def _mixedtypes_datastring2rawniml(s, niml):
tps = niml['vec_typ']
ncols = len(tps)
nrows = niml['vec_len']
lines = s.strip().split(_TEXT_ROWSEP)
if len(lines) != nrows:
raise ValueError("Expected %d rows, but found %d" %
(nrows, len(lines)))
elems = map(lambda x: x.strip().split(_TEXT_COLSEP), lines)
fs = map(types.code2python_convertor, tps)
data = []
for col in xrange(ncols):
f = fs[col]
if types.sametype(tps[col], 'String'):
d = map(f, [elems[r][col] for r in xrange(nrows)])
else:
tp = types.code2numpy_type(tps[col])
niform = niml.get('ni_form', None)
if not niform is None:
raise ValueError(
'Not supported: have ni_form with mixed types')
d = np.zeros((nrows, ), dtype=tp) # allocate one-dimensional array
for r in xrange(nrows):
d[r] = f(elems[r][col])
data.append(d)
return data
def _binary_data_bytecount(niml):
'''helper function that returns how many bytes a NIML binary data
element should have'''
niform = niml['ni_form']
if not 'binary' in niform:
raise ValueError('Illegal niform %s' % niform)
tps = niml['vec_typ']
onetype = types.findonetype(tps)
if onetype is None:
debug('NIML', 'Not unique type: %r', tps)
return None
# numeric, either int or float
ncols = niml['vec_num']
nrows = niml['vec_len']
tp = types.code2numpy_type(onetype)
bytes_per_elem = types.numpy_type2bytecount(tp)
if bytes_per_elem is None:
raise ValueError("Type not supported: %r" % onetype)
nb = ncols * nrows * bytes_per_elem
debug('NIML', 'Number of bytes for %s: %d x %d with %d bytes / element',
(niform, ncols, nrows, bytes_per_elem))
return nb
def _mixedtypes_datastring2rawniml(s, niml):
tps = niml['vec_typ']
ncols = len(tps)
nrows = niml['vec_len']
lines = s.strip().split(_TEXT_ROWSEP)
if len(lines) != nrows:
raise ValueError("Expected %d rows, but found %d" % (nrows, len(lines)))
elems = map(lambda x : x.strip().split(_TEXT_COLSEP), lines)
fs = map(types.code2python_convertor, tps)
data = []
for col in xrange(ncols):
f = fs[col]
if types.sametype(tps[col], 'String'):
d = map(f, [elems[r][col] for r in xrange(nrows)])
else:
tp = types.code2numpy_type(tps[col])
niform = niml.get('ni_form', None)
if not niform is None:
raise ValueError('Not supported: have ni_form with mixed types')
d = np.zeros((nrows,), dtype=tp) # allocate one-dimensional array
for r in xrange(nrows):
d[r] = f(elems[r][col])
data.append(d)
return data
def _binary_data_bytecount(niml):
'''helper function that returns how many bytes a NIML binary data
element should have'''
niform = niml['ni_form']
if not 'binary' in niform:
raise ValueError('Illegal niform %s' % niform)
tps = niml['vec_typ']
onetype = types.findonetype(tps)
if onetype is None:
debug('NIML', 'Not unique type: %r', tps)
return None
# numeric, either int or float
ncols = niml['vec_num']
nrows = niml['vec_len']
tp = types.code2numpy_type(onetype)
bytes_per_elem = types.numpy_type2bytecount(tp)
if bytes_per_elem is None:
raise ValueError("Type not supported: %r" % onetype)
nb = ncols * nrows * bytes_per_elem
debug('NIML', 'Number of bytes for %s: %d x %d with %d bytes / element',
(niform, ncols, nrows, bytes_per_elem))
return nb
def _datastring2rawniml(s, niml):
'''Converts data with uniform type to raw NIML'''
debug('NIML', 'Raw string to NIML: %d characters', len(s))
tps = niml['vec_typ']
onetype = types.findonetype(tps)
if onetype is None or ([onetype] == types.str2codes('string')
and len(tps) > 1):
return _mixedtypes_datastring2rawniml(s, niml)
if [onetype] == types.str2codes('string'):
# single string
return decode_escape(s.decode()) # do not string2rawniml
# numeric, either int or float
ncols = niml['vec_num']
nrows = niml['vec_len']
tp = types.code2numpy_type(onetype)
niform = niml.get('ni_form', None)
if not niform or niform == 'text':
data = np.zeros((nrows, ncols), dtype=tp) # allocate space for data
convertor = types.code2python_convertor(
onetype) # string to type convertor
vals = s.split(None) # split by whitespace seperator
if len(vals) != ncols * nrows:
raise ValueError("unexpected number of elements")
for i, val in enumerate(vals):
data[i // ncols, i % ncols] = convertor(val)
else:
dtype = np.dtype(tp)
dtype = types.byteorder_from_niform(niform, dtype)
if 'base64' in niform:
debug('NIML', 'base64, %d chars: %s',
(len(s), _partial_string(s, 0)))
s = base64.b64decode(s)
elif not 'binary' in niform:
raise ValueError('Illegal niform %s' % niform)
data_1d = np.fromstring(s, dtype=tp)
debug('NIML', 'data vector has %d elements, reshape to %d x %d = %d',
(np.size(data_1d), nrows, ncols, nrows * ncols))
data = np.reshape(data_1d, (nrows, ncols))
return data
def _datastring2rawniml(s, niml):
'''Converts data with uniform type to raw NIML'''
debug('NIML', 'Raw string to NIML: %d characters', len(s))
tps = niml['vec_typ']
onetype = types.findonetype(tps)
if onetype is None or ([onetype] == types.str2codes('string') and
len(tps) > 1):
return _mixedtypes_datastring2rawniml(s, niml)
if [onetype] == types.str2codes('string'):
# single string
return decode_escape(s.decode()) # do not string2rawniml
# numeric, either int or float
ncols = niml['vec_num']
nrows = niml['vec_len']
tp = types.code2numpy_type(onetype)
niform = niml.get('ni_form', None)
if not niform or niform == 'text':
data = np.zeros((nrows, ncols), dtype=tp) # allocate space for data
convertor = types.code2python_convertor(onetype) # string to type convertor
vals = s.split(None) # split by whitespace seperator
if len(vals) != ncols * nrows:
raise ValueError("unexpected number of elements")
for i, val in enumerate(vals):
data[i // ncols, i % ncols] = convertor(val)
else:
dtype = np.dtype(tp)
dtype = types.byteorder_from_niform(niform, dtype)
if 'base64' in niform:
debug('NIML', 'base64, %d chars: %s',
(len(s), _partial_string(s, 0)))
s = base64.b64decode(s)
elif not 'binary' in niform:
raise ValueError('Illegal niform %s' % niform)
data_1d = np.fromstring(s, dtype=tp)
debug('NIML', 'data vector has %d elements, reshape to %d x %d = %d',
(np.size(data_1d), nrows, ncols, nrows * ncols))
data = np.reshape(data_1d, (nrows, ncols))
return data
