How to use the numcodecs.compat.ensure_contiguous_ndarray function in numcodecs

def decode(self, buf, out=None):
        arr = ensure_contiguous_ndarray(buf).view('u1')
        expect = arr[:4].view('

def decode(self, buf, out=None):

        # normalise inputs
        buf = ensure_contiguous_ndarray(buf)
        if out is not None:
            out = ensure_contiguous_ndarray(out)

        # do decompression
        dec = _zlib.decompress(buf)

        # handle destination - Python standard library zlib module does not
        # support direct decompression into buffer, so we have to copy into
        # out if given
        return ndarray_copy(dec, out)

def encode(self, buf):

        # normalise input
        buf = ensure_contiguous_ndarray(buf)

        # do compression
        return _bz2.compress(buf, self.level)

def decode(self, buf, out=None):

        # normalise inputs
        # BytesIO only copies if the data is not of `bytes` type.
        # This allows `bytes` objects to pass through without copying.
        buf = io.BytesIO(ensure_bytes(buf))

        # do decompression
        with _gzip.GzipFile(fileobj=buf, mode='rb') as decompressor:
            if out is not None:
                out_view = ensure_contiguous_ndarray(out)
                decompressor.readinto(out_view)
                if decompressor.read(1) != b'':
                    raise ValueError("Unable to fit data into `out`")
            else:
                out = decompressor.read()

        return out

def decode(self, buf, out=None):

        # normalise inputs
        buf = ensure_contiguous_ndarray(buf)
        if out is not None:
            out = ensure_contiguous_ndarray(out)

        # do decompression
        dec = _zlib.decompress(buf)

        # handle destination - Python standard library zlib module does not
        # support direct decompression into buffer, so we have to copy into
        # out if given
        return ndarray_copy(dec, out)

def encode(self, buf):

            # normalise inputs
            buf = ensure_contiguous_ndarray(buf)

            # do compression
            return _lzma.compress(buf, format=self.format, check=self.check,
                                  preset=self.preset, filters=self.filters)

def encode(self, buf):
        arr = ensure_contiguous_ndarray(buf).view('u1')
        checksum = self.checksum(arr) & 0xffffffff
        enc = np.empty(arr.nbytes + 4, dtype='u1')
        enc[:4].view('

def decode(self, buf, out=None):

        # normalise inputs
        buf = ensure_contiguous_ndarray(buf)
        if out is not None:
            out = ensure_contiguous_ndarray(out)

        # N.B., bz2 cannot handle ndarray directly because of truth testing issues
        buf = memoryview(buf)

        # do decompression
        dec = _bz2.decompress(buf)

        # handle destination - Python standard library bz2 module does not
        # support direct decompression into buffer, so we have to copy into
        # out if given
        return ndarray_copy(dec, out)

def encode(self, buf):

        # normalise inputs
        buf = ensure_contiguous_ndarray(buf)

        # do compression
        return _zlib.compress(buf, self.level)

def decode(self, buf, out=None):
        buf = ensure_contiguous_ndarray(buf)
        items = msgpack.unpackb(buf, raw=self.raw)
        dec = np.empty(items[-1], dtype=items[-2])
        dec[:] = items[:-2]
        if out is not None:
            np.copyto(out, dec)
            return out
        else:
            return dec