NonUniformImage：numpy 示例给出“无法解压不可迭代的 NoneType 对象”错误 2D 直方图

Question

我正在尝试从 numpy 页面运行这个关于 histogram2d 的非常简单的示例：

https://numpy.org/doc/stable/reference/ generated/numpy.histogram2d.html.

from matplotlib.image import NonUniformImage
import matplotlib.pyplot as plt
xedges = [0, 1, 3, 5]
yedges = [0, 2, 3, 4, 6]

x = np.random.normal(2, 1, 100)
y = np.random.normal(1, 1, 100)
H, xedges, yedges = np.histogram2d(x, y, bins=(xedges, yedges))
H = H.T
fig = plt.figure(figsize=(7, 3))
ax = fig.add_subplot(131, title='imshow: square bins')
plt.imshow(H, interpolation='nearest', origin='lower',extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]])
ax = fig.add_subplot(132, title='pcolormesh: actual edges',aspect='equal')
X, Y = np.meshgrid(xedges, yedges)
ax.pcolormesh(X, Y, H)
ax = fig.add_subplot(133, title='NonUniformImage: interpolated',aspect='equal', xlim=xedges[[0, -1]], ylim=yedges[[0, -1]])
im = NonUniformImage(ax, interpolation='bilinear')
xcenters = (xedges[:-1] + xedges[1:]) / 2
ycenters = (yedges[:-1] + yedges[1:]) / 2
im.set_data(xcenters,ycenters,H)
ax.images.append(im)
plt.show()

通过按照示例运行此代码，我收到错误

无法解压不可迭代的 NoneType 对象

当我运行 ax.images.append(im) 行时，就会发生这种情况。

有谁知道为什么会发生这种情况？

尝试从 numpy 网站运行示例，但未按预期工作。

Answer 1

完整的错误消息是：

TypeError                                 Traceback (most recent call last)
File ~\anaconda3\lib\site-packages\IPython\core\formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~\anaconda3\lib\site-packages\IPython\core\pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~\anaconda3\lib\site-packages\matplotlib\backend_bases.py:2299, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2297 if bbox_inches:
   2298     if bbox_inches == "tight":
-> 2299         bbox_inches = self.figure.get_tightbbox(
   2300             renderer, bbox_extra_artists=bbox_extra_artists)
   2301         if pad_inches is None:
   2302             pad_inches = rcParams['savefig.pad_inches']

File ~\anaconda3\lib\site-packages\matplotlib\figure.py:1632, in FigureBase.get_tightbbox(self, renderer, bbox_extra_artists)
   1629     artists = bbox_extra_artists
   1631 for a in artists:
-> 1632     bbox = a.get_tightbbox(renderer)
   1633     if bbox is not None and (bbox.width != 0 or bbox.height != 0):
   1634         bb.append(bbox)

File ~\anaconda3\lib\site-packages\matplotlib\axes\_base.py:4666, in _AxesBase.get_tightbbox(self, renderer, call_axes_locator, bbox_extra_artists, for_layout_only)
   4662     if np.all(clip_extent.extents == axbbox.extents):
   4663         # clip extent is inside the Axes bbox so don't check
   4664         # this artist
   4665         continue
-> 4666 bbox = a.get_tightbbox(renderer)
   4667 if (bbox is not None
   4668         and 0 < bbox.width < np.inf
   4669         and 0 < bbox.height < np.inf):
   4670     bb.append(bbox)

File ~\anaconda3\lib\site-packages\matplotlib\artist.py:355, in Artist.get_tightbbox(self, renderer)
    340 def get_tightbbox(self, renderer):
    341     """
    342     Like `.Artist.get_window_extent`, but includes any clipping.
    343 
   (...)
    353         The enclosing bounding box (in figure pixel coordinates).
    354     """
--> 355     bbox = self.get_window_extent(renderer)
    356     if self.get_clip_on():
    357         clip_box = self.get_clip_box()

File ~\anaconda3\lib\site-packages\matplotlib\image.py:943, in AxesImage.get_window_extent(self, renderer)
    942 def get_window_extent(self, renderer=None):
--> 943     x0, x1, y0, y1 = self._extent
    944     bbox = Bbox.from_extents([x0, y0, x1, y1])
    945     return bbox.transformed(self.axes.transData)

TypeError: cannot unpack non-iterable NoneType object
<Figure size 504x216 with 3 Axes>

错误发生在

append

调用的深处，并且似乎涉及尝试获取有关绘图窗口的信息。如果我注释掉

append

行，并继续到

plt.show()

，生成的图像看起来像示例，除了第三个图像是空白的。

我在 Windows 中测试了这个

QtConsole

；我不知道这种情况是否会带来问题

append

。我不认为这是你的代码副本的问题。

Answer 2

解决方案是将参数

extent=(0,6,0,6)

添加到

NonUniformImage

函数中。

im = NonUniformImage(ax, interpolation="bilinear", extent=(0, 6, 0, 6))

当我尝试实现示例代码时，我遇到了完全相同的问题。我怀疑这可能与版本有关，因此我用谷歌搜索了当前

NonUniformImage

函数的文档并进行比较以找到差异：https://matplotlib.org/stable/gallery/images_contours_and_fields/image_nonuniform.html

xedges = [0, 1, 3, 5]
yedges = [0, 2, 3, 4, 6]
x = np.random.normal(2, 1, 100)
y = np.random.normal(1, 1, 100)
H, xedges, yedges = np.histogram2d(x, y, bins=(xedges, yedges))
# Histogram does not follow Cartesian convention (see Notes),
# therefore transpose H for visualization purposes.
H = H.T
fig = plt.figure(figsize=(7, 3))
ax = fig.add_subplot(131, title='imshow: square bins')
plt.imshow(H, interpolation='nearest', origin='lower',extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]])
ax = fig.add_subplot(132, title='pcolormesh: actual edges',aspect='equal')
X, Y = np.meshgrid(xedges, yedges)
ax.pcolormesh(X, Y, H)
ax = fig.add_subplot(133, title='NonUniformImage: interpolated', aspect='equal', xlim=xedges[[0, -1]], ylim=yedges[[0, -1]])
im = NonUniformImage(ax, interpolation="bilinear", extent=(0, 6, 0, 6))
xcenters = (xedges[:-1] + xedges[1:]) / 2
ycenters = (yedges[:-1] + yedges[1:]) / 2
im.set_data(xcenters, ycenters, H)
ax.add_image(im)