def testBuggyExport1(self):
with self.db.transaction() as tr:
indexes = (AnaIndex(),
LevelIndex(frozen=True, start=((1, None, None), (3, 2, None))),
TimeRangeIndex(),
DateTimeIndex())
query = {}
query['rep_memo'] = 'synop'
read(tr.query_data(query), indexes, checkConflicts=True, attributes=True)
def testConflicts(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = dict(ana_id=1, var="B13011")
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
# Here conflicting values are overwritten
vars = read(tr.query_data(query), (AnaIndex(), ), checkConflicts=False)
self.assertEqual(type(vars), dict)
# Here insted they should be detected
with self.assertRaises(IndexError):
read(tr.query_data(query), (AnaIndex(),), checkConflicts=True)
def testUnsharedIndex(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = dict(ana_id=1, rep_memo="synop")
vars = read(tr.query_data(query),
(AnaIndex(), TimeRangeIndex(), DateTimeIndex()))
self.assertEqual(len(vars["B13011"].dims[2]), len(vars["B10004"].dims[2]))
self.assertEqual(vars["B13011"].dims[2], vars["B10004"].dims[2])
vars = read(tr.query_data(query),
(AnaIndex(), TimeRangeIndex(), DateTimeIndex(shared=False)))
self.assertNotEqual(len(vars["B13011"].dims[2]), len(vars["B10004"].dims[2]))
def testIndexFind(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = dict(ana_id=1, var="B13011", rep_memo="synop")
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
vars = read(tr.query_data(query), (AnaIndex(), TimeRangeIndex()))
self.assertEqual(vars["B13011"].dims[1].index((4, -21600, 0)), 1)
def testExportAna(self):
with self.db.transaction() as tr:
indexes = (AnaIndex(),)
query = {}
query["rep_memo"] = "synop"
vars = read(tr.query_station_data(query), indexes, checkConflicts=True)
self.assertEqual(sorted(vars.keys()), ["B01001", "B01002", "B01019"])
def testSomeAttrs(self):
with self.db.transaction() as tr:
# Same export as testAnaNetwork, but check that the
# attributes are synchronised
query = {}
query["var"] = "B10004"
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
vars = read(tr.query_data(query), (AnaIndex(), NetworkIndex()), attributes=('B33040',))
self.assertEqual(len(vars), 1)
self.assertCountEqual(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEqual(len(data.attrs), 1)
self.assertCountEqual(data.attrs.keys(), ['B33040'])
a = data.attrs['B33040']
self.assertEqual(data.dims, a.dims)
self.assertEqual(data.vals.size, a.vals.size)
self.assertEqual(data.vals.shape, a.vals.shape)
# Find the temp index
netidx = -1
for idx, n in enumerate(data.dims[1]):
if n == "temp":
netidx = idx
break
self.assertNotEqual(netidx, -1)
# Only compare the values on the temp index
self.assertEqual([x for x in a.vals.mask[:, 1-netidx].flat], [True]*len(a.vals.mask[:, 1-netidx].flat))
self.assertEqual([x for x in data.vals.mask[:, netidx].flat], [x for x in a.vals.mask[:, netidx].flat])
self.assertEqual(round(ma.average(a.vals)), 54)
def testAttrs(self):
with self.db.transaction() as tr:
# Same export as testAnaNetwork, but check that the
# attributes are synchronised
query = {}
query["var"] = "B10004"
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
vars = read(tr.query_data(query), (AnaIndex(), NetworkIndex()), attributes=True)
self.assertEqual(len(vars), 1)
self.assertCountEqual(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEqual(len(data.attrs), 2)
self.assertCountEqual(sorted(data.attrs.keys()), ['B33007', 'B33040'])
for net, a in ('synop', 'B33007'), ('temp', 'B33040'):
self.assertEqual(data.dims, data.attrs[a].dims)
self.assertEqual(data.vals.size, data.attrs[a].vals.size)
self.assertEqual(data.vals.shape, data.attrs[a].vals.shape)
# Find what is the network dimension where we have the attributes
netidx = -1
for idx, n in enumerate(data.dims[1]):
if n == net:
netidx = idx
break
self.assertNotEqual(netidx, -1)
