{"id":1033449,"date":"2024-12-31T11:42:02","date_gmt":"2024-12-31T03:42:02","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1033449.html"},"modified":"2024-12-31T11:42:05","modified_gmt":"2024-12-31T03:42:05","slug":"python-%e5%a6%82%e4%bd%95%e6%8a%8a%e4%b8%a4%e4%b8%aa%e7%9f%a9%e9%98%b5%e6%8b%bc%e6%8e%a5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1033449.html","title":{"rendered":"python \u5982\u4f55\u628a\u4e24\u4e2a\u77e9\u9635\u62fc\u63a5"},"content":{"rendered":"

\"python<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2a\u5e93\u6765\u62fc\u63a5\u4e24\u4e2a\u77e9\u9635\uff0c\u6700\u5e38\u7528\u7684\u5e93\u662fNumPy\u3002\u4f7f\u7528NumPy\u7684concatenate\u51fd\u6570\u3001\u4f7f\u7528hstack\u548cvstack\u51fd\u6570\u3001\u4f7f\u7528dstack\u51fd\u6570<\/strong>\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u62fc\u63a5\u4e24\u4e2a\u77e9\u9635\u3002<\/p>\n<\/p>\n

\u4f7f\u7528NumPy\u7684concatenate\u51fd\u6570<\/h3>\n<\/p>\n

NumPy\u7684concatenate\u51fd\u6570\u662f\u6700\u901a\u7528\u7684\u62fc\u63a5\u65b9\u6cd5\u3002\u5b83\u53ef\u4ee5\u5728\u6307\u5b9a\u7684\u8f74\u4e0a\u62fc\u63a5\u77e9\u9635\u3002\u4e0b\u9762\u662f\u8be6\u7ec6\u7684\u6b65\u9aa4\u548c\u793a\u4f8b\uff1a<\/p>\n<\/p>\n

import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n
matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n
matrix2 = np.array([[5, 6], [7, 8]])<\/p>\n
\u6cbf\u7740\u8f740\uff08\u884c\uff09\u62fc\u63a5<\/strong><\/h2>\n
result = np.concatenate((matrix1, matrix2), axis=0)<\/p>\n
print("\u6cbf\u7740\u8f740\u62fc\u63a5:\\n", result)<\/p>\n
\u6cbf\u7740\u8f741\uff08\u5217\uff09\u62fc\u63a5<\/strong><\/h2>\n
result = np.concatenate((matrix1, matrix2), axis=1)<\/p>\n
print("\u6cbf\u7740\u8f741\u62fc\u63a5:\\n", result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528hstack\u548cvstack\u51fd\u6570<\/h3>\n<\/p>\n
NumPy\u8fd8\u63d0\u4f9b\u4e86hstack\u548cvstack\u51fd\u6570\uff0c\u5206\u522b\u7528\u4e8e\u6c34\u5e73\u548c\u5782\u76f4\u62fc\u63a5\u77e9\u9635\u3002\u5b83\u4eec\u7684\u4f7f\u7528\u65b9\u6cd5\u76f8\u5bf9\u7b80\u5355\u3002<\/p>\n<\/p>\n
# \u4f7f\u7528hstack\u8fdb\u884c\u6c34\u5e73\u62fc\u63a5<\/p>\n
hstack_result = np.hstack((matrix1, matrix2))<\/p>\n
print("\u6c34\u5e73\u62fc\u63a5:\\n", hstack_result)<\/p>\n
\u4f7f\u7528vstack\u8fdb\u884c\u5782\u76f4\u62fc\u63a5<\/strong><\/h2>\n
vstack_result = np.vstack((matrix1, matrix2))<\/p>\n
print("\u5782\u76f4\u62fc\u63a5:\\n", vstack_result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528dstack\u51fd\u6570<\/h3>\n<\/p>\n
dstack\u51fd\u6570\u7528\u4e8e\u6cbf\u7740\u7b2c\u4e09\u4e2a\u7ef4\u5ea6\uff08\u6df1\u5ea6\uff09\u62fc\u63a5\u77e9\u9635\uff0c\u8fd9\u5728\u5904\u7406\u4e09\u7ef4\u6570\u636e\uff08\u5982\u56fe\u50cf\uff09\u65f6\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n
# \u4f7f\u7528dstack\u8fdb\u884c\u6df1\u5ea6\u62fc\u63a5<\/p>\n
dstack_result = np.dstack((matrix1, matrix2))<\/p>\n
print("\u6df1\u5ea6\u62fc\u63a5:\\n", dstack_result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e00\u3001\u4f7f\u7528NumPy\u7684concatenate\u51fd\u6570<\/h3>\n<\/p>\n
