Merge branch 'development' of magit1.mpie.de:damask/DAMASK into incs-no-leading-zero

.gitlab-ci.yml

@@ -1,6 +1,7 @@
 ---
 stages:
   - prepareAll
+  - python
   - preprocessing
   - postprocessing
   - compilePETSc
@@ -103,6 +104,16 @@ checkout:
     - master
     - release
 
+###################################################################################################
+Pytest:
+  stage: python
+  script:
+    - cd $DAMASKROOT/python
+    - pytest
+  except:
+    - master
+    - release
+
 ###################################################################################################
 OrientationRelationship:
   stage: preprocessing

VERSION

@@ -1 +1 @@
-v2.0.3-1133-gfede8225
+v2.0.3-1136-gcc67f0e1

processing/post/DADF5toDREAM3D.py

@@ -49,7 +49,7 @@ Phase_types = {'Primary': 0} #further additions to these can be done by looking
 # --------------------------------------------------------------------
 parser = argparse.ArgumentParser(description='Creating a file for DREAM3D from DAMASK data')
 parser.add_argument('filenames',nargs='+',help='HDF5 based output file')
-parser.add_argument('--inc',nargs='+',help='Increment for which DREAM3D to be used, eg. 00025',type=int)
+parser.add_argument('--inc',nargs='+',help='Increment for which DREAM3D to be used, eg. 25',type=int)
 parser.add_argument('-d','--dir', dest='dir',default='postProc',metavar='string',
                     help='name of subdirectory to hold output')
 
@@ -59,15 +59,13 @@ options = parser.parse_args()
 # loop over input files
 for filename in options.filenames:
   f = damask.DADF5(filename)  #DAMASK output file
-  count = 0
+  for increment in options.inc:
-  for increment in f.increments:
+    f.set_by_increment(increment,increment)
-    if int(increment[3:]) not in options.inc: 
+    if len(f.visible['increments']) == 0:
-      count = count + 1
       continue
 
     #-------output file creation-------------------------------------
     dirname  = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir))
-    print(dirname)
     try:
       os.mkdir(dirname)
     except FileExistsError:
@@ -90,11 +88,10 @@ for filename in options.filenames:
     # Phase information of DREAM.3D is constituent ID in DAMASK
     o[cell_data_label + '/Phases'] = f.get_constituent_ID().reshape(tuple(f.grid)+(1,))  
     # Data quaternions
-    DAMASK_quaternion = f.read_dataset(f.get_dataset_location('orientation'),0)
+    DAMASK_quaternion = f.read_dataset(f.get_dataset_location('orientation'))
-    DREAM_3D_quaternion = np.empty((np.prod(f.grid),4),dtype=np.float32)
     # Convert: DAMASK uses P = -1, DREAM.3D uses P = +1. Also change position of imagninary part
     DREAM_3D_quaternion = np.hstack((-DAMASK_quaternion['x'],-DAMASK_quaternion['y'],-DAMASK_quaternion['z'],
-                                      DAMASK_quaternion['w']))
+                                      DAMASK_quaternion['w'])).astype(np.float32)
     o[cell_data_label + '/Quats'] = DREAM_3D_quaternion.reshape(tuple(f.grid)+(4,))
     
     # Attributes to CellData group
@@ -109,12 +106,14 @@ for filename in options.filenames:
     # phase attributes
     o[cell_data_label + '/Phases'].attrs['ComponentDimensions'] = np.array([1],np.uint64)
     o[cell_data_label + '/Phases'].attrs['ObjectType']          = 'DataArray<int32_t>'
+    o[cell_data_label + '/Phases'].attrs['TupleDimensions']     = f.grid.astype(np.uint64)
     
     # Quats attributes
     o[cell_data_label + '/Quats'].attrs['ComponentDimensions'] = np.array([4],np.uint64)
     o[cell_data_label + '/Quats'].attrs['ObjectType']          = 'DataArray<float>'        
-
+    o[cell_data_label + '/Quats'].attrs['TupleDimensions']     = f.grid.astype(np.uint64)
-    # Create EnsembleAttributeMatrix
+   
+   # Create EnsembleAttributeMatrix
     ensemble_label = data_container_label + '/EnsembleAttributeMatrix' 
     
     # Data CrystalStructures

processing/post/addCauchy.py

@@ -2,10 +2,9 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
-import numpy as np
-
 import damask
 
 
@@ -36,54 +35,15 @@ parser.set_defaults(defgrad = 'f',
                    )
 
 (options,filenames) = parser.parse_args()
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name, buffered = False)
-  except:
-    continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    table.add('Cauchy',
+              damask.mechanics.Cauchy(table.get(options.defgrad).reshape(-1,3,3),
+                                      table.get(options.stress ).reshape(-1,3,3)).reshape(-1,9),
+              scriptID+' '+' '.join(sys.argv[1:]))
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-
-# ------------------------------------------ sanity checks ----------------------------------------
-
-  errors = []
-  column = {}
-  
-  for tensor in [options.defgrad,options.stress]:
-    dim = table.label_dimension(tensor)
-    if   dim <  0: errors.append('column {} not found.'.format(tensor))
-    elif dim != 9: errors.append('column {} is not a tensor.'.format(tensor))
-    else:
-      column[tensor] = table.label_index(tensor)
-
-  if errors != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header --------------------------------------
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.labels_append(['{}_Cauchy'.format(i+1) for i in range(9)])                                  # extend ASCII header with new labels
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    F = np.array(list(map(float,table.data[column[options.defgrad]:column[options.defgrad]+9])),'d').reshape(3,3)
-    P = np.array(list(map(float,table.data[column[options.stress ]:column[options.stress ]+9])),'d').reshape(3,3)
-    table.data_append(list(1.0/np.linalg.det(F)*np.dot(P,F.T).reshape(9)))                          # [Cauchy] = (1/det(F)) * [P].[F_transpose]
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/addDeterminant.py

