Hi,
My name is Francisco and I'm a python and ipython user. Today I was
coding in python a little bit, in particular with the function quiver,
in matplotlib. I got an error when I tried to use the option
angles='xy'
A problem related with the broadcasting arose. It was really strange
because if I used another arrays it worked. Anyways, when I continued
trying some options another error arose, Ipython crashes and a report
file was created. I was wondering if you could help me with that, or
tell me where can I ask for help, honestly I don't know what else I can
do for now. The file is attached.
Thank you in advance,
Regards,
Francisco
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***************************************************************************
IPython post-mortem report
{'commit_hash': '8ff8693',
'commit_source': 'installation',
'default_encoding': 'UTF-8',
'ipython_path': '/home/chinoley/anaconda3/lib/python3.5/site-packages/IPython',
'ipython_version': '4.0.3',
'os_name': 'posix',
'platform': 'Linux-3.19.0-32-generic-x86_64-with-debian-jessie-sid',
'sys_executable': '/home/chinoley/anaconda3/bin/python3',
'sys_platform': 'linux',
'sys_version': '3.5.1 |Anaconda 2.5.0 (64-bit)| (default, Dec 7 2015, '
'11:16:01) \n'
'[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]'}
***************************************************************************
***************************************************************************
Crash traceback:
---------------------------------------------------------------------------
---------------------------------------------------------------------------
ValueError Python 3.5.1: /home/chinoley/anaconda3/bin/python3
Mon Apr 4 20:31:55 2016
A problem occurred executing Python code. Here is the sequence of function
calls leading up to the error, with the most recent (innermost) call last.
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/backends/backend_qt5agg.py in __draw_idle_agg(self=<matplotlib.backends.backend_qt4agg.FigureCanvasQTAgg object>, *args=())
161 def draw_idle(self):
162 """
163 Queue redraw of the Agg buffer and request Qt paintEvent.
164 """
165 # The Agg draw needs to be handled by the same thread matplotlib
166 # modifies the scene graph from. Post Agg draw request to the
167 # current event loop in order to ensure thread affinity and to
168 # accumulate multiple draw requests from event handling.
169 # TODO: queued signal connection might be safer than singleShot
170 if not self._agg_draw_pending:
171 self._agg_draw_pending = True
172 QtCore.QTimer.singleShot(0, self.__draw_idle_agg)
173
174 def __draw_idle_agg(self, *args):
175 try:
--> 176 FigureCanvasAgg.draw(self)
global FigureCanvasAgg.draw = <function FigureCanvasAgg.draw at 0x7f6a5e2ded90>
self = <matplotlib.backends.backend_qt4agg.FigureCanvasQTAgg object at 0x7f6a3d6c3048>
177 self.update()
178 finally:
179 self._agg_draw_pending = False
180
181 def blit(self, bbox=None):
182 """
183 Blit the region in bbox
184 """
185 # If bbox is None, blit the entire canvas. Otherwise
186 # blit only the area defined by the bbox.
187 if bbox is None and self.figure:
188 bbox = self.figure.bbox
189
190 self.blitbox = bbox
191 l, b, w, h = bbox.bounds
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/backends/backend_agg.py in draw(self=<matplotlib.backends.backend_qt4agg.FigureCanvasQTAgg object>)
459 def restore_region(self, region, bbox=None, xy=None):
460 renderer = self.get_renderer()
461 return renderer.restore_region(region, bbox, xy)
462
463 def draw(self):
464 """
465 Draw the figure using the renderer
466 """
467 if __debug__: verbose.report('FigureCanvasAgg.draw', 'debug-annoying')
468
469 self.renderer = self.get_renderer(cleared=True)
470 # acquire a lock on the shared font cache
471 RendererAgg.lock.acquire()
472
473 try:
--> 474 self.figure.draw(self.renderer)
self.figure.draw = <bound method allow_rasterization.<locals>.draw_wrapper of <matplotlib.figure.Figure object at 0x7f6a3d852c88>>
self.renderer = <matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>
475 finally:
476 RendererAgg.lock.release()
477
478 def get_renderer(self, cleared=False):
479 l, b, w, h = self.figure.bbox.bounds
480 key = w, h, self.figure.dpi
481 try: self._lastKey, self.renderer
482 except AttributeError: need_new_renderer = True
483 else: need_new_renderer = (self._lastKey != key)
484
485 if need_new_renderer:
486 self.renderer = RendererAgg(w, h, self.figure.dpi)
487 self._lastKey = key
488 elif cleared:
489 self.renderer.clear()
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/artist.py in draw_wrapper(artist=<matplotlib.figure.Figure object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>, *args=(), **kwargs={})
46
47 if artist.get_agg_filter() is not None:
48 renderer.start_filter()
49
50 def after(artist, renderer):
51
52 if artist.get_agg_filter() is not None:
53 renderer.stop_filter(artist.get_agg_filter())
54
55 if artist.get_rasterized():
56 renderer.stop_rasterizing()
57
58 # the axes class has a second argument inframe for its draw method.
