def test_include_04(self):
#if PY2:
#wb = 'wb'
#else:
#wb = 'w'
with codec_open('include4.bdf', 'w') as f:
f.write('$ pyNastran: punch=True\n')
f.write('$ pyNastran: dumplines=True\n')
f.write("INCLUDE 'include4b.inc'\n\n")
with codec_open('include4b.inc', 'w') as f:
f.write('$ GRID comment\n')
f.write('GRID,2,,2.0\n')
model = BDF(log=log, debug=False)
model.read_bdf('include4.bdf')
model.write_bdf('include4.out.bdf')
os.remove('include4.out.bdf')
os.remove('include4b.inc')
#os.remove('include4.inc')
# os.remove('c.bdf')
# os.remove('executive_control.inc')
# os.remove('case_control.inc')
self.assertEqual(len(model.nodes), 1)
self.assertEqual(model.nnodes, 1, 'nnodes=%s' % model.nnodes)
def test_include_05(self):
with codec_open('include5.bdf', 'w') as bdf_file:
bdf_file.write('$ pyNastran: punch=True\n')
bdf_file.write('$ pyNastran: dumplines=True\n')
bdf_file.write("INCLUDE 'include5b.inc'\n\n")
with codec_open('include5b.inc', 'w') as bdf_file:
bdf_file.write('ECHOON\n')
bdf_file.write('$ GRID comment\n')
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write('ECHOOFF\n')
bdf_file.write('GRID,3,,3.0\n')
bdf_file.write('grid,4,,4.0\n')
bdf_file.write('grid ,5,,5.0\n')
model = BDF(log=log, debug=False)
model.read_bdf('include5.bdf')
assert model.echo is False, model.echo
#model.write_bdf('include5.out.bdf')
# os.remove('c.bdf')
# os.remove('executive_control.inc')
# os.remove('case_control.inc')
self.assertEqual(len(model.nodes), 4)
self.assertEqual(model.nnodes, 4, 'nnodes=%s' % model.nnodes)
model2 = read_bdf(bdf_filename='include5.bdf', xref=True, punch=False,
log=log, encoding=None)
self.assertEqual(len(model2.nodes), 4)
self.assertEqual(model2.nnodes, 4, 'nnodes=%s' % model.nnodes)
os.remove('include5.bdf')
#os.remove('include5.out.bdf')
os.remove('include5b.inc')
def test_include_end_02(self):
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write('CEND\n')
bdf_file.write('BEGIN BULK\n')
bdf_file.write('GRID,1,,1.0\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
bdf_file.write('GRID,4,,4.0\n')
with codec_open('b.bdf', 'w') as bdf_file:
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write("INCLUDE 'c.bdf'\n\n")
bdf_file.write('GRID,5,,5.0\n')
with codec_open('c.bdf', 'w') as bdf_file:
bdf_file.write('GRID,3,,3.0\n\n')
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 5)
self.assertEqual(model.nnodes, 5, 'nnodes=%s' % model.nnodes)
def Initialize():
#key = chunk_id of first chunk in hit
#value = Row object
fragment_dict = defaultdict(list)
#key = video_id
#value = Video object
video_dict = defaultdict(Video)
with codec_open(fragment_HIT, 'rb', 'utf-8') as fragment_csv:
f = list( csv.reader(fragment_csv) )
for row in f[1:]:
fragment_list = []
total_clip_time = 0
chunks = [ row[i:i+5] for i in range(0, len(row), 5) ]
for c in chunks:
temp = Fragment(c[0], c[1], c[2], c[3])
total_clip_time += temp.duration
fragment_list.append( temp )
cur_row = Row(total_clip_time, fragment_list)
fragment_dict[fragment_list[0].id] = cur_row
with codec_open(full_CSV, 'rb', 'utf-8') as full_csv:
f = list( csv.reader(full_csv) )
for row in f[1:]:
temp = Video(row[0], row[5])
video_dict[temp.id] = temp
return fragment_dict,video_dict
def test_include_04(self):
"""tests pyNastran: punch=True with includes"""
with codec_open('include4.bdf', 'w') as bdf_file:
bdf_file.write('$ pyNastran: punch=True\n')
bdf_file.write('$ pyNastran: dumplines=True\n')
bdf_file.write("INCLUDE 'include4b.inc'\n\n")
with codec_open('include4b.inc', 'w') as bdf_file:
bdf_file.write('$ GRID comment\n')
bdf_file.write('GRID,2,,2.0\n')
model = BDF(log=log, debug=False)
model.read_bdf('include4.bdf')
model.write_bdf('include4.out.bdf')
os.remove('include4.out.bdf')
os.remove('include4b.inc')
os.remove('include4.bdf')
#os.remove('include4.inc')
# os.remove('c.bdf')
# os.remove('executive_control.inc')
# os.remove('case_control.inc')
self.assertEqual(len(model.nodes), 1)
self.assertEqual(model.nnodes, 1, 'nnodes=%s' % model.nnodes)
def Initialize():
#key = chunk_id of first chunk in hit
#value = Row object
fragment_dict = defaultdict(list)
#key = video_id
#value = Video object
video_dict = defaultdict(Video)
with codec_open(fragment_HIT, 'rb', 'utf-8') as fragment_csv:
f = list(csv.reader(fragment_csv))
for row in f[1:]:
fragment_list = []
total_clip_time = 0
chunks = [row[i:i + 5] for i in range(0, len(row), 5)]
for c in chunks:
temp = Fragment(c[0], c[1], c[2], c[3])
total_clip_time += temp.duration
fragment_list.append(temp)
cur_row = Row(total_clip_time, fragment_list)
fragment_dict[fragment_list[0].id] = cur_row
with codec_open(full_CSV, 'rb', 'utf-8') as full_csv:
f = list(csv.reader(full_csv))
for row in f[1:]:
temp = Video(row[0], row[5])
video_dict[temp.id] = temp
return fragment_dict, video_dict
def test_include_end(self):
"""tests multiple levels of includes"""
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write('CEND\n')
bdf_file.write('BEGIN BULK\n')
bdf_file.write('GRID,1,,1.0\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
with codec_open('b.bdf', 'w') as bdf_file:
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write("INCLUDE 'c.bdf'\n\n")
with codec_open('c.bdf', 'w') as bdf_file:
bdf_file.write('GRID,3,,3.0\n\n')
bdf_file.write("ENDDATA\n")
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 3)
self.assertEqual(model.nnodes, 3, 'nnodes=%s' % model.nnodes)
def test_include_05(self):
#if PY2:
#wb = 'wb'
#else:
#wb = 'w'
with codec_open('include5.bdf', 'w') as f:
f.write('$ pyNastran: punch=True\n')
f.write('$ pyNastran: dumplines=True\n')
f.write("INCLUDE 'include5b.inc'\n\n")
with codec_open('include5b.inc', 'w') as f:
f.write('ECHOON\n')
f.write('$ GRID comment\n')
f.write('GRID,2,,2.0\n')
f.write('ECHOOFF\n')
f.write('GRID,3,,3.0\n')
f.write('grid,4,,4.0\n')
f.write('grid ,5,,5.0\n')
model = BDF(log=log, debug=False)
model.read_bdf('include5.bdf')
assert model.echo == False, model.echo
#model.write_bdf('include4.out.bdf')
os.remove('include5.bdf')
#os.remove('include5.out.bdf')
os.remove('include5b.inc')
# os.remove('c.bdf')
# os.remove('executive_control.inc')
# os.remove('case_control.inc')
self.assertEqual(len(model.nodes), 4)
self.assertEqual(model.nnodes, 4, 'nnodes=%s' % model.nnodes)
def test_include_end(self):
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write('CEND\n')
bdf_file.write('BEGIN BULK\n')
bdf_file.write('GRID,1,,1.0\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
with codec_open('b.bdf', 'w') as bdf_file:
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write("INCLUDE 'c.bdf'\n\n")
with codec_open('c.bdf', 'w') as bdf_file:
bdf_file.write('GRID,3,,3.0\n\n')
bdf_file.write("ENDDATA\n")
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 3)
self.assertEqual(model.nnodes, 3, 'nnodes=%s' % model.nnodes)
def UpdateMturkCSV(self, name):
