Bits and Integers
The goal
Manipulation of integers and their bits
Questions to David Rotermund
numpy.ndarray.byteswap
ndarray.byteswap(inplace=False)
Swap the bytes of the array elements
Toggle between low-endian and big-endian data representation by returning a byteswapped array, optionally swapped in-place. Arrays of byte-strings are not swapped. The real and imaginary parts of a complex number are swapped individually.
inplace : bool, optional
If True, swap bytes in-place, default is False.
import numpy as np
v = np.uint16(255)
print(f"{v:016b}") # -> 0000000011111111
print(f"{v.byteswap():016b}") # -> 1111111100000000
numpy.bitwise_and
numpy.bitwise_and(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Compute the bit-wise AND of two arrays element-wise.
Computes the bit-wise AND of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator &.
import numpy as np
a = [True, True, False, False]
b = [True, False, True, False]
u = 3
v = 5
print(f"{u:04b}") # -> 0011
print(f"{v:04b}") # -> 0101
print(np.bitwise_and(a, b)) # -> [ True False False False]
print(f"{np.bitwise_and(u, v):04b}") # -> 0001
numpy.bitwise_or
numpy.bitwise_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Compute the bit-wise OR of two arrays element-wise.
Computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator |.
import numpy as np
a = [True, True, False, False]
b = [True, False, True, False]
u = 3
v = 5
print(f"{u:04b}") # -> 0011
print(f"{v:04b}") # -> 0101
print(np.bitwise_or(a, b)) # -> [ True True True False]
print(f"{np.bitwise_or(u, v):04b}") # -> 0111
numpy.bitwise_xor
numpy.bitwise_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Compute the bit-wise XOR of two arrays element-wise.
Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^.
import numpy as np
a = [True, True, False, False]
b = [True, False, True, False]
u = 3
v = 5
print(f"{u:04b}") # -> 0011
print(f"{v:04b}") # -> 0101
print(np.bitwise_xor(a, b)) # -> [False True True False]
print(f"{np.bitwise_xor(u, v):04b}") # -> 0110
bitwise_not
bitwise_not is an alias for invert
numpy.invert(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ~.
For signed integer inputs, the two’s complement is returned.
import numpy as np
a = [True, True, False, False]
u = 3
v = np.uint8(u)
print(f"{u:08b}") # -> 00000011
print(f"{v:08b}") # -> 00000011
print(np.bitwise_not(a)) # -> [False False True True]
print(f"{np.bitwise_not(u)}") # -> -4
print(f"{np.bitwise_not(v):08b}") # -> 11111100
numpy.left_shift
numpy.left_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Shift the bits of an integer to the left.
Bits are shifted to the left by appending x2 0s at the right of x1. Since the internal representation of numbers is in binary format, this operation is equivalent to multiplying x1 by 2**x2
numpy.right_shift
numpy.right_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
Shift the bits of an integer to the right.
Bits are shifted to the right x2. Because the internal representation of numbers is in binary format, this operation is equivalent to dividing x1 by 2**x2.
numpy.binary_repr
numpy.binary_repr(num, width=None)
Return the binary representation of the input number as a string.
The source code is Open Source and can be found on GitHub.