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#!/usr/bin/python
# -*- coding: UTF-8 -*-
import dballe
from volnd import *
import unittest, random, sys
from datetime import *
import numpy
import numpy.ma as ma
db = dballe.DB.connect_test()
class TestTddiv(unittest.TestCase):
# def tons(td):
# return td.days * 86400000000 + td.seconds * 1000000 + td.microseconds
def dtest(self, td1, td2):
self.assertEquals(tddivmod1(td1, td2), tddivmod2(td1, td2))
q, r = tddivmod1(td1, td2)
self.assertEquals(td2 * q + r, td1)
def testtddiv(self):
#self.assertEquals(tddivmod(timedelta(10, 0, 0), timedelta(2, 0, 0)), (5, timedelta(0)))
#self.assertEquals(tddivmod(timedelta(10, 0, 1), timedelta(2, 0, 0)), (5, timedelta(0, 0, 1)))
#self.assertEquals(tddivmod(timedelta(10, 0, 1), timedelta(3, 0, 0)), (3, timedelta(1, 0, 1)))
#self.assertEquals(tddivmod(timedelta(10, 6, 18), timedelta(5, 3, 9)), (2, timedelta(0)))
#self.assertEquals(tddivmod(timedelta(3, 4, 5), timedelta(1, 3, 10)), (2, timedelta(0, 86397, 999985)))
#self.assertEquals(tddivmod(timedelta(0, 4, 5), timedelta(0, 3, 10)), (1, timedelta(0, 0, 999995)))
#self.assertEquals(tddivmod(timedelta(2, 40, 10), timedelta(0, 0, 5)), (34568000002, timedelta(0)))
self.dtest(timedelta(10, 0, 0), timedelta(2, 0, 0))
self.dtest(timedelta(10, 0, 1), timedelta(2, 0, 0))
self.dtest(timedelta(10, 0, 1), timedelta(3, 0, 0))
self.dtest(timedelta(10, 6, 18), timedelta(5, 3, 9))
self.dtest(timedelta(3, 4, 5), timedelta(1, 3, 10))
self.dtest(timedelta(0, 4, 5), timedelta(0, 3, 10))
self.dtest(timedelta(2, 40, 10), timedelta(0, 0, 5))
# Re-enable when Debian bug #48872 has been fixed
#self.dtest(timedelta(999999999, 86399, 999999), timedelta(0, 0, 2))
random.seed(1)
for i in xrange(100):
td1 = timedelta(random.randint(0, 999999999), random.randint(0, 86400), random.randint(0, 1000000))
td2 = timedelta(random.randint(0, 999999999), random.randint(0, 86400), random.randint(0, 1000000))
self.dtest(td1, td2)
# Re-enable when Debian bug #48872 has been fixed
#for i in xrange(100):
# td1 = timedelta(random.randint(0, 999999999), random.randint(0, 86400), random.randint(0, 1000000))
# td2 = timedelta(0, random.randint(0, 86400), random.randint(0, 1000000))
# self.dtest(td1, td2)
#for i in xrange(100):
# td1 = timedelta(random.randint(0, 999999999), random.randint(0, 86400), random.randint(0, 1000000))
# td2 = timedelta(0, 0, random.randint(0, 1000000))
# self.dtest(td1, td2)
#for i in xrange(100):
# td1 = timedelta(0, random.randint(0, 86400), random.randint(0, 1000000))
# td2 = timedelta(0, 0, random.randint(0, 1000000))
# self.dtest(td1, td2)
class TestRead(unittest.TestCase):
def setUp(self):
# We want a predictable dataset
random.seed(1)
rattr = random.Random()
rattr.seed(1)
self.db = db
# Wipe the test database
self.db.reset()
attrs = dballe.Record()
rec = dballe.Record(mobile=0)
def contexts():
# 2 networks
for net in ('synop', 'temp'):
# 6 stations
for lat in (10., 20., 30.):
for lon in (15., 25.):
yield net, lat, lon
def dtrange(start, stop, delta):
while (start < stop):
yield start
start += delta
def everyxhours(x):
return dtrange(
datetime(2007, 1, 1, 0, 0, 0),
datetime(2007, 1, 7, 0, 0, 0),
timedelta(0, x*3600, 0))
def maybe_insert(rec, aname):
if random.random() <= 0.9:
#print repr(rec)
self.db.insert(rec, False, True)
attrs.clear()
attrs[aname] = rattr.random() * 100.
for code in rec:
self.db.attr_insert(code, attrs)
# Enter some sample data
for net, lat, lon in contexts():
rec["rep_memo"] = net
if net == 'synop':
aname = 'B33007'
else:
aname = 'B33040'
rec["lat"] = lat
rec["lon"] = lon
# 6 hours precipitations
rec["level"] = (1,)
rec["trange"] = (4, -21600, 0)
for dt in everyxhours(6):
rec["date"] = dt
rec["B13011"] = random.random()*10.
