def testAnnualSeasonalAverage(self):
f = cdms2.open(self.filename, "r")
# Read in the raw data EXCLUDING a leap year
obs_timeseries1 = f('obs', time=slice(0, 48)) # 1900.1. to 1903.12.
# Read in the raw data INCLUDING a leap year
obs_timeseries2 = f('obs', time=slice(
0, 60)) # 1900.1. to 1904.12., 1904 is year lear
### Truncate first Jan, Feb and last Dec before get Annual cycle anomaly ... (to have fair DJF seasonal mean later)
obs_timeseries1 = obs_timeseries1[2:-1]
obs_timeseries2 = obs_timeseries2[2:-1]
### Set monthly time bounds ...
cdutil.setTimeBoundsMonthly(obs_timeseries1)
cdutil.setTimeBoundsMonthly(obs_timeseries2)
#### Removing Annual cycle ...
obs_timeseries_ano1 = cdutil.ANNUALCYCLE.departures(obs_timeseries1)
obs_timeseries_ano2 = cdutil.ANNUALCYCLE.departures(obs_timeseries2)
#### Calculate time average ...
obs_timeseries_ano_timeave1 = cdutil.averager(
obs_timeseries_ano1, axis='t') ## This should be zero and it does
obs_timeseries_ano_timeave2 = cdutil.averager(
obs_timeseries_ano2,
axis='t') ## This should be zero BUT it does NOT
#### SEASONAL MEAN TEST ####
obs_timeseries_ano1_DJF = cdutil.DJF(obs_timeseries_ano1,
criteriaarg=[0.95, None])
obs_timeseries_ano2_DJF = cdutil.DJF(obs_timeseries_ano2,
criteriaarg=[0.95, None])
obs_timeseries_ano1_JJA = cdutil.JJA(obs_timeseries_ano1,
criteriaarg=[0.95, None])
obs_timeseries_ano2_JJA = cdutil.JJA(obs_timeseries_ano2,
criteriaarg=[0.95, None])
#### Calculate time average ...
obs_timeseries_ano1_DJF_timeave = cdutil.averager(
obs_timeseries_ano1_DJF,
axis='t') ## This should be zero and it does
obs_timeseries_ano2_DJF_timeave = cdutil.averager(
obs_timeseries_ano2_DJF,
axis='t') ## This should be zero BUT it does NOT
obs_timeseries_ano1_JJA_timeave = cdutil.averager(
obs_timeseries_ano1_JJA,
axis='t') ## This should be zero and it does
obs_timeseries_ano2_JJA_timeave = cdutil.averager(
obs_timeseries_ano2_JJA,
axis='t') ## This should be zero and it does
numpy.testing.assert_almost_equal(obs_timeseries_ano_timeave2,
obs_timeseries_ano_timeave1, 10)
numpy.testing.assert_almost_equal(obs_timeseries_ano1_JJA_timeave,
obs_timeseries_ano2_JJA_timeave, 10)
numpy.testing.assert_almost_equal(obs_timeseries_ano1_DJF_timeave,
obs_timeseries_ano2_DJF_timeave, 10)
def cru_jja():
f = cdms.open(
"../DROUGHT_ATLAS/scPDSI.cru_ts3.26early.bams2018.GLOBAL.1901.2017.nc")
cru = f("scpdsi")
cru.getTime().units = 'days since 1900-1-1'
cdutil.setTimeBoundsMonthly(cru)
cdutil.setTimeBoundsMonthly(cru)
cru_jja = cdutil.JJA(cru)
cru_jja = MV.masked_where(np.abs(cru_jja) > 1000, cru_jja)
fgrid = cdms.open("OBS/gpcp.precip.mon.mean.nc")
gpcp_grid = fgrid("precip").getGrid()
fgrid.close()
cru2 = cru_jja.regrid(gpcp_grid, regridTool='regrid2')
cru2.id = "pdsi"
for att in cru.attributes.keys():
setattr(cru2, att, cru.attributes[att])
fw = cdms.open("../DROUGHT_ATLAS/OBSERVATIONS/CRU_selfcalibrated.nc", "w")
fw.write(cru2)
fw.close()
f.close()
return cru2
def dai_jja():
f = cdms.open("../DROUGHT_ATLAS/pdsi.mon.mean.selfcalibrated.nc")
dai = f("pdsi")
cdutil.setTimeBoundsMonthly(dai)
dai_jja = cdutil.JJA(dai)
fgrid = cdms.open("OBS/gpcp.precip.mon.mean.nc")
gpcp_grid = fgrid("precip").getGrid()
fgrid.close()
dai2 = dai_jja.regrid(gpcp_grid, regridTool='regrid2')
dai2.id = "pdsi"
for att in dai.attributes.keys():
setattr(dai2, att, dai.attributes[att])
fw = cdms.open("../DROUGHT_ATLAS/OBSERVATIONS/DAI_selfcalibrated.nc", "w")
fw.write(dai2)
fw.close()
return dai2
def testMissingSeason(self):
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(), 'clt.nc'))
s = f("clt")
cdutil.setTimeBoundsMonthly(s)
print('Getting JJA, which should be inexistant in data')
with self.assertRaises(Exception):
cdutil.JJA(s[:5])
## Create a year worth of data w/o JJA
s1 = s[:5]
s2 = s[8:12]
s3 = MV2.concatenate((s1, s2))
t = MV2.concatenate((s1.getTime()[:], s2.getTime()[:]))
t = cdms2.createAxis(t, id='time')
t.units = s.getTime().units
t.designateTime()
s3.setAxis(0, t)
cdutil.setTimeBoundsMonthly(s3)
with self.assertRaises(Exception):
cdutil.JJA(s3)
with self.assertRaises(Exception):
cdutil.JJA.departures(s3)
## Original Test (badly impleemnted was checking for this
## But now returns None
#with self.assertRaises(Exception):
self.assertIsNone(cdutil.JJA.climatology(s3))
# Now gets seasonal cycle, should have JJA all missing
print('Testing seasonal cycle on 1 year data w/o JJA should work')
a = cdutil.SEASONALCYCLE(s3)
self.assertEqual(a.shape, (4, 46, 72))
self.assertTrue(numpy.allclose(a.getTime(), [0., 3., 9., 12.]))
