Reconstructing a signed floating point value from its 2's complement fixed point representation in a numpy/cupy friendly way

fixed_point_reconstruction.py

import numpy as np
from fxpmath import Fxp

N_FRAC = 8
BITS = 32

def twos_comp(val, bits):
    # numpy/cupy/kernel friendly version of https://stackoverflow.com/a/9147327
    sign_bits = (val & (1 << (bits - 1))) >> (bits - 1)
    return np.int32(np.subtract(val, np.multiply(sign_bits, (1 << bits))))

# Get some random values
actual = np.random.ranf(10) - np.random.ranf(10)
# Get fixed point representation
fxp = Fxp(actual, signed = True, n_frac = N_FRAC)
# Get raw values
raw = np.uint32(fxp.raw())

# Calculate two's complement of each of the raw values
twos = twos_comp(raw, BITS)
# Reconstruct the original floating point value
reconstructed = twos / (2 ** N_FRAC)

# How did we do?
print(f"actual: {actual}")
print(f"reconstructed: {reconstructed}")