* quick fix in order to make it work for elements of type 57 (quadratic with reduced integration)
* length for results of type "elemental tensor" is exactly 7
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@ -264,6 +264,14 @@ def ipCoords(elemType, nodalCoordinates):
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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57: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0],
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[ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0],
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[ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0],
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[ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0],
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[ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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117: [ [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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117: [ [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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[ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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[ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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[ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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[ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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@ -283,8 +291,9 @@ def ipCoords(elemType, nodalCoordinates):
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[ 5.0, 5.0, 14.0, 15.0, 15.0, 42.0] ],
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[ 5.0, 5.0, 14.0, 15.0, 15.0, 42.0] ],
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}
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}
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ipCoordinates = [[0.0,0.0,0.0] for i in range(len(nodalCoordinates))]
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Nips = len(nodeWeightsPerNode[elemType])
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for ip in range(len(nodeWeightsPerNode[elemType])):
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ipCoordinates = [[0.0,0.0,0.0] for i in range(Nips)]
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for ip in range(Nips):
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for node in range(len(nodeWeightsPerNode[elemType][ip])):
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for node in range(len(nodeWeightsPerNode[elemType][ip])):
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for i in range(3):
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for i in range(3):
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ipCoordinates[ip][i] += nodeWeightsPerNode[elemType][ip][node] * nodalCoordinates[node][i]
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ipCoordinates[ip][i] += nodeWeightsPerNode[elemType][ip][node] * nodalCoordinates[node][i]
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@ -804,11 +813,15 @@ if options.nodalScalar:
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else:
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else:
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for e in xrange(stat['NumberOfElements']):
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for e in xrange(stat['NumberOfElements']):
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if p.element(e).type == 57:
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myNodeIDs = p.element(e).items[:8]
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else:
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myNodeIDs = p.element(e).items
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if e%1000 == 0:
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if e%1000 == 0:
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bg.set_message('scan elem %i...'%e)
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bg.set_message('scan elem %i...'%e)
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myElemID = p.element_id(e)
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myElemID = p.element_id(e)
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myIpCoordinates = ipCoords(p.element(e).type, map(lambda node: [node.x, node.y, node.z], map(p.node, map(p.node_sequence,p.element(e).items))))
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myIpCoordinates = ipCoords(p.element(e).type, map(lambda node: [node.x, node.y, node.z], map(p.node, map(p.node_sequence,myNodeIDs))))
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for n,myNodeID in enumerate(p.element(e).items):
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for n,myNodeID in enumerate(myNodeIDs):
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for g in range(('GrainCount' in stat['IndexOfLabel'] and int(p.element_scalar(e, stat['IndexOfLabel']['GrainCount'])[0].value))
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for g in range(('GrainCount' in stat['IndexOfLabel'] and int(p.element_scalar(e, stat['IndexOfLabel']['GrainCount'])[0].value))
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or 1):
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or 1):
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myGrainID = g + 1
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myGrainID = g + 1
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@ -929,7 +942,7 @@ for incCount,increment in enumerate(increments):
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header += heading('.',[[label.replace(' ',''),component] for component in ['intensity','t11','t22','t33','t12','t23','t13']])
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header += heading('.',[[label.replace(' ',''),component] for component in ['intensity','t11','t22','t33','t12','t23','t13']])
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myTensor = p.element_tensor(p.element_sequence(e),stat['IndexOfLabel'][label])[n_local]
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myTensor = p.element_tensor(p.element_sequence(e),stat['IndexOfLabel'][label])[n_local]
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newby.append({'label':label,
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newby.append({'label':label,
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'len':length,
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'len':7,
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'content':[ myTensor.intensity,
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'content':[ myTensor.intensity,
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myTensor.t11, myTensor.t22, myTensor.t33,
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myTensor.t11, myTensor.t22, myTensor.t33,
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myTensor.t12, myTensor.t23, myTensor.t13,
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myTensor.t12, myTensor.t23, myTensor.t13,
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