def cov_io(self, context, value_array, comp_val=None):
pdict = ParameterDictionary()
time = ParameterContext(name='time', param_type=QuantityType(value_encoding=np.float64))
pdict.add_context(context)
pdict.add_context(time, True)
# Construct temporal and spatial Coordinate Reference System objects
tcrs = CRS([AxisTypeEnum.TIME])
scrs = CRS([AxisTypeEnum.LON, AxisTypeEnum.LAT])
# Construct temporal and spatial Domain objects
tdom = GridDomain(GridShape('temporal', [0]), tcrs, MutabilityEnum.EXTENSIBLE) # 1d (timeline)
sdom = GridDomain(GridShape('spatial', [0]), scrs, MutabilityEnum.IMMUTABLE) # 0d spatial topology (station/trajectory)
# Instantiate the SimplexCoverage providing the ParameterDictionary, spatial Domain and temporal Domain
cov = SimplexCoverage('test_data', create_guid(), 'sample coverage_model', parameter_dictionary=pdict, temporal_domain=tdom, spatial_domain=sdom)
cov.insert_timesteps(len(value_array))
cov.set_parameter_values('test', tdoa=slice(0,len(value_array)), value=value_array)
comp_val = comp_val if comp_val is not None else value_array
testval = cov.get_parameter_values('test')
try:
np.testing.assert_array_equal(testval, comp_val)
except:
print repr(value_array)
raise
def __init__(self,
total_domain=(10, 10),
brick_size=5,
use_hdf=False,
root_dir='test_data/multi_dim_trials',
guid=None,
dtype='int16'):
self.total_domain = total_domain
self.brick_sizes = tuple(brick_size for x in total_domain)
self.use_hdf = use_hdf
self.dtype = np.dtype(dtype).name
if self.use_hdf:
self.guid = guid or create_guid()
name = '%s_%s' % (self.guid, self.dtype)
self.root_dir = root_dir
if not os.path.exists(self.root_dir):
os.makedirs(self.root_dir)
if os.path.exists(os.path.join(self.root_dir, name)):
shutil.rmtree(os.path.join(self.root_dir, name))
self.master_manager = MasterManager(
self.root_dir, name, name='md_test_{0}'.format(name))
self.master_manager.flush()
pc = ParameterContext('test_param',
param_type=QuantityType(self.dtype),
fill_value=-1)
self.param_manager = ParameterManager(
os.path.join(self.root_dir, name, pc.name), pc.name)
self.param_manager.parameter_context = pc
self.master_manager.create_group(pc.name)
self.param_manager.flush()
self.bricks = {}
self.brick_origins = bricking_utils.calc_brick_origins(
self.total_domain, self.brick_sizes)
self.brick_extents, self.rtree_extents = bricking_utils.calc_brick_and_rtree_extents(
self.brick_origins, self.brick_sizes)
self.build_bricks()
self.rtree = RTreeProxy()
for x in BrickingAssessor.rtree_populator(self.rtree_extents,
self.brick_extents):
self.rtree.insert(*x)
def __init__(
self,
total_domain=(10, 10),
brick_size=5,
use_hdf=False,
root_dir="test_data/multi_dim_trials",
guid=None,
dtype="int16",
):
self.total_domain = total_domain
self.brick_sizes = tuple(brick_size for x in total_domain)
self.use_hdf = use_hdf
self.dtype = np.dtype(dtype).name
if self.use_hdf:
self.guid = guid or create_guid()
name = "%s_%s" % (self.guid, self.dtype)
self.root_dir = root_dir
if not os.path.exists(self.root_dir):
os.makedirs(self.root_dir)
if os.path.exists(os.path.join(self.root_dir, name)):
shutil.rmtree(os.path.join(self.root_dir, name))
# self.master_manager = MasterManager(self.root_dir, name, name='md_test_{0}'.format(name))
self.master_manager = MetadataManagerFactory.buildMetadataManager(
self.root_dir, name, name="md_test_{0}".format(name)
)
self.master_manager.flush()
pc = ParameterContext("test_param", param_type=QuantityType(self.dtype), fill_value=-1)
self.param_manager = ParameterManager(os.path.join(self.root_dir, name, pc.name), pc.name)
self.param_manager.parameter_context = pc
self.master_manager.create_group(pc.name)
self.param_manager.flush()
self.bricks = {}
self.brick_origins = bricking_utils.calc_brick_origins(self.total_domain, self.brick_sizes)
self.brick_extents, self.rtree_extents = bricking_utils.calc_brick_and_rtree_extents(
self.brick_origins, self.brick_sizes
)
self.build_bricks()
self.rtree = RTreeProxy()
for x in BrickingAssessor.rtree_populator(self.rtree_extents, self.brick_extents):
self.rtree.insert(*x)
def cov_io(self, context, value_array, comp_val=None):
pdict = ParameterDictionary()
time = ParameterContext(
name='time', param_type=QuantityType(value_encoding=np.float64))
pdict.add_context(context)
pdict.add_context(time, True)
# Construct temporal and spatial Coordinate Reference System objects
tcrs = CRS([AxisTypeEnum.TIME])
scrs = CRS([AxisTypeEnum.LON, AxisTypeEnum.LAT])
# Construct temporal and spatial Domain objects
tdom = GridDomain(GridShape('temporal', [0]), tcrs,
MutabilityEnum.EXTENSIBLE) # 1d (timeline)
sdom = GridDomain(GridShape('spatial',
[0]), scrs, MutabilityEnum.IMMUTABLE
) # 0d spatial topology (station/trajectory)
# Instantiate the SimplexCoverage providing the ParameterDictionary, spatial Domain and temporal Domain
cov = SimplexCoverage('test_data',
create_guid(),
'sample coverage_model',
parameter_dictionary=pdict,
temporal_domain=tdom,
spatial_domain=sdom)
self.addCleanup(shutil.rmtree, cov.persistence_dir)
cov.insert_timesteps(len(value_array))
cov.set_parameter_values('test',
tdoa=slice(0, len(value_array)),
value=value_array)
comp_val = comp_val if comp_val is not None else value_array
testval = cov.get_parameter_values('test')
try:
np.testing.assert_array_equal(testval, comp_val)
except:
print repr(value_array)
raise
