added ASCIItable tests to CI pipelining

.gitlab-ci.yml

@@ -156,6 +156,13 @@ Post_AverageDown:
     - master
     - release
 
+Post_ASCIItable:
+  stage: postprocessing
+  script: ASCIItable/test.py
+  except:
+    - master
+    - release
+
 Post_General:
   stage: postprocessing
   script: PostProcessing/test.py

PRIVATE

@@ -1 +1 @@
-Subproject commit c6db7cee2d9349e2d463f5ef6284446007fc7915
+Subproject commit 3d12562fbfb3a57dbb3777ac045a12376b3400e8

processing/post/addLinked.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python3
 # -*- coding: UTF-8 no BOM -*-
 
 import os,sys
@@ -21,7 +21,7 @@ Add data of selected column(s) from (first) row of linked ASCIItable that shares
 parser.add_option('--link',
                   dest = 'link', nargs = 2,
                   type = 'string', metavar = 'string string',
-                  help = 'column labels containing linked values')
+                  help = 'column labels of table and linked table containing linking values')
 parser.add_option('-l','--label',
                   dest = 'label',
                   action = 'extend', metavar = '<string LIST>',
@@ -105,7 +105,7 @@ for name in filenames:
   outputAlive = True
   while outputAlive and table.data_read():                                                          # read next data line of ASCII table
     try:
-      table.data_append(data[np.argwhere(np.all((map(float,table.data[myLink:myLink+myLinkDim]) - index)==0,axis=1))[0]])  # add data of first matching line
+      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

processing/post/addTable.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python3
 # -*- coding: UTF-8 no BOM -*-
 
 import os,sys

processing/pre/geom_grainGrowth.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python3
 # -*- coding: UTF-8 no BOM -*-
 
 import os,sys,math
@@ -49,7 +49,7 @@ parser.set_defaults(d = 1,
 
 (options, filenames) = parser.parse_args()
 
-options.immutable = map(int,options.immutable)
+options.immutable = list(map(int,options.immutable))
 
 getInterfaceEnergy = lambda A,B: np.float32((A*B != 0)*(A != B)*1.0)                               # 1.0 if A & B are distinct & nonzero, 0.0 otherwise
 struc = ndimage.generate_binary_structure(3,1)                                                     # 3D von Neumann neighborhood
@@ -70,9 +70,9 @@ for name in filenames:
   table.head_read()
   info,extra_header = table.head_getGeom()
   
-  damask.util.croak(['grid     a b c:  {}'.format(' x '.join(map(str,info['grid']))),
+  damask.util.croak(['grid     a b c:  {}'.format(' x '.join(list(map(str,info['grid'])))),
-                     'size     x y z:  {}'.format(' x '.join(map(str,info['size']))),
+                     'size     x y z:  {}'.format(' x '.join(list(map(str,info['size'])))),
-                     'origin   x y z:  {}'.format(' : '.join(map(str,info['origin']))),
+                     'origin   x y z:  {}'.format(' : '.join(list(map(str,info['origin'])))),
                      'homogenization:  {}'.format(info['homogenization']),
                      'microstructures: {}'.format(info['microstructures']),
                     ])
@@ -102,9 +102,9 @@ for name in filenames:
     gauss = np.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d),dtype=np.float32) \
             /np.power(2.0*np.pi*options.d*options.d,(3.0 - np.count_nonzero(info['grid'] == 1))/2.,dtype=np.float32)
           
-    gauss[:,:,:grid[2]/2:-1] = gauss[:,:,1:(grid[2]+1)/2]     # trying to cope with uneven (odd) grid size
+    gauss[:,:,:grid[2]//2:-1] = gauss[:,:,1:(grid[2]+1)//2]     # trying to cope with uneven (odd) grid size
-    gauss[:,:grid[1]/2:-1,:] = gauss[:,1:(grid[1]+1)/2,:]
+    gauss[:,:grid[1]//2:-1,:] = gauss[:,1:(grid[1]+1)//2,:]
-    gauss[:grid[0]/2:-1,:,:] = gauss[1:(grid[0]+1)/2,:,:]
+    gauss[:grid[0]//2:-1,:,:] = gauss[1:(grid[0]+1)//2,:,:]
     gauss = np.fft.rfftn(gauss).astype(np.complex64)
 
   for smoothIter in range(options.N):
@@ -119,9 +119,9 @@ for name in filenames:
                                                           microstructure,i,axis=0), j,axis=1), k,axis=2)))
 
     # periodically extend interfacial energy array by half a grid size in positive and negative directions
-    periodic_interfaceEnergy = np.tile(interfaceEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
+    periodic_interfaceEnergy = np.tile(interfaceEnergy,(3,3,3))[grid[0]//2:-grid[0]//2,
-                                                                grid[1]/2:-grid[1]/2,
+                                                                grid[1]//2:-grid[1]//2,
-                                                                grid[2]/2:-grid[2]/2]
+                                                                grid[2]//2:-grid[2]//2]
 
