H5Table support customize data storage layout

This commit is contained in:
chen 2016-10-09 18:59:50 -04:00
parent 753bdfd5a9
commit 912aa6989c
1 changed files with 41 additions and 31 deletions

View File

@ -34,8 +34,12 @@ def lables_to_path(label, dsXMLPath=None):
""" read the xml definition file and return the path."""
if dsXMLPath is None:
# use the default storage layout in DS_HDF5.xml
dsXMLPath = os.path.abspath(__file__).replace("h5table.py",
"DS_HDF5.xml")
if "h5table.pyc" in __file__:
dsXMLPath = os.path.abspath(__file__).replace("h5table.pyc",
"DS_HDF5.xml")
else:
dsXMLPath = os.path.abspath(__file__).replace("h5table.py",
"DS_HDF5.xml")
# This current implementation requires that all variables
# stay under the root node, the nesting is defined through the
# h5path. This could be improved easily with more advanced parsing
@ -77,53 +81,59 @@ class H5Table(object):
each dataset as dataset attribute.
"""
def __init__(self, h5f_path):
"""
"""
def __init__(self, h5f_path, new_file=False, dsXMLFile=None):
self.h5f_path = h5f_path
self.dsXMLFile = dsXMLFile
msg = 'Created by H5Talbe from DAMASK'
mode = 'w' if new_file else 'a'
with h5py.File(self.h5f_path, mode) as h5f:
h5f['/'].attrs['description'] = msg
def del_entry(self, feature_name):
""" delete entry in HDF5 table """
# WARNING: this will PERMENANTLY delete attributes/dataset
# use with caution
dataType, h5f_path = lables_to_path(feature_name)
h5f = h5py.File(self.h5f_path, 'a')
del h5f[h5f_path]
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
del h5f[h5f_path]
def get_attr(self, attr_name):
h5f = h5py.File(self.h5f_path, 'r')
dataType, h5f_path = lables_to_path(attr_name)
return h5f[h5f_path].attrs[attr_name]
dataType, h5f_path = lables_to_path(attr_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
rst_attr = h5f[h5f_path].attrs[attr_name]
return rst_attr
def add_attr(self, attr_name, attr_data):
h5f = h5py.File(self.h5f_path, 'a')
dataType, h5f_path = lables_to_path(attr_name)
if dataType == "attr":
dataType, h5f_path = lables_to_path(attr_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
h5f[h5f_path].attrs[attr_name] = attr_data
else:
raise ValueError("Unspported attr: {}".format(attr_name))
h5f.flush()
def get_data(self, feature_name=None):
""" extract dataset from HDF5 table and return it in a numpy array """
dataType, h5f_path = lables_to_path(feature_name)
h5f = h5py.File(self.h5f_path, 'r')
h5f_dst = h5f[h5f_path] # get the handle for target dataset(table)
return h5f_dst.read_direct(np.zeros(h5f_dst.shape))
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
h5f_dst = h5f[h5f_path] # get the handle for target dataset(table)
rst_data = h5f_dst.read_direct(np.zeros(h5f_dst.shape))
return rst_data
def add_data(self, feature_name, dataset=None, cmd_log=None):
def add_data(self, feature_name, dataset, cmd_log=None):
""" adding new feature into existing HDF5 file """
dataType, h5f_path = lables_to_path(feature_name)
if dataType is not "attr":
h5f = h5py.File(self.h5f_path, 'a')
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
h5f.create_dataset(h5f_path, data=dataset)
# store the cmd in log is possible
if cmd_log is not None:
h5f[h5f_path].attrs['log'] = str(cmd_log)
else:
raise ValueError("feature {} isn't valid".format(feature_name))
h5f.flush()
def get_cmdlog(self, feature_name):
""" get cmd history used to generate the feature"""
dataType, h5f_path = lables_to_path(feature_name)
h5f = ht5py.File(self.h5f_path, 'r')
return h5f[h5f_path].attrs['log']
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with ht5py.File(self.h5f_path, 'a') as h5f:
cmd_logs = h5f[h5f_path].attrs['log']
return cmd_logs