csv_original = list(
csv.reader(
codec_open(os.path.join(MTURK_DIR, name + "_results.csv"),
'rb', 'utf-8')))
filtered_dir = os.getcwd() + '/filtered'
with codec_open(
os.path.join(filtered_dir, name + "_results_filtered.csv"),
'w', 'utf-8') as csv_filtered:
csv_writer = csv.writer(csv_filtered)
for i in range(len(csv_original)):
if i == 0:
# AssignmentStatus = csv_original[0].index('AssignmentStatus')
# RequesterFeedback = csv_original[0].index('RequesterFeedback')
# Reject = csv_original[0].index('Reject')
pass
else:
hit = self.HIT_list[i - 1]
if hit.reject_flag:
#csv_original[i][AssignmentStatus] = 'Rejected'
#csv_original[i][RequesterFeedback] = hit.reject_reason
csv_original[i].append('')
csv_original[i].append(hit.reject_reason)
csv_writer.writerow(csv_original[i])
def test_case_control_08(self):
lines_expected = [
'$pyNastran: version=msc\n',
'$pyNastran: punch=True\n',
'$pyNastran: encoding=ascii\n',
'$NODES\n',
'GRID,100000,,43.91715,-29.,.8712984\n',
]
bdf_filename = 'test7.bdf'
bdf_filename2 = 'test7_bad.bdf'
with codec_open(bdf_filename, 'w', encoding='ascii') as f:
for line in lines_expected:
f.write(line)
bdf = BDF()
bdf.read_bdf(bdf_filename)
bdf.write_bdf(bdf_filename2)
with codec_open(bdf_filename, 'r', encoding='ascii') as f:
lines = f.readlines()
i = 0
for line, line_expected in zip(lines, lines_expected):
line = line.rstrip()
line_expected = line_expected.rstrip()
msg = 'The lines are not the same...i=%s\n' % i
msg += 'line = %r\n' % line
msg += 'expected = %r\n' % line_expected
msg += '-------------\n--Actual--\n%s' % ''.join(lines)
msg += '-------------\n--Expected--\n%s' % ''.join(lines_expected)
self.assertEqual(line, line_expected, msg)
i += 1
def test_include_end_02(self):
with codec_open('a.bdf', 'w') as f:
f.write('CEND\n')
f.write('BEGIN BULK\n')
f.write('GRID,1,,1.0\n')
f.write("INCLUDE 'b.bdf'\n\n")
f.write('GRID,4,,4.0\n')
with codec_open('b.bdf', 'w') as f:
f.write('GRID,2,,2.0\n')
f.write("INCLUDE 'c.bdf'\n\n")
f.write('GRID,5,,5.0\n')
with codec_open('c.bdf', 'w') as f:
f.write('GRID,3,,3.0\n\n')
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 5)
self.assertEqual(model.nnodes, 5, 'nnodes=%s' % model.nnodes)
def test_tri_180_01(self):
r"""
Identify a reasonable tri with super tight tolerances
y
^ 4
| / /
| / /
| / /
| / /
/ /
1------2-------> x
"""
msg = (
'CEND\n'
'BEGIN BULK\n'
'GRID,1,,0.,0.,0.\n'
'GRID,2,,1.,0.,0.\n'
'GRID,4,,2., 1.,0.\n'
'CTRIA3,100,1, 1,2,4\n'
'PSHELL,1,1,0.1\n'
'MAT1,1,3.0,, 0.3\n'
'ENDDATA'
)
bdf_filename = 'ctria3.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.write(msg)
model = read_bdf(bdf_filename, xref=True)
eids_to_delete = get_bad_shells(model, max_theta=180.,
max_skew=1000., max_aspect_ratio=1000.)
assert eids_to_delete == [100], eids_to_delete
os.remove(bdf_filename)
def get_content(article):
source_content = None
with codec_open(article.source_path, 'r', 'utf-8') as source_file:
source_content = source_file.read()
if path.splitext(article.source_path)[1] == '.rst':
return parse_rst_content(article.source_path, source_content)
return source_content
def AVFull(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.id
#[28] = Input.transcription
#[33] = Answer.partial_transcription
#[34] = Answer.“polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as audio_full_csv:
f = list(csv.reader(audio_full_csv))
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
vid_id = [row[27]]
vid_transcription = [row[33]]
answer_polarity = [row[34]]
age = row[30]
location = row[31]
gender = row[32]
temp = HIT(hit_id, worker_id, work_time, vid_id, answer_polarity,
age, location, gender)
temp.transcriptions = set(vid_transcription)
for field in [age, location, gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append(temp)
return HIT_list
def TextFull(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.id
#[33] = Answer.“polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as text_full_csv:
f = list(csv.reader(text_full_csv))
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
vid_id = [row[27]]
answer_polarity = [row[32]]
age, location = row[30].split('|')
gender = row[31]
temp = HIT(hit_id, worker_id, work_time, vid_id, answer_polarity,
age, location, gender)
for field in [age, location, gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append(temp)
return HIT_list
def get_content(article):
source_content = None
with codec_open(article.source_path, 'r', 'utf-8') as source_file:
source_content = source_file.read()
if path.splitext(article.source_path)[1] == '.rst':
return parse_rst_content(article.source_path, source_content)
return source_content
def AVFull(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.id
#[28] = Input.transcription
#[33] = Answer.partial_transcription
#[34] = Answer.“polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as audio_full_csv:
f = list( csv.reader(audio_full_csv) )
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
vid_id = [row[27]]
vid_transcription = [row[33]]
answer_polarity = [row[34]]
age = row[30]
location = row[31]
gender = row[32]
temp = HIT(hit_id, worker_id, work_time, vid_id, answer_polarity, age, location, gender)
temp.transcriptions = set(vid_transcription)
for field in [age,location,gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append( temp )
return HIT_list
def TextFull(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.id
#[33] = Answer.“polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as text_full_csv:
f = list( csv.reader(text_full_csv) )
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
vid_id = [row[27]]
answer_polarity = [row[32]]
age,location = row[30].split('|')
gender = row[31]
temp = HIT(hit_id, worker_id, work_time, vid_id, answer_polarity, age, location, gender)
for field in [age,location,gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append( temp )
return HIT_list
def test_enddata_1(self):
"""
There is an ENDDATA is in the baseline BDF, so None -> ENDDATA
"""
model = BDF(debug=False)
full_path = os.path.join(test_path, 'include_dir')
model2 = BDF(debug=False)
bdf_filename = 'test_include.bdf'
if not os.path.exists(bdf_filename):
bdf_filename = os.path.join(test_path, bdf_filename)
model2.read_bdf(bdf_filename, xref=True, punch=False)
for out_filename, is_enddata, write_flag in [
('enddata1.bdf', True, None),
('enddata2.bdf', True, True),
('enddata3.bdf', False, False)]:
out_filename = os.path.join(test_path, out_filename)
model2.write_bdf(out_filename=out_filename+'.out', interspersed=True, size=8,
is_double=False, enddata=write_flag)
with codec_open(out_filename + '.out', 'r') as f:
data = f.read()
if is_enddata:
self.assertTrue('ENDDATA' in data)
else:
self.assertFalse('ENDDATA' in data)
os.remove(out_filename + '.out')
def load_csv(out_filename, encoding='latin1'):
"""
The GUI CSV loading function.
