示例#1
0
def rep_galois_modl_search(info, query):
    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)
示例#2
0
def higher_genus_w_automorphisms_search(**args):
    info = to_dict(args)
    bread = get_bread([("Search results", url_for('.search'))])
    C = base.getDBConnection()
    query = {}
    if 'jump_to' in info:
        return render_hgcwa_webpage({'label': info['jump_to']})

    try:
        parse_list(info,query,'group', name='Group')
        parse_ints(info,query,'genus',name='Genus')
        parse_list(info,query,'signature',name='Signature')
        parse_ints(info,query,'dim',name='Dimension of the family')
        if 'inc_hyper' in info:
            if info['inc_hyper'] == 'exclude':
                query['hyperelliptic'] = False
            elif info['inc_hyper'] == 'only':
                query['hyperelliptic'] = True
    except ValueError:
        return search_input_error(info, bread)
    count = parse_count(info)
    start = parse_start(info)
    
    res = C.curve_automorphisms.families.find(query).sort([(
         'g', pymongo.ASCENDING), ('dim', pymongo.ASCENDING)])
    nres = res.count()
    res = res.skip(start).limit(count)

    if(start >= nres):
        start -= (1 + (start - nres) / count) * count
    if(start < 0):
        start = 0

    info['fields'] = res
    info['number'] = nres
    info['group_display'] = group_display_shortC(C)
    info['sign_display'] = sign_display
    info['start'] = start
    if nres == 1:
        info['report'] = 'unique match'
    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

    return render_template("hgcwa-search.html", info=info, title="Higher Genus Curves with Automorphisms Search Result", bread=bread, credit=HGCwA_credit)
示例#3
0
文件: main.py 项目: lexmart/lmfdb
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())
示例#4
0
文件: main.py 项目: AurelPage/lmfdb
def rep_galois_modl_search(**args):
    C = getDBConnection()
    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 rep_galois_modl_by_label_or_name(info.get('label'), C)
    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 = C.mod_l_galois.reps.find(query).sort([('dim', ASC), ('det', ASC), ('level', ASC), ('class_number', ASC), ('label', ASC)]).skip(start).limit(count)
    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['gram']=vect_to_matrix(v['gram'])
        res_clean.append(v_clean)

    info['rep_galois_modls'] = res_clean

    t = 'Mod &#x2113; Galois representations Search Results'

    bread = [('Representations', "/Representation"),("mod &#x2113;", url_for(".index")), ('Search Results', ' ')]
    properties = []
    return render_template("rep_galois_modl-search.html", info=info, title=t, properties=properties, bread=bread, learnmore=learnmore_list())
示例#5
0
文件: main.py 项目: riiduan/lmfdb
def rep_galois_modl_search(**args):
    C = getDBConnection()
    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 rep_galois_modl_by_label_or_name(info.get('label'), C)
    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 = C.mod_l_galois.reps.find(query).sort([('dim', ASC), ('det', ASC),
                                                ('level', ASC),
                                                ('class_number', ASC),
                                                ('label', ASC)
                                                ]).skip(start).limit(count)
    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['gram'] = vect_to_matrix(v['gram'])
        res_clean.append(v_clean)

    info['rep_galois_modls'] = res_clean

    t = 'Mod &#x2113; Galois representations Search Results'

    bread = [('Representations', "/Representation"),
             ("mod &#x2113;", url_for(".index")), ('Search Results', ' ')]
    properties = []
    return render_template("rep_galois_modl-search.html",
                           info=info,
                           title=t,
                           properties=properties,
                           bread=bread,
                           learnmore=learnmore_list())
示例#6
0
def lattice_search(**args):
    C = getDBConnection()
    C.Lattices.lat.ensure_index([('dim', ASC), ('label', ASC)])
    info = to_dict(args)  # what has been entered in the search boxes
    if 'label' in info:
        lab = info.get('label')
        control = by_label_or_name(lab, C)
        if control == "ok":
            args = {'label': lab}
            return render_lattice_webpage(**args)
        else:
            check = lattice_label_error(control, lab,
                                        url_for(".lattice_render_webpage"))
            if check is not None:
                return check

