223031012
/
DAMASK_EICMD
mirror of https://github.com/achalhp/DAMASK_EICMD.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

Merge branch 'new-ASCII' into grid-filters

This commit is contained in:
Martin Diehl 2019-12-05 10:50:56 +01:00
parent 381c95bd1e 1018b89296
commit 274aaa7359
14 changed files with 280 additions and 227 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
processing/post/addCauchy.py
View File

@ -41,9 +41,9 @@ 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)
table.add_array('Cauchy',
damask.mechanics.Cauchy(table.get_array(options.defgrad).reshape(-1,3,3),
table.get_array(options.stress).reshape(-1,3,3)).reshape(-1,9),
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.to_ASCII(sys.stdout if name is None else name)

4
processing/post/addDeterminant.py
View File

@ -38,8 +38,8 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
for tensor in options.tensor:
table.add_array('det({})'.format(tensor),
np.linalg.det(table.get_array(tensor).reshape(-1,3,3)),
table.add('det({})'.format(tensor),
np.linalg.det(table.get(tensor).reshape(-1,3,3)),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

8
processing/post/addDeviator.py
View File

@ -40,12 +40,12 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
for tensor in options.tensor:
table.add_array('dev({})'.format(tensor),
damask.mechanics.deviatoric_part(table.get_array(tensor).reshape(-1,3,3)).reshape((-1,9)),
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_array('sph({})'.format(tensor),
damask.mechanics.spherical_part(table.get_array(tensor).reshape(-1,3,3)),
table.add('sph({})'.format(tensor),
damask.mechanics.spherical_part(table.get(tensor).reshape(-1,3,3)),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

29
processing/post/addInfo.py
View File

@ -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,
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.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
table.to_ASCII(sys.stdout if name is None else name)

8
processing/post/addMises.py
View File

@ -45,12 +45,12 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
for strain in options.strain:
table.add_array('Mises({})'.format(strain),
damask.mechanics.Mises_strain(damask.mechanics.symmetric(table.get_array(strain).reshape(-1,3,3))),
table.add('Mises({})'.format(strain),
damask.mechanics.Mises_strain(damask.mechanics.symmetric(table.get(strain).reshape(-1,3,3))),
scriptID+' '+' '.join(sys.argv[1:]))
for stress in options.stress:
table.add_array('Mises({})'.format(stress),
damask.mechanics.Mises_stress(damask.mechanics.symmetric(table.get_array(stress).reshape(-1,3,3))),
table.add('Mises({})'.format(stress),
damask.mechanics.Mises_stress(damask.mechanics.symmetric(table.get(stress).reshape(-1,3,3))),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

6
processing/post/addPK2.py
View File

@ -42,9 +42,9 @@ for name in filenames:
table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
table.add_array('S',
damask.mechanics.PK2(table.get_array(options.defgrad).reshape(-1,3,3),
table.get_array(options.stress).reshape(-1,3,3)).reshape(-1,9),
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:]))
table.to_ASCII(sys.stdout if name is None else name)

64
processing/post/reLabel.py
View File

@ -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,
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()
# ------------------------------------------ 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
table.to_ASCII(sys.stdout if name is None else name)

9
processing/post/scaleData.py
View File

@ -22,7 +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',
@ -31,7 +31,7 @@ parser.add_option('-f','--factor',
help = 'factor(s) per column')
parser.set_defaults(label = [],
)
factor = [])
(options,filenames) = parser.parse_args()
if filenames == []: filenames = [None]
@ -43,8 +43,9 @@ 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)
for i,label in enumerate(options.label):
table.set_array(label,table.get_array(label)*float(options.factor[i]),
for i,label in enumerate(options.labels):
table.set(label,
table.get(label)*float(options.factor[i]),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

9
processing/post/shiftData.py
View File

@ -22,7 +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',
@ -31,7 +31,7 @@ parser.add_option('-o','--offset',
help = 'offset(s) per column')
parser.set_defaults(label = [],
)
offset = [])
(options,filenames) = parser.parse_args()
if filenames == []: filenames = [None]
@ -43,8 +43,9 @@ 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)
for i,label in enumerate(options.label):
table.set_array(label,table.get_array(label)+float(options.offset[i]),
for i,label in enumerate(options.labels):
table.set(label,
table.get(label)+float(options.offset[i]),
scriptID+' '+' '.join(sys.argv[1:]))
table.to_ASCII(sys.stdout if name is None else name)

