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在ipython笔记本中“将matplotlib.pyplot导入为plt”

[英]“import matplotlib.pyplot as plt” in ipython notebook

I'm new to ipython notebook, but I have the following error message whenever I run import matplotlib.pyplot as plt . 我是ipython笔记本的新手,但每当我运行import matplotlib.pyplot as plt时,我都会收到以下错误消息。 I'm using Mac. 我正在使用Mac。 It works fine with the built-in python or Canopy. 它与内置的python或Canopy一起工作正常。 The problem only exists with ipython notebook . 这个问题只存在于ipython notebook I also tried to update the numpy, but the problem still exists. 我也尝试更新numpy,但问题仍然存在。 Would be grateful for someone to help! 非常感谢有人帮忙!

import matplotlib.pyplot as plt

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
RuntimeError: module compiled against API version 9 but this version of numpy is 7

---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-4-6f467123fe04> in <module>()
----> 1 import matplotlib.pyplot

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/pyplot.py in <module>()
     22 
     23 import matplotlib
---> 24 import matplotlib.colorbar
     25 from matplotlib import _pylab_helpers, interactive
     26 from matplotlib.cbook import dedent, silent_list, is_string_like, is_numlike

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/colorbar.py in <module>()
     27 import matplotlib.artist as martist
     28 import matplotlib.cbook as cbook
---> 29 import matplotlib.collections as collections
     30 import matplotlib.colors as colors
     31 import matplotlib.contour as contour

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/collections.py in <module>()
     21 import matplotlib.artist as artist
     22 from matplotlib.artist import allow_rasterization
---> 23 import matplotlib.backend_bases as backend_bases
     24 import matplotlib.path as mpath
     25 from matplotlib import _path

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/backend_bases.py in <module>()
     48 
     49 import matplotlib.tight_bbox as tight_bbox
---> 50 import matplotlib.textpath as textpath
     51 from matplotlib.path import Path
     52 from matplotlib.cbook import mplDeprecation

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/textpath.py in <module>()
      9 from matplotlib.path import Path
     10 from matplotlib import rcParams
---> 11 import matplotlib.font_manager as font_manager
     12 from matplotlib.ft2font import FT2Font, KERNING_DEFAULT, LOAD_NO_HINTING
     13 from matplotlib.ft2font import LOAD_TARGET_LIGHT

/Users/Michael/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib/font_manager.py in <module>()
     51 import matplotlib
     52 from matplotlib import afm
---> 53 from matplotlib import ft2font
     54 from matplotlib import rcParams, get_cachedir
     55 from matplotlib.cbook import is_string_like

ImportError: numpy.core.multiarray failed to import

How committed are you to Canopy? 你对Canopy的承诺如何? I had a few configuration issues attempting to use Canopy and ended up using Homebrew to customize my own Python install instead. 我有一些配置问题试图使用Canopy,最后使用Homebrew来定制我自己的Python安装。 There's a really helpful guide at: 有一个非常有用的指南:

http://joernhees.de/blog/2013/06/08/mac-os-x-10-8-scientific-python-with-homebrew/ http://joernhees.de/blog/2013/06/08/mac-os-x-10-8-scientific-python-with-homebrew/

I followed all of those steps except for two or three (don't remember which exactly) the "brew install" method didn't work and I had to pip the module instead. 我遵循了所有这些步骤,除了两个或三个(不记得究竟是哪个)“brew install”方法不起作用,我不得不改变模块。

I just opened up an IPython notebook to verify that everything works fine on my distribution. 我刚打开一个IPython笔记本来验证我的发行版上的一切正常。

from matplotlib import pyplot as plt
import numpy as np

x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x, y)
plt.show()

The above gives me the expected output. 以上给出了预期的输出。

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