.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "matplotlib/plot_complex_KAM.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_matplotlib_plot_complex_KAM.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_matplotlib_plot_complex_KAM.py:


Complexified KAM curve (standard map)
=======================================

:math:`k=0.9, \nu=0.618034`

[1]J. M. Greene and I. C. Percival, Hamiltonian Maps in the Complex Plane, Physica D: Nonlinear Phenomena 3, 530 (1981).

.. GENERATED FROM PYTHON SOURCE LINES 10-90

.. code-block:: default


    import numpy as np
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    import sys
    import glob


    k = -0.9
    twopi=2.0*np.pi

    def Q(coeff, theta):
        res = np.copy(theta) + 0.j
        for i, m in enumerate(coeff[0]):
            res += -1.j*coeff[1][i]*np.exp(1.j*theta*m) + 1.j*coeff[1][i]*np.exp(-1.j*theta*m)
        return res

    def P(coeff, theta):
        return Q(coeff, theta) - Q(coeff, theta + twopi*nu) - np.sin(Q(coeff, theta))*k/2



    dirname = "nu_0.618034"
    nu = float(dirname.split("_")[1])
    path = dirname + "/fourier_coeff_j21.dat"
    coeff = np.loadtxt(path).transpose()

    fig = plt.figure()
    ax = fig.add_subplot(1,1,1,projection='3d')
    ax.axis('off')

    traj = np.loadtxt(dirname + "/traj.DAT").T
    ymin,ymax = 3.5, 4.5
    index = (traj[1]>ymin) & (traj[1]<ymax)
    index2 = (traj[1]<3.8) & (traj[0]<4)
    traj[0][index2] = np.nan
    traj[1][index2] = np.nan
    index2 = (traj[1]<4.1) & (traj[0]<0.8)
    traj[0][index2] = np.nan
    traj[1][index2] = np.nan
    ax.plot(traj[0][index],traj[1][index],',',c='k')

    sample=100
    im_max= 0.0
    theta = np.linspace(0,twopi,sample) + 1.j*im_max

    q = Q(coeff, theta)
    p = P(coeff, theta)
    ax.plot(q.real, -p.real, q.imag,'-k',lw=2)


    sample=3000
    im_max= 0.083717354931950
    theta = np.linspace(0,twopi,sample) + 1.j*im_max

    q = Q(coeff, theta)
    p = P(coeff, theta)
    ax.plot(q.real, -p.real, q.imag,'-k',lw=2)

    sample=200
    #im_max = 0.0155717354931950
    [re_theta, im_theta] = np.meshgrid(
        np.linspace(0,twopi, sample),
        np.linspace(0, im_max, sample)
    )
    theta = re_theta + 1.j*im_theta

    q = Q(coeff, theta)
    p = P(coeff, theta)
    #ax.plot_wireframe(q.real, -p.real, q.imag,rstride=20, cstride=1, alpha=0.1,color='k')
    ax.plot_wireframe(q.real, -p.real, q.imag,rstride=20, cstride=2, color='k',alpha=0.5)


    ax.set_ylim(ymin,ymax)
    ax.set_xlim(0,2*np.pi)
    ax.view_init(40,40)
    #plt.savefig("KAM.png",transparent=True)
    plt.show()





.. image:: /matplotlib/images/sphx_glr_plot_complex_KAM_001.png
    :alt: plot complex KAM
    :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 91-95

A table of fourier coefficients
-------------------------------



.. GENERATED FROM PYTHON SOURCE LINES 95-96

.. code-block:: default

    print(coeff) # fourier_coeff_j21.dat"




