Python numpy.unpackbits方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def test_unpackbits_empty_with_axis():
    # Lists of packed shapes for different axes and unpacked shapes.
    shapes = [
        ([(0,)], (0,)),
        ([(2, 24, 0), (16, 3, 0), (16, 24, 0)], (16, 24, 0)),
        ([(2, 0, 24), (16, 0, 24), (16, 0, 3)], (16, 0, 24)),
        ([(0, 16, 24), (0, 2, 24), (0, 16, 3)], (0, 16, 24)),
        ([(3, 0, 0), (24, 0, 0), (24, 0, 0)], (24, 0, 0)),
        ([(0, 24, 0), (0, 3, 0), (0, 24, 0)], (0, 24, 0)),
        ([(0, 0, 24), (0, 0, 24), (0, 0, 3)], (0, 0, 24)),
        ([(0, 0, 0), (0, 0, 0), (0, 0, 0)], (0, 0, 0)),
    ]
    for in_shapes, out_shape in shapes:
        for ax, in_shape in enumerate(in_shapes):
            a = np.empty(in_shape, dtype=np.uint8)
            b = np.unpackbits(a, axis=ax)
            assert_equal(b.dtype, np.uint8)
            assert_equal(b.shape, out_shape) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def decode(self, buf, out=None):

        # normalise input
        enc = ensure_ndarray(buf).view('u1')

        # flatten to simplify implementation
        enc = enc.reshape(-1, order='A')

        # find out how many bits were padded
        n_bits_padded = int(enc[0])

        # apply decoding
        dec = np.unpackbits(enc[1:])

        # remove padded bits
        if n_bits_padded:
            dec = dec[:-n_bits_padded]

        # view as boolean array
        dec = dec.view(bool)

        # handle destination
        return ndarray_copy(dec, out) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def lsb_deinterleave_bytes(carrier, num_bits, num_lsb, byte_depth=1):
    """
    Deinterleave num_bits bits from the num_lsb LSBs of carrier.

    :param carrier: carrier bytes
    :param num_bits: number of num_bits to retrieve
    :param num_lsb: number of least significant bits to use
    :param byte_depth: byte depth of carrier values
    :return: The deinterleaved bytes
    """

    plen = roundup(num_bits / num_lsb)
    carrier_dtype = byte_depth_to_dtype[byte_depth]
    payload_bits = np.unpackbits(
        np.frombuffer(carrier, dtype=carrier_dtype, count=plen).view(np.uint8)
    ).reshape(plen, 8 * byte_depth)[:, 8 * byte_depth - num_lsb: 8 * byte_depth]
    return np.packbits(payload_bits).tobytes()[: num_bits // 8] 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def decode_long_array(
    long_array: numpy.ndarray, size: int, dense=True
) -> numpy.ndarray:
    """
    Decode an long array (from BlockStates or Heightmaps)
    :param long_array: Encoded long array
    :param size: int: The expected size of the returned array
    :return: Decoded array as numpy array
    """
    long_array = long_array.astype(">q")
    bits_per_entry = (len(long_array) * 64) // size
    bits = numpy.unpackbits(long_array[::-1].astype(">i8").view("uint8"))
    if not dense:
        entry_per_long = 64 // bits_per_entry
        bits = bits.reshape(-1, 64)[:, -entry_per_long * bits_per_entry :]

    return numpy.packbits(
        numpy.pad(
            bits.reshape(-1, bits_per_entry)[-size:, :],
            [(0, 0), (16 - bits_per_entry, 0)],
            "constant",
        )
    ).view(dtype=">h")[::-1] 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def read(filename):
        with gzip.open(filename, "rb") as f:
            header_bytes = f.read(CHUNK_HEADER_SIZE)
            data_size, board_size, input_planes, is_test = struct.unpack(CHUNK_HEADER_FORMAT, header_bytes)

            position_dims = data_size * board_size * board_size * input_planes
            next_move_dims = data_size * board_size * board_size

            # the +7 // 8 compensates for numpy's bitpacking padding
            packed_position_bytes = f.read((position_dims + 7) // 8)
            packed_next_move_bytes = f.read((next_move_dims + 7) // 8)
            # should have cleanly finished reading all bytes from file!
            assert len(f.read()) == 0

            flat_position = np.unpackbits(np.fromstring(packed_position_bytes, dtype=np.uint8))[:position_dims]
            flat_nextmoves = np.unpackbits(np.fromstring(packed_next_move_bytes, dtype=np.uint8))[:next_move_dims]

            pos_features = flat_position.reshape(data_size, board_size, board_size, input_planes)
            next_moves = flat_nextmoves.reshape(data_size, board_size * board_size)

        return DataSet(pos_features, next_moves, [], is_test=is_test) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def decode(self, img):
        """
        Decode the image from internal image format.
        """
        assert len(img.shape) == 1
        assert img.shape[0] >= (self._h * self._w / 8)
        assert img.shape[0] % self._align == 0

        img_8b_1d = np.unpackbits(img) * 255  # to 8bit gray scale.
        img_8b_1d_trimmed = img_8b_1d[0: (self._h * self._w)]
        img_8b_2d = np.reshape(img_8b_1d_trimmed, (self._h, self._w))

