Performs a test to verify that 8, 10, 12, and 16-bit code values can be converted to normalized 32-bit floats, rounded to only 5 decimal places (!!!), and reconverted losslessly back to the original integer code value.

Float32Precision.py

import numpy as np

def float32PrecisionTest(bitdepth, floatingPointDecimalPlaces):
    maximumCodeValue = pow(2, bitdepth) - 1
    maximumCodeValueAsFloat = np.float32(maximumCodeValue)

    failedCodeValues = []
    for codeValue in range(0, pow(2, bitdepth)):
        normalizedFloatValue = np.round(np.float32(codeValue) / maximumCodeValueAsFloat, floatingPointDecimalPlaces)
        rescaledCodeValue = np.uint16(np.round(normalizedFloatValue * maximumCodeValueAsFloat))
        if codeValue != rescaledCodeValue:
            failedCodeValues.append(codeValue)
    return failedCodeValues

floatingPointDecimalPlaces = 5
for bitdepth in [8, 10, 12, 16]:
    result = float32PrecisionTest(bitdepth, floatingPointDecimalPlaces)
    if len(result) is 0:
        print(str(bitdepth) + "-bit test passed.")
    else:
        print(str(bitdepth) + "-bit test failed for " + str(len(result)) + " code values")

Output of running this:

8-bit test passed.
10-bit test passed.
12-bit test passed.
16-bit test passed.