140 lines
5.5 KiB
Python
Executable File
140 lines
5.5 KiB
Python
Executable File
#!/usr/bin/env python2.7
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# -*- coding: UTF-8 no BOM -*-
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# ------------------------------------------------------------------- #
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# NOTE: #
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# 1. Not all output is defined in the DS_HDF5.xml, please add new #
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# new one to the system wide definition file #
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# <DAMASK_ROOT>/lib/damask/DS_HDF5.xml #
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# or specify your own when initializing HDF5 class #
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# 2. Somehow the point cloud structure cannot be properly handled #
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# by Xdmf, which is a descriptive wrapper for visualizing HDF5 #
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# using Paraview. The current solution is using cell structured #
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# HDF5 so that Xdmf can describe the data shape as a rectangular #
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# mesh rather than polyvertex. #
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# TODO: #
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# 1. remove the <ASCII_TABLE>._tmp file, basically need a way to #
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# just load data from ASCII table. #
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# 2. a progress monitor when transferring data from ASCII table #
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# to HDF5. #
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# 3. a more flexible way handle the data structure rather than a #
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# xml file. #
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# ------------------------------------------------------------------- #
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import os
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import damask
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import numpy as np
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from optparse import OptionParser
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName, damask.version])
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# ----- helper function ----- #
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def get_rectMshVectors(xyz_array, posNum):
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"""Get Vx, Vy, Vz for rectLinear grid"""
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# need some improvement, and only works for rectangular grid
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v = sorted(list(set(xyz_array[:, posNum])))
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v_interval = (v[2]+v[1])/2.0 - (v[1]+v[0])/2.0
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v_start = (v[1]+v[0])/2.0 - v_interval
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v_end = (v[-1]+v[-2])/2.0 + v_interval
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V = np.linspace(v_start, v_end, len(v)+1)
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return V
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# ----- MAIN ---- #
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desp_msg = "Convert DAMASK ascii table to HDF5 file"
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parser = OptionParser(option_class=damask.extendableOption,
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usage='%prog options [file[s]]',
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description=desp_msg,
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version=scriptID)
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parser.add_option('-D', '--DefinitionFile',
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dest='storage definition file',
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type='string',
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metavar='string',
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help='definition file for H5 data storage')
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parser.add_option('-p', '--pos', '--position',
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dest='pos',
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type='string', metavar='string',
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help='label of coordinates [%default]')
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parser.set_defaults(DefinitionFile='default',
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pos='pos')
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(options, filenames) = parser.parse_args()
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filename = filenames[0]
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if options.DefinitionFile == 'default':
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defFile = None
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else:
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defFile = options.DefinitionFile
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# ----- read in data using DAMASK ASCII table class ----- #
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asciiTable = damask.ASCIItable(name=filename, buffered=False)
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asciiTable.head_read()
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asciiTable.data_readArray()
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incNum = int(asciiTable.data[asciiTable.label_index('inc'), 0])
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fullTable = np.copy(asciiTable.data) # deep copy all data, just to be safe
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labels = asciiTable.labels()
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labels_idx = [asciiTable.label_index(label) for label in labels]
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featuresDim = [labels_idx[i+1] - labels_idx[i] for i in xrange(len(labels)-1)]
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featuresDim.append(fullTable.shape[1] - labels_idx[-1])
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# ----- figure out size and grid ----- #
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pos_idx = asciiTable.label_index('pos')
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xyz_array = asciiTable.data[:, pos_idx:pos_idx+3]
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Vx = get_rectMshVectors(xyz_array, 0)
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Vy = get_rectMshVectors(xyz_array, 1)
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Vz = get_rectMshVectors(xyz_array, 2)
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# use the dimension of the rectangular grid to reshape all other data
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mshGridDim = [len(Vx)-1, len(Vy)-1, len(Vz)-1]
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# ----- create a new HDF5 file and save the data -----#
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# force remove existing HDF5 file
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h5fName = filename.replace(".txt", ".h5")
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try:
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os.remove(h5fName)
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except OSError:
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pass
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h5f = damask.H5Table(h5fName,
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new_file=True,
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dsXMLFile=defFile)
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# adding increment number as root level attributes
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h5f.add_attr('inc', incNum)
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# add the mesh grid data now
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h5f.add_data("Vx", Vx)
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h5f.add_data("Vy", Vy)
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h5f.add_data("Vz", Vz)
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# add the rest of data from table
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labelsProcessed = ['inc']
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for fi in xrange(len(labels)):
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featureName = labels[fi]
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# remove trouble maker "("" and ")" from label/feature name
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if "(" in featureName:
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featureName = featureName.replace("(", "")
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if ")" in featureName:
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featureName = featureName.replace(")", "")
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# skip increment and duplicated columns in the ASCII table
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if featureName in labelsProcessed:
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continue
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featureIdx = labels_idx[fi]
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featureDim = featuresDim[fi]
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# grab the data hook
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dataset = fullTable[:, featureIdx:featureIdx+featureDim]
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# mapping 2D data onto a 3D rectangular mesh to get 4D data
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# WARNING: In paraview, the data for a recmesh is mapped as:
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# --> len(z), len(y), len(x), size(data)
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# dataset = dataset.reshape((mshGridDim[0],
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# mshGridDim[1],
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# mshGridDim[2],
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# dataset.shape[1]))
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# write out data
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print "adding {}...".format(featureName)
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h5f.add_data(featureName, dataset)
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# write down the processed label
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labelsProcessed.append(featureName)
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