Add vectorized from_bits and to_bits
#1199
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| @@ -528,6 +592,13 @@ def from_bits(self, bits: Sequence[int]) -> Fxp: | |||
| fxp_bin = "0b" + bits_bin[: -self.num_frac] + "." + bits_bin[-self.num_frac :] | |||
| return Fxp(fxp_bin, dtype=self.fxp_dtype_str) | |||
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| def from_bits_array(self, bits_array: NDArray[np.uint8]): | |||
| assert isinstance(self.bitsize, int), "cannot convert to bits for symbolic bitsize" | |||
| # TODO figure out why `np.vectorize` is not working here | |||
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Add a link to an open issue with the TODO?
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I'm planning to remove the fxpmath dependency in classical sim for now, in a follow-up PR, so this might become irrelevant. I can perhaps open an issue later when we decide to actually use fxpmath as our floating point library.
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You want to remove all code that uses fxpmath and remove the QFxp type ? That seems aggressive.
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No no, the QFxp type will stay, but will use integer values (i.e. binary repr of the fxp) for the classical simulator (i.e. from_bits and to_bits), instead of Fxp.
And other uses of fxpmath in the code will not be touched, e.g. the current phase gradient scaled_val etc.
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So when calling bloq.call_classically(phase_grad=_fxp_value_); the _fxp_value_ would be an int I believe ?
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Yep, like it is right now. I'll add a helper method to QFxp to convert a float/Fxp value into the correct int value for passing to the classical sim, so that end users don't have to manually figure out the correct binary representation.
Adds
from_bits_arrayandto_bits_array, and uses these functions in classical_sim'sints_to_bitsandbits_to_ints(which will be removed in a follow up PR).part of #1142