table class operates out of place

.gitlab-ci.yml

@@ -141,13 +141,6 @@ Pre_General:
     - release
 
 ###################################################################################################
-Post_ASCIItable:
-  stage: postprocessing
-  script: ASCIItable/test.py
-  except:
-    - master
-    - release
-
 Post_General:
   stage: postprocessing
   script: PostProcessing/test.py

processing/post/DADF5_postResults.py

@@ -39,7 +39,7 @@ for filename in options.filenames:
     N_digits = 5 # hack to keep test intact
     for inc in damask.util.show_progress(results.iterate('increments'),len(results.increments)):
         table = damask.Table(np.ones(np.product(results.grid),dtype=int)*int(inc[3:]),{'inc':(1,)})
-        table.add('pos',coords.reshape(-1,3))
+        table = table.add('pos',coords.reshape(-1,3))
 
         results.pick('materialpoints',False)
         results.pick('constituents',  True)
@@ -53,7 +53,7 @@ for filename in options.filenames:
         for label in options.mat:
             x = results.get_dataset_location(label)
             if len(x) != 0:
-                table.add(label,results.read_dataset(x,0,plain=True).reshape(results.grid.prod(),-1))
+                table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.grid.prod(),-1))
 
         dirname  = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir))
         if not os.path.isdir(dirname):

processing/post/addCompatibilityMismatch.py

@@ -181,13 +181,13 @@ for name in filenames:
   if options.shape:
     centers = damask.grid_filters.cell_coord(size,F)
     shapeMismatch = shapeMismatch(size,F,nodes,centers)
-    table.add('shapeMismatch(({}))'.format(options.defgrad),
+    table = table.add('shapeMismatch(({}))'.format(options.defgrad),
                       shapeMismatch.reshape(-1,1,order='F'),
                       scriptID+' '+' '.join(sys.argv[1:]))
 
   if options.volume:
     volumeMismatch = volumeMismatch(size,F,nodes)
-    table.add('volMismatch(({}))'.format(options.defgrad),
+    table = table.add('volMismatch(({}))'.format(options.defgrad),
                       volumeMismatch.reshape(-1,1,order='F'),
                       scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addCurl.py

@@ -51,7 +51,7 @@ for name in filenames:
         shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3)                         # vector or tensor
         field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
         curl  = damask.grid_filters.curl(size,field)
-        table.add('curlFFT({})'.format(label),
+        table = table.add('curlFFT({})'.format(label),
                           curl.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape),order='F'),
                           scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addDerivative.py

@@ -67,7 +67,7 @@ for name in filenames:
 
     table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
     for label in options.labels:
-        table.add('d({})/d({})'.format(label,options.coordinates),
+        table = table.add('d({})/d({})'.format(label,options.coordinates),
                           derivative(table.get(options.coordinates),table.get(label)),
                           scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addDisplacement.py

@@ -53,19 +53,19 @@ for name in filenames:
     F = table.get(options.f).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
     if options.nodal:
         table = damask.Table(damask.grid_filters.node_coord0(grid,size).reshape(-1,3,order='F'),
-                             {'pos':(3,)})
+                     {'pos':(3,)})\
-        table.add('avg({}).{}'.format(options.f,options.pos),
+              .add('avg({}).{}'.format(options.f,options.pos),
                    damask.grid_filters.node_displacement_avg(size,F).reshape(-1,3,order='F'),
-                  scriptID+' '+' '.join(sys.argv[1:]))
+                   scriptID+' '+' '.join(sys.argv[1:]))\
-        table.add('fluct({}).{}'.format(options.f,options.pos),
+              .add('fluct({}).{}'.format(options.f,options.pos),
                    damask.grid_filters.node_displacement_fluct(size,F).reshape(-1,3,order='F'),
                     scriptID+' '+' '.join(sys.argv[1:]))
         table.to_file(sys.stdout if name is None else os.path.splitext(name)[0]+'_nodal.txt')
     else:
-        table.add('avg({}).{}'.format(options.f,options.pos),
+        table = table.add('avg({}).{}'.format(options.f,options.pos),
                   damask.grid_filters.cell_displacement_avg(size,F).reshape(-1,3,order='F'),
-                  scriptID+' '+' '.join(sys.argv[1:]))
+                  scriptID+' '+' '.join(sys.argv[1:]))\
-        table.add('fluct({}).{}'.format(options.f,options.pos),
+             .add('fluct({}).{}'.format(options.f,options.pos),
                   damask.grid_filters.cell_displacement_fluct(size,F).reshape(-1,3,order='F'),
                   scriptID+' '+' '.join(sys.argv[1:]))
         table.to_file(sys.stdout if name is None else name)