maybe_insert(rec, aname)
# 12 hours precipitations at different times
rec["level"] = (1,)
rec["trange"] = (4, -43200, 0)
for dt in everyxhours(12):
rec["date"] = dt
rec["B13011"] = random.random()*10.
maybe_insert(rec, aname)
# Randomly measured
# precipitations on a different
# (meaningless) level
# At slightly off times
rec["level"] = (3, 2)
rec["trange"] = (4, -21600, 0)
for dt in everyxhours(6):
rec["date"] = (dt + timedelta(0, random.randint(-600, 600)))
rec["B13011"] = random.random()*10.
maybe_insert(rec, aname)
del rec["B13011"]
# Pressures every 12 hours
rec["level"] = (1,)
rec["trange"] = (0,)
for dt in everyxhours(12):
rec["date"] = dt
rec["B10004"] = float(random.randint(70000, 105000))
maybe_insert(rec, aname)
del rec["B10004"]
# Insert some pseudoana data for the station 1, to test
# pseudoana export and mixed data types
rec.clear()
rec.update(ana_id=1, B01001=12, B01002=123, B01019="Test of long station name", rep_memo="synop")
rec.set_station_context()
self.db.insert(rec, False, True)
def tearDown(self):
#self.db.disconnect()
pass
def testIndexFind(self):
# Ana in one dimension, network in the other
query = dballe.Record(ana_id=1, var="B13011", rep_memo="synop")
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
vars = read(self.db.query_data(query), (AnaIndex(), TimeRangeIndex()))
self.assertEquals(vars["B13011"].dims[1].index((4, -21600, 0)), 1)
def testFilter(self):
# Ana in one dimension, network in the other
query = dballe.Record(ana_id=1, var="B13011", rep_memo="synop")
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
vars = read(self.db.query_data(query), \
(AnaIndex(), TimeRangeIndex()), \
filter=lambda rec: rec["timerange"] == (4, -21600, 0))
self.assertEquals(vars["B13011"].dims[1].index((4, -21600, 0)), 0)
def testUnsharedIndex(self):
# Ana in one dimension, network in the other
query = dballe.Record(ana_id=1, rep_memo="synop")
vars = read(self.db.query_data(query),
(AnaIndex(), TimeRangeIndex(), DateTimeIndex()))
self.assertEquals(len(vars["B13011"].dims[2]), len(vars["B10004"].dims[2]))
self.assertEquals(vars["B13011"].dims[2], vars["B10004"].dims[2])
vars = read(self.db.query_data(query),
(AnaIndex(), TimeRangeIndex(), DateTimeIndex(shared=False)))
self.assertNotEquals(len(vars["B13011"].dims[2]), len(vars["B10004"].dims[2]))
def testConflicts(self):
# Ana in one dimension, network in the other
query = dballe.Record(ana_id=1, var="B13011")
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
# Here conflicting values are overwritten
vars = read(self.db.query_data(query), (AnaIndex(), ), checkConflicts=False)
self.assertEquals(type(vars), dict)
# Here insted they should be detected
self.assertRaises(IndexError, read,
self.db.query_data(query),
(AnaIndex(),),
checkConflicts=True)
def testFixedIndex(self):
# Ana in one dimension, network in the other
query = dballe.Record(ana_id=1, rep_memo="synop", year=2007, month=1, day=1)
vars = read(self.db.query_data(query),
(AnaIndex(), TimeRangeIndex(frozen=True,
start=((4, -21600, 0), (4, -43200, 0)) ) ),
checkConflicts=False)
self.assertEquals(len(vars["B13011"].dims[1]), 2)
vars = read(self.db.query_data(query),
(AnaIndex(), TimeRangeIndex()),
checkConflicts=False)
self.assertEquals(len(vars["B13011"].dims[1]), 3)
vars = read(self.db.query_data(query),
(AnaIndex(), LevelIndex(frozen=True, start=((1, None, None, None),))),
checkConflicts=False)
self.assertEquals(len(vars["B13011"].dims[1]), 1)
vars = read(self.db.query_data(query),
(AnaIndex(), LevelIndex()),
checkConflicts=False)
self.assertEquals(len(vars["B13011"].dims[1]), 2)
def testAnaNetwork(self):
# Ana in one dimension, network in the other
query = dballe.Record()
query["var"] = "B10004"
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
vars = read(self.db.query_data(query), (AnaIndex(), NetworkIndex()))
self.assertEquals(len(vars), 1)
self.assertEquals(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEquals(data.name, "B10004")
self.assertEquals(len(data.attrs), 0)
