def _set_orderby_desc(self, query, model, limit,
last_id, offset, descending, orderby):
"""Return an updated query with the proper orderby and desc."""
if orderby == 'fav_user_ids':
n_favs = func.coalesce(func.array_length(model.fav_user_ids, 1), 0).label('n_favs')
query = query.add_column(n_favs)
if orderby in ['created', 'updated', 'finish_time']:
if descending:
query = query.order_by(desc(
cast(getattr(model,
orderby),
TIMESTAMP)))
else:
query = query.order_by(cast(getattr(model, orderby), TIMESTAMP))
else:
if orderby != 'fav_user_ids':
if descending:
query = query.order_by(desc(getattr(model, orderby)))
else:
query = query.order_by(getattr(model, orderby))
else:
if descending:
query = query.order_by(desc(text("n_favs")))
else:
query = query.order_by(text("n_favs"))
if last_id:
query = query.limit(limit)
else:
query = query.limit(limit).offset(offset)
return query
def get_paras(entries_q, profile_id=None):
CE, CU = CacheEntry, CacheUser
entries = entries_q.join(CE, CE.entry_id == Entry.id) \
.filter(func.array_length(CE.paras,1)>0) \
.with_entities(CE.paras).all()
paras = [p for e in entries for p in e.paras if e.paras]
if profile_id:
profile = db.session.query(CU) \
.filter(func.array_length(CU.paras,1)>0, CU.user_id == profile_id) \
.with_entities(CU.paras) \
.first()
if profile:
paras = profile.paras + paras
return paras
def _set_orderby_desc(self, query, model, limit,
last_id, offset, descending, orderby):
"""Return an updated query with the proper orderby and desc."""
if orderby == 'fav_user_ids':
n_favs = func.coalesce(func.array_length(model.fav_user_ids, 1), 0).label('n_favs')
query = query.add_column(n_favs)
if orderby in ['created', 'updated', 'finish_time']:
if descending:
query = query.order_by(desc(
cast(getattr(model,
orderby),
TIMESTAMP)))
else:
query = query.order_by(cast(getattr(model, orderby), TIMESTAMP))
else:
if orderby != 'fav_user_ids':
if descending:
query = query.order_by(desc(getattr(model, orderby)))
else:
query = query.order_by(getattr(model, orderby))
else:
if descending:
query = query.order_by(desc("n_favs"))
else:
query = query.order_by("n_favs")
if last_id:
query = query.limit(limit)
else:
query = query.limit(limit).offset(offset)
return query
def get_profiles():
error, verification_token = get_token(request.headers)
if error:
return error
query = request.args.get('query')
verification_email_id = VerificationToken.query.filter(
VerificationToken.token == verification_token.token).value(
VerificationToken.email_id)
return jsonify(
profiles_schema.dump(
matching_profiles(query).order_by(
# Is this the logged-in user's profile? If so, return it first (false)
Profile.verification_email_id != verification_email_id,
# Get the last word in the name.
# Won't work with suffixes.
func.split_part(
Profile.name,
' ',
func.array_length(
func.string_to_array(
func.regexp_replace(
Profile.name, '(,|MD).*',
''), # Remove suffixes after comma and MD
' '),
1 # How many words in the name
)))))
def themes(eids, algo='agglomorative'):
logger.info("Themes")
with session() as sess:
# use Model to decrypt fields
E, CE = M.Entry, M.CacheEntry
res = sess.query(CE) \
.with_entities(CE.paras, CE.clean, CE.vectors) \
.join(E, E.id == CE.entry_id) \
.filter(E.id.in_(eids), func.array_length(CE.vectors,1)>0) \
.order_by(E.created_at.desc()) \
.all()
# assert len(eids) == len(res)
entries = pd.Series([e for r in res for e in r.paras])
stripped = pd.Series([c for r in res for c in r.clean])
vecs = np.vstack([r.vectors for r in res]).astype(np.float32)
chain = Similars(vecs)
if False and os.path.exists(vars.AE_PATH):
chain = chain.autoencode(filename=vars.AE_PATH).cluster(algo=algo)
else:
chain = chain.normalize().cluster(algo=algo)
clusters = chain.value()
labels = chain.data.labels
topics = []
for l, center in enumerate(clusters):
mask = labels == l
n_entries = mask.sum().item()
print('n_entries', n_entries)
if n_entries < 2:
print('skipping')
continue
vecs_, stripped_, entries_ = vecs[mask], stripped[mask], entries[mask]
dists = Similars(center,
vecs_).normalize().cosine(abs=True).value().squeeze()
entries_ = entries_.iloc[dists.argsort()].tolist()[:5]
terms = top_terms(stripped_.tolist())
topics.append({
'n_entries': n_entries,
'terms': terms,
'summary': entries_, # add full thing, will batch-compute next
'sentiment': None,
})
groups = [t['summary'] for t in topics]
batch_summaries = nlp_.summarization(groups, min_length=50, max_length=300)
for i, res in enumerate(batch_summaries):
print(res)
topics[i]['summary'] = res['summary']
topics[i]['sentiment'] = res['sentiment']
topics = {'terms': top_terms(stripped, 10), 'themes': topics}
return topics
def sampling_figure(prefix="plots"):
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 26
xmin = 0.
