jax.numpy.poly#

jax.numpy.poly(seq_of_zeros)[source]#

Returns the coefficients of a polynomial for the given sequence of roots.

JAX implementation ofnumpy.poly().

Parameters:

seq_of_zeros (ArrayLike) – A scalar or an array of roots of the polynomial of shape(M,)or(M,M).

Returns:

An array containing the coefficients of the polynomial. The dtype of theoutput is always promoted to inexact.

Return type:

Array

Note

jax.numpy.poly() differs fromnumpy.poly():

• When the input is a scalar,np.poly raises aTypeError, whereasjnp.poly treats scalars the same as length-1 arrays.

• For complex-valued or square-shaped inputs,jnp.poly always returnscomplex coefficients, whereasnp.poly may return real or complexdepending on their values.

See also

• jax.numpy.polyfit(): Least squares polynomial fit.

• jax.numpy.polyval(): Evaluate a polynomial at specific values.

• jax.numpy.roots(): Computes the roots of a polynomial for givencoefficients.

Examples

Scalar inputs:

>>>jnp.poly(1)Array([ 1., -1.], dtype=float32)

Input array with integer values:

>>>x=jnp.array([1,2,3])>>>jnp.poly(x)Array([ 1., -6., 11., -6.], dtype=float32)

Input array with complex conjugates:

>>>x=jnp.array([2,1+2j,1-2j])>>>jnp.poly(x)Array([  1.+0.j,  -4.+0.j,   9.+0.j, -10.+0.j], dtype=complex64)

Input array as square matrix with real valued inputs:

>>>x=jnp.array([[2,1,5],...[3,4,7],...[1,3,5]])>>>jnp.round(jnp.poly(x))Array([  1.+0.j, -11.-0.j,   9.+0.j, -15.+0.j], dtype=complex64)