self.assertEquals(len(data.dims), 2)
self.assertEquals(len(data.dims[0]), 6)
self.assertEquals(len(data.dims[1]), 2)
self.assertEquals(data.vals.size, 12)
self.assertEquals(data.vals.shape, (6, 2))
self.assertEquals(sum(data.vals.mask.flat), 1)
self.assertEquals(ma.average(data.vals), 86890)
self.assertEquals(data.dims[0][0], (1, 10., 15., None))
self.assertEquals(data.dims[0][1], (2, 10., 25., None))
self.assertEquals(data.dims[0][2], (3, 20., 15., None))
self.assertEquals(data.dims[0][3], (4, 20., 25., None))
self.assertEquals(data.dims[0][4], (5, 30., 15., None))
self.assertEquals(data.dims[0][5], (6, 30., 25., None))
self.assertEquals(set(data.dims[1]), set((("temp",), ("synop",))))
def testAnaTrangeNetwork(self):
# 3 dimensions: ana, timerange, network
# 2 variables
query = dballe.Record(date=datetime(2007, 1, 1, 0, 0, 0))
vars = read(self.db.query_data(query), (AnaIndex(), TimeRangeIndex(shared=False), NetworkIndex()))
self.assertEquals(len(vars), 2)
self.assertEquals(sorted(vars.keys()), ["B10004", "B13011"])
data = vars["B10004"]
self.assertEquals(data.name, "B10004")
self.assertEquals(len(data.attrs), 0)
self.assertEquals(len(data.dims), 3)
self.assertEquals(len(data.dims[0]), 6)
self.assertEquals(len(data.dims[1]), 1)
self.assertEquals(len(data.dims[2]), 2)
self.assertEquals(data.vals.size, 12)
self.assertEquals(data.vals.shape, (6, 1, 2))
self.assertEquals(sum(data.vals.mask.flat), 1)
self.assertEquals(ma.average(data.vals), 86890)
self.assertEquals(data.dims[0][0], (1, 10., 15., None))
self.assertEquals(data.dims[0][1], (2, 10., 25., None))
self.assertEquals(data.dims[0][2], (3, 20., 15., None))
self.assertEquals(data.dims[0][3], (4, 20., 25., None))
self.assertEquals(data.dims[0][4], (5, 30., 15., None))
self.assertEquals(data.dims[0][5], (6, 30., 25., None))
self.assertEquals(data.dims[1][0], (0, None, None))
self.assertEquals(set(data.dims[2]), set((("temp",), ("synop",))))
data = vars["B13011"]
self.assertEquals(data.name, "B13011")
self.assertEquals(len(data.attrs), 0)
self.assertEquals(len(data.dims), 3)
self.assertEquals(len(data.dims[0]), 6)
self.assertEquals(len(data.dims[1]), 2)
self.assertEquals(len(data.dims[2]), 2)
self.assertEquals(data.vals.size, 24)
self.assertEquals(data.vals.shape, (6, 2, 2))
self.assertEquals(sum(data.vals.mask.flat), 3)
self.assertAlmostEquals(ma.average(data.vals), 4.033333, 6)
self.assertEquals(data.dims[0][0], (1, 10., 15., None))
self.assertEquals(data.dims[0][1], (2, 10., 25., None))
self.assertEquals(data.dims[0][2], (3, 20., 15., None))
self.assertEquals(data.dims[0][3], (4, 20., 25., None))
self.assertEquals(data.dims[0][4], (5, 30., 15., None))
self.assertEquals(data.dims[0][5], (6, 30., 25., None))
self.assertEquals(data.dims[1][0], (4, -43200, 0))
self.assertEquals(data.dims[1][1], (4, -21600, 0))
self.assertEquals(set(data.dims[2]), set((("temp",), ("synop",))))
self.assertEquals(vars["B10004"].dims[0], vars["B13011"].dims[0])
self.assertNotEquals(vars["B10004"].dims[1], vars["B13011"].dims[1])
self.assertEquals(vars["B10004"].dims[2], vars["B13011"].dims[2])
def testAttrs(self):
# Same export as testAnaNetwork, but check that the
# attributes are synchronised
query = dballe.Record()
query["var"] = "B10004"
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
vars = read(self.db.query_data(query), (AnaIndex(), NetworkIndex()), attributes=True)
self.assertEquals(len(vars), 1)
self.assertEquals(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEquals(len(data.attrs), 2)
self.assertEquals(sorted(data.attrs.keys()), ['B33007', 'B33040'])
for net, a in ('synop', 'B33007'), ('temp', 'B33040'):
self.assertEquals(data.dims, data.attrs[a].dims)
self.assertEquals(data.vals.size, data.attrs[a].vals.size)
self.assertEquals(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[0] == net:
netidx = idx
break
self.assertNotEquals(netidx, -1)