    query = {}
    for field in [
            'dim', 'det', 'level', 'gram', 'minimum', 'class_number', 'aut'
    ]:
        if info.get(field):
            if field in [
                    'dim', 'det', 'level', 'minimum', 'class_number', 'aut'
            ]:
                try:
                    info['start']
                    check = parse_ints(info.get(field), query, field)
                except:
                    check = parse_ints(info.get(field), query, field,
                                       url_for(".lattice_render_webpage"))
                if check is not None:
                    return check
            elif field == 'gram':
                try:
                    info['start']
                    check = parse_list(info.get(field), query, field,
                                       vect_to_sym)
                except:
                    check = parse_list(info.get(field), query, field,
                                       vect_to_sym,
                                       url_for(".lattice_render_webpage"))
                if check is not None:
                    return check
    info['query'] = dict(query)
    res = C.Lattices.lat.find(query).sort([('level', ASC), ('label', ASC)])
    nres = res.count()
    count = 100

    if nres == 1:
        info['report'] = 'unique match'
    else:
        if nres > count:
            info['report'] = 'displaying first %s of %s matches' % (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['gram'] = vect_to_matrix(v['gram'])
        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)
示例#7
0
文件: main.py 项目: am-github/lmfdb
def lattice_search(**args):
    C = getDBConnection()
    C.Lattices.lat.ensure_index([('dim', ASC), ('label', ASC)])
    info = to_dict(args)  # what has been entered in the search boxes
    if 'label' in info:
        lab = info.get('label')
        control= by_label_or_name(lab, C)
        if control == "ok":
            args = {'label': lab }
            return render_lattice_webpage(**args)
        else:
            check=lattice_label_error(control, lab , url_for(".lattice_render_webpage"))
            if check is not None:
                return check

    query = {}
    for field in ['dim','det','level', 'gram', 'minimum', 'class_number', 'aut']:
        if info.get(field):
            if field in ['dim', 'det', 'level', 'minimum', 'class_number', 'aut']:
                try:
                    info['start']
                    check= parse_ints(info.get(field), query, field)
                except:
                    check= parse_ints(info.get(field), query, field, url_for(".lattice_render_webpage"))
                if check is not None:
                    return check
            elif field == 'gram':
                try:
                    info['start']
                    check= parse_list(info.get(field), query, field, vect_to_sym)
                except:
                    check= parse_list(info.get(field), query, field, vect_to_sym, url_for(".lattice_render_webpage"))
                if check is not None:
                    return check
    info['query'] = dict(query)
    res = C.Lattices.lat.find(query).sort([('dim', ASC), ('det', ASC), ('label', ASC)])
    nres = res.count()
    count = 100

    if nres == 1:
        info['report'] = 'unique match'
    else:
        if nres > count:
            info['report'] = 'displaying first %s of %s matches' % (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['gram']=vect_to_matrix(v['gram'])
        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)
示例#8
0
文件: main.py 项目: alinabucur/lmfdb
def rep_galois_modl_search(**args):
    C = getDBConnection()
    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 rep_galois_modl_by_label_or_name(info.get("label"), C)
    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 = (
        C.mod_l_galois.reps.find(query)
        .sort([("dim", ASC), ("det", ASC), ("level", ASC), ("class_number", ASC), ("label", ASC)])
        .skip(start)
        .limit(count)
    )
    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["gram"] = vect_to_matrix(v["gram"])
        res_clean.append(v_clean)

    info["rep_galois_modls"] = res_clean

    t = "Mod &#x2113; Galois representations Search Results"

    bread = [("Representations", "/Representation"), ("mod &#x2113;", url_for(".index")), ("Search Results", " ")]
    properties = []
    return render_template(
        "rep_galois_modl-search.html",
        info=info,
        title=t,
        properties=properties,
        bread=bread,
        learnmore=learnmore_list(),
    )