processing/post/addDivergence.py

@@ -51,7 +51,7 @@ for name in filenames:
         shape = (3,) if np.prod(field.shape)//np.prod(grid) == 3 else (3,3)                         # vector or tensor
         field = field.reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+shape)
         div   = damask.grid_filters.divergence(size,field)
-        table.add('divFFT({})'.format(label),
+        table = table.add('divFFT({})'.format(label),
                           div.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)//3,order='F'),
                           scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addEuclideanDistance.py

@@ -180,7 +180,7 @@ for name in filenames:
 
 
     for i,feature in enumerate(feature_list):
-        table.add('ED_{}({})'.format(features[feature]['names'][0],options.id),
+        table = table.add('ED_{}({})'.format(features[feature]['names'][0],options.id),
                           distance[i,:],
                           scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addGaussian.py

@@ -67,7 +67,7 @@ for name in filenames:
     damask.grid_filters.coord0_check(table.get(options.pos))
 
     for label in options.labels:
-        table.add('Gauss{}({})'.format(options.sigma,label),
+        table = table.add('Gauss{}({})'.format(options.sigma,label),
                           ndimage.filters.gaussian_filter(table.get(label).reshape(-1),
                                                           options.sigma,options.order,
                                                           mode = 'wrap' if options.periodic else 'nearest'),

processing/post/addGradient.py

@@ -51,7 +51,7 @@ for name in filenames:
         shape = (1,) if np.prod(field.shape)//np.prod(grid) == 1 else (3,)                          # scalar or vector
         field = field.reshape(tuple(grid)+(-1,),order='F')
         grad  = damask.grid_filters.gradient(size,field)
-        table.add('gradFFT({})'.format(label),
+        table = table.add('gradFFT({})'.format(label),
                           grad.reshape(tuple(grid)+(-1,)).reshape(-1,np.prod(shape)*3,order='F'),
                           scriptID+' '+' '.join(sys.argv[1:]))
 

processing/post/addIndexed.py

@@ -1,64 +0,0 @@
-#!/usr/bin/env python3
-
-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])
-
-# --------------------------------------------------------------------
-#                                MAIN
-# --------------------------------------------------------------------
-
-parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
-Add data in column(s) of mapped ASCIItable selected from the row indexed by the value in a mapping column.
-Row numbers start at 1.
-
-""", version = scriptID)
-
-parser.add_option('--index',
-                  dest = 'index',
-                  type = 'string', metavar = 'string',
-                  help = 'column label containing row index')
-parser.add_option('-o','--offset',
-                  dest = 'offset',
-                  type = 'int', metavar = 'int',
-                  help = 'constant offset for index column value [%default]')
-parser.add_option('-l','--label',
-                  dest = 'label',
-                  action = 'extend', metavar = '<string LIST>',
-                  help = 'column label(s) to be appended')
-parser.add_option('-a','--asciitable',
-                  dest = 'asciitable',
-                  type = 'string', metavar = 'string',
-                  help = 'indexed ASCIItable')
-
-parser.set_defaults(offset = 0,
-                   )
-
-(options,filenames) = parser.parse_args()
-if filenames == []: filenames = [None]
-
-if options.label is None:
-  parser.error('no data columns specified.')
-if options.index is None:
-  parser.error('no index column given.')
-
-for name in filenames:
-    damask.util.report(scriptName,name)
-
-    table        = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
-    indexedTable = damask.Table.from_ASCII(options.asciitable)
-    idx = np.reshape(table.get(options.index).astype(int) + options.offset,(-1))-1
-
-    for data in options.label:
-        table.add(data+'_addIndexed',indexedTable.get(data)[idx],scriptID+' '+' '.join(sys.argv[1:]))
-
-    table.to_file(sys.stdout if name is None else name)

