Hi everyone, I wondered how to express a numpy float exactly in terms of format, and found `%r` quite useful: `float(repr(a)) == a` is guaranteed for Python `float`s. When trying the same thing with lower-precision Python floats, I found this identity not quite fulfilled: ``` import numpy b = numpy.array([1.0 / 3.0], dtype=np.float16) float(repr(b[0])) - b[0] Out[12]: -1.9531250000093259e-06 ``` Indeed, ``` b Out[6]: array([ 0.33325195], dtype=float16) ``` ``` repr(b[0]) Out[7]: '0.33325' ``` When counting the bits, a float16 should hold 4.8 decimal digits, so `repr()` seems right. Where does the garbage tail -1.9531250000093259e-06 come from though?
Cheers, Nico
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