99 lines
3.6 KiB
Python
Executable File
99 lines
3.6 KiB
Python
Executable File
#!/usr/bin/env python3
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import os
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import argparse
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import numpy as np
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import damask
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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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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = argparse.ArgumentParser()
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#ToDo: We need to decide on a way of handling arguments of variable lentght
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#https://stackoverflow.com/questions/15459997/passing-integer-lists-to-python
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#parser.add_argument('--version', action='version', version='%(prog)s {}'.format(scriptID))
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parser.add_argument('filenames', nargs='+',
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help='DADF5 files')
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parser.add_argument('-d','--dir', dest='dir',default='postProc',metavar='string',
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help='name of subdirectory to hold output')
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parser.add_argument('--mat', nargs='+',
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help='labels for materialpoint',dest='mat')
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parser.add_argument('--con', nargs='+',
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help='labels for constituent',dest='con')
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options = parser.parse_args()
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if options.mat is None: options.mat=[]
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if options.con is None: options.con=[]
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# --- loop over input files ------------------------------------------------------------------------
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for filename in options.filenames:
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results = damask.DADF5(filename)
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if not results.structured: continue
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delta = results.size/results.grid*0.5
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x, y, z = np.meshgrid(np.linspace(delta[2],results.size[2]-delta[2],results.grid[2]),
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np.linspace(delta[1],results.size[1]-delta[1],results.grid[1]),
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np.linspace(delta[0],results.size[0]-delta[0],results.grid[0]),
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indexing = 'ij')
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coords = np.concatenate((z[:,:,:,None],y[:,:,:,None],x[:,:,:,None]),axis = 3)
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for i,inc in enumerate(results.iter_visible('increments')):
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print('Output step {}/{}'.format(i+1,len(results.increments)))
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header = '1 header\n'
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data = np.array([int(inc[3:]) for j in range(np.product(results.grid))]).reshape([np.product(results.grid),1])
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header+= 'inc'
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coords = coords.reshape([np.product(results.grid),3])
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data = np.concatenate((data,coords),1)
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header+=' 1_pos 2_pos 3_pos'
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for label in options.con:
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for p in results.iter_visible('con_physics'):
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for c in results.iter_visible('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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d = int(np.product(np.shape(array)[1:]))
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data = np.concatenate((data,np.reshape(array,[np.product(results.grid),d])),1)
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if d>1:
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header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
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else:
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header+=' '+label
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for label in options.mat:
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for p in results.iter_visible('mat_physics'):
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for m in results.iter_visible('materialpoints'):
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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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d = int(np.product(np.shape(array)[1:]))
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data = np.concatenate((data,np.reshape(array,[np.product(results.grid),d])),1)
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if d>1:
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header+= ''.join([' {}_{}'.format(j+1,label) for j in range(d)])
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else:
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header+=' '+label
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dirname = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir))
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try:
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os.mkdir(dirname)
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except FileExistsError:
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pass
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file_out = '{}_{}.txt'.format(filename.split('.')[0],inc)
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np.savetxt(os.path.join(dirname,file_out),data,header=header,comments='')
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