def readarray(self, size=None, offset=0, dtype=np.uint8, shape=None):
"""
Similar to file.read(), but returns the contents of the underlying
file as a numpy array (or mmap'd array if memmap=True) rather than a
string.
Usually it's best not to use the `size` argument with this method, but
it's provided for compatibility.
"""
if not hasattr(self.__file, 'read'):
raise EOFError
if not isinstance(dtype, np.dtype):
dtype = np.dtype(dtype)
if size and size % dtype.itemsize != 0:
raise ValueError('size %d not a multiple of %s' % (size, dtype))
if isinstance(shape, int):
shape = (shape,)
if size and shape:
actualsize = sum(dim * dtype.itemsize for dim in shape)
if actualsize < size:
raise ValueError('size %d is too few bytes for a %s array of '
'%s' % (size, shape, dtype))
if actualsize < size:
raise ValueError('size %d is too many bytes for a %s array of '
'%s' % (size, shape, dtype))
if size and not shape:
shape = (size // dtype.itemsize,)
if not (size or shape):
warnings.warn('No size or shape given to readarray(); assuming a '
'shape of (1,)')
shape = (1,)
if self.memmap:
return Memmap(self.__file, offset=offset,
mode=MEMMAP_MODES[self.mode], dtype=dtype,
shape=shape).view(np.ndarray)
else:
count = reduce(lambda x, y: x * y, shape)
pos = self.__file.tell()
self.__file.seek(offset)
data = _array_from_file(self.__file, dtype, count, '')
data.shape = shape
self.__file.seek(pos)
return data
def get_pdata(dtype, count):
return _array_from_file(self._file, dtype=dtype,
count=count, sep='')
