visualizing data from DADF5: first prototype
This commit is contained in:
Martin Diehl
parent
7c771647ad
commit
6b7fd6b7ea
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@ -24,22 +24,23 @@ parser.add_argument('filenames', nargs='+',
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options = parser.parse_args()
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options.labels = ['Fe','Fp','xi_sl']
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# --- loop over input files ------------------------------------------------------------------------
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for filename in options.filenames:
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data = damask.DADF5(filename)
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results = damask.DADF5(filename)
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if data.structured: # for grid solvers use rectilinear grid
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if results.structured: # for grid solvers use rectilinear grid
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rGrid = vtk.vtkRectilinearGrid()
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coordArray = [vtk.vtkDoubleArray(),
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vtk.vtkDoubleArray(),
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vtk.vtkDoubleArray(),
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]
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rGrid.SetDimensions(*(data.grid+1))
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rGrid.SetDimensions(*(results.grid+1))
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for dim in [0,1,2]:
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for c in np.linspace(0,data.size[dim],1+data.grid[dim]):
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for c in np.linspace(0,results.size[dim],1+results.grid[dim]):
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coordArray[dim].InsertNextValue(c)
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rGrid.SetXCoordinates(coordArray[0])
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@ -47,22 +48,45 @@ for filename in options.filenames:
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rGrid.SetZCoordinates(coordArray[2])
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for i,inc in enumerate(data.increments):
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data.active['increments'] = [inc]
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x = data.get_dataset_location('xi_sl')[0]
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VTKarray = numpy_support.numpy_to_vtk(num_array=data.read_dataset(x,0),deep=True,array_type= vtk.VTK_DOUBLE)
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VTKarray.SetName('xi_sl')
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rGrid.GetCellData().AddArray(VTKarray)
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if data.structured:
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for i,inc in enumerate(results.increments):
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print('Output step {}/{}'.format(i+1,len(results.increments)))
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vtk_data = []
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results.active['increments'] = [inc]
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for label in options.labels:
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for o in results.c_output_types:
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results.active['c_output_types'] = [o]
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if o != 'generic':
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for c in results.constituents:
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results.active['constituents'] = [c]
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x = results.get_dataset_location(label)
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if len(x) == 0:
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continue
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array = results.read_dataset(x,0)
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shape = [array.shape[0],np.product(array.shape[1:])]
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vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),deep=True,array_type= vtk.VTK_DOUBLE))
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vtk_data[-1].SetName('1_'+x[0].split('/',1)[1])
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rGrid.GetCellData().AddArray(vtk_data[-1])
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else:
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results.active['constituents'] = results.constituents
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x = results.get_dataset_location(label)
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if len(x) == 0:
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continue
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array = results.read_dataset(x,0)
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shape = [array.shape[0],np.product(array.shape[1:])]
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vtk_data.append(numpy_support.numpy_to_vtk(num_array=array.reshape(shape),deep=True,array_type= vtk.VTK_DOUBLE))
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vtk_data[-1].SetName('1_'+x[0].split('/')[1]+'/generic/'+label)
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rGrid.GetCellData().AddArray(vtk_data[-1])
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if results.structured:
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writer = vtk.vtkXMLRectilinearGridWriter()
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writer.SetCompressorTypeToZLib()
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writer.SetDataModeToBinary()
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writer.SetFileName(os.path.join(os.path.split(filename)[0],
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os.path.splitext(os.path.split(filename)[1])[0] +
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'_inc{:04d}'.format(i) + # ToDo: adjust to lenght of increments
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'_inc{:04d}'.format(i) + # ToDo: adjust to length of increments
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'.' + writer.GetDefaultFileExtension()))
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if data.structured:
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if results.structured:
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writer.SetInputData(rGrid)
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writer.Write()
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@ -35,29 +35,56 @@ class DADF5():
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'time': round(f[u].attrs['time/s'],12),
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} for u in f.keys() if r.match(u)]
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self.constituents = np.unique(f['mapping/cellResults/constituent']['Name']).tolist() # ToDo: I am not to happy with the name
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self.constituents = [c.decode() for c in self.constituents]
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self.materialpoints = np.unique(f['mapping/cellResults/materialpoint']['Name']).tolist() # ToDo: I am not to happy with the name
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self.materialpoints = [m.decode() for m in self.materialpoints]
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self.Nconstitutents = np.shape(f['mapping/cellResults/constituent'])[1]
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self.Nmaterialpoints= np.shape(f['mapping/cellResults/constituent'])[0]
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self.constituents = np.unique(f['mapping/cellResults/constituent']['Name']).tolist() # ToDo: I am not to happy with the name
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self.constituents = [c.decode() for c in self.constituents]
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self.active= {'increments' :self.increments,
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'constituents' :self.constituents,
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'materialpoints':self.materialpoints}
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self.materialpoints = np.unique(f['mapping/cellResults/materialpoint']['Name']).tolist() # ToDo: I am not to happy with the name
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self.materialpoints = [m.decode() for m in self.materialpoints]
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self.Nconstituents = [i for i in range(np.shape(f['mapping/cellResults/constituent'])[1])]
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self.Nmaterialpoints = np.shape(f['mapping/cellResults/constituent'])[0]
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self.c_output_types = []
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for c in self.constituents:
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for o in f['inc{:05}/constituent/{}'.format(self.increments[0]['inc'],c)].keys():
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self.c_output_types.append(o)
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self.c_output_types = list(set(self.c_output_types)) # make unique
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self.active= {'increments': self.increments,
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'constituents': self.constituents,
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'materialpoints': self.materialpoints,
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'constituent': self.Nconstituents,
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'c_output_types': self.c_output_types}
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self.filename = filename
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self.mode = mode
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def list_data(self):
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"""Shows information on all datasets in the file"""
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with h5py.File(self.filename,'r') as f:
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group_inc = 'inc{:05}'.format(self.active['increments'][0]['inc'])
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for c in self.active['constituents']:
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print('\n'+c)
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group_constituent = group_inc+'/constituent/'+c
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for t in self.active['c_output_types']:
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print(' {}'.format(t))
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group_output_types = group_constituent+'/'+t
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try:
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for x in f[group_output_types].keys():
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print(' {} ({})'.format(x,f[group_output_types+'/'+x].attrs['Description'].decode()))
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except:
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pass
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def get_dataset_location(self,label):
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"""Returns the location of all active datasets with given label"""
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path = []
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with h5py.File(self.filename,'r') as f:
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for i in self.active['increments']:
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group_inc = 'inc{:05}'.format(i['inc'])
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for c in self.active['constituents']:
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group_constituent = group_inc+'/constituent/'+c
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for t in f[group_constituent].keys():
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for t in self.active['c_output_types']:
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try:
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f[group_constituent+'/'+t+'/'+label]
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path.append(group_constituent+'/'+t+'/'+label)
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@ -67,12 +94,20 @@ class DADF5():
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def read_dataset(self,path,c):
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"""
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Dataset for all points/cells
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If more than one path is given, the dataset is composed of the individual contributions
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"""
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with h5py.File(self.filename,'r') as f:
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shape = (self.Nmaterialpoints,) + np.shape(f[path])[1:]
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shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
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dataset = np.full(shape,np.nan)
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label = path.split('/')[2]
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p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))
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for s in p: dataset[s,:] = f[path][s,:]
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for pa in path:
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label = pa.split('/')[2]
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p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))[0]
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u = (f['mapping/cellResults/constituent'][p,c]['Position'])
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dataset[p,:] = f[pa][u,:]
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return dataset
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