.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    [[ 1.00000000e+00  2.00000000e+00  3.00000000e+00  4.00000000e+00
       5.00000000e+00  6.00000000e+00  7.00000000e+00  8.00000000e+00
       9.00000000e+00  1.00000000e+01  1.10000000e+01  1.20000000e+01
       1.30000000e+01  1.40000000e+01  1.50000000e+01  1.60000000e+01
       1.70000000e+01  1.80000000e+01  1.90000000e+01  2.00000000e+01
       2.10000000e+01  2.20000000e+01  2.30000000e+01  2.40000000e+01
       2.50000000e+01  2.60000000e+01  2.70000000e+01  2.80000000e+01
       2.90000000e+01  3.00000000e+01  3.10000000e+01  3.20000000e+01
       3.30000000e+01  3.40000000e+01  3.50000000e+01  3.60000000e+01
       3.70000000e+01  3.80000000e+01  3.90000000e+01  4.00000000e+01
       4.10000000e+01  4.20000000e+01  4.30000000e+01  4.40000000e+01
       4.50000000e+01  4.60000000e+01  4.70000000e+01  4.80000000e+01
       4.90000000e+01  5.00000000e+01  5.10000000e+01  5.20000000e+01
       5.30000000e+01  5.40000000e+01  5.50000000e+01  5.60000000e+01
       5.70000000e+01  5.80000000e+01  5.90000000e+01  6.00000000e+01
       6.10000000e+01  6.20000000e+01  6.30000000e+01  6.40000000e+01
       6.50000000e+01  6.60000000e+01  6.70000000e+01  6.80000000e+01
       6.90000000e+01  7.00000000e+01  7.10000000e+01  7.20000000e+01
       7.30000000e+01  7.40000000e+01  7.50000000e+01  7.60000000e+01
       7.70000000e+01  7.80000000e+01  7.90000000e+01  8.00000000e+01
       8.10000000e+01  8.20000000e+01  8.30000000e+01  8.40000000e+01
       8.50000000e+01  8.60000000e+01  8.70000000e+01  8.80000000e+01
       8.90000000e+01  9.00000000e+01  9.10000000e+01  9.20000000e+01
       9.30000000e+01  9.40000000e+01  9.50000000e+01  9.60000000e+01
       9.70000000e+01  9.80000000e+01  9.90000000e+01  1.00000000e+02
       1.01000000e+02  1.02000000e+02  1.03000000e+02  1.04000000e+02
       1.05000000e+02  1.06000000e+02  1.07000000e+02  1.08000000e+02
       1.09000000e+02  1.10000000e+02  1.11000000e+02  1.12000000e+02
       1.13000000e+02  1.14000000e+02  1.15000000e+02  1.16000000e+02
       1.17000000e+02  1.18000000e+02  1.19000000e+02  1.20000000e+02
       1.21000000e+02  1.22000000e+02  1.23000000e+02  1.24000000e+02
       1.25000000e+02  1.26000000e+02  1.27000000e+02  1.28000000e+02
       1.29000000e+02  1.30000000e+02  1.31000000e+02  1.32000000e+02
       1.33000000e+02  1.34000000e+02  1.35000000e+02  1.36000000e+02
       1.37000000e+02  1.38000000e+02  1.39000000e+02  1.40000000e+02
       1.41000000e+02  1.42000000e+02  1.43000000e+02  1.44000000e+02
       1.45000000e+02  1.46000000e+02  1.47000000e+02  1.48000000e+02
       1.49000000e+02  1.50000000e+02  1.51000000e+02  1.52000000e+02
       1.53000000e+02  1.54000000e+02  1.55000000e+02  1.56000000e+02
       1.57000000e+02  1.58000000e+02  1.59000000e+02  1.60000000e+02
       1.61000000e+02  1.62000000e+02  1.63000000e+02  1.64000000e+02
       1.65000000e+02  1.66000000e+02  1.67000000e+02  1.68000000e+02
