def remove_duplicate_grains(grain_data,
qsyms,
dist_thresh=0.01,
misorient_thresh=0.1,
comp_diff=0.1):
total_grains = grain_data.shape[0]
all_comp = grain_data[:, 1]
grain_quats = rot.quatOfExpMap(grain_data[:, 3:6].T)
dup_list = np.array([])
print 'Removing duplicate grains'
for i in np.arange(total_grains - 1):
cur_pos = grain_data[i, 3:6]
other_pos = grain_data[(i + 1):, 3:6]
xdist = cur_pos[0] - other_pos[:, 0]
ydist = cur_pos[1] - other_pos[:, 1]
zdist = cur_pos[2] - other_pos[:, 2]
dist = np.sqrt(xdist**2. + ydist**2. + zdist**2.)
if np.min(dist) < dist_thresh:
q1 = sym.toFundamentalRegion(np.atleast_2d(grain_quats[:, i]).T,
crysSym=qsyms)
q2 = sym.toFundamentalRegion(np.atleast_2d(
grain_quats[:, np.argmin(dist) + i + 1]).T,
crysSym=qsyms)
misorientation = rot.misorientation(q1, q2)[0] * 180. / np.pi
if misorientation < misorient_thresh:
dup_list = np.append(dup_list, np.argmin(dist) + i + 1)
if (np.abs(all_comp[i] - all_comp[np.argmin(dist) + i + 1]) <=
comp_diff):
grain_data[
i, :] = (grain_data[i, :] +
grain_data[np.argmin(dist) + i + 1, :]) / 2.
elif ((all_comp[np.argmin(dist) + i + 1] - all_comp[i]) > 0):
grain_data[i, :] = grain_data[np.argmin(dist) + i + 1, :]
grain_data = np.delete(grain_data, dup_list, axis=0)
print 'Removed %d Grains' % (len(dup_list))
grain_data[:, 0] = np.arange(grain_data.shape[0])
return grain_data, dup_list
def remove_duplicate_grains(grain_data,qsyms,dist_thresh=0.01,misorient_thresh=0.1,comp_diff=0.1):
total_grains=grain_data.shape[0]
all_comp=grain_data[:,1]
grain_quats=rot.quatOfExpMap(grain_data[:,3:6].T)
dup_list=np.array([])
print 'Removing duplicate grains'
for i in np.arange(total_grains-1):
cur_pos=grain_data[i,3:6]
other_pos=grain_data[(i+1):,3:6]
xdist=cur_pos[0]-other_pos[:,0]
ydist=cur_pos[1]-other_pos[:,1]
zdist=cur_pos[2]-other_pos[:,2]
dist=np.sqrt(xdist**2.+ydist**2.+zdist**2.)
if np.min(dist)<dist_thresh:
q1=sym.toFundamentalRegion(np.atleast_2d(grain_quats[:,i]).T,crysSym=qsyms)
q2=sym.toFundamentalRegion(np.atleast_2d(grain_quats[:,np.argmin(dist)+i+1]).T,crysSym=qsyms)
misorientation=rot.misorientation(q1,q2)[0]*180./np.pi
if misorientation < misorient_thresh:
dup_list=np.append(dup_list,np.argmin(dist)+i+1)
if (np.abs(all_comp[i] - all_comp[np.argmin(dist)+i+1]) <=comp_diff):
grain_data[i,:]=(grain_data[i,:]+grain_data[np.argmin(dist)+i+1,:])/2.
