def setUp(self):
# Create test dataset
f = Dataset('./testnc_methods.nc', 'w')
f.setncattr('test', 'Created for SemSL tests')
dim1 = f.createDimension('T', DIMSIZE)
dim1d = f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = f.createDimension('Z', DIMSIZE)
dim2d = f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = f.createDimension('Y', DIMSIZE)
dim3d = f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = f.createDimension('X', DIMSIZE)
dim4d = f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
var = f.createVariable(VARNAME,
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
#print('IN TEST: {}'.format(self.var._cfa_file))
#print('IN TEST: {}'.format(type(self.var)))
#print('INTEST: {}'.format(self.var.setncattr))
np.random.seed(0)
var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
var.setncattr('units', 'test unit')
f.close()
f = Dataset('./testnc_methods.nc', 'r')
var = f.variables['var']
atr = var.getncattr('units')
assert atr == 'test unit'
f.close()
f = Dataset('./testnc_methods/testnc_methods_var_[0].nc', 'r')
#print('IN SETUP TEST SET3 {}'.format(f.variables['var']))
atr = f.variables['var'].getncattr('units')
assert atr == 'test unit'
#print(self.f.variables['var'])
f.close()
def test_multicfavar(self):
# Create test dataset
f = Dataset('./testnc_multivar.nc', 'w')
f.setncattr('test', 'Created for SemSL tests')
dim1 = f.createDimension('T', DIMSIZE)
dim1d = f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = f.createDimension('Z', DIMSIZE)
dim2d = f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = f.createDimension('Y', DIMSIZE)
dim3d = f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = f.createDimension('X', DIMSIZE)
dim4d = f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
np.random.seed(0)
var = f.createVariable('var',
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
var.setncattr('units', 'test unit')
var2 = f.createVariable('var2',
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
var2[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
var2.setncattr('units', 'test unit')
f.close()
# Now remove the files
os.remove('./testnc_multivar.nc')
subfiles = glob('./testnc_multivar/*.nc')
# print('IN TEARDOWN {}'.format(subfiles))
for f in subfiles:
os.remove(f)
os.rmdir('./testnc_multivar')
self.assertFalse(os.path.exists('./testnc_multivar/'))
def test_getncattr(self):
f = Dataset('./testnc_methods.nc', 'a')
f.setncattr('rootgroupattr', 'val')
g = f.createGroup('testgroup')
g.setncattr('testattr','val')
v = g.createVariable('var', 'f8',('T','Y','X'))
v.setncattr('varattr','val')
v[:] = np.zeros((20,20,20))
f.close()
f = Dataset('./testnc_methods.nc', 'r')
g = f.groups['testgroup']
self.assertEqual(g.getncattr('testattr'),'val')
f.close()
f = Dataset('./testnc_methods/testnc_methods_testgroup_var_[0].nc', 'r')
g = f.groups['testgroup']
v = g.variables['var']
#self.assertEqual(v.getncattr('varattr'),'val')
self.assertEqual(g.getncattr('testattr'),'val')
#self.assertEqual(f.getncattr('rootgroupattr'),'val')
f.close()
def setUp(self):
# Create test dataset
f = Dataset('./testnc_group.nc', 'w', format='NETCDF4')
f.setncattr('test', 'Created for SemSL tests')
dim1 = f.createDimension('T', DIMSIZE)
dim1d = f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = f.createDimension('Z', DIMSIZE)
dim2d = f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = f.createDimension('Y', DIMSIZE)
dim3d = f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = f.createDimension('X', DIMSIZE)
dim4d = f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
f.close()
class test_set1_variables(unittest.TestCase):
def test_multicfavar(self):
# Create test dataset
f = Dataset('./testnc_multivar.nc', 'w')
f.setncattr('test', 'Created for SemSL tests')
dim1 = f.createDimension('T', DIMSIZE)
dim1d = f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = f.createDimension('Z', DIMSIZE)
dim2d = f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = f.createDimension('Y', DIMSIZE)
dim3d = f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = f.createDimension('X', DIMSIZE)
dim4d = f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
np.random.seed(0)
var = f.createVariable('var',
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
var.setncattr('units', 'test unit')
var2 = f.createVariable('var2',
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
var2[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
var2.setncattr('units', 'test unit')
f.close()
# Now remove the files
os.remove('./testnc_multivar.nc')
subfiles = glob('./testnc_multivar/*.nc')
# print('IN TEARDOWN {}'.format(subfiles))
for f in subfiles:
os.remove(f)
os.rmdir('./testnc_multivar')
self.assertFalse(os.path.exists('./testnc_multivar/'))
