def _slistShape(slist, itemsize=None, shape=None):
"""_slistShape(slist, itemsize=None, shape=None) computes the "natural"
shape and itemsize of slist, and combines this with the specified
itemsize and shape, checking for consistency.
Specifying an itemsize overrides the slist's natural itemsize.
>>> _slistShape(["this","that"], itemsize=10)
((2,), 10)
>>> _slistShape(["this","that"], itemsize=3)
((2,), 3)
Specifying a shape checks for consistency against the slist's shape.
>>> _slistShape(["this","that"], shape=(2,1,1))
((2, 1, 1), 4)
>>> _slistShape(["this","that"], shape=(3,2))
Traceback (most recent call last):
...
ValueError: Inconsistent list and shape
"""
shape_items = _slistShape0(slist)
if shape is None:
shape = shape_items[0]
else:
if _gen.product(shape) != _gen.product(shape_items[0]):
raise ValueError("Inconsistent list and shape")
if itemsize is None:
itemsize = shape_items[-1]
else:
pass # specified itemsize => padded extension or silent truncation.
return (shape, itemsize)
def __init__(self, objects=None, shape=None, rank=None):
"""
>>> ObjectArray(shape=(1,))
ObjectArray([None])
>>> ObjectArray(objects=['t','u'])
ObjectArray(['t', 'u'])
>>> ObjectArray(objects=['t','u'], shape=(3,))
Traceback (most recent call last):
...
ValueError: object list is not compatible with shape
"""
if rank is None:
rank = _getRank(objects)
if objects is not None:
oshape = _shapeFromNestedSequence(objects, rank)
if shape is None:
shape = oshape
else:
if _gen.product(shape) != _gen.product(oshape):
raise ValueError("object list is not compatible with shape")
objects = _flatten(objects, rank)
else:
if shape is None:
shape = (1,)
if isinstance(objects, _gen.NDArray) and shape == ():
objects = [objects[()]]
if not isinstance(shape, (list, tuple)):
shape = (shape,)
_objarr.__init__(self, shape, objects)
def __init__(self, objects=None, shape=None, rank=None):
"""
>>> ObjectArray(shape=(1,))
ObjectArray([None])
>>> ObjectArray(objects=['t','u'])
ObjectArray(['t', 'u'])
>>> ObjectArray(objects=['t','u'], shape=(3,))
Traceback (most recent call last):
...
ValueError: object list is not compatible with shape
"""
if rank is None:
rank = _getRank(objects)
if objects is not None:
oshape = _shapeFromNestedSequence(objects, rank)
if shape is None:
shape = oshape
else:
if _gen.product(shape) != _gen.product(oshape):
raise ValueError(
"object list is not compatible with shape")
objects = _flatten(objects, rank)
else:
if shape is None:
shape = (1, )
if isinstance(objects, _gen.NDArray) and shape == ():
objects = [objects[()]]
if not isinstance(shape, (list, tuple)):
shape = (shape, )
_objarr.__init__(self, shape, objects)
def _slistShape(slist, itemsize=None, shape=None):
"""_slistShape(slist, itemsize=None, shape=None) computes the "natural"
shape and itemsize of slist, and combines this with the specified
itemsize and shape, checking for consistency.
Specifying an itemsize overrides the slist's natural itemsize.
>>> _slistShape(["this","that"], itemsize=10)
((2,), 10)
>>> _slistShape(["this","that"], itemsize=3)
((2,), 3)
Specifying a shape checks for consistency against the slist's shape.
>>> _slistShape(["this","that"], shape=(2,1,1))
((2, 1, 1), 4)
>>> _slistShape(["this","that"], shape=(3,2))
Traceback (most recent call last):
...
ValueError: Inconsistent list and shape
"""
shape_items = _slistShape0(slist)
if shape is None:
shape = shape_items[0]
else:
if _gen.product(shape) != _gen.product(shape_items[0]):
raise ValueError("Inconsistent list and shape")
if itemsize is None:
itemsize = shape_items[-1]
else:
pass # specified itemsize => padded extension or silent truncation.