self.assertTrue(
numpy.allclose(
a.getTime().getBounds(),
numpy.array([[-1., 2.], [2., 5.], [8., 11.], [11., 14.]])))
self.assertEqual(a.shape, (4, 46, 72),
"Error returned data with wrong shape")
self.assertTrue(
numpy.equal(a.getTime()[:], [0., 3., 9., 12.]).all(),
"Error time are not valid")
self.assertTrue(
numpy.equal(a.getTime().getBounds()[:],
[[-1., 2.], [2., 5.], [8., 11.], [11., 14.]]).all(),
"Error bound time are not valid")
d = cdutil.SEASONALCYCLE.departures(s3)
c = cdutil.SEASONALCYCLE.climatology(s3)
## Create 2 year worth of data w/o JJA
s1 = s[:5]
s2 = s[8:17]
s3 = s[20:24]
s4 = MV2.concatenate((s1, s2))
s5 = MV2.concatenate((s4, s3))
t = MV2.concatenate((s1.getTime()[:], s2.getTime()[:]))
t2 = MV2.concatenate((t, s3.getTime()[:]))
t = cdms2.createAxis(t2, id='time')
t.units = s.getTime().units
t.designateTime()
s5.setAxis(0, t)
cdutil.setTimeBoundsMonthly(s5)
d = cdutil.SEASONALCYCLE.departures(s5)
c = cdutil.SEASONALCYCLE.climatology(s5)
with self.assertRaises(Exception):
cdutil.JJA(s5)
# Now gets seasonal cycle, should have JJA all missing
print('Testing seasonal cycle on 2 years data w/o JJA should work')
a = cdutil.SEASONALCYCLE(s5)
self.assertEqual(a.shape, (7, 46, 72),
"Error returned data with wrong shape")
## Create 2 years worth of data w/o 1st JJA
s1 = s[:5]
s2 = s[8:24]
s3 = MV2.concatenate((s1, s2))
t = MV2.concatenate((s1.getTime()[:], s2.getTime()[:]))
t = cdms2.createAxis(t, id='time')
t.units = s.getTime().units
t.designateTime()
s3.setAxis(0, t)
cdutil.setTimeBoundsMonthly(s3)
a = cdutil.JJA(s3)
self.assertIsNotNone(a, "data w/o 1st season did not return None")
# Now gets seasonal cycle, should have JJA all missing
print('Testing seasonal cycle on 2 years data w/o 1st JJA should work')
a = cdutil.SEASONALCYCLE(s3)
d = cdutil.SEASONALCYCLE.departures(s3)
c = cdutil.SEASONALCYCLE.climatology(s3)
self.assertEqual(a.shape, (8, 46, 72),
"Error returned data with wrong shape")
self.assertTrue(
numpy.equal(a.getTime()[:],
[0., 3., 9., 12., 15., 18., 21, 24]).all(),
"Error time are not valid")
self.assertTrue(
numpy.equal(
a.getTime().getBounds()[:],
[[-1., 2.], [2., 5.], [8., 11.], [11., 14.], [14., 17.],
[17., 20.], [20., 23.], [23., 26.]]).all(),
"Error bound time are not valid")
print(" Ok we test the filling part")
print(" this should add month '6' as all missing")
b = cdutil.times.insert_monthly_seasons(a, [
'JJA',
])
self.assertEqual(b.shape, (9, 46, 72),
"Error returned data with wrong shape")
self.assertTrue(
numpy.equal(b.getTime()[:],
[0., 3., 6, 9., 12., 15., 18., 21, 24]).all(),
"Error time are not valid")
self.assertTrue(
numpy.equal(
b.getTime().getBounds()[:],
[[-1., 2.], [2., 5.], [5, 8], [8., 11.], [11., 14.],
[14., 17.], [17., 20.], [20., 23.], [23., 26.]]).all(),
"Error bound time are not valid")
self.assertEqual(b[2].count(), 0,
"Error not all times missing in added spot")
# Now gets seasonal cycle, should have JJA all missing
print('Testing seasonal cycle on 2 years data w/o JJA should work')
a = cdutil.SEASONALCYCLE(s5)
self.assertEqual(a.shape, (7, 46, 72),
"Error returned data with wrong shape")
