f'Invalid dimensionality of input array.\n Input must have dimensionality of at least 2; got {buf.ndim}'
)
if len(self.input_shape) != len(bufa.shape):
raise ValueError(
f'Invalid input size.\n Input must have dimensionality matching the input_shape parameter of this compressor, i.e. {self.input_shape}, which has a dimensionality of {len(self.input_shape)}.\n Got input with shape {bufa.shape} instead, which has a dimensionality of {len(bufa.shape)}.'
)
if not all(chnk >= shpe
for chnk, shpe in zip(self.input_shape, bufa.shape)):
raise ValueError(
f'Invalid input size. Input must be less than or equal to the input_shape parameter of this compressor, i.e. {self.input_shape}. Got input with shape {bufa.shape} instead'
)
new_shape = [
np.prod([bufa.shape[dim] for dim in axis], dtype='int')
for axis in axis_reduction
]
tiled = bufa.reshape(new_shape)
return jpeg_encode(tiled, level=self.quality)
def decode(self, buf, out=None):
buf = ensure_contiguous_ndarray(buf)
if out is not None:
out = ensure_contiguous_ndarray(out)
tiled = jpeg_decode(buf)
return ndarray_copy(tiled, out)
register_codec(jpeg)
# broadcast to 3rd dimension having 2 elements, least significant
# bit then second least, in that order; results in nxmx2 array
# containing individual bits as bools
# see: https://stackoverflow.com/questions/22227595/convert-integer-to-binary-array-with-suitable-padding
arr = arr[:, :, None] & self.__bit_mask
bool_arr = arr > 0
# NOTE: -1 codes as [True, True] which equals to 3 in uint8 bit encoding
return super().encode(bool_arr)
def decode(self,
buf: np.ndarray,
out: Optional[np.ndarray] = None) -> np.ndarray:
dec = super().decode(buf, out=None)
# given a flattened version of what was originally an nxmx2 array,
# reshape to group adjacent bits in second dimension and
# convert back to int based on each little-endian bit pair
dec = np.packbits(dec.reshape((-1, 2)), bitorder="little", axis=1)
dec = dec.squeeze(axis=1)
# -1 which codes for missing data got encoded as 11000000 which codes for 3 in uint8,
# we revert that here
dec[dec == 3] = -1
# handle destination
return ndarray_copy(dec, out)
register_codec(PackGeneticBits)
pipelines in a variety of ways.
If you have a question, find a bug, would like to make a suggestion or
contribute code, please `raise an issue on GitHub
<https://github.com/alimanfoo/numcodecs/issues>`_.
"""
import multiprocessing
import atexit
from numcodecs.version import version as __version__
from numcodecs.registry import get_codec, register_codec
from numcodecs.zlib import Zlib
register_codec(Zlib)
from numcodecs.gzip import GZip
register_codec(GZip)
from numcodecs.bz2 import BZ2
register_codec(BZ2)
try:
from numcodecs.lzma import LZMA
register_codec(LZMA)
except ImportError: # pragma: no cover
pass
try:
from numcodecs import blosc
contribute code, please `raise an issue on GitHub
<https://github.com/alimanfoo/numcodecs/issues>`_.
"""
from __future__ import absolute_import, print_function, division
import multiprocessing
import atexit
from numcodecs.version import version as __version__
from numcodecs.registry import get_codec, register_codec
from numcodecs.compat import PY2
from numcodecs.zlib import Zlib
register_codec(Zlib)
from numcodecs.bz2 import BZ2
register_codec(BZ2)
if not PY2:
from numcodecs.lzma import LZMA
register_codec(LZMA)
try:
from numcodecs import blosc as _blosc
from numcodecs.blosc import Blosc
register_codec(Blosc)
# initialize blosc
ncores = multiprocessing.cpu_count()
_blosc.init()
def setup(self, worker):
from numcodecs.registry import register_codec
register_codec(PackGeneticBits)
If you have a question, find a bug, would like to make a suggestion or
contribute code, please `raise an issue on GitHub
<https://github.com/alimanfoo/numcodecs/issues>`_.
"""
from __future__ import absolute_import, print_function, division
import multiprocessing
import atexit
from numcodecs.version import version as __version__
from numcodecs.registry import get_codec, register_codec
from numcodecs.zlib import Zlib
register_codec(Zlib)
register_codec(Zlib, 'gzip') # alias
from numcodecs.bz2 import BZ2
register_codec(BZ2)
try:
from numcodecs.lzma import LZMA
register_codec(LZMA)
except ImportError: # pragma: no cover
pass
try:
from numcodecs import blosc
from numcodecs.blosc import Blosc
def _read_header(self, chunk):
num_dims = struct.unpack('>H', chunk[2:4])[0]
shape = tuple(
struct.unpack('>I', chunk[i:i + 4])[0]
for i in range(4, num_dims * 4 + 4, 4))[::-1]
len_header = 4 + num_dims * 4
return len_header, shape
def _to_big_endian(self, data):
# assumes data is ndarray
if self._little_endian:
return data.byteswap()
return data
def _from_big_endian(self, data):
# assumes data is byte array in big endian
if not self._little_endian:
return data
a = np.frombuffer(data, self.dtype.newbyteorder('>'))
return a.astype(self.dtype)
register_codec(N5ChunkWrapper, N5ChunkWrapper.codec_id)
def register_codec(cls=Tiff, codec_id=None):
"""Register Tiff codec with numcodecs."""
registry.register_codec(cls, codec_id=codec_id)
