def test1():
import upf;reload(upf)
import matplotlib.pyplot as plt
import os
ex_text_filename = os.path.join(
path_to_vpsc,'examples',
'ex15_FLD','magnesium','az31','az31dirk.cmb')
mypf =upf.polefigure(
filename=ex_text_filename,
csym='hexag',cdim=[1,1,1.6235])
fig = mypf.pf_new(
poles=[[0,0,0,2],[1,0,-1,1],[1,1,-2,1]],nlev=5,
mode='line',cmap='jet',ires=True,mn=0.5,
dth=15,dph=15)
fig = mypf.pf_new(
poles=[[0,0,0,2],[1,0,-1,1],[1,1,-2,1]],nlev=5,
mode='fill',cmap='jet',ires=True,mn=0.5,
dth=15,dph=15)
fig = mypf.pf_new(
poles=[[0,0,0,2],[1,0,-1,1],[1,1,-2,1]],nlev=5,
mode='fill',cmap='rainbow',ires=True,mn=0.5,
dth=15,dph=15)
def main(component='cube', ngrain=100, w0=10, ifig=1):
"""
arguments
=========
component = 'cube', 'copper', 'rbrass', 'goss'
ngrain = 100
w0 = 10
ifig = 1
"""
import upf
angs = comp2euler(component)
xtal = []
for i in range(len(angs)):
myx = textur(p1=angs[i][0], p=angs[i][1], p2=angs[i][2], w0=w0,
ngrain = ngrain/len(angs), filename='dum',
iplot=False)
myx.gr
for j in range(len(myx.gr)):
xtal.append(myx.gr[j])
mypf = upf.polefigure(grains = xtal, csym='cubic')
mypf.pf(pole=[[1,0,0],[1,1,0],[1,1,1]], ifig=ifig, mode='contourf')
f = open('%s%s.cmb'%(str(len(xtal)),component), 'w')
f.write('dum\ndum\ndum\nB %i\n'%len(xtal))
for i in range(len(xtal)):
f.write('%9.2f %9.2f %9.2f %s\n'%(
xtal[i][0], xtal[i][1], xtal[i][2], str(1./len(xtal))))
return xtal
def main(component='cube', ngrain=100, w0=10, ifig=1):
"""
arguments
=========
component = 'cube', 'copper', 'rbrass', 'goss'
ngrain = 100
w0 = 10
ifig = 1
"""
import upf
angs = comp2euler(component)
xtal = []
for i in range(len(angs)):
myx = textur(p1=angs[i][0],
p=angs[i][1],
p2=angs[i][2],
w0=w0,
ngrain=ngrain / len(angs),
filename='dum',
iplot=False)
myx.gr
for j in range(len(myx.gr)):
xtal.append(myx.gr[j])
mypf = upf.polefigure(grains=xtal, csym='cubic')
mypf.pf(pole=[[1, 0, 0], [1, 1, 0], [1, 1, 1]], ifig=ifig, mode='contourf')
f = open('%s%s.cmb' % (str(len(xtal)), component), 'w')
f.write('dum\ndum\ndum\nB %i\n' % len(xtal))
for i in range(len(xtal)):
f.write('%9.2f %9.2f %9.2f %s\n' %
(xtal[i][0], xtal[i][1], xtal[i][2], str(1. / len(xtal))))
return xtal
def main(odf, ngrain, outputfile, iplot=True, irandom=True):
"""
Arguments
odf: od filename
ngrain : number of grains in the RVE
output : combined file
iplot =True : flag for plotting
"""
import upf
import matplotlib.pyplot as plt
temp = RVE(ngrain=ngrain, odf=odf, cmbfile=outputfile)
if iplot==True:
mypf = upf.polefigure(grains = temp.rve, csym='cubic')
mypf.pf(pole=[[1,0,0],[1,1,0],[1,1,1]], mode='contourf', ifig=2)
plt.show()
pass
if irandom==True:
filename='iso.cmb'
FILE = open(filename, 'w')
FILE.writelines('dummy\ndummy\ndummy\n %s %i\n'%('B', int(ngrain)))
for i in range(len(temp.gr)):
FILE.writelines('%11.7f %11.7f %11.7f %10.4e \n'%
(temp.gr[i][0], temp.gr[i][1],
temp.gr[i][2], temp.gr[i][3]))
pass
FILE.close()
#np.savetxt(filename, temp.gr)
print 'The random isotropic aggregate is written to %s'%filename
pass
pass
def __init__(self,
p1,
p2,
p,
w0,
ngrain,
filename='temp.txt',
dist='g',
iplot=True,
mode='contour',
pole=[[1, 0, 0], [1, 1, 0], [1, 1, 1]],
ifig=1):
f = open(filename, 'w')
f.writelines('Designed texture '\
'using probability distributions \n')
f.writelines('Given Euler angles are as below \n')
f.writelines('ph1, phi2, PHI = ' + str(p1) + str(p2) + str(p))
f.write('\nB ' + str(ngrain))
self.gr = []
for i in range(ngrain):
txt = text(p1=p1, p2=p2, p=p, w0=w0, dist=dist)
angle = txt.angle
f.write('\n %9.2f %9.2f %9.2f %9.3f' %
(angle[0], angle[1], angle[2], 0.1))
self.gr.append([angle[0], angle[1], angle[2], 0.1])
f.close()
if iplot == True:
mypf = upf.polefigure(filename=filename, csym='cubic')
mypf.pf(pole=pole, mode=mode, ifig=ifig)
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 progressive_texture(steps=[0,1]):
import upf
import matplotlib.pyplot as plt
