def prep_m():
try:
d = pickle.load(open('elems.pkl', 'rb'))
SpGrp.allelems = d[0]
SpGrp.allhasI = d[1]
except: ## ... parse and save to file
ls = open('elems.dat').readlines()
ls = filter(lambda l: l, map(lambda l: l.strip(), ls))
for sls in groupby(ls, 4):
num, snum, inv, s, cnt = map(lambda s: int(s), sls[0].split())
mats = [Mat(0, 0, 0, 0, 0, 0, 0, 0, 0)
for i in xrange(cnt)] ## create empty matrices
vecs = [Vec(0, 0, 0) for i in xrange(cnt)] ## ..and empty vectors
for i in xrange(1, 4):
prts = map(lambda s: float(s), sls[i].split())
for j, els in enumerate(groupby(
prts, 4)): ## group by (m11, m12, m13, v1) groups
mats[j][i - 1] = els[:-1] ## set one row of matrix
vecs[j][i - 1] = els[-1] ## set one coord of vec
els = map(lambda e: SGElem(e[0], e[1]), zip(mats, vecs))
SpGrp.allelems[num - 1].append(
els) ## SpGrp[ num ][ subnum ] = [ elem1, elem2, ... ]
SpGrp.allhasI[num - 1].append(inv)
f = open('elems.pkl', 'wb')
pickle.dump((SpGrp.allelems, SpGrp.allhasI), f, -1)
f.close()
def prep_m():
try:
d = pickle.load( open( 'elems.pkl', 'rb' ) )
SpGrp.allelems = d[ 0 ]
SpGrp.allhasI = d[ 1 ]
except: ## ... parse and save to file
ls = open( 'elems.dat' ).readlines()
ls = filter( lambda l: l, map( lambda l: l.strip(), ls ) )
for sls in groupby( ls, 4 ):
num, snum, inv, s, cnt = map( lambda s: int( s ), sls[ 0 ].split() )
mats = [ Mat( 0,0,0,0,0,0,0,0,0 ) for i in xrange( cnt ) ] ## create empty matrices
vecs = [ Vec( 0,0,0 ) for i in xrange( cnt ) ] ## ..and empty vectors
for i in xrange( 1, 4 ):
prts = map( lambda s: float( s ), sls[ i ].split() )
for j, els in enumerate( groupby( prts, 4 ) ): ## group by (m11, m12, m13, v1) groups
mats[ j ][ i-1 ] = els[ :-1 ] ## set one row of matrix
vecs[ j ][ i-1 ] = els[ -1 ] ## set one coord of vec
els = map( lambda e: SGElem( e[0], e[1] ), zip( mats, vecs ) )
SpGrp.allelems[ num-1 ].append( els ) ## SpGrp[ num ][ subnum ] = [ elem1, elem2, ... ]
SpGrp.allhasI[ num-1 ].append( inv )
f = open( 'elems.pkl', 'wb' )
pickle.dump( ( SpGrp.allelems,
SpGrp.allhasI ), f, -1 )
f.close()
yield res
ls = open( 'spgrp.dat' ).readlines()
ls = ls[ 235: ] ## drop conversion data
exp = re.compile( r'^spgr\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(.*)$' )
data = [ [] for i in xrange( 230 ) ]
for s in sg( ls ):
res = exp.match( s[ 0 ] )
if res:
num, snum, laue, inv, ngp, nsp, ngen = map( int, res.groups()[:-1] )
symb = res.groups()[ -1 ]
wyck = list( groupby( map( int, s[ 2 ].split() ), 2 ) )
gens = []
for l in filter( lambda l: l, s[ 3: ] ):
ps = l.split()
n = int( ps[ 0 ] )
v = tuple( map( float, ps[ 1: ] ) )
gens.append( ( n, v ) )
gens.reverse()
ginf = dict( laue = laue,
inv = inv,
ngp = ngp,
#nsp = nsp,
#ngen = ngen,
ls = open('spgrp.dat').readlines()
ls = ls[235:] ## drop conversion data
exp = re.compile(
r'^spgr\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(\d+)\s+(.*)$')
data = [[] for i in xrange(230)]
for s in sg(ls):
res = exp.match(s[0])
if res:
num, snum, laue, inv, ngp, nsp, ngen = map(int, res.groups()[:-1])
symb = res.groups()[-1]
wyck = list(groupby(map(int, s[2].split()), 2))
gens = []
for l in filter(lambda l: l, s[3:]):
ps = l.split()
n = int(ps[0])
v = tuple(map(float, ps[1:]))
gens.append((n, v))
gens.reverse()
ginf = dict(
laue=laue,
inv=inv,
ngp=ngp,
#nsp = nsp,