def do_import(ll):
dim,det,level,gram,density,hermite,minimum,kissing,shortest,aut,theta_series,class_number,genus_reps,name,comments = ll
mykeys = ['dim','det','level','gram','density','hermite', 'minimum','kissing','shortest','aut','theta_series','class_number','genus_reps','name','comments']
data = {}
for j in range(len(mykeys)):
data[mykeys[j]] = ll[j]
blabel = base_label(data['dim'],data['det'],data['level'], data['class_number'])
data['base_label'] = blabel
data['index'] = label_lookup(blabel)
label= last_label(blabel, data['index'])
data['label'] = label
lattice = lat.find_one({'label': label})
if lattice is None:
print "new lattice"
print "***********"
print "check for isometries..."
A=data['gram'];
n=len(A[0])
d=matrix(A).determinant()
result=[B for B in lat.find({'dim': int(n), 'det' : int(d)}) if isom(A, B['gram'])]
if len(result)>0:
print "... the lattice with base label "+ blabel + " is isometric to " + str(result[0]['gram'])
print "***********"
else:
lattice = data
else:
print "lattice already in the database"
lattice.update(data)
if saving:
lat.update({'label': label} , {"$set": lattice}, upsert=True)
def lattice_search_isometric(res, info, query):
"""
We check for isometric lattices if the user enters a valid gram matrix
but not one stored in the database
This may become slow in the future: at the moment we compare against
a list of stored matrices with same dimension and determinant
(just compare with respect to dimension is slow)
"""
if info['number'] == 0 and info.get('gram'):
A = query['gram']
n = len(A[0])
d = matrix(A).determinant()
for gram in db.lat_lattices.search({'dim': n, 'det': int(d)}, 'gram'):
if isom(A, gram):
query['gram'] = gram
proj = lattice_search_projection
count = parse_count(info)
start = parse_start(info)
res = db.lat_lattices.search(query, proj, limit=count, offset=start, info=info)
break
for v in res:
v['min'] = v.pop('minimum')
return res
def do_import(ll):
dim,det,level,gram,density,hermite,minimum,kissing,shortest,aut,theta_series,class_number,genus_reps,name,comments = ll
mykeys = ['dim','det','level','gram','density','hermite', 'minimum','kissing','shortest','aut','theta_series','class_number','genus_reps','name','comments']
data = {}
for j in range(len(mykeys)):
data[mykeys[j]] = ll[j]
blabel = base_label(data['dim'],data['det'],data['level'], data['class_number'])
data['base_label'] = blabel
data['index'] = label_lookup(blabel)
label= last_label(blabel, data['index'])
data['label'] = label
lattice = lat.find_one({'label': label})
if lattice is None:
print("new lattice")
print("***********")
print("check for isometries...")
A=data['gram'];
n=len(A[0])
d=matrix(A).determinant()
result=[B for B in lat.find({'dim': int(n), 'det' : int(d)}) if isom(A, B['gram'])]
if len(result)>0:
print("... the lattice with base label "+ blabel + " is isometric to " + str(result[0]['gram']))
print("***********")
else:
lattice = data
else:
print("lattice already in the database")
lattice.update(data)
if saving:
lat.update({'label': label} , {"$set": lattice}, upsert=True)
def lattice_search_isometric(res, info, query):
"""
We check for isometric lattices if the user enters a valid gram matrix
but not one stored in the database
This may become slow in the future: at the moment we compare against
a list of stored matrices with same dimension and determinant
(just compare with respect to dimension is slow)
"""
if info['number'] == 0 and info.get('gram'):
A = query['gram']
n = len(A[0])
d = matrix(A).determinant()
for gram in db.lat_lattices.search({'dim': n, 'det': int(d)}, 'gram'):
if isom(A, gram):
query['gram'] = gram
proj = lattice_search_projection
count = parse_count(info)
start = parse_start(info)
res = db.lat_lattices.search(query, proj, limit=count, offset=start, info=info)
break
for v in res:
v['min'] = v.pop('minimum')
return res
def add_lattice_nf(ll):
n_field, gram_input = ll
gram_input = [[int(i) for i in l] for l in gram_input]
R = PolynomialRing(QQ, 'x')
nf_label = poly_to_field_label(R(n_field))
lattice = l1.find_one({'gram': gram_input})
if lattice is None:
n = len(gram_input[0])
d = matrix(gram_input).determinant()
result = [
B for B in l1.find({
'dim': int(n),
'det': int(d)
}) if isom(gram_input, B['gram'])
]
if len(result) == 1:
lat_label = result[0]['label']
is_lat_in = "yes"
elif len(result) > 1:
print "... need to be checked ..."
