def test_returnArray(foo_nc):
nco = Nco(cdfMod='netcdf4')
random1 = nco.ncea(input=foo_nc, output="tmp.nc", returnCdf=True, options=['-O']).variables['random'][:]
assert type(random1) == np.ndarray
random2 = nco.ncea(input=foo_nc, output="tmp.nc",returnArray='random' ,options=['-O'])
assert type(random2) == np.ndarray
np.testing.assert_equal(random1, random2)
def test_return_array(foo_nc):
nco = Nco(cdf_module="netcdf4")
random1 = nco.ncea(
input=foo_nc, output="tmp.nc", returnCdf=True, options=["-O"]
).variables["random"][:]
assert isinstance(random1, np.ndarray)
random2 = nco.ncea(
input=foo_nc, output="tmp.nc", returnArray="random", options=["-O"]
)
assert isinstance(random2, np.ndarray)
np.testing.assert_equal(random1, random2)
def test_return_cdf(foo_nc):
nco = Nco(cdf_module="scipy")
test_cdf = nco.ncea(input=foo_nc, output="tmp.nc", returnCdf=True, options=["-O"])
assert type(test_cdf) == scipy.io.netcdf.netcdf_file
expected_vars = ["time", "random"]
for var in expected_vars:
assert var in list(test_cdf.variables.keys())
nco = Nco(cdf_module="netcdf4")
test_cdf = nco.ncea(input=foo_nc, output="tmp.nc", returnCdf=True, options=["-O"])
assert type(test_cdf) == netCDF4.Dataset
for var in expected_vars:
assert var in list(test_cdf.variables.keys())
def test_returnCdf(foo_nc):
nco = Nco(cdfMod='scipy')
testCdf = nco.ncea(input=foo_nc, output="tmp.nc", returnCdf=True,options=['-O'])
assert type(testCdf) == scipy.io.netcdf.netcdf_file
expected_vars = ['time', 'random']
for var in expected_vars:
assert var in list(testCdf.variables.keys())
nco = Nco(cdfMod='netcdf4')
testCdf = nco.ncea(input=foo_nc, output="tmp.nc", returnCdf=True, options=['-O'])
assert type(testCdf) == netCDF4.Dataset
for var in expected_vars:
assert var in list(testCdf.variables.keys())
def test_returnArray(foo_nc):
nco = Nco(cdfMod='netcdf4')
random1 = nco.ncea(input=foo_nc,
output="tmp.nc",
returnCdf=True,
options=['-O']).variables['random'][:]
assert type(random1) == np.ndarray
random2 = nco.ncea(input=foo_nc,
output="tmp.nc",
returnArray='random',
options=['-O'])
assert type(random2) == np.ndarray
np.testing.assert_equal(random1, random2)
def test_returnMaArray(bar_mask_nc, random_masked_field):
nco = Nco()
field = nco.ncea(input=bar_mask_nc,
output="tmp.nc",
returnMaArray='random',
options=['-O'])
assert type(field) == np.ma.core.MaskedArray
def test_returnCdf(foo_nc):
nco = Nco(cdfMod='scipy')
testCdf = nco.ncea(input=foo_nc,
output="tmp.nc",
returnCdf=True,
options=['-O'])
assert type(testCdf) == scipy.io.netcdf.netcdf_file
expected_vars = ['time', 'random']
for var in expected_vars:
assert var in list(testCdf.variables.keys())
nco = Nco(cdfMod='netcdf4')
testCdf = nco.ncea(input=foo_nc,
output="tmp.nc",
returnCdf=True,
options=['-O'])
assert type(testCdf) == netCDF4.Dataset
for var in expected_vars:
assert var in list(testCdf.variables.keys())
def test_return_ma_array(bar_mask_nc, random_masked_field):
nco = Nco()
field = nco.ncea(
input=bar_mask_nc, output="tmp.nc", returnMaArray="random", options=["-O"]
)
assert type(field) == np.ma.core.MaskedArray
def test_ncea_mult_files(foo_nc, bar_nc):
nco = Nco(debug=True)
infiles = [foo_nc, bar_nc]
nco.ncea(input=infiles, output="out.nc")
def test_returnMaArray(bar_mask_nc, random_masked_field):
nco = Nco()
field = nco.ncea(input=bar_mask_nc, returnMaArray='random')
assert type(field) == np.ma.core.MaskedArray