43
processing/post/sortTable.py
View File

@ -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,
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.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
table.to_ASCII(sys.stdout if name is None else name)

183
python/damask/table.py
View File

@ -1,3 +1,4 @@
import random
import re
import pandas as pd
@ -6,40 +7,40 @@ import numpy as np
class Table():
"""Store spreadsheet-like data."""
def __init__(self,array,headings,comments=None):
def __init__(self,data,shapes,comments=None):
"""
New spreadsheet data.
New spreadsheet.
Parameters
----------
array : numpy.ndarray
data : numpy.ndarray
Data.
headings : dict
Column headings. Labels as keys and shape as tuple. Example 'F':(3,3) for a deformation gradient.
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
Additional, human-readable information.
"""
self.data = pd.DataFrame(data=array)
self.data = pd.DataFrame(data=data)
d = {}
labels = {}
i = 0
for label in headings:
for components in range(np.prod(headings[label])):
d[i] = label
for label in shapes.keys():
for components in range(np.prod(shapes[label])):
labels[i] = label
i+=1
if i != self.data.shape[1]:
raise IndexError('Mismatch between array shape and headings')
raise IndexError('Shape mismatch between shapes and data')
self.data.rename(columns=d,inplace=True)
self.data.rename(columns=labels,inplace=True)
if comments is None:
self.comments = []
else:
self.comments = [c for c in comments]
self.headings = headings
self.shapes = shapes
@staticmethod
def from_ASCII(fname):
@ -47,8 +48,8 @@ class Table():
Create table from ASCII file.
The first line needs to indicate the number of subsequent header lines as 'n header'.
Vector data labels are indicated by '1_v, 2_v, ..., n_v'.
Tensor data labels are indicated by '3x3:1_T, 3x3:2_T, ..., 3x3:9_T'.
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
----------
@ -69,93 +70,159 @@ class Table():
comments = [f.readline()[:-1] for i in range(header-1)]
labels = f.readline().split()
headings = {}
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')
headings[label.split('_',1)[1]] = tuple([int(d) for d in my_shape])
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:
headings[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
shapes[label.split('_',1)[1]] = (int(label.split('_',1)[0]),)
else:
headings[label]=(1,)
shapes[label]=(1,)
return Table(np.loadtxt(f),headings,comments)
data = pd.read_csv(f,names=[i for i in range(len(labels))],sep=r'\s+').to_numpy()
def get_array(self,label):
return Table(data,shapes,comments)
def labels(self):
"""Return the labels of all columns."""
return list(self.shapes.keys())
def get(self,label):
"""
Return data as array.
Get column data.
Parameters
----------
label : str
Label of the array.
Column label.
"""
if re.match(r'[0-9]*?_',label):
idx,key = label.split('_',1)
return self.data[key].to_numpy()[:,int(idx)-1]
return self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
else:
return self.data[label].to_numpy().reshape((-1,)+self.headings[label])
return self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
def set_array(self,label,array,info):
def set(self,label,data,info=None):
"""
Modify data in the spreadsheet.
Set column data.
Parameters
----------
label : str
Label for the new data.
array : np.ndarray
Column label.
data : np.ndarray
New data.
info : str
info : str, optional
Human-readable information about the new data.
"""
if np.prod(array.shape[1:],dtype=int) == 1:
if info is not None:
if np.prod(data.shape[1:],dtype=int) == 1:
self.comments.append('{}: {}'.format(label,info))
else:
self.comments.append('{} {}: {}'.format(label,array.shape[1:],info))
self.comments.append('{} {}: {}'.format(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] = array
self.data.iloc[:,iloc] = data
else:
self.data[label] = array.reshape(self.data[label].shape)
self.data[label] = data.reshape(self.data[label].shape)
def get_labels(self):
"""Return the labels of all columns."""
return [label for label in self.headings]
def add_array(self,label,array,info):
def add(self,label,data,info=None):
"""
Add data to the spreadsheet.
Add column data.
Parameters
----------
label : str
Label for the new data.
array : np.ndarray
New data.
info : str
Human-readable information about the new data.
Column label.
data : np.ndarray
Modified data.
info : str, optional
Human-readable information about the modified data.
"""
if np.prod(array.shape[1:],dtype=int) == 1:
if info is not None:
if np.prod(data.shape[1:],dtype=int) == 1:
self.comments.append('{}: {}'.format(label,info))
else:
self.comments.append('{} {}: {}'.format(label,array.shape[1:],info))
self.comments.append('{} {}: {}'.format(label,data.shape[1:],info))
self.headings[label] = array.shape[1:] if len(array.shape) > 1 else (1,)
size = np.prod(array.shape[1:],dtype=int)
new_data = pd.DataFrame(data=array.reshape(-1,size),
self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
size = np.prod(data.shape[1:],dtype=int)
new_data = pd.DataFrame(data=data.reshape(-1,size),
columns=[label for l in range(size)])
self.data = pd.concat([self.data,new_data],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)
comments = '{} => {}'.format(label_old,label_new)
comments += ': {}'.format(info) if info is not None else ''
self.comments.append(comments)
self.shapes[label_new] = self.shapes.pop(label_old)
def sort_by(self,labels,ascending=True):
"""
Get column data.
Parameters
----------
label : list of str or str
Column labels.
ascending : bool, optional
Set sort order.
"""
_temp = []
_labels = []
for label in labels if isinstance(labels,list) else [labels]:
if re.match(r'[0-9]*?_',label):
_temp.append(str(random.getrandbits(128)))
self.add(_temp[-1],self.get(label))
_labels.append(_temp[-1])
else:
_labels.append(label)
self.data.sort_values(_labels,axis=0,inplace=True,ascending=ascending)
for t in _temp: self.delete(t)
self.comments.append('sorted by [{}]'.format(', '.join(labels)))
def to_ASCII(self,fname):
"""
Store as plain text file.
@ -167,15 +234,15 @@ class Table():
"""
labels = []
for l in self.headings:
if(self.headings[l] == (1,)):
for l in self.shapes:
if(self.shapes[l] == (1,)):
labels.append('{}'.format(l))
elif(len(self.headings[l]) == 1):
elif(len(self.shapes[l]) == 1):
labels+=['{}_{}'.format(i+1,l)\
for i in range(self.headings[l][0])]
for i in range(self.shapes[l][0])]
else:
labels+=['{}:{}_{}'.format('x'.join([str(d) for d in self.headings[l]]),i+1,l)\
for i in range(np.prod(self.headings[l],dtype=int))]
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\

