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DAMASK_EICMD
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polishing

This commit is contained in:
Martin Diehl 2021-05-28 13:20:56 +02:00
parent dd4612dd9b
commit e431d89957
1 changed files with 18 additions and 18 deletions
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36
python/damask/_result.py
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@ -26,6 +26,8 @@ from . import util
h5py3 = h5py.__version__[0] == '3'
chunk_size = 1024**2//8 # for compression in HDF5
def _read(dataset):
"""Read a dataset and its metadata into a numpy.ndarray."""
@ -1124,8 +1126,8 @@ class Result:
'label': f"{t}({F['label']})",
'meta': {
'unit': F['meta']['unit'],
'description': '{} stretch tensor of {} ({})'.format('left' if t.upper() == 'V' else 'right',
F['label'],F['meta']['description']),
'description': f"{'left' if t.upper() == 'V' else 'right'} stretch tensor "\
+f"of {F['label']} ({F['meta']['description']})",
'creator': 'add_stretch_tensor'
}
}
@ -1145,7 +1147,7 @@ class Result:
self._add_generic_pointwise(self._add_stretch_tensor,{'F':F},{'t':t})
def _job(self,group,func,datasets,args,lock):
def _job_pointwise(self,group,func,datasets,args,lock):
"""Execute job for _add_generic_pointwise."""
try:
datasets_in = {}
@ -1163,7 +1165,6 @@ class Result:
print(f'Error during calculation: {err}.')
return None
def _add_generic_pointwise(self,func,datasets,args={}):
"""
General function to add pointwise data.
@ -1180,7 +1181,6 @@ class Result:
Arguments parsed to func.
"""
chunk_size = 1024**2//8
pool = mp.Pool(int(os.environ.get('OMP_NUM_THREADS',4)))
lock = mp.Manager().Lock()
@ -1197,34 +1197,34 @@ class Result:
print('No matching dataset found, no data was added.')
return
default_arg = partial(self._job,func=func,datasets=datasets,args=args,lock=lock)
default_arg = partial(self._job_pointwise,func=func,datasets=datasets,args=args,lock=lock)
for result in util.show_progress(pool.imap_unordered(default_arg,groups),len(groups)):
for group,result in util.show_progress(pool.imap_unordered(default_arg,groups),len(groups)):
if not result:
continue
lock.acquire()
with h5py.File(self.fname, 'a') as f:
try:
if self._allow_modification and result[0]+'/'+result[1]['label'] in f:
dataset = f[result[0]+'/'+result[1]['label']]
dataset[...] = result[1]['data']
if self._allow_modification and '/'.join([group,result['label']]) in f:
dataset = f['/'.join([group,result['label']])]
dataset[...] = result['data']
dataset.attrs['overwritten'] = True
else:
if result[1]['data'].size >= chunk_size*2:
shape = result[1]['data'].shape
if result['data'].size >= chunk_size*2:
shape = result['data'].shape
chunks = (chunk_size//np.prod(shape[1:]),)+shape[1:]
dataset = f[result[0]].create_dataset(result[1]['label'],data=result[1]['data'],
maxshape=shape, chunks=chunks,
compression='gzip', compression_opts=6,
shuffle=True,fletcher32=True)
dataset = f[group].create_dataset(result['label'],data=result['data'],
maxshape=shape, chunks=chunks,
compression='gzip', compression_opts=6,
shuffle=True,fletcher32=True)
else:
dataset = f[result[0]].create_dataset(result[1]['label'],data=result[1]['data'])
dataset = f[group].create_dataset(result['label'],data=result['data'])
now = datetime.datetime.now().astimezone()
dataset.attrs['created'] = now.strftime('%Y-%m-%d %H:%M:%S%z') if h5py3 else \
now.strftime('%Y-%m-%d %H:%M:%S%z').encode()
for l,v in result[1]['meta'].items():
for l,v in result['meta'].items():
dataset.attrs[l.lower()]=v if h5py3 else v.encode()
creator = dataset.attrs['creator'] if h5py3 else \
dataset.attrs['creator'].decode()