# No attrs in the other network
self.assertEqual([x for x in data.attrs[a].vals.mask[:, 1-netidx].flat], [True]*len(data.attrs[a].vals.mask[:, 1-netidx].flat))
# Same attrs as values in this network
self.assertEqual([x for x in data.vals.mask[:, netidx].flat], [x for x in data.attrs[a].vals.mask[:, netidx].flat])
self.assertEqual(round(ma.average(data.attrs['B33007'].vals)), 32)
self.assertEqual(round(ma.average(data.attrs['B33040'].vals)), 54)
def testAnaNetwork(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = {}
query["var"] = "B10004"
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
vars = read(tr.query_data(query), (AnaIndex(), NetworkIndex()))
self.assertEqual(len(vars), 1)
self.assertCountEqual(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEqual(data.name, "B10004")
self.assertEqual(len(data.attrs), 0)
self.assertEqual(len(data.dims), 2)
self.assertEqual(len(data.dims[0]), 11)
self.assertEqual(len(data.dims[1]), 2)
self.assertEqual(data.vals.size, 22)
self.assertEqual(data.vals.shape, (11, 2))
self.assertEqual(sum(data.vals.mask.flat), 11)
self.assertEqual(round(ma.average(data.vals)), 83185)
self.assertEqual(data.dims[0][0], (1, 10., 15., None))
self.assertEqual(data.dims[0][1], (2, 10., 25., None))
self.assertEqual(data.dims[0][2], (3, 20., 15., None))
self.assertEqual(data.dims[0][3], (4, 20., 25., None))
self.assertEqual(data.dims[0][4], (5, 30., 15., None))
self.assertEqual(data.dims[0][5], (6, 30., 25., None))
self.assertEqual(set(data.dims[1]), set(("temp", "synop")))
def test_bug1(self):
# Second test case reported by Paolo
query = dballe.Record()
# query.setd("latmin", 10.)
# query.setd("latmax", 60.)
# query.setd("lonmin", -10.)
# query.setd("lonmax", 40.)
query["var"] = "B13011"
vars = volnd.read(self.db.query_data(query), (volnd.AnaIndex(), volnd.DateTimeIndex()), checkConflicts=False)
rconvert.volnd_save_to_r(vars, "/tmp/pippo")
def testFilter(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = dict(ana_id=1, var="B13011", rep_memo="synop")
query["datetime"] = datetime.datetime(2007, 1, 1, 0, 0, 0)
with warnings.catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
vars = read(tr.query_data(query),
(AnaIndex(), TimeRangeIndex()),
filter=lambda rec: rec["trange"] == (4, -21600, 0))
self.assertEqual(vars["B13011"].dims[1].index((4, -21600, 0)), 0)
def testFixedIndex(self):
with self.db.transaction() as tr:
# Ana in one dimension, network in the other
query = dict(ana_id=1, rep_memo="synop", year=2007, month=1, day=1)
vars = read(tr.query_data(query),
(AnaIndex(), TimeRangeIndex(frozen=True, start=(dballe.Trange(4, -21600, 0), (4, -43200, 0)))),
checkConflicts=False)
self.assertEqual(len(vars["B13011"].dims[1]), 2)
vars = read(tr.query_data(query), (AnaIndex(), TimeRangeIndex()), checkConflicts=False)
self.assertEqual(len(vars["B13011"].dims[1]), 3)
vars = read(tr.query_data(query),
(AnaIndex(), LevelIndex(frozen=True, start=(dballe.Level(1, None, None, None),))),
checkConflicts=False)
self.assertEqual(len(vars["B13011"].dims[1]), 1)
vars = read(tr.query_data(query), (AnaIndex(), LevelIndex()), checkConflicts=False)
self.assertEqual(len(vars["B13011"].dims[1]), 2)
def testAnaTrangeNetwork(self):
with self.db.transaction() as tr:
# 3 dimensions: ana, timerange, network
# 2 variables
query = dict(datetime=datetime.datetime(2007, 1, 1, 0, 0, 0))
vars = read(tr.query_data(query), (AnaIndex(), TimeRangeIndex(shared=False), NetworkIndex()))
self.assertEqual(len(vars), 2)
self.assertEqual(sorted(vars.keys()), ["B10004", "B13011"])
data = vars["B10004"]
self.assertEqual(data.name, "B10004")
self.assertEqual(len(data.attrs), 0)
self.assertEqual(len(data.dims), 3)
self.assertEqual(len(data.dims[0]), 12)
self.assertEqual(len(data.dims[1]), 1)
self.assertEqual(len(data.dims[2]), 2)
self.assertEqual(data.vals.size, 24)
