{"id":1027376,"date":"2024-12-31T10:50:26","date_gmt":"2024-12-31T02:50:26","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1027376.html"},"modified":"2024-12-31T10:50:28","modified_gmt":"2024-12-31T02:50:28","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%94%bb%e6%a8%b1%e8%8a%b1%e6%a0%91%e6%ad%a5%e9%aa%a4","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1027376.html","title":{"rendered":"\u5982\u4f55\u7528python\u753b\u6a31\u82b1\u6811\u6b65\u9aa4"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u753b\u6a31\u82b1\u6811\u6b65\u9aa4\"<\/p>\n

\u5982\u4f55\u7528Python\u753b\u6a31\u82b1\u6811\u6b65\u9aa4<\/h3>\n<\/p>\n

\u4f7f\u7528Python\u753b\u6a31\u82b1\u6811\u7684\u6b65\u9aa4\u5305\u62ec\uff1a\u5b89\u88c5\u5fc5\u8981\u7684\u5e93\u3001\u8bbe\u7f6e\u753b\u5e03\u3001\u7ed8\u5236\u6811\u5e72\u548c\u6811\u679d\u3001\u751f\u6210\u6a31\u82b1\u4f4d\u7f6e\u3001\u7ed8\u5236\u6a31\u82b1\u3001\u589e\u52a0\u7ec6\u8282\u3002<\/strong>\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u6bcf\u4e00\u4e2a\u6b65\u9aa4\u53ca\u5176\u5b9e\u73b0\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u7ed8\u5236\u6a31\u82b1\u6811\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u5fc5\u8981\u7684Python\u5e93\uff0c\u5305\u62ecmatplotlib\u3001numpy\u548cPIL\uff08Pillow\uff09\u3002\u8fd9\u4e9b\u5e93\u5c06\u5e2e\u52a9\u6211\u4eec\u521b\u5efa\u548c\u5904\u7406\u56fe\u50cf\u3002<\/p>\n<\/p>\n

pip install matplotlib numpy pillow<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bbe\u7f6e\u753b\u5e03<\/h3>\n<\/p>\n
\u5728\u7ed8\u5236\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u753b\u5e03\u6765\u5bb9\u7eb3\u6211\u4eec\u7684\u6a31\u82b1\u6811\u3002\u5728Python\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib\u5e93\u6765\u521b\u5efa\u753b\u5e03\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u56fe\u5f62<\/strong><\/h2>\n
fig, ax = plt.subplots(figsize=(10, 10))<\/p>\n
\u8bbe\u7f6e\u80cc\u666f\u989c\u8272\u4e3a\u767d\u8272<\/strong><\/h2>\n
fig.patch.set_facecolor('white')<\/p>\n
\u9690\u85cf\u5750\u6807\u8f74<\/strong><\/h2>\n
ax.axis('off')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u7ed8\u5236\u6811\u5e72\u548c\u6811\u679d<\/h3>\n<\/p>\n
\u6811\u5e72\u548c\u6811\u679d\u662f\u6a31\u82b1\u6811\u7684\u4e3b\u8981\u7ed3\u6784\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u9012\u5f52\u65b9\u6cd5\u6765\u7ed8\u5236\u6811\u5e72\u548c\u6811\u679d\u3002\u9012\u5f52\u65b9\u6cd5\u5141\u8bb8\u6211\u4eec\u901a\u8fc7\u91cd\u590d\u76f8\u540c\u7684\u6b65\u9aa4\u6765\u521b\u5efa\u66f4\u590d\u6742\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
def draw_branch(x, y, angle, length, width, ax, depth=0):<\/p>\n
    if length < 2 or width < 0.5 or depth > 10:<\/p>\n
        return<\/p>\n
    # \u8ba1\u7b97\u6811\u679d\u7684\u7ec8\u70b9<\/p>\n
    x_end = x + length * np.cos(angle)<\/p>\n
    y_end = y + length * np.sin(angle)<\/p>\n
    # \u7ed8\u5236\u6811\u679d<\/p>\n
    ax.plot([x, x_end], [y, y_end], color='brown', lw=width)<\/p>\n
    # \u9012\u5f52\u7ed8\u5236\u5b50\u6811\u679d<\/p>\n
    draw_branch(x_end, y_end, angle + np.pi\/6, length * 0.7, width * 0.7, ax, depth+1)<\/p>\n
    draw_branch(x_end, y_end, angle - np.pi\/6, length * 0.7, width * 0.7, ax, depth+1)<\/p>\n
\u7ed8\u5236\u6811\u5e72<\/strong><\/h2>\n
draw_branch(0, -200, np.pi\/2, 100, 10, ax)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u751f\u6210\u6a31\u82b1\u4f4d\u7f6e<\/h3>\n<\/p>\n
