DAMASK_EICMD/lib/damask/h5table.py

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# -*- 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. #
# ----------------------------------------------------------- #
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import os
import h5py
import numpy as np
import xml.etree.cElementTree as ET
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# ---------------------------------------------------------------- #
# 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
def lables_to_path(label, dsXMLPath=None):
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"""read the xml definition file and return the path."""
if dsXMLPath is None:
# use the default storage layout in 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.
# Allow new derived data to be put under the root
tree = ET.parse(dsXMLPath)
try:
dataType = tree.find('{}/type'.format(label)).text
h5path = tree.find('{}/h5path'.format(label)).text
except:
dataType = "Scalar"
h5path = "/{}".format(label) # just put it under root
return (dataType, h5path)
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class H5Table(object):
"""light weight interface class for h5py
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DESCRIPTION
-----------
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Interface/wrapper class for manipulating data in HDF5 with DAMASK
specialized data structure.
-->try to maintain a minimal API design.
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PARAMETERS
----------
h5f_path: str
Absolute path the HDF5 file
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METHOD
------
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del_entry() -- Force delete attributes/group/datasets (Dangerous)
get_attr() -- Return attributes if possible
add_attr() -- Add NEW attributes to dataset/group (please delete old first!)
get_data() -- Retrieve data in numpy.ndarray
add_data() -- Add dataset to H5 file
get_cmdlog() -- Return the command used to generate the data if possible.
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NOTE
----
1. As an interface class, it uses the lazy evaluation design
that read the data only when its absolutely necessary.
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2. The command line used to generate new feature is stored with
each dataset as dataset attribute.
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"""
def __init__(self, h5f_path, new_file=False, dsXMLFile=None):
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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
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def del_entry(self, feature_name):
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"""delete entry in HDF5 table"""
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
del h5f[h5f_path]
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def get_attr(self, 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
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def add_attr(self, attr_name, attr_data):
dataType, h5f_path = lables_to_path(attr_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
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h5f[h5f_path].attrs[attr_name] = attr_data
h5f.flush()
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def get_data(self, feature_name=None):
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"""extract dataset from HDF5 table and return it in a numpy array"""
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 = np.zeros(h5f_dst.shape)
h5f_dst.read_direct(rst_data)
return rst_data
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def add_data(self, feature_name, dataset, cmd_log=None):
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"""adding new feature into existing HDF5 file"""
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
with h5py.File(self.h5f_path, 'a') as h5f:
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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)
h5f.flush()
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def get_cmdlog(self, feature_name):
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"""get cmd history used to generate the feature"""
dataType, h5f_path = lables_to_path(feature_name,
dsXMLPath=self.dsXMLFile)
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with h5py.File(self.h5f_path, 'a') as h5f:
cmd_logs = h5f[h5f_path].attrs['log']
return cmd_logs