Source Code for Module ivs.inout.hdf5

  1  # -*- coding: utf-8 -*- 
  2  """ 
  3  Read and write HDF5 files. 
  4   
  5  HDF5 is a data model, library, and file format for storing and managing data. It supports 
  6  an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for 
  7  high volume and complex data. HDF5 is portable and is extensible, allowing applications  
  8  to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications 
  9  for managing, manipulating, viewing, and analyzing data in the HDF5 format. 
 10  http://alfven.org/wp/hdf5-for-python/ 
 11  """ 
 12   
 13  import os 
 14  import h5py 
 15  import logging 
 16  from ivs.aux import loggers 
 17   
 18  logger = logging.getLogger("IO.HDF5") 
 19  logger.addHandler(loggers.NullHandler()) 
 20   
 21  #{ Input 
 22   
 23 -def read2dict(filename): 
 24      """ 
 25      Read the filestructure of a hdf5 file to a dictionary. 
 26       
 27      @param filename: the name of the hdf5 file to read 
 28      @type filename: str 
 29      @return: dictionary with read filestructure 
 30      @rtype: dict 
 31      """ 
 32       
 33      if not os.path.isfile(filename): 
 34          logger.error('The file you try to read does not exist!') 
 35          raise IOError 
 36       
 37      def read_rec(hdf): 
 38          """ recusively read the hdf5 file """ 
 39          res = {} 
 40          for name,grp in hdf.items(): 
 41              #-- read the subgroups and datasets 
 42              if hasattr(grp, 'items'): 
 43                  # in case of a group, read the group into a new dictionary key 
 44                  res[name] = read_rec(grp) 
 45              else: 
 46                  # in case of dataset, read the value 
 47                  res[name] = grp.value 
 48                   
 49          #-- read all the attributes 
 50          for name, atr in hdf.attrs.iteritems(): 
 51              res[name] = atr 
 52                   
 53          return res 
 54       
 55      hdf = h5py.File(filename, 'r') 
 56      result = read_rec(hdf) 
 57      hdf.close() 
 58       
 59      return result 
 60   
 61  #} 
 62   
 63  #{ Output 
 64   
 65 -def write_dict(data, filename, update=True, attr_types=[]): 
 66      """ 
 67      Write the content of a dictionary to a hdf5 file. The dictionary can contain other 
 68      nested dictionaries, this file stucture will be maintained in the saved hdf5 file. 
 69       
 70      Pay attention to the fact that the data type of lists might change when writing to  
 71      hdf5. Lists are stored as numpy arrays, thus all items in a list are converted to 
 72      the same type: ['bla', 1, 24.5] will become ['bla', '1', '24.5']. Upt till now there 
 73      is nothing in place to check this, or correct it when reading a hdf5 file. 
 74       
 75      @param data: the dictionary to write to file 
 76      @type data: dict 
 77      @param filename: the name of the hdf5 file to write to 
 78      @type filename: str 
 79      @param update: True if you want to update an existing file, False to overwrite 
 80      @type update: bool 
 81      @param attr_types: the data types that you want to save as an attribute instead of 
 82                         a dataset. (standard everything is saved as dataset.) 
 83      @type attr_types: List of types 
 84      """ 
 85       
 86      if not update and os.path.isfile(filename): 
 87          os.remove(filename) 
 88       
 89      def save_rec(data, hdf): 
 90          """ recusively save a dictionary """ 
 91          for key in data.keys(): 
 92               
 93              if type(data[key]) == dict: 
 94                  # if part is dictionary: add 1 level and save dictionary in new level 
 95                  if not key in hdf: 
 96                      hdf.create_group(key) 
 97                  save_rec(data[key], hdf[key]) 
 98                   
 99              elif type(data[key]) in attr_types: 
100                  # save data as attribute 
101                  hdf.attrs[key] = data[key] 
102                   
103              else: 
104                  # other data is stored as datasets 
105                  if key in hdf: 
106                      del hdf[key] 
107                  hdf.create_dataset(key, data=data[key]) 
108       
109      hdf = h5py.File(filename) 
110      save_rec(data, hdf) 
111      hdf.close() 
112  #} 
113