59 def draw_wrapper(artist, renderer, *args, **kwargs):
60 before(artist, renderer)
---> 61 draw(artist, renderer, *args, **kwargs)
global draw = undefined
artist = <matplotlib.figure.Figure object at 0x7f6a3d852c88>
renderer = <matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>
args = ()
kwargs = {}
62 after(artist, renderer)
63
64 # "safe wrapping" to exactly replicate anything we haven't overridden above
65 draw_wrapper.__name__ = draw.__name__
66 draw_wrapper.__dict__ = draw.__dict__
67 draw_wrapper.__doc__ = draw.__doc__
68 draw_wrapper._supports_rasterization = True
69 return draw_wrapper
70
71
72 def _stale_axes_callback(self, val):
73 if self.axes:
74 self.axes.stale = val
75
76
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/figure.py in draw(self=<matplotlib.figure.Figure object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>)
1144
1145 # render the axes
1146 for a in self.axes:
1147 dsu.append((a.get_zorder(), a, a.draw, [renderer]))
1148
1149 # render the figure text
1150 for a in self.texts:
1151 dsu.append((a.get_zorder(), a, a.draw, [renderer]))
1152
1153 for a in self.legends:
1154 dsu.append((a.get_zorder(), a, a.draw, [renderer]))
1155
1156 dsu = [row for row in dsu if not row[1].get_animated()]
1157 dsu.sort(key=itemgetter(0))
1158 for zorder, a, func, args in dsu:
-> 1159 func(*args)
func = <bound method allow_rasterization.<locals>.draw_wrapper of <matplotlib.axes._subplots.AxesSubplot object at 0x7f6a3d8382e8>>
args = [<matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>]
1160
1161 renderer.close_group('figure')
1162 self.stale = False
1163
1164 self._cachedRenderer = renderer
1165 self.canvas.draw_event(renderer)
1166
1167 def draw_artist(self, a):
1168 """
1169 draw :class:`matplotlib.artist.Artist` instance *a* only --
1170 this is available only after the figure is drawn
1171 """
1172 if self._cachedRenderer is None:
1173 msg = ('draw_artist can only be used after an initial draw which'
1174 ' caches the render')
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/artist.py in draw_wrapper(artist=<matplotlib.axes._subplots.AxesSubplot object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>, *args=(), **kwargs={})
46
47 if artist.get_agg_filter() is not None:
48 renderer.start_filter()
49
50 def after(artist, renderer):
51
52 if artist.get_agg_filter() is not None:
53 renderer.stop_filter(artist.get_agg_filter())
54
55 if artist.get_rasterized():
56 renderer.stop_rasterizing()
57
58 # the axes class has a second argument inframe for its draw method.
59 def draw_wrapper(artist, renderer, *args, **kwargs):
60 before(artist, renderer)
---> 61 draw(artist, renderer, *args, **kwargs)
global draw = undefined
artist = <matplotlib.axes._subplots.AxesSubplot object at 0x7f6a3d8382e8>
renderer = <matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>
args = ()
kwargs = {}
62 after(artist, renderer)
63
64 # "safe wrapping" to exactly replicate anything we haven't overridden above
65 draw_wrapper.__name__ = draw.__name__
66 draw_wrapper.__dict__ = draw.__dict__
67 draw_wrapper.__doc__ = draw.__doc__
68 draw_wrapper._supports_rasterization = True
69 return draw_wrapper
70
71
72 def _stale_axes_callback(self, val):
73 if self.axes:
74 self.axes.stale = val
75
76
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/axes/_base.py in draw(self=<matplotlib.axes._subplots.AxesSubplot object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>, inframe=False)
2309 gc = renderer.new_gc()
2310 gc.set_clip_rectangle(self.bbox)
2311 gc.set_clip_path(mtransforms.TransformedPath(
2312 self.patch.get_path(),
2313 self.patch.get_transform()))
2314
2315 renderer.draw_image(gc, round(l), round(b), im)
2316 gc.restore()
2317
2318 if dsu_rasterized:
2319 for zorder, a in dsu_rasterized:
2320 a.draw(renderer)
2321 renderer.stop_rasterizing()
2322
2323 for zorder, a in dsu:
-> 2324 a.draw(renderer)
a.draw = <bound method allow_rasterization.<locals>.draw_wrapper of <matplotlib.quiver.Quiver object at 0x7f6a3d5374e0>>
renderer = <matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>
2325
2326 renderer.close_group('axes')
2327 self._cachedRenderer = renderer
2328 self.stale = False
2329
2330 def draw_artist(self, a):
2331 """
2332 This method can only be used after an initial draw which
2333 caches the renderer. It is used to efficiently update Axes
2334 data (axis ticks, labels, etc are not updated)
2335 """
2336 if self._cachedRenderer is None:
2337 msg = ('draw_artist can only be used after an initial draw which'
2338 ' caches the render')
2339 raise AttributeError(msg)
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/artist.py in draw_wrapper(artist=<matplotlib.quiver.Quiver object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>, *args=(), **kwargs={})
46
47 if artist.get_agg_filter() is not None:
48 renderer.start_filter()
49
50 def after(artist, renderer):
51
52 if artist.get_agg_filter() is not None:
53 renderer.stop_filter(artist.get_agg_filter())
54
55 if artist.get_rasterized():
56 renderer.stop_rasterizing()
57
58 # the axes class has a second argument inframe for its draw method.