Considers:
- extension in determining how to load a file (e.g. commas or not)
- header line of file for information regarding data types
"""
ext = os.path.splitext(out_filename)[1].lower()
if ext not in ['.csv', '.dat', '.txt']:
raise NotImplementedError(
'extension=%r is not supported (use .dat, .txt, or .csv)' % ext)
with codec_open(_filename(out_filename), 'r',
encoding=encoding) as file_obj:
names, fmt_dict, dtype, delimiter = _load_format_header(
file_obj, ext, force_float=False)
try:
#A = loadtxt(file_obj, dtype=dtype, delimiter=delimiter)
A = loadtxt_nice(file_obj, dtype=dtype, delimiter=delimiter)
except:
traceback.print_exc(file=sys.stdout)
msg = 'extension=%r nheaders=%s delimiter=%r dtype=%s' % (
ext, len(names), delimiter, dtype)
raise RuntimeError(msg)
return A, fmt_dict, names
def write_cart3d(self, outfilename, is_binary=False, float_fmt='%6.7f'):
assert len(self.points) > 0, 'len(self.points)=%s' % len(self.points)
if self.loads is None or self.loads == {}:
loads = {}
is_loads = False
# print("no loads")
else:
is_loads = True
self.log.info("---writing cart3d file...%r---" % outfilename)
if is_binary:
form = 'wb'
else:
if PY2:
form = 'w'
else:
form = 'wb'
with codec_open(outfilename, form) as outfile:
int_fmt = self._write_header(outfile, self.points, self.elements, is_loads, is_binary)
self._write_points(outfile, self.points, is_binary, float_fmt)
self._write_elements(outfile, self.elements, is_binary, int_fmt)
self._write_regions(outfile, self.regions, is_binary)
if is_loads:
assert is_binary is False, 'is_binary=%r is not supported for loads' % is_binary
self._write_loads(outfile, self.loads, is_binary, float_fmt)
outfile.close()
def test_encoding_write(self):
from pyNastran.bdf.bdf import BDF
mesh = BDF()
mesh.add_card(['GRID', 100000, 0, 43.91715, -29., .8712984], 'GRID')
mesh.write_bdf('out.bdf')
lines_expected = [
'$pyNastran: version=msc',
'$pyNastran: punch=False',
'$pyNastran: encoding=ascii',
'$NODES',
'GRID 100000 43.91715 -29..8712984',
]
bdf_filename = 'out.bdf'
with codec_open(bdf_filename, 'r', encoding='ascii') as f:
lines = f.readlines()
i = 0
for line, line_expected in zip(lines, lines_expected):
line = line.rstrip()
line_expected = line_expected.rstrip()
msg = 'The lines are not the same...i=%s\n' % i
msg += 'line = %r\n' % line
msg += 'expected = %r\n' % line_expected
msg += '-------------\n--Actual--\n%s' % ''.join(lines)
msg += '-------------\n--Expected--\n%s' % ''.join(lines_expected)
self.assertEqual(line, line_expected, msg)
i += 1
def read(*parts):
"""
Build an absolute path from *parts* and and return the contents of the
resulting file. Assume UTF-8 encoding.
"""
with codec_open(joinpath(HERE, *parts), 'rb', 'utf-8') as dfp:
return dfp.read()
def write_cart3d(self, outfilename, is_binary=False, float_fmt='%6.7f'):
"""
writes a cart3d file
"""
assert len(self.points) > 0, 'len(self.points)=%s' % len(self.points)
if self.loads is None or self.loads == {}:
loads = {}
is_loads = False
else:
is_loads = True
self.log.info("---writing cart3d...%r---" % outfilename)
if is_binary:
form = 'wb'
else:
form = write_ascii
with codec_open(outfilename, form) as outfile:
int_fmt = self._write_header(outfile, self.points, self.elements,
is_loads, is_binary)
self._write_points(outfile, self.points, is_binary, float_fmt)
self._write_elements(outfile, self.elements, is_binary, int_fmt)
self._write_regions(outfile, self.regions, is_binary)
if is_loads:
assert is_binary is False, 'is_binary=%r is not supported for loads' % is_binary
self._write_loads(outfile, self.loads, is_binary, float_fmt)
def _open_file(self, bdf_filename, basename=False, check=True):
"""
Opens a new bdf_filename with the proper encoding and include directory
Parameters
----------
bdf_filename : str
the filename to open
basename : bool (default=False)
should the basename of bdf_filename be appended to the include directory
"""
if basename:
bdf_filename_inc = os.path.join(self.include_dir,
os.path.basename(bdf_filename))
else:
bdf_filename_inc = os.path.join(self.include_dir, bdf_filename)
self._validate_open_file(bdf_filename, bdf_filename_inc, check)
self.log.debug('opening %r' % bdf_filename_inc)
self.active_filenames.append(bdf_filename_inc)
#print('ENCODING - _open_file=%r' % self.encoding)
bdf_file = codec_open(_filename(bdf_filename_inc),
'r',
encoding=self.encoding)
return bdf_file
def load_file_contents(file_path, as_list=True):
"""Load file as string or list"""
abs_file_path = path.join(HERE, file_path)
with codec_open(abs_file_path, encoding='utf-8') as file_pointer:
if as_list:
return file_pointer.read().splitlines()
return file_pointer.read()
def test_include_stop(self):
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write('CEND\n')
bdf_file.write('BEGIN BULK\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
bdf_file.write('GRID,1,,1.0\n')
model = BDF(log=log, debug=False)
with self.assertRaises(IOError):
model.read_bdf(bdf_filename='a.bdf',
xref=True,
punch=False,
read_includes=True,
encoding=None)
with self.assertRaises(IOError):
read_bdf(bdf_filename='a.bdf',
xref=True,
punch=False,
encoding=None,
log=log)
model.read_bdf(bdf_filename='a.bdf',
xref=True,
punch=False,
read_includes=False,
encoding=None)
model.write_bdf('out.bdf')
os.remove('a.bdf')
os.remove('out.bdf')
def test_enddata_1(self):
"""
There is an ENDDATA is in the baseline BDF, so None -> ENDDATA
