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