59 def draw_wrapper(artist, renderer, *args, **kwargs):
60 before(artist, renderer)
---> 61 draw(artist, renderer, *args, **kwargs)
global draw = undefined
artist = <matplotlib.quiver.Quiver object at 0x7f6a3d5374e0>
renderer = <matplotlib.backends.backend_agg.RendererAgg object at 0x7f6a3d85d668>
args = ()
kwargs = {}
62 after(artist, renderer)
63
64 # "safe wrapping" to exactly replicate anything we haven't overridden above
65 draw_wrapper.__name__ = draw.__name__
66 draw_wrapper.__dict__ = draw.__dict__
67 draw_wrapper.__doc__ = draw.__doc__
68 draw_wrapper._supports_rasterization = True
69 return draw_wrapper
70
71
72 def _stale_axes_callback(self, val):
73 if self.axes:
74 self.axes.stale = val
75
76
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/quiver.py in draw(self=<matplotlib.quiver.Quiver object>, renderer=<matplotlib.backends.backend_agg.RendererAgg object>)
512
513 self._initialized = True
514
515 def get_datalim(self, transData):
516 trans = self.get_transform()
517 transOffset = self.get_offset_transform()
518 full_transform = (trans - transData) + (transOffset - transData)
519 XY = full_transform.transform(self.XY)
520 bbox = transforms.Bbox.null()
521 bbox.update_from_data_xy(XY, ignore=True)
522 return bbox
523
524 @allow_rasterization
525 def draw(self, renderer):
526 self._init()
--> 527 verts = self._make_verts(self.U, self.V)
verts = undefined
self._make_verts = <bound method Quiver._make_verts of <matplotlib.quiver.Quiver object at 0x7f6a3d5374e0>>
self.U = array([ 0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0.26315789, 0.26315789, 0.26315789, 0.26315789, 0.26315789,
0.26315789, 0.26315789, 0.26315789, 0.26315789, 0.26315789,
0.26315789, 0.26315789, 0.26315789, 0.26315789, 0.26315789,
0.26315789, 0.26315789, 0.26315789, 0.26315789, 0.26315789,
0.52631579, 0.52631579, 0.52631579, 0.52631579, 0.52631579,
0.52631579, 0.52631579, 0.52631579, 0.52631579, 0.52631579,
0.52631579, 0.52631579, 0.52631579, 0.52631579, 0.52631579,
0.52631579, 0.52631579, 0.52631579, 0.52631579, 0.52631579,
0.78947368, 0.78947368, 0.78947368, 0.78947368, 0.78947368,
0.78947368, 0.78947368, 0.78947368, 0.78947368, 0.78947368,
0.78947368, 0.78947368, 0.78947368, 0.78947368, 0.78947368,
0.78947368, 0.78947368, 0.78947368, 0.78947368, 0.78947368,
1.05263158, 1.05263158, 1.05263158, 1.05263158, 1.05263158,
1.05263158, 1.05263158, 1.05263158, 1.05263158, 1.05263158,
1.05263158, 1.05263158, 1.05263158, 1.05263158, 1.05263158,
1.05263158, 1.05263158, 1.05263158, 1.05263158, 1.05263158,
1.31578947, 1.31578947, 1.31578947, 1.31578947, 1.31578947,
1.31578947, 1.31578947, 1.31578947, 1.31578947, 1.31578947,
1.31578947, 1.31578947, 1.31578947, 1.31578947, 1.31578947,
1.31578947, 1.31578947, 1.31578947, 1.31578947, 1.31578947,
1.57894737, 1.57894737, 1.57894737, 1.57894737, 1.57894737,
1.57894737, 1.57894737, 1.57894737, 1.57894737, 1.57894737,
1.57894737, 1.57894737, 1.57894737, 1.57894737, 1.57894737,
1.57894737, 1.57894737, 1.57894737, 1.57894737, 1.57894737,
1.84210526, 1.84210526, 1.84210526, 1.84210526, 1.84210526,
1.84210526, 1.84210526, 1.84210526, 1.84210526, 1.84210526,
1.84210526, 1.84210526, 1.84210526, 1.84210526, 1.84210526,
1.84210526, 1.84210526, 1.84210526, 1.84210526, 1.84210526,
2.10526316, 2.10526316, 2.10526316, 2.10526316, 2.10526316,
2.10526316, 2.10526316, 2.10526316, 2.10526316, 2.10526316,
2.10526316, 2.10526316, 2.10526316, 2.10526316, 2.10526316,
2.10526316, 2.10526316, 2.10526316, 2.10526316, 2.10526316,
2.36842105, 2.36842105, 2.36842105, 2.36842105, 2.36842105,
2.36842105, 2.36842105, 2.36842105, 2.36842105, 2.36842105,
2.36842105, 2.36842105, 2.36842105, 2.36842105, 2.36842105,
2.36842105, 2.36842105, 2.36842105, 2.36842105, 2.36842105,
2.63157895, 2.63157895, 2.63157895, 2.63157895, 2.63157895,
2.63157895, 2.63157895, 2.63157895, 2.63157895, 2.63157895,
2.63157895, 2.63157895, 2.63157895, 2.63157895, 2.63157895,
2.63157895, 2.63157895, 2.63157895, 2.63157895, 2.63157895,
2.89473684, 2.89473684, 2.89473684, 2.89473684, 2.89473684,
2.89473684, 2.89473684, 2.89473684, 2.89473684, 2.89473684,
2.89473684, 2.89473684, 2.89473684, 2.89473684, 2.89473684,
2.89473684, 2.89473684, 2.89473684, 2.89473684, 2.89473684,
3.15789474, 3.15789474, 3.15789474, 3.15789474, 3.15789474,
3.15789474, 3.15789474, 3.15789474, 3.15789474, 3.15789474,
3.15789474, 3.15789474, 3.15789474, 3.15789474, 3.15789474,
3.15789474, 3.15789474, 3.15789474, 3.15789474, 3.15789474,
3.42105263, 3.42105263, 3.42105263, 3.42105263, 3.42105263,
3.42105263, 3.42105263, 3.42105263, 3.42105263, 3.42105263,
3.42105263, 3.42105263, 3.42105263, 3.42105263, 3.42105263,
3.42105263, 3.42105263, 3.42105263, 3.42105263, 3.42105263,
3.68421053, 3.68421053, 3.68421053, 3.68421053, 3.68421053,
3.68421053, 3.68421053, 3.68421053, 3.68421053, 3.68421053,
3.68421053, 3.68421053, 3.68421053, 3.68421053, 3.68421053,
3.68421053, 3.68421053, 3.68421053, 3.68421053, 3.68421053,
3.94736842, 3.94736842, 3.94736842, 3.94736842, 3.94736842,
3.94736842, 3.94736842, 3.94736842, 3.94736842, 3.94736842,
3.94736842, 3.94736842, 3.94736842, 3.94736842, 3.94736842,
3.94736842, 3.94736842, 3.94736842, 3.94736842, 3.94736842,
4.21052632, 4.21052632, 4.21052632, 4.21052632, 4.21052632,
4.21052632, 4.21052632, 4.21052632, 4.21052632, 4.21052632,
4.21052632, 4.21052632, 4.21052632, 4.21052632, 4.21052632,
4.21052632, 4.21052632, 4.21052632, 4.21052632, 4.21052632,
4.47368421, 4.47368421, 4.47368421, 4.47368421, 4.47368421,