"""
model2 = BDF(log=log, debug=False)
bdf_filename = 'test_include.bdf'
if not os.path.exists(bdf_filename):
bdf_filename = os.path.join(test_path, bdf_filename)
model2.read_bdf(bdf_filename, xref=True, punch=False)
cases = [
('enddata1.bdf', True, None),
('enddata2.bdf', True, True),
('enddata3.bdf', False, False),
]
for out_filename, is_enddata, write_flag in cases:
out_filename = os.path.join(test_path, out_filename)
model2.write_bdf(out_filename=out_filename + '.out',
interspersed=True,
size=8,
is_double=False,
enddata=write_flag)
with codec_open(out_filename + '.out', 'r') as bdf_file:
data = bdf_file.read()
if is_enddata:
self.assertTrue('ENDDATA' in data)
else:
self.assertFalse('ENDDATA' in data)
os.remove(out_filename + '.out')
def test_enddata_2(self):
"""
There is no ENDDATA is in the baseline BDF, so None -> no ENDDATA
"""
model = BDF(debug=False)
full_path = os.path.join(test_path, 'include_dir')
model2 = BDF(debug=False)
bdf_name = os.path.join(test_path, 'test_mass.dat')
model2.read_bdf(bdf_name, xref=True, punch=False)
for out_filename, is_enddata, write_flag in [
('test_mass1.dat', False, None),
('test_mass2.dat', True, True),
('test_mass3.dat', False, False)]:
model2.write_bdf(out_filename=out_filename, interspersed=True, size=8,
is_double=False, enddata=write_flag)
with codec_open(out_filename, 'r') as f:
data = f.read()
msg = 'outfilename=%r expected=%r write_flag=%s card_count=%r' % (out_filename, is_enddata, write_flag, model2.card_count.keys())
if is_enddata:
self.assertTrue('ENDDATA' in data, msg)
else:
self.assertFalse('ENDDATA' in data, msg)
os.remove(out_filename)
def test_tri_180_01(self):
r"""
Identify a reasonable tri with super tight tolerances
y
^ 4
| / /
| / /
| / /
| / /
/ /
1------2-------> x
"""
msg = (
'CEND\n'
'BEGIN BULK\n'
'GRID,1,,0.,0.,0.\n'
'GRID,2,,1.,0.,0.\n'
'GRID,4,,2., 1.,0.\n'
'CTRIA3,100,1, 1,2,4\n'
'PSHELL,1,1,0.1\n'
'MAT1,1,3.0,, 0.3\n'
'ENDDATA'
)
bdf_filename = 'ctria3.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.write(msg)
model = read_bdf(bdf_filename, xref=True)
eids_to_delete = get_bad_shells(model, max_theta=180.,
max_skew=1000., max_aspect_ratio=1000.)
assert eids_to_delete == [100], eids_to_delete
os.remove(bdf_filename)
def read_cart3d(self, infilename, result_names=None):
"""extracts the points, elements, and Cp"""
self.infilename = infilename
self.log.info("---starting reading cart3d file...%r---" % self.infilename)
self.infilename = infilename
if is_binary_file(infilename):
with open(infilename, 'rb') as self.infile:
npoints, nelements, nresults = self._read_header_binary()
self.points = self._read_points_binary(npoints)
self.elements = self._read_elements_binary(nelements)
self.regions = self._read_regions_binary(nelements)
# TODO: loads
else:
with codec_open(_filename(infilename), 'r', encoding=self._encoding) as self.infile:
npoints, nelements, nresults = self._read_header_ascii()
self.points = self._read_points_ascii(npoints)
self.elements = self._read_elements_ascii(nelements)
self.regions = self._read_regions_ascii(nelements)
self._read_results_ascii(0, self.infile, nresults, result_names=result_names)
self.log.debug("npoints=%s nelements=%s" % (self.npoints, self.nelements))
self.log.info("---finished reading cart3d file...%r---" % self.infilename)
assert self.npoints > 0, 'npoints=%s' % self.npoints
assert self.nelements > 0, 'nelements=%s' % self.nelements
def test_enddata_2(self):
"""
There is no ENDDATA is in the baseline BDF, so None -> no ENDDATA
"""
model2 = BDF(log=log, debug=False)
bdf_name = os.path.join(test_path, 'test_mass.dat')
model2.read_bdf(bdf_name, xref=True, punch=False)
cases = [('test_mass1.dat', False, None),
('test_mass2.dat', True, True),
('test_mass3.dat', False, False)]
for out_filename, is_enddata, write_flag in cases:
model2.write_bdf(out_filename=out_filename,
interspersed=True,
size=8,
is_double=False,
enddata=write_flag)
with codec_open(out_filename, 'r') as bdf_file:
data = bdf_file.read()
msg = 'outfilename=%r expected=%r write_flag=%s card_count=%r' % (
out_filename, is_enddata, write_flag, model2.card_count.keys())
if is_enddata:
self.assertTrue('ENDDATA' in data, msg)
else:
self.assertFalse('ENDDATA' in data, msg)
os.remove(out_filename)
def test_eq4(self):
r"""
5
6 *-------* 40
| \ |
| \ |
| \ |
*-------* 3
1 20
"""
msg = 'CEND\n'
msg += 'BEGIN BULK\n'
msg += 'GRID,1, , 0., 0., 0.\n'
msg += 'GRID,20,, 1., 0., 0.\n'
msg += 'GRID,3, , 1.01, 0., 0.\n'
msg += 'GRID,41,, 1., 1., 0.\n' # eq
msg += 'GRID,4,, 1., 1., 0.\n' # eq
msg += 'GRID,40,, 1., 1., 0.\n' # eq
msg += 'GRID,4,, 1., 1., 0.\n' # eq
msg += 'GRID,5, , 0., 1., 0.\n'
msg += 'GRID,6, , 0., 1.01, 0.\n'
msg += 'CTRIA3,1, 100,1,20,6\n'
msg += 'CTRIA3,10,100,3,40,5\n'
msg += 'PSHELL,100,1000,0.1\n'
msg += 'MAT1,1000,3.0,, 0.3\n'
msg += 'ENDDATA'
bdf_filename = 'nonunique.bdf'
bdf_filename_out = 'unique.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.write(msg)
tol = 0.2
node_set = [4, 40, 41]
# Collapse 5/6 and 20/3; Put a 40 and 20 to test non-sequential IDs
bdf_equivalence_nodes(bdf_filename, bdf_filename_out, tol,
renumber_nodes=False, neq_max=4, xref=True,
node_set=node_set, crash_on_collapse=False,
log=log, debug=False)
model = BDF(log=log, debug=False)
model.read_bdf(bdf_filename_out)
nids = model.nodes.keys()
assert len(model.nodes) == 6, 'nnodes=%s nodes=%s' % (len(model.nodes), nids)