\u4e3a\u4e86\u4f7f\u6a31\u82b1\u770b\u8d77\u6765\u66f4\u52a0\u81ea\u7136\uff0c\u6211\u4eec\u9700\u8981\u968f\u673a\u751f\u6210\u6a31\u82b1\u7684\u4f4d\u7f6e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528numpy\u5e93\u6765\u751f\u6210\u968f\u673a\u7684\u6a31\u82b1\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n
# \u751f\u6210\u6a31\u82b1\u4f4d\u7f6e<\/p>\n
num_flowers = 500<\/p>\n
x_flowers = np.random.uniform(-200, 200, num_flowers)<\/p>\n
y_flowers = np.random.uniform(-200, 200, num_flowers)<\/p>\n
\u8fc7\u6ee4\u6389\u4e0d\u5728\u6811\u679d\u4e0a\u7684\u6a31\u82b1<\/strong><\/h2>\n
mask = y_flowers < 0.7 * np.abs(x_flowers) - 100<\/p>\n
x_flowers = x_flowers[~mask]<\/p>\n
y_flowers = y_flowers[~mask]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u7ed8\u5236\u6a31\u82b1<\/h3>\n<\/p>\n
\u6a31\u82b1\u662f\u6a31\u82b1\u6811\u7684\u91cd\u70b9\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528PIL\u5e93\u7ed8\u5236\u6a31\u82b1\u3002\u6a31\u82b1\u53ef\u4ee5\u88ab\u7ed8\u5236\u6210\u5c0f\u5706\u5f62\uff0c\u5e76\u968f\u673a\u5206\u5e03\u5728\u6811\u679d\u4e0a\u3002<\/p>\n<\/p>\n
from PIL import Image, ImageDraw<\/p>\n
def draw_flower(ax, x, y):<\/p>\n
    flower_size = np.random.uniform(1, 3)<\/p>\n
    circle = plt.Circle((x, y), flower_size, color='pink', ec='pink')<\/p>\n
    ax.add_patch(circle)<\/p>\n
\u7ed8\u5236\u6a31\u82b1<\/strong><\/h2>\n
for x, y in zip(x_flowers, y_flowers):<\/p>\n
    draw_flower(ax, x, y)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u589e\u52a0\u7ec6\u8282<\/h3>\n<\/p>\n
\u4e3a\u4e86\u4f7f\u6a31\u82b1\u6811\u66f4\u52a0\u903c\u771f\uff0c\u6211\u4eec\u53ef\u4ee5\u589e\u52a0\u4e00\u4e9b\u7ec6\u8282\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u6dfb\u52a0\u4e00\u4e9b\u5c0f\u7684\u5206\u679d\u6216\u66f4\u591a\u7684\u6a31\u82b1\u3002\u6b64\u5916\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u8c03\u6574\u989c\u8272\u548c\u5927\u5c0f\uff0c\u4f7f\u6a31\u82b1\u6811\u770b\u8d77\u6765\u66f4\u52a0\u81ea\u7136\u3002<\/p>\n<\/p>\n
# \u589e\u52a0\u66f4\u591a\u7684\u6a31\u82b1<\/p>\n
num_extra_flowers = 200<\/p>\n
x_extra_flowers = np.random.uniform(-200, 200, num_extra_flowers)<\/p>\n
y_extra_flowers = np.random.uniform(-200, 200, num_extra_flowers)<\/p>\n
\u8fc7\u6ee4\u6389\u4e0d\u5728\u6811\u679d\u4e0a\u7684\u6a31\u82b1<\/strong><\/h2>\n
mask = y_extra_flowers < 0.7 * np.abs(x_extra_flowers) - 100<\/p>\n
x_extra_flowers = x_extra_flowers[~mask]<\/p>\n
y_extra_flowers = y_extra_flowers[~mask]<\/p>\n
\u7ed8\u5236\u989d\u5916\u7684\u6a31\u82b1<\/strong><\/h2>\n
for x, y in zip(x_extra_flowers, y_extra_flowers):<\/p>\n
    draw_flower(ax, x, y)<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u6210\u529f\u5730\u4f7f\u7528Python\u7ed8\u5236\u4e86\u4e00\u68f5\u6a31\u82b1\u6811\u3002\u60a8\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8c03\u6574\u53c2\u6570\uff0c\u4ee5\u521b\u5efa\u4e0d\u540c\u98ce\u683c\u7684\u6a31\u82b1\u6811\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\uff0c\u795d\u60a8\u7ed8\u56fe\u6109\u5feb\uff01<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684Python\u5e93\u6765\u7ed8\u5236\u6a31\u82b1\u6811\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u6709\u51e0\u4e2a\u5e93\u53ef\u4ee5\u5e2e\u52a9\u4f60\u7ed8\u5236\u6a31\u82b1\u6811\uff0c\u5982Matplotlib\u3001Turtle\u548cPygame\u3002\u6bcf\u4e2a\u5e93\u90fd\u6