@@ -2,22 +2,16 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
+import numpy as np
+
 import damask
 
-
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
-def determinant(m):
-  return  +m[0]*m[4]*m[8] \
-          +m[1]*m[5]*m[6] \
-          +m[2]*m[3]*m[7] \
-          -m[2]*m[4]*m[6] \
-          -m[1]*m[3]*m[8] \
-          -m[0]*m[5]*m[7]
-
 
 # --------------------------------------------------------------------
 #                                MAIN
@@ -34,61 +28,18 @@ parser.add_option('-t','--tensor',
                   help = 'heading of columns containing tensor field values')
 
 (options,filenames) = parser.parse_args()
+if filenames == []: filenames = [None]
 
 if options.tensor is None:
   parser.error('no data column specified.')
 
-# --- loop over input files -------------------------------------------------------------------------
-
-if filenames == []: filenames = [None]
-
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name,
-                              buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    for tensor in options.tensor:
+         table.add('det({})'.format(tensor),
+                   np.linalg.det(table.get(tensor).reshape(-1,3,3)),
+                   scriptID+' '+' '.join(sys.argv[1:]))
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-
-# ------------------------------------------ sanity checks ----------------------------------------
-
-  items = {
-            'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.tensor, 'column': []},
-          }
-  errors  = []
-  remarks = []
-  
-  for type, data in items.items():
-    for what in data['labels']:
-      dim = table.label_dimension(what)
-      if dim != data['dim']: remarks.append('column {} is not a {}...'.format(what,type))
-      else:
-        items[type]['column'].append(table.label_index(what))
-        table.labels_append('det({})'.format(what))                                                 # extend ASCII header with new labels
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header --------------------------------------
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    for type, data in items.items():
-      for column in data['column']:
-        table.data_append(determinant(list(map(float,table.data[column: column+data['dim']]))))
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/addDeviator.py

@@ -2,6 +2,7 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
 import damask
@@ -9,17 +10,6 @@ import damask
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
-oneThird = 1.0/3.0
-
-def deviator(m,spherical = False):                                                                  # Careful, do not change the value of m, its intent(inout)!
-  sph = oneThird*(m[0]+m[4]+m[8])
-  dev = [
-           m[0]-sph,  m[1],     m[2],
-           m[3],      m[4]-sph, m[5],
-           m[6],      m[7],     m[8]-sph,
-        ]
-  return dev,sph if spherical else dev
-
 
 # --------------------------------------------------------------------
 #                                MAIN
@@ -40,67 +30,22 @@ parser.add_option('-s','--spherical',
                   help = 'report spherical part of tensor (hydrostatic component, pressure)')
 
 (options,filenames) = parser.parse_args()
-
-if options.tensor is None:
-  parser.error('no data column specified...')
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
+if options.tensor is None:
+    parser.error('no data column specified...')
+
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name, buffered = False)
+    
-  except:
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
-    continue
+    for tensor in options.tensor:
-  damask.util.report(scriptName,name)
+         table.add('dev({})'.format(tensor),
+                   damask.mechanics.deviatoric_part(table.get(tensor).reshape(-1,3,3)).reshape((-1,9)),
+                   scriptID+' '+' '.join(sys.argv[1:]))
+         if options.spherical:
+             table.add('sph({})'.format(tensor),
+                       damask.mechanics.spherical_part(table.get(tensor).reshape(-1,3,3)),
+                       scriptID+' '+' '.join(sys.argv[1:]))
 
-# ------------------------------------------ read header ------------------------------------------
+    table.to_ASCII(sys.stdout if name is None else name)
-
-  table.head_read()
-
-# ------------------------------------------ sanity checks ----------------------------------------
-
-  items = {
-            'tensor': {'dim': 9, 'shape': [3,3], 'labels':options.tensor, 'active':[], 'column': []},
-          }
-  errors  = []
-  remarks = []
-  column = {}
-  
-  for type, data in items.items():
-    for what in data['labels']:
-      dim = table.label_dimension(what)
-      if dim != data['dim']: remarks.append('column {} is not a {}.'.format(what,type))
-      else:
-        items[type]['active'].append(what)
-        items[type]['column'].append(table.label_index(what))
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header --------------------------------------
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  for type, data in items.items():
-    for label in data['active']:
-      table.labels_append(['{}_dev({})'.format(i+1,label) for i in range(data['dim'])] + \
-                         (['sph({})'.format(label)] if options.spherical else []))                  # extend ASCII header with new labels
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    for type, data in items.items():
-      for column in data['column']:
-        table.data_append(deviator(list(map(float,table.data[column:
-                                                        column+data['dim']])),options.spherical))
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/addInfo.py

@@ -1,6 +1,8 @@
 #!/usr/bin/env python3
 
 import os
+import sys
+from io import StringIO
 from optparse import OptionParser
 
 import damask
@@ -24,35 +26,16 @@ parser.add_option('-i',
                   dest = 'info', action = 'extend', metavar = '<string LIST>',
                   help    = 'items to add')
 
-
 (options,filenames) = parser.parse_args()
+if filenames == []: filenames = [None]
 
 if options.info is None:
   parser.error('no info specified.')
 