4.47368421, 4.47368421, 4.47368421, 4.47368421, 4.47368421,
4.47368421, 4.47368421, 4.47368421, 4.47368421, 4.47368421,
4.47368421, 4.47368421, 4.47368421, 4.47368421, 4.47368421,
4.73684211, 4.73684211, 4.73684211, 4.73684211, 4.73684211,
4.73684211, 4.73684211, 4.73684211, 4.73684211, 4.73684211,
4.73684211, 4.73684211, 4.73684211, 4.73684211, 4.73684211,
4.73684211, 4.73684211, 4.73684211, 4.73684211, 4.73684211,
5. , 5. , 5. , 5. , 5. ,
5. , 5. , 5. , 5. , 5. ,
5. , 5. , 5. , 5. , 5. ,
5. , 5. , 5. , 5. , 5. ])
self.V = array([ 0. , 0.26315789, 0.52631579, 0.78947368, 1.05263158,
1.31578947, 1.57894737, 1.84210526, 2.10526316, 2.36842105,
2.63157895, 2.89473684, 3.15789474, 3.42105263, 3.68421053,
3.94736842, 4.21052632, 4.47368421, 4.73684211, 5. ,
0.18421053, 0.44736842, 0.71052632, 0.97368421, 1.23684211,
1.5 , 1.76315789, 2.02631579, 2.28947368, 2.55263158,
2.81578947, 3.07894737, 3.34210526, 3.60526316, 3.86842105,
4.13157895, 4.39473684, 4.65789474, 4.92105263, 5.18421053,
0.36842105, 0.63157895, 0.89473684, 1.15789474, 1.42105263,
1.68421053, 1.94736842, 2.21052632, 2.47368421, 2.73684211,
3. , 3.26315789, 3.52631579, 3.78947368, 4.05263158,
4.31578947, 4.57894737, 4.84210526, 5.10526316, 5.36842105,
0.55263158, 0.81578947, 1.07894737, 1.34210526, 1.60526316,
1.86842105, 2.13157895, 2.39473684, 2.65789474, 2.92105263,
3.18421053, 3.44736842, 3.71052632, 3.97368421, 4.23684211,
4.5 , 4.76315789, 5.02631579, 5.28947368, 5.55263158,
0.73684211, 1. , 1.26315789, 1.52631579, 1.78947368,
2.05263158, 2.31578947, 2.57894737, 2.84210526, 3.10526316,
3.36842105, 3.63157895, 3.89473684, 4.15789474, 4.42105263,
4.68421053, 4.94736842, 5.21052632, 5.47368421, 5.73684211,
0.92105263, 1.18421053, 1.44736842, 1.71052632, 1.97368421,
2.23684211, 2.5 , 2.76315789, 3.02631579, 3.28947368,
3.55263158, 3.81578947, 4.07894737, 4.34210526, 4.60526316,
4.86842105, 5.13157895, 5.39473684, 5.65789474, 5.92105263,
1.10526316, 1.36842105, 1.63157895, 1.89473684, 2.15789474,
2.42105263, 2.68421053, 2.94736842, 3.21052632, 3.47368421,
3.73684211, 4. , 4.26315789, 4.52631579, 4.78947368,
5.05263158, 5.31578947, 5.57894737, 5.84210526, 6.10526316,
1.28947368, 1.55263158, 1.81578947, 2.07894737, 2.34210526,
2.60526316, 2.86842105, 3.13157895, 3.39473684, 3.65789474,
3.92105263, 4.18421053, 4.44736842, 4.71052632, 4.97368421,
5.23684211, 5.5 , 5.76315789, 6.02631579, 6.28947368,
1.47368421, 1.73684211, 2. , 2.26315789, 2.52631579,
2.78947368, 3.05263158, 3.31578947, 3.57894737, 3.84210526,
4.10526316, 4.36842105, 4.63157895, 4.89473684, 5.15789474,
5.42105263, 5.68421053, 5.94736842, 6.21052632, 6.47368421,
1.65789474, 1.92105263, 2.18421053, 2.44736842, 2.71052632,
2.97368421, 3.23684211, 3.5 , 3.76315789, 4.02631579,
4.28947368, 4.55263158, 4.81578947, 5.07894737, 5.34210526,
5.60526316, 5.86842105, 6.13157895, 6.39473684, 6.65789474,
1.84210526, 2.10526316, 2.36842105, 2.63157895, 2.89473684,
3.15789474, 3.42105263, 3.68421053, 3.94736842, 4.21052632,
4.47368421, 4.73684211, 5. , 5.26315789, 5.52631579,
5.78947368, 6.05263158, 6.31578947, 6.57894737, 6.84210526,
2.02631579, 2.28947368, 2.55263158, 2.81578947, 3.07894737,
3.34210526, 3.60526316, 3.86842105, 4.13157895, 4.39473684,
4.65789474, 4.92105263, 5.18421053, 5.44736842, 5.71052632,
5.97368421, 6.23684211, 6.5 , 6.76315789, 7.02631579,
2.21052632, 2.47368421, 2.73684211, 3. , 3.26315789,
3.52631579, 3.78947368, 4.05263158, 4.31578947, 4.57894737,
4.84210526, 5.10526316, 5.36842105, 5.63157895, 5.89473684,
6.15789474, 6.42105263, 6.68421053, 6.94736842, 7.21052632,
2.39473684, 2.65789474, 2.92105263, 3.18421053, 3.44736842,
3.71052632, 3.97368421, 4.23684211, 4.5 , 4.76315789,
5.02631579, 5.28947368, 5.55263158, 5.81578947, 6.07894737,
6.34210526, 6.60526316, 6.86842105, 7.13157895, 7.39473684,
2.57894737, 2.84210526, 3.10526316, 3.36842105, 3.63157895,
3.89473684, 4.15789474, 4.42105263, 4.68421053, 4.94736842,
5.21052632, 5.47368421, 5.73684211, 6. , 6.26315789,
6.52631579, 6.78947368, 7.05263158, 7.31578947, 7.57894737,
2.76315789, 3.02631579, 3.28947368, 3.55263158, 3.81578947,
4.07894737, 4.34210526, 4.60526316, 4.86842105, 5.13157895,
5.39473684, 5.65789474, 5.92105263, 6.18421053, 6.44736842,
6.71052632, 6.97368421, 7.23684211, 7.5 , 7.76315789,
2.94736842, 3.21052632, 3.47368421, 3.73684211, 4. ,
4.26315789, 4.52631579, 4.78947368, 5.05263158, 5.31578947,
5.57894737, 5.84210526, 6.10526316, 6.36842105, 6.63157895,
6.89473684, 7.15789474, 7.42105263, 7.68421053, 7.94736842,
3.13157895, 3.39473684, 3.65789474, 3.92105263, 4.18421053,
4.44736842, 4.71052632, 4.97368421, 5.23684211, 5.5 ,
5.76315789, 6.02631579, 6.28947368, 6.55263158, 6.81578947,
7.07894737, 7.34210526, 7.60526316, 7.86842105, 8.13157895,
3.31578947, 3.57894737, 3.84210526, 4.10526316, 4.36842105,
4.63157895, 4.89473684, 5.15789474, 5.42105263, 5.68421053,
5.94736842, 6.21052632, 6.47368421, 6.73684211, 7. ,
7.26315789, 7.52631579, 7.78947368, 8.05263158, 8.31578947,
3.5 , 3.76315789, 4.02631579, 4.28947368, 4.55263158,
4.81578947, 5.07894737, 5.34210526, 5.60526316, 5.86842105,
6.13157895, 6.39473684, 6.65789474, 6.92105263, 7.18421053,
7.44736842, 7.71052632, 7.97368421, 8.23684211, 8.5 ])
528 self.set_verts(verts, closed=False)
529 self._new_UV = False
530 mcollections.PolyCollection.draw(self, renderer)
531 self.stale = False
532
533 def set_UVC(self, U, V, C=None):
534 # We need to ensure we have a copy, not a reference
535 # to an array that might change before draw().