       1.69000000e+02  1.70000000e+02  1.71000000e+02  1.72000000e+02
       1.73000000e+02  1.74000000e+02  1.75000000e+02  1.76000000e+02
       1.77000000e+02  1.78000000e+02  1.79000000e+02  1.80000000e+02
       1.81000000e+02  1.82000000e+02  1.83000000e+02  1.84000000e+02
       1.85000000e+02  1.86000000e+02  1.87000000e+02  1.88000000e+02
       1.89000000e+02  1.90000000e+02  1.91000000e+02  1.92000000e+02
       1.93000000e+02  1.94000000e+02  1.95000000e+02  1.96000000e+02
       1.97000000e+02  1.98000000e+02  1.99000000e+02  2.00000000e+02
       2.01000000e+02  2.02000000e+02  2.03000000e+02  2.04000000e+02
       2.05000000e+02  2.06000000e+02  2.07000000e+02  2.08000000e+02
       2.09000000e+02  2.10000000e+02  2.11000000e+02  2.12000000e+02
       2.13000000e+02  2.14000000e+02  2.15000000e+02  2.16000000e+02
       2.17000000e+02  2.18000000e+02  2.19000000e+02  2.20000000e+02
       2.21000000e+02  2.22000000e+02  2.23000000e+02  2.24000000e+02
       2.25000000e+02  2.26000000e+02  2.27000000e+02  2.28000000e+02
       2.29000000e+02  2.30000000e+02  2.31000000e+02  2.32000000e+02
       2.33000000e+02  2.34000000e+02  2.35000000e+02  2.36000000e+02
       2.37000000e+02  2.38000000e+02  2.39000000e+02  2.40000000e+02
       2.41000000e+02  2.42000000e+02  2.43000000e+02  2.44000000e+02
       2.45000000e+02  2.46000000e+02  2.47000000e+02  2.48000000e+02
       2.49000000e+02  2.50000000e+02  2.51000000e+02  2.52000000e+02
       2.53000000e+02  2.54000000e+02  2.55000000e+02  2.56000000e+02
       2.57000000e+02  2.58000000e+02  2.59000000e+02  2.60000000e+02
       2.61000000e+02  2.62000000e+02  2.63000000e+02  2.64000000e+02
       2.65000000e+02  2.66000000e+02  2.67000000e+02  2.68000000e+02
       2.69000000e+02  2.70000000e+02  2.71000000e+02  2.72000000e+02
       2.73000000e+02  2.74000000e+02  2.75000000e+02  2.76000000e+02
       2.77000000e+02  2.78000000e+02  2.79000000e+02  2.80000000e+02
       2.81000000e+02  2.82000000e+02  2.83000000e+02  2.84000000e+02
       2.85000000e+02  2.86000000e+02  2.87000000e+02  2.88000000e+02
       2.89000000e+02  2.90000000e+02  2.91000000e+02  2.92000000e+02
       2.93000000e+02  2.94000000e+02  2.95000000e+02  2.96000000e+02
       2.97000000e+02  2.98000000e+02  2.99000000e+02  3.00000000e+02
       3.01000000e+02  3.02000000e+02  3.03000000e+02  3.04000000e+02
       3.05000000e+02  3.06000000e+02  3.07000000e+02  3.08000000e+02
       3.09000000e+02  3.10000000e+02  3.11000000e+02  3.12000000e+02
       3.13000000e+02  3.14000000e+02  3.15000000e+02  3.16000000e+02
       3.17000000e+02  3.18000000e+02  3.19000000e+02  3.20000000e+02
       3.21000000e+02  3.22000000e+02  3.23000000e+02  3.24000000e+02
       3.25000000e+02  3.26000000e+02  3.27000000e+02  3.28000000e+02
       3.29000000e+02  3.30000000e+02  3.31000000e+02  3.32000000e+02
       3.33000000e+02  3.34000000e+02  3.35000000e+02  3.36000000e+02
       3.37000000e+02  3.38000000e+02  3.39000000e+02  3.40000000e+02