-# --- loop over input files ------------------------------------------------------------------------
-
-if filenames == []: filenames = [None]
-
 for name in filenames:
-  try:    table = damask.ASCIItable(name = name,
+    damask.util.report(scriptName,name)
-                                    buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ assemble header ---------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    table.comments += options.info
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-  table.info_append(options.info)
-  table.head_write()
-
-# ------------------------------------------ pass through data -------------------------------------
-
-  outputAlive = True
-
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close ASCII tables

processing/post/addMises.py

@@ -2,10 +2,8 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
-from collections import OrderedDict
-
-import numpy as np
 
 import damask
 
@@ -13,15 +11,6 @@ import damask
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
-def Mises(what,tensor):
-
-  dev = tensor - np.trace(tensor)/3.0*np.eye(3)
-  symdev = 0.5*(dev+dev.T)
-  return np.sqrt(np.sum(symdev*symdev.T)*
-        {
-         'stress': 3.0/2.0,
-         'strain': 2.0/3.0,
-         }[what.lower()])
 
 # --------------------------------------------------------------------
 #                                MAIN
@@ -47,62 +36,21 @@ parser.set_defaults(strain = [],
 (options,filenames) = parser.parse_args()
 
 if options.stress is [] and options.strain is []:
-  parser.error('no data column specified...')
+    parser.error('no data column specified...')
-
-# --- loop over input files -------------------------------------------------------------------------
 
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name,
-                              buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
-
+    for strain in options.strain:
-  table.head_read()
+        table.add('Mises({})'.format(strain),
-
+                  damask.mechanics.Mises_strain(damask.mechanics.symmetric(table.get(strain).reshape(-1,3,3))),
-# ------------------------------------------ sanity checks ----------------------------------------
+                  scriptID+' '+' '.join(sys.argv[1:]))
-
+    for stress in options.stress:
-  items = OrderedDict([
+        table.add('Mises({})'.format(stress),
-            ('strain', {'dim': 9, 'shape': [3,3], 'labels':options.strain, 'active':[], 'column': []}),
+                  damask.mechanics.Mises_stress(damask.mechanics.symmetric(table.get(stress).reshape(-1,3,3))),
-            ('stress', {'dim': 9, 'shape': [3,3], 'labels':options.stress, 'active':[], 'column': []})
+                  scriptID+' '+' '.join(sys.argv[1:]))
-          ])
+    
-  errors  = []
+    table.to_ASCII(sys.stdout if name is None else name)
-  remarks = []
-  
-  for type, data in items.items():
-    for what in data['labels']:
-      dim = table.label_dimension(what)
-      if dim != data['dim']: remarks.append('column {} is not a {}...'.format(what,type))
-      else:
-        items[type]['active'].append(what)
-        items[type]['column'].append(table.label_index(what))
-        table.labels_append('Mises({})'.format(what))                                               # extend ASCII header with new labels
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header --------------------------------------
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    for type, data in items.items():
-      for column in data['column']:
-        table.data_append(Mises(type,
-                                np.array(table.data[column:column+data['dim']],'d').reshape(data['shape'])))
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/addPK2.py

@@ -2,10 +2,9 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
-import numpy as np
-
 import damask
 
 
@@ -36,53 +35,16 @@ parser.set_defaults(defgrad = 'f',
                    )
 
 (options,filenames) = parser.parse_args()
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name,
-                              buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
 
-  table.head_read()
+    table.add('S',
+              damask.mechanics.PK2(table.get(options.defgrad).reshape(-1,3,3),
+                                   table.get(options.stress ).reshape(-1,3,3)).reshape(-1,9),
+              scriptID+' '+' '.join(sys.argv[1:]))
 
-# ------------------------------------------ sanity checks ----------------------------------------
+    table.to_ASCII(sys.stdout if name is None else name)
-
-  errors = []
-  column = {}
-  
-  for tensor in [options.defgrad,options.stress]:
-    dim = table.label_dimension(tensor)
-    if   dim <  0: errors.append('column {} not found.'.format(tensor))
-    elif dim != 9: errors.append('column {} is not a tensor.'.format(tensor))
-    else:
-      column[tensor] = table.label_index(tensor)
-
-  if errors != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header --------------------------------------
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.labels_append(['{}_S'.format(i+1) for i in range(9)])                                       # extend ASCII header with new labels
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    F = np.array(list(map(float,table.data[column[options.defgrad]:column[options.defgrad]+9])),'d').reshape(3,3)
-    P = np.array(list(map(float,table.data[column[options.stress ]:column[options.stress ]+9])),'d').reshape(3,3)
-    table.data_append(list(np.dot(np.linalg.inv(F),P).reshape(9)))                                  # [S] =[P].[F-1]
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------
-
-  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/reLabel.py