536 U = ma.masked_invalid(U, copy=True).ravel()
537 V = ma.masked_invalid(V, copy=True).ravel()
538 mask = ma.mask_or(U.mask, V.mask, copy=False, shrink=True)
539 if C is not None:
540 C = ma.masked_invalid(C, copy=True).ravel()
541 mask = ma.mask_or(mask, C.mask, copy=False, shrink=True)
542 if mask is ma.nomask:
/home/chinoley/anaconda3/lib/python3.5/site-packages/matplotlib/quiver.py in _make_verts(self=<matplotlib.quiver.Quiver object>, U=array([ 0. , 0. , 0. , 0... , 5. , 5. , 5. ]), V=array([ 0. , 0.26315789, 0.52631579, 0...71052632, 7.97368421, 8.23684211, 8.5 ]))
642 widthu_per_lenu = dx / self._trans_scale
643 if self.scale is None:
644 self.scale = scale * widthu_per_lenu
645 length = a * (widthu_per_lenu / (self.scale * self.width))
646 X, Y = self._h_arrows(length)
647 if self.angles == 'xy':
648 theta = angles
649 elif self.angles == 'uv':
650 theta = np.angle(uv)
651 else:
652 # Make a copy to avoid changing the input array.
653 theta = ma.masked_invalid(self.angles, copy=True).filled(0)
654 theta = theta.ravel()
655 theta *= (np.pi / 180.0)
656 theta.shape = (theta.shape[0], 1) # for broadcasting
--> 657 xy = (X + Y * 1j) * np.exp(1j * theta) * self.width
xy = undefined
X = array([[ 5.00000000e-01, 2.50000000e-01, -2.50000000e-01, ...,
2.50000000e-01, 5.00000000e-01, 2.50000000e-01],
[ 0.00000000e+00, 2.42541838e+00, 0.00000000e+00, ...,
2.42541838e+00, 0.00000000e+00, 0.00000000e+00],
[ 0.00000000e+00, 9.08234295e+00, 6.58234295e+00, ...,
9.08234295e+00, 0.00000000e+00, 0.00000000e+00],
...,
[ 0.00000000e+00, 3.87231325e+02, 3.84731325e+02, ...,
3.87231325e+02, 0.00000000e+00, 0.00000000e+00],
[ 0.00000000e+00, 3.90840896e+02, 3.88340896e+02, ...,
3.90840896e+02, 0.00000000e+00, 0.00000000e+00],
[ 0.00000000e+00, 3.94533403e+02, 3.92033403e+02, ...,
3.94533403e+02, 0.00000000e+00, 0.00000000e+00]])
Y = array([[ 0.00000000e+00, 4.33012702e-01, 4.33012702e-01, ...,
-4.33012702e-01, -1.22464680e-16, 4.33012702e-01],
[ 4.85083677e-01, 4.85083677e-01, 1.45525103e+00, ...,
-4.85083677e-01, -4.85083677e-01, 4.85083677e-01],
[ 5.00000000e-01, 5.00000000e-01, 1.50000000e+00, ...,
-5.00000000e-01, -5.00000000e-01, 5.00000000e-01],
...,
[ 5.00000000e-01, 5.00000000e-01, 1.50000000e+00, ...,
-5.00000000e-01, -5.00000000e-01, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 1.50000000e+00, ...,
-5.00000000e-01, -5.00000000e-01, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 1.50000000e+00, ...,
-5.00000000e-01, -5.00000000e-01, 5.00000000e-01]])
global np.exp = <ufunc 'exp'>
theta = array([[ 0.00000000e+00],
[ 8.95159981e+00],
[ 1.79031996e+01],
[ 2.68547994e+01],
[ 3.58063992e+01],
[ 4.47579990e+01],
[ 5.37095988e+01],
[ 6.26611987e+01],
[ 7.16127985e+01],
[ 8.05643983e+01],
[ 8.95159981e+01],
[ 9.84675979e+01],
[ 1.07419198e+02],
[ 1.16370798e+02],
[ 1.25322397e+02],
[ 1.34273997e+02],
[ 1.43225597e+02],
[ 1.52177197e+02],
[ 1.61128797e+02],
[ 1.70080396e+02],
[ 1.79031996e+02],
[ 1.87983596e+02],
[ 1.96935196e+02],
[ 2.05886796e+02],
[ 2.14838395e+02],
[ 2.23789995e+02],
[ 2.32741595e+02],
[ 2.41693195e+02],
[ 2.50644795e+02],
[ 2.59596394e+02],
[ 2.68547994e+02],
[ 2.77499594e+02],
[ 2.86451194e+02],
[ 2.95402794e+02],
[ 3.04354393e+02],
[ 3.13305993e+02],
[ 3.22257593e+02],
[ 3.31209193e+02],
[ 3.40160793e+02],
[ 3.49112393e+02],
[ 3.58063992e+02],
[ 3.67015592e+02],
[ 3.75967192e+02],
[ 3.84918792e+02],
[ 3.93870392e+02],
[ 4.02821991e+02],
[ 3.69599136e-01],
[ 9.32119894e+00],
[ 1.82727988e+01],
[ 2.72243986e+01],
[ 3.61759984e+01],
[ 4.51275982e+01],
[ 5.40791980e+01],
[ 6.30307978e+01],
[ 7.19823976e+01],
[ 8.09339974e+01],
[ 8.98855972e+01],
[ 9.88371970e+01],
[ 1.07788797e+02],
[ 1.16740397e+02],
[ 1.25691996e+02],
[ 1.34643596e+02],
[ 1.43595196e+02],
[ 1.52546796e+02],