return (shape, itemsize)
def fromfile(file, formats, shape=-1, names=None, byteorder=sys.byteorder, aligned=0):
"""Create an array from binary file data
If file is a string then that file is opened, else it is assumed
to be a file object. No options at the moment, all file positioning
must be done prior to this function call with a file object
>>> import testdata, sys
>>> fd=open(testdata.filename)
>>> fd.seek(2880*2)
>>> r=fromfile(fd, formats='f8,i4,a5', shape=3, byteorder='big')
>>> print r[0]
(5.1000000000000005, 61, 'abcde')
>>> r._shape
(3,)
"""
if isinstance(shape, types.IntType) or isinstance(shape, types.LongType):
shape = (shape,)
name = 0
if isinstance(file, types.StringType):
name = 1
file = open(file, 'rb')
try:
size = os.fstat(file.fileno())[stat.ST_SIZE] - file.tell()
except:
size = os.path.getsize(file.name) - file.tell()
dummy = array(None, formats=formats, shape=0, aligned=aligned)
itemsize = dummy._itemsize
if shape and itemsize:
shapesize = _gen.product(shape)*itemsize
if shapesize < 0:
shape = list(shape)
shape[ shape.index(-1) ] = size / -shapesize
shape = tuple(shape)
nbytes = _gen.product(shape)*itemsize
if nbytes > size:
raise ValueError(
"Not enough bytes left in file for specified shape and type")
# create the array
_array = RecArray(None, formats=formats, shape=shape, names=names,
byteorder=byteorder, aligned=aligned)
nbytesread = file.readinto(_array._data)
if nbytesread != nbytes:
raise IOError("Didn't read as many bytes as expected")
if name:
file.close()
return _array
def fromstring(datastring, formats, shape=0, names=None, byteorder=sys.byteorder, aligned=0):
""" create a Record Array from binary data contained in a string"""
_array = RecArray(chararray._stringToBuffer(datastring), formats, shape, names,
byteorder=byteorder, aligned=aligned)
if _gen.product(_array._shape)*_array._itemsize > len(datastring):
raise ValueError("Insufficient input data.")
else:
return _array
def __init__(self, shape, objects=None):
if objects is None:
objects = [None] * _gen.product(shape)
_gen.NDArray.__init__(self,
shape=shape,
buffer=_dummyBuffer,
itemsize=1)
self._objects = objects[:]
def _clone(self, shape):
"""returns an empty array identical to 'self' but with 'shape'
"""
c = self.view()
c._shape = shape
c._strides = _stridesFromShape(shape)
c._byteoffset = 0
c._objects = [None] * _gen.product(shape)
return c
def _clone(self, shape):
"""returns an empty array identical to 'self' but with 'shape'
"""
c = self.view()
c._shape = shape
c._strides = _stridesFromShape(shape)
c._byteoffset = 0
c._objects = [None] * _gen.product(shape)
return c
def _stridesFromShape(shape):
"""_stridesFromShape() computes the strides which correspond to
the specified shape."""
if len(shape) > 1:
head = [_gen.product(shape[1:])]
tail = _stridesFromShape(shape[1:])
head.extend(tail)
return head
else:
return [1]
def _stridesFromShape(shape):
"""_stridesFromShape() computes the strides which correspond to
the specified shape."""
if len(shape) > 1:
head = [_gen.product(shape[1:])]
tail = _stridesFromShape(shape[1:])
head.extend(tail)
return head
else:
return [1]
def fromstring(datastring,
formats,
shape=0,
names=None,
byteorder=sys.byteorder,
aligned=0):
""" create a Record Array from binary data contained in a string"""
_array = RecArray(chararray._stringToBuffer(datastring),
formats,
shape,
names,
byteorder=byteorder,
aligned=aligned)
if _gen.product(_array._shape) * _array._itemsize > len(datastring):
raise ValueError("Insufficient input data.")
else:
return _array
def __init__(self, shape, objects=None):
if objects is None:
objects = [None] * _gen.product(shape)
_gen.NDArray.__init__(self, shape=shape, buffer=_dummyBuffer, itemsize=1)
self._objects = objects[:]
def fromfile(file,
formats,
shape=-1,
names=None,
byteorder=sys.byteorder,
aligned=0):
"""Create an array from binary file data
If file is a string then that file is opened, else it is assumed
to be a file object. No options at the moment, all file positioning
must be done prior to this function call with a file object
>>> import testdata, sys
>>> fd=open(testdata.filename)
>>> fd.seek(2880*2)
>>> r=fromfile(fd, formats='f8,i4,a5', shape=3, byteorder='big')
>>> print r[0]
(5.1000000000000005, 61, 'abcde')
>>> r._shape
(3,)
"""
if isinstance(shape, types.IntType) or isinstance(shape, types.LongType):
shape = (shape, )
name = 0
if isinstance(file, types.StringType):
name = 1
file = open(file, 'rb')
try:
size = os.fstat(file.fileno())[stat.ST_SIZE] - file.tell()
except:
size = os.path.getsize(file.name) - file.tell()
dummy = array(None, formats=formats, shape=0, aligned=aligned)
itemsize = dummy._itemsize
if shape and itemsize:
shapesize = _gen.product(shape) * itemsize
if shapesize < 0:
shape = list(shape)
shape[shape.index(-1)] = size / -shapesize
shape = tuple(shape)
nbytes = _gen.product(shape) * itemsize
if nbytes > size:
raise ValueError(
"Not enough bytes left in file for specified shape and type")
# create the array
_array = RecArray(None,
formats=formats,
shape=shape,
names=names,
byteorder=byteorder,
aligned=aligned)
nbytesread = file.readinto(_array._data)
if nbytesread != nbytes:
raise IOError("Didn't read as many bytes as expected")
if name:
file.close()
return _array