def test_changearrayvalues(self):
# create file in backend
self.f = Dataset('s3://test/databucket/testnc_varchange.nc', 'w')
self.f.setncattr('test', 'Created for SemSL tests')
dim1 = self.f.createDimension('T', DIMSIZE)
dim1d = self.f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = self.f.createDimension('Z', DIMSIZE)
dim2d = self.f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = self.f.createDimension('Y', DIMSIZE)
dim3d = self.f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = self.f.createDimension('X', DIMSIZE)
dim4d = self.f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
self.var = self.f.createVariable('var',
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
self.var.setncattr('units', 'test unit')
self.var[:] = np.zeros((DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE))
self.f.close()
# remove the files in cache
sl_cache = slCacheManager()
sl_cache._clear_cache()
# Now reopen
f = Dataset('s3://test/databucket/testnc_varchange.nc', 'a')
var = f.variables['var']
self.assertEqual(var[0, 0, 0, 0], 0)
var[0, 0, 0, :] = np.ones((1, 1, 1, DIMSIZE))
self.assertEqual(var[0, 0, 0, 0], 1)
f.close()
# remove the files in cache
sl_cache = slCacheManager()
sl_cache._clear_cache()
# now reopen again and check the change
f = Dataset('s3://test/databucket/testnc_varchange.nc', 'r')
var = f.variables['var']
self.assertEqual(var[0, 0, 0, 0], 1)
f.close()
# cleanup
sl_config = slConfig()
slDB = slCacheDB()
conn_man = slConnectionManager(sl_config)
conn = conn_man.open("s3://test")
sl_cache = slCacheManager()
sl_cache._clear_cache()
s3 = conn.get()
subfiles = s3.list_objects(Bucket='databucket',
Prefix='testnc_varchange/')['Contents']
for sf in subfiles:
s3.delete_object(Bucket='databucket', Key=sf['Key'])
s3.delete_object(Bucket='databucket', Key='testnc_varchange.nc')
s3.delete_bucket(Bucket='databucket')
class test_set4_Methods_s3_noncfa(unittest.TestCase):
def setUp(self):
# Create test dataset
self.f = Dataset('s3://test/databucket/testnc_methods.nc',
'w',
format='NETCDF4')
self.f.setncattr('test', 'Created for SemSL tests')
dim1 = self.f.createDimension('T', DIMSIZE)
dim1d = self.f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = self.f.createDimension('Z', DIMSIZE)
dim2d = self.f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = self.f.createDimension('Y', DIMSIZE)
dim3d = self.f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = self.f.createDimension('X', DIMSIZE)
dim4d = self.f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
self.var = self.f.createVariable(VARNAME,
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
self.var.units = 'test unit'
np.random.seed(0)
self.var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
self.f.close()
def tearDown(self):
# remove test file
sl_cache = slCacheManager()
sl_config = slConfig()
slDB = slCacheDB()
cache_loc = sl_config['cache']['location']
conn_man = slConnectionManager(sl_config)
conn = conn_man.open("s3://test")
sl_cache._clear_cache()
s3 = conn.get()
s3.delete_object(Bucket='databucket', Key='testnc_methods.nc')
s3.delete_bucket(Bucket='databucket')
def test_var_ncattrs(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
attrs = v.ncattrs()
self.assertEqual(attrs, ['units'])
f.close()
def test_var_setncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr('newtest', 'newtestvalue')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_setncattr_string(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr_string('newtest', 'newtestvalue')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_setncatts(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncatts({'newtest': 'newtestvalue', 'secondnew': 'secondnewval'})
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
self.assertEqual(v.getncattr('secondnew'), 'secondnewval')
f.close()
def test_var_getncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertEqual(v.getncattr('units'), 'test unit')
f.close()
def test_var_delncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.delncattr('units')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
test_bool = False
try:
units = v.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
f.close()
def test_get_var_chunk_cache(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.get_var_chunk_cache(), (1048576, 521, 0.75))
f.close()
def test_set_var_chunk_cache(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.set_var_chunk_cache(size=10485760)
self.assertEqual(v.get_var_chunk_cache(), (10485760, 521, 0.75))
f.close()
def test_var_renameAttribute(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.renameAttribute('units', 'renamedattr')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
test_bool = False
try:
attr = f.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
self.assertEqual(v.getncattr('renamedattr'), 'test unit')
f.close()
def test_var_set_auto_chartostring(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].chartostring)
v.set_auto_chartostring(False)
self.assertFalse(f.variables['var'].chartostring)
f.close()
def test_var_set_auto_mask(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].mask)
v.set_auto_mask(False)
self.assertFalse(f.variables['var'].mask)
f.close()
def test_var_set_auto_maskandscale(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].mask)
self.assertTrue(f.variables['var'].scale)
v.set_auto_maskandscale(False)
self.assertFalse(f.variables['var'].mask)
self.assertFalse(f.variables['var'].scale)
f.close()
def test_var_set_auto_scale(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].scale)
v.set_auto_scale(False)
self.assertFalse(f.variables['var'].scale)
f.close()
class test_set5_Methods_s3_cfa(unittest.TestCase):
def setUp(self):
# Create test dataset
self.f = Dataset('s3://test/databucket/testnc_methods.nc', 'w')
self.f.setncattr('test', 'Created for SemSL tests')
dim1 = self.f.createDimension('T', DIMSIZE)
dim1d = self.f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = self.f.createDimension('Z', DIMSIZE)
dim2d = self.f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = self.f.createDimension('Y', DIMSIZE)
dim3d = self.f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = self.f.createDimension('X', DIMSIZE)
dim4d = self.f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
self.var = self.f.createVariable(VARNAME,
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
self.var.setncattr('units', 'test unit')
np.random.seed(0)
self.var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
self.f.close()
def tearDown(self):
# remove test file
sl_cache = slCacheManager()
sl_config = slConfig()
slDB = slCacheDB()
cache_loc = sl_config['cache']['location']
conn_man = slConnectionManager(sl_config)
conn = conn_man.open("s3://test")
# construct list of subfiles
subfiles = glob('{}/testnc_methods/*.nc'.format(cache_loc))
subfiles = [
'testnc_methods/' + file.split('/')[-1] for file in subfiles
]
sl_cache._clear_cache()
s3 = conn.get()
s3.delete_object(Bucket='databucket', Key='testnc_methods.nc')
for file in subfiles:
#print(file)
s3.delete_object(Bucket='databucket', Key=file)
s3.delete_bucket(Bucket='databucket')
def test_var_setncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr('newtest', 'newtestvalue')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_ncattrs(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
attrs = v.ncattrs()
self.assertEqual(attrs,
['cf_role', 'cf_dimensions', 'cfa_array', 'units'])
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
attrs = v.ncattrs()
self.assertEqual(attrs,
['cf_role', 'cf_dimensions', 'cfa_array', 'units'])
f.close()
def test_var_setncattr_string(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr_string('newtest', 'newtestvalue')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_setncatts(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.setncatts({'newtest': 'newtestvalue', 'secondnew': 'secondnewval'})
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
self.assertEqual(v.getncattr('secondnew'), 'secondnewval')
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
self.assertEqual(v.getncattr('secondnew'), 'secondnewval')
f.close()
def test_var_getncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
self.assertEqual(v.getncattr('units'), 'test unit')
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
self.assertEqual(v.getncattr('units'), 'test unit')
f.close()
def test_var_delncattr(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.delncattr('units')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
test_bool = False
try:
units = v.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
test_bool = False
try:
units = v.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
f.close()
def test_get_var_chunk_cache(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.get_var_chunk_cache(), (1048576, 521, 0.75))
f.close()
def test_set_var_chunk_cache(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.set_var_chunk_cache(size=10485760)
self.assertEqual(v.get_var_chunk_cache(), (10485760, 521, 0.75))
f.close()
def test_var_renameAttribute(self):
f = Dataset('s3://test/databucket/testnc_methods.nc', 'a')
v = f.variables['var']
v.renameAttribute('units', 'renamedattr')
f.close()
f = Dataset('s3://test/databucket/testnc_methods.nc', 'r')
v = f.variables['var']
test_bool = False
try:
attr = f.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
self.assertEqual(v.getncattr('renamedattr'), 'test unit')
f.close()