## Creates data with big gap in years
s1 = s[:15]
s2 = s[68:]
s3 = MV2.concatenate((s1, s2))
t = MV2.concatenate((s1.getTime()[:], s2.getTime()[:]))
t = cdms2.createAxis(t, id='time')
t.units = s.getTime().units
t.designateTime()
s3.setAxis(0, t)
cdutil.setTimeBoundsMonthly(s3)
a = cdutil.JJA(s3)
self.assertIsNotNone(a, "data with gap returned None")
# Now gets seasonal cycle, should have JJA all missing
print('Testing seasonal cycle on data with years of gap should work')
a = cdutil.SEASONALCYCLE(s3)
d = cdutil.SEASONALCYCLE.departures(s3)
c = cdutil.SEASONALCYCLE.climatology(s3)
self.assertEqual(s3.shape, (67, 46, 72))
self.assertEqual(a.shape, (24, 46, 72))
self.assertTrue(
numpy.equal(a.getTime(), [
0., 3., 6., 9., 12., 15., 69., 72., 75., 78., 81., 84., 87.,
90., 93., 96., 99., 102., 105., 108., 111., 114., 117., 120.
]).all())
print(" Ok we test the filling part")
print(" this should add month '6' as all missing")
b = cdutil.times.insert_monthly_seasons(
a, cdutil.times.SEASONALCYCLE.seasons)
self.assertEqual(b.shape, (41, 46, 72))
self.assertTrue(
numpy.equal(b.getTime()[:], [
0., 3., 6., 9., 12., 15., 18., 21., 24., 27., 30., 33., 36.,
39., 42., 45., 48., 51., 54., 57., 60., 63., 66., 69., 72.,
75., 78., 81., 84., 87., 90., 93., 96., 99., 102., 105., 108.,
111., 114., 117., 120.
]).all())
self.assertEqual(
cdutil.SEASONALCYCLE.departures(s3).shape, (24, 46, 72))
self.assertEqual(a.shape, (24, 46, 72))
self.assertEqual(
cdutil.SEASONALCYCLE.climatology(s3).shape, (4, 46, 72))
import cdms2, cdutil, sys, MV2, numpy, os
f = cdms2.open(
os.path.join(cdms2.__path__[0], '..', '..', '..', '..', 'sample_data',
'clt.nc'))
s = f("clt")
cdutil.setTimeBoundsMonthly(s)
print 'Getting JJA, which should be inexistant in data'
if cdutil.JJA(s[:5]) is not None:
raise RuntimeError, "data w/o season did not return None"
## Create a year worth of data w/o JJA
s1 = s[:5]
s2 = s[8:12]
s3 = MV2.concatenate((s1, s2))
t = MV2.concatenate((s1.getTime()[:], s2.getTime()[:]))
t = cdms2.createAxis(t, id='time')
t.units = s.getTime().units
t.designateTime()
s3.setAxis(0, t)
cdutil.setTimeBoundsMonthly(s3)
if cdutil.JJA(s3) is not None:
raise RuntimeError, "data w/o season did not return None"
if cdutil.JJA.departures(s3) is not None:
raise RuntimeError, "data w/o season did not return None for dep"
if cdutil.JJA.climatology(s3) is not None:
raise RuntimeError, "data w/o season did not return None for clim"
import cdms2,cdutil,sys,MV2,numpy,os,cdat_info
f=cdms2.open(os.path.join(cdat_info.get_sampledata_path(),'clt.nc'))
s=f("clt")
cdutil.setTimeBoundsMonthly(s)
print 'Getting JJA, which should be inexistant in data'
try:
cdutil.JJA(s[:5])
raise RuntimeError( "data w/o season did not fail")
except:
pass
## Create a year worth of data w/o JJA
s1 = s[:5]
s2 = s[8:12]
s3 = MV2.concatenate((s1,s2))
t = MV2.concatenate((s1.getTime()[:],s2.getTime()[:]))
t = cdms2.createAxis(t,id='time')
t.units=s.getTime().units
t.designateTime()
s3.setAxis(0,t)
cdutil.setTimeBoundsMonthly(s3)
try:
cdutil.JJA(s3)
raise RuntimeError, "data w/o season did not return None"
except:
pass