask.Orientation(random=True, symmetry='tetragonal')
v, symOp = o.inversePole([0., 0., 1.])
print "vector", v, symOp, "\n"
X = v[0] / (1. + abs(v[2]))
Y = v[1] / (1. + abs(v[2]))
p = o.equivalentOrientations()[symOp]
eta = np.arccos(abs(v[2]))
zeta = np.arctan2(v[1], v[0])
c = damask.Orientation(Eulers=np.array(
[1.5 * np.pi + zeta, eta, 0.5 * np.pi - zeta]),
symmetry='tetragonal')
print "random", o.asEulers(degrees=True)
if options.verbose: bg.set_message('assigning grain IDs...')
for z in xrange(grid[2]):
for y in xrange(grid[1]):
for x in xrange(grid[0]):
if (myPos+1)%(N/500.) < 1:
time_delta = (time.clock()-tick) * (N - myPos) / myPos
if options.verbose: bg.set_message('(%02i:%02i:%02i) processing point %i of %i (grain count %i)...'
%(time_delta//3600,time_delta%3600//60,time_delta%60,myPos,N,nGrains))
myData = table.data[index[myPos]] # read data for current grid point
myPhase = int(myData[colPhase])
mySym = options.symmetry[min(myPhase,len(options.symmetry))-1] # take last specified option for all with higher index
if inputtype == 'eulers':
o = damask.Orientation(Eulers = myData[colOri:colOri+3]*toRadians,
symmetry = mySym)
elif inputtype == 'matrix':
o = damask.Orientation(matrix = myData[colOri:colOri+9].reshape(3,3).transpose(),
symmetry = mySym)
elif inputtype == 'frame':
o = damask.Orientation(matrix = np.hstack((myData[colOri[0]:colOri[0]+3],
myData[colOri[1]:colOri[1]+3],
myData[colOri[2]:colOri[2]+3],
)).reshape(3,3),
symmetry = mySym)
elif inputtype == 'quaternion':
o = damask.Orientation(quaternion = myData[colOri:colOri+4],
symmetry = mySym)
cos_disorientations = -np.ones(1,dtype='f') # largest possible disorientation
closest_grain = -1 # invalid neighbor
# close table
asciiTable.close(dismiss=True)
# ----- count slip traces in each grain ----- #
gids = set(texture_vctr) # get unique grain id
gammas_gid = []
sfs_gid = []
qs_gid = []
# calculate grain average accumulated shear and Schmid factors
for gid in gids:
gid_idc = np.where(texture_vctr == gid)[0]
gammas_gid.append(np.mean(gammas[gid_idc, :], axis=0))
sfs_gid.append(np.mean(sfs[gid_idc, :], axis=0))
# ----- get grain average orientation ----- #
qs_tmp = qs[gid_idc, :]
qs_tmp = [damask.Orientation(quaternion=damask.Quaternion(quatArray=q))
for q in qs_tmp]
qs_gid.append(damask.Orientation.average(qs_tmp).asQuaternion())
gammaSum_gid = [sum(map(abs, gamma)) for gamma in gammas_gid]
with open(fname.replace(".txt", ".grainSum.txt"), 'w') as f:
outstr = '1 header\n gammaSum\n'
outstr += "\n".join(map(str, gammaSum_gid))
f.write(outstr)
# slip family ID
sf_ids = [1]*3 + [2]*3 + [3]*6 + [4]*12
# write out the population file
# --> all slip systems in all grains
with open(fname.replace(".txt", ".population.txt"), 'w') as f:
action = 'store_true',
help = 'angles are given in degrees [%default]')
parser.add_option('-e', '--eulers',
dest='eulers',
type = 'float', nargs = 3, metavar = ' '.join(['float']*3),
help = 'crystallographic orientation as euler angles')
parser.set_defaults(eulers = (0.,0.,0.), # no rotation about 1,1,1
radians = False)
(options, filenames) = parser.parse_args()
eulers=np.array(options.eulers)
if not options.radians: eulers*=(np.pi/180.)
ori = damask.Orientation(matrix=np.dot(np.array([[0.0,-1.0,0.0],[-1.0,0.0,0.0],[0.0,0.0,-1.0]]),
damask.Orientation(Eulers=eulers).asMatrix()))
ori=damask.Orientation()
coordinates=[]
for x in np.linspace(-0.5,0.5,3):
for y in np.linspace(-0.5,0.5,3):
for z in np.linspace(-0.5,0.5,3):
coordinates.append([x,y,z])
coordinates=np.array(coordinates)
for i,c in enumerate(coordinates):
coordinates[i,:] = np.dot(ori.asMatrix(),c)
Miller110=np.array(
[[ 0, 1, 1],
[ 0,-1, 1],
[ 1, 0, 1],
[-1, 0, 1],