radecs = []
level = 0.
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(111)
for ii in range(100):
lightCurves = session.query(LightCurve).filter(
func.array_length(LightCurve.mjd, 1) > 100).limit(100).all()
if level >= 10: break
for lc in lightCurves:
if (max(lc.mjd) - min(lc.mjd)) > 365:
next_lc = False
for radec in radecs:
try:
sep = g.subtends(lc.ra,
lc.dec,
radec[0],
radec[1],
units="degrees")
except ValueError:
next_lc = True
if sep < 5.:
next_lc = True
if next_lc: continue
else: radecs.append((lc.ra, lc.dec))
#ax.errorbar(lc.Rmjd, lc.Rmag, lc.Rerror, ls='none', marker='o', c='k', ecolor='0.7', capsize=0)
ax.plot(lc.Rmjd, [level] * len(lc.Rmjd),
marker='o',
ms=20.0,
c='k',
ls='none',
alpha=0.3)
if xmin == 0:
xmin = min(lc.Rmjd)
ax.set_xlim(xmin, xmin + 365)
level += 1
ymin, ymax = ax.get_ylim()
ydel = ymax - ymin
ax.set_ylim(ymin - ydel / 10., ymax + ydel / 10.)
ax.set_xlabel("MJD")
ax.set_yticklabels([])
plt.savefig(os.path.join(prefix, "ptf_sampling_figure.pdf"))
def register_about_page_navbar_links():
"""Generate all about page titles and URLs for use in the navbar."""
# NOTE: Because of the unconventional usage of Flask-Copilot
# (i.e. not as a routing decorator and always assigning an
# endpoint), our shorter navbar_paths must come before longer
# ones.
for page in AboutPage.query.current.filter_by(active=True).order_by(
func.array_length(AboutPage.navbar_path, 1)):
copilot.register_entry({
'path': page.navbar_path,
'endpoint': 'about.rst_content',
'url_for_kwargs': {'slug': page.slug},
})
def numero_differe_view(request):
"""
get numero_differe
"""
# Check connected
if not Utils.check_connected(request):
raise exc.HTTPForbidden()
role = request.params['role'] if 'role' in request.params else None
num_agg = func.array_agg(VNumeros.numero, type_=ARRAY(Integer)).label('numero')
diff_id_agg = func.array_agg(VNumeros.diff_id, type_=ARRAY(Integer)).label('numero_id')
query = request.dbsession.query(VNumeros.diff_affaire_id.label('diff_affaire_id'), VNumeros.cadastre.label('cadastre'), num_agg, diff_id_agg, func.min(VNumeros.diff_entree).label('diff_entree_min'))
if role == "mo":
user_id = request.params['user_id'] if 'user_id' in request.params else None
affaires = request.dbsession.query(Affaire, VNumeros)
if user_id is not None:
affaires = affaires.filter(Affaire.technicien_id == user_id)
affaires = affaires.filter(Affaire.id == VNumeros.diff_affaire_id).all()
affaires_id = [aff.Affaire.id for aff in affaires]
query = query.filter(and_(
VNumeros.diff_entree.isnot(None),
VNumeros.diff_sortie == None,
VNumeros.diff_affaire_id.in_(affaires_id)
))
elif role == "secr":
query = query.filter(and_(
VNumeros.diff_req_radiation.isnot(True),
VNumeros.diff_sortie.isnot(None)
))
result = query.group_by(VNumeros.diff_affaire_id, VNumeros.cadastre).having(func.array_length(num_agg, 1) > 0).all()
numeros = []
for num in result:
numeros.append({
'diff_affaire_id': num[0],
'cadastre': num[1],
'numero': num[2],
'diff_id': num[3],
'diff_entree': datetime.strftime(num[4], '%Y-%m-%d')
})
return json.dumps(numeros)
def register_about_page_navbar_links():
"""Generate all about page titles and URLs for use in the navbar."""
