def main(ngrains=100,
sigma=15.,
c2a=1.6235,
mu=0.,
prc='cst',
isc=False,
tilt_1=0.,
tilts_about_ax1=0.,
tilts_about_ax2=0.):
"""
Arguments
=========
ngrains = 100
sigma = 15.
c2a = 1.6235
prc = 'cst' or 'ext'
tilts_about_ax1 = 0. -- Systematic tilting abount axis 1
tilts_about_ax2 = 0. -- Systematic tilting abount axis 2
tilt_1 = 0. -- Tilt in the basis pole. (systematic tilting away from ND)
"""
if isc:
h = mmm()
else:
h = np.array([np.identity(3)])
gr = []
for i in xrange(ngrains):
dth = random.uniform(-180., 180.)
if prc == 'cst':
g = gen_gr_fiber(th=dth, sigma=sigma, mu=mu, tilt=tilt_1,
iopt=0) # Basal//ND
elif prc == 'ext':
g = gen_gr_fiber(th=dth, sigma=sigma, mu=mu, tilt=tilt_1,
iopt=1) # Basal//ED
else:
raise IOError, 'Unexpected option'
for j in xrange(len(h)):
temp = np.dot(g, h[j].T)
## tilts_about_ax1
if abs(tilts_about_ax1) > 0:
g_tilt = rd_rot(tilts_about_ax1)
temp = np.dot(temp, g_tilt.T)
## tilts_about_ax2?
elif abs(tilts_about_ax2) > 0:
g_tilt = td_rot(tilts_about_ax2)
temp = np.dot(temp, g_tilt.T)
elif abs(tilts_about_ax2) > 0 and abs(tilts_about_ax2) > 0:
raise IOError, 'One tilt at a time is allowed.'
phi1, phi, phi2 = euler(a=temp, echo=False)
gr.append([phi1, phi, phi2, 1. / ngrains])
mypf = upf.polefigure(grains=gr, csym='hexag', cdim=[1, 1, c2a])
mypf.pf_new(poles=[[0, 0, 0, 2], [1, 0, -1, 0]],
cmap='jet',
ix='TD',
iy='RD')
return np.array(gr)
def to909090(gr):
"""
Reduce a grain in the full range angules to 90x90x90 cube
"""
# if gr[0]<0.:
# gr[0] = 360 + gr[0]
from sym import __mmm__ as mmm
from sym import cubic
sam = mmm() # orthorhombic sample symmetry
crm = cubic() # cubic crystal symmetry
a = euler(ph=gr[0], th=gr[1], tm=gr[2], echo=False) # ca<-sa
mats = []
newa = []
for i in range(len(sam)):
dum = np.dot(a, sam[i].T) # ca<-sa H
for j in range(len(crm)):
nnewa = np.dot(crm[j], dum) # H_ca ca<-sa H_sa
mats.append(nnewa)
#print len(mats)
eul_angs = []
n = 0
for i in range(len(mats)):
angs = euler(a=mats[i], echo=False)
if all(angs[k]<=90. for k in range(3)) and \
all(angs[k]>=0. for k in range(3)):
n = n + 1
#print angs
eul_angs.append(angs)
temp_gr = []
for i in range(len(eul_angs)):
temp_gr.append([eul_angs[i][0],
eul_angs[i][1],
eul_angs[i][2]])
temp_gr = np.around(temp_gr, decimals=3)
temp_gr = unique2d(np.array(temp_gr))
new_gr = []
for i in range(len(temp_gr)):
dgr = [temp_gr[i][0],temp_gr[i][1],temp_gr[i][2],gr[-1]/len(temp_gr)]
new_gr.append(dgr)
return np.array(new_gr)
def main(ngrains=100,sigma=15.,c2a=1.6235,mu=0.,
prc='cst',isc=False,tilt_1=0.,
tilts_about_ax1=0.,tilts_about_ax2=0.):
"""
Arguments
=========
ngrains = 100
sigma = 15.
c2a = 1.6235
prc = 'cst' or 'ext'
tilts_about_ax1 = 0. -- Systematic tilting abount axis 1
tilts_about_ax2 = 0. -- Systematic tilting abount axis 2
tilt_1 = 0. -- Tilt in the basis pole. (systematic tilting away from ND)
"""
if isc:
h = mmm()
else:
h=np.array([np.identity(3)])
gr = []
for i in xrange(ngrains):
dth = random.uniform(-180., 180.)
