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# scipy.special.itairy

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

  Integrals of Airy functions

  Calculates the integrals of Airy functions from 0 to x.

  Parameters:
    xarray_like

      Upper limit of integration (float).

    outtuple of ndarray, optional

      Optional output arrays for the function values

  Returns:
    Aptscalar or ndarray

      Integral of Ai(t) from 0 to x.

    Bptscalar or ndarray

      Integral of Bi(t) from 0 to x.

    Antscalar or ndarray

      Integral of Ai(-t) from 0 to x.

    Bntscalar or ndarray

      Integral of Bi(-t) from 0 to x.

  Notes

  Wrapper for a Fortran routine created by Shanjie Zhang and Jianming Jin [1].

  References

  [1]

  Zhang, Shanjie and Jin, Jianming. “Computation of Special Functions”, John Wiley and Sons, 1996. https://people.sc.fsu.edu/~jburkardt/f_src/special_functions/special_functions.html

  Examples

  Compute the functions at `x=1.`.

      >>> import numpy as np
      >>> from scipy.special import itairy
      >>> import matplotlib.pyplot as plt
      >>> apt, bpt, ant, bnt = itairy(1.)
      >>> apt, bpt, ant, bnt
      (0.23631734191710949,
       0.8727691167380077,
       0.46567398346706845,
       0.3730050096342943)

  Compute the functions at several points by providing a NumPy array for x.

      >>> x = np.array([1., 1.5, 2.5, 5])
      >>> apt, bpt, ant, bnt = itairy(x)
      >>> apt, bpt, ant, bnt
      (array([0.23631734, 0.28678675, 0.324638  , 0.33328759]),
       array([  0.87276912,   1.62470809,   5.20906691, 321.47831857]),
       array([0.46567398, 0.72232876, 0.93187776, 0.7178822 ]),
       array([ 0.37300501,  0.35038814, -0.02812939,  0.15873094]))

  Plot the functions from -10 to 10.

      >>> x = np.linspace(-10, 10, 500)
      >>> apt, bpt, ant, bnt = itairy(x)
      >>> fig, ax = plt.subplots(figsize=(6, 5))
      >>> ax.plot(x, apt, label=r"$\int_0^x\, Ai(t)\, dt$")
      >>> ax.plot(x, bpt, ls="dashed", label=r"$\int_0^x\, Bi(t)\, dt$")
      >>> ax.plot(x, ant, ls="dashdot", label=r"$\int_0^x\, Ai(-t)\, dt$")
      >>> ax.plot(x, bnt, ls="dotted", label=r"$\int_0^x\, Bi(-t)\, dt$")
      >>> ax.set_ylim(-2, 1.5)
      >>> ax.legend(loc="lower right")
      >>> plt.show()