python - 从列表或元组创建新的 numpy 数组

Question

创建新的 numpy 数组时，可以像这样制作它们:

a = numpy.array((2, 5))
b = numpy.array((a[0] + 1, 10))

或者像这样:

a = numpy.array([2, 5])
b = numpy.array([a[0] + 1, 10])

哪种方式更好？

Answer 1

经过一些基于 @leopardshark 的测试的answer ，似乎只有基于常量初始化数组，元组才会更好。如果您从变量元组/列表进行初始化，则差异可以忽略不计

常量测试设置

import dis, timeit

list_timing = timeit.timeit('numpy.array([2, 5])', setup = 'import numpy', number = 1000000)
tuple_timing = timeit.timeit('numpy.array((2, 5))', setup = 'import numpy', number = 1000000)

print(f"List mean time: {list_timing}")
>>> 0.6392972
print(f"Tuple mean time: {tuple_timing}")
>>> 0.6296533

这里的反汇编输出与 @leopardshark 相同的

变量测试设置

import dis, timeit
x, y = 2, 5

list_timing = timeit.timeit('numpy.array([x, y])', setup = 'import numpy; x, y = 2, 5', number = 1000000)
tuple_timing = timeit.timeit('numpy.array((x, y))', setup = 'import numpy; x, y = 2, 5', number = 1000000)

print(f"List mean time: {list_timing}")
>>> 0.6279472
print(f"Tuple mean time: {tuple_timing}")
>>> 0.6288363

print(dis.dis('numpy.array([x, y])'))
>>>  1           0 LOAD_NAME                0 (numpy)
>>>              2 LOAD_METHOD              1 (array)
>>>              4 LOAD_NAME                2 (x)
>>>              6 LOAD_NAME                3 (y)
>>>              8 BUILD_LIST               2
>>>             10 CALL_METHOD              1
>>>             12 RETURN_VALUE

print(dis.dis('numpy.array((x, y))'))
>>>  1           0 LOAD_NAME                0 (numpy)
>>>              2 LOAD_METHOD              1 (array)
>>>              4 LOAD_NAME                2 (x)
>>>              6 LOAD_NAME                3 (y)
>>>              8 BUILD_TUPLE              2
>>>             10 CALL_METHOD              1
>>>             12 RETURN_VALUE

反汇编的输出是相同的，而时序更接近