processing/post/addLinked.py

@@ -1,118 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import sys
-from optparse import OptionParser
-
-import numpy as np
-
-import damask
-
-
-scriptName = os.path.splitext(os.path.basename(__file__))[0]
-scriptID   = ' '.join([scriptName,damask.version])
-
-# --------------------------------------------------------------------
-#                                MAIN
-# --------------------------------------------------------------------
-
-parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
-Add data of selected column(s) from (first) row of linked ASCIItable that shares the linking column value.
-
-""", version = scriptID)
-
-parser.add_option('--link',
-                  dest = 'link', nargs = 2,
-                  type = 'string', metavar = 'string string',
-                  help = 'column labels of table and linked table containing linking values')
-parser.add_option('-l','--label',
-                  dest = 'label',
-                  action = 'extend', metavar = '<string LIST>',
-                  help = 'column label(s) to add from linked ASCIItable')
-parser.add_option('-a','--asciitable',
-                  dest = 'asciitable',
-                  type = 'string', metavar = 'string',
-                  help = 'linked ASCIItable')
-
-parser.set_defaults()
-
-(options,filenames) = parser.parse_args()
-
-if options.label is None:
-  parser.error('no data columns specified.')
-if options.link is None:
-  parser.error('no linking columns given.')
-
-# -------------------------------------- process linked ASCIItable --------------------------------
-
-if options.asciitable is not None and os.path.isfile(options.asciitable):
-
-  linkedTable = damask.ASCIItable(name = options.asciitable, readonly = True) 
-  linkedTable.head_read()                                                                           # read ASCII header info of linked table
-  linkDim = linkedTable.label_dimension(options.link[1])                                            # dimension of linking column
-
-  missing_labels = linkedTable.data_readArray([options.link[1]]+options.label)                      # try reading linked ASCII table
-  linkedTable.close()                                                                               # close linked ASCII table
-
-  if len(missing_labels) > 0:
-    damask.util.croak('column{} {} not found...'.format('s' if len(missing_labels) > 1 else '',', '.join(missing_labels)))
-  if len(missing_labels) >= len(options.label):
-    damask.util.croak('aborting...')
-    sys.exit()
-
-  index = linkedTable.data[:,:linkDim]
-  data  = linkedTable.data[:,linkDim:]
-else:
-  parser.error('no linked ASCIItable given.')
-
-# --- loop over input files -----------------------------------------------------------------------
-
-if filenames == []: filenames = [None]
-
-for name in filenames:
-  try:
-    table = damask.ASCIItable(name = name)
-  except IOError:
-    continue
-  damask.util.report(scriptName,"{} {} <== {} {}".format(name,damask.util.deemph('@ '+options.link[0]),
-                                                         options.asciitable,damask.util.deemph('@ '+options.link[1])))
-
-# ------------------------------------------ read header ------------------------------------------
-
-  table.head_read()
-
-# ------------------------------------------ sanity checks ----------------------------------------
-
-  errors = []
-
-  myLink    = table.label_index    (options.link[0])  
-  myLinkDim = table.label_dimension(options.link[0])  
-  if myLink <  0:          errors.append('linking column {} not found.'.format(options.link[0]))
-  if myLinkDim != linkDim: errors.append('dimension mismatch for column {}.'.format(options.link[0]))
-
-  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(linkedTable.labels(raw = True)[linkDim:])                                     # extend with new labels (except for linked column)
-  
-  table.head_write()
-
-# ------------------------------------------ process data ------------------------------------------
-
-  outputAlive = True
-  while outputAlive and table.data_read():                                                          # read next data line of ASCII table
-    try:
-      table.data_append(data[np.argwhere(np.all((list(map(float,table.data[myLink:myLink+myLinkDim])) - index)==0,
-                                                 axis=1))[0]])                                      # add data of first matching line
-    except IndexError:
-      table.data_append(np.nan*np.ones_like(data[0]))                                               # or add NaNs
-    outputAlive = table.data_write()                                                                # output processed line
-
-# ------------------------------------------ output finalization -----------------------------------  
-
-  table.close()                                                                                     # close ASCII tables

processing/post/addOrientations.py

@@ -137,14 +137,14 @@ for name in filenames:
 