self.assertEqual(data.vals.shape, (12, 1, 2))
self.assertEqual(sum(data.vals.mask.flat), 13)
self.assertEqual(round(ma.average(data.vals)), 83185)
self.assertEqual(data.dims[0][0], (1, 10., 15., None))
self.assertEqual(data.dims[0][1], (2, 10., 25., None))
self.assertEqual(data.dims[0][2], (3, 20., 15., None))
self.assertEqual(data.dims[0][3], (4, 20., 25., None))
self.assertEqual(data.dims[0][4], (5, 30., 15., None))
self.assertEqual(data.dims[0][5], (6, 30., 25., None))
self.assertEqual(data.dims[1][0], (0, None, None))
self.assertEqual(set(data.dims[2]), set(("temp", "synop")))
data = vars["B13011"]
self.assertEqual(data.name, "B13011")
self.assertEqual(len(data.attrs), 0)
self.assertEqual(len(data.dims), 3)
self.assertEqual(len(data.dims[0]), 12)
self.assertEqual(len(data.dims[1]), 2)
self.assertEqual(len(data.dims[2]), 2)
self.assertEqual(data.vals.size, 48)
self.assertEqual(data.vals.shape, (12, 2, 2))
self.assertEqual(sum(data.vals.mask.flat), 24)
self.assertAlmostEqual(ma.average(data.vals), 5.325, 6)
self.assertEqual(data.dims[0][0], (1, 10., 15., None))
self.assertEqual(data.dims[0][1], (2, 10., 25., None))
self.assertEqual(data.dims[0][2], (3, 20., 15., None))
self.assertEqual(data.dims[0][3], (4, 20., 25., None))
self.assertEqual(data.dims[0][4], (5, 30., 15., None))
self.assertEqual(data.dims[0][5], (6, 30., 25., None))
self.assertEqual(data.dims[1][0], (4, -43200, 0))
self.assertEqual(data.dims[1][1], (4, -21600, 0))
self.assertEqual(set(data.dims[2]), set(("temp", "synop")))
self.assertEqual(vars["B10004"].dims[0], vars["B13011"].dims[0])
self.assertNotEqual(vars["B10004"].dims[1], vars["B13011"].dims[1])
self.assertEqual(vars["B10004"].dims[2], vars["B13011"].dims[2])
def testExportSyncAna(self):
with self.db.transaction() as tr:
# Export some data
indexes = (AnaIndex(), DateTimeIndex())
query = {}
query["rep_memo"] = 'synop'
query["level"] = (1,)
query["trange"] = (4, -21600, 0)
vars = read(tr.query_data(query), indexes, checkConflicts=True)
self.assertEqual(sorted(vars.keys()), ["B13011"])
# Freeze all the indexes
for i in range(len(indexes)):
indexes[i].freeze()
# Export the pseudoana data in sync with the data
query.clear()
query["rep_memo"] = "synop"
anas = read(tr.query_station_data(query), (indexes[0],), checkConflicts=True)
self.assertEqual(sorted(anas.keys()), ["B01001", "B01002", "B01019"])
self.assertEqual(anas["B01001"].dims[0], vars["B13011"].dims[0])
def testGhostIndexes(self):
with self.db.transaction() as tr:
# If an index rejects a variable after another index
# has successfuly added an item, we used to end up with
# a 'ghost' index entry with no items in it
indexes = (TimeRangeIndex(), LevelIndex(frozen=True, start=(dballe.Level(3, 2, None, None),)))
query = {}
query['ana_id'] = 1
query['var'] = 'B13011'
vars = read(tr.query_data(query), indexes, checkConflicts=False)
self.assertCountEqual(vars.keys(), ["B13011"])
self.assertEqual(len(vars["B13011"].dims[1]), 1)
self.assertEqual(vars["B13011"].dims[0][0], (4, -21600, 0))
def test_volnd(self):
# Test from volnd
query = dballe.Record(datetime=datetime(2007, 1, 1, 0, 0, 0))
# query.set("var", "B10004")
# query.settimerange(dballe.TimeRange(0,0,0))
vars = volnd.read(
self.db.query_data(query),
(volnd.AnaIndex(), volnd.NetworkIndex(), volnd.LevelIndex(), volnd.TimeRangeIndex()),
)
# print "ana:", vars["B10004"].dims[0]
# print "net:", vars["B10004"].dims[1]
# print vars["B10004"]
# rpy.r.print_(rconvert.vnddata_to_r(vars['B10004']))
# rpy.r.assign('pippo', rconvert.vnddata_to_r(vars['B10004']))
# rpy.r.save('pippo', file='/tmp/pippo')
rconvert.volnd_save_to_r(vars, "/tmp/pippo")
def testEmptyExport(self):
with self.db.transaction() as tr:
query = {}
query["ana_id"] = 5000
vars = read(tr.query_data(query), (AnaIndex(), NetworkIndex()), attributes=True)
self.assertEqual(len(vars), 0)