plt.ioff()
for i in range(len(steps)):
step = steps[i]
gr=readerstep(fn='TEX_PH1.OUT', step=step, mode='texture')
mypf=upf.polefigure(csym='cubic',grains=gr)
mypf.pf(pole=[[0,0,1]],ifig=i+1)
plt.figure(i+1).savefig('pf_%i.pdf'%(steps[i]+1))
plt.close(i+1)
print 'i th pf saved'
def progressive_texture(steps=[0, 1]):
import upf
import matplotlib.pyplot as plt
plt.ioff()
for i in range(len(steps)):
step = steps[i]
gr = readerstep(fn='TEX_PH1.OUT', step=step, mode='texture')
mypf = upf.polefigure(csym='cubic', grains=gr)
mypf.pf(pole=[[0, 0, 1]], ifig=i + 1)
plt.figure(i + 1).savefig('pf_%i.pdf' % (steps[i] + 1))
plt.close(i + 1)
print 'i th pf saved'
def plot(self,csym='cubic',**kwargs):
"""
Plot pole figure
Arguments
---------
csym : crystal symmetry
**kwargs: kw arguments to be passed to pf_new
"""
import upf,time
mypf = upf.polefigure(grains = self.rve, csym=csym)
fig=mypf.pf_new(**kwargs)
plt.show()
return fig
def main(hkl,uvw,w0,ngr=1,ifig=10):
import upf
import matplotlib.pyplot as plt
phi1,phi,phi2 = miller2euler(hkl,uvw)
mat0 = eul(phi1,phi,phi2,echo=False) # ca<-sa
# print 'mat0:', mat0
mmm = sample_mmm()
mats = [mat0]
# print mats
for i in range(len(mmm)):
mats.append(np.dot(mat0,mmm[i]))
gauss = random.gauss
r = random.random
# print 'ind_mat:', ind_mat
# print 'ngr:', ngr
grs = []
for i in range(ngr):
ind_mat = int(r() * len(mats))
if w0==0: w=0
else: w = gauss(mu=0., sigma=w0)
# print 'w:',w
# print 'mats:', mats[ind_mat]
C = rot_vectang(th=w, r=mats[ind_mat])
# print C
phi1, phi, phi2 = eul(a=C, echo=False)
grs.append([phi1,phi,phi2,1])
#print phi1,phi,phi2
#print grs
mypf = upf.polefigure(grains=grs,csym='cubic')
mypf.pf(mode='contourf',cmode='gray_r',ifig=ifig)
#mypf.pf(mode='dot',cmode='gray_r',ifig=ifig)
plt.tight_layout()
hkl = '%i%i%i'%(hkl[0],hkl[1],hkl[2])
uvw = '%i%i%i'%(uvw[0],uvw[1],uvw[2])
fn = 'hkl_%s_uvw_%s_th_%i_ngr_%i.txt'%(hkl,uvw,w0,ngr)
f = open(fn,'w')
f.writelines(' dum\n dum\n dum\n B %i \n'%ngr)
for i in range(ngr):
f.writelines('%8.3f %8.3f %8.3f %12.7f\n'%(
grs[i][0],grs[i][1],grs[i][2],1./ngr))
f.close()
print '%s has created'%fn
def main(hkl, uvw, w0, ngr=1, ifig=10):
import upf
import matplotlib.pyplot as plt
phi1, phi, phi2 = miller2euler(hkl, uvw)
mat0 = eul(phi1, phi, phi2, echo=False) # ca<-sa
# print 'mat0:', mat0
mmm = sample_mmm()
mats = [mat0]
# print mats
for i in range(len(mmm)):
mats.append(np.dot(mat0, mmm[i]))
gauss = random.gauss
r = random.random
# print 'ind_mat:', ind_mat
# print 'ngr:', ngr
grs = []
for i in range(ngr):
ind_mat = int(r() * len(mats))
if w0 == 0: w = 0
else: w = gauss(mu=0., sigma=w0)
# print 'w:',w
# print 'mats:', mats[ind_mat]
C = rot_vectang(th=w, r=mats[ind_mat])
# print C
phi1, phi, phi2 = eul(a=C, echo=False)
grs.append([phi1, phi, phi2, 1])
#print phi1,phi,phi2
#print grs
mypf = upf.polefigure(grains=grs, csym='cubic')
mypf.pf(mode='contourf', cmode='gray_r', ifig=ifig)
#mypf.pf(mode='dot',cmode='gray_r',ifig=ifig)
plt.tight_layout()
hkl = '%i%i%i' % (hkl[0], hkl[1], hkl[2])
uvw = '%i%i%i' % (uvw[0], uvw[1], uvw[2])
fn = 'hkl_%s_uvw_%s_th_%i_ngr_%i.txt' % (hkl, uvw, w0, ngr)
f = open(fn, 'w')
f.writelines(' dum\n dum\n dum\n B %i \n' % ngr)
for i in range(ngr):
f.writelines('%8.3f %8.3f %8.3f %12.7f\n' %
(grs[i][0], grs[i][1], grs[i][2], 1. / ngr))
f.close()
print '%s has created' % fn
def main(fn='TEX_PH1.OUT', step=100, igr=1,ifig=3):
"""
Given the texture file, plots a continuous trace of
texture evolution in the pole figure representation.
Arguments
=========
fn = 'TEX_PH1.OUT'
step = 100
igr = 1
ifig = 3
"""
import upf
grains, eps = reader(fn, step, igr) # particular grain
mypf = upf.polefigure(csym='cubic', grains=grains)
mypf.pf(pole=[[0,0,1]], mode='trace',ifig=ifig)
def main(fn='TEX_PH1.OUT', step=100, igr=1, ifig=3):
"""
Given the texture file, plots a continuous trace of
texture evolution in the pole figure representation.
