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numpy的squeeze函数

 木俊 2018-10-07

http://blog.csdn.net/zenghaitao0128/article/details/78512715

reshape函数:改变数组的维数(注意不是shape大小)

  1. >>> e= np.arange(10)
  2. >>> e
  3. array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> e.reshape(1,1,10)
array([[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]])
  1. >>> e.reshape(1,1,10)
  2. array([[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]])
  3. >>> e.reshape(1,10,1)
  4. array([[[0],
  5. [1],
  6. [2],
  7. [3],
  8. [4],
  9. [5],
  10. [6],
  11. [7],
  12. [8],
  13. [9]]])

squeeze 函数:从数组的形状中删除单维度条目,即把shape中为1的维度去掉

用法:numpy.squeeze(a,axis = None)

  1. 1)a表示输入的数组;
  2. 2)axis用于指定需要删除的维度,但是指定的维度必须为单维度,否则将会报错;
  3. 3)axis的取值可为None 或 int 或 tuple of ints, 可选。若axis为空,则删除所有单维度的条目;
  4. 4)返回值:数组
  5. 5) 不会修改原数组;

  1. >>> a = e.reshape(1,1,10)
  2. >>> a
  3. array([[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]])
  4. >>> np.squeeze(a)
  5. array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

体现在画图时

  1. >>> plt.plot(a)
  2. Traceback (most recent call last):
  3. File "<stdin>", line 1, in <module>
  4. File "C:\Python27\lib\site-packages\matplotlib\pyplot.py", line 3240, in plot
  5. ret = ax.plot(*args, **kwargs)
  6. File "C:\Python27\lib\site-packages\matplotlib\__init__.py", line 1710, in inner
  7. return func(ax, *args, **kwargs)
  8. File "C:\Python27\lib\site-packages\matplotlib\axes\_axes.py", line 1437, in plot
  9. for line in self._get_lines(*args, **kwargs):
  10. File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 404, in _grab_next_args
  11. for seg in self._plot_args(this, kwargs):
  12. File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 384, in _plot_args
  13. x, y = self._xy_from_xy(x, y)
  14. File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 246, in _xy_from_xy
  15. "shapes {} and {}".format(x.shape, y.shape))
  16. ValueError: x and y can be no greater than 2-D, but have shapes (1L,) and (1L, 1L, 10L)
  17. >>> plt.plot(np.squeeze(a))
  18. [<matplotlib.lines.Line2D object at 0x00000000146CD940>]
  19. >>> plt.show()


  1. >>> np.squeeze(a).shape
  2. (10L,)

通过np.squeeze()函数转换后,要显示的数组变成了秩为1的数组,即(10,)

参考:http://blog.csdn.net/zenghaitao0128/article/details/78512715

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