@@ -2,8 +2,8 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
-import re
 
 import damask
 
@@ -35,62 +35,18 @@ parser.set_defaults(label = [],
                    )
 
 (options,filenames) = parser.parse_args()
-
-pattern = [re.compile('^()(.+)$'),                                                                # label pattern for scalar
-           re.compile('^(\d+_)?(.+)$'),                                                           # label pattern for multidimension
-          ]
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
+if len(options.label) != len(options.substitute):
+    parser.error('number of column labels and substitutes do not match.')
+
 for name in filenames:
-  try:    table = damask.ASCIItable(name = name,
+    damask.util.report(scriptName,name)
-                                    buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------  
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    for i,label in enumerate(options.label):
+        table.rename(label,
+                     options.substitute[i],
+                     scriptID+' '+' '.join(sys.argv[1:]))
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-
-# ------------------------------------------ process labels ---------------------------------------  
-
-  errors  = []
-  remarks = []
-
-  if len(options.label) == 0:
-    errors.append('no labels specified.')
-  elif len(options.label) != len(options.substitute):
-    errors.append('mismatch between number of labels ({}) and substitutes ({}).'.format(len(options.label),
-                                                                                        len(options.substitute)))
-  else:
-    indices    = table.label_index    (options.label)
-    dimensions = table.label_dimension(options.label)
-    for i,index in enumerate(indices):
-      if index == -1: remarks.append('label "{}" not present...'.format(options.label[i]))
-      else:
-        m = pattern[int(dimensions[i]>1)].match(table.tags[index])                                  # isolate label name
-        for j in range(dimensions[i]):
-          table.tags[index+j] = table.tags[index+j].replace(m.group(2),options.substitute[i])       # replace name with substitute
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-
-# ------------------------------------------ assemble header ---------------------------------------  
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------  
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------  
-
-  table.close()                                                                                     # close ASCII tables

processing/post/scaleData.py

@@ -2,10 +2,9 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
-import numpy as np
-
 import damask
 
 
@@ -23,7 +22,7 @@ Uniformly scale column values by given factor.
 """, version = scriptID)
 
 parser.add_option('-l','--label',
-                  dest = 'label',
+                  dest = 'labels',
                   action = 'extend', metavar = '<string LIST>',
                   help  ='column(s) to scale')
 parser.add_option('-f','--factor',
@@ -32,61 +31,21 @@ parser.add_option('-f','--factor',
                   help = 'factor(s) per column')
 
 parser.set_defaults(label  = [],
-                   )
+                    factor = [])
 
 (options,filenames) = parser.parse_args()
-
-if len(options.label) != len(options.factor):
-  parser.error('number of column labels and factors do not match.')
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
+if len(options.labels) != len(options.factor):
+    parser.error('number of column labels and factors do not match.')
+
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name,
-                              buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    for i,label in enumerate(options.labels):
+        table.set(label,
+                  table.get(label)*float(options.factor[i]),
+                  scriptID+' '+' '.join(sys.argv[1:]))
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-
-  errors  = []
-  remarks = []
-  columns  = []
-  dims     = []
-  factors  = []
-
-  for what,factor in zip(options.label,options.factor):
-    col = table.label_index(what)
-    if col < 0: remarks.append('column {} not found...'.format(what,type))
-    else:
-      columns.append(col)
-      factors.append(float(factor))
-      dims.append(table.label_dimension(what))
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-       
-# ------------------------------------------ assemble header ---------------------------------------  
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    for col,dim,factor in zip(columns,dims,factors):                                                # loop over items
-      table.data[col:col+dim] = factor * np.array(table.data[col:col+dim],'d')
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------  
-
-  table.close()                                                                                     # close ASCII tables

processing/post/shiftData.py

@@ -2,10 +2,9 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
-import numpy as np
-
 import damask
 
 
@@ -23,7 +22,7 @@ Uniformly shift column values by given offset.
 """, version = scriptID)
 
 parser.add_option('-l','--label',
-                  dest = 'label',
+                  dest = 'labels',
                   action = 'extend', metavar = '<string LIST>',
                   help  ='column(s) to shift')
 parser.add_option('-o','--offset',
@@ -32,61 +31,21 @@ parser.add_option('-o','--offset',
                   help = 'offset(s) per column')
 
 parser.set_defaults(label  = [],
-                   )
+                    offset = [])
 
 (options,filenames) = parser.parse_args()
-
-if len(options.label) != len(options.offset):
-  parser.error('number of column labels and offsets do not match.')
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
+if len(options.labels) != len(options.offset):
+    parser.error('number of column labels and offsets do not match.')
+
 for name in filenames:
-  try:
+    damask.util.report(scriptName,name)
-    table = damask.ASCIItable(name = name,
-                              buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ read header ------------------------------------------
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    for i,label in enumerate(options.labels):
+        table.set(label,
+                  table.get(label)+float(options.offset[i]),
+                  scriptID+' '+' '.join(sys.argv[1:]))
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-
-  errors  = []
-  remarks = []
-  columns  = []
-  dims     = []
-  offsets  = []
-
-  for what,offset in zip(options.label,options.offset):
-    col = table.label_index(what)
-    if col < 0: remarks.append('column {} not found...'.format(what,type))
-    else:
-      columns.append(col)
-      offsets.append(float(offset))
-      dims.append(table.label_dimension(what))
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors  != []:
-    damask.util.croak(errors)
-    table.close(dismiss = True)
-    continue
-       
-# ------------------------------------------ assemble header ---------------------------------------  
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    for col,dim,offset in zip(columns,dims,offsets):                                                # loop over items
-      table.data[col:col+dim] = offset + np.array(table.data[col:col+dim],'d')
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------  
-
-  table.close()                                                                                     # close ASCII tables

