当axis=0时,numpy沿着第0维的方向进行求和,也就是第一个元素值=a0000+a1000+a2000+a3000=11,第二个元素=a0001+a1001+a2001+a3001=5,同理可得最后的结果如下: >>>data.sum(axis=0)array([[[11,5,6],[7,9,4]],[[6,6,11],[7,10,9]],[[6,11,4],[7,12,8]]]) 当axis=3时,numpy沿...
In [2]: x = np.random.randint(0,9, (2,3)) In [3]: x Out[3]: array([[0,8,6], [1,2,1]]) In [4]: x.ndim Out[4]:2In [5]: x.shape Out[5]: (2,3) In [6]: x[0] Out[6]: array([0,8,6]) In [7]: x[:,0] Out[7]: array([0,1]) In [8]: x.s...
In [54]: arr = np.random.randn(5,4) In [55]: arr.sum(axis=0) Out[55]: array([-0.78235764, -0.05712849, -3.87703455,1.51758567]) In [56]: arr.sum(axis=1) Out[56]: array([-0.51765783, -2.78973184,0.73440357,0.45910145, -1.08505038]) In [57]: arr Out[57]: array([[-0.2516431...
In[1]:importnumpyasnp In[2]:x=np.random.randint(0,9,(2,3))In[3]:x Out[3]:array([[0,8,6],[1,2,1]])In[4]:x.ndim Out[4]:2In[5]:x.shape Out[5]:(2,3)In[6]:x[0]Out[6]:array([0,8,6])In[7]:x[:,0]Out[7]:array([0,1])In[8]:x.sum(axis=0)Out[8]...
In [1]: import numpyasnpIn [2]: x=np.random.randint(0,9, (2,3))In [3]: xOut[3]:array([[0,8,6], [1,2,1]])In [4]: x.ndimOut[4]:2In [5]: x.shapeOut[5]: (2,3)In[6]: x[0]Out [6]:array([0,8,6])In ...
importnumpyasnp ndarray.shape 感受一个ndarray,最简单的方法就是打印ndarray的shape。 官方文档里面是这样写的: the dimensions of the array. This is a tuple of integers indicating the size of the array in each dimension. For a matrix withnrows andmcolumns,shapewill be(n,m). The length of the...
>>> import numpy as np >>> a = np.array([10,11,12,16,30,31,101,102,103]) 一维数组a只有1个轴,调用cumsum(axis)方法时,只能传入0,若传入0以上的数值,该方法会报错。 >>> a.cumsum(1) Traceback (most recent call last): File "<pyshell#3>", line 1, in <module> a.cumsum(1) ...
for tmp in a: if tmp > a[maxindex]: maxindex = i i += 1 print(maxindex) 二、参数理解 1.一维数组 import numpy as np a = np.array([3, 1, 2, 4, 6, 1]) print(np.argmax(a)) 当没有指定axis的时候,默认是0.所以最后输出的是4(也就是表示第四维值最大) ...
numpy库中横轴、纵轴 axis 参数实例详解: In[1]: import numpy as np #生成一个3行4列的数组 In [2]: a = np.arange(12).reshape(3,4) In [3]: a Out[3]:array([[0,1,2,3], [4,5,6,7], [8,9,10,11]]) #axis=0对a的横轴进行操作,在运算的过程中其运算的方向表现为纵向运算 ...
In [8]: arr.transpose(0,1,2) Out[8]: array([[[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]], [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]) B.transpose(0,2,1),即以0为参考编号,数组0-1和0-2即为所求平面数组,但是2,1相对于(0,1,...