[：，：]在NumPy数组上是什么意思

Question

很抱歉这个愚蠢的问题。 我在PHP上编程，但在Python上找到了一些不错的代码，想在PHP上“重新创建”它。 但我对这条线很失望

self.h = -0.1    
self.activity = numpy.zeros((512, 512)) + self.h
self.activity[:, :] = self.h

但我不明白

[:, :]

卑鄙。

此外，我不能“谷歌它”。

完整代码

import math
import numpy
import pygame
from scipy.misc import imsave
from scipy.ndimage.filters import gaussian_filter


class AmariModel(object):

    def __init__(self, size):
        self.h = -0.1
        self.k = 0.05
        self.K = 0.125
        self.m = 0.025
        self.M = 0.065

        self.stimulus = -self.h * numpy.random.random(size)
        self.activity = numpy.zeros(size) + self.h
        self.excitement = numpy.zeros(size)
        self.inhibition = numpy.zeros(size)

    def stimulate(self):
        self.activity[:, :] = self.activity > 0

        sigma = 1 / math.sqrt(2 * self.k)
        gaussian_filter(self.activity, sigma, 0, self.excitement, "wrap")
        self.excitement *= self.K * math.pi / self.k

        sigma = 1 / math.sqrt(2 * self.m)
        gaussian_filter(self.activity, sigma, 0, self.inhibition, "wrap")
        self.inhibition *= self.M * math.pi / self.m

        self.activity[:, :] = self.h
        self.activity[:, :] += self.excitement
        self.activity[:, :] -= self.inhibition
        self.activity[:, :] += self.stimulus


class AmariMazeGenerator(object):

    def __init__(self, size):
        self.model = AmariModel(size)

        pygame.init()
        self.display = pygame.display.set_mode(size, 0)
        pygame.display.set_caption("Amari Maze Generator")

    def run(self):
        pixels = pygame.surfarray.pixels3d(self.display)

        index = 0
        running = True
        while running:
            self.model.stimulate()

            pixels[:, :, :] = (255 * (self.model.activity > 0))[:, :, None]
            pygame.display.flip()

            for event in pygame.event.get():
                if event.type == pygame.QUIT:
                    running = False
                elif event.type == pygame.KEYDOWN:
                    if event.key == pygame.K_ESCAPE:
                        running = False
                    elif event.key == pygame.K_s:
                        imsave("{0:04d}.png".format(index), pixels[:, :, 0])
                        index = index + 1
                elif event.type == pygame.MOUSEBUTTONDOWN:
                    position = pygame.mouse.get_pos()
                    self.model.activity[position] = 1

        pygame.quit()


def main():
    generator = AmariMazeGenerator((512, 512))
    generator.run()


if __name__ == "__main__":
    main()

Answer 1

[:, :]代表从开始到结束的所有内容，就像列表一样。区别在于第一个:代表第一个维度，第二个:代表第二个维度。

a = numpy.zeros((3, 3))

In [132]: a
Out[132]: 
array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.]])

分配到第二行：

In [133]: a[1, :] = 3

In [134]: a
Out[134]: 
array([[ 0.,  0.,  0.],
       [ 3.,  3.,  3.],
       [ 0.,  0.,  0.]])

分配到第二列：

In [135]: a[:, 1] = 4

In [136]: a
Out[136]: 
array([[ 0.,  4.,  0.],
       [ 3.,  4.,  3.],
       [ 0.,  4.,  0.]])

分配给所有人：

In [137]: a[:] = 10

In [138]: a
Out[138]: 
array([[ 10.,  10.,  10.],
       [ 10.,  10.,  10.],
       [ 10.,  10.,  10.]])

Answer 2

这是切片分配。从技术上讲，它称为¹

self.activity.__setitem__((slice(None,None,None),slice(None,None,None)),self.h)

它将self.activity中的所有元素设置为self.h存储的任何值。你那里的代码看起来真的很多余。据我所知，您可以删除前一行的加法，或者只使用slice赋值：

self.activity = numpy.zeros((512,512)) + self.h

或者

self.activity = numpy.zeros((512,512))
self.activity[:,:] = self.h

可能最快的方法是分配一个空数组，并使用期望值.fill：

self.activity = numpy.empty((512,512))
self.activity.fill(self.h)

^{1实际上，__setslice__在调用__setitem__之前尝试过，但是__setslice__被弃用，除非您有很好的理由，否则不应该在现代代码中使用。}

Answer 3

numpy使用元组作为索引。在本例中，这是一个详细的切片分配。

[0] 
#means line 0 of your matrix
[(0,0)] #means cell at 0,0 of your matrix
[0:1] #means lines 0 to 1 excluded of your matrix
[:1] #excluding the first value means all lines until line 1 excluded
[1:] #excluding the last param mean all lines starting form line 1 included
[:] #excluding both means all lines
[::2] #the addition of a second ':' is the sampling. (1 item every 2)
[::] #exluding it means a sampling of 1
[:,:] #simply uses a tuple (a single , represents an empty tuple) instead of an index.

它相当于

self.activity[:] = self.h

（也适用于常规列表）