processing/post/sortTable.py

@@ -2,10 +2,9 @@
 
 import os
 import sys
+from io import StringIO
 from optparse import OptionParser
 
-import numpy as np
-
 import damask
 
 
@@ -26,7 +25,7 @@ With coordinates in columns "x", "y", and "z"; sorting with x slowest and z fast
 
 
 parser.add_option('-l','--label',
-                  dest   = 'keys',
+                  dest   = 'labels',
                   action = 'extend', metavar = '<string LIST>',
                   help   = 'list of column labels (a,b,c,...)')
 parser.add_option('-r','--reverse',
@@ -38,42 +37,14 @@ parser.set_defaults(reverse = False,
                    )
 
 (options,filenames) = parser.parse_args()
-
-
-# --- loop over input files -------------------------------------------------------------------------
-
 if filenames == []: filenames = [None]
 
+if options.labels is None:
+    parser.error('no labels specified.')
 for name in filenames:
-  try:    table = damask.ASCIItable(name = name,
+    damask.util.report(scriptName,name)
-                                    buffered = False)
-  except: continue
-  damask.util.report(scriptName,name)
 
-# ------------------------------------------ assemble header ---------------------------------------  
+    table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
+    table.sort_by(options.labels,not options.reverse)
 
-  table.head_read()
+    table.to_ASCII(sys.stdout if name is None else name)
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data ---------------------------------------  
-
-  table.data_readArray()
-
-  keys = table.labels(raw = True)[::-1] if options.keys is None else options.keys[::-1]             # numpy sorts with most significant column as last
-
-  cols    = []
-  remarks = []
-  for i,column in enumerate(table.label_index(keys)):
-    if column < 0: remarks.append('label "{}" not present...'.format(keys[i]))
-    else:          cols += [table.data[:,column]]
-  if remarks != []: damask.util.croak(remarks)
-  
-  ind = np.lexsort(cols) if cols != [] else np.arange(table.data.shape[0])
-  if options.reverse: ind = ind[::-1]
-
-# ------------------------------------------ output result ---------------------------------------  
-
-  table.data = table.data[ind]
-  table.data_writeArray()
-  table.close()                                                                                     # close ASCII table

python/damask/__init__.py

@@ -9,6 +9,7 @@ name = 'damask'
 # classes
 from .environment import Environment      # noqa
 from .asciitable  import ASCIItable       # noqa
+from .table       import Table            # noqa
     
 from .config      import Material         # noqa
 from .colormaps   import Colormap, Color  # noqa

python/damask/dadf5.py

@@ -18,17 +18,17 @@ class DADF5():
   """
   
 # ------------------------------------------------------------------
-  def __init__(self,filename):
+  def __init__(self,fname):
     """
     Opens an existing DADF5 file.
     
     Parameters
     ----------
-    filename : str
+    fname : str
         name of the DADF5 file to be openend.
     
     """
-    with h5py.File(filename,'r') as f:
+    with h5py.File(fname,'r') as f:
       
       try:
         self.version_major = f.attrs['DADF5_version_major']
@@ -72,7 +72,7 @@ class DADF5():
                    'con_physics':    self.con_physics,
                    'mat_physics':    self.mat_physics}
                   
-    self.filename   = filename
+    self.fname = fname
 
 
   def __manage_visible(self,datasets,what,action):
@@ -315,7 +315,7 @@ class DADF5():
 
     groups = []
     
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
       for i in self.iter_visible('increments'):
         for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
           for oo in self.iter_visible(o):
@@ -332,9 +332,9 @@ class DADF5():
   def list_data(self):
     """Return information on all active datasets in the file."""
     message = ''
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
-      for i in self.iter_visible('increments'):
+      for s,i in enumerate(self.iter_visible('increments')):
-        message+='\n{} ({}s)\n'.format(i,self.times[self.increments.index(i)])
+        message+='\n{} ({}s)\n'.format(i,self.times[s])
         for o,p in zip(['constituents','materialpoints'],['con_physics','mat_physics']):
           for oo in self.iter_visible(o):
             message+='  {}\n'.format(oo)
@@ -353,7 +353,7 @@ class DADF5():
   def get_dataset_location(self,label):
     """Return the location of all active datasets with given label."""
     path = []
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
       for i in self.iter_visible('increments'):
         k = '/'.join([i,'geometry',label])
         try:
@@ -375,14 +375,14 @@ class DADF5():
     
   def get_constituent_ID(self,c=0):
     """Pointwise constituent ID."""
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
       names = f['/mapping/cellResults/constituent']['Name'][:,c].astype('str')
     return np.array([int(n.split('_')[0]) for n in names.tolist()],dtype=np.int32)
 
 
   def get_crystal_structure(self):                                                                  # ToDo: extension to multi constituents/phase
     """Info about the crystal structure."""
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
       return f[self.get_dataset_location('orientation')[0]].attrs['Lattice'].astype('str')          # np.bytes_ to string
 
