DAMASK_EICMD/lib/damask/h5table.py

130 lines
4.7 KiB
Python
Raw Normal View History

2016-10-07 19:17:15 +05:30
# -*- coding: UTF-8 no BOM -*-
# ----------------------------------------------------------- #
# Ideally the h5py should be enough to serve as the data #
# interface for future DAMASK, but since we are still not #
# sure when this major shift will happen, it seems to be a #
# good idea to provide a interface class that help user ease #
# into using HDF5 as the new daily storage driver. #
# ----------------------------------------------------------- #
2016-10-07 19:17:15 +05:30
import os
import sys
import h5py
import numpy as np
import xml.etree.cElementTree as ET
2016-10-07 19:17:15 +05:30
# ---------------------------------------------------------------- #
# python 3 has no unicode object, this ensures that the code works #
# on Python 2&3 #
# ---------------------------------------------------------------- #
try:
test=isinstance('test', unicode)
except(NameError):
unicode=str
# ------------------------------------------------------- #
# Singleton class for converting feature name to H5F path #
# ------------------------------------------------------- #
# NOTE:
# use simple function to mimic the singleton class in
2016-10-07 19:17:15 +05:30
# C++/Java
def lables_to_path(label, dsXMLPath=None):
2016-10-07 19:17:15 +05:30
""" 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")
# 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
# using ET interface, but for now I can not see the benefits in doing
# so.
tree = ET.parse(dsXMLPath)
dataType = tree.find('{}/type'.format(label)).text
h5path = tree.find('{}/h5path'.format(label)).text
return (dataType, h5path)
2016-10-07 19:17:15 +05:30
# ----------------------- #
# H5Table interface class #
# ----------------------- #
class H5Table(object):
"""
DESCRIPTION
-----------
Interface class for manipulating data in HDF5 with DAMASK
specialized data structure.
2016-10-07 19:17:15 +05:30
PARAMETERS
----------
h5f_path: str
Absolute path the HDF5 file
2016-10-07 19:17:15 +05:30
METHOD
------
2016-10-08 03:13:52 +05:30
del_entry()
2016-10-07 19:17:15 +05:30
get_attr()
add_attr()
get_data()
add_data()
get_cmdlog()
Return the command used to generate the data if possible.
2016-10-07 19:17:15 +05:30
NOTE
----
1. As an interface class, it uses the lazy evaluation design
that read the data only when its absolutely necessary.
2016-10-08 03:13:52 +05:30
2. The command line used to generate new feature is stored with
each dataset as dataset attribute.
2016-10-07 19:17:15 +05:30
"""
def __init__(self, h5f_path):
"""
"""
self.h5f_path = h5f_path
2016-10-08 03:13:52 +05:30
def del_entry(self, feature_name):
""" delete entry in HDF5 table """
# WARNING: this will PERMENANTLY delete attributes/dataset
# use with caution
2016-10-08 02:11:17 +05:30
dataType, h5f_path = lables_to_path(feature_name)
h5f = h5py.File(self.h5f_path, 'a')
del h5f[h5f_path]
2016-10-08 03:13:52 +05:30
def get_attr(self, attr_name):
2016-10-07 19:17:15 +05:30
h5f = h5py.File(self.h5f_path, 'r')
2016-10-08 03:13:52 +05:30
dataType, h5f_path = lables_to_path(attr_name)
return h5f[h5f_path].attrs[attr_name]
2016-10-07 19:17:15 +05:30
2016-10-08 03:13:52 +05:30
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":
h5f[h5f_path].attrs[attr_name] = attr_data
else:
raise ValueError("Unspported attr: {}".format(attr_name))
2016-10-07 19:17:15 +05:30
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))
2016-10-07 19:17:15 +05:30
def add_data(self, feature_name, dataset=None, cmd_log=None):
2016-10-08 02:11:17 +05:30
""" 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')
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)
2016-10-08 02:11:17 +05:30
else:
raise ValueError("feature {} isn't valid".format(feature_name))
2016-10-08 03:13:52 +05:30
def get_cmdlog(self, feature_name):
""" get cmd history used to generate the feature"""
2016-10-08 03:13:52 +05:30
dataType, h5f_path = lables_to_path(feature_name)
h5f = ht5py.File(self.h5f_path, 'r')
return h5f[h5f_path].attrs['log']