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#main-title{ | ||
margin-top: 180px; | ||
@font-face { | ||
font-family: Dancing_Script; | ||
src: url("../DancingScript-Bold.ttf"); | ||
} | ||
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#main-title { | ||
margin-top: 1px; | ||
font-family: Dancing_Script, "Rakkas", "Alegreya", "Lora"; | ||
font-size: 3em; | ||
font-weight: bold; | ||
} | ||
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.home .hero img { | ||
max-width: 100%; | ||
max-height: 155px; | ||
display: block; | ||
margin: 3rem auto 1.5rem; | ||
} |
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window.onload = function () { | ||
var heroimg = document.querySelectorAll('.hero img'); | ||
if (heroimg.length !== 0) { | ||
heroimg[0].style.maxHeight = '155px'; | ||
} | ||
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--- | ||
home: true | ||
# heroImage: /blank.png | ||
heroImage: /blank.png | ||
heroText: PyCINRAD | ||
tagline: 国内最强大的雷达数据处理工具 | ||
actionText: 快速上手 → | ||
actionLink: /install/ | ||
lang: zh-CN | ||
features: | ||
- title: 格式大师 | ||
details: 支持多种CINRAD雷达数据格式,兼容性强,横扫CMA雷达基数据和产品,国内首个支持“探测中心拼图3.0”。 | ||
details: 支持多种CINRAD雷达数据格式,兼容性强,横扫CMA雷达基数据和产品,国内率先支持“探测中心拼图3.0”。 | ||
- title: 计算达人 | ||
details: 快速提取、计算雷达衍生产品,如组合反射率CR、回波顶高ET、降水粒子分类HCL等。 | ||
- title: 广为人知 | ||
details: 作为一个开源项目,PyCINRAD对所有用户免费开放,鼓励社区贡献和改进。据悉已遍布CMA的各个系统角落。 | ||
footer: MIT Licensed | Copyright © 2024-present CyanideCN & Pysoer. | ||
--- | ||
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::: slot footer | ||
MIT Licensed | Copyright © 2024-present CyanideCN & Pysoer. [湘ICP备2024085395号-2](https://beian.miit.gov.cn/#/Integrated/index) | ||
::: |
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# 简介 | ||
`PyCINRAD`是一个专为解码和可视化中国新一代天气雷达(CINRAD)数据而设计的Python模块。它堪称气象数据领域的超级明星,为气象科研人员、天气预报员及气象爱好者提供了一个高效、便捷的雷达数据解决方案。 | ||
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* **数据支持全面** 无论是旧版本还是新标准的数据,PyCINRAD都能轻松应对。通过其强大的数据处理能力,用户可以快速提取所需信息,进行复合反射率、回波顶高、垂直积分液态含水量等多种雷达衍生产品的计算。此外,数据校正功能如速度退模糊等,确保了数据的准确性和可靠性。 | ||
* **数据支持全面** 全面支持标准格式基数据(包括X波段相控阵)、ROSE2产品、探测中心拼图、SWAN产品等等。通过其强大的数据处理能力,用户可以快速提取所需信息,进行组合反射率、回波顶高、垂直积分液态含水量、降水粒子分类等多种雷达衍生产品的计算。此外还支持数据校正功能如速度退模糊等。 | ||
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* **出色的可视化** 支持PPI(平面位置显示)和Section(剖面)等多种可视化方式,用户可以自定义绘图参数,实现高度个性化的数据展示。这些功能使得气象数据的解读和分析变得更加直观和便捷。 | ||
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* **易于安装和使用** 它兼容Python 3.9及以上版本,支持通过pip快速安装。此外,丰富的文档和示例代码,以及活跃的开发者社区,使得用户在使用过程中能够获得及时的帮助和支持。 | ||
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* **永久开源** 作为一个开源项目,PyCINRAD对所有用户免费开放,鼓励社区贡献和改进。它的应用场景广泛,包括但不限于气象研究、天气预报、灾害预警以及教育培训等。无论是在学术研究还是实际应用中,PyCINRAD都展现出了其无与伦比的价值和潜力。 | ||
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PyCINRAD是一个功能全面、易于上手且高度可定制的气象雷达数据处理与可视化库。它让气象数据的处理和分析变得更加简单、高效和直观,是气象领域不可或缺的一款工具。 | ||
PyCINRAD是一个功能全面、易于上手且高度可定制的气象雷达数据处理与可视化库。让气象数据的处理和分析变得更加简单、高效和直观,是气象领域不可或缺的一款工具。 | ||
源码地址:[https://github.com/CyanideCN/PyCINRAD](https://github.com/CyanideCN/PyCINRAD) | ||
QQ群:`480305660` |
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# 安装 | ||
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本文档运行的cinrad 版本为`v1.9.2`,Python 版本要求: `3.9+` 至于`cartopy`,`numpy`,`matplotlib`等库,安装最新版即可,`cartopy`版本>0.22。 | ||
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安装方法 ①: | ||
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```python | ||
pip install cartopy matplotlib numpy -U | ||
pip install cinrad -U | ||
``` | ||
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网速慢的话,在上面命令后边加上 `-i https://pypi.tuna.tsinghua.edu.cn/simple` | ||
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安装方法 ②:请先安装[git](https://blog.csdn.net/weixin_42242910/article/details/136297201) | ||
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```bash | ||
D: # 进入D盘,因为C盘权限会不够 | ||
pip uninstall cinrad # 卸载当前版本 | ||
git clone https://github.com/CyanideCN/PyCINRAD.git | ||
cd PyCINRAD | ||
python setup.py install | ||
``` | ||
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pip安装报错: Microsoft Visual C++ 14.0 or greater is required. Get it with “Microsoft C++ Build Tools“ | ||
[https://blog.csdn.net/zymhhh/article/details/140642202](https://blog.csdn.net/zymhhh/article/details/140642202) | ||
参考这个方法,把右边那些该勾上的都勾上。特别是windows xx SDK |
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# 开始测试 | ||
- 运行代码时,需要import导入cinrad,示例如下。 | ||
- 说明:本文中的所有数据,雷达站所在的经纬度都作了**脱密,站号均改成了Z9999**,因此画图的位置是错的,请忽略。 | ||
```python | ||
import cinrad | ||
import cartopy | ||
from cinrad.visualize import PPI | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
import datetime | ||
%matplotlib inline #这一句只在jupyter notebook中使用,在编辑器或命令行运行请删掉 | ||
import warnings | ||
warnings.filterwarnings("ignore") | ||
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# 这里是我测试的数据文件目录,请根据实际情况修改 | ||
basePath = "d:/temp/" # 数据存放路径 | ||
print(cinrad.__version__) # 打印cinrad版本 | ||
print(np.__version__) # 打印numpy版本 | ||
print(cartopy.__version__) # 打印cartopy版本 | ||
``` | ||
```md | ||
1.9.2 | ||
2.0.2 | ||
0.23.0 | ||
``` |
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