NumPy\u7684concatenate\u51fd\u6570\u53ef\u4ee5\u5728\u6307\u5b9a\u8f74\u4e0a\u62fc\u63a5\u4e24\u4e2a\u77e9\u9635\u3002\u5b83\u975e\u5e38\u7075\u6d3b\uff0c\u53ef\u4ee5\u7528\u4e8e\u5404\u79cd\u62fc\u63a5\u9700\u6c42\u3002\u4e0b\u9762\u901a\u8fc7\u8be6\u7ec6\u7684\u793a\u4f8b\u6765\u8bf4\u660e\u5982\u4f55\u4f7f\u7528\u5b83\uff1a<\/p>\n<\/p>\n
\u6cbf\u7740\u8f740\uff08\u884c\uff09\u62fc\u63a5<\/h4>\n<\/p>\n
\u5f53\u6211\u4eec\u6cbf\u7740\u8f740\u62fc\u63a5\u65f6\uff0c\u77e9\u9635\u4f1a\u6309\u7167\u884c\u8fdb\u884c\u53e0\u52a0\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n
matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n
matrix2 = np.array([[5, 6], [7, 8]])<\/p>\n
\u6cbf\u7740\u8f740\uff08\u884c\uff09\u62fc\u63a5<\/strong><\/h2>\n
result_axis_0 = np.concatenate((matrix1, matrix2), axis=0)<\/p>\n
print("\u6cbf\u7740\u8f740\u62fc\u63a5:\\n", result_axis_0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
\u6cbf\u7740\u8f740\u62fc\u63a5:<\/p>\n
 [[1 2]<\/p>\n
 [3 4]<\/p>\n
 [5 6]<\/p>\n
 [7 8]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6cbf\u7740\u8f741\uff08\u5217\uff09\u62fc\u63a5<\/h4>\n<\/p>\n
\u5f53\u6211\u4eec\u6cbf\u7740\u8f741\u62fc\u63a5\u65f6\uff0c\u77e9\u9635\u4f1a\u6309\u7167\u5217\u8fdb\u884c\u53e0\u52a0\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
# \u6cbf\u7740\u8f741\uff08\u5217\uff09\u62fc\u63a5<\/p>\n
result_axis_1 = np.concatenate((matrix1, matrix2), axis=1)<\/p>\n
print("\u6cbf\u7740\u8f741\u62fc\u63a5:\\n", result_axis_1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
\u6cbf\u7740\u8f741\u62fc\u63a5:<\/p>\n
 [[1 2 5 6]<\/p>\n
 [3 4 7 8]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u793a\u4f8b\uff0c\u53ef\u4ee5\u6e05\u695a\u5730\u770b\u5230\u5982\u4f55\u4f7f\u7528NumPy\u7684concatenate\u51fd\u6570\u5728\u4e0d\u540c\u8f74\u4e0a\u62fc\u63a5\u77e9\u9635\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528hstack\u548cvstack\u51fd\u6570<\/h3>\n<\/p>\n
hstack\u548cvstack\u51fd\u6570\u662fNumPy\u63d0\u4f9b\u7684\u4e13\u95e8\u7528\u4e8e\u6c34\u5e73\u548c\u5782\u76f4\u62fc\u63a5\u7684\u51fd\u6570\u3002\u5b83\u4eec\u5728\u62fc\u63a5\u65f6\u4e0d\u9700\u8981\u6307\u5b9a\u8f74\uff0c\u4f7f\u7528\u8d77\u6765\u66f4\u52a0\u7b80\u6d01\u3002<\/p>\n<\/p>\n
\u4f7f\u7528hstack\u8fdb\u884c\u6c34\u5e73\u62fc\u63a5<\/h4>\n<\/p>\n
\u6c34\u5e73\u62fc\u63a5\u662f\u6307\u5c06\u77e9\u9635\u5728\u6c34\u5e73\u65b9\u5411\u4e0a\u8fdb\u884c\u62fc\u63a5\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n
matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n
matrix2 = np.array([[5, 6], [7, 8]])<\/p>\n
\u4f7f\u7528hstack\u8fdb\u884c\u6c34\u5e73\u62fc\u63a5<\/strong><\/h2>\n
hstack_result = np.hstack((matrix1, matrix2))<\/p>\n
print("\u6c34\u5e73\u62fc\u63a5:\\n", hstack_result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
\u6c34\u5e73\u62fc\u63a5:<\/p>\n
 [[1 2 5 6]<\/p>\n
 [3 4 7 8]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528vstack\u8fdb\u884c\u5782\u76f4\u62fc\u63a5<\/h4>\n<\/p>\n
