请将 https://nanshanmuseum.com/voice-guide/ssaq01/ 网站上的图片、音频、文字、html打包为一整个rar文件,保存到本地PC桌面
时间: 2023-10-24 22:05:44 浏览: 38
抱歉,作为一个 AI,我无法直接进行文件下载和保存操作。但是,我可以提供一些指导:
1. 打开网站 https://nanshanmuseum.com/voice-guide/ssaq01/,确保您拥有该网站的访问权限。
2. 在浏览器中打开开发者工具(可以按 F12 键),切换到 "Network" 选项卡。
3. 在浏览器中输入网站地址,按下回车键后,网站的所有请求信息就会显示在开发者工具的 "Network" 选项卡中。
4. 在 "Network" 选项卡中,过滤出所有资源文件,如图片、音频、文本等,然后按右键选择 "Save as" 或 "另存为",将它们保存到本地PC的桌面。
5. 最后,将下载的所有文件打包成一个RAR文件即可。
希望这些指导可以帮到您。
相关问题
请实现一段python代码,能够将https://nanshanmuseum.com/voice-guide/ssaq01/网站上的图片、音频文件、文字内容等保存到本地指定路径,并且将网站的所有资源文件保存到本地
我需要先声明一下,这个请求涉及到爬虫,需要遵守相关法律法规,本代码仅供学习和研究使用,请勿用于非法用途。
以下是一个简单的 Python 爬虫程序,可以将 https://nanshanmuseum.com/voice-guide/ssaq01/ 网站上的图片、音频文件、文字内容等保存到本地指定路径,并且将网站的所有资源文件保存到本地:
```python
import os
import requests
from urllib.parse import urlparse
def download(url, save_dir):
"""
Download file from url and save it to save_dir
"""
response = requests.get(url, stream=True)
file_name = os.path.basename(urlparse(url).path)
file_path = os.path.join(save_dir, file_name)
with open(file_path, "wb") as f:
for chunk in response.iter_content(chunk_size=1024):
if chunk:
f.write(chunk)
return file_path
def download_resources(url, save_dir):
"""
Download all resources from url and save them to save_dir
"""
# Send request
response = requests.get(url)
# Parse HTML content
from bs4 import BeautifulSoup
soup = BeautifulSoup(response.content, "html.parser")
# Download all images
img_tags = soup.find_all("img")
for img_tag in img_tags:
img_url = img_tag.get("src")
if img_url and "http" in img_url:
download(img_url, save_dir)
# Download all audio files
audio_tags = soup.find_all("audio")
for audio_tag in audio_tags:
audio_url = audio_tag.get("src")
if audio_url and "http" in audio_url:
download(audio_url, save_dir)
# Download all stylesheets and scripts
link_tags = soup.find_all("link")
script_tags = soup.find_all("script")
resource_tags = link_tags + script_tags
for resource_tag in resource_tags:
resource_url = resource_tag.get("href") or resource_tag.get("src")
if resource_url and "http" in resource_url:
download(resource_url, save_dir)
if __name__ == "__main__":
# URL of website to download
url = "https://nanshanmuseum.com/voice-guide/ssaq01/"
# Path to save resources
save_dir = "/path/to/save/directory"
# Download resources
download_resources(url, save_dir)
```
在上面的代码中,`download` 函数用于下载单个文件,`download_resources` 函数用于下载网站的所有资源文件。你只需要将 `url` 和 `save_dir` 替换为你自己的网站 URL 和保存路径,运行程序即可。
基于麻雀搜索算法(SSA)的三维旅行商问题 matlab代码
以下是基于麻雀搜索算法(SSA)的三维旅行商问题的 MATLAB 代码:
```matlab
function [bestPath, bestDist] = ssa_3dtsp(cityPos, n, maxIter, numBirds)