# No attrs in the other network
self.assertEquals([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.assertEquals([x for x in data.vals.mask[:,netidx].flat], [x for x in data.attrs[a].vals.mask[:,netidx].flat])
self.assertEquals(ma.average(data.attrs['B33007'].vals), 53.5)
self.assertEquals(ma.average(data.attrs['B33040'].vals), 36.8)
def testSomeAttrs(self):
# Same export as testAnaNetwork, but check that the
# attributes are synchronised
query = dballe.Record()
query["var"] = "B10004"
query["date"] = datetime(2007, 1, 1, 0, 0, 0)
vars = read(self.db.query_data(query), (AnaIndex(), NetworkIndex()), attributes=('B33040',))
self.assertEquals(len(vars), 1)
self.assertEquals(vars.keys(), ["B10004"])
data = vars["B10004"]
self.assertEquals(len(data.attrs), 1)
self.assertEquals(data.attrs.keys(), ['B33040'])
a = data.attrs['B33040']
self.assertEquals(data.dims, a.dims)
self.assertEquals(data.vals.size, a.vals.size)
self.assertEquals(data.vals.shape, a.vals.shape)
# Find the temp index
netidx = -1
for idx, n in enumerate(data.dims[1]):
if n[0] == "temp":
netidx = idx
break
self.assertNotEquals(netidx, -1)
# Only compare the values on the temp index
self.assertEquals([x for x in a.vals.mask[:,1-netidx].flat], [True]*len(a.vals.mask[:,1-netidx].flat))
self.assertEquals([x for x in data.vals.mask[:,netidx].flat], [x for x in a.vals.mask[:,netidx].flat])
self.assertEquals(ma.average(a.vals), 36.8)
def testEmptyExport(self):
query = dballe.Record()
query["ana_id"] = 5000
vars = read(self.db.query_data(query), (AnaIndex(), NetworkIndex()), attributes=True)
self.assertEquals(len(vars), 0)
def testGhostIndexes(self):
# 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=((3, 2, None, None),) ))
query = dballe.Record()
query['ana_id'] = 1
query['var'] = 'B13011'
vars = read(self.db.query_data(query), indexes, \
checkConflicts=False)
self.assertEquals(vars.keys(), ["B13011"])
self.assertEquals(len(vars["B13011"].dims[1]), 1)
self.assertEquals(vars["B13011"].dims[0][0], (4, -21600, 0))
def testBuggyExport1(self):
indexes = (AnaIndex(),
LevelIndex(frozen=True, start=((1, None, None), (3, 2, None))),
TimeRangeIndex(),
DateTimeIndex())
query = dballe.Record()
query['rep_memo'] = 'synop'
vars = read(self.db.query_data(query), indexes,
checkConflicts=True, attributes=True)
def testExportAna(self):
indexes = (AnaIndex(),)
query = dballe.Record()
query.set_station_context()
query["rep_memo"] = "synop"
vars = read(self.db.query_data(query), indexes, checkConflicts=True)
self.assertEquals(sorted(vars.keys()), ["B01001", "B01002", "B01019"])
def testExportSyncAna(self):
# Export some data
indexes = (AnaIndex(), DateTimeIndex())
query = dballe.Record()
query["rep_memo"] = 'synop'
query["level"] = (1,)
query["trange"] = (4, -21600, 0)
vars = read(self.db.query_data(query), indexes, checkConflicts=True)
self.assertEquals(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.set_station_context()
query["rep_memo"] = "synop"
anas = read(self.db.query_data(query), (indexes[0],), checkConflicts=True)
self.assertEquals(sorted(anas.keys()), ["B01001", "B01002", "B01019"])
self.assertEquals(anas["B01001"].dims[0], vars["B13011"].dims[0])
if __name__ == "__main__":
db.connect_test();
unittest.main()
# This is already automatically done
#if len(sys.argv) == 1:
# unittest.main()
#else:
# suite = unittest.TestLoader().loadTestsFromNames(
# map(lambda x: __name__ + '.' + x, sys.argv[1:]))
# unittest.TextTestRunner().run(suite)
#query = dballe.Record()
##query.set("var", "B12001")
##vars = readv7d(db.query(query), (AnaIndex,NetworkIndex))
##vars = readv7d(db.query(query), (AnaIndex,LevelIndex))
##vars = read(db.query(query), (AnaIndex(),DateTimeIndex()))
#
#query.set("rep_memo", "temp")
#vars = read(db.query(query), (AnaIndex(),IntervalIndex(datetime(2007,01,11,11,24), timedelta(0, 120), timedelta(0, 60))))
#
#print vars
##print vars['B12001'].dims[0][:20]
##print vars['B12001'].dims[1][:20]
#
##print "Lat:", res[0][:10]
##print "Lon:", res[1][:10]
##print "Id :", res[2][:10]
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