shorter function name; setup_files is property
This commit is contained in:
Philip Eisenlohr
parent
836feaa5f4
commit
1a748ec5aa
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@ -109,7 +109,7 @@ class Result:
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if self.version_major != 0 or not 12 <= self.version_minor <= 14:
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raise TypeError(f'unsupported DADF5 version "{self.version_major}.{self.version_minor}"')
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if self.version_major == 0 and self.version_minor < 14:
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self.export_simulation_setup_files = None # type: ignore
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self.export_simulation_setup = None # type: ignore
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self.structured = 'cells' in f['geometry'].attrs.keys()
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@ -561,6 +561,14 @@ class Result:
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print(f'Function {func.__name__} enabled in add_calculation.')
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@property
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def simulation_setup_files(self):
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"""Simulation setup files used to generate the Result object."""
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files = []
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with h5py.File(self.fname,'r') as f_in:
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f_in['setup'].visit(lambda name: files.append(name))
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return files
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@property
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def incs(self):
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return [int(i.split(prefix_inc)[-1]) for i in self.increments]
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@ -1515,6 +1523,166 @@ class Result:
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pool.join()
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def _mappings(self):
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"""Mappings to place data spatially."""
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with h5py.File(self.fname,'r') as f:
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at_cell_ph = []
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in_data_ph = []
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for c in range(self.N_constituents):
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at_cell_ph.append({label: np.where(self.phase[:,c] == label)[0] \
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for label in self.visible['phases']})
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in_data_ph.append({label: f['/'.join(['cell_to','phase'])]['entry'][at_cell_ph[c][label]][:,c] \
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for label in self.visible['phases']})
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at_cell_ho = {label: np.where(self.homogenization[:] == label)[0] \
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for label in self.visible['homogenizations']}
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in_data_ho = {label: f['/'.join(['cell_to','homogenization'])]['entry'][at_cell_ho[label]] \
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for label in self.visible['homogenizations']}
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return at_cell_ph,in_data_ph,at_cell_ho,in_data_ho
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def get(self,
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output: Union[str, List[str]] = '*',
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flatten: bool = True,
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prune: bool = True):
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"""
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Collect data per phase/homogenization reflecting the group/folder structure in the DADF5 file.
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Parameters
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----------
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output : (list of) str, optional
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Names of the datasets to read.
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Defaults to '*', in which case all datasets are read.
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flatten : bool, optional
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Remove singular levels of the folder hierarchy.
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This might be beneficial in case of single increment,
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phase/homogenization, or field. Defaults to True.
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prune : bool, optional
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Remove branches with no data. Defaults to True.
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Returns
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-------
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data : dict of numpy.ndarray
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Datasets structured by phase/homogenization and according to selected view.
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"""
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r = {} # type: ignore
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with h5py.File(self.fname,'r') as f:
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for inc in util.show_progress(self.visible['increments']):
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r[inc] = {'phase':{},'homogenization':{},'geometry':{}}
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for out in _match(output,f['/'.join([inc,'geometry'])].keys()):
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r[inc]['geometry'][out] = _read(f['/'.join([inc,'geometry',out])])
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for ty in ['phase','homogenization']:
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for label in self.visible[ty+'s']:
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r[inc][ty][label] = {}
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for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
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r[inc][ty][label][field] = {}
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for out in _match(output,f['/'.join([inc,ty,label,field])].keys()):
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r[inc][ty][label][field][out] = _read(f['/'.join([inc,ty,label,field,out])])
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if prune: r = util.dict_prune(r)
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if flatten: r = util.dict_flatten(r)
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return None if (type(r) == dict and r == {}) else r
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def place(self,
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output: Union[str, List[str]] = '*',
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flatten: bool = True,
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prune: bool = True,
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constituents: IntSequence = None,
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fill_float: float = np.nan,
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fill_int: int = 0):
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"""
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Merge data into spatial order that is compatible with the damask.VTK geometry representation.
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The returned data structure reflects the group/folder structure in the DADF5 file.
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Multi-phase data is fused into a single output.
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`place` is equivalent to `get` if only one phase/homogenization
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and one constituent is present.
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Parameters
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----------
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output : (list of) str, optional
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Names of the datasets to read.
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Defaults to '*', in which case all visible datasets are placed.
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flatten : bool, optional
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Remove singular levels of the folder hierarchy.
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This might be beneficial in case of single increment or field.
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Defaults to True.
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prune : bool, optional
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Remove branches with no data. Defaults to True.
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constituents : (list of) int, optional
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Constituents to consider.
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Defaults to None, in which case all constituents are considered.
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fill_float : float, optional
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Fill value for non-existent entries of floating point type.
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Defaults to NaN.
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fill_int : int, optional
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Fill value for non-existent entries of integer type.