[ 1.61498396e+02],
[ 1.70449995e+02],
[ 1.79401595e+02],
[ 1.88353195e+02],
[ 1.97304795e+02],
[ 2.06256395e+02],
[ 2.15207995e+02],
[ 2.24159594e+02],
[ 2.33111194e+02],
[ 2.42062794e+02],
[ 2.51014394e+02],
[ 2.59965994e+02],
[ 2.68917593e+02],
[ 2.77869193e+02],
[ 2.86820793e+02],
[ 2.95772393e+02],
[ 3.04723993e+02],
[ 3.13675592e+02],
[ 3.22627192e+02],
[ 3.31578792e+02],
[ 3.40530392e+02],
[ 3.49481992e+02],
[ 3.58433591e+02],
[ 3.67385191e+02],
[ 3.76336791e+02],
[ 3.85288391e+02],
[ 3.94239991e+02],
[ 4.03191590e+02],
[ 7.39198271e-01],
[ 9.69079808e+00],
[ 1.86423979e+01],
[ 2.75939977e+01],
[ 3.65455975e+01],
[ 4.54971973e+01],
[ 5.44487971e+01],
[ 6.34003969e+01],
[ 7.23519967e+01],
[ 8.13035965e+01],
[ 9.02551964e+01],
[ 9.92067962e+01],
[ 1.08158396e+02],
[ 1.17109996e+02],
[ 1.26061596e+02],
[ 1.35013195e+02],
[ 1.43964795e+02],
[ 1.52916395e+02],
[ 1.61867995e+02],
[ 1.70819595e+02],
[ 1.79771194e+02],
[ 1.88722794e+02],
[ 1.97674394e+02],
[ 2.06625994e+02],
[ 2.15577594e+02],
[ 2.24529193e+02],
[ 2.33480793e+02],
[ 2.42432393e+02],
[ 2.51383993e+02],
[ 2.60335593e+02],
[ 2.69287193e+02],
[ 2.78238792e+02],
[ 2.87190392e+02],
[ 2.96141992e+02],
[ 3.05093592e+02],
[ 3.14045192e+02],
[ 3.22996791e+02],
[ 3.31948391e+02],
[ 3.40899991e+02],
[ 3.49851591e+02],
[ 3.58803191e+02],
[ 3.67754790e+02],
[ 3.76706390e+02],
[ 3.85657990e+02],
[ 3.94609590e+02],
[ 4.03561190e+02],
[ 1.10879741e+00],
[ 1.00603972e+01],
[ 1.90119970e+01],
[ 2.79635968e+01],
[ 3.69151966e+01],
[ 4.58667964e+01],
[ 5.48183963e+01],
[ 6.37699961e+01],
[ 7.27215959e+01],
[ 8.16731957e+01],
[ 9.06247955e+01],
[ 9.95763953e+01],
[ 1.08527995e+02],
[ 1.17479595e+02],
[ 1.26431195e+02],
[ 1.35382795e+02],
[ 1.44334394e+02],
[ 1.53285994e+02],
[ 1.62237594e+02],
[ 1.71189194e+02],
[ 1.80140794e+02],
[ 1.89092393e+02],
[ 1.98043993e+02],
[ 2.06995593e+02],
[ 2.15947193e+02],
[ 2.24898793e+02],
[ 2.33850392e+02],
[ 2.42801992e+02],
[ 2.51753592e+02],
[ 2.60705192e+02],
[ 2.69656792e+02],
[ 2.78608391e+02],
[ 2.87559991e+02],
[ 2.96511591e+02],
[ 3.05463191e+02],
[ 3.14414791e+02],
[ 3.23366390e+02],
[ 3.32317990e+02],
[ 3.41269590e+02],
[ 3.50221190e+02],
[ 3.59172790e+02],
[ 3.68124390e+02],
[ 3.77075989e+02],
[ 3.86027589e+02],
[ 3.94979189e+02],
[ 4.03930789e+02],
[ 1.47839654e+00],
[ 1.04299964e+01],
[ 1.93815962e+01],
[ 2.83331960e+01],
[ 3.72847958e+01],
[ 4.62363956e+01],
[ 5.51879954e+01],
[ 6.41395952e+01],
[ 7.30911950e+01],
[ 8.20427948e+01],
[ 9.09943946e+01],
[ 9.99459944e+01],
[ 1.08897594e+02],
[ 1.17849194e+02],
[ 1.26800794e+02],
[ 1.35752394e+02],
[ 1.44703993e+02],
[ 1.53655593e+02],
[ 1.62607193e+02],
[ 1.71558793e+02],
[ 1.80510393e+02],
[ 1.89461993e+02],
[ 1.98413592e+02],
[ 2.07365192e+02],
[ 2.16316792e+02],
[ 2.25268392e+02],
[ 2.34219992e+02],
[ 2.43171591e+02],
[ 2.52123191e+02],
[ 2.61074791e+02],
[ 2.70026391e+02],
[ 2.78977991e+02],
[ 2.87929590e+02],
[ 2.96881190e+02],
[ 3.05832790e+02],
[ 3.14784390e+02],
[ 3.23735990e+02],
[ 3.32687589e+02],
[ 3.41639189e+02],
[ 3.50590789e+02],
[ 3.59542389e+02],
[ 3.68493989e+02],
[ 3.77445588e+02],
[ 3.86397188e+02],
[ 3.95348788e+02],
[ 4.04300388e+02],
[ 1.84799568e+00],
[ 1.07995955e+01],
[ 1.97511953e+01],
[ 2.87027951e+01],
[ 3.76543949e+01],
[ 4.66059947e+01],
[ 5.55575945e+01],
[ 6.45091943e+01],
[ 7.34607941e+01],
[ 8.24123940e+01],
[ 9.13639938e+01],
[ 1.00315594e+02],
[ 1.09267193e+02],
[ 1.18218793e+02],
[ 1.27170393e+02],
[ 1.36121993e+02],
[ 1.45073593e+02],
[ 1.54025192e+02],
[ 1.62976792e+02],
[ 1.71928392e+02],
[ 1.80879992e+02],
[ 1.89831592e+02],
[ 1.98783191e+02],
[ 2.07734791e+02],
[ 2.16686391e+02],
[ 2.25637991e+02],
[ 2.34589591e+02],
[ 2.43541190e+02],
[ 2.52492790e+02],
[ 2.61444390e+02],
[ 2.70395990e+02],
[ 2.79347590e+02],