assert 1 in nids, nids
assert 20 in nids, nids
assert 3 in nids, nids
assert 4 in nids, nids
assert 5 in nids, nids
assert 6 in nids, nids
assert 40 not in nids, nids
assert 41 not in nids, nids
#print(nids)
os.remove(bdf_filename)
os.remove(bdf_filename_out)
def writePage(path, page):
(parent, file) = os.path.split(path)
if settings.verbose:
print('writing ' + path)
if (os.path.isfile(path)):
os.remove(path)
ensure_dir(parent)
with codec_open(path, mode="a", encoding="utf-8") as htmlFile:
htmlFile.write(page)
def test_eq4(self):
r"""
5
6 *-------* 40
| \ |
| \ |
| \ |
*-------* 3
1 20
"""
msg = 'CEND\n'
msg += 'BEGIN BULK\n'
msg += 'GRID,1, , 0., 0., 0.\n'
msg += 'GRID,20,, 1., 0., 0.\n'
msg += 'GRID,3, , 1.01, 0., 0.\n'
msg += 'GRID,41,, 1., 1., 0.\n' # eq
msg += 'GRID,4,, 1., 1., 0.\n' # eq
msg += 'GRID,40,, 1., 1., 0.\n' # eq
msg += 'GRID,4,, 1., 1., 0.\n' # eq
msg += 'GRID,5, , 0., 1., 0.\n'
msg += 'GRID,6, , 0., 1.01, 0.\n'
msg += 'CTRIA3,1, 100,1,20,6\n'
msg += 'CTRIA3,10,100,3,40,5\n'
msg += 'PSHELL,100,1000,0.1\n'
msg += 'MAT1,1000,3.0,, 0.3\n'
msg += 'ENDDATA'
bdf_filename = 'nonunique.bdf'
bdf_filename_out = 'unique.bdf'
bdf_file = codec_open(bdf_filename, 'w')
bdf_file.write(msg)
bdf_file.close()
tol = 0.2
node_set = [4, 40, 41]
# Collapse 5/6 and 20/3; Put a 40 and 20 to test non-sequential IDs
bdf_equivalence_nodes(bdf_filename, bdf_filename_out, tol,
renumber_nodes=False, neq_max=4, xref=True,
node_set=node_set, crash_on_collapse=False, debug=False)
model = BDF(debug=False)
model.read_bdf(bdf_filename_out)
nids = model.nodes.keys()
assert len(model.nodes) == 6, 'nnodes=%s nodes=%s' % (len(model.nodes), nids)
assert 1 in nids, nids
assert 20 in nids, nids
assert 3 in nids, nids
assert 4 in nids, nids
assert 5 in nids, nids
assert 6 in nids, nids
assert 40 not in nids, nids
assert 41 not in nids, nids
#print(nids)
os.remove(bdf_filename)
os.remove(bdf_filename_out)
def writePage (path, page):
(parent, file ) = os.path.split(path)
if settings.verbose:
print ('writing ' + path)
if (os.path.isfile(path)):
os.remove(path)
ensure_dir(parent)
with codec_open(path, mode="a", encoding="utf-8") as htmlFile:
htmlFile.write(page)
def nastran_to_cart3d_filename(bdf_filename, cart3d_filename, log=None, debug=False):
"""
Creates a Nastran BDF from a Cart3D file.
Parameters
----------
bdf_filename : str
the path to the bdf file
cart3d_filename : str
the path to the cart3d output file
log : log; default=None -> dummyLogger
a logger object
debug : bool; default=False
True/False (used if log is not defined)
"""
model = BDF(log=log, debug=debug)
model.read_bdf(bdf_filename)
nnodes = len(model.nodes)
nelements = len(model.elements)
f = codec_open(cart3d_filename, 'w', encoding='utf8')
f.write('%s %s\n' % (nnodes, nelements))
node_id_shift = {}
i = 1
for node_id, node in sorted(iteritems(model.nodes)):
node_id_shift[node_id] = i
x, y, z = node.get_position()
f.write('%s %s %s\n' % (x, y, z))
i += 1
mids = ''
j = 0
for element_id, element in sorted(iteritems(model.elements)):
if element.type in ['CQUADR', 'CQUAD4', 'CONM2']:
print('element type=%s is not supported' % element.type)
continue
assert element.type in ['CTRIA3', 'CTRIAR'], element.type
out = element.node_ids
try:
n1, n2, n3 = out
except:
print("type =", element.type)
raise
#print out
n1 = node_id_shift[n1]
n2 = node_id_shift[n2]
n3 = node_id_shift[n3]
mid = element.Mid()
f.write('%i %i %i\n' % (n1, n2, n3))
mids += '%i ' % mid
if j != 0 and j % 20 == 0:
mids += '\n'
j += 1
f.write(mids + '\n')
f.close()
def nastran_to_cart3d_filename(bdf_filename,
cart3d_filename,
log=None,
debug=False):
"""
Creates a Nastran BDF from a Cart3D file.
Parameters
----------
bdf_filename : str
the path to the bdf file
cart3d_filename : str
the path to the cart3d output file
log : log; default=None -> dummyLogger
a logger object
debug : bool; default=False
True/False (used if log is not defined)
"""
model = BDF(log=log, debug=debug)
model.read_bdf(bdf_filename)
nnodes = len(model.nodes)
nelements = len(model.elements)
with codec_open(cart3d_filename, 'w', encoding='utf8') as cart3d:
cart3d.write('%s %s\n' % (nnodes, nelements))
node_id_shift = {}
i = 1
for node_id, node in sorted(iteritems(model.nodes)):
node_id_shift[node_id] = i
x, y, z = node.get_position()
cart3d.write('%s %s %s\n' % (x, y, z))
i += 1
mids = ''
j = 0
for element_id, element in sorted(iteritems(model.elements)):
if element.type in ['CQUADR', 'CQUAD4', 'CONM2']:
print('element type=%s is not supported' % element.type)
continue
assert element.type in ['CTRIA3', 'CTRIAR'], element.type
out = element.node_ids
try:
n1, n2, n3 = out
except:
print("type =", element.type)
raise
n1 = node_id_shift[n1]
n2 = node_id_shift[n2]
n3 = node_id_shift[n3]
mid = element.Mid()
cart3d.write('%i %i %i\n' % (n1, n2, n3))
mids += '%i ' % mid
if j != 0 and j % 20 == 0:
mids += '\n'
j += 1
cart3d.write(mids + '\n')
def test_include_03(self):
if PY2:
wb = 'wb'
else:
wb = 'w'
with codec_open('a.bdf', 'w') as f:
f.write("INCLUDE 'executive_control.inc'\n\n")
f.write('CEND\n')
f.write("INCLUDE 'case_control.inc'\n\n")
f.write('BEGIN BULK\n')
f.write('GRID,1,,1.0\n')
f.write("INCLUDE 'b.bdf'\n\n")
f.write('GRID,4,,4.0\n')
with codec_open('executive_control.inc', 'w') as f:
f.write('SOL = 103\n')
with codec_open('case_control.inc', 'w') as f:
f.write('DISP = ALL\n')
with codec_open('b.bdf', 'w') as f:
f.write('GRID,2,,2.0\n')
f.write("INCLUDE 'c.bdf'\n\n")
f.write('GRID,5,,5.0\n')
with codec_open('c.bdf', 'w') as f:
f.write('GRID,3,,3.0\n\n')
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('executive_control.inc')
os.remove('case_control.inc')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 5)
self.assertEqual(model.nnodes, 5, 'nnodes=%s' % model.nnodes)
def test_case_control_08(self):
lines_expected = [
'$pyNastran: version=msc\n',
'$pyNastran: punch=True\n',
'$pyNastran: encoding=ascii\n' if PY2 else '$pyNastran: encoding=utf-8\n',
'$NODES\n',
'GRID,100000,,43.91715,-29.,.8712984\n',
]
bdf_filename = 'test7.bdf'
bdf_filename2 = 'test7_bad.bdf'
with codec_open(bdf_filename, 'w', encoding='ascii') as f:
for line in lines_expected:
f.write(line)
bdf = BDF()
bdf.read_bdf(bdf_filename)
bdf.write_bdf(bdf_filename2)
with codec_open(bdf_filename, 'r', encoding='ascii') as f:
lines = f.readlines()
compare_lines(self, lines, lines_expected, has_endline=True)
def MakeCSV(transcriptions_list):
with codec_open(OUTFILE, 'w', 'utf-8-sig') as outfile:
outfile.write(','.join(LABELS.split()) + os.linesep)
while len(transcriptions_list) > 0:
HIT = random.sample(transcriptions_list, min(5, len(transcriptions_list)) )
hit = [x.comma_delimited for x in HIT]
outfile.write(",".join(hit) + os.linesep)
transcriptions_list = set(transcriptions_list).difference(set(HIT))
def UpdateMturkCSV(self, name):
csv_original = list( csv.reader(codec_open(os.path.join(MTURK_DIR,name + "_results.csv"), 'rb', 'utf-8')) )
filtered_dir = os.getcwd() + '/filtered'
with codec_open(os.path.join(filtered_dir, name + "_results_filtered.csv"), 'w', 'utf-8') as csv_filtered:
csv_writer = csv.writer(csv_filtered)
for i in range( len(csv_original) ):
if i == 0:
# AssignmentStatus = csv_original[0].index('AssignmentStatus')
# RequesterFeedback = csv_original[0].index('RequesterFeedback')
# Reject = csv_original[0].index('Reject')
pass
else:
hit = self.HIT_list[i-1]
if hit.reject_flag:
#csv_original[i][AssignmentStatus] = 'Rejected'
#csv_original[i][RequesterFeedback] = hit.reject_reason
csv_original[i].append('')
csv_original[i].append( hit.reject_reason )
csv_writer.writerow(csv_original[i])
def test_case_control_08(self):
lines_expected = [
'$pyNastran: version=msc\n',
'$pyNastran: punch=True\n',
'$pyNastran: encoding=ascii\n' if PY2 else '$pyNastran: encoding=utf-8\n',
'$NODES\n',
'GRID,100000,,43.91715,-29.,.8712984\n',
]
bdf_filename = 'test7.bdf'
bdf_filename2 = 'test7_bad.bdf'
with codec_open(bdf_filename, 'w', encoding='ascii') as f:
for line in lines_expected:
f.write(line)
bdf = BDF(debug=False)
bdf.read_bdf(bdf_filename)
bdf.write_bdf(bdf_filename2)
with codec_open(bdf_filename, 'r', encoding='ascii') as f:
lines = f.readlines()
compare_lines(self, lines, lines_expected, has_endline=True)
os.remove(bdf_filename)
os.remove(bdf_filename2)
def test_include_03(self):
"""tests executive/case control includes"""
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write("INCLUDE 'executive_control.inc'\n\n")
bdf_file.write('CEND\n')
bdf_file.write("INCLUDE 'case_control.inc'\n\n")
bdf_file.write('BEGIN BULK\n')
bdf_file.write('GRID,1,,1.0\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
bdf_file.write('GRID,4,,4.0\n')
with codec_open('executive_control.inc', 'w') as bdf_file:
bdf_file.write('SOL = 103\n')
with codec_open('case_control.inc', 'w') as bdf_file:
bdf_file.write('DISP = ALL\n')
with codec_open('b.bdf', 'w') as bdf_file:
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write("INCLUDE 'c.bdf'\n\n")
bdf_file.write('GRID,5,,5.0\n')
with codec_open('c.bdf', 'w') as bdf_file:
bdf_file.write('GRID,3,,3.0\n\n')
model = BDF(log=log, debug=False)
model.read_bdf('a.bdf')
model.write_bdf('a.out.bdf')
os.remove('a.bdf')
os.remove('b.bdf')
os.remove('c.bdf')
os.remove('executive_control.inc')
os.remove('case_control.inc')
os.remove('a.out.bdf')
self.assertEqual(len(model.nodes), 5)
self.assertEqual(model.nnodes, 5, 'nnodes=%s' % model.nnodes)
def TextFragment(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.chunk_1_id
#[32] = Input.chunk_2_id
#[37] = Input.chunk_3_id
#[42] = Input.chunk_4_id
#[47] = Input.chunk_5_id
#[60] = Answer.“chunk_1_polarityâ€
#[61] = Answer.“chunk_2_polarityâ€
#[62] = Answer.“chunk_3_polarityâ€
#[63] = Answer.“chunk_4_polarityâ€
#[64] = Answer.“chunk_5_polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as text_fragment_csv:
f = list(csv.reader(text_fragment_csv))
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
chunk_ids = row[27:52:5]
answer_polarities = row[54:59]
#this checks for the two cases where a text transcription
#fragments 5.1 and 14.1
#was mistakenly omitted from the experiment. This ensures that
#HITs with these fragments are not rejected for being incomplete
if chunk_ids[0] == ('5.1'):
chunk_ids = chunk_ids[1:]
answer_polarities = answer_polarities[1:]
elif chunk_ids[2] == ('14.1'):
chunk_ids.pop(2)
answer_polarities.pop(2)
age, location = row[52].split('|')
gender = row[53]
temp = HIT(hit_id, worker_id, work_time, chunk_ids,
answer_polarities, age, location, gender)
for field in [age, location, gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append(temp)
return HIT_list
def load_deflection_csv(out_filename, encoding='latin1'):
"""
The GUI deflection CSV loading function.