# NOTE: Because of the unconventional usage of Flask-Copilot
# (i.e. not as a routing decorator and always assigning an
# endpoint), our shorter navbar_paths must come before longer
# ones.
for page in AboutPage.query.current.filter_by(active=True).order_by(
func.array_length(AboutPage.navbar_path, 1)):
copilot.register_entry({
'path': page.navbar_path,
'endpoint': 'about.rst_content',
'url_for_kwargs': {
'slug': page.slug
},
})
def get_profiles():
error, verification_token = get_token(request.headers)
if error:
return error
query = request.args.get('query')
degrees = request.args.get('degrees', '')
affiliations = request.args.get('affiliations', '')
page = int(request.args.get('page', 1))
start, end = pagination(page)
verification_email_id = VerificationToken.query.filter(
VerificationToken.token == verification_token.token).value(
VerificationToken.email_id)
queryset = (
matching_profiles(query, degrees, affiliations).order_by(
# Is this the logged-in user's profile? If so, return it first (false)
Profile.verification_email_id != verification_email_id,
# Get the last word in the name.
# Won't work with suffixes.
func.split_part(
Profile.name,
' ',
func.array_length(
func.string_to_array(
func.regexp_replace(
Profile.name, '(,|MD).*',
''), # Remove suffixes after comma and MD
' ',
),
1, # How many words in the name
),
),
).group_by(Profile.id))
return jsonify({
'profileCount': queryset.count(),
'profiles': profiles_schema.dump(queryset[start:end]),
})
def sampling_figure(prefix="plots"):
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 26
xmin = 0.
radecs = []
level = 0.
fig = plt.figure(figsize=(15,15))
ax = fig.add_subplot(111)
for ii in range(100):
lightCurves = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 100).limit(100).all()
if level >= 10: break
for lc in lightCurves:
if (max(lc.mjd) - min(lc.mjd)) > 365:
next_lc = False
for radec in radecs:
try:
sep = g.subtends(lc.ra, lc.dec, radec[0], radec[1], units="degrees")
except ValueError:
next_lc = True
if sep < 5.:
next_lc = True
if next_lc: continue
else: radecs.append((lc.ra, lc.dec))
#ax.errorbar(lc.Rmjd, lc.Rmag, lc.Rerror, ls='none', marker='o', c='k', ecolor='0.7', capsize=0)
ax.plot(lc.Rmjd, [level]*len(lc.Rmjd), marker='o', ms=20.0, c='k', ls='none', alpha=0.3)
if xmin == 0:
xmin = min(lc.Rmjd)
ax.set_xlim(xmin, xmin+365)
level += 1
ymin, ymax = ax.get_ylim()
ydel = ymax-ymin
ax.set_ylim(ymin-ydel/10., ymax+ydel/10.)
ax.set_xlabel("MJD")
ax.set_yticklabels([])
plt.savefig(os.path.join(prefix, "ptf_sampling_figure.pdf"))
def count_by_group(self):
""" Returns the total number of notices by groups.
Returns a tuple ``(group name, number of notices)``
for each group. Filters by the state of the collection.