elif ( (all_comp[np.argmin(dist)+i+1]-all_comp[i]) >0):
grain_data[i,:]=grain_data[np.argmin(dist)+i+1,:]
grain_data=np.delete(grain_data,dup_list,axis=0)
print 'Removed %d Grains' % (len(dup_list))
grain_data[:,0]=np.arange(grain_data.shape[0])
return grain_data,dup_list
mat_list = cpl.load(open(material_file_loc, 'r'))
mat_idx = np.where([
mat_list[i].name == mat_name for i in range(len(mat_list))
])[0]
# grab plane data, and useful things hanging off of it
pd = mat_list[mat_idx[0]].planeData
qsyms = sym.quatOfLaueGroup(pd.getLaueGroup())
for w in range(0, len(test[0])):
q2 = np.atleast_2d(q_mor[:, grain_map_g[test[0][w],
test[1][w],
test[2][w]]]).T
q1 = np.atleast_2d(q_avg[:, grain_id]).T
mis[test[0][w], test[1][w],
test[2][w]] = rot.misorientation(q1,
q2)[0] * 180. / np.pi
# plt.imshow(confidence_map_g[20,:,:],cmap='gray')
# plt.hold(True)
# plt.imshow(mis[20,:,:], alpha = 0.5)
# plt.colorbar()
#==============================================================================
# put back into the master mesh
#==============================================================================
print('put in master mesh')
#fresh array
empty_map_full = np.zeros(compiled_map.shape)
#confidence_index_local = np.copy(empty_map_full)
#grain_map_local = np.copy(empty_map_full)
mis_local = np.copy(empty_map_full)
compiled_map_local = np.copy(empty_map_full)
# rotmats_grain = []
# expmaps_grain = []
# Eulers_grain = np.zeros([len(no_load_scans),3])
quats_init = rot.quatOfExpMap(grain_data['scan21'][:, 3:6].T)
expmaps_init = grain_data['scan21'][:, 3:6].T
quats_final = rot.quatOfExpMap(
(grain_data['scan%d' % no_load_scans[-1]][:, 3:6].T))
expmaps_final = grain_data['scan111'][:, 3:6].T
grainlist = []
for i in range(ngrains):
mis = rot.misorientation(quats_init[:, i:i + 1], quats_final[:, i:i + 1],
(crystal_symmetry, ))[0]
mis_deg = np.degrees(mis)
if mis_deg > 0.05:
grainlist.append(i)
#%%
rmats_init = rot.rotMatOfExpMap(np.array(expmaps_init)[:, grainlist])
rmats_final = rot.rotMatOfExpMap(np.array(expmaps_final)[:, grainlist])
# getting symmetry group directly here; could also grab from planeData object
# qsym = symm.quatOfLaueGroup('d6h')
plane_data = load_pdata(
'/Users/rachellim/Documents/Research/CHESS_Jun17/2020-08-03/materials2.hexrd',
'ti7al')
qsym = plane_data.getQSym()
bmat = plane_data.latVecOps['B']
symmetry_symbol = 'd6h' #cubic high, d6h for hex high
crystal_symmetry = sym.quatOfLaueGroup(symmetry_symbol)
grain = 49
grain_id = int(grain_data['scan12'][grain, 0])
mis_ang = []
rotmats_grain = []
expmaps_grain = []
Eulers_grain = np.zeros([len(scanIDs), 3])
for i in range(len(scanIDs)):
q108 = rot.quatOfExpMap(grain_data['scan%d' % scanIDs[i]][:, 3:6].T)
expmaps_grain.append(grain_data['scan%d' % scanIDs[i]][grain, 3:6])
mis = rot.misorientation(quats_init[:, grain:grain + 1],
q108[:, grain:grain + 1], (crystal_symmetry, ))[0]
mis_ang.append(mis)
# rotmats_grain.append(rot.rotMatOfExpMap(grain_data['scan%d'%no_load_scans[i]][grain,3:6].T))
# Eulers_grain[i,:] = rot.angles_from_rmat_zxz(rot.rotMatOfExpMap(expmaps_grain))
mis_ang_deg = np.degrees(np.array(mis_ang))
#%%
rmats = rot.rotMatOfExpMap(np.array(expmaps_grain).T)
# getting symmetry group directly here; could also grab from planeData object
# qsym = symm.quatOfLaueGroup('d6h')
plane_data = load_pdata(
'/Users/rachellim/Documents/Research/CHESS_Jun17/2020-08-03/materials2.hexrd',
'ti7al')
qsym = plane_data.getQSym()
delta_stress22 = np.diff(stress22)
delta_stress33 = np.diff(stress33)
delta_vonmises = np.diff(vonmises)
delta_hydrostatic = np.diff(hydrostatic)
#%% Calculate misorientation from initial orientation
mis = np.zeros([ngrains, len(scanIDs)])
quats_init = rot.quatOfExpMap(grain_data['scan%d' % scanIDs[0]][:, 3:6].T)
for i in range(len(scanIDs)):
quats_this = rot.quatOfExpMap(grain_data['scan%d' % scanIDs[i]][:, 3:6].T)
for j in range(len(quats_init.T)):
mis[j, i] = np.degrees(
rot.misorientation(quats_init[:, j:j + 1], quats_this[:,
j:j + 1])[0])
#%% Stress reasonability check
mean_stress11 = np.mean(stress11, axis=0)
mean_stress22 = np.mean(stress22, axis=0)
mean_stress33 = np.mean(stress33, axis=0)
mean_vonmises = np.mean(vonmises, axis=0)
mean_hydrostatic = np.mean(hydrostatic, axis=0)
fig2 = plt.figure()
plt.plot(mean_stress11, '.')
plt.plot(mean_stress22, '.')
plt.plot(mean_stress33, '.')
plt.plot(mean_vonmises, '.')
plt.plot(mean_hydrostatic, '.')