▍1