Source code for openpnm.io._hdf5
import logging
from openpnm.io import project_to_dict, _parse_filename
import pandas as pd
logger = logging.getLogger(__name__)
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def project_to_hdf5(project, filename=''):
r"""
Creates an HDF5 file containing data from the specified objects
Parameters
----------
network : Network
The network containing the desired data
phases : list[Phase]s (optional, default is none)
A list of phase objects whose data are to be included
Returns
-------
f : hdf5 file handle
A handle to an hdf5 file. This must be closed when done (i.e.
``f.close()``.
"""
from h5py import File as hdfFile
if filename == '':
filename = project.name
filename = _parse_filename(filename, ext='hdf')
dct = project_to_dict(project=project)
d = pd.json_normalize(dct, sep='.').to_dict(orient='records')[0]
for k in list(d.keys()):
d[k.replace('.', '/')] = d.pop(k)
f = hdfFile(filename, "w")
for item in list(d.keys()):
tempname = '_'.join(item.split('.'))
arr = d[item]
if d[item].dtype == 'O':
logger.warning(item + ' has dtype object, will not write to file')
del d[item]
elif 'U' in str(arr[0].dtype):
pass
else:
f.create_dataset(name='/'+tempname, shape=arr.shape,
dtype=arr.dtype, data=arr)
return f
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def print_hdf5(f, flat=False):
r"""
Given an hdf5 file handle, prints to console in a human readable manner
Parameters
----------
f : file handle
The hdf5 file to print
flat : bool
Flag to indicate if print should be nested or flat. The default is
``flat==False`` resulting in a nested view.
"""
if flat is False:
def print_level(f, p='', indent='-'):
for item in f.keys():
if hasattr(f[item], 'keys'):
p = print_level(f[item], p=p, indent=indent + indent[0])
elif indent[-1] != ' ':
indent = indent + ''
p = indent + item + '\n' + p
return p
p = print_level(f)
print(p)
else:
f.visit(print)
