def test_attrs(self):
result = cdl(ov('x', dd=[od('p'), od('q')],
aa=[oa('n1', _long(3)), oa('r1', 1.24)],
data=np.array(1.0)))
self.assertEqual(result,
'double x(p, q) ;\n'
' x:n1 = 3L ;\n'
' x:r1 = 1.24 ;')
def test_inner_groups(self):
g = og('group_name', gg=[og('sub_group')])
result = cdl(g)
self.assertEqual(result,
'netcdf group_name {\n'
'\n'
'group: sub_group {\n'
'} // group sub_group\n'
'}')
def test_attr(self):
g = og('group_name', aa=[oa('x', _long(2))])
result = cdl(g)
self.assertEqual(result,
'netcdf group_name {\n'
'\n'
'// global attributes:\n'
' :x = 2L ;\n'
'}')
def test_dim(self):
g = og('group_name', dd=[od('x', 2)])
result = cdl(g)
self.assertEqual(result,
'netcdf group_name {\n'
'\n'
'dimensions:\n'
' x = 2 ;\n'
'}')
def test_var(self):
g = og('group_name', vv=[ov('x', data=np.array(1.0))])
result = cdl(g)
self.assertEqual(result,
'netcdf group_name {\n'
'\n'
'variables:\n'
' double x ;\n'
'}')
def test_attrs(self):
def _write_testdata(ds):
# Create a simple x2 dimension for array testing.
ds.createDimension('pair', 2)
# Create variables + attributes of all netcdf basic types.
for np_type, type_name in \
ncdl._DTYPES_TYPE_NAMES.iteritems():
if type_name == 'char':
scalar = 'A'
array = 'String_data'
# N.B. Wrapping this with np.array() has no effect.
else:
scalar = np.array(1.25, dtype=np_type)
array = np.array([1.25, 13.25], dtype=np_type)
attr_name = 'scalar_attr_' + type_name
ds.setncattr(attr_name, scalar)
attr_name = 'vector_attr_' + type_name
ds.setncattr(attr_name, array)
var_name = 'scalar_var_' + type_name
var = ds.createVariable(varname=var_name,
datatype=np_type)
var[:] = scalar
var_name = 'array_var_' + type_name
var = ds.createVariable(varname=var_name,
datatype=np_type,
dimensions=('pair',))
var[:] = array
testfile_name = 'alltypes.nc'
temp_dirpath = tempfile.mkdtemp()
try:
file_path = os.path.join(temp_dirpath, testfile_name)
with nc4.Dataset(file_path, 'w') as ds:
_write_testdata(ds)
ncdump_output = subprocess.check_output(
'ncdump -h ' + file_path, shell=True)
with nc4.Dataset(file_path, 'r') as ds:
read_data = ncf.read(ds)
read_data.rename('alltypes')
cdl_results = cdl(read_data)
expected = sort_lines(strip_lines(ncdump_output))
found = sort_lines(strip_lines(cdl_results))
self.assertEqual(found, expected)
finally:
shutil.rmtree(temp_dirpath)
def test_inner_group_attr(self):
g = og('group_name',
gg=[og('sub_group',
aa=[oa('x', _long(2))])])
result = cdl(g)
self.assertEqual(result,
'netcdf group_name {\n'
'\n'
'group: sub_group {\n'
'\n'
'// group attributes:\n'
' :x = 2L ;\n'
'} // group sub_group\n'
'}')
def check_file_cdl(file_path):
# Load from the given file
with netCDF4.Dataset(file_path) as ds:
g = ncds.read(ds)
# Re-save to a temporary file, to get an ncdump output in known order.
ncds.write('temp.nc', g)
# Rename so name matches temporary file name as seen by ncdump.
g.rename('temp')
# Generate cdl.
g_cdl = cdl(g)
try:
# Run ncdump on the test file
f_cdl = subprocess.check_output('ncdump -h temp.nc', shell=True)
finally:
os.remove('temp.nc')
# Check that the two CDL strings are "essentially" the same.
g_cdl_std = ncdl.comparable_cdl(g_cdl)
f_cdl_std = ncdl.comparable_cdl(f_cdl)
if g_cdl_std == f_cdl_std:
print 'OK (ncdump and ncobj output EQUAL)'
else:
print 'FAIL: ncdump and ncobj output differ..'