[ 2.88299190e+02],
[ 2.97250789e+02],
[ 3.06202389e+02],
[ 3.15153989e+02],
[ 3.24105589e+02],
[ 3.33057189e+02],
[ 3.42008788e+02],
[ 3.50960388e+02],
[ 3.59911988e+02],
[ 3.68863588e+02],
[ 3.77815188e+02],
[ 3.86766787e+02],
[ 3.95718387e+02],
[ 4.04669987e+02],
[ 2.21759481e+00],
[ 1.11691946e+01],
[ 2.01207944e+01],
[ 2.90723942e+01],
[ 3.80239940e+01],
[ 4.69755939e+01],
[ 5.59271937e+01],
[ 6.48787935e+01],
[ 7.38303933e+01],
[ 8.27819931e+01],
[ 9.17335929e+01],
[ 1.00685193e+02],
[ 1.09636793e+02],
[ 1.18588392e+02],
[ 1.27539992e+02],
[ 1.36491592e+02],
[ 1.45443192e+02],
[ 1.54394792e+02],
[ 1.63346391e+02],
[ 1.72297991e+02],
[ 1.81249591e+02],
[ 1.90201191e+02],
[ 1.99152791e+02],
[ 2.08104390e+02],
[ 2.17055990e+02],
[ 2.26007590e+02],
[ 2.34959190e+02],
[ 2.43910790e+02],
[ 2.52862389e+02],
[ 2.61813989e+02],
[ 2.70765589e+02],
[ 2.79717189e+02],
[ 2.88668789e+02],
[ 2.97620388e+02],
[ 3.06571988e+02],
[ 3.15523588e+02],
[ 3.24475188e+02],
[ 3.33426788e+02],
[ 3.42378388e+02],
[ 3.51329987e+02],
[ 3.60281587e+02],
[ 3.69233187e+02],
[ 3.78184787e+02],
[ 3.87136387e+02],
[ 3.96087986e+02],
[ 4.05039586e+02],
[ 2.58719395e+00],
[ 1.15387938e+01],
[ 2.04903936e+01],
[ 2.94419934e+01],
[ 3.83935932e+01],
[ 4.73451930e+01],
[ 5.62967928e+01],
[ 6.52483926e+01],
[ 7.41999924e+01],
[ 8.31515922e+01],
[ 9.21031920e+01],
[ 1.01054792e+02],
[ 1.10006392e+02],
[ 1.18957991e+02],
[ 1.27909591e+02],
[ 1.36861191e+02],
[ 1.45812791e+02],
[ 1.54764391e+02],
[ 1.63715990e+02],
[ 1.72667590e+02],
[ 1.81619190e+02],
[ 1.90570790e+02],
[ 1.99522390e+02],
[ 2.08473990e+02],
[ 2.17425589e+02],
[ 2.26377189e+02],
[ 2.35328789e+02],
[ 2.44280389e+02],
[ 2.53231989e+02],
[ 2.62183588e+02],
[ 2.71135188e+02],
[ 2.80086788e+02],
[ 2.89038388e+02],
[ 2.97989988e+02],
[ 3.06941587e+02],
[ 3.15893187e+02],
[ 3.24844787e+02],
[ 3.33796387e+02],
[ 3.42747987e+02],
[ 3.51699586e+02],
[ 3.60651186e+02],
[ 3.69602786e+02],
[ 3.78554386e+02],
[ 3.87505986e+02],
[ 3.96457586e+02],
[ 4.05409185e+02],
[ 2.95679309e+00],
[ 1.19083929e+01],
[ 2.08599927e+01],
[ 2.98115925e+01],
[ 3.87631923e+01],
[ 4.77147921e+01],
[ 5.66663919e+01],
[ 6.56179917e+01],
[ 7.45695915e+01],
[ 8.35211914e+01],
[ 9.24727912e+01],
[ 1.01424391e+02],
[ 1.10375991e+02],
[ 1.19327591e+02],
[ 1.28279190e+02],
[ 1.37230790e+02],
[ 1.46182390e+02],
[ 1.55133990e+02],
[ 1.64085590e+02],
[ 1.73037189e+02],
[ 1.81988789e+02],
[ 1.90940389e+02],
[ 1.99891989e+02],
[ 2.08843589e+02],
[ 2.17795188e+02],
[ 2.26746788e+02],
[ 2.35698388e+02],
[ 2.44649988e+02],
[ 2.53601588e+02],
[ 2.62553188e+02],
[ 2.71504787e+02],
[ 2.80456387e+02],
[ 2.89407987e+02],
[ 2.98359587e+02],
[ 3.07311187e+02],
[ 3.16262786e+02],
[ 3.25214386e+02],
[ 3.34165986e+02],
[ 3.43117586e+02],
[ 3.52069186e+02],
[ 3.61020785e+02],
[ 3.69972385e+02],
[ 3.78923985e+02],
[ 3.87875585e+02],
[ 3.96827185e+02],
[ 4.05778784e+02],
[ 3.32639222e+00],
[ 1.22779920e+01],
[ 2.12295918e+01],
[ 3.01811916e+01],
[ 3.91327915e+01],
[ 4.80843913e+01],
[ 5.70359911e+01],
[ 6.59875909e+01],
[ 7.49391907e+01],
[ 8.38907905e+01],
[ 9.28423903e+01],
[ 1.01793990e+02],
[ 1.10745590e+02],
[ 1.19697190e+02],
[ 1.28648790e+02],
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[ 3.01685979e+02],
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[ 3.19589179e+02],
[ 3.28540778e+02],
[ 3.37492378e+02],
[ 3.46443978e+02],
[ 3.55395578e+02],
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self.width = 0.0030000000000000001
658 xy = xy[:, :, np.newaxis]
659 XY = np.concatenate((xy.real, xy.imag), axis=2)
660 if self.Umask is not ma.nomask:
661 XY = ma.array(XY)
662 XY[self.Umask] = ma.masked
663 # This might be handled more efficiently with nans, given
664 # that nans will end up in the paths anyway.