print "***********"
else:
lat_label = "new"
is_lat_in = gram_input
else:
lat_label = lattice['label']
is_lat_in = "yes"
try:
lab = nf_label + lat_label
except:
print nf_label, lat_label
print "fail"
res = l2.find_one({'label': lab})
if res is None:
print "new data"
if saving:
l2.insert_one({
'nf_label': nf_label,
'lat_label': lat_label,
'is_lat_in': is_lat_in,
'label': lab
})
else:
print "data already in the database"
def add_lattice_nf(ll):
n_field,gram_input = ll
gram_input=[[int(i) for i in l] for l in gram_input]
R = PolynomialRing(QQ, 'x');
nf_label = poly_to_field_label(R(n_field))
lattice = l1.find_one({'gram': gram_input })
if lattice is None:
n=len(gram_input[0])
d=matrix(gram_input).determinant()
result=[B for B in l1.find({'dim': int(n), 'det' : int(d)}) if isom(gram_input, B['gram'])]
if len(result)==1:
lat_label =result[0]['label']
is_lat_in = "yes"
elif len(result)>1:
print "... need to be checked ..."
print "***********"
else :
lat_label = "new"
is_lat_in = gram_input
else:
lat_label=lattice['label']
is_lat_in = "yes"
try:
lab=nf_label+lat_label
except:
print nf_label, lat_label
print "fail"
res=l2.find_one({'label': lab })
if res is None:
print "new data"
if saving:
l2.insert_one({'nf_label': nf_label, 'lat_label': lat_label, 'is_lat_in' : is_lat_in, 'label': lab})
else:
print "data already in the database"
def lattice_search(**args):
info = to_dict(args) # what has been entered in the search boxes
if 'download' in info:
return download_search(info)
if 'label' in info and info.get('label'):
return lattice_by_label_or_name(info.get('label'))
query = {}
try:
for field, name in (('dim','Dimension'),('det','Determinant'),('level',None),
('minimum','Minimal vector length'), ('class_number',None), ('aut','Group order')):
parse_ints(info, query, field, name)
# Check if length of gram is triangular
gram = info.get('gram')
if gram and not (9 + 8*ZZ(gram.count(','))).is_square():
flash(Markup("Error: <span style='color:black'>%s</span> is not a valid input for Gram matrix. It must be a list of integer vectors of triangular length, such as [1,2,3]." % (gram)),"error")
raise ValueError
parse_list(info, query, 'gram', process=vect_to_sym)
except ValueError as err:
info['err'] = str(err)
return search_input_error(info)
count = parse_count(info,50)
start = parse_start(info)
info['query'] = dict(query)
res = lattice_db().find(query).sort([('dim', ASC), ('det', ASC), ('level', ASC), ('class_number', ASC), ('label', ASC), ('minimum', ASC), ('aut', ASC)]).skip(start).limit(count)
nres = res.count()
# here we are checking for isometric lattices if the user enters a valid gram matrix but not one stored in the database_names, this may become slow in the future: at the moment we compare against list of stored matrices with same dimension and determinant (just compare with respect to dimension is slow)
if nres==0 and info.get('gram'):
A=query['gram'];
n=len(A[0])
d=matrix(A).determinant()
result=[B for B in lattice_db().find({'dim': int(n), 'det' : int(d)}) if isom(A, B['gram'])]
if len(result)>0:
result=result[0]['gram']
query_gram={ 'gram' : result }
query.update(query_gram)
res = lattice_db().find(query)
nres = res.count()
if(start >= nres):
start -= (1 + (start - nres) / count) * count
if(start < 0):
start = 0
info['number'] = nres
info['start'] = int(start)
info['more'] = int(start + count < nres)
if nres == 1:
info['report'] = 'unique match'
else:
if nres == 0:
info['report'] = 'no matches'
else:
if nres > count or start != 0:
info['report'] = 'displaying matches %s-%s of %s' % (start + 1, min(nres, start + count), nres)
else:
info['report'] = 'displaying all %s matches' % nres
res_clean = []
for v in res:
v_clean = {}
v_clean['label']=v['label']
v_clean['dim']=v['dim']
v_clean['det']=v['det']
v_clean['level']=v['level']
v_clean['class_number']=v['class_number']
v_clean['min']=v['minimum']
v_clean['aut']=v['aut']
res_clean.append(v_clean)
info['lattices'] = res_clean
t = 'Integral Lattices Search Results'
bread = [('Lattices', url_for(".lattice_render_webpage")),('Search Results', ' ')]
properties = []
return render_template("lattice-search.html", info=info, title=t, properties=properties, bread=bread, learnmore=learnmore_list())