"""
result = self.session.query(UserGroup.name,
GazetteNotice._issues.keys())
result = result.filter(
GazetteNotice.group_id == UserGroup.id,
func.array_length(GazetteNotice._issues.keys(), 1) != 0)
if self.state:
result = result.filter(GazetteNotice.state == self.state)
if self.issues:
result = result.filter(GazetteNotice._issues.has_any(self.issues))
result = result.order_by(UserGroup.name)
issues = set(self.issues or [])
operation = issues.intersection if issues else issues.union
return [(group[0], sum([len(operation(set(x[1]))) for x in group[1]]))
for group in groupbylist(result, lambda a: a[0])]
def get_ordering(sorting):
last_name_sorting = func.split_part(
profile_class.name,
" ",
func.array_length(
func.string_to_array(profile_class.name, " "),
1, # Length in the 1st dimension
),
)
sort_options = {
"starred": [
desc(text("profile_star_count")),
desc(profile_class.date_updated),
],
"last_name_alphabetical": [asc(last_name_sorting)],
"last_name_reverse_alphabetical": [desc(last_name_sorting)],
"date_updated": [desc(profile_class.date_updated)],
}
if sorting not in sort_options:
raise InvalidPayloadError({"sorting": ["invalid"]})
return sort_options[sorting]
def has_synonyms(query: Query) -> Query:
return query.filter(func.array_length(VocabularyTerm.french, 1) > 1)
def api_v1_get_replays():
if 'key' in request.args:
api_key = request.args['key']
else:
api_key = None
args = request.args
print(args)
if 'page' not in args:
page = 0
else:
page = int(args['page']) - 1
if page < 0:
page = 0
session = current_app.config['db']()
games = session.query(Game)
# RANK STUFF
if 'rankany' in args:
rank_opt = 'any'
else:
rank_opt = 'all'
if 'maxrank' in args:
games = games.filter(
getattr(Game.ranks, rank_opt)(int(args['maxrank']),
operator=operators.ge))
if 'minrank' in args:
games = games.filter(
getattr(Game.ranks, rank_opt)(int(args['minrank']),
operator=operators.le))
any_rank_modifier = ['minrank', 'maxrank']
if any([m in args for m in any_rank_modifier]):
games = games.filter(func.array_length(Game.ranks, 1) > 0)
# MMR stuff
if 'mmrany' in args:
mmr_opt = 'any'
else:
mmr_opt = 'all'
if 'maxmmr' in args:
games = games.filter(
getattr(Game.mmrs, mmr_opt)(int(args['maxmmr']),
operator=operators.ge))
if 'minmmr' in args:
games = games.filter(
getattr(Game.mmrs, mmr_opt)(int(args['minmmr']),
operator=operators.le))
any_mmr_modifier = ['maxmmr', 'minmmr']
if any([m in args for m in any_mmr_modifier]):
games = games.filter(func.array_length(Game.mmrs, 1) > 0)
# USER stuff
if 'user' in args:
games = games.filter(Game.players.any(args['user']))
# YEAR stuff
if 'year' in args:
games = games.filter(
Game.match_date > datetime.date(int(args['year']), 1, 1)).filter(
Game.match_date < datetime.date(int(args['year']) + 1, 1, 1))
# GAME stuff
if 'map' in args:
games = games.filter(Game.map == args['map'])
if 'teamsize' in args:
games = games.filter(Game.teamsize == int(args['teamsize']))
pagesize = 50
if 'num' in args:
pagesize = int(args['num'])
response = {}
data = []
games = games[page * pagesize:(page + 1) * pagesize]
game: Game
for game in games:
data.append({
'team_blue_score':
game.team0score,
'team_orange_score':
game.team1score,
'match_date':
game.match_date,
'upload_date':
game.upload_date,
'map':
game.map,
'matchtype':
game.matchtype,
'teamsize':
game.teamsize,
'hash':
game.hash,
'link':
url_for('replays.view_replay', id_=game.hash),
'download':
url_for('replays.download_replay', id_=game.hash),
'info':
url_for('apiv1.api_v1_get_replay_info', id_=game.hash,
key=api_key),
'mmrs':
game.mmrs,
'ranks':
game.ranks,
'players':
game.players
})
response['data'] = data
response['page'] = page + 1
response['next'] = url_for('apiv1.api_v1_get_replays',
page=page + 2,
key=api_key)
response['version'] = 1
session.close()
return jsonify(response)
)
temp_radgroupreply = as_copy(radgroupreply, 'temp_radgroupreply')
radpostauth = Table(
'radpostauth', metadata,
Column('Id', BigInteger, primary_key=True, nullable=False),
Column('UserName', Text, nullable=False),
Column('NASIPAddress', IPAddress, nullable=False),
Column('NASPortId', Text),
Column('PacketType', Text, nullable=False),
Column('Groups', TupleArray(Text, dimensions=1)),
Column('Reply', TupleArray(Text, dimensions=2)),
Column('AuthDate', DateTime(timezone=True), nullable=False),
CheckConstraint(func.array_ndim("Groups") == 1),
CheckConstraint(func.array_ndim("Reply") == 2 and
func.array_length("Reply", 2) == 2),
)
radreply = Table(
'radreply', metadata,
Column('Priority', Integer, nullable=False),
Column('UserName', Text, nullable=False),
Column('NASIPAddress', IPAddress, nullable=False),
Column('NASPortId', Text, nullable=False),
Column('Attribute', Text, nullable=False),
Column('Op', String(2), default='=', nullable=False),
Column('Value', Text, nullable=False),
UniqueConstraint('UserName', 'NASIPAddress', 'NASPortId', 'Priority'),
)
temp_radreply = as_copy(radreply, 'temp_radreply')
def bad_data_figure(prefix="plots"):
matplotlib.rcParams["axes.titlesize"] = 40
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 20
matplotlib.rcParams["ytick.labelsize"] = 20
lightCurve1 = session.query(LightCurve).filter(
LightCurve.objid == 14688560553413090141).one()
lightCurve2 = session.query(LightCurve).filter(
LightCurve.objid == 14688560553413090134).one()
print "Distance between objects: {0}\"".format(
g.subtends(lightCurve1.ra,
lightCurve1.dec,
lightCurve2.ra,
lightCurve2.dec,
units="degrees") * 3600.)