709\u5176\u72ec\u7279\u7684\u529f\u80fd\u548c\u9002\u7528\u573a\u666f\u3002Matplotlib\u9002\u5408\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4f46\u4e5f\u53ef\u4ee5\u7528\u6765\u521b\u5efa\u7b80\u5355\u7684\u56fe\u5f62\u3002Turtle\u662f\u4e00\u4e2a\u9002\u5408\u521d\u5b66\u8005\u7684\u5e93\uff0c\u80fd\u591f\u901a\u8fc7\u7b80\u5355\u7684\u6307\u4ee4\u7ed8\u5236\u590d\u6742\u7684\u56fe\u5f62\u3002\u800cPygame\u5219\u66f4\u9002\u5408\u9700\u8981\u52a8\u753b\u548c\u4e92\u52a8\u7684\u56fe\u5f62\u9879\u76ee\u3002\u9009\u62e9\u5408\u9002\u7684\u5e93\u53d6\u51b3\u4e8e\u4f60\u7684\u9700\u6c42\u548c\u7f16\u7a0b\u6c34\u5e73\u3002<\/p>\n
\u5982\u4f55\u6784\u5efa\u6a31\u82b1\u6811\u7684\u57fa\u672c\u5f62\u72b6\u4e0e\u989c\u8272\uff1f<\/strong>
\u5728\u7ed8\u5236\u6a31\u82b1\u6811\u65f6\uff0c\u57fa\u7840\u5f62\u72b6\u901a\u5e38\u5305\u62ec\u6811\u5e72\u548c\u6811\u51a0\u3002\u6811\u5e72\u53ef\u4ee5\u4f7f\u7528\u7b80\u5355\u7684\u77e9\u5f62\u6216\u591a\u8fb9\u5f62\u8868\u793a\uff0c\u800c\u6811\u51a0\u5219\u53ef\u4ee5\u901a\u8fc7\u5706\u5f62\u6216\u692d\u5706\u5f62\u8868\u793a\u3002\u4e3a\u4e86\u589e\u52a0\u771f\u5b9e\u611f\uff0c\u53ef\u4ee5\u4f7f\u7528\u6e10\u53d8\u8272\u6216\u4e0d\u540c\u7684\u7c89\u8272\u8c03\u6765\u8868\u793a\u6a31\u82b1\u7684\u82b1\u74e3\u3002\u5229\u7528Python\u5e93\u4e2d\u7684\u989c\u8272\u586b\u5145\u529f\u80fd\uff0c\u53ef\u4ee5\u8ba9\u4f60\u7684\u6a31\u82b1\u6811\u770b\u8d77\u6765\u66f4\u52a0\u751f\u52a8\u3002<\/p>\n
\u5982\u4f55\u6dfb\u52a0\u52a8\u6001\u6548\u679c\u6216\u52a8\u753b\u5230\u6a31\u82b1\u6811\u7684\u7ed8\u5236\u4e2d\uff1f<\/strong>
\u5982\u679c\u5e0c\u671b\u4f60\u7684\u6a31\u82b1\u6811\u66f4\u52a0\u751f\u52a8\uff0c\u53ef\u4ee5\u8003\u8651\u6dfb\u52a0\u52a8\u6001\u6548\u679c\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u901a\u8fc7\u6539\u53d8\u82b1\u74e3\u7684\u900f\u660e\u5ea6\u6216\u989c\u8272\u6765\u6a21\u62df\u98ce\u5439\u52a8\u82b1\u74e3\u7684\u6548\u679c\u3002\u4f7f\u7528Turtle\u5e93\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u5faa\u73af\u548c\u65f6\u95f4\u5ef6\u8fdf\u5b9e\u73b0\u7b80\u5355\u7684\u52a8\u753b\u6548\u679c\u3002\u800c\u5728Pygame\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u66f4\u65b0\u663e\u793a\u5c4f\u548c\u5904\u7406\u4e8b\u4ef6\u6765\u5b9e\u73b0\u66f4\u590d\u6742\u7684\u52a8\u753b\u3002\u8fd9\u6837\u7684\u52a8\u6001\u6548\u679c\u4f1a\u8ba9\u4f60\u7684\u6a31\u82b1\u6811\u66f4\u52a0\u5f15\u4eba\u6ce8\u76ee\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u753b\u6a31\u82b1\u6811\u6b65\u9aa4 \u4f7f\u7528Python\u753b\u6a31\u82b1\u6811\u7684\u6b65\u9aa4\u5305\u62ec\uff1a\u5b89\u88c5\u5fc5\u8981\u7684\u5e93\u3001\u8bbe\u7f6e\u753b\u5e03\u3001\u7ed8\u5236\u6811\u5e72\u548c\u6811\u679d\u3001\u751f […]","protected":false},"author":3,"featured_media":1027381,"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\/1027376"}],"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=1027376"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1027376\/revisions"}],"predecessor-version":[{"id":1027386,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1027376\/revisions\/1027386"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1027381"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1027376"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1027376"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1027376"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}