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tst_multifile2.py
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tst_multifile2.py
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from netCDF4 import Dataset, MFDataset, MFTime, num2date, date2num, date2index
import numpy as np
from numpy.random import seed, randint
from numpy.testing import assert_array_equal, assert_equal
from numpy import ma
import tempfile, unittest, os, datetime
nx=100; ydim=5; zdim=1
nfiles = 10
ninc = nx/nfiles
files = [tempfile.mktemp(".nc") for nfile in range(nfiles)]
data = randint(0,10,size=(nx,ydim,zdim))
missval = 99
data[::10] = missval
data = ma.masked_values(data,missval)
class VariablesTestCase(unittest.TestCase):
def setUp(self):
self.files = files
for nfile,file in enumerate(self.files):
f = Dataset(file,'w',format='NETCDF4_CLASSIC')
#f.createDimension('x',None)
f.createDimension('x',ninc)
f.createDimension('y',ydim)
f.createDimension('z',zdim)
f.history = 'created today'
x = f.createVariable('x','i',('x',))
x.units = 'zlotys'
dat = f.createVariable('data','i',('x','y','z',))
dat.long_name = 'phony data'
dat.missing_value = missval
nx1 = nfile*ninc; nx2 = ninc*(nfile+1)
#x[0:ninc] = np.arange(nfile*ninc,ninc*(nfile+1))
x[:] = np.arange(nfile*ninc,ninc*(nfile+1))
#dat[0:ninc] = data[nx1:nx2]
dat[:] = data[nx1:nx2]
f.close()
def tearDown(self):
# Remove the temporary files
for file in self.files:
os.remove(file)
def runTest(self):
"""testing multi-file dataset access"""
# specify the aggregation dim (not necessarily unlimited)
f = MFDataset(self.files,aggdim='x',check=True)
assert f.history == 'created today'
assert_array_equal(np.arange(0,nx),f.variables['x'][:])
varin = f.variables['data']
datin = varin[:]
assert_array_equal(datin.mask,data.mask)
varin.set_auto_maskandscale(False)
data2 = data.filled()
assert varin.long_name == 'phony data'
assert len(varin) == nx
assert varin.shape == (nx,ydim,zdim)
assert varin.dimensions == ('x','y','z')
assert_array_equal(varin[4:-4:4,3:5,2:8],data2[4:-4:4,3:5,2:8])
assert varin[0,0,0] == data2[0,0,0]
assert_array_equal(varin[:],data2)
assert getattr(varin,'nonexistantatt',None) == None
f.close()
class NonuniformTimeTestCase(unittest.TestCase):
ninc = 365
def setUp(self):
self.files = [tempfile.mktemp(".nc") for nfile in range(2)]
for nfile,file in enumerate(self.files):
f = Dataset(file,'w',format='NETCDF4_CLASSIC')
f.createDimension('time',None)
f.createDimension('y',ydim)
f.createDimension('z',zdim)
f.history = 'created today'
time = f.createVariable('time', 'f', ('time', ))
#time.units = 'days since {0}-01-01'.format(1979+nfile)
yr = 1979+nfile
time.units = 'days since %s-01-01' % yr
time.calendar = 'standard'
x = f.createVariable('x','f',('time', 'y', 'z'))
x.units = 'potatoes per square mile'
nx1 = self.ninc*nfile;
nx2 = self.ninc*(nfile+1)
time[:] = np.arange(self.ninc)
x[:] = np.arange(nx1, nx2).reshape(self.ninc,1,1) * np.ones((1, ydim, zdim))
f.close()
def tearDown(self):
# Remove the temporary files
for file in self.files:
os.remove(file)
def runTest(self):
# Get the real dates
dates = []
for file in self.files:
f = Dataset(file)
t = f.variables['time']
dates.extend(num2date(t[:], t.units, t.calendar))
f.close()
# Compare with the MF dates
f = MFDataset(self.files,check=True)
t = f.variables['time']
mfdates = num2date(t[:], t.units, t.calendar)
T = MFTime(t)
assert_equal(len(T), len(t))
assert_equal(T.shape, t.shape)
assert_equal(T.dimensions, t.dimensions)
assert_equal(T.typecode(), t.typecode())
assert_array_equal(num2date(T[:], T.units, T.calendar), dates)
assert_equal(date2index(datetime.datetime(1980, 1, 2), T), 366)
f.close()
if __name__ == '__main__':
unittest.main()