     # transform bulk volume (i.e. where interfacial energy remained zero), store index of closest boundary voxel
     index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0.,                                            
@@ -148,15 +148,15 @@ for name in filenames:
                          ndimage.morphology.binary_dilation(interfaceEnergy > 0.,
                                                             structure = struc,
                                                             iterations = int(round(options.d*2.))-1),# fat boundary
-                         periodic_bulkEnergy[grid[0]/2:-grid[0]/2,                                 # retain filled energy on fat boundary...
+                         periodic_bulkEnergy[grid[0]//2:-grid[0]//2,                                 # retain filled energy on fat boundary...
-                                             grid[1]/2:-grid[1]/2,
+                                             grid[1]//2:-grid[1]//2,
-                                             grid[2]/2:-grid[2]/2],                                # ...and zero everywhere else
+                                             grid[2]//2:-grid[2]//2],                                # ...and zero everywhere else
                          0.)).astype(np.complex64) *
                          gauss).astype(np.float32)
 
-      periodic_diffusedEnergy = np.tile(diffusedEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
+      periodic_diffusedEnergy = np.tile(diffusedEnergy,(3,3,3))[grid[0]//2:-grid[0]//2,
-                                                                grid[1]/2:-grid[1]/2,
+                                                                grid[1]//2:-grid[1]//2,
-                                                                grid[2]/2:-grid[2]/2]              # periodically extend the smoothed bulk energy
+                                                                grid[2]//2:-grid[2]//2]              # periodically extend the smoothed bulk energy
 
 
     # transform voxels close to interface region
@@ -164,15 +164,15 @@ for name in filenames:
                                                       return_distances = False,
                                                       return_indices = True)                       # want index of closest bulk grain
 
-    periodic_microstructure = np.tile(microstructure,(3,3,3))[grid[0]/2:-grid[0]/2,
+    periodic_microstructure = np.tile(microstructure,(3,3,3))[grid[0]//2:-grid[0]//2,
-                                                              grid[1]/2:-grid[1]/2,
+                                                              grid[1]//2:-grid[1]//2,
-                                                              grid[2]/2:-grid[2]/2]                # periodically extend the microstructure
+                                                              grid[2]//2:-grid[2]//2]                # periodically extend the microstructure
 
     microstructure = periodic_microstructure[index[0],
                                              index[1],
-                                             index[2]].reshape(2*grid)[grid[0]/2:-grid[0]/2,
+                                             index[2]].reshape(2*grid)[grid[0]//2:-grid[0]//2,
-                                                                       grid[1]/2:-grid[1]/2,
+                                                                       grid[1]//2:-grid[1]//2,
-                                                                       grid[2]/2:-grid[2]/2]       # extent grains into interface region
+                                                                       grid[2]//2:-grid[2]//2]       # extent grains into interface region
 
     # replace immutable microstructures with closest mutable ones
     index = ndimage.morphology.distance_transform_edt(np.in1d(microstructure,options.immutable).reshape(grid),
@@ -236,3 +236,4 @@ for name in filenames:
 # --- output finalization --------------------------------------------------------------------------
 
   table.close()     
+  

processing/pre/seeds_fromDistribution.py

@@ -1,10 +1,11 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python3
 # -*- coding: UTF-8 no BOM -*-
 
 import threading,time,os,sys,random
 import numpy as np
 from optparse import OptionParser
-from cStringIO import StringIO
+from io import StringIO
+import binascii
 import damask
 
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
@@ -96,7 +97,7 @@ class myThread (threading.Thread):
       perturbedGeomVFile = StringIO()
       perturbedSeedsVFile.reset()
       perturbedGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
-                     ' -g '+' '.join(map(str, options.grid)),streamIn=perturbedSeedsVFile)[0])
+                     ' -g '+' '.join(list(map(str, options.grid))),streamIn=perturbedSeedsVFile)[0])
       perturbedGeomVFile.reset()
 
 #--- evaluate current seeds file ----------------------------------------------------------------------
@@ -214,7 +215,7 @@ options = parser.parse_args()[0]
 damask.util.report(scriptName,options.seedFile)
 
 if options.randomSeed is None:
-  options.randomSeed = int(os.urandom(4).encode('hex'), 16)
+  options.randomSeed = int(binascii.hexlify(os.urandom(4)),16)
 damask.util.croak(options.randomSeed)
 delta = (options.scale/options.grid[0],options.scale/options.grid[1],options.scale/options.grid[2])
 baseFile=os.path.splitext(os.path.basename(options.seedFile))[0]
@@ -240,17 +241,17 @@ if os.path.isfile(os.path.splitext(options.seedFile)[0]+'.seeds'):
     for line in initialSeedFile: bestSeedsVFile.write(line)
 else:
   bestSeedsVFile.write(damask.util.execute('seeds_fromRandom'+\
-                                ' -g '+' '.join(map(str, options.grid))+\
+                                ' -g '+' '.join(list(map(str, options.grid)))+\
                                 ' -r {:d}'.format(options.randomSeed)+\
                                 ' -N '+str(nMicrostructures))[0])
 bestSeedsUpdate = time.time()
 
 # ----------- tessellate initial seed file to get and evaluate geom file
-bestSeedsVFile.reset()
+bestSeedsVFile.seek(0)
 initialGeomVFile = StringIO()
 initialGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
-                               ' -g '+' '.join(map(str, options.grid)),bestSeedsVFile)[0])
+                               ' -g '+' '.join(list(map(str, options.grid))),bestSeedsVFile)[0])
-initialGeomVFile.reset()
+initialGeomVFile.seek(0)
 initialGeomTable = damask.ASCIItable(initialGeomVFile,None,labeled=False,readonly=True)
 initialGeomTable.head_read()
 info,devNull =  initialGeomTable.head_getGeom()