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
fig = plt.figure(figsize=(20, 25))
fig.subplots_adjust(hspace=0.2, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd,
lightCurve1.mag,
lightCurve1.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd,
lightCurve2.mag,
lightCurve2.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax1.set_ylim(medMag1 - 0.5, medMag1 + 0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2 - 0.5, medMag2 + 0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.savefig(os.path.join(prefix, "bad_data_figure.pdf"))
return
# Code below is to search for light curves that are similar
while True:
lightCurve1 = session.query(LightCurve).filter(
func.array_length(LightCurve.mjd, 1) > 200).order_by(
func.random()).limit(1).one()
lightCurve2 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).\
filter(func.q3c_radial_query(LightCurve.ra, LightCurve.dec, lightCurve1.ra, lightCurve1.dec, 60./3600.)).\
order_by(func.random()).limit(1).one()
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
if medMag1 > 17 or medMag2 > 17: continue
fig = plt.figure(figsize=(20, 25))
fig.subplots_adjust(hspace=0.3, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd,
lightCurve1.mag,
lightCurve1.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd,
lightCurve2.mag,
lightCurve2.error,
ls='none',
marker='o',
ecolor='0.7',
capsize=0)
ax1.set_ylim(medMag1 - 0.5, medMag1 + 0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2 - 0.5, medMag2 + 0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.show()
def numero_differe_view(request):
"""
get numero_differe
"""
# Check connected
if not Utils.check_connected(request):
raise exc.HTTPForbidden()
numero_projet_id = int(request.registry.settings['numero_projet_id'])
numero_vigueur_id = int(request.registry.settings['numero_vigueur_id'])
role = request.params['role'] if 'role' in request.params else None
num_agg = func.array_agg(VNumeros.numero, type_=ARRAY(Integer))
num_id_agg = func.array_agg(VNumeros.id, type_=ARRAY(Integer))
diff_id_agg = func.array_agg(VNumeros.diff_id, type_=ARRAY(Integer))
query = request.dbsession.query(
VNumeros.diff_affaire_id,
VNumeros.cadastre, num_agg, num_id_agg, diff_id_agg,
func.min(VNumeros.diff_entree), VNumeros.diff_operateur_id,
VNumeros.diff_operateur_nom, VNumeros.diff_operateur_prenom,
VNumeros.diff_operateur_initiales)
if role == "mo":
user_id = request.params[
'user_id'] if 'user_id' in request.params else None
if user_id is not None:
query = query.filter(VNumeros.diff_operateur_id == user_id)
query = query.filter(
and_(VNumeros.diff_entree.isnot(None),
VNumeros.diff_sortie == None))
elif role == "secr":
query = query.filter(
and_(VNumeros.diff_req_radiation.isnot(True),
VNumeros.diff_sortie.isnot(None),
VNumeros.etat_id.in_((numero_projet_id, numero_vigueur_id))))
result = query.group_by(VNumeros.diff_affaire_id, VNumeros.cadastre,
VNumeros.diff_operateur_id,
VNumeros.diff_operateur_nom,
VNumeros.diff_operateur_prenom,
VNumeros.diff_operateur_initiales).having(
func.array_length(num_agg, 1) > 0).all()
numeros = []
for num in result:
numeros.append({
'diff_affaire_id': num[0],
'cadastre': num[1],
'numero': num[2],
'numero_id': num[3],
'diff_id': num[4],
'diff_entree': datetime.strftime(num[5], '%Y-%m-%d'),
'diff_operateur_id': num[6],
'diff_operateur_nom': num[7],
'diff_operateur_prenom': num[8],
'diff_operateur_initiales': num[9]
})
return numeros
def bad_data_figure(prefix="plots"):
matplotlib.rcParams["axes.titlesize"] = 40
matplotlib.rcParams["axes.labelsize"] = 40
matplotlib.rcParams["xtick.labelsize"] = 20
matplotlib.rcParams["ytick.labelsize"] = 20
lightCurve1 = session.query(LightCurve).filter(LightCurve.objid == 14688560553413090141).one()
lightCurve2 = session.query(LightCurve).filter(LightCurve.objid == 14688560553413090134).one()
print "Distance between objects: {0}\"".format(g.subtends(lightCurve1.ra, lightCurve1.dec, lightCurve2.ra, lightCurve2.dec, units="degrees")*3600.)