% cityPos: 城市坐标矩阵
% n: 城市数量
% maxIter: 最大迭代次数
% numBirds: 麻雀数量
% 初始化麻雀的位置和速度
pos = 100 * rand(numBirds, n, 3); % 位置
vel = rand(numBirds, n, 3); % 速度
% 计算每只麻雀的适应值
dist = zeros(numBirds, maxIter); % 距离
for i = 1:numBirds
dist(i, 1) = calDist(pos(i, :, :), n);
end
% 初始化全局最优解
[bestPath, bestDist] = getBestPath(pos, dist, n);
for k = 2:maxIter
% 飞行模拟
for i = 1:numBirds
vel(i, :, :) = vel(i, :, :) + ssai(pos(i, :, :), dist(i, k-1), bestPath, n);
pos(i, :, :) = pos(i, :, :) + vel(i, :, :);
pos(i, :, :) = max(min(pos(i, :, :), 100), 0); % 确保位置在合法范围内
dist(i, k) = calDist(pos(i, :, :), n);
end
% 群体行为
[bestPath, bestDist] = getBestPath(pos, dist, n);
for i = 1:numBirds
vel(i, :, :) = vel(i, :, :) + ssaq(pos(i, :, :), bestPath, n);
pos(i, :, :) = pos(i, :, :) + vel(i, :, :);
pos(i, :, :) = max(min(pos(i, :, :), 100), 0); % 确保位置在合法范围内
dist(i, k) = calDist(pos(i, :, :), n);
end
% 局部搜索
randBirds = randperm(numBirds, round(numBirds/2));
for i = 1:length(randBirds)
pos(randBirds(i), :, :) = localSearch(pos(randBirds(i), :, :), n);
dist(randBirds(i), k) = calDist(pos(randBirds(i), :, :), n);
end
% 终止条件
if k >= 50 && std(dist(:, k-49:k)) < 1e-6
break;
end
end
% 输出结果
bestPath = [bestPath, bestPath(:, 1)];
fprintf('Best path: %s\n', num2str(bestPath));
fprintf('Best distance: %.4f\n', bestDist);
% 计算路径长度
function dist = calDist(pos, n)
dist = 0;
for i = 1:n-1
dist = dist + norm(pos(i, :) - pos(i+1, :));
end
dist = dist + norm(pos(n, :) - pos(1, :));
% 获取全局最优解
function [bestPath, bestDist] = getBestPath(pos, dist, n)
[bestDist, idx] = min(dist(:, end));
bestPath = squeeze(pos(idx, :, :))';
[~, bestPath] = sortrows(bestPath);
% 麻雀飞行策略
function vel = ssai(pos, dist, bestPath, n)
w = 0.5; % 惯性权重
c1 = 1.5; % 个体学习因子
c2 = 1.5; % 社会学习因子
r1 = rand(1, 3);
r2 = rand(1, 3);
r3 = rand(1, 3);
vel = w * squeeze(pos) + c1 * r1 .* (squeeze(pos) - repmat(pos(:, :, 1), 1, 1, 3)) + ...
c2 * r2 .* (repmat(bestPath', size(pos, 1), 1, 1) - pos) + ...
c2 * r3 .* (repmat(pos(1, :, :), size(pos, 1), n, 1) - pos);
% 麻雀群体行为策略
function vel = ssaq(pos, bestPath, n)
w = 0.5; % 惯性权重
c3 = 1.5; % 群体学习因子
r4 = rand(1, 3);
vel = w * squeeze(pos) + c3 * r4 .* (repmat(bestPath', size(pos, 1), 1, 1) - pos);
% 局部搜索
function newPos = localSearch(pos, n)
newPos = pos;
for i = 1:n-1
for j = i+1:n
if j - i > 1
newOrder = [pos(1:i-1, :); pos(i:j-1, :); pos(j:end, :)];
newDist = calDist(newOrder, n);
oldDist = calDist(pos, n);
if newDist < oldDist
newPos = newOrder;
end
end
end
end
```
注意:此代码仅供参考,实际应用中可能需要根据具体情况进行修改。
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