View source for Manipulation of integers and their bits

== The goal ==
Manipulation of integers and their bits

Questions to [mailto:davrot@uni-bremen.de David Rotermund]

== [https://numpy.org/doc/stable/reference/generated/numpy.ndarray.byteswap.html numpy.ndarray.byteswap] ==
<syntaxhighlight lang="python">ndarray.byteswap(inplace=False)</syntaxhighlight><blockquote>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.</blockquote><syntaxhighlight lang="python">import numpy as np

v = np.uint16(255)

print(f"{v:016b}")  # -> 0000000011111111

print(f"{v.byteswap():016b}")  # -> 1111111100000000</syntaxhighlight>

== [https://numpy.org/doc/stable/reference/generated/numpy.bitwise_and.html numpy.bitwise_and] ==
<syntaxhighlight lang="python">numpy.bitwise_and(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])</syntaxhighlight><blockquote>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 &#x26;.</blockquote><syntaxhighlight lang="python">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</syntaxhighlight>

== [https://numpy.org/doc/stable/reference/generated/numpy.bitwise_or.html numpy.bitwise_or] ==
<syntaxhighlight lang="python">numpy.bitwise_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) </syntaxhighlight><blockquote>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 |.</blockquote><syntaxhighlight lang="python">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</syntaxhighlight>

== [https://numpy.org/doc/stable/reference/generated/numpy.bitwise_xor.html numpy.bitwise_xor] ==
<syntaxhighlight lang="python">numpy.bitwise_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])</syntaxhighlight><blockquote>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 ^.</blockquote><syntaxhighlight lang="python">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</syntaxhighlight>

== [https://numpy.org/doc/stable/reference/generated/numpy.invert.html bitwise_not] ==
<blockquote>'''bitwise_not is an alias for invert'''</blockquote><syntaxhighlight lang="python">numpy.invert(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])</syntaxhighlight><blockquote>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.</blockquote><syntaxhighlight lang="python">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</syntaxhighlight>

== [https://numpy.org/doc/stable/reference/generated/numpy.left_shift.html numpy.left_shift] ==
<syntaxhighlight lang="python">numpy.left_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])</syntaxhighlight><blockquote>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</blockquote>

== [https://numpy.org/doc/stable/reference/generated/numpy.right_shift.html numpy.right_shift] ==
<syntaxhighlight lang="python">numpy.right_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])</syntaxhighlight><blockquote>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.</blockquote>

== [https://numpy.org/doc/stable/reference/generated/numpy.binary_repr.html numpy.binary_repr] ==
<syntaxhighlight lang="python">numpy.binary_repr(num, width=None)</syntaxhighlight><blockquote>Return the binary representation of the input number as a string.</blockquote>