665
666 return XY
667
668 def _h_arrows(self, length):
669 """ length is in arrow width units """
670 # It might be possible to streamline the code
671 # and speed it up a bit by using complex (x,y)
672 # instead of separate arrays; but any gain would be slight.
ValueError: operands could not be broadcast together with shapes (400,8) (828,1)
***************************************************************************
History of session input:X,Y=mgrid[0:5:20j , 0:10:20j]U = X ; V = 0.7*X + 0.5*Yplt.quiver(Z , Y , hyper_bz_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:], cmap=cm.Reds, scale=0.05, headwidth=8, headlength=8, angles='xy')plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale_units='xy', scale=1)figure()angles = (X * 20 + Y * 20).ravel() plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=1., scale=1)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=1)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=10)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=30)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=50)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles='xy', scale=60)angles = (X * 20 + Y * 20).ravel() #plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)figure()#plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)plt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)x = arange(4) y = arange(5) X, Y = meshgrid(x, y) u = ones_like(X) v = zeros_like(X) c = arange(u.size) # values mapped to colors angles = (X * 20 + Y * 20).ravel() quiver(X, Y, u, v, c, angles=angles) x = N.linspace(0, 1, 10)y = N.linspace(0, 1, 10)x = linspace(0, 1, 10)y = linspace(0, 1, 10)angles =linspace(0, 360, 10)P.quiver(x, y, 1, 0, angles=angles)quiver(x, y, 1, 0, angles=angles)import globimport h5pyarchivos = np.sort(glob.glob('../comp5ppc80_L1100_wces1200_nt100//*flds.tot*')) #names of the fields files in orderN = 30 #Number of snaps we want to loadistep=1if istep == 1:
point=2
ghost1=2 #2 ghosts At the beginning of each array
ghost2=3 #3 ghosts At the end of each array
#Here we create the Hypercube containing the magnetic field of each snaphyper_bx = np.array([ np.array(h5py.File(archivos[i]).get('bx')) for i in range(N) ])hyper_by = np.array([ np.array(h5py.File(archivos[i]).get('by')) for i in range(N) ])hyper_bz = np.array([ np.array(h5py.File(archivos[i]).get('bz')) for i in range(N) ])#Here we create the Hypercube containing the electric field of each snaphyper_ex = np.array([ np.array(h5py.File(archivos[i]).get('ex')) for i in range(N) ])hyper_ey = np.array([ np.array(h5py.File(archivos[i]).get('ey')) for i in range(N) ])hyper_ez = np.array([ np.array(h5py.File(archivos[i]).get('ez')) for i in range(N) ])#Here we clean the arrays from the ghosts cellstam0 = np.shape(hyper_bx)[1]-ghost2 #z-axis (16 cells + 5 ghosts)tam1 = np.shape(hyper_bx)[2]-ghost2 #y-axis (1152 cells + 5 ghosts) #With ghost2 I wipe out the three last ghost cells#tam2 = np.shape(hyper_bx)[3]-ghost2 #x-axis (1 cell + 6 ghosts)hyper_bx_trunc=np.array([ hyper_bx[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])hyper_by_trunc=np.array([ hyper_by[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])hyper_bz_trunc=np.array([ hyper_bz[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])hyper_ex_trunc=np.array([ hyper_ex[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])hyper_ey_trunc=np.array([ hyper_ey[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])hyper_ez_trunc=np.array([ hyper_ez[i,ghost1:tam0,ghost1:tam1,point] for i in range(N) ])nn = 25Z , Y = np.mgrid[0:tam0:(tam0*1j) , 0:tam1:(tam1*1j)/nn ]angles = (X * 20 + Y * 20).ravel() hyper_bz_trunc_half = np.array([ hyper_bz_trunc[i,:,::nn] for i in range(N) ]) #Reduce the elements taking elements nn by nnhyper_by_trunc_half = np.array([ hyper_by_trunc[i,:,::nn] for i in range(N) ]) angles = (Z * 20 + Y * 20).ravel()plt.quiver(Z , Y , hyper_bz_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:], cmap=cm.Reds, scale=0.05, headwidth=8, headlength=8)plt.quiver(Z , Y , hyper_bz_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:] , hyper_by_trunc_half[0,:,:], cmap=cm.Reds, scale=0.05, headwidth=8, headlength=8, angles='xy')get_ipython().magic('config Application.verbose_crash=True')get_ipython().magic('debug')X, Y = meshgrid(x, y)X,Y=mgrid[0:5:20j , 0:10:20j]U = X ; V = 0.7*X + 0.5*Yplt.quiver(X, Y, U, V, # data
U, # colour the arrows based on this array
cmap=cm.seismic, # colour map
headlength=7, # length of the arrows
angles=angles, scale_units='xy', scale=1)
*** Last line of input (may not be in above history):
U = X ; V = 0.7*X + 0.5*Y