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# scipy.special.i1e

scipy.special.i1e(x, out=None) = <ufunc 'i1e'>

  Exponentially scaled modified Bessel function of order 1.

  Defined as:

      i1e(x) = exp(-abs(x)) * i1(x)

  Parameters:
    xarray_like

      Argument (float)

    outndarray, optional

      Optional output array for the function values

  Returns:
    Iscalar or ndarray

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

  See also

  `iv`

    Modified Bessel function of the first kind

  `i1`

    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. The polynomial expansions used are the same as those in `i1`, but they are not multiplied by the dominant exponential factor.

  This function is a wrapper for the Cephes [1] routine `i1e`. `i1e` is useful for large arguments x: for these, `i1` quickly overflows.

  `i1e` 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 `i1` returns infinity whereas `i1e` still returns a finite number.

      >>> from scipy.special import i1, i1e
      >>> i1(1000.), i1e(1000.)
      (inf, 0.01261093025692863)

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

      >>> import numpy as np
      >>> i1e(np.array([-2., 0., 6.]))
      array([-0.21526929,  0.        ,  0.15205146])

  Plot the function between -10 and 10.

      >>> import matplotlib.pyplot as plt
      >>> fig, ax = plt.subplots()
      >>> x = np.linspace(-10., 10., 1000)
      >>> y = i1e(x)
      >>> ax.plot(x, y)
      >>> plt.show()