#
# This file is part of postpic.
#
# postpic is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# postpic is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with postpic. If not, see <http://www.gnu.org/licenses/>.
#
# Copyright Stephan Kuschel 2016
'''
.. _openPMD: https://github.com/openPMD/openPMD-standard
Support for hdf5 files following the openPMD_ Standard.
Dependecies:
- h5py: read hdf5 files with python
Written by Stephan Kuschel 2016
'''
from __future__ import absolute_import, division, print_function, unicode_literals
from . import Dumpreader_ifc
from . import Simulationreader_ifc
import numpy as np
import re
from .. import helper
__all__ = ['OpenPMDreader', 'FileSeries']
[docs]class OpenPMDreader(Dumpreader_ifc):
'''
The Reader implementation for Data written in the hdf5 file
format following openPMD_ naming conventions.
Args:
h5file : String
A String containing the relative Path to the .h5 file.
'''
def __init__(self, h5file, **kwargs):
super(self.__class__, self).__init__(h5file, **kwargs)
import os.path
import h5py
if not os.path.isfile(h5file):
raise IOError('File "' + str(h5file) + '" doesnt exist.')
self._h5 = h5py.File(h5file, 'r')
self._iteration = int(list(self._h5['data'].keys())[0])
self._data = self._h5['/data/{:d}/'.format(self._iteration)]
self.attrs = self._data.attrs
[docs] def __del__(self):
del self._data
# --- Level 0 methods ---
[docs] def keys(self):
return list(self._data.keys())
[docs] def __getitem__(self, key):
return self._data[key]
# --- Level 1 methods ---
[docs] def data(self, key):
'''
should work with any key, that contains data, thus on every hdf5.Dataset,
but not on hdf5.Group. Will extract the data, convert it to SI and return it
as a numpy array. Constant records will be detected and converted to
a numpy array containing a single value only.
'''
record = self[key]
if "value" in record.attrs:
# constant data (a single int or float)
ret = np.float64(record.attrs['value']) * record.attrs['unitSI']
else:
# array data
ret = np.float64(record.value) * record.attrs['unitSI']
return ret
[docs] def gridoffset(self, key, axis):
axid = helper.axesidentify[axis]
if "gridUnitSI" in self[key].attrs:
attrs = self[key].attrs
else:
attrs = self[key].parent.attrs
return attrs['gridGlobalOffset'][axid] * attrs['gridUnitSI']
[docs] def gridspacing(self, key, axis):
axid = helper.axesidentify[axis]
if "gridUnitSI" in self[key].attrs:
attrs = self[key].attrs
else:
attrs = self[key].parent.attrs
return attrs['gridSpacing'][axid] * attrs['gridUnitSI']
[docs] def gridpoints(self, key, axis):
axid = helper.axesidentify[axis]
return self[key].shape[axid]
# --- Level 2 methods ---
[docs] def timestep(self):
return self._iteration
[docs] def time(self):
return np.float64(self.attrs['time'] * self.attrs['timeUnitSI'])
[docs] def simdimensions(self):
'''
the number of spatial dimensions the simulation was using.
'''
for k in self._simgridkeys():
try:
gs = self.gridspacing(k, None)
return len(gs)
except(KeyError):
pass
raise KeyError('number of simdimensions could not be retrieved for {}'.format(self))
def _keyE(self, component, **kwargs):
axsuffix = {0: 'x', 1: 'y', 2: 'z'}[helper.axesidentify[component]]
return 'fields/E/' + axsuffix
def _keyB(self, component, **kwargs):
axsuffix = {0: 'x', 1: 'y', 2: 'z'}[helper.axesidentify[component]]
return 'fields/B/' + axsuffix
def _simgridkeys(self):
return ['fields/E/x', 'fields/E/y', 'fields/E/z',
'fields/B/x', 'fields/B/y', 'fields/B/z']
[docs] def listSpecies(self):
ret = list(self['particles'].keys())
return ret
[docs] def getSpecies(self, species, attrib):
"""
Returns one of the attributes out of (x,y,z,px,py,pz,weight,ID,mass,charge) of
this particle species.
"""
attribid = helper.attribidentify[attrib]
options = {9: lambda s: self.data('particles/' + s + '/weighting'),
0: lambda s: self.data('particles/' + s + '/position/x') +
self.data('particles/' + s + '/positionOffset/x'),
1: lambda s: self.data('particles/' + s + '/position/y') +
self.data('particles/' + s + '/positionOffset/y'),
2: lambda s: self.data('particles/' + s + '/position/z') +
self.data('particles/' + s + '/positionOffset/z'),
3: lambda s: self.data('particles/' + s + '/momentum/x'),
4: lambda s: self.data('particles/' + s + '/momentum/y'),
5: lambda s: self.data('particles/' + s + '/momentum/z'),
10: lambda s: self.data('particles/' + s + '/id'),
11: lambda s: self.data('particles/' + s + '/mass'),
12: lambda s: self.data('particles/' + s + '/charge')}
try:
ret = np.float64(options[attribid](species))
except(IndexError):
raise KeyError
return ret
[docs] def getderived(self):
'''
return all other fields dumped, except E and B.
'''
ret = []
self['fields'].visit(ret.append)
ret = ['fields/' + r for r in ret if not (r.startswith('E') or r.startswith('B'))]
ret = [r for r in ret if hasattr(self[r], 'value')]
ret.sort()
return ret
def __str__(self):
return '<OpenPMDh5reader at "' + str(self.dumpidentifier) + '">'
[docs]class FileSeries(Simulationreader_ifc):
'''
Reads a time series of dumps from a given directory.
The simidentifier is expanded using glob in order to
find matching files.
'''
def __init__(self, simidentifier, dumpreadercls=OpenPMDreader, **kwargs):
super(self.__class__, self).__init__(simidentifier, **kwargs)
self.dumpreadercls = dumpreadercls
import glob
self._dumpfiles = glob.glob(simidentifier)
self._dumpfiles.sort()
def _getDumpreader(self, n):
'''
Do not use this method. It will be called by __getitem__.
Use __getitem__ instead.
'''
return self.dumpreadercls(self._dumpfiles[n])
def __len__(self):
return len(self._dumpfiles)
def __str__(self):
return '<FileSeries at "' + self.simidentifier + '">'