Considers:
- extension in determining how to load a file (e.g. commas or not)
- header line of file for information regarding data types
"""
ext = os.path.splitext(out_filename)[1].lower()
if ext not in ['.csv', '.dat', '.txt']:
raise NotImplementedError('extension=%r is not supported (use .dat, .txt, or .csv)' % ext)
with codec_open(_filename(out_filename), 'r', encoding=encoding) as file_obj:
names, fmt_dict, dtype, delimiter = _load_format_header(file_obj, ext, force_float=False)
try:
#A = np.loadtxt(file_obj, dtype=dtype, delimiter=delimiter)
A = loadtxt_nice(file_obj, delimiter=delimiter)
except:
traceback.print_exc(file=sys.stdout)
msg = 'extension=%r nheaders=%s delimiter=%r dtype=%s' % (
ext, len(names), delimiter, dtype)
raise RuntimeError(msg)
names_without_index = names[1:]
fmt_dict_without_index = {key:fmt_dict[key] for key in names_without_index}
nnames_without_index = len(names_without_index)
nexpected_results = 1 + 3 * nnames_without_index
try:
_nrows, ncols = A.shape
except ValueError:
msg = ('A should be (nnodes, 1+ndeflection_results); '
'A.shape=%s nexpected_results=%s names=%s' % (
str(A.shape), nexpected_results, names))
raise ValueError(msg)
if ncols != nexpected_results:
msg = 'A.shape=%s ncols=%s nexpected_results=%s names=%s nnames_without_index=%s' % (
str(A.shape), ncols, nexpected_results, names, nnames_without_index)
raise ValueError(msg)
B = {}
for i, name in enumerate(names_without_index):
B[name] = A[:, 3*i:3*i+3]
assert len(B) == len(fmt_dict_without_index), 'B.keys()=%s fmt_dict.keys()=%s' % (list(B.keys()), list(fmt_dict_without_index.keys()))
assert len(B) == len(names_without_index), 'B.keys()=%s names.keys()=%s' % (list(B.keys()), names_without_index)
return B, fmt_dict_without_index, names_without_index
def test_include_05(self):
with codec_open('include5.bdf', 'w') as bdf_file:
bdf_file.write('$ pyNastran: punch=True\n')
bdf_file.write('$ pyNastran: dumplines=True\n')
bdf_file.write("INCLUDE 'include5b.inc'\n\n")
with codec_open('include5b.inc', 'w') as bdf_file:
bdf_file.write('ECHOON\n')
bdf_file.write('$ GRID comment\n')
bdf_file.write('GRID,2,,2.0\n')
bdf_file.write('ECHOOFF\n')
bdf_file.write('GRID,3,,3.0\n')
bdf_file.write('grid,4,,4.0\n')
bdf_file.write('grid ,5,,5.0\n')
model = BDF(log=log, debug=False)
model.read_bdf('include5.bdf')
assert model.echo is False, model.echo
#model.write_bdf('include5.out.bdf')
# os.remove('c.bdf')
# os.remove('executive_control.inc')
# os.remove('case_control.inc')
self.assertEqual(len(model.nodes), 4)
self.assertEqual(model.nnodes, 4, 'nnodes=%s' % model.nnodes)
model2 = read_bdf(bdf_filename='include5.bdf',
xref=True,
punch=False,
log=log,
encoding=None)
self.assertEqual(len(model2.nodes), 4)
self.assertEqual(model2.nnodes, 4, 'nnodes=%s' % model.nnodes)
os.remove('include5.bdf')
#os.remove('include5.out.bdf')
os.remove('include5b.inc')
def TextFragment(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.chunk_1_id
#[32] = Input.chunk_2_id
#[37] = Input.chunk_3_id
#[42] = Input.chunk_4_id
#[47] = Input.chunk_5_id
#[60] = Answer.“chunk_1_polarityâ€
#[61] = Answer.“chunk_2_polarityâ€
#[62] = Answer.“chunk_3_polarityâ€
#[63] = Answer.“chunk_4_polarityâ€
#[64] = Answer.“chunk_5_polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as text_fragment_csv:
f = list( csv.reader(text_fragment_csv) )
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
chunk_ids = row[27:52:5]
answer_polarities = row[54:59]
#this checks for the two cases where a text transcription
#fragments 5.1 and 14.1
#was mistakenly omitted from the experiment. This ensures that
#HITs with these fragments are not rejected for being incomplete
if chunk_ids[0] == ('5.1'):
chunk_ids = chunk_ids[1:]
answer_polarities = answer_polarities[1:]
elif chunk_ids[2] == ('14.1'):
chunk_ids.pop(2)
answer_polarities.pop(2)
age,location = row[52].split('|')
gender = row[53]
temp = HIT(hit_id, worker_id, work_time, chunk_ids, answer_polarities, age, location, gender)
for field in [age,location,gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append( temp )
return HIT_list
def test_encoding_write(self):
mesh = BDF(log=log, debug=False)
mesh.add_card(['GRID', 100000, 0, 43.91715, -29., .8712984], 'GRID')
mesh.write_bdf('out.bdf')
lines_expected = [
'$pyNastran: version=msc',
'$pyNastran: punch=True',
'$pyNastran: encoding=ascii' if PY2 else '$pyNastran: encoding=utf-8\n',
'$pyNastran: nnodes=1',
'$pyNastran: nelements=0',
'$NODES',
'GRID 100000 43.91715 -29..8712984',
]
bdf_filename = 'out.bdf'
with codec_open(bdf_filename, 'r', encoding='ascii') as bdf_file:
lines = bdf_file.readlines()
compare_lines(self, lines, lines_expected, has_endline=False)
def AVFragment(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.chunk_1_id
#[32] = Input.chunk_2_id
#[37] = Input.chunk_3_id
#[42] = Input.chunk_4_id
#[47] = Input.chunk_5_id
#[55] = Answer.chunk_1_transcription
#[56] = Answer.chunk_2_transcription
#[57] = Answer.chunk_3_transcription
#[58] = Answer.chunk_4_transcription
#[59] = Answer.chunk_5_transcription
#[60] = Answer.“chunk_1_polarityâ€
#[61] = Answer.“chunk_2_polarityâ€
#[62] = Answer.“chunk_3_polarityâ€
#[63] = Answer.“chunk_4_polarityâ€
#[64] = Answer.“chunk_5_polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as audio_fragment_csv:
f = list(csv.reader(audio_fragment_csv))
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
chunk_ids = row[27:52:5]
chunk_transcriptions = row[55:60]
answer_polarities = row[60:65]
age = row[52]
location = row[53]
gender = row[54]
temp = HIT(hit_id, worker_id, work_time, chunk_ids,
answer_polarities, age, location, gender)
temp.transcriptions = set(chunk_transcriptions)
for field in [age, location, gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append(temp)
return HIT_list
def AVFragment(mturk_csv, experiment):
#[0] = HITId
#[15] = WorkerId
#[23] = WorkTimeInSeconds
#[27] = Input.chunk_1_id
#[32] = Input.chunk_2_id
#[37] = Input.chunk_3_id
#[42] = Input.chunk_4_id
#[47] = Input.chunk_5_id
#[55] = Answer.chunk_1_transcription
#[56] = Answer.chunk_2_transcription
#[57] = Answer.chunk_3_transcription
#[58] = Answer.chunk_4_transcription
#[59] = Answer.chunk_5_transcription
#[60] = Answer.“chunk_1_polarityâ€
#[61] = Answer.“chunk_2_polarityâ€
#[62] = Answer.“chunk_3_polarityâ€
#[63] = Answer.“chunk_4_polarityâ€
#[64] = Answer.“chunk_5_polarityâ€
HIT_list = []
with codec_open(mturk_csv, 'rb', 'utf-8') as audio_fragment_csv:
f = list( csv.reader(audio_fragment_csv) )
for row in f[1:]:
hit_id = row[0]
worker_id = row[15]
work_time = row[23]
chunk_ids = row[27:52:5]
chunk_transcriptions = row[55:60]
answer_polarities = row[60:65]
age = row[52]
location = row[53]
gender = row[54]
temp = HIT(hit_id, worker_id, work_time, chunk_ids, answer_polarities, age, location, gender)
temp.transcriptions = set(chunk_transcriptions)
for field in [age,location,gender]:
if 'select one' in field:
temp.reject_flag = True
temp.reject_reason = 'Pre-survey was left incomplete'
HIT_list.append( temp )
return HIT_list
def test_quad_180_01(self):
r"""
Identify a 180+ degree quad
y
^ 4
| / |
| / |
| / |
| / |
/ |
1------2 |----> x
\ |
\|
3
"""
msg = ('CEND\n'
'BEGIN BULK\n'
'GRID,1,,0.,0.,0.\n'
'GRID,2,,1.,0.,0.\n'
'GRID,3,,2.,-1.,0.\n'
'GRID,4,,2., 1.,0.\n'
'CQUAD4,100,1, 1,2,3,4\n'
'PSHELL,1,1,0.1\n'
'MAT1,1,3.0,, 0.3\n'
'ENDDATA')
bdf_filename = 'cquad4.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.write(msg)
model = read_bdf(bdf_filename, log=log, xref=True)
xyz_cid0 = model.get_xyz_in_coord(cid=0, fdtype='float32')
nid_map = {}
for i, (nid, node) in enumerate(sorted(iteritems(model.nodes))):
#xyz = node.get_position()
#xyz_cid0[i, :] = xyz
nid_map[nid] = i
eids_to_delete = get_bad_shells(model,
xyz_cid0,
nid_map,
max_theta=180.,
max_skew=1000.,
max_aspect_ratio=1000.)
