这篇教程numpy的squeeze函数使用方法写得很实用,希望能帮到您。 reshape函数:改变数组的维数(注意不是shape大小) >>> e= np.arange(10)>>> earray([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]]])>>> e.reshape(1,1,10)array([[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]])>>> e.reshape(1,10,1)array([[[0], [1], [2], [3], [4], [5], [6], [7], [8], [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)a表示输入的数组; 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)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)返回值:数组 5) 不会修改原数组; >>> a = e.reshape(1,1,10)>>> aarray([[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]])>>> np.squeeze(a)array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) 体现在画图时 >>> plt.plot(a)Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:/Python27/lib/site-packages/matplotlib/pyplot.py", line 3240, in plot ret = ax.plot(*args, **kwargs) File "C:/Python27/lib/site-packages/matplotlib/__init__.py", line 1710, in inner return func(ax, *args, **kwargs) File "C:/Python27/lib/site-packages/matplotlib/axes/_axes.py", line 1437, in plot for line in self._get_lines(*args, **kwargs): File "C:/Python27/lib/site-packages/matplotlib/axes/_base.py", line 404, in _grab_next_args for seg in self._plot_args(this, kwargs): File "C:/Python27/lib/site-packages/matplotlib/axes/_base.py", line 384, in _plot_args x, y = self._xy_from_xy(x, y) File "C:/Python27/lib/site-packages/matplotlib/axes/_base.py", line 246, in _xy_from_xy "shapes {} and {}".format(x.shape, y.shape))ValueError: x and y can be no greater than 2-D, but have shapes (1L,) and (1L, 1L, 10L)>>> plt.plot(np.squeeze(a))[<matplotlib.lines.Line2D object at 0x00000000146CD940>]>>> plt.show()
>>> np.squeeze(a).shape(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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