 
     if 'rodrigues' in options.output:
-        table.add('ro({})'.format(label),o.as_Rodrigues(),                scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add('ro({})'.format(label),o.as_Rodrigues(),                scriptID+' '+' '.join(sys.argv[1:]))
     if 'eulers' in options.output:
-        table.add('eu({})'.format(label),o.as_Eulers(options.degrees),    scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add('eu({})'.format(label),o.as_Eulers(options.degrees),    scriptID+' '+' '.join(sys.argv[1:]))
     if 'quaternion' in options.output:
-        table.add('qu({})'.format(label),o.as_quaternion(),               scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add('qu({})'.format(label),o.as_quaternion(),               scriptID+' '+' '.join(sys.argv[1:]))
     if 'matrix' in options.output:
-        table.add('om({})'.format(label),o.as_matrix(),                   scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add('om({})'.format(label),o.as_matrix(),                   scriptID+' '+' '.join(sys.argv[1:]))
     if 'axisangle' in options.output:
-        table.add('om({})'.format(label),o.as_axisangle(options.degrees), scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add('om({})'.format(label),o.as_axisangle(options.degrees), scriptID+' '+' '.join(sys.argv[1:]))
 
     table.to_file(sys.stdout if name is None else name)

processing/post/addSchmidfactors.py

@@ -187,6 +187,6 @@ for name in filenames:
                np.einsum('ijk,ik->ij',slip_normal,   (o@normal)))
 
     for i,label in enumerate(labels):
-        table.add(label,S[:,i],scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.add(label,S[:,i],scriptID+' '+' '.join(sys.argv[1:]))
 
     table.to_file(sys.stdout if name is None else name)

processing/post/groupTable.py

@@ -1,142 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import sys
-from optparse import OptionParser, OptionGroup
-import math                                                                                         # noqa
-
-import numpy as np
-
-import damask
-
-
-def periodicAverage(coords, limits):
-  """Centroid in periodic domain, see https://en.wikipedia.org/wiki/Center_of_mass#Systems_with_periodic_boundary_conditions."""
-  theta     = 2.0*np.pi * (coords - limits[0])/(limits[1] - limits[0])
-  theta_avg = np.pi + np.arctan2(-np.sin(theta).mean(axis=0), -np.cos(theta).mean(axis=0))
-  return limits[0] + theta_avg * (limits[1] - limits[0])/2.0/np.pi
-
-
-scriptName = os.path.splitext(os.path.basename(__file__))[0]
-scriptID   = ' '.join([scriptName,damask.version])
-
-# --------------------------------------------------------------------
-#                                MAIN
-# --------------------------------------------------------------------
-
-parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
-Apply a user-specified function to condense into a single row all those rows for which columns 'label' have identical values.
-Output table will contain as many rows as there are different (unique) values in the grouping column(s).
-Periodic domain averaging of coordinate values is supported.
-
-Examples:
-For grain averaged values, replace all rows of particular 'texture' with a single row containing their average.
-{name} --label texture --function np.average data.txt
-""".format(name = scriptName), version = scriptID)
-
-parser.add_option('-l','--label',
-                  dest = 'label',
-                  action = 'extend', metavar = '<string LIST>',
-                  help = 'column label(s) for grouping rows')
-parser.add_option('-f','--function',
-                  dest = 'function',
-                  type = 'string', metavar = 'string',
-                  help = 'mapping function [%default]')
-parser.add_option('-a','--all',
-                  dest = 'all',
-                  action = 'store_true',
-                  help = 'apply mapping function also to grouping column(s)')
-                  
-group = OptionGroup(parser, "periodic averaging", "")
-
-group.add_option ('-p','--periodic',
-                  dest   = 'periodic',
-                  action = 'extend', metavar = '<string LIST>',
-                  help   = 'coordinate label(s) to average across periodic domain')
-group.add_option ('--limits',
-                  dest = 'boundary',
-                  type = 'float', metavar = 'float float', nargs = 2,
-                  help = 'min and max of periodic domain %default')
-
-parser.add_option_group(group)
-
-parser.set_defaults(function = 'np.average',
-                    all      = False,
-                    label    = [],
-                    boundary = [0.0, 1.0])
-
-(options,filenames) = parser.parse_args()
-
-funcModule,funcName = options.function.split('.')
-
-try:
-  mapFunction = getattr(locals().get(funcModule) or 
-                        globals().get(funcModule) or
-                        __import__(funcModule), 
-                        funcName)
-except Exception:
-  mapFunction = None
-
-if options.label is []:
-  parser.error('no grouping column specified.')
-if not hasattr(mapFunction,'__call__'):
-  parser.error('function "{}" is not callable.'.format(options.function))
-
-
-# --- loop over input files -------------------------------------------------------------------------
-
-if filenames == []: filenames = [None]
-
-for name in filenames:
-  try:
-    table = damask.ASCIItable(name = name)
-  except IOError:
-    continue
-  damask.util.report(scriptName,name)
-
-# ------------------------------------------ sanity checks ---------------------------------------  
-
-  remarks = []
-  errors = []
-
-  table.head_read()
-  grpColumns = table.label_index(options.label)[::-1]
-  grpColumns = grpColumns[np.where(grpColumns>=0)]
-
-  if len(grpColumns) == 0:  errors.append('no valid grouping column present.')
-
-  if remarks != []: damask.util.croak(remarks)
-  if errors != []:
-    damask.util.croak(errors)
-    table.close(dismiss=True)
-    continue
-
-# ------------------------------------------ assemble info ---------------------------------------  
-
-  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
-  table.head_write()
-
-# ------------------------------------------ process data -------------------------------- 
-
-  table.data_readArray()
-  indexrange = table.label_indexrange(options.periodic) if options.periodic is not None else []
-  rows,cols  = table.data.shape
-
-  table.data = table.data[np.lexsort(table.data[:,grpColumns].T)]                                   # sort data by grpColumn(s)
-  values,index = np.unique(table.data[:,grpColumns], axis=0, return_index=True)                     # unique grpColumn values and their positions
-  index = sorted(np.append(index,rows))                                                             # add termination position
-  grpTable = np.empty((len(values), cols))                                                          # initialize output
-  
-  for i in range(len(values)):                                                                      # iterate over groups (unique values in grpColumn)
-    grpTable[i] = np.apply_along_axis(mapFunction,0,table.data[index[i]:index[i+1]])                # apply (general) mapping function
-    grpTable[i,indexrange] = \
-      periodicAverage(table.data[index[i]:index[i+1],indexrange],options.boundary)                  # apply periodicAverage mapping function
-
-    if not options.all: grpTable[i,grpColumns] = table.data[index[i],grpColumns]                    # restore grouping column value
-  
-  table.data = grpTable
-
-# ------------------------------------------ output result -------------------------------  
-
-  table.data_writeArray()
-  table.close()                                                                                     # close ASCII table