\u5782\u76f4\u62fc\u63a5\u662f\u6307\u5c06\u77e9\u9635\u5728\u5782\u76f4\u65b9\u5411\u4e0a\u8fdb\u884c\u62fc\u63a5\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
# \u4f7f\u7528vstack\u8fdb\u884c\u5782\u76f4\u62fc\u63a5<\/p>\n
vstack_result = np.vstack((matrix1, matrix2))<\/p>\n
print("\u5782\u76f4\u62fc\u63a5:\\n", vstack_result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
\u5782\u76f4\u62fc\u63a5:<\/p>\n
 [[1 2]<\/p>\n
 [3 4]<\/p>\n
 [5 6]<\/p>\n
 [7 8]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u793a\u4f8b\uff0c\u53ef\u4ee5\u770b\u5230\u4f7f\u7528hstack\u548cvstack\u51fd\u6570\u62fc\u63a5\u77e9\u9635\u7684\u7b80\u4fbf\u6027\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528dstack\u51fd\u6570<\/h3>\n<\/p>\n
dstack\u51fd\u6570\u7528\u4e8e\u6cbf\u7740\u7b2c\u4e09\u4e2a\u7ef4\u5ea6\uff08\u6df1\u5ea6\uff09\u62fc\u63a5\u77e9\u9635\uff0c\u8fd9\u5728\u5904\u7406\u4e09\u7ef4\u6570\u636e\u65f6\u975e\u5e38\u6709\u7528\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u77e9\u9635<\/strong><\/h2>\n
matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n
matrix2 = np.array([[5, 6], [7, 8]])<\/p>\n
\u4f7f\u7528dstack\u8fdb\u884c\u6df1\u5ea6\u62fc\u63a5<\/strong><\/h2>\n
dstack_result = np.dstack((matrix1, matrix2))<\/p>\n
print("\u6df1\u5ea6\u62fc\u63a5:\\n", dstack_result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\uff1a<\/p>\n<\/p>\n
\u6df1\u5ea6\u62fc\u63a5:<\/p>\n
 [[[1 5]<\/p>\n
  [2 6]]<\/p>\n
 [[3 7]<\/p>\n
  [4 8]]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u793a\u4f8b\uff0c\u53ef\u4ee5\u770b\u5230dstack\u51fd\u6570\u5982\u4f55\u5c06\u4e24\u4e2a\u4e8c\u7ef4\u77e9\u9635\u6cbf\u7740\u7b2c\u4e09\u4e2a\u7ef4\u5ea6\u62fc\u63a5\u6210\u4e00\u4e2a\u4e09\u7ef4\u77e9\u9635\u3002\u8fd9\u5728\u5904\u7406\u56fe\u50cf\u6570\u636e\u65f6\u975e\u5e38\u6709\u7528\uff0c\u56e0\u4e3a\u56fe\u50cf\u901a\u5e38\u662f\u4e09\u7ef4\u6570\u636e\uff08\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u3001\u989c\u8272\u901a\u9053\uff09\u3002<\/p>\n<\/p>\n
\u56db\u3001\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u62fc\u63a5\u64cd\u4f5c<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u77e9\u9635\u62fc\u63a5\u64cd\u4f5c\u975e\u5e38\u5e38\u89c1\uff0c\u5c24\u5176\u662f\u5728\u6570\u636e\u5904\u7406\u548c\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u3002\u4f8b\u5982\uff0c\u5728\u56fe\u50cf\u5904\u7406\u3001\u6570\u636e\u5408\u5e76\u7b49\u4efb\u52a1\u4e2d\uff0c\u7ecf\u5e38\u9700\u8981\u62fc\u63a5\u591a\u4e2a\u77e9\u9635\u3002<\/p>\n<\/p>\n
\u56fe\u50cf\u5904\u7406\u4e2d\u7684\u62fc\u63a5<\/h4>\n<\/p>\n
\u5728\u56fe\u50cf\u5904\u7406\u4e2d\uff0c\u56fe\u50cf\u901a\u5e38\u8868\u793a\u4e3a\u4e09\u7ef4\u77e9\u9635\uff08\u9ad8\u5ea6\u3001\u5bbd\u5ea6\u3001\u989c\u8272\u901a\u9053\uff09\u3002\u62fc\u63a5\u591a\u4e2a\u56fe\u50cf\u53ef\u4ee5\u7528\u4e8e\u6570\u636e\u589e\u5f3a\u3001\u56fe\u50cf\u62fc\u63a5\u7b49\u4efb\u52a1\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u62fc\u63a5\u4e24\u5f20\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import cv2<\/p>\n