       3.41000000e+02  3.42000000e+02  3.43000000e+02  3.44000000e+02
       3.45000000e+02  3.46000000e+02  3.47000000e+02  3.48000000e+02
       3.49000000e+02  3.50000000e+02  3.51000000e+02  3.52000000e+02
       3.53000000e+02  3.54000000e+02  3.55000000e+02  3.56000000e+02
       3.57000000e+02  3.58000000e+02  3.59000000e+02  3.60000000e+02
       3.61000000e+02  3.62000000e+02  3.63000000e+02  3.64000000e+02
       3.65000000e+02  3.66000000e+02  3.67000000e+02  3.68000000e+02
       3.69000000e+02  3.70000000e+02  3.71000000e+02  3.72000000e+02
       3.73000000e+02  3.74000000e+02  3.75000000e+02  3.76000000e+02
       3.77000000e+02  3.78000000e+02  3.79000000e+02  3.80000000e+02
       3.81000000e+02  3.82000000e+02  3.83000000e+02  3.84000000e+02
       3.85000000e+02  3.86000000e+02  3.87000000e+02  3.88000000e+02
       3.89000000e+02  3.90000000e+02  3.91000000e+02  3.92000000e+02
       3.93000000e+02  3.94000000e+02  3.95000000e+02  3.96000000e+02
       3.97000000e+02  3.98000000e+02  3.99000000e+02  4.00000000e+02
       4.01000000e+02  4.02000000e+02  4.03000000e+02  4.04000000e+02
       4.05000000e+02  4.06000000e+02  4.07000000e+02  4.08000000e+02
       4.09000000e+02  4.10000000e+02  4.11000000e+02  4.12000000e+02
       4.13000000e+02  4.14000000e+02  4.15000000e+02  4.16000000e+02
       4.17000000e+02  4.18000000e+02  4.19000000e+02  4.20000000e+02
       4.21000000e+02  4.22000000e+02  4.23000000e+02  4.24000000e+02
       4.25000000e+02  4.26000000e+02  4.27000000e+02  4.28000000e+02
       4.29000000e+02  4.30000000e+02  4.31000000e+02  4.32000000e+02
       4.33000000e+02  4.34000000e+02  4.35000000e+02  4.36000000e+02
       4.37000000e+02  4.38000000e+02  4.39000000e+02  4.40000000e+02
       4.41000000e+02  4.42000000e+02  4.43000000e+02  4.44000000e+02
       4.45000000e+02  4.46000000e+02  4.47000000e+02  4.48000000e+02
       4.49000000e+02  4.50000000e+02  4.51000000e+02  4.52000000e+02
       4.53000000e+02  4.54000000e+02  4.55000000e+02  4.56000000e+02
       4.57000000e+02  4.58000000e+02  4.59000000e+02  4.60000000e+02
       4.61000000e+02  4.62000000e+02  4.63000000e+02  4.64000000e+02
       4.65000000e+02  4.66000000e+02  4.67000000e+02  4.68000000e+02
       4.69000000e+02  4.70000000e+02  4.71000000e+02  4.72000000e+02
       4.73000000e+02  4.74000000e+02  4.75000000e+02  4.76000000e+02
       4.77000000e+02  4.78000000e+02  4.79000000e+02  4.80000000e+02
       4.81000000e+02  4.82000000e+02  4.83000000e+02  4.84000000e+02
       4.85000000e+02  4.86000000e+02  4.87000000e+02  4.88000000e+02
       4.89000000e+02  4.90000000e+02  4.91000000e+02  4.92000000e+02
       4.93000000e+02  4.94000000e+02  4.95000000e+02  4.96000000e+02
       4.97000000e+02  4.98000000e+02  4.99000000e+02  5.00000000e+02]
     [-1.30923453e-01  3.56452081e-02 -2.41351069e-02  4.25617201e-03
      -1.08149058e-02  2.35555567e-03 -1.38691088e-03  5.54426960e-03