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
fig = plt.figure(figsize=(20,25))
fig.subplots_adjust(hspace=0.2, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd, lightCurve1.mag, lightCurve1.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd, lightCurve2.mag, lightCurve2.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax1.set_ylim(medMag1-0.5,medMag1+0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2-0.5,medMag2+0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.savefig(os.path.join(prefix, "bad_data_figure.pdf"))
return
# Code below is to search for light curves that are similar
while True:
lightCurve1 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).order_by(func.random()).limit(1).one()
lightCurve2 = session.query(LightCurve).filter(func.array_length(LightCurve.mjd, 1) > 200).\
filter(func.q3c_radial_query(LightCurve.ra, LightCurve.dec, lightCurve1.ra, lightCurve1.dec, 60./3600.)).\
order_by(func.random()).limit(1).one()
medMag1 = np.median(lightCurve1.mag)
medMag2 = np.median(lightCurve2.mag)
if medMag1 > 17 or medMag2 > 17: continue
fig = plt.figure(figsize=(20,25))
fig.subplots_adjust(hspace=0.3, left=0.1)
ax1 = fig.add_subplot(211)
ax1.errorbar(lightCurve1.mjd, lightCurve1.mag, lightCurve1.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax2 = fig.add_subplot(212)
ax2.errorbar(lightCurve2.mjd, lightCurve2.mag, lightCurve2.error, ls='none', marker='o', ecolor='0.7', capsize=0)
ax1.set_ylim(medMag1-0.5,medMag1+0.5)
ax1.set_ylim(ax1.get_ylim()[::-1])
ax1.set_xlim(55000, 56000)
ax1.set_ylabel(r"$R$")
ax1.set_xticklabels([])
ax1.set_title("objid: {0}".format(lightCurve1.objid))
ax2.set_ylim(medMag2-0.5,medMag2+0.5)
ax2.set_ylim(ax2.get_ylim()[::-1])
ax2.set_xlim(55000, 56000)
ax2.set_ylabel(r"$R$")
ax2.set_xlabel("MJD")
ax2.set_title("objid: {0}".format(lightCurve2.objid))
plt.show()
radpostauth = Table(
"radpostauth",
metadata,
Column('Id', BigInteger, primary_key=True, nullable=False),
Column('UserName', Text, nullable=False),
Column('NASIPAddress', IPAddress, nullable=False),
Column('NASPortId', Text),
Column('PacketType', Text, nullable=False),
Column('Groups', TupleArray(Text, dimensions=1)),
Column('Reply', TupleArray(Text, dimensions=2)),
Column('AuthDate', DateTime(timezone=True), nullable=False),
CheckConstraint(func.coalesce(func.array_ndims("Groups"), 1) == 1),
CheckConstraint(
func.coalesce(func.array_ndims("Reply"), 2) == 2
and func.coalesce(func.array_length("Reply", 2), 2) == 2),
)
radreply = Table(
"radreply",
metadata,
Column('Priority', Integer, nullable=False),
Column('UserName', Text, nullable=False),
Column('NASIPAddress', IPAddress, nullable=False),
Column('NASPortId', Text, nullable=False),
Column('Attribute', Text, nullable=False),
Column('Op', String(2), default='=', nullable=False),
Column('Value', Text, nullable=False),
UniqueConstraint('UserName', 'NASIPAddress', 'NASPortId', 'Priority'),
)
temp_radreply = as_copy(radreply, 'temp_radreply')