4
python/tests/reference/Table/datatype-mix.txt Normal file
View File

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

6
python/tests/reference/Table/whitespace-mix.txt Normal file
View File

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

94
python/tests/test_Table.py
View File

@ -1,25 +1,40 @@
import os
import pytest
import numpy as np
from damask import Table
@pytest.fixture
def default():
"""Simple Table."""
x = np.ones((5,13))
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_tensor(self,default):
d = default.get_array('F')
assert np.allclose(d,1.0) and d.shape[1:] == (3,3)
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_array('v')
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')))
@ -32,26 +47,75 @@ class TestTable:
new = Table.from_ASCII(f)
assert all(default.data==new.data)
def test_set_array(self,default):
default.set_array('F',np.zeros((5,3,3)),'set to zero')
d=default.get_array('F')
@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_get_labels(self,default):
assert default.get_labels() == ['F','v','s']
def test_labels(self,default):
assert default.labels() == ['F','v','s']
def test_add_array(self,default):
def test_add(self,default):
d = np.random.random((5,9))
default.add_array('nine',d,'random data')
assert np.allclose(d,default.get_array('nine'))
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,default):
x = default.get_array('v')
x = default.get('v')
with pytest.raises(IndexError):
Table(x,{'F':(3,3)})
def test_invalid_set(self,default):
x = default.get_array('v')
x = default.get('v')
with pytest.raises(ValueError):
default.set_array('F',x,'does not work')
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',False)
sort = t.get('4_F')
assert np.all(np.sort(sort,0)==sort[::-1,:])