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# scipy.special.i1

scipy.special.i1(x, out=None) = <ufunc 'i1'>

  Modified Bessel function of order 1.

  Defined as,

  \[I_1(x) = \frac{1}{2}x \sum_{k=0}^\infty \frac{(x^2/4)^k}{k! (k + 1)!} = -\imath J_1(\imath x),\]

  where \(J_1\) is the Bessel function of the first kind of order 1.

  Parameters:
    x array_like

      Argument (float)

    out ndarray, optional

      Optional output array for the function values

  Returns:
    I scalar or ndarray

      Value of the modified Bessel function of order 1 at x.

  See also

  `iv`

    Modified Bessel function of the first kind

  `i1e`

    Exponentially scaled modified Bessel function of order 1

  Notes

  The range is partitioned into the two intervals [0, 8] and (8, infinity). Chebyshev polynomial expansions are employed in each interval.

  This function is a wrapper for the Cephes [1] routine `i1`.

  Array API Standard Support

  `i1` has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable `SCIPY_ARRAY_API=1` and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

  Library | CPU | GPU
  --- | --- | ---
  NumPy | ✅ | n/a
  CuPy | n/a | ✅
  PyTorch | ✅ | ✅
  JAX | ✅ | ✅
  Dask | ✅ | n/a

  See Support for the array API standard for more information.

  References

  [1]

  Cephes Mathematical Functions Library, http://www.netlib.org/cephes/

  Examples

  Calculate the function at one point:

      >>> from scipy.special import i1
      >>> i1(1.)
      0.5651591039924851

  Calculate the function at several points:

      >>> import numpy as np
      >>> i1(np.array([-2., 0., 6.]))
      array([-1.59063685,  0.        , 61.34193678])

  Plot the function between -10 and 10.

      >>> import matplotlib.pyplot as plt
      >>> fig, ax = plt.subplots()
      >>> x = np.linspace(-10., 10., 1000)
      >>> y = i1(x)
      >>> ax.plot(x, y)
      >>> plt.show()