 
@@ -392,7 +392,7 @@ class DADF5():
     
     If more than one path is given, the dataset is composed of the individual contributions.
     """
-    with h5py.File(self.filename,'r') as f:
+    with h5py.File(self.fname,'r') as f:
       shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
       if len(shape) == 1: shape = shape +(1,)
       dataset = np.full(shape,np.nan,dtype=np.dtype(f[path[0]]))
@@ -435,7 +435,7 @@ class DADF5():
                            )
       return np.concatenate((x[:,:,:,None],y[:,:,:,None],y[:,:,:,None]),axis = 3).reshape([np.product(self.grid),3])
     else:
-      with h5py.File(self.filename,'r') as f:
+      with h5py.File(self.fname,'r') as f:
         return f['geometry/x_c'][()]
     
     
@@ -815,7 +815,7 @@ class DADF5():
     todo = []
     # ToDo: It would be more memory efficient to read only from file when required, i.e. do to it in pool.add_task
     for group in self.groups_with_datasets([d['label'] for d in datasets_requested]):
-      with h5py.File(self.filename,'r') as f:
+      with h5py.File(self.fname,'r') as f:
         datasets_in = {}
         for d in datasets_requested:
           loc  = f[group+'/'+d['label']]
@@ -830,7 +830,7 @@ class DADF5():
     N_not_calculated = len(todo)
     while N_not_calculated > 0:    
       result = results.get()
-      with h5py.File(self.filename,'a') as f:                                                       # write to file
+      with h5py.File(self.fname,'a') as f:                                                       # write to file
         dataset_out = f[result['group']].create_dataset(result['label'],data=result['data'])
         for k in result['meta'].keys():
           dataset_out.attrs[k] = result['meta'][k].encode()

python/damask/geom.py

@@ -239,8 +239,8 @@ class Geom():
         header.append('homogenization {}'.format(self.get_homogenization()))
         return header
         
-    @classmethod
+    @staticmethod
-    def from_file(cls,fname):
+    def from_file(fname):
         """
         Reads a geom file.
 
@@ -300,7 +300,7 @@ class Geom():
         if not np.any(np.mod(microstructure.flatten(),1) != 0.0):                                   # no float present
             microstructure = microstructure.astype('int')
         
-        return cls(microstructure.reshape(grid),size,origin,homogenization,comments)
+        return Geom(microstructure.reshape(grid),size,origin,homogenization,comments)
 
 
     def to_file(self,fname,pack=None):

python/damask/mechanics.py

@@ -19,7 +19,26 @@ def Cauchy(F,P):
     else:
         sigma = np.einsum('i,ijk,ilk->ijl',1.0/np.linalg.det(F),P,F)
     return symmetric(sigma)
-  
+
+
+def PK2(F,P):
+    """
+    Return 2. Piola-Kirchhoff stress calculated from 1. Piola-Kirchhoff stress and deformation gradient.
+      
+    Parameters
+    ----------
+    F : numpy.array of shape (:,3,3) or (3,3)
+      Deformation gradient.
+    P : numpy.array of shape (:,3,3) or (3,3)
+      1. Piola-Kirchhoff stress.
+
+    """
+    if np.shape(F) == np.shape(P) == (3,3):
+        S = np.dot(np.linalg.inv(F),P)
+    else:
+        S = np.einsum('ijk,ikl->ijl',np.linalg.inv(F),P)
+    return S
+
 
 def strain_tensor(F,t,m):
     """

