有效初始化多个Numpy数组

Question

我需要初始化具有相同形状的多个Numpy数组。想知道哪种方式是最好的：

1. 为每个人写一行：

dist_x=np.zeros((1,len(pose07)-1))
dist_y=np.zeros((1,len(pose07)-1))
rots_absulute=np.zeros((1,len(pose07)-1))
rots=np.zeros((1,len(pose07)-1))

length=len(pose07)-1

dist_x=np.zeros(1,length)
dist_y=np.zeros(1,length)
rots_absulute=np.zeros(1,length)
rots=np.zeros(1,length)

dist_x=np.zeros((1,len(pose07)-1))
dist_y=np.copy(dist_x)
rots_absulute=np.copy(dist_x)
rots=np.copy(dist_x)

或者有更好的方法？

Answer 1

arr1, arr2, arr3, arr4 = np.zeros((4, 1, len(pose07)-1))

编辑：做了一些基准测试

def func1(inp):
    
    a = np.zeros([1, len(inp)])
    b = np.zeros([1, len(inp)])
    c = np.zeros([1, len(inp)])
    d = np.zeros([1, len(inp)])
    
    return 1

def func2(inp):
    
    length = len(inp)

    a = np.zeros([1, length])
    b = np.zeros([1, length])
    c = np.zeros([1, length])
    d = np.zeros([1, length])
    
    return 1

def func3(inp):
    
    a = np.zeros([1, len(inp)])
    b = np.copy(a)
    c = np.copy(a)
    d = np.copy(a)
    
    return 1

def func4(inp):
    
    a, b, c, d = np.zeros([4, 1, len(inp)])
    
    return 1

import perfplot

bench = perfplot.bench(
    n_range= range(1, 50),
    setup= lambda n: np.random.randint(100, size= [n]),
    kernels= [
        func1,
        func2,
        func3,
        func4
    ]
)

bench.show()

根据基准测试func2（长度首先存储在变量中）似乎表现最好，

并尽量避免func 4，正如Paul Panzer在下面的评论中指出的，func 4可能会导致内存泄漏