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Defaults to 0.
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Returns
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-------
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data : dict of numpy.ma.MaskedArray
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Datasets structured by spatial position and according to selected view.
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"""
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r = {} # type: ignore
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constituents_ = list(map(int,constituents)) if isinstance(constituents,Iterable) else \
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(range(self.N_constituents) if constituents is None else [constituents]) # type: ignore
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suffixes = [''] if self.N_constituents == 1 or isinstance(constituents,int) else \
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[f'#{c}' for c in constituents_]
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at_cell_ph,in_data_ph,at_cell_ho,in_data_ho = self._mappings()
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with h5py.File(self.fname,'r') as f:
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for inc in util.show_progress(self.visible['increments']):
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r[inc] = {'phase':{},'homogenization':{},'geometry':{}}
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for out in _match(output,f['/'.join([inc,'geometry'])].keys()):
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r[inc]['geometry'][out] = ma.array(_read(f['/'.join([inc,'geometry',out])]),fill_value = fill_float)
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for ty in ['phase','homogenization']:
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for label in self.visible[ty+'s']:
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for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
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if field not in r[inc][ty].keys():
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r[inc][ty][field] = {}
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for out in _match(output,f['/'.join([inc,ty,label,field])].keys()):
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data = ma.array(_read(f['/'.join([inc,ty,label,field,out])]))
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if ty == 'phase':
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if out+suffixes[0] not in r[inc][ty][field].keys():
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for c,suffix in zip(constituents_,suffixes):
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r[inc][ty][field][out+suffix] = \
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_empty_like(data,self.N_materialpoints,fill_float,fill_int)
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for c,suffix in zip(constituents_,suffixes):
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r[inc][ty][field][out+suffix][at_cell_ph[c][label]] = data[in_data_ph[c][label]]
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if ty == 'homogenization':
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if out not in r[inc][ty][field].keys():
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r[inc][ty][field][out] = \
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_empty_like(data,self.N_materialpoints,fill_float,fill_int)
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r[inc][ty][field][out][at_cell_ho[label]] = data[in_data_ho[label]]
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if prune: r = util.dict_prune(r)
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if flatten: r = util.dict_flatten(r)
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return None if (type(r) == dict and r == {}) else r
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def export_XDMF(self,
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output: Union[str, List[str]] = '*',
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target_dir: Union[str, Path] = None,
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@ -1642,26 +1810,6 @@ class Result:
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f.write(xml.dom.minidom.parseString(ET.tostring(xdmf).decode()).toprettyxml())
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def _mappings(self):
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"""Mappings to place data spatially."""
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with h5py.File(self.fname,'r') as f:
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at_cell_ph = []
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in_data_ph = []
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for c in range(self.N_constituents):
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at_cell_ph.append({label: np.where(self.phase[:,c] == label)[0] \
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for label in self.visible['phases']})
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in_data_ph.append({label: f['/'.join(['cell_to','phase'])]['entry'][at_cell_ph[c][label]][:,c] \
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for label in self.visible['phases']})
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at_cell_ho = {label: np.where(self.homogenization[:] == label)[0] \
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for label in self.visible['homogenizations']}
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in_data_ho = {label: f['/'.join(['cell_to','homogenization'])]['entry'][at_cell_ho[label]] \
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for label in self.visible['homogenizations']}
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return at_cell_ph,in_data_ph,at_cell_ho,in_data_ho
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def export_VTK(self,
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output: Union[str,List[str]] = '*',
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mode: str = 'cell',
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@ -1682,7 +1830,7 @@ class Result:
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----------
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output : (list of) str, optional
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Names of the datasets to export to the VTK file.
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Defaults to '*', in which case all datasets are exported.
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Defaults to '*', in which case all visible datasets are exported.
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mode : {'cell', 'point'}, optional
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Export in cell format or point format.
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Defaults to 'cell'.
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@ -1766,54 +1914,6 @@ class Result:
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v.save(vtk_dir/f'{self.fname.stem}_inc{inc.split(prefix_inc)[-1].zfill(N_digits)}',
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parallel=parallel)
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def get(self,
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output: Union[str, List[str]] = '*',
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flatten: bool = True,
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prune: bool = True):
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"""
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Collect data per phase/homogenization reflecting the group/folder structure in the DADF5 file.
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Parameters
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----------
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output : (list of) str, optional
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Names of the datasets to read.
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Defaults to '*', in which case all datasets are read.
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flatten : bool, optional
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Remove singular levels of the folder hierarchy.
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This might be beneficial in case of single increment,
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phase/homogenization, or field. Defaults to True.
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prune : bool, optional
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Remove branches with no data. Defaults to True.
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Returns
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-------
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data : dict of numpy.ndarray
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Datasets structured by phase/homogenization and according to selected view.
