importnumpyasnp 数组创建 ## 常规创建方法a=np.array([2,3,4])b=np.array([2.0,3.0,4.0])c=np.array([[1.0,2.0],[3.0,4.0]])d=np.array([[1,2],[3,4]],dtype=complex)# 指定数据类型printa,a.dtypeprintb,b.dtypeprintc,c.dtypeprintd,d.dtype [234]int32[2\.3\.4.]float64[[1\...
代码实例 import numpy as np X = np.array([[0,1,2,3],[10,11,12,13],[20,21,22,23],[30,31,32,33]]) #X 是一个二维数组,维度为 0 ,1;第 0 层 [] 表示第 0 维;第 1 层 [] 表示第 1 维; # X[n0,n1] 表示第 0 维 取第n0 个元素 ,第 1 维取第 n1 个元素 print(X[...
I’m first going to define my array z1. 我首先要定义我的数组z1。 And let’s put in a few elements in there– 1, 3, 5, 7, and 9, for example. 让我们把一些元素放进去,比如1,3,5,7和9。 I can then define a new array called z2, which is just z1 with one added to every ...
With two-dimensional arrays, the first index specifies the row of the array and the second index 对于二维数组,第一个索引指定数组的行,第二个索引指定行 specifies the column of the array. 指定数组的列。 This is exactly the way we would index elements of a matrix in linear algebra. 这正是我...
>>>np.dstack((a,b))array([[0,0],[1,2],[2,4],[3,6],[4,8],[5,10],[6,12],[7,14],[8,16]]) 4、列组合column_stack() 一维数组:按列方向组合 二维数组:同hstack一样 5、行组合row_stack() 以为数组:按行方向组合 二维数组:和vstack一样 ...
[1],1))yuv_array=np.concatenate((y,u,v),axis=2)yuv_array[:,:,0]=yuv_array[:,:,0].clip(16,235).astype(yuv_array.dtype)-16yuv_array[:,:,1:]=yuv_array[:,:,1:].clip(16,240).astype(yuv_array.dtype)-128convert=np.array([#[1.164,0.000,1.793],[1.164,-0.213,-0.533],[...
[1],1))yuv_array=np.concatenate((y,u,v),axis=2)yuv_array[:,:,0]=yuv_array[:,:,0].clip(16,235).astype(yuv_array.dtype)-16yuv_array[:,:,1:]=yuv_array[:,:,1:].clip(16,240).astype(yuv_array.dtype)-128convert=np.array([#[1.164,0.000,1.793],[1.164,-0.213,-0.533],[...