Replace NaN and infinite entries in an array.
JAX implementation of numpy.nan_to_num().
x (ArrayLike) – array of values to be replaced. If it does not have an inexact dtype it will be returned unmodified.
copy (bool) – unused by JAX
nan (ArrayLike) – value to substitute for NaN entries. Defaults to 0.0.
posinf (ArrayLike | None) – value to substitute for positive infinite entries. Defaults to the maximum representable value.
neginf (ArrayLike | None) – value to substitute for positive infinite entries. Defaults to the minimum representable value.
A copy of x with the requested substitutions.
Examples
>>> x = jnp.array([0, jnp.nan, 1, jnp.inf, 2, -jnp.inf])
Default substitution values:
>>> jnp.nan_to_num(x)
Array([ 0.0000000e+00, 0.0000000e+00, 1.0000000e+00, 3.4028235e+38,
2.0000000e+00, -3.4028235e+38], dtype=float32)
Overriding substitutions for -inf and +inf:
>>> jnp.nan_to_num(x, posinf=999, neginf=-999) Array([ 0., 0., 1., 999., 2., -999.], dtype=float32)
If you only wish to substitute for NaN values while leaving inf values untouched, using where() with jax.numpy.isnan() is a better option:
>>> jnp.where(jnp.isnan(x), 0, x) Array([ 0., 0., 1., inf, 2., -inf], dtype=float32)
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