Unpack the bits in a uint8 array.
JAX implementation of numpy.unpackbits().
a (ArrayLike) – N-dimensional array of type uint8.
axis (int | None) – optional axis along which to unpack. If not specified, a will be flattened
count (int | None) – specify the number of bits to unpack (if positive) or the number of bits to trim from the end (if negative).
bitorder (str) – "big" (default) or "little": specify whether the bit order is big-endian or little-endian.
a uint8 array of unpacked bits.
Examples
Unpacking bits from a scalar:
>>> jnp.unpackbits(jnp.uint8(27)) # big-endian by default Array([0, 0, 0, 1, 1, 0, 1, 1], dtype=uint8) >>> jnp.unpackbits(jnp.uint8(27), bitorder="little") Array([1, 1, 0, 1, 1, 0, 0, 0], dtype=uint8)
Compare this to the Python binary representation:
Unpacking bits along an axis:
>>> vals = jnp.array([[154],
... [ 49]], dtype='uint8')
>>> bits = jnp.unpackbits(vals, axis=1)
>>> bits
Array([[1, 0, 0, 1, 1, 0, 1, 0],
[0, 0, 1, 1, 0, 0, 0, 1]], dtype=uint8)
Using packbits() to invert this:
>>> jnp.packbits(bits, axis=1)
Array([[154],
[ 49]], dtype=uint8)
The count keyword lets unpackbits serve as an inverse of packbits in cases where not all bits are present:
>>> bits = jnp.array([1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1]) # 11 bits >>> vals = jnp.packbits(bits) >>> vals Array([219, 96], dtype=uint8) >>> jnp.unpackbits(vals) # 16 zero-padded bits Array([1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0], dtype=uint8) >>> jnp.unpackbits(vals, count=11) # specify 11 output bits Array([1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1], dtype=uint8) >>> jnp.unpackbits(vals, count=-5) # specify 5 bits to be trimmed Array([1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1], dtype=uint8)
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