processing/post/permuteData.py

@@ -56,6 +56,6 @@ for name in filenames:
         data = table.get(label)
         uniques,inverse  = np.unique(data,return_inverse=True,axis=0) if options.unique else (data,np.arange(len(data)))
         rng.shuffle(uniques)
-        table.set(label,uniques[inverse], scriptID+' '+' '.join(sys.argv[1:]))
+        table = table.set(label,uniques[inverse], scriptID+' '+' '.join(sys.argv[1:]))
 
     table.to_file(sys.stdout if name is None else name)

processing/pre/seeds_fromGeom.py

@@ -64,6 +64,5 @@ for name in filenames:
                 'homogenization\t{}'.format(geom.homogenization)]
 
     table = damask.Table(seeds[mask],{'pos':(3,)},comments)
-    table.add('microstructure',microstructure[mask])
+    table = table.add('microstructure',microstructure[mask])
-    table.to_file(sys.stdout if name is None else \
+    table.to_file(sys.stdout if name is None else os.path.splitext(name)[0]+'.seeds')
-                  os.path.splitext(name)[0]+'.seeds')

processing/pre/seeds_fromRandom.py

@@ -155,11 +155,11 @@ for name in filenames:
                ]
 
     table = damask.Table(np.hstack((seeds,eulers)),{'pos':(3,),'euler':(3,)},comments)
-    table.add('microstructure',np.arange(options.microstructure,options.microstructure + options.N,dtype=int))
+    table = table.add('microstructure',np.arange(options.microstructure,options.microstructure + options.N,dtype=int))
 
     if options.weights:
         weights = np.random.uniform(low = 0, high = options.max, size = options.N) if options.max > 0.0 \
              else np.random.normal(loc = options.mean, scale = options.sigma, size = options.N)
-        table.add('weight',weights)
+        table = table.add('weight',weights)
 
     table.to_file(sys.stdout if name is None else name)

python/damask/_table.py

@@ -1,4 +1,5 @@
 import re
+import copy
 
 import pandas as pd
 import numpy as np
@@ -29,6 +30,15 @@ class Table:
         self._label_condensed()
 