      -7.48850216e-04  7.34701963e-04 -4.93464786e-04  3.33601388e-04
      -2.18632563e-03  3.32386775e-04 -1.68928509e-04  2.96589257e-04
      -6.00715667e-05  1.53032506e-04 -7.72359230e-05  1.07113688e-04
      -7.27102937e-04  9.46203658e-05 -6.18993016e-05  5.12473018e-05
      -1.65296139e-05  7.31971149e-05 -1.55929042e-05  1.01956250e-05
      -3.57031209e-05  6.90268106e-06 -1.52776812e-05  1.40683532e-05
      -2.04246481e-05  1.57194976e-04 -2.16376889e-05  1.12356598e-05
      -1.38645589e-05  2.97813726e-06 -8.28524409e-06  2.66171287e-06
      -2.31687357e-06  1.28261351e-05 -1.83549012e-06  1.65549397e-06
      -1.29469777e-06  7.25814220e-07 -4.60583734e-06  8.57269507e-07
      -6.12687164e-07  1.69546286e-06 -4.56644395e-07  1.67331898e-06
      -1.36976436e-06  2.48610059e-06 -1.85838261e-05  2.42087387e-06
      -1.40405350e-06  1.30931501e-06 -3.41171455e-07  1.22449849e-06
      -2.93903811e-07  1.88734654e-07 -7.76776041e-07  1.26545941e-07
      -1.68467056e-07  1.31565235e-07 -1.27321730e-07  9.60248840e-07
      -1.47304584e-07  7.83522691e-08 -1.25334553e-07  2.68487720e-08
      -7.21855840e-08  3.14499150e-08 -3.90066027e-08  2.60298973e-07
      -3.65430432e-08  2.91391256e-08 -2.59999117e-08  1.24501313e-08
      -7.01442489e-08  1.53027017e-08 -1.54997242e-08  5.79078259e-08
      -1.55080967e-08  5.65304420e-08 -5.73708215e-08  1.00312396e-07
      -7.75370675e-07  1.03357334e-07 -5.51155239e-08  6.01401514e-08
      -1.35878085e-08  4.08594834e-08 -1.15072875e-08  8.54425604e-09
      -4.21693305e-08  6.25701237e-09 -6.26547779e-09  4.64987645e-09
      -2.99552271e-09  2.05549896e-08 -3.54933458e-09  2.03542689e-09
      -4.32809196e-09  9.81755629e-10 -2.87125015e-09  1.80852168e-09
      -2.95183072e-09  2.16558513e-08 -2.90497524e-09  1.86456359e-09
      -1.65736459e-09  5.01379730e-10 -2.10317269e-09  4.80644067e-10
      -3.10224043e-10  1.17570331e-09 -2.13749141e-10  3.82381888e-10
      -3.36889688e-10  4.36568318e-10 -3.49922398e-09  5.15697043e-10
      -2.77984207e-10  3.91402599e-10 -8.75585124e-11  2.53288280e-10
      -9.57887585e-11  1.05929367e-10 -6.46926755e-10  9.37932539e-11
      -9.32077592e-11  9.19803778e-11 -6.50162347e-11  4.21176732e-10
      -8.66616288e-11  1.00039472e-10 -3.52762607e-10  1.10598876e-10
      -4.67860591e-10  4.38690472e-10 -8.15522323e-10  6.20084036e-09
      -8.09893287e-10  4.51238706e-10 -4.43073852e-10  1.08101969e-10
      -3.59338671e-10  9.07723109e-11 -6.04545939e-11  2.65733344e-10
      -4.14486710e-11  4.84916888e-11 -3.64124639e-11  2.97289472e-11
      -2.16518913e-10  3.45949922e-11 -1.86027379e-11  3.27261122e-11
      -6.97900182e-12  1.85250001e-11 -9.06210178e-12  1.23715204e-11
      -8.68435302e-11  1.20437798e-11 -8.66257484e-12  7.45449646e-12
      -2.74485679e-12  1.35575878e-11 -2.97214718e-12  2.20385591e-12
      -7.97269016e-12  1.75329330e-12 -4.82982741e-12  4.79027861e-12
      -7.72812100e-12  6.09243126e-11 -8.44044195e-12  4.50707959e-12
