Streamplot for Uneven Curvilinear Grid

My problem is that I have a curvilinear grid with some velocity data and I'm
trying to so streamplot
of it. I read at documentation that streamplot do not plot uneven grids and
so I googled it and found this website:
http://www.flannaghan.com/2013/02/23/interpolation
<http://www.flannaghan.com/2013/02/23/interpolation> that someone solved
the uneven problem with interpolation, but my problem is a quite harder. My
grid is not just uneven, it is curvilinear. This is really important to me
and I would be very thankful for any help.
The example code and the result:

import numpy as np
import matplotlib.pyplot as plt

xx = np.array([[-32.77352506, -32.50517324, -32.30341846, -32.12060867,
-31.99103968],
   [-32.88670112, -32.63078693, -32.42892793, -32.2527705 , -32.11911059],
   [-32.99884749, -32.75419286, -32.55377179, -32.38220417,-32.24664094],
   [-33.10888993, -32.87495033, -32.67707405, -32.50885765,-32.37311971],
   [-33.2179889 , -32.99317728, -32.79848554, -32.63304009,-32.49815164],
   [-33.32651265, -33.10917094, -32.91791567, -32.75496914,-32.62146004],
   [-33.43449219, -33.22321261, -33.03537769, -32.87477271,-32.74286757],
   [-33.54184645, -33.33551502, -33.15092328, -32.99252837,-32.86227065],
   [-33.64847256, -33.44622558, -33.26461466, -33.1082882 ,-32.97961644],
   [-33.7542787 , -33.55544297, -33.37651245, -33.22209182,-33.09488502],
   [-33.85919362, -33.66323316, -33.48667092, -33.33397251,-33.20807667],
   [-33.96316738, -33.76964127, -33.59513666, -33.44395994,-33.31920308],
   [-34.06616899, -33.87469962, -33.70194888, -33.55208114,-33.42828168],
   [-34.16818354, -33.97843289, -33.80714029, -33.6583608 , -33.5353318 ],
   [-34.26920936, -34.08086103, -33.91073804, -33.76282129,-33.64037232],
   [-34.36925566, -34.18200076, -34.01276449, -33.86548266,-33.74342012],
   [-34.46834041, -34.28186594, -34.11323791, -33.96636282,-33.84448915],
   [-34.56648851, -34.38046701, -34.21217281, -34.06547784,-33.94358994],
   [-34.66372971, -34.4778096 , -34.30958029, -34.16284263, -34.0407292 ],
   [-34.76009619, -34.57389229, -34.40546833, -34.2584719 ,-34.13590974],
   [-34.85561889, -34.66870332, -34.49984222, -34.35238178,-34.22913045],
   [-34.95032165, -34.76221629, -34.59270529, -34.44459209,-34.32038648],
   [-35.04421102, -34.85438466, -34.6840602 , -34.5351297 ,-34.40966975],
   [-35.13725786, -34.94513595, -34.77391107, -34.62403315,-34.49697031],
   [-35.22936336, -35.03436723, -34.86226647, -34.7113589 , -34.5822793 ],
   [-35.3202956 , -35.12194712, -34.9491432 , -34.79718943,-34.66559567],
   [-35.40957149, -35.20773648, -35.03457067, -34.88164276,-34.74693998],
   [-35.49624617, -35.29165455, -35.11859869, -34.96488179,-34.82637986],
   [-35.57858891, -35.3738341 , -35.20134195, -35.04711944,-34.90406862],
   [-35.65407127, -35.45484625, -35.28327484, -35.12861303,-34.98028311]])

yy = np.array([[-11.3529916 , -10.83017948, -10.36062676,
-9.85499224,-9.36742115],
   [-11.24914312, -10.77486528, -10.30767657, -9.81790781,-9.33347811],
   [-11.16896123, -10.71827884, -10.25654788, -9.77873607,-9.29985941],
   [-11.09864806, -10.66157581, -10.20688907, -9.7389486 ,-9.26669158],
   [-11.03379175, -10.60554773, -10.15836065, -9.69919353, -9.2340536 ],
   [-10.97234269, -10.55056628, -10.11076275, -9.65973621,-9.20197376],
   [-10.91318741, -10.49672964, -10.06398502, -9.62068888,-9.17044015],
   [-10.85567682, -10.44399733, -10.01795592, -9.58209354,-9.13941538],
   [-10.79941292, -10.39227109, -9.97261586, -9.54395471,-9.10884902],
   [-10.74413933, -10.3414354 , -9.92790608, -9.50625469,-9.07868586],
   [-10.68968138, -10.29137538, -9.88376528, -9.46896173,-9.04887037],
   [-10.63591212, -10.24198327, -9.84012944, -9.43203502,-9.01934878],
   [-10.58273238, -10.19315956, -9.79693259, -9.39542787,-8.99006955],
   [-10.53005851, -10.14481189, -9.75410767, -9.35908973,-8.96098324],
   [-10.47781454, -10.09685326, -9.71158727, -9.32296761,-8.93204187],
   [-10.42592671, -10.04920008, -9.66930413, -9.28700687,-8.90319822],
   [-10.37431922, -10.00177041, -9.62719161, -9.25115173, -8.874405 ],
   [-10.32291042, -9.95448254, -9.5851842 , -9.21534553,-8.84561388],
   [-10.27160885, -9.90725399, -9.54321824, -9.17953081, -8.8167744 ],
   [-10.22030865, -9.86000117, -9.50123304, -9.1436493 ,-8.78783251],
   [-10.16888358, -9.81263985, -9.45917264, -9.10764179,-8.75872859],
   [-10.11717908, -9.7650871 , -9.41698825, -9.07144794,-8.72939466],
   [-10.06500151, -9.71726547, -9.37464171, -9.03500603,-8.69975035],
   [-10.01210356, -9.66911062, -9.33211024, -8.99825263,-8.66969694],
   [ -9.95816574, -9.62058406, -9.28939255, -8.96112225, -8.639109 ],
   [ -9.90277604, -9.57169217, -9.24651752, -8.92354679,-8.60782312],
   [ -9.84541584, -9.52250952, -9.2035585 , -8.88545441,-8.57562469],
   [ -9.78546516, -9.4731919 , -9.1606645 , -8.84676681,-8.54223813],
   [ -9.72217224, -9.42392909, -9.11814094, -8.80739381,-8.50733329],
   [ -9.65407127, -9.37474785, -9.07654968, -8.76722606,-8.47056622]])

u = 3*np.cos(xx)*(-3)*np.sin(yy)
v = 2*np.sin(xx)*3*np.cos(yy)
speed = np.sqrt((u**2)+(v**2))

plt.ion()
fig,(ax1,ax2) = plt.subplots(1,2,figsize=(14,8))

ax1.contourf(xx,yy,speed)
ax1.plot(xx,yy,'-k',alpha=0.3)
ax1.plot(xx.T,yy.T,'-k',alpha=0.3)
ax1.quiver(xx,yy,u,v)

ax2.contourf(xx,yy,speed)
ax2.plot(xx,yy,'-k',alpha=0.3)
ax2.plot(xx.T,yy.T,'-k',alpha=0.3)
ax2.streamplot(xx,yy,u,v)

<http://matplotlib.1069221.n5.nabble.com/file/n43795/error.png>

···

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