python/damask/table.py

@@ -0,0 +1,257 @@
+import re
+
+import pandas as pd
+import numpy as np
+
+class Table():
+    """Store spreadsheet-like data."""
+  
+    def __init__(self,data,shapes,comments=None):
+        """
+        New spreadsheet.
+        
+        Parameters
+        ----------
+        data : numpy.ndarray
+            Data.
+        shapes : dict with str:tuple pairs
+            Shapes of the columns. Example 'F':(3,3) for a deformation gradient. 
+        comments : iterable of str, optional
+            Additional, human-readable information.
+        
+        """
+        self.comments = [] if comments is None else [c for c in comments]
+        self.data = pd.DataFrame(data=data)
+        self.shapes = shapes
+        self.__label_condensed()
+
+
+    def __label_flat(self):
+        """Label data individually, e.g. v v v ==> 1_v 2_v 3_v."""
+        labels = []
+        for label,shape in self.shapes.items():
+            size = np.prod(shape)
+            labels += ['{}{}'.format('' if size == 1 else '{}_'.format(i+1),label) for i in range(size)]
+        self.data.columns = labels
+        
+        
+    def __label_condensed(self):
+        """Label data condensed, e.g. 1_v 2_v 3_v ==> v v v."""
+        labels = []
+        for label,shape in self.shapes.items():
+            labels += [label] * np.prod(shape)
+        self.data.columns = labels
+
+
+    def __add_comment(self,label,shape,info):
+        if info is not None:
+            self.comments.append('{}{}: {}'.format(label,
+                                                   ' '+str(shape) if np.prod(shape,dtype=int) > 1 else '',
+                                                   info))
+
+    
+    @staticmethod
+    def from_ASCII(fname):
+        """
+        Create table from ASCII file.
+
+        The first line needs to indicate the number of subsequent header lines as 'n header'.
+        Vector data column labels are indicated by '1_v, 2_v, ..., n_v'.
+        Tensor data column labels are indicated by '3x3:1_T, 3x3:2_T, ..., 3x3:9_T'.
+
+        Parameters
+        ----------
+        fname : file, str, or pathlib.Path
+            Filename or file for reading.
+
+        """
+        try:
+            f = open(fname)
+        except TypeError:
+            f = fname
+
+        header,keyword = f.readline().split()
+        if keyword == 'header':
+            header = int(header)
+        else:
+            raise Exception
+        comments = [f.readline()[:-1] for i in range(1,header)]
+        labels   = f.readline().split()
+       
+        shapes = {}
+        for label in labels:
+            tensor_column = re.search(r'[0-9,x]*?:[0-9]*?_',label)
+            if tensor_column:
+                my_shape = tensor_column.group().split(':',1)[0].split('x')
+                shapes[label.split('_',1)[1]] = tuple([int(d) for d in my_shape])
+            else:
+                vector_column = re.match(r'[0-9]*?_',label)
+                if vector_column:
+                    shapes[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
+                else:
+                    shapes[label] = (1,)
+        
+        data = pd.read_csv(f,names=list(range(len(labels))),sep=r'\s+').to_numpy()
+
+        return Table(data,shapes,comments)
+
+    @property
+    def labels(self):
+        """Return the labels of all columns."""
+        return list(self.shapes.keys())
+
+
+    def get(self,label):
+        """
+        Get column data.
+
+        Parameters
+        ----------
+        label : str
+            Column label.
+
+        """
+        if re.match(r'[0-9]*?_',label):
+            idx,key = label.split('_',1)
+            data = self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
+        else: 
+            data = self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
+
+        return data.astype(type(data.flatten()[0]))
+
+
+    def set(self,label,data,info=None):
+        """
+        Set column data.
+
+        Parameters
+        ----------
+        label : str
+            Column label.
+        data : np.ndarray
+            New data.
+        info : str, optional
+            Human-readable information about the new data.
+
+        """
+        self.__add_comment(label,data.shape[1:],info)
+
+        if re.match(r'[0-9]*?_',label):
+            idx,key = label.split('_',1)
+            iloc = self.data.columns.get_loc(key).tolist().index(True) + int(idx) -1
+            self.data.iloc[:,iloc] = data
+        else: 
+            self.data[label]       = data.reshape(self.data[label].shape)
+
+
+    def add(self,label,data,info=None):
+        """
+        Add column data.
+
+        Parameters
+        ----------
+        label : str
+            Column label.
+        data : np.ndarray
+            Modified data.
+        info : str, optional
+            Human-readable information about the modified data.
+
+        """
+        self.__add_comment(label,data.shape[1:],info)
+
+        self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
+        size = np.prod(data.shape[1:],dtype=int)
+        new = pd.DataFrame(data=data.reshape(-1,size),
+                           columns=[label]*size,
+                          )
+        new.index = self.data.index
+        self.data = pd.concat([self.data,new],axis=1)
+
+
+    def delete(self,label):
+        """
+        Delete column data.
+
+        Parameters
+        ----------
+        label : str
+            Column label.
+
+        """
+        self.data.drop(columns=label,inplace=True)
+
+        del self.shapes[label]
+
+
+    def rename(self,label_old,label_new,info=None):
+        """
+        Rename column data.
+
+        Parameters
+        ----------
+        label_old : str
+            Old column label.
+        label_new : str
+            New column label.
+
+        """
+        self.data.rename(columns={label_old:label_new},inplace=True)
+
+        self.comments.append('{} => {}{}'.format(label_old,
+                                                 label_new,
+                                                 '' if info is None else ': {}'.format(info),
+                                                 ))
+
+        self.shapes[label_new] = self.shapes.pop(label_old)
+
+
+    def sort_by(self,labels,ascending=True):
+        """
+        Get column data.
+
+        Parameters
+        ----------
+        label : str or list
+            Column labels.
+        ascending : bool or list, optional
+            Set sort order.
+
+        """
+        self.__label_flat()
+        self.data.sort_values(labels,axis=0,inplace=True,ascending=ascending)
+        self.__label_condensed()
+        self.comments.append('sorted by [{}]'.format(', '.join(labels)))
+
+
+    def to_ASCII(self,fname):
+        """
+        Store as plain text file.
+
+        Parameters
+        ----------
+        fname : file, str, or pathlib.Path
+            Filename or file for reading.
+
+        """
+        labels = []
+        for l in self.shapes:
+            if(self.shapes[l] == (1,)):
+                labels.append('{}'.format(l))
+            elif(len(self.shapes[l]) == 1):
+                labels += ['{}_{}'.format(i+1,l) \
+                          for i in range(self.shapes[l][0])]
+            else:
+                labels += ['{}:{}_{}'.format('x'.join([str(d) for d in self.shapes[l]]),i+1,l) \
+                          for i in range(np.prod(self.shapes[l],dtype=int))]
+
+        header = ['{} header'.format(len(self.comments)+1)] \
+               + self.comments \
+               + [' '.join(labels)]
+
+        try:
+            f = open(fname,'w')
+        except TypeError:
+            f = fname
+        for line in header: f.write(line+'\n')
+        self.data.to_csv(f,sep=' ',index=False,header=False)