      -5.40071330e-12  1.20196899e-12 -3.49958127e-12  1.08598510e-12
      -8.99561316e-13  4.86100006e-12 -7.17738367e-13  6.80387205e-13
      -5.24592007e-13  3.07968469e-13 -2.04760004e-12  3.76266781e-13
      -2.40651485e-13  6.02495504e-13 -1.51745094e-13  5.12383055e-13
      -3.88277263e-13  6.97907462e-13 -5.29251890e-12  7.09261180e-13
      -4.34586272e-13  4.04279220e-13 -1.13105824e-13  4.37698210e-13
      -1.04652427e-13  6.79501905e-14 -2.75012105e-13  4.72522958e-14
      -7.06559370e-14  5.83442945e-14 -6.41670249e-14  5.09932690e-13
      -7.80636229e-14  4.29360379e-14 -6.80905676e-14  1.60239584e-14
      -4.98205168e-14  2.25823254e-14 -3.16692550e-14  2.05435611e-13
      -2.92206746e-14  3.00688719e-14 -3.40594183e-14  2.53993981e-14
      -1.61815023e-13  3.59972521e-14 -4.94286263e-14  1.91419323e-13
      -5.79777798e-14  2.38765740e-13 -2.40150795e-13  4.35630053e-13
      -3.34804322e-12  4.41273066e-13 -2.38249322e-13  2.48569571e-13
      -5.75029794e-14  1.78751531e-13 -4.80351418e-14  3.39195584e-14
      -1.59663452e-13  2.40288961e-14 -2.53062000e-14  1.86862532e-14
      -1.30547626e-14  9.16599097e-14 -1.53273340e-14  8.48933193e-15
      -1.66659296e-14  3.64657636e-15 -1.00880330e-14  5.72269587e-15
      -8.74284790e-15  6.31426206e-14 -8.55821963e-15  5.71160948e-15
      -4.98626678e-15  1.60499110e-15 -7.13538152e-15  1.59872141e-15
      -1.05451984e-15  3.88327658e-15 -7.45396610e-16  1.54129501e-15
      -1.42716333e-15  2.03523556e-15 -1.62135920e-14  2.34035401e-15
      -1.25629997e-15  1.65799399e-15 -3.66013651e-16  1.04009651e-15
      -3.58374953e-16  3.39270441e-16 -1.98825329e-15  2.91038197e-16
      -2.68564223e-16  2.24822296e-16 -1.32416417e-16  8.53547975e-16
      -1.66839022e-16  1.40086064e-16 -4.32647611e-16  1.26481451e-16
      -5.02878878e-16  4.42507115e-16 -8.26070603e-16  6.30066519e-15
      -8.31231475e-16  4.80159890e-16 -4.61849741e-16  1.18617125e-16
      -4.18111099e-16  1.03460856e-16 -6.79943025e-17  2.90415292e-16
      -4.70447572e-17  6.01213336e-17 -4.66793179e-17  4.27932934e-17
      -3.21794862e-16  5.06977858e-17 -2.73215943e-17  4.57276217e-17
      -9.83579305e-18  2.63660945e-17 -1.20622899e-17  1.55587062e-17
      -1.07468594e-16  1.52052983e-17 -1.16513854e-17  1.01876511e-17
      -4.29803168e-18  2.31319687e-17 -5.09154144e-18  4.45798611e-18
      -1.65404073e-17  4.13366624e-18 -1.38111861e-17  1.41651368e-17
      -2.44403604e-17  1.92764231e-16 -2.63578148e-17  1.42083988e-17
      -1.62334816e-17  3.68187305e-18 -1.10431565e-17  3.25856649e-18
      -2.54355720e-18  1.31365997e-17 -1.96441562e-18  1.94169138e-18
      -1.47276050e-18  9.20297380e-19 -6.30802101e-18  1.12642070e-18
      -6.74025066e-19  1.53372257e-18 -3.63289335e-19  1.12616046e-18
      -7.68529688e-19  1.31859730e-18 -9.89385371e-18  1.33721744e-18
      -8.49681366e-19  7.74441894e-19 -2.28941800e-19  9.38827590e-19