 
+    def __copy__(self):
+        """Copy Table."""
+        return copy.deepcopy(self)
+
+    def copy(self):
+        """Copy Table."""
+        return self.__copy__()
+
+
     def _label_flat(self):
         """Label data individually, e.g. v v v ==> 1_v 2_v 3_v."""
         labels = []
@@ -191,15 +201,16 @@ class Table:
             Human-readable information about the new data.
 
         """
-        self._add_comment(label,data.shape[1:],info)
+        dup = self.copy()
+        dup._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
+            iloc = dup.data.columns.get_loc(key).tolist().index(True) + int(idx) -1
-            self.data.iloc[:,iloc] = data
+            dup.data.iloc[:,iloc] = data
         else:
-            self.data[label]       = data.reshape(self.data[label].shape)
+            dup.data[label]       = data.reshape(dup.data[label].shape)
-
+        return dup
 
     def add(self,label,data,info=None):
         """
@@ -215,15 +226,17 @@ class Table:
             Human-readable information about the modified data.
 
         """
-        self._add_comment(label,data.shape[1:],info)
+        dup = self.copy()
+        dup._add_comment(label,data.shape[1:],info)
 
-        self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
+        dup.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
+        new.index = dup.data.index
-        self.data = pd.concat([self.data,new],axis=1)
+        dup.data = pd.concat([dup.data,new],axis=1)
+        return dup
 
 
     def delete(self,label):
@@ -236,25 +249,31 @@ class Table:
             Column label.
 
         """
-        self.data.drop(columns=label,inplace=True)
+        dup = self.copy()
-        del self.shapes[label]
+        dup.data.drop(columns=label,inplace=True)
+        del dup.shapes[label]
+        return dup
 
 
-    def rename(self,label_old,label_new,info=None):
+    def rename(self,old,new,info=None):
         """
         Rename column data.
 
         Parameters
         ----------
-        label_old : str
+        label_old : str or iterable of str
-            Old column label.
+            Old column label(s).
-        label_new : str
+        label_new : str or iterable of str
-            New column label.
+            New column label(s).
 
         """
-        self.data.rename(columns={label_old:label_new},inplace=True)
+        dup = self.copy()
-        self.comments.append(f'{label_old} => {label_new}'+('' if info is None else f': {info}'))
+        columns = dict(zip([old] if isinstance(old,str) else old,
-        self.shapes = {(label if label != label_old else label_new):self.shapes[label] for label in self.shapes}
+                           [new] if isinstance(new,str) else new))
+        dup.data.rename(columns=columns,inplace=True)
+        dup.comments.append(f'{old} => {new}'+('' if info is None else f': {info}'))
+        dup.shapes = {(label if label not in columns else columns[label]):dup.shapes[label] for label in dup.shapes}
+        return dup
 
 
     def sort_by(self,labels,ascending=True):
@@ -269,10 +288,12 @@ class Table:
             Set sort order.
 
         """
-        self._label_flat()
+        dup = self.copy()
-        self.data.sort_values(labels,axis=0,inplace=True,ascending=ascending)
+        dup._label_flat()
-        self._label_condensed()
+        dup.data.sort_values(labels,axis=0,inplace=True,ascending=ascending)
-        self.comments.append(f'sorted by [{", ".join(labels)}]')
+        dup._label_condensed()
+        dup.comments.append(f'sorted {"ascending" if ascending else "descending"} by {labels}')
+        return dup
 
 
     def append(self,other):
@@ -290,7 +311,9 @@ class Table:
         if self.shapes != other.shapes or not self.data.columns.equals(other.data.columns):
             raise KeyError('Labels or shapes or order do not match')
         else:
-            self.data = self.data.append(other.data,ignore_index=True)
+            dup = self.copy()
+            dup.data = dup.data.append(other.data,ignore_index=True)
+            return dup
 