if prc=='cst': g = gen_gr_fiber(th=dth,sigma=sigma,mu=mu,tilt=tilt_1,iopt=0) # Basal//ND
elif prc=='ext': g = gen_gr_fiber(th=dth,sigma=sigma,mu=mu,tilt=tilt_1,iopt=1) # Basal//ED
else:
raise IOError, 'Unexpected option'
for j in xrange(len(h)):
temp = np.dot(g,h[j].T)
## tilts_about_ax1
if abs(tilts_about_ax1)>0:
g_tilt = rd_rot(tilts_about_ax1)
temp = np.dot(temp,g_tilt.T)
## tilts_about_ax2?
elif abs(tilts_about_ax2)>0:
g_tilt = td_rot(tilts_about_ax2)
temp = np.dot(temp,g_tilt.T)
elif abs(tilts_about_ax2)>0 and abs(tilts_about_ax2)>0:
raise IOError, 'One tilt at a time is allowed.'
phi1,phi,phi2 = euler(a=temp, echo=False)
gr.append([phi1,phi,phi2,1./ngrains])
mypf=upf.polefigure(grains=gr,csym='hexag',cdim=[1,1,c2a])
mypf.pf_new(poles=[[0,0,0,2],[1,0,-1,0]],cmap='jet',ix='TD',iy='RD')
return np.array(gr)
def main(ngrains=100, sigma=5.0, iopt=1, ifig=1):
"""
arguments
=========
ngrains = 100
sigma = 5.
iopt = 1 (1: gauss (recommended); 2: expov; 3: logno; 4: norma)
ifig = 1
"""
import upf
import matplotlib.pyplot as plt
h = mmm()
gr = []
for i in range(ngrains):
dth = random.uniform(-180.0, 180.0)
g = gen_gamma_gr(dth, sigma, iopt=iopt)
for j in range(len(h)):
temp = np.dot(g, h[j].T)
phi1, phi, phi2 = euler(a=temp, echo=False)
gr.append([phi1, phi, phi2, 1.0 / ngrains])
fn = "gam_fib_ngr%s_sigma%s.cmb" % (str(len(gr)).zfill(5), str(sigma).zfill(3))
f = open(fn, "w")
f.writelines("Artificial gamma fibered polycrystal aggregate\n")
f.writelines("var_gam_fiber.py python script\n")
f.writelines("distribution: %s")
if iopt == 1:
f.writelines(" gauss")
if iopt == 2:
f.writelines(" expov")
if iopt == 3:
f.writelines(" logno")
if iopt == 4:
f.writelines(" norma")
f.writelines("\n")
f.writelines("B %i\n" % ngrains)
for i in range(len(gr)):
f.writelines("%7.3f %7.3f %7.3f %13.4e\n" % (gr[i][0], gr[i][1], gr[i][2], 1.0 / len(gr)))
upf.cubgr(gr=gr, ifig=ifig)
plt.figure(ifig).savefig("%s.pdf" % (fn.split(".cmb")[0]))
return np.array(gr)
def main(ngrains=100,sigma=5.,iopt=1,ifig=1):
"""
arguments
=========
ngrains = 100
sigma = 5.
iopt = 1 (1: gauss (recommended); 2: expov; 3: logno; 4: norma)
ifig = 1
"""
import upf
import matplotlib.pyplot as plt
h = mmm()
gr = []
for i in range(ngrains):
dth = random.uniform(-180., 180.)
g = gen_gamma_gr(dth, sigma, iopt=iopt)
for j in range(len(h)):
temp = np.dot(g,h[j].T)
phi1,phi,phi2 = euler(a=temp, echo=False)
gr.append([phi1,phi,phi2,1./ngrains])
fn = 'gam_fib_ngr%s_sigma%s.cmb'%(str(len(gr)).zfill(5),str(sigma).zfill(3))
f = open(fn,'w')
f.writelines('Artificial gamma fibered polycrystal aggregate\n')
f.writelines('var_gam_fiber.py python script\n')
f.writelines('distribution: %s')
if iopt==1: f.writelines(' gauss')
if iopt==2: f.writelines(' expov')
if iopt==3: f.writelines(' logno')
if iopt==4: f.writelines(' norma')
f.writelines('\n')
f.writelines('B %i\n'%ngrains)
for i in range(len(gr)):
f.writelines('%7.3f %7.3f %7.3f %13.4e\n'%(
gr[i][0], gr[i][1], gr[i][2], 1./len(gr)))
upf.cubgr(gr=gr,ifig=ifig)
plt.figure(ifig).savefig('%s.pdf'%(fn.split('.cmb')[0]))
return np.array(gr)