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"""
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r = {} # type: ignore
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with h5py.File(self.fname,'r') as f:
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for inc in util.show_progress(self.visible['increments']):
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r[inc] = {'phase':{},'homogenization':{},'geometry':{}}
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for out in _match(output,f['/'.join([inc,'geometry'])].keys()):
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r[inc]['geometry'][out] = _read(f['/'.join([inc,'geometry',out])])
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for ty in ['phase','homogenization']:
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for label in self.visible[ty+'s']:
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r[inc][ty][label] = {}
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for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
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r[inc][ty][label][field] = {}
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for out in _match(output,f['/'.join([inc,ty,label,field])].keys()):
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r[inc][ty][label][field][out] = _read(f['/'.join([inc,ty,label,field,out])])
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if prune: r = util.dict_prune(r)
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if flatten: r = util.dict_flatten(r)
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return None if (type(r) == dict and r == {}) else r
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def export_DADF5(self,
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fname,
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output: Union[str, List[str]] = '*'):
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@ -1858,99 +1958,7 @@ class Result:
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f_in[p].copy(out,f_out[p])
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def place(self,
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output: Union[str, List[str]] = '*',
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flatten: bool = True,
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prune: bool = True,
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constituents: IntSequence = None,
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fill_float: float = np.nan,
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fill_int: int = 0):
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"""
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Merge data into spatial order that is compatible with the damask.VTK geometry representation.
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The returned data structure reflects the group/folder structure in the DADF5 file.
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Multi-phase data is fused into a single output.
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`place` is equivalent to `get` if only one phase/homogenization
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and one constituent is present.
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Parameters
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----------
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output : (list of) str, optional
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Names of the datasets to read.
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Defaults to '*', in which case all datasets are placed.
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flatten : bool, optional
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Remove singular levels of the folder hierarchy.
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This might be beneficial in case of single increment or field.
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Defaults to True.
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prune : bool, optional
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Remove branches with no data. Defaults to True.
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constituents : (list of) int, optional
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Constituents to consider.
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Defaults to None, in which case all constituents are considered.
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fill_float : float, optional
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Fill value for non-existent entries of floating point type.
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Defaults to NaN.
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fill_int : int, optional
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Fill value for non-existent entries of integer type.
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Defaults to 0.
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Returns
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-------
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data : dict of numpy.ma.MaskedArray
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Datasets structured by spatial position and according to selected view.
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"""
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r = {} # type: ignore
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constituents_ = list(map(int,constituents)) if isinstance(constituents,Iterable) else \
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(range(self.N_constituents) if constituents is None else [constituents]) # type: ignore
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suffixes = [''] if self.N_constituents == 1 or isinstance(constituents,int) else \
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[f'#{c}' for c in constituents_]
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at_cell_ph,in_data_ph,at_cell_ho,in_data_ho = self._mappings()
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with h5py.File(self.fname,'r') as f:
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for inc in util.show_progress(self.visible['increments']):
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r[inc] = {'phase':{},'homogenization':{},'geometry':{}}
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for out in _match(output,f['/'.join([inc,'geometry'])].keys()):
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r[inc]['geometry'][out] = ma.array(_read(f['/'.join([inc,'geometry',out])]),fill_value = fill_float)
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for ty in ['phase','homogenization']:
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for label in self.visible[ty+'s']:
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for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
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if field not in r[inc][ty].keys():
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r[inc][ty][field] = {}
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for out in _match(output,f['/'.join([inc,ty,label,field])].keys()):
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data = ma.array(_read(f['/'.join([inc,ty,label,field,out])]))
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if ty == 'phase':
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if out+suffixes[0] not in r[inc][ty][field].keys():
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for c,suffix in zip(constituents_,suffixes):
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r[inc][ty][field][out+suffix] = \
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_empty_like(data,self.N_materialpoints,fill_float,fill_int)
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for c,suffix in zip(constituents_,suffixes):
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r[inc][ty][field][out+suffix][at_cell_ph[c][label]] = data[in_data_ph[c][label]]
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if ty == 'homogenization':
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if out not in r[inc][ty][field].keys():
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r[inc][ty][field][out] = \
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_empty_like(data,self.N_materialpoints,fill_float,fill_int)
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r[inc][ty][field][out][at_cell_ho[label]] = data[in_data_ho[label]]
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if prune: r = util.dict_prune(r)
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if flatten: r = util.dict_flatten(r)
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return None if (type(r) == dict and r == {}) else r
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def export_simulation_setup_files(self,
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def export_simulation_setup(self,
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output: Union[str, List[str]] = '*',
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target_dir: Union[str, Path] = None,
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overwrite: bool = False,
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@ -1962,11 +1970,11 @@ class Result:
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----------
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output : (list of) str, optional
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Names of the datasets to export to the file.