 
     def join(self,other):
@@ -308,9 +331,11 @@ class Table:
         if set(self.shapes) & set(other.shapes) or self.data.shape[0] != other.data.shape[0]:
             raise KeyError('Dublicated keys or row count mismatch')
         else:
-            self.data = self.data.join(other.data)
+            dup = self.copy()
+            dup.data = dup.data.join(other.data)
             for key in other.shapes:
-                self.shapes[key] = other.shapes[key]
+                dup.shapes[key] = other.shapes[key]
+            return dup
 
 
     def to_file(self,fname,format='ASCII',new_style=False):

python/tests/test_Orientation.py

@@ -105,7 +105,7 @@ class TestOrientation:
         if update:
             coords = np.array([(1,i+1) for i,x in enumerate(eu)])
             table = Table(eu,{'Eulers':(3,)})
-            table.add('pos',coords)
+            table = table.add('pos',coords)
             table.to_ASCII(reference)
         assert np.allclose(eu,Table.from_ASCII(reference).get('Eulers'))
 

python/tests/test_Table.py

@@ -81,13 +81,11 @@ class TestTable:
             Table.from_ASCII(f)
 
     def test_set(self,default):
-        default.set('F',np.zeros((5,3,3)),'set to zero')
+        d = default.set('F',np.zeros((5,3,3)),'set to zero').get('F')
-        d=default.get('F')
         assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
 
     def test_set_component(self,default):
-        default.set('1_F',np.zeros((5)),'set to zero')
+        d = default.set('1_F',np.zeros((5)),'set to zero').get('F')
-        d=default.get('F')
         assert np.allclose(d[...,0,0],0.0) and d.shape[1:] == (3,3)
 
     def test_labels(self,default):
@@ -95,36 +93,34 @@ class TestTable:
 
     def test_add(self,default):
         d = np.random.random((5,9))
-        default.add('nine',d,'random data')
+        assert np.allclose(d,default.add('nine',d,'random data').get('nine'))
-        assert np.allclose(d,default.get('nine'))
 
     def test_rename_equivalent(self):
         x = np.random.random((5,13))
         t = Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['random test data'])
         s = t.get('s')
-        t.rename('s','u')
+        u = t.rename('s','u').get('u')
-        u = t.get('u')
         assert np.all(s == u)
 
     def test_rename_gone(self,default):
-        default.rename('v','V')
+        gone = default.rename('v','V')
-        assert 'v' not in default.shapes and 'v' not in default.data.columns
+        assert 'v' not in gone.shapes and 'v' not in gone.data.columns
         with pytest.raises(KeyError):
-            default.get('v')
+            gone.get('v')
 
     def test_delete(self,default):
-        default.delete('v')
+        delete = default.delete('v')
-        assert 'v' not in default.shapes and 'v' not in default.data.columns
+        assert 'v' not in delete.shapes and 'v' not in delete.data.columns
         with pytest.raises(KeyError):
-            default.get('v')
+            delete.get('v')
 
     def test_join(self):
         x = np.random.random((5,13))
         a = Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['random test data'])
         y = np.random.random((5,3))
         b = Table(y,{'u':(3,)},['random test data'])
-        a.join(b)
+        c = a.join(b)
-        assert np.array_equal(a.get('u'), b.get('u'))
+        assert np.array_equal(c.get('u'), b.get('u'))
 
     def test_join_invalid(self):
         x = np.random.random((5,13))
@@ -135,8 +131,8 @@ class TestTable:
     def test_append(self):
         x = np.random.random((5,13))
         a = Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['random test data'])
-        a.append(a)
+        b = a.append(a)
-        assert np.array_equal(a.data[:5].to_numpy(),a.data[5:].to_numpy())
+        assert np.array_equal(b.data[:5].to_numpy(),b.data[5:].to_numpy())
 
     def test_append_invalid(self):
         x = np.random.random((5,13))
@@ -163,29 +159,26 @@ class TestTable:
         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.sort_by('s').get('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.sort_by('4_F').get('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.sort_by('4_F',ascending=False).get('4_F')
-        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'])
+                  ['test data'])\
-        t.add('s',np.array(['b','a']))
+                  .add('s',np.array(['b','a']))\
-        t.sort_by('s')
+                  .sort_by('s')
         assert np.all(t.get('1_v') == np.array([2,0]).reshape(2,1))