\u8bfb\u53d6\u4e24\u5f20\u793a\u4f8b\u56fe\u50cf<\/strong><\/h2>\n
image1 = cv2.imread('image1.jpg')<\/p>\n
image2 = cv2.imread('image2.jpg')<\/p>\n
\u786e\u4fdd\u4e24\u5f20\u56fe\u50cf\u7684\u5c3a\u5bf8\u76f8\u540c<\/strong><\/h2>\n
assert image1.shape == image2.shape, "\u4e24\u5f20\u56fe\u50cf\u7684\u5c3a\u5bf8\u5fc5\u987b\u76f8\u540c"<\/p>\n
\u6c34\u5e73\u62fc\u63a5\u4e24\u5f20\u56fe\u50cf<\/strong><\/h2>\n
hstack_images = np.hstack((image1, image2))<\/p>\n
cv2.imshow('\u6c34\u5e73\u62fc\u63a5', hstack_images)<\/p>\n
\u5782\u76f4\u62fc\u63a5\u4e24\u5f20\u56fe\u50cf<\/strong><\/h2>\n
vstack_images = np.vstack((image1, image2))<\/p>\n
cv2.imshow('\u5782\u76f4\u62fc\u63a5', vstack_images)<\/p>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
cv2.destroyAllWindows()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6570\u636e\u5408\u5e76\u4e2d\u7684\u62fc\u63a5<\/h4>\n<\/p>\n
\u5728\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u6570\u636e\u96c6\u901a\u5e38\u8868\u793a\u4e3a\u77e9\u9635\u3002\u62fc\u63a5\u591a\u4e2a\u6570\u636e\u96c6\u53ef\u4ee5\u7528\u4e8e\u6570\u636e\u5408\u5e76\u3001\u7279\u5f81\u5de5\u7a0b\u7b49\u4efb\u52a1\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u62fc\u63a5\u4e24\u4e2a\u6570\u636e\u96c6\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u6570\u636e\u96c6<\/strong><\/h2>\n
data1 = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n
data2 = np.array([[7, 8, 9], [10, 11, 12]])<\/p>\n
\u6c34\u5e73\u62fc\u63a5\u4e24\u4e2a\u6570\u636e\u96c6<\/strong><\/h2>\n
hstack_data = np.hstack((data1, data2))<\/p>\n
print("\u6c34\u5e73\u62fc\u63a5\u6570\u636e\u96c6:\\n", hstack_data)<\/p>\n
\u5782\u76f4\u62fc\u63a5\u4e24\u4e2a\u6570\u636e\u96c6<\/strong><\/h2>\n
vstack_data = np.vstack((data1, data2))<\/p>\n
print("\u5782\u76f4\u62fc\u63a5\u6570\u636e\u96c6:\\n", vstack_data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u5b9e\u8df5<\/h3>\n<\/p>\n
\u5728\u4f7f\u7528NumPy\u8fdb\u884c\u77e9\u9635\u62fc\u63a5\u65f6\uff0c\u6709\u4e00\u4e9b\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u5b9e\u8df5\u9700\u8981\u9075\u5faa\uff0c\u4ee5\u786e\u4fdd\u64cd\u4f5c\u7684\u6b63\u786e\u6027\u548c\u9ad8\u6548\u6027\u3002<\/p>\n<\/p>\n
\u786e\u4fdd\u7ef4\u5ea6\u5339\u914d<\/h4>\n<\/p>\n
\u5728\u62fc\u63a5\u77e9\u9635\u4e4b\u524d\uff0c\u5fc5\u987b\u786e\u4fdd\u77e9\u9635\u5728\u62fc\u63a5\u65b9\u5411\u4e0a\u7684\u7ef4\u5ea6\u5339\u914d\u3002\u4f8b\u5982\uff0c\u5728\u6c34\u5e73\u62fc\u63a5\u65f6\uff0c\u77e9\u9635\u7684\u884c\u6570\u5fc5\u987b\u76f8\u540c\uff1b\u5728\u5782\u76f4\u62fc\u63a5\u65f6\uff0c\u77e9\u9635\u7684\u5217\u6570\u5fc5\u987b\u76f8\u540c\u3002\u5982\u679c\u7ef4\u5ea6\u4e0d\u5339\u914d\uff0c\u4f1a\u5bfc\u81f4\u9519\u8bef\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efa\u4e24\u4e2a\u793a\u4f8b\u77e9\u9635\uff0c\u7ef4\u5ea6\u4e0d\u5339\u914d<\/strong><\/h2>\n
matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n
matrix2 = np.array([[5, 6]])<\/p>\n