assert eids_to_delete == [100], eids_to_delete
os.remove(bdf_filename)
def test_encoding_write(self):
mesh = BDF(log=log, debug=False)
mesh.add_card(['GRID', 100000, 0, 43.91715, -29., .8712984], 'GRID')
mesh.write_bdf('out.bdf')
lines_expected = [
'$pyNastran: version=msc',
'$pyNastran: punch=True',
'$pyNastran: encoding=ascii'
if PY2 else '$pyNastran: encoding=utf-8\n',
'$pyNastran: nnodes=1',
'$pyNastran: nelements=0',
'$NODES',
'GRID 100000 43.91715 -29..8712984',
]
bdf_filename = 'out.bdf'
with codec_open(bdf_filename, 'r', encoding='ascii') as bdf_file:
lines = bdf_file.readlines()
compare_lines(self, lines, lines_expected, has_endline=False)
def test_include_stop(self):
with codec_open('a.bdf', 'w') as bdf_file:
bdf_file.write('CEND\n')
bdf_file.write('BEGIN BULK\n')
bdf_file.write("INCLUDE 'b.bdf'\n\n")
bdf_file.write('GRID,1,,1.0\n')
model = BDF(log=log, debug=False)
with self.assertRaises(IOError):
model.read_bdf(bdf_filename='a.bdf', xref=True, punch=False,
read_includes=True, encoding=None)
with self.assertRaises(IOError):
read_bdf(bdf_filename='a.bdf', xref=True, punch=False,
encoding=None, log=log)
model.read_bdf(bdf_filename='a.bdf', xref=True, punch=False,
read_includes=False, encoding=None)
model.write_bdf('out.bdf')
os.remove('a.bdf')
os.remove('out.bdf')
def test_read_bad_02(self):
"""tests when users don't add punch=True to read_bdf(...)"""
lines = [
'GRID 1000177 0 1. 0. 0. 0\n',
'GRID 1000178 0 0. 1. 0. 0\n',
'GRID 1000186 0 0. 0. 1. 0\n',
'GRID 1000187 0 1. 1. 1. 0\n',
'GRID 15000014 0 2. 1. 1. 0\n',
'RBE2 1500002215000014 123456 1000177 1000178 1000186 1000187\n',
]
bdf_filename = 'xref_test.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.writelines(lines)
with self.assertRaises(RuntimeError):
read_bdf(bdf_filename, validate=False, xref=False,
punch=False, encoding=None,
log=log, debug=True, mode='msc')
os.remove(bdf_filename)
def test_quad_180_01(self):
r"""
Identify a 180+ degree quad
y
^ 4
| / |
| / |
| / |
| / |
/ |
1------2 |----> x
\ |
\|
3
"""
msg = (
'CEND\n'
'BEGIN BULK\n'
'GRID,1,,0.,0.,0.\n'
'GRID,2,,1.,0.,0.\n'
'GRID,3,,2.,-1.,0.\n'
'GRID,4,,2., 1.,0.\n'
'CQUAD4,100,1, 1,2,3,4\n'
'PSHELL,1,1,0.1\n'
'MAT1,1,3.0,, 0.3\n'
'ENDDATA'
)
bdf_filename = 'cquad4.bdf'
with codec_open(bdf_filename, 'w') as bdf_file:
bdf_file.write(msg)
model = read_bdf(bdf_filename, xref=True)
xyz_cid0 = model.get_xyz_in_coord(cid=0, dtype='float32')
nid_map = {}
for i, (nid, node) in enumerate(sorted(iteritems(model.nodes))):
#xyz = node.get_position()
#xyz_cid0[i, :] = xyz
nid_map[nid] = i
eids_to_delete = get_bad_shells(model, xyz_cid0, nid_map, max_theta=180.,
max_skew=1000., max_aspect_ratio=1000.)
assert eids_to_delete == [100], eids_to_delete
os.remove(bdf_filename)
def _dump_file(self, bdf_dump_filename, lines, i):
# type: (str, List[str], int) -> None
"""
Writes a BDF up to some failed line index
Parameters
----------
bdf_dump_filename : str
the bdf filename to dump
lines : List[str]
the entire list of lines
i : int
the last index to write
"""
with codec_open(_filename(bdf_dump_filename),
'w',
encoding=self.encoding) as crash_file:
for line in lines[:i]:
crash_file.write(line)
def load_deflection_csv(out_filename, encoding='latin1'):
"""
The GUI deflection CSV loading function.
Considers:
- extension in determining how to load a file (e.g. commas or not)
- header line of file for information regarding data types
"""
ext = os.path.splitext(out_filename)[1].lower()
if ext not in ['.csv', '.dat', '.txt']:
raise NotImplementedError('extension=%r is not supported (use .dat, .txt, or .csv)' % ext)
with codec_open(_filename(out_filename), 'r', encoding=encoding) as file_obj:
names, fmt_dict, dtype, delimiter = _load_format_header(file_obj, ext, force_float=False)
nnames = len(names)
try:
#A = np.loadtxt(file_obj, dtype=dtype, delimiter=delimiter)
A = loadtxt_nice(file_obj, delimiter=delimiter)
except:
traceback.print_exc(file=sys.stdout)
msg = 'extension=%r nheaders=%s delimiter=%r dtype=%s' % (
ext, len(names), delimiter, dtype)
raise RuntimeError(msg)
try:
nrows, ncols = A.shape
except ValueError:
msg = 'A should be (nnodes, 3); A.shape=%s nnames*3=%s names=%s' % (
str(A.shape), nnames*3, names)
raise ValueError(msg)
if ncols != (nnames * 3):
msg = 'A.shape=%s ncols=%s nnames*3=%s names=%s' % (
str(A.shape), ncols, nnames*3, names)
raise RuntimeError(msg)
B = {}
for i, name in enumerate(names):
B[name] = A[:, 3*i:3*i+3]
return B, fmt_dict, names
