python - ndarray的快速突变(替换numpy ndarray的部分)

Question

我正在寻找最快的方法来替换预分配的 numpy ndarray 的部分。下面您可以看到sim_matrix(2D ndarray)。 “For 循环”逐行迭代它并覆盖由levels (numpy.array) 给出的值。

有一些快速的方法，已找到:

1. numpy.copyto()
2. numpy.fromiter()
3. = 分配给切片

注意:为简单起见，我在每次迭代中分配相同的值，但生产设置中的情况并非如此。在实际设置中，levels 每行包含不同的值。因此，不鼓励使用 numpy.repeat 或 numpy.hstack 等快捷方式作为答案。

是否有更快的方法来更改 ndarray 的某些部分？

numpy_overwrite.py:

import numpy
panel_size = 365 * 7
rows = 1 * (1+1+2*4) * 10000
# rows = 100
levels = [1778.24] * panel_size
levels_array = numpy.fromiter(levels,dtype='single', count = len(levels))
sim_matrix = numpy.empty([rows, panel_size],dtype='single')

def _copyto(sim_matrix_, level_):
    for i in range(sim_matrix_.shape[0]):
        numpy.copyto(sim_matrix[i], level_)


def _fromiter(sim_matrix_, level_):
    len_level = len(level_)
    for i in range(sim_matrix_.shape[0]):
        sim_matrix[i] = numpy.fromiter(level_,
                                      dtype='single', 
                                      count = len_level)

def _just_assign(sim_matrix_, level_):
    for i in range(sim_matrix_.shape[0]):
        sim_matrix[i] = level_

<小时/>

numpy_overwrite_test.py

import timeit
import numpy_overwrite as npo
print('_fromiter')
print(timeit.timeit('npo._fromiter(npo.sim_matrix, npo.levels)', setup="import numpy_overwrite as npo;", number=3))
print(timeit.timeit('npo._fromiter(npo.sim_matrix, npo.levels_array)', setup="import numpy_overwrite as npo;", number=3))
print('_copyto')
print(timeit.timeit('npo._copyto(npo.sim_matrix, npo.levels)', setup="import numpy_overwrite as npo;", number=3))
print(timeit.timeit('npo._copyto(npo.sim_matrix, npo.levels_array)', setup="import numpy_overwrite as npo;", number=3))
print('_just_assign')
print(timeit.timeit('npo._just_assign(npo.sim_matrix, npo.levels)', setup="import numpy_overwrite as npo;", number=3))
print(timeit.timeit('npo._just_assign(npo.sim_matrix, npo.levels_array)', setup="import numpy_overwrite as npo;", number=3))

<小时/>

运行测试

_fromiter
=========
from python list: 21.129429172957316
from numpy.array: 61.76275303697912

_copyto
=========
from python list: 52.4522930260282
from numpy.array: 0.7605530479922891

_just_assign
=========
from python list: 52.251478374004364
from numpy.array: 0.6351132979616523
    

Answer 1

您是否可能只是在寻找这个？

sim_matrix[:] = levels

编辑:要修改单行，应使用sim_matrix[row_id] =levels

顺便说一句，请注意 using mutables as default function arguments .