      -2.19995073e-19  1.42954284e-19 -5.59845669e-19  1.00187062e-19
      -1.67733818e-19  1.45108281e-19 -1.78393939e-19  1.45681931e-18
      -2.19863898e-19  1.23177817e-19 -1.91566890e-19  4.93680415e-20
      -1.75484642e-19  8.14763106e-20 -1.26554251e-19  8.02015279e-19
      -1.15769076e-19  1.45818000e-19 -1.85187602e-19  1.64607736e-19
      -1.09481862e-18  2.35817253e-19 -3.30181890e-19  1.24343108e-18
      -3.96394371e-19  1.70310635e-18 -1.65360042e-18  3.06137341e-18
      -2.33714696e-17  3.05680066e-18 -1.67868151e-18  1.68271158e-18
      -4.01034703e-19  1.29583022e-18 -3.34153681e-19  2.26554878e-19
      -1.02032423e-18  1.56545799e-19 -1.75112983e-19  1.30035642e-19
      -9.96139960e-20  7.14658285e-19 -1.15905945e-19  6.27225311e-20
      -1.14608467e-19  2.45292046e-20 -6.55704655e-20  3.37757259e-20
      -4.80936167e-20  3.41618040e-19 -4.69098216e-20  3.26958426e-20
      -2.81846323e-20  9.77517419e-21 -4.62503430e-20  1.01939988e-20
      -7.10124896e-21  2.57083371e-20 -5.31691383e-21  1.30472453e-20
      -1.26386425e-20  1.95280583e-20 -1.54570838e-19  2.17185194e-20
      -1.15985936e-20  1.43944304e-20 -3.18441459e-21  9.15450085e-21
      -2.94684238e-21  2.55051166e-21 -1.42258708e-20  2.09206598e-21
      -1.94593935e-21  1.52962366e-21 -8.78022533e-22  5.75592781e-21
      -1.08077421e-21  7.41008048e-22 -1.99576685e-21  5.29739174e-22
      -1.90786037e-21  1.54155406e-21 -2.83581018e-21  2.16390370e-20
      -2.88756196e-21  1.73229737e-21 -1.63446003e-21  4.42871694e-22
      -1.65635836e-21  4.01691190e-22 -2.61767432e-22  1.08363309e-21
      -1.82160172e-22  2.55963823e-22 -2.06327094e-22  2.12061360e-22
      -1.63605612e-21  2.53372297e-22 -1.36896091e-22  2.18118213e-22
      -4.77337856e-23  1.32213409e-22 -5.76585258e-23  7.26009216e-23
      -4.88821494e-22  6.98992641e-23 -5.95535584e-23  5.66019977e-23
      -3.13274686e-23  1.87767072e-22 -4.17856573e-23  4.83925917e-23
      -1.86383513e-22  5.31780375e-23 -2.07273466e-22  2.12443864e-22
      -3.81106169e-22  2.96555414e-21 -3.96463575e-22  2.13910330e-22
      -2.31077321e-22  5.30278081e-23 -1.62624004e-22  4.52906247e-23
      -3.31837002e-23  1.62117588e-22 -2.43511389e-23  2.50026444e-23
      -1.86265429e-23  1.24452501e-23 -8.69064702e-23  1.49322881e-23
      -8.49006744e-24  1.76198937e-23 -3.96031297e-24  1.13881553e-23
      -6.94009774e-24  1.11467868e-23 -8.20009943e-23  1.11190013e-23
      -7.29085557e-24  6.47795987e-24 -2.01735040e-24  8.71381120e-24
      -1.98930778e-24  1.29832838e-24 -4.89958786e-24  9.13777266e-25
      -1.73361454e-24  1.56823314e-24 -2.12781362e-24  1.70421110e-23]]





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  2.968 seconds)


.. _sphx_glr_download_matplotlib_plot_complex_KAM.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_complex_KAM.py <plot_complex_KAM.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_complex_KAM.ipynb <plot_complex_KAM.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_