# now check a subfile...
f = Dataset(
's3://test/databucket/testnc_methods/testnc_methods_var_[0].nc',
'r')
v = f.variables['var']
test_bool = False
try:
attr = f.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
self.assertEqual(v.getncattr('renamedattr'), 'test unit')
f.close()
class test_set2_Methods_posix_noncfa(unittest.TestCase):
def setUp(self):
# Create test dataset
self.f = Dataset('./testnc_methods.nc', 'w', format='NETCDF4')
self.f.setncattr('test', 'Created for SemSL tests')
dim1 = self.f.createDimension('T', DIMSIZE)
dim1d = self.f.createVariable('T', 'i4', ('T', ))
dim1d[:] = range(DIMSIZE)
dim2 = self.f.createDimension('Z', DIMSIZE)
dim2d = self.f.createVariable('Z', 'i4', ('Z', ))
dim2d[:] = range(DIMSIZE)
dim3 = self.f.createDimension('Y', DIMSIZE)
dim3d = self.f.createVariable('Y', 'i4', ('Y', ))
dim3d[:] = range(DIMSIZE)
dim4 = self.f.createDimension('X', DIMSIZE)
dim4d = self.f.createVariable('X', 'i4', ('X', ))
dim4d[:] = range(DIMSIZE)
dim1d.axis = "T"
dim2d.axis = "Z"
dim3d.axis = "Y"
dim4d.axis = "X"
self.var = self.f.createVariable(VARNAME,
'f8', ('T', 'Z', 'Y', 'X'),
contiguous=True)
self.var.units = 'test unit'
np.random.seed(0)
self.var[:] = np.random.rand(DIMSIZE, DIMSIZE, DIMSIZE, DIMSIZE)
self.f.close()
def tearDown(self):
# remove test file
os.remove('./testnc_methods.nc')
def test_var_ncattrs(self):
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
attrs = v.ncattrs()
self.assertEqual(attrs, ['units'])
f.close()
def test_var_setncattr(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr('newtest', 'newtestvalue')
f.close()
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_setncattr_string(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.setncattr_string('newtest', 'newtestvalue')
f.close()
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
f.close()
def test_var_setncatts(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.setncatts({'newtest': 'newtestvalue', 'secondnew': 'secondnewval'})
f.close()
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.getncattr('newtest'), 'newtestvalue')
self.assertEqual(v.getncattr('secondnew'), 'secondnewval')
f.close()
def test_var_getncattr(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
self.assertEqual(v.getncattr('units'), 'test unit')
f.close()
def test_var_delncattr(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.delncattr('units')
f.close()
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
test_bool = False
try:
units = v.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
f.close()
def test_get_var_chunk_cache(self):
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
self.assertEqual(v.get_var_chunk_cache(), (1048576, 521, 0.75))
f.close()
def test_set_var_chunk_cache(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.set_var_chunk_cache(size=10485760)
self.assertEqual(v.get_var_chunk_cache(), (10485760, 521, 0.75))
f.close()
def test_var_renameAttribute(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
v.renameAttribute('units', 'renamedattr')
f.close()
f = Dataset('./testnc_methods.nc', 'r')
v = f.variables['var']
test_bool = False
try:
attr = f.getncattr('units')
except AttributeError:
test_bool = True
self.assertTrue(test_bool)
self.assertEqual(v.getncattr('renamedattr'), 'test unit')
f.close()
def test_var_set_auto_chartostring(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].chartostring)
v.set_auto_chartostring(False)
self.assertFalse(f.variables['var'].chartostring)
f.close()
def test_var_set_auto_mask(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].mask)
v.set_auto_mask(False)
self.assertFalse(f.variables['var'].mask)
f.close()
def test_var_set_auto_maskandscale(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].mask)
self.assertTrue(f.variables['var'].scale)
v.set_auto_maskandscale(False)
self.assertFalse(f.variables['var'].mask)
self.assertFalse(f.variables['var'].scale)
f.close()
def test_var_set_auto_scale(self):
f = Dataset('./testnc_methods.nc', 'a')
v = f.variables['var']
self.assertTrue(f.variables['var'].scale)
v.set_auto_scale(False)
self.assertFalse(f.variables['var'].scale)
f.close()
