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# scipy.special.i0e

scipy.special.i0e(x, out=None) = <ufunc 'i0e'>

  Exponentially scaled modified Bessel function of order 0.

  Defined as:

      i0e(x) = exp(-abs(x)) * i0(x).

  Parameters:
    x array_like

      Argument (float)

    out ndarray, optional

      Optional output array for the function values

  Returns:
    I scalar or ndarray

      Value of the exponentially scaled modified Bessel function of order 0 at x.

  See also

  `iv`

    Modified Bessel function of the first kind

  `i0`

    Modified Bessel function of order 0

  Notes

  The range is partitioned into the two intervals [0, 8] and (8, infinity). Chebyshev polynomial expansions are employed in each interval. The polynomial expansions used are the same as those in `i0`, but they are not multiplied by the dominant exponential factor.

  This function is a wrapper for the Cephes [1] routine `i0e`. `i0e` is useful for large arguments x: for these, `i0` quickly overflows.

  `i0e` 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

  In the following example `i0` returns infinity whereas `i0e` still returns a finite number.

      >>> from scipy.special import i0, i0e
      >>> i0(1000.), i0e(1000.)
      (inf, 0.012617240455891257)

  Calculate the function at several points by providing a NumPy array or list for x:

      >>> import numpy as np
      >>> i0e(np.array([-2., 0., 3.]))
      array([0.30850832, 1.        , 0.24300035])

  Plot the function from -10 to 10.

      >>> import matplotlib.pyplot as plt
      >>> fig, ax = plt.subplots()
      >>> x = np.linspace(-10., 10., 1000)
      >>> y = i0e(x)
      >>> ax.plot(x, y)
      >>> plt.show()