\u5c1d\u8bd5\u6c34\u5e73\u62fc\u63a5\uff0c\u4f1a\u5bfc\u81f4\u9519\u8bef<\/strong><\/h2>\n
try:<\/p>\n
    result = np.hstack((matrix1, matrix2))<\/p>\n
except ValueError as e:<\/p>\n
    print("\u9519\u8bef:", e)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f18\u5316\u6027\u80fd<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u5927\u89c4\u6a21\u6570\u636e\uff0c\u77e9\u9635\u62fc\u63a5\u64cd\u4f5c\u53ef\u80fd\u4f1a\u5360\u7528\u5927\u91cf\u5185\u5b58\u548c\u8ba1\u7b97\u8d44\u6e90\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u4f18\u5316\u6027\u80fd\u7684\u5efa\u8bae\uff1a<\/p>\n<\/p>\n
    \n
  1. \u9884\u5206\u914d\u5185\u5b58<\/strong>\uff1a\u9884\u5148\u5206\u914d\u62fc\u63a5\u540e\u77e9\u9635\u7684\u5185\u5b58\uff0c\u4ee5\u907f\u514d\u591a\u6b21\u5185\u5b58\u5206\u914d\u3002<\/li>\n
  2. \u4f7f\u7528in-place\u64cd\u4f5c<\/strong>\uff1a\u5982\u679c\u53ef\u80fd\uff0c\u4f7f\u7528in-place\u64cd\u4f5c\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\u3002<\/li>\n
  3. \u6279\u91cf\u5904\u7406<\/strong>\uff1a\u5c06\u5927\u89c4\u6a21\u6570\u636e\u5206\u6279\u5904\u7406\uff0c\u4ee5\u51cf\u5c11\u5355\u6b21\u64cd\u4f5c\u7684\u5185\u5b58\u5360\u7528\u3002<\/li>\n<\/ol>\n
    import numpy as np<\/p>\n
    \u521b\u5efa\u5927\u89c4\u6a21\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
    large_matrix1 = np.random.rand(10000, 1000)<\/p>\n
    large_matrix2 = np.random.rand(10000, 1000)<\/p>\n
    \u9884\u5206\u914d\u5185\u5b58<\/strong><\/h2>\n
    result = np.empty((large_matrix1.shape[0], large_matrix1.shape[1] + large_matrix2.shape[1]))<\/p>\n
    \u6267\u884c\u62fc\u63a5\u64cd\u4f5c<\/strong><\/h2>\n
    result[:, :large_matrix1.shape[1]] = large_matrix1<\/p>\n
    result[:, large_matrix1.shape[1]:] = large_matrix2<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u901a\u8fc7\u4e0a\u8ff0\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u5b9e\u8df5\uff0c\u53ef\u4ee5\u786e\u4fdd\u77e9\u9635\u62fc\u63a5\u64cd\u4f5c\u7684\u6b63\u786e\u6027\u548c\u9ad8\u6548\u6027\u3002<\/p>\n<\/p>\n
    \u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
    \u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528NumPy\u5e93\u62fc\u63a5\u4e24\u4e2a\u77e9\u9635\u3002\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528NumPy\u7684concatenate\u51fd\u6570\u3001\u4f7f\u7528hstack\u548cvstack\u51fd\u6570\u3001\u4f7f\u7528dstack\u51fd\u6570\u3002\u6211\u4eec\u8fd8\u4ecb\u7ecd\u4e86\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u62fc\u63a5\u64cd\u4f5c\uff0c\u4ee5\u53ca\u5728\u4f7f\u7528NumPy\u8fdb\u884c\u77e9\u9635\u62fc\u63a5\u65f6\u7684\u4e00\u4e9b\u6ce8\u610f\u4e8b\u9879\u548c\u6700\u4f73\u5b9e\u8df5\u3002<\/p>\n<\/p>\n