print
def test_ushort(self):
result = cdl(ov('x', data=np.array(1, dtype=np.dtype('uint16'))))
self.assertEqual(result, 'ushort x ;')
def test_ulong_type(self):
result = cdl(oa('x', np.array(5, dtype=np.dtype('uint64'))))
self.assertEqual(result, 'x = 5UL')
def test_float_type(self):
result = cdl(oa('x', np.array(1.23, dtype=np.dtype('float32'))))
self.assertEqual(result, 'x = 1.23f')
def test_empty(self):
g = og('group_name')
result = cdl(g)
self.assertEqual(result, 'netcdf group_name {\n}')
def test__group(self):
g = _make_complex_group()
result_cdl = cdl(g)
expect_cdl = _complex_cdl[:]
self.assertEqual(result_cdl, expect_cdl)
def test_chars(self):
result = cdl(ov('x', dd=[od('STRLEN_4', 4)],
data=np.array(['t', 'h', 'i', 's'])))
self.assertEqual(result, 'char x(STRLEN_4) ;')
def test_unsigned_type(self):
result = cdl(oa('x', np.array(5, dtype=np.dtype('uint32'))))
self.assertEqual(result, 'x = 5U')
def test_double_type(self):
result = cdl(oa('x', np.array(1.23, dtype=np.dtype('float64'))))
self.assertEqual(result, 'x = 1.23')
def ncfile_cdl(file_path):
with netCDF4.Dataset(file_path) as ds:
group = ncds.read(ds)
result = cdl(group)
return result
def test_basic(self):
result = cdl(od('x', 3))
self.assertEqual(result, 'x = 3 ;')
def test_ubyte(self):
result = cdl(ov('x', data=np.array(1, dtype=np.dtype('uint8'))))
self.assertEqual(result, 'ubyte x ;')
def test_unlimited(self):
result = cdl(od('x', 3, u=True))
self.assertEqual(result, 'x = UNLIMITED ;')
def test_nd(self):
result = cdl(ov('x', dd=[od('p'), od('q')], data=np.array(1.0)))
self.assertEqual(result, 'double x(p, q) ;')
def test_scalar(self):
result = cdl(ov('x', data=np.array(3.21, dtype=np.float32)))
self.assertEqual(result, 'float x ;')
def test_int(self):
result = cdl(ov('x', data=np.array(1, dtype=np.dtype('int32'))))
self.assertEqual(result, 'int x ;')
def test_ulong(self):
result = cdl(ov('x', data=np.array(1, dtype=np.dtype('uint64'))))
self.assertEqual(result, 'uint64 x ;')
def show_results(extracted):
#print extracted
print cdl(extracted)
print 'vars data: \n' + '\n'.join("{}:{}".format(var.name, var.data)
for var in ncg.all_variables(extracted))
def test_float(self):
result = cdl(ov('x', data=np.array(1.0,
dtype=np.dtype('float32'))))
self.assertEqual(result, 'float x ;')
""" Example code demonstrating 'flatten' operation for enhanced semantic containers definition. """ from ncobj.cdl import cdl import ncobj.examples.semantic_containers as egs g = egs.eg_simple_flat() g_cdl = cdl(g) print print '----------------' print 'Original flat version:' print '----------------' print g_cdl print '----------------' g_grouped = egs.group_flat_containers(g) g_grouped_cdl = cdl(g_grouped) print print '----------------' print 'Result, grouped from flat form:' print '----------------' print g_grouped_cdl print '----------------' g_grp_eg = egs.eg_simple_grouped()
def test_double(self):
result = cdl(ov('x', data=np.array(1.0)))
self.assertEqual(result, 'double x ;')
""" Example code demonstrating 'flatten' operation for enhanced semantic containers definition. """ from ncobj.cdl import cdl import ncobj.examples.semantic_containers as egs g = egs.eg_simple_grouped() g_cdl = cdl(g) print print '----------------' print 'Original grouped version:' print '----------------' print g_cdl print '----------------' g_flattened = egs.flatten_grouped_containers(g) g_flattened_cdl = cdl(g_flattened) print print '----------------' print 'Result, flattened from grouped form:' print '----------------' print g_flattened_cdl print '----------------' g_flat_eg = egs.eg_simple_flat()
def test_single_type(self):
result = cdl(oa('x', np.array(5, dtype=np.dtype('int32'))))
self.assertEqual(result, 'x = 5')