        return img_8b_2d

#    def convert(self, img):
#        return np.packbits(img) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def decode_1bit(self, img):
    """
    Decode the image from popcnt internal image format.
    """
    assert len(img.shape) == 1
    assert img.shape[0] >= (self._h * self._w / 8)
    assert img.shape[0] % self._align == 0

    bitrev8 = lambda x: sum(1 << (8 - 1 - i) for i in range(8) if x >> i & 1)
    img_reverse = np.array(
        list(map(lambda x: bitrev8(x), img)), dtype=np.uint8)

    img_8b_1d = np.unpackbits(img_reverse) * 255  # to 8bit gray scale.
    img_8b_1d_trimmed = img_8b_1d[0: (self._h * self._w)]
    img_8b_2d = np.reshape(img_8b_1d_trimmed, (self._h, self._w))

    return img_8b_2d 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def decode_1bit(values):
    return np.unpackbits(values.view(np.uint8)).astype(np.float32) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def test_payload_basics(self):
        assert self.payload.complex_data is False
        assert self.payload.sample_shape == (2,)
        assert self.payload.bps == 8
        assert self.payload.nbytes == 8
        assert self.payload.shape == (4, 2)
        assert self.payload.size == 8
        assert self.payload.ndim == 2
        assert np.all(self.payload.data.ravel()
                      == self.payload.words.view(np.int8))
        assert np.all(np.array(self.payload).ravel()
                      == self.payload.words.view(np.int8))
        assert np.all(np.array(self.payload, dtype=np.int8).ravel()
                      == self.payload.words.view(np.int8))
        payload = self.Payload(self.payload.words, bps=4)
        with pytest.raises(KeyError):
            payload.data
        with pytest.raises(ValueError):
            self.Payload(self.payload.words.astype('>u4'), bps=4)
        payload = self.Payload(self.payload.words, bps=8, complex_data=True)
        assert np.all(payload.data
                      == (self.payload.data[:, 0]
                          + 1j * self.payload.data[:, 1]))

        assert self.payload1bit.complex_data is True
        assert self.payload1bit.sample_shape == (5,)
        assert self.payload1bit.bps == 1
        assert self.payload1bit.shape == (16, 5)
        assert self.payload1bit.nbytes == 20
        assert np.all(self.payload1bit.data.ravel()
                      == (np.unpackbits(self.payload1bit.words.view(np.uint8))
                          .astype(np.float32).view(np.complex64))) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def get_coldata(coldata):
    """ return values and rowmask """
    dtype = np.dtype(coldata[DTYPE])
    values = np.frombuffer(decompress(coldata[DATA]), dtype=dtype)
    rowmask = np.unpackbits(np.frombuffer(decompress(coldata[ROWMASK]), dtype='uint8'))
    return list(values), list(rowmask) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def test_unpackbits():
    # Copied from the docstring.
    a = np.array([[2], [7], [23]], dtype=np.uint8)
    b = np.unpackbits(a, axis=1)
    assert_equal(b.dtype, np.uint8)
    assert_array_equal(b, np.array([[0, 0, 0, 0, 0, 0, 1, 0],
                                    [0, 0, 0, 0, 0, 1, 1, 1],
                                    [0, 0, 0, 1, 0, 1, 1, 1]])) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def test_unpackbits_empty():
    a = np.empty((0,), dtype=np.uint8)
    b = np.unpackbits(a)
    assert_equal(b.dtype, np.uint8)
    assert_array_equal(b, np.empty((0,))) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def test_unpackbits_large():
    # test all possible numbers via comparison to already tested packbits
    d = np.arange(277, dtype=np.uint8)
    assert_array_equal(np.packbits(np.unpackbits(d)), d)
    assert_array_equal(np.packbits(np.unpackbits(d[::2])), d[::2])
    d = np.tile(d, (3, 1))
    assert_array_equal(np.packbits(np.unpackbits(d, axis=1), axis=1), d)
    d = d.T.copy()
    assert_array_equal(np.packbits(np.unpackbits(d, axis=0), axis=0), d) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def split_sync(sync_tr):
    """
    The synchronization channelx are stored as single bits, this will split the int16 original
    channel into 16 single bits channels

    :param sync_tr: numpy vector: samples of synchronisation trace
    :return: int8 numpy array of 16 channels, 1 column per sync trace
    """
    sync_tr = np.int16(np.copy(sync_tr))
    out = np.unpackbits(sync_tr.view(np.uint8)).reshape(sync_tr.size, 16)
    out = np.flip(np.roll(out, 8, axis=1), axis=1)
    return np.int8(out) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import unpackbits [as 別名]
def fetch_aligned_array_of_bits(self, count: int) -> numpy.ndarray:
        """
        Quickly decodes an aligned array of bits using the numpy's fast bit unpacking routine.
        A new array is always created (the memory cannot be shared with the buffer due to the layout transformation).
        The returned array is of dtype :class:`numpy.bool`.
        """
        _ensure_cardinal(count)
        assert self._bit_offset % 8 == 0
        bs = self._buf.get_unsigned_slice(self._byte_offset, self._byte_offset + (count + 7) // 8)
        out = numpy.unpackbits(bs, bitorder='little')[:count]
        self._bit_offset += count
        assert len(out) == count
        return out.astype(dtype=numpy.bool)