Arguments
=========
fn = 'TEX_PH1.OUT'
step = 100
igr = 1
ifig = 3
"""
import upf
grains, eps = reader(fn, step, igr) # particular grain
mypf = upf.polefigure(csym='cubic', grains=grains)
mypf.pf(pole=[[0, 0, 1]], mode='trace', ifig=ifig)
def sampling(odf=None, p1=360., p2=90., *args):
"""
Sampling several representative grain sets.
---------
Arguments
odf = None : discrete OD file name
*args: number of grains. (500,~)
-------
Example
In order to obtain 500, 1000, 2000, 4000, RVEs,
follow the below:
>>> import randomEuler
>>> randomEuler.sampling('304_surface.TXT', 500,1000,2000,4000,...)
. . .
"""
import upf
files = []
print 'p1=', p1, 'p2=', p2
for i in range(len(args)):
re = randomEuler(ngrain=args[i], p1=p1, p2=p2)
re.odf_reading(odf)
filename = "%s_%s%s" % (odf.split('.TXT')[0], str(
args[i]).zfill(5), '.cmb')
re.combine(
filename
) #"%s_%s%s"%(odf.split('.TXT')[0],str(args[i]).zfill(5),'.cmb'))
files.append(filename)
pass
## pole figure plotting
flag = raw_input('Polefigure? (bcc or fcc)')
if flag == 'bcc' or 'fcc':
for i in range(len(files)):
pf = upf.polefigure(filename=files[i],
csym='cubic',
cdim=[1., 1., 1.],
cang=[90., 90., 90.])
pf.pf(pole=[[1, 1, 1]], mode='contourf', ifig=1 + i, cmode=None)
pass
pass
else:
pass
pass
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(odf, ngrain, outputfile, iplot=True, irandom=False):
"""
Arguments
=========
odf: od filename
ngrain : number of grains in the RVE
outputfile : combined file
iplot =True : flag for plotting
irandom=True
"""
import upf, time
import matplotlib.pyplot as plt
temp = RVE(ngrain=ngrain, odf=odf, cmbfile=outputfile)
if iplot == True:
mypf = upf.polefigure(grains=temp.rve, csym='cubic')
mypf.pf(pole=[[1, 0, 0], [1, 1, 0], [1, 1, 1]],
mode='contourf',
ifig=2)
plt.show()
pass
if irandom == True:
filename = 'iso.cmb'
FILE = open(filename, 'w')
FILE.writelines(
'%s\n%s\n%s\n %s %i\n' %
(time.asctime(), 'Current texture file was made by cmb.py',
'contact: [email protected]', 'B', int(ngrain)))
for i in range(len(temp.gr)):
FILE.writelines(
'%11.7f %11.7f %11.7f %10.4e \n' %
(temp.gr[i][0], temp.gr[i][1], temp.gr[i][2], temp.gr[i][3]))
pass
FILE.close()
#np.savetxt(filename, temp.gr)
print 'The random isotropic aggregate is written to %s' % filename
pass
pass
def sampling(odf=None, p1=360., p2=90., *args):
"""
Sampling several representative grain sets.
---------
Arguments
odf = None : discrete OD file name
*args: number of grains. (500,~)
-------
Example
In order to obtain 500, 1000, 2000, 4000, RVEs,
follow the below:
>>> import randomEuler
>>> randomEuler.sampling('304_surface.TXT', 500,1000,2000,4000,...)
. . .
"""
import upf
files = []
print 'p1=', p1, 'p2=', p2
for i in range(len(args)):
re = randomEuler(ngrain=args[i], p1=p1, p2=p2)
re.odf_reading(odf)
filename = "%s_%s%s"%(odf.split('.TXT')[0],str(args[i]).zfill(5),'.cmb')
re.combine(filename) #"%s_%s%s"%(odf.split('.TXT')[0],str(args[i]).zfill(5),'.cmb'))
files.append(filename)
pass
## pole figure plotting
flag = raw_input('Polefigure? (bcc or fcc)')
if flag=='bcc' or 'fcc':
for i in range(len(files)):
pf = upf.polefigure(filename=files[i], csym='cubic',
cdim=[1.,1.,1.], cang=[90.,90.,90.])