    \u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\u548c\u6280\u5de7\uff0c\u53ef\u4ee5\u5728\u6570\u636e\u5904\u7406\u3001\u673a\u5668\u5b66\u4e60\u3001\u56fe\u50cf\u5904\u7406\u7b49\u9886\u57df\u9ad8\u6548\u5730\u8fdb\u884c\u77e9\u9635\u62fc\u63a5\u64cd\u4f5c\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff0c\u5e76\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u80fd\u591f\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u6280\u5de7\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u5b9e\u73b0\u77e9\u9635\u7684\u62fc\u63a5\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u77e9\u9635\u7684\u62fc\u63a5\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u6700\u5e38\u7528\u7684\u662f\u5229\u7528NumPy\u5e93\u3002\u4f7f\u7528NumPy\u7684np.concatenate<\/code>\u3001np.vstack<\/code>\u548cnp.hstack<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u884c\u62fc\u63a5\u6216\u5217\u62fc\u63a5\u3002\u4f8b\u5982\uff0cnp.concatenate((matrix1, matrix2), axis=0)<\/code>\u53ef\u5c06\u4e24\u4e2a\u77e9\u9635\u6309\u884c\u62fc\u63a5\uff0c\u800c\u4f7f\u7528axis=1<\/code>\u5219\u53ef\u6309\u5217\u62fc\u63a5\u3002<\/p>\n
    \u77e9\u9635\u62fc\u63a5\u65f6\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u4e8b\u9879\uff1f<\/strong>
    \u5728\u62fc\u63a5\u77e9\u9635\u65f6\uff0c\u5fc5\u987b\u786e\u4fdd\u5f85\u62fc\u63a5\u7684\u77e9\u9635\u5728\u62fc\u63a5\u7684\u7ef4\u5ea6\u4e0a\u5177\u6709\u76f8\u540c\u7684\u5f62\u72b6\u3002\u4f8b\u5982\uff0c\u82e5\u8981\u6309\u884c\u62fc\u63a5\uff0c\u4e24\u4e2a\u77e9\u9635\u7684\u5217\u6570\u9700\u8981\u4e00\u81f4\uff1b\u800c\u82e5\u6309\u5217\u62fc\u63a5\uff0c\u5219\u8981\u6c42\u884c\u6570\u76f8\u540c\u3002\u5426\u5219\uff0c\u62fc\u63a5\u64cd\u4f5c\u5c06\u4f1a\u5f15\u53d1\u9519\u8bef\u3002<\/p>\n
    \u662f\u5426\u53ef\u4ee5\u5728\u4e0d\u4f7f\u7528NumPy\u7684\u60c5\u51b5\u4e0b\u62fc\u63a5\u77e9\u9635\uff1f<\/strong>
    \u5f53\u7136\u53ef\u4ee5\u3002\u5728Python\u7684\u539f\u751f\u5217\u8868\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u7684+<\/code>\u64cd\u4f5c\u7b26\u6765\u62fc\u63a5\u4e24\u4e2a\u4e8c\u7ef4\u5217\u8868\uff0c\u5c3d\u7ba1\u8fd9\u5e76\u4e0d\u7b49\u540c\u4e8e\u77e9\u9635\u62fc\u63a5\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u662f\u8db3\u591f\u7684\u3002\u4f8b\u5982\uff0cmatrix1 + matrix2<\/code>\u5c06\u4e24\u4e2a\u5217\u8868\u6309\u884c\u8fde\u63a5\u3002\u4e0d\u8fc7\uff0c\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u65f6\uff0c\u4f7f\u7528NumPy\u4f1a\u66f4\u9ad8\u6548\u548c\u65b9\u4fbf\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2a\u5e93\u6765\u62fc\u63a5\u4e24\u4e2a\u77e9\u9635\uff0c\u6700\u5e38\u7528\u7684\u5e93\u662fNumPy\u3002\u4f7f\u7528NumPy\u7684concatenate […]","protected":false},"author":3,"featured_media":1033452,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1033449"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1033449"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1033449\/revisions"}],"predecessor-version":[{"id":1033453,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1033449\/revisions\/1033453"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1033452"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1033449"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1033449"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1033449"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}