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Defaults to '*', in which case all datasets are exported.
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Defaults to '*', in which case all setup files are exported.
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target_dir : str or pathlib.Path, optional
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Directory to save configuration files. Will be created if non-existent.
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Directory to save setup files. Will be created if non-existent.
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overwrite : bool, optional
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Overwrite existing configuration files.
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Overwrite any existing setup files.
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Defaults to False.
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"""
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@ -1982,27 +1990,16 @@ class Result:
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d = obj.attrs['description'] if h5py3 else obj.attrs['description'].decode()
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if overwrite or not cfg.exists():
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with util.open_text(cfg,'w') as f_out: f_out.write(obj[0].decode())
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print(f'Exported {d} to "{cfg}".')
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print(f'{d} --> "{cfg}"')
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else:
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print(f'"{cfg}" exists, {d} not exported.')
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print(f'{d} --x "{cfg}" exists!')
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elif type(obj) == h5py.Group:
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cfg.mkdir(parents=True,exist_ok=True)
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cfg_dir = (Path.cwd() if target_dir is None else Path(target_dir))
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cfg_dir = (Path.cwd() if target_dir is None else Path(target_dir))
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cfg_dir.mkdir(parents=True,exist_ok=True)
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with h5py.File(self.fname,'r') as f_in:
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f_in['setup'].visititems(partial(export,
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output=output,
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cfg_dir=cfg_dir,
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overwrite=overwrite))
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def list_simulation_setup_files(self):
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"""List available simulation setup files used to generate the Result object."""
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simulation_datasets = []
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def retrieve_dataset(name, node):
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simulation_datasets.append(name)
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with h5py.File(self.fname,'r') as f_in:
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f_in['setup'].visititems(retrieve_dataset)
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return simulation_datasets
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||||
|
|
|
|||
|
|
@ -543,30 +543,30 @@ class TestResult:
|
|||
'6grains6x7x8_single_phase_tensionY.hdf5'])
|
||||
@pytest.mark.parametrize('output',['material.yaml','*'])
|
||||
@pytest.mark.parametrize('overwrite',[True,False])
|
||||
def test_export_simulation_setup_files(self,ref_path,tmp_path,fname,output,overwrite):
|
||||
def test_export_simulation_setup(self,ref_path,tmp_path,fname,output,overwrite):
|
||||
r = Result(ref_path/fname)
|
||||
r.export_simulation_setup_files(output,target_dir=tmp_path)
|
||||
r.export_simulation_setup(output,target_dir=tmp_path)
|
||||
with h5py.File(ref_path/fname,'r') as f_hdf5:
|
||||
for file in fnmatch.filter(f_hdf5['setup'].keys(),output):
|
||||
with open(tmp_path/file) as f:
|
||||
assert f_hdf5[f'setup/{file}'][()][0].decode() == f.read()
|
||||
r.export_simulation_setup_files(output,target_dir=tmp_path,overwrite=overwrite)
|
||||
r.export_simulation_setup(output,target_dir=tmp_path,overwrite=overwrite)
|
||||
|
||||
def test_export_simulation_setup_files_custom_path(self,ref_path,tmp_path):
|
||||
def test_export_simulation_setup_custom_path(self,ref_path,tmp_path):
|
||||
src = ref_path/'4grains2x4x3_compressionY.hdf5'
|
||||
subdir = 'export_dir'
|
||||
absdir = tmp_path/subdir
|
||||
absdir.mkdir()
|
||||
absdir.mkdir(exist_ok=True)
|
||||
|
||||
r = Result(src)
|
||||
for t,cwd in zip([absdir,subdir,None],[tmp_path,tmp_path,absdir]):
|
||||
os.chdir(cwd)
|
||||
r.export_simulation_setup_files('material.yaml',target_dir=t)
|
||||
r.export_simulation_setup('material.yaml',target_dir=t)
|
||||
assert 'material.yaml' in os.listdir(absdir); (absdir/'material.yaml').unlink()
|
||||
|
||||
def test_list_simulation_setup_files(self,ref_path):
|
||||
def test_simulation_setup_files(self,ref_path):
|
||||
r = Result(ref_path/'4grains2x4x3_compressionY.hdf5')
|
||||
assert r.list_simulation_setup_files()==['4grains2x4x3.vti', 'compressionY.yaml', 'material.yaml']
|
||||
assert set(r.simulation_setup_files) == set(['4grains2x4x3.vti', 'compressionY.yaml', 'material.yaml'])
|
||||
|
||||
@pytest.mark.parametrize('fname',['4grains2x4x3_compressionY.hdf5',
|
||||
'6grains6x7x8_single_phase_tensionY.hdf5'])
|
||||
|
|
|
|||
Loading…
Reference in New Issue