pf.pf(pole=[[1,1,1]], mode='contourf', ifig=1+i, cmode=None)
pass
pass
else: pass
pass
def test1():
import upf
reload(upf)
import matplotlib.pyplot as plt
import os
ex_text_filename = os.path.join(path_to_vpsc, 'examples', 'ex15_FLD',
'magnesium', 'az31', 'az31dirk.cmb')
mypf = upf.polefigure(filename=ex_text_filename,
csym='hexag',
cdim=[1, 1, 1.6235])
fig = mypf.pf_new(poles=[[0, 0, 0, 2], [1, 0, -1, 1], [1, 1, -2, 1]],
nlev=5,
mode='line',
cmap='jet',
ires=True,
mn=0.5,
dth=15,
dph=15)
fig = mypf.pf_new(poles=[[0, 0, 0, 2], [1, 0, -1, 1], [1, 1, -2, 1]],
nlev=5,
mode='fill',
cmap='jet',
ires=True,
mn=0.5,
dth=15,
dph=15)
fig = mypf.pf_new(poles=[[0, 0, 0, 2], [1, 0, -1, 1], [1, 1, -2, 1]],
nlev=5,
mode='fill',
cmap='rainbow',
ires=True,
mn=0.5,
dth=15,
dph=15)
def __init__(self, p1, p2, p, w0, ngrain,
filename='temp.txt', dist='g',
iplot=True, mode='contour',
pole=[[1,0,0],[1,1,0],[1,1,1]], ifig=1):
f = open(filename, 'w')
f.writelines('Designed texture '\
'using probability distributions \n')
f.writelines('Given Euler angles are as below \n')
f.writelines('ph1, phi2, PHI = ' + str(p1) + str(p2)+ str(p) )
f.write('\nB '+ str(ngrain))
self.gr = []
for i in range(ngrain):
txt = text(p1=p1, p2=p2, p=p, w0=w0, dist=dist)
angle = txt.angle
f.write('\n %9.2f %9.2f %9.2f %9.3f'%(
angle[0],angle[1],angle[2], 0.1))
self.gr.append([angle[0],angle[1],angle[2], 0.1])
f.close()
if iplot==True:
mypf = upf.polefigure(filename=filename, csym='cubic')
mypf.pf(pole=pole, mode=mode, ifig=ifig)
def sampling_simplex(odf=None, iang = 10.,
ngrain=100,maxiter=40,xtol=10,
header = None, p1=360., p2=90.,
iplot=False,ifig=30):
"""
RVE sampling over an OD file using an optimization scheme
argument
odf = grided crystallograhpic orientation distribution file
iang = initial anglular increment
ngrain = 100, # the targetted number of grains
maxiter = 40, maximum number of iteration for which the optimization loop
iterates
xtol = 10, the tolerance
header = None
p1 = 360, (maximum phi1 angle)
p2 = 90 , (maximum phi2 angle)
"""
import matplotlib.pyplot as plt
#import upf
from scipy.optimize import fmin #optimization scheme
rst = fmin(__refunc__, #function to be optimized
[iang,0], # the parameters
args=(ngrain,p1,p2), # *args
callback = __callback__, # callback function
xtol = xtol, ##changeable...
maxiter=maxiter
)
# raw_input('press enter to close >>>')
# plt.close()
print 'angle =', rst
grains = []
while True:
tmp = randomEuler(d_ang=rst[0], p1=p1, p2=p2, echo=False)
grains.append(tmp.ngr)
if tmp.ngr==ngrain:
break
pass
print "-----------------------"
print "Interation: %i"%len(grains)
print "mean number: %6.2f"%np.array(grains).mean()
print "-----------------------"
tmp.odf_reading(odf)
if header==None: filename= '%s.cmb'%str(ngrain).zfill(5)
else: filename= '%s_%s.cmb'%(header, str(ngrain).zfill(5))
tmp.combine(filename)
print "written to '%s'"%filename
if iplot==True:
import upf
pf = upf.polefigure(filename=filename, csym='cubic',
cdim=[1.,1.,1.], cang=[90.,90.,90.])
pf.pf(pole=[[1,0,0],[1,1,0],[1,1,1]], mode='contourf', ifig=ifig)
pass
return rst
def c2e(component='cube', ngrain=100, w0=10, ifig=1, mode='contour'):
"""
Provided (hkl)// ND and [uvw]//RD,
arguments
=========
component = 'cube'
ngrain = 100
w0 = 10
ifig = 1
mode = 'contour'
"""
import numpy as np
from euler import euler
import upf
comp = component.lower()
print comp
if comp == 'cube':
hkl = [1, 0, 0]
uvw = [0, 1, 0]
elif comp == 'copper':
hkl = [1, 1, 2]
uvw = [-1, -1, 1]
elif comp == 'goss':
hkl = [1, 1, 0]
uvw = [0, 0, 1]
elif comp == 'rbrass':
hkl = [-1, 1, 0]
uvw = [1, 1, 1]
print 'hkl', hkl
print 'uvw', uvw, '\n'
# mat0: trasformation matrix that converts
# sample axes to crystal ones [ca<-sa]
mat0 = miller2mat(hkl=map(round, hkl), uvw=map(round, uvw))
print 'mat0'
for i in range(len(mat0)):
for j in range(len(mat0[i])):
print '%5.1f ' % mat0[i][j],
print ''
# Mirror reflection by RD and TD in the sample coordinate system.
# mat0[ca<-sa]
RD, TD = orthogonal()
mat1 = np.dot(mat0, RD)
mat2 = np.dot(mat0, TD)
mat3 = np.dot(np.dot(mat0, RD), TD)
print 'mat1'
for i in range(len(mat1)):
for j in range(len(mat1[i])):
print '%5.1f ' % mat1[i][j],
print ''
print 'mat2'
for i in range(len(mat2)):
for j in range(len(mat2[i])):
print '%5.1f ' % mat2[i][j],
print ''
print 'mat3'
for i in range(len(mat3)):
for j in range(len(mat3[i])):
print '%5.1f ' % mat3[i][j],
print ''
ang0 = euler(a=mat0, echo=False)
ang1 = euler(a=mat1, echo=False)
ang2 = euler(a=mat2, echo=False)
ang3 = euler(a=mat3, echo=False)
angs = [ang0, ang1, ang2, ang3]
for i in range(len(angs)):
for j in iter(angs[i]):
print '%5.1f ' % j,
print ''
xtal = []
for i in range(4):
phi1, p, phi2 = angs[i]
myx = textur(p1=phi1,
p=p,
p2=phi2,
w0=w0,
ngrain=ngrain / 4,
filename='dum',
iplot=False)
for j in range(len(myx.gr)):
xtal.append(myx.gr[j])
mypf = upf.polefigure(grains=xtal, csym='cubic')
mypf.pf(pole=[[1, 0, 0], [1, 1, 0], [1, 1, 1]], mode=mode, ifig=ifig)
## Write
gr2f(gr=xtal,
header='module: %s, w0: %i' % ('ce2', w0),
filename='%i%s%i_%s.cmb' % (len(xtal), component, w0, 'ce2'))
return xtal
def main(ngrains=100,sigma=5.,iopt=1,ifig=1,fiber='gamma',
iexit=False,ipfplot=False):
"""
Arguments
=========
ngrains = 100
sigma = 5.