python/tests/reference/Table/datatype-mix.txt

@@ -0,0 +1,4 @@
+1 header
+a b
+1.0 hallo
+0.1 "hallo test"

python/tests/reference/Table/whitespace-mix.txt

@@ -0,0 +1,6 @@
+1 header
+a b 1_c 2_c
+1    2 3     4
+5 6 7	 8
+9	10.	12.			12
+

python/tests/test_Table.py

@@ -0,0 +1,128 @@
+import os
+
+import pytest
+import numpy as np
+
+from damask import Table
+
+
+@pytest.fixture
+def default():
+    """Simple Table."""
+    x = np.ones((5,13),dtype=float)
+    return Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['test data','contains only ones'])
+
+@pytest.fixture
+def reference_dir(reference_dir_base):
+    """Directory containing reference results."""
+    return os.path.join(reference_dir_base,'Table')
+
+class TestTable:
+    
+    def test_get_scalar(self,default):
+        d = default.get('s')
+        assert np.allclose(d,1.0) and d.shape[1:] == (1,)
+
+    def test_get_vector(self,default):
+        d = default.get('v')
+        assert np.allclose(d,1.0) and d.shape[1:] == (3,)
+
+    def test_get_tensor(self,default):
+        d = default.get('F')
+        assert np.allclose(d,1.0) and d.shape[1:] == (3,3) 
+
+    def test_get_component(self,default):
+        d = default.get('5_F')
+        assert np.allclose(d,1.0) and d.shape[1:] == (1,)
+  
+    def test_write_read_str(self,default,tmpdir):
+        default.to_ASCII(str(tmpdir.join('default.txt')))
+        new = Table.from_ASCII(str(tmpdir.join('default.txt')))
+        assert all(default.data==new.data)
+
+    def test_write_read_file(self,default,tmpdir):
+        with open(tmpdir.join('default.txt'),'w') as f:
+            default.to_ASCII(f)
+        with open(tmpdir.join('default.txt')) as f:
+            new = Table.from_ASCII(f)
+        assert all(default.data==new.data)
+
+    @pytest.mark.parametrize('fname',['datatype-mix.txt','whitespace-mix.txt'])
+    def test_read_strange(self,reference_dir,fname):
+        with open(os.path.join(reference_dir,fname)) as f:
+            Table.from_ASCII(f)
+    
+    def test_set(self,default):
+        default.set('F',np.zeros((5,3,3)),'set to zero')
+        d=default.get('F')
+        assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
+
+    def test_labels(self,default):
+        assert default.labels == ['F','v','s']
+        
+    def test_add(self,default):
+        d = np.random.random((5,9))
+        default.add('nine',d,'random data')
+        assert np.allclose(d,default.get('nine'))
+
+    def test_rename_equivalent(self,default):
+        v = default.get('v')
+        default.rename('v','u')
+        u = default.get('u')
+        assert np.all(v == u)
+
+    def test_rename_gone(self,default):
+        default.rename('v','V')
+        with pytest.raises(KeyError):
+            default.get('v')
+
+    def test_delete(self,default):
+        default.delete('v')
+        with pytest.raises(KeyError):
+            default.get('v')
+
+
+    def test_invalid_initialization(self):
+        x = np.random.random((5,10))
+        with pytest.raises(ValueError):
+            Table(x,{'F':(3,3)})
+
+    def test_invalid_set(self,default):
+        x = default.get('v')
+        with pytest.raises(ValueError):
+            default.set('F',x,'does not work')
+
+    def test_invalid_get(self,default):
+        with pytest.raises(KeyError):
+            default.get('n')
+
+    def test_sort_scalar(self):
+        x = np.random.random((5,13))
+        t = Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['random test data'])
+        unsort = t.get('s')
+        t.sort_by('s')
+        sort   = t.get('s')
+        assert np.all(np.sort(unsort,0)==sort)
+
+    def test_sort_component(self):
+        x = np.random.random((5,12))
+        t = Table(x,{'F':(3,3),'v':(3,)},['random test data'])
+        unsort = t.get('4_F')
+        t.sort_by('4_F')
+        sort = t.get('4_F')
+        assert np.all(np.sort(unsort,0)==sort)
+
+    def test_sort_revert(self):
+        x = np.random.random((5,12))
+        t = Table(x,{'F':(3,3),'v':(3,)},['random test data'])
+        t.sort_by('4_F',ascending=False)
+        sort = t.get('4_F')
+        assert np.all(np.sort(sort,0)==sort[::-1,:])
+
+    def test_sort(self):
+        t = Table(np.array([[0,1,],[2,1,]]),
+                  {'v':(2,)},
+                  ['test data'])
+        t.add('s',np.array(['b','a']))
+        t.sort_by('s')
+        assert np.all(t.get('1_v') == np.array([2,0]).reshape((2,1)))