iopt = 1 (1: gauss (recommended); 2: expov; 3: logno; 4: norma)
ifig = 1
fiber = 'gamma', 'alpha', 'eta', 'epsilon', 'sigma', 'random'
ipfplot = False
Returns
-------
It returns the poly-crystal aggregate in the form of numpy's ndarray.
"""
import upf
import matplotlib.pyplot as plt
import cmb
# h = mmm() ## m-m-m sample symmetry is applied.
h = [np.identity(3)]
gr = []
for i in xrange(ngrains):
dth = random.uniform(-180., 180.)
if fiber in ['gamma','alpha', 'eta', 'epsilon', 'sigma']:
g = gen_gr_fiber(dth,sigma,iopt,fiber)
elif fiber=='random':
g = cmb.randomGrain(360,360,360)
for j in xrange(len(h)):
temp = np.dot(g,h[j].T)
phi1,phi,phi2 = euler(a=temp, echo=False)
gr.append([phi1,phi,phi2,1./ngrains])
if iexit: return np.array(gr)
fn = '%s_fib_ngr%s_sigma%s.cmb'%(fiber,str(len(gr)).zfill(5),str(sigma).zfill(3))
f = open(fn,'w')
f.writelines('Artificial %s fibered polycrystal aggregate\n'%fiber)
f.writelines('bcc_rolling_fiber.py python script\n')
f.writelines('distribution: ')
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 xrange(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)))
if ipfplot:
mypf1 = upf.polefigure(grains=gr,csym='cubic')
mypf1.pf_new(poles=[[1,0,0],[1,1,0],[1,1,1]],ix='RD',iy='TD')
fig=plt.gcf()
fig.tight_layout()
print 'aggregate saved to %s'%fn
fig.savefig(
'%s_contf.pdf'%(fn.split('.cmb')[0]),
bbox_inches='tight')
fig.savefig(
'%s_contf.png'%(fn.split('.cmb')[0]),
bbox_inches='tight')
fig.clf()
plt.close(fig)
return np.array(gr),fn
def c2e(component='cube', ngrain=100, w0=10, ifig=1, mode='contour'):
"""
Provided (hkl)// ND and [uvw]//RD,
arguments
=========
component = 'cube'
ngrain = 100
w0 = 10
ifig = 1
mode = 'contour'
"""
import numpy as np
from euler import euler
import upf
comp = component.lower()
print comp
if comp=='cube':
hkl=[1,0,0]
uvw=[0,1,0]
elif comp=='copper':
hkl=[1,1,2]
uvw=[-1,-1,1]
elif comp=='goss':
hkl=[1,1,0]
uvw=[0,0,1]
elif comp=='rbrass':
hkl=[-1,1,0]
uvw=[1,1,1]
print 'hkl',hkl
print 'uvw',uvw,'\n'
# mat0: trasformation matrix that converts
# sample axes to crystal ones [ca<-sa]
mat0 = miller2mat(hkl=map(round, hkl), uvw=map(round, uvw))
print 'mat0'
for i in range(len(mat0)):
for j in range(len(mat0[i])):
print '%5.1f '%mat0[i][j],
print ''
# Mirror reflection by RD and TD in the sample coordinate system.
# mat0[ca<-sa]
RD, TD = orthogonal()
mat1 = np.dot(mat0, RD)
mat2 = np.dot(mat0, TD)
mat3 = np.dot(np.dot(mat0, RD), TD)
print 'mat1'
for i in range(len(mat1)):
for j in range(len(mat1[i])):
print '%5.1f '%mat1[i][j],
print ''
print 'mat2'
for i in range(len(mat2)):
for j in range(len(mat2[i])):
print '%5.1f '%mat2[i][j],
print ''
print 'mat3'
for i in range(len(mat3)):
for j in range(len(mat3[i])):
print '%5.1f '%mat3[i][j],
print ''
ang0 = euler(a=mat0, echo=False)
ang1 = euler(a=mat1, echo=False)
ang2 = euler(a=mat2, echo=False)
ang3 = euler(a=mat3, echo=False)
angs = [ang0, ang1, ang2, ang3]
for i in range(len(angs)):
for j in iter(angs[i]):
print '%5.1f '%j,
print ''
xtal = []
for i in range(4):
phi1, p, phi2 = angs[i]
myx = textur(p1=phi1,p=p, p2=phi2, w0=w0, ngrain = ngrain/4,
filename='dum', iplot=False)
for j in range(len(myx.gr)):
xtal.append(myx.gr[j])
mypf = upf.polefigure(grains=xtal,csym='cubic')
mypf.pf(pole=[[1,0,0],[1,1,0],[1,1,1]], mode=mode, ifig=ifig)
## Write
gr2f(gr=xtal, header='module: %s, w0: %i'%('ce2', w0),
filename='%i%s%i_%s.cmb'%(len(xtal), component, w0, 'ce2'))
return xtal
def ex(fact=100, res=1.0, filename=None, ngrain=None):
kde = stats.gaussian_kde
mypf = upf.polefigure(ngrain=ngrain, filename=filename, csym='cubic')
mypf.pf(pole=[[1, 0, 0]], mode='contourf')
# PF[# of pole, mgrid(rot=azmthl), ngrid(tilt= declination)]
PF = mypf.pfnodes[0]
mn, nn = PF.shape
dbeta = 360. / (mn - 1) # Rotating
dalpha = 90. / (nn - 1) # tilting
beta = np.linspace(0., 360., mn) # 0.~360.
alpha = np.linspace(0., 90., nn) # 0.~90.
#dum1 = np.arange(0.,360. + res/10., res)
#dum2 = np.arange(0.,90. + res/10., res)
x = []
y = []
#len(dum2)))
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
maxint = max(PF.flatten())
for i in range(len(PF)):
for j in range(len(PF[i])):
nsample = int(PF[i][j] / maxint * fact)
for k in range(nsample):
x.append(beta[i])
y.append(alpha[j])
# For a new resolution
beta = np.arange(0., 360. + res / 2., res)
alpha = np.arange(0., 90. + res / 2., res)
A, B = np.meshgrid(alpha, beta)
positions = np.vstack([B.ravel(), A.ravel()])
values = np.vstack([x, y]) # beta, alpha
kernel = stats.gaussian_kde(values)
Z = np.reshape(kernel.evaluate(positions).T, A.shape)
plt.figure(3)
ax = plt.gca()
ax.set_frame_on(False)
ax.set_aspect('equal')
ax.set_axis_off()
rx, ry = upf.circle()
ax.plot(rx, ry, 'k')
pi = np.pi
nm = (360.0 - 0.) / res
nn = (180. - 90.) / res
theta = np.linspace(pi, pi / 2., nn + 1)
phi = np.linspace(0., 2. * pi, nm + 1)
r = np.sin(theta) / (1 - np.cos(theta))
R, PHI = np.meshgrid(r, phi)
PHI = PHI + pi / 2.
x = R * np.cos(PHI)
y = R * np.sin(PHI)
ax.contourf(x, y, Z)
def ex(fact=100, res=1.0,filename=None,ngrain=None):
kde = stats.gaussian_kde
mypf = upf.polefigure(ngrain=ngrain, filename=filename, csym='cubic')
mypf.pf(pole=[[1,0,0]],mode='contourf')
# PF[# of pole, mgrid(rot=azmthl), ngrid(tilt= declination)]
PF = mypf.pfnodes[0]
mn, nn = PF.shape
dbeta = 360./(mn -1) # Rotating
dalpha = 90./(nn-1) # tilting
beta = np.linspace(0.,360., mn) # 0.~360.
alpha = np.linspace(0., 90., nn) # 0.~90.
#dum1 = np.arange(0.,360. + res/10., res)
#dum2 = np.arange(0.,90. + res/10., res)
x = []
y = []
#len(dum2)))
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
# | | | | |
# |---------------|
maxint = max(PF.flatten())
for i in range(len(PF)):
for j in range(len(PF[i])):
nsample = int(PF[i][j]/maxint*fact)
for k in range(nsample):
x.append(beta[i])
y.append(alpha[j])
# For a new resolution
beta = np.arange(0.,360.+res/2.,res)
alpha = np.arange(0.,90.+res/2.,res)
A, B = np.meshgrid(alpha, beta)
positions = np.vstack([B.ravel(), A.ravel()])
values = np.vstack([x,y]) # beta, alpha
kernel = stats.gaussian_kde(values)
Z = np.reshape(kernel.evaluate(positions).T, A.shape)
plt.figure(3)
ax = plt.gca()
ax.set_frame_on(False)
ax.set_aspect('equal')
ax.set_axis_off()
rx, ry = upf.circle()
ax.plot(rx,ry,'k')
pi = np.pi
nm = (360.0-0.)/res; nn = (180.-90.)/res
theta = np.linspace(pi, pi/2., nn+1)
phi = np.linspace(0.,2.*pi, nm+1)
r = np.sin(theta)/(1-np.cos(theta))
R, PHI = np.meshgrid(r,phi)
PHI = PHI + pi/2.
x = R*np.cos(PHI); y= R*np.sin(PHI)
ax.contourf(x, y, Z)
def sampling_simplex(odf=None,
iang=10.,
ngrain=100,
maxiter=40,
xtol=10,
header=None,
p1=360.,
p2=90.,
iplot=False,
ifig=30):
"""
RVE sampling over an OD file using an optimization scheme
argument
odf = grided crystallograhpic orientation distribution file
iang = initial anglular increment
ngrain = 100, # the targetted number of grains
maxiter = 40, maximum number of iteration for which the optimization loop
iterates
xtol = 10, the tolerance
header = None
p1 = 360, (maximum phi1 angle)
p2 = 90 , (maximum phi2 angle)
"""
import matplotlib.pyplot as plt
#import upf
from scipy.optimize import fmin #optimization scheme
rst = fmin(
__refunc__, #function to be optimized
[iang, 0], # the parameters
args=(ngrain, p1, p2), # *args
callback=__callback__, # callback function
xtol=xtol, ##changeable...
maxiter=maxiter)
# raw_input('press enter to close >>>')
# plt.close()
print 'angle =', rst
grains = []
while True:
tmp = randomEuler(d_ang=rst[0], p1=p1, p2=p2, echo=False)
grains.append(tmp.ngr)
if tmp.ngr == ngrain:
break
pass
print "-----------------------"
print "Interation: %i" % len(grains)
print "mean number: %6.2f" % np.array(grains).mean()
print "-----------------------"
tmp.odf_reading(odf)
if header == None: filename = '%s.cmb' % str(ngrain).zfill(5)
else: filename = '%s_%s.cmb' % (header, str(ngrain).zfill(5))
tmp.combine(filename)
print "written to '%s'" % filename
if iplot == True:
import upf
pf = upf.polefigure(filename=filename,
csym='cubic',
cdim=[1., 1., 1.],
cang=[90., 90., 90.])
pf.pf(pole=[[1, 0, 0], [1, 1, 0], [1, 1, 1]],
mode='contourf',
ifig=ifig)
pass
return rst
def app(ngr=100,c2a=1.6235):
"""
Application for FLD-Mg paper
Create a set of polycrystals
## ZE10
1) Small doughnut
2) Big dougnut
## AZ31
1) double let (tilt of 30 degree)
1) double let (tilt of 50 degree)
Arguments
---------
ngr=100
c2a=1.6235 c2a ratio for HCP structure
"""
import matplotlib.pyplot as plt
## small donuts
# plt.gcf().clf()
grs = main(mu=0,ngrains=ngr,tilt_1=30.,sigma=15)
plt.gcf().savefig('small_doughnut.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='sm_doughnut',ngr=ngr)
write_gr(f,grs)
## Big donuts
grs = main(mu=0,ngrains=ngr,tilt_1=50.,sigma=15)
plt.gcf().savefig('big_doughnut.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='big_doughnut',ngr=ngr)
write_gr(f,grs)
## twin tilts (30).
gr1=main(mu=0,ngrains=ngr/2,tilts_about_ax1=30.,sigma=45)
plt.gcf().clf()
gr2=main(mu=0,ngrains=ngr/2,tilts_about_ax1=-30.,sigma=45)
plt.gcf().clf()
grs =[]
for i in xrange(len(gr1)):
grs.append(gr1[i])
grs.append(gr2[i])
grs=np.array(grs)
mypf=upf.polefigure(grains=grs,csym='hexag',cdim=[1,1,c2a])
mypf.pf_new(poles=[[0,0,0,1],[1,0,-1,0]],cmap='jet',ix='TD',iy='RD')
plt.gcf().savefig('t30.pdf',bbox_inches='tight')
f = gen_file(lab='dbl_lets_30',ngr=ngr)
write_gr(f,grs)
## twin tilts (50).
gr1=main(mu=0,ngrains=ngr/2,tilts_about_ax1=50.,sigma=45)
plt.gcf().clf()
gr2=main(mu=0,ngrains=ngr/2,tilts_about_ax1=-50.,sigma=45)
plt.gcf().clf()
gr =[]
for i in xrange(len(gr1)):
gr.append(gr1[i])
gr.append(gr2[i])
gr=np.array(gr)
mypf=upf.polefigure(grains=gr,csym='hexag',cdim=[1,1,c2a])
mypf.pf_new(poles=[[0,0,0,1],[1,0,-1,0]],cmap='jet',ix='TD',iy='RD')
plt.gcf().savefig('t50.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='dbl_lets_50',ngr=ngr)
write_gr(f,gr)
def app(ngr=100,c2a=1.6235):
"""
Application for FLD-Mg paper
Create a set of polycrystals
## ZE10
1) Small doughnut
2) Big dougnut
## AZ31
1) double let (tilt of 30 degree)
1) double let (tilt of 50 degree)
Arguments
---------
ngr=100
c2a=1.6235 c2a ratio for HCP structure
"""
import matplotlib.pyplot as plt
## small donuts
# plt.gcf().clf()
grs = main(mu=0,ngrains=ngr,tilt_1=30.,sigma=15)
plt.gcf().savefig('small_doughnut.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='sm_doughnut',ngr=ngr)
write_gr(f,grs)
## Big donuts
grs = main(mu=0,ngrains=ngr,tilt_1=50.,sigma=15)
plt.gcf().savefig('big_doughnut.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='big_doughnut',ngr=ngr)
write_gr(f,grs)
## twin tilts (30).
gr1=main(mu=0,ngrains=ngr/2,tilts_about_ax1=30.,sigma=45)
plt.gcf().clf()
gr2=main(mu=0,ngrains=ngr/2,tilts_about_ax1=-30.,sigma=45)
plt.gcf().clf()
grs =[]
for i in range(len(gr1)):
grs.append(gr1[i])
grs.append(gr2[i])
grs=np.array(grs)
mypf=upf.polefigure(grains=grs,csym='hexag',cdim=[1,1,c2a])
mypf.pf_new(poles=[[0,0,0,1],[1,0,-1,0]],cmap='jet',ix='TD',iy='RD')
plt.gcf().savefig('t30.pdf',bbox_inches='tight')
f = gen_file(lab='dbl_lets_30',ngr=ngr)
write_gr(f,grs)
## twin tilts (50).
gr1=main(mu=0,ngrains=ngr/2,tilts_about_ax1=50.,sigma=45)
plt.gcf().clf()
gr2=main(mu=0,ngrains=ngr/2,tilts_about_ax1=-50.,sigma=45)
plt.gcf().clf()
gr =[]
for i in range(len(gr1)):
gr.append(gr1[i])
gr.append(gr2[i])
gr=np.array(gr)
mypf=upf.polefigure(grains=gr,csym='hexag',cdim=[1,1,c2a])
mypf.pf_new(poles=[[0,0,0,1],[1,0,-1,0]],cmap='jet',ix='TD',iy='RD')
plt.gcf().savefig('t50.pdf',bbox_inches='tight')
plt.gcf().clf()
f = gen_file(lab='dbl_lets_50',ngr=ngr)
write_gr(f,gr)
def harm_pf(grains=None, filename=None, l=2, dm=7.5, dn=7.5,
pole=[[1,0,0]], csym='cubic'):
"""
Something is wrong and I couldn't figure out.
Further development is defferred.
Arguments
=========
grains = None
filename = None
l = 10
dm = 7.5
dn = 7.5
pole = [[1, 0, 0]]
csym = 'cubic'
"""
import numpy as np
import cmb
from upf import polefigure, circle
pi = np.pi
if grains==None and filename==None:
gr = cmb.random(filename='dum.tex',ngrain=1000,
phi1=360., phi=90., phi2=180.)
mypf = polefigure(grains=grains, csym=csym)
else: mypf = polefigure(grains=grains, filename=filename, csym=csym)
mypf.pf(pole=pole, dm=dm, dn=dn)
hpf = []
import matplotlib.pyplot as plt
fact = 2. #size factor
figsize = (len(pole)*2.*fact, 1.*2.*fact)
fig = plt.figure(33, figsize=figsize)
ax = plt.gca()
for ip in range(len(pole)):
extended_PF = extPF(mypf.pfnodes[ip])
print 'extended_PF.shape', extended_PF.shape
#dum = harm_PF(PF=mypf.pfnodes[ip], l=l)
dum = harm_PF(PF=extended_PF, l=l)
reduced_PF = redPF(dum)
hpf.append(reduced_PF)
# print 'max:', np.real(max(hpf[ip].flatten()))
# print 'min:', np.real(min(hpf[ip].flatten()))
theta = np.linspace(pi, pi/2., (90.)/dn + 1)
phi = np.linspace(0.,2.*pi, (360.)/dm+1)
r = np.sin(theta)/(1-np.cos(theta))
R, PHI = np.meshgrid(r,phi)
PHI = PHI + pi/2.
x = R*np.cos(PHI); y = R*np.sin(PHI)
# return x, y, mypf.pfnodes[0]
cnt = ax.contourf(x,y, hpf[0])
ax.set_frame_on(False)
ax.set_axis_off()
ax.set_aspect('equal')
rx, ry = circle()
ax.plot(rx, ry, 'k')
ax.set_xlim(-1.2,1.5)
ax.set_ylim(-1.2,1.5)
tcolors = cnt.tcolors
clev = cnt._levels
for i in range(len(tcolors)):
cc = tcolors[i][0][0:3]
#if levels==None:
if ip==len(pole)-1:
## level line
ax.plot([1.28, 1.35],
[1. - i * 0.2, 1. - i * 0.2],
color=cc)
## level text
ax.text(x=1.40, y= 1. - i*0.2 - 0.05,
s='%3.2f'%(clev[i]),
fontsize=4*fact)
return hpf, mypf.pfnodes
def harm_pf(grains=None,
filename=None,
l=2,
dm=7.5,
dn=7.5,
pole=[[1, 0, 0]],
csym='cubic'):
"""
Something is wrong and I couldn't figure out.
Further development is defferred.
Arguments
=========
grains = None
filename = None
l = 10
dm = 7.5
dn = 7.5
pole = [[1, 0, 0]]
csym = 'cubic'
"""
import numpy as np
import cmb
from upf import polefigure, circle
pi = np.pi
if grains == None and filename == None:
gr = cmb.random(filename='dum.tex',
ngrain=1000,
phi1=360.,
phi=90.,
phi2=180.)
mypf = polefigure(grains=grains, csym=csym)
else:
mypf = polefigure(grains=grains, filename=filename, csym=csym)
mypf.pf(pole=pole, dm=dm, dn=dn)
hpf = []
import matplotlib.pyplot as plt
fact = 2. #size factor
figsize = (len(pole) * 2. * fact, 1. * 2. * fact)
fig = plt.figure(33, figsize=figsize)
ax = plt.gca()
for ip in range(len(pole)):
extended_PF = extPF(mypf.pfnodes[ip])
print 'extended_PF.shape', extended_PF.shape
#dum = harm_PF(PF=mypf.pfnodes[ip], l=l)
dum = harm_PF(PF=extended_PF, l=l)
reduced_PF = redPF(dum)
hpf.append(reduced_PF)
# print 'max:', np.real(max(hpf[ip].flatten()))
# print 'min:', np.real(min(hpf[ip].flatten()))
theta = np.linspace(pi, pi / 2., (90.) / dn + 1)
phi = np.linspace(0., 2. * pi, (360.) / dm + 1)
r = np.sin(theta) / (1 - np.cos(theta))
R, PHI = np.meshgrid(r, phi)
PHI = PHI + pi / 2.
x = R * np.cos(PHI)
y = R * np.sin(PHI)
# return x, y, mypf.pfnodes[0]
cnt = ax.contourf(x, y, hpf[0])
ax.set_frame_on(False)
ax.set_axis_off()
ax.set_aspect('equal')
rx, ry = circle()
ax.plot(rx, ry, 'k')
ax.set_xlim(-1.2, 1.5)
ax.set_ylim(-1.2, 1.5)
tcolors = cnt.tcolors
clev = cnt._levels
for i in range(len(tcolors)):
cc = tcolors[i][0][0:3]
#if levels==None:
if ip == len(pole) - 1:
## level line
ax.plot([1.28, 1.35], [1. - i * 0.2, 1. - i * 0.2], color=cc)
## level text
ax.text(x=1.40,
y=1. - i * 0.2 - 0.05,
s='%3.2f' % (clev[i]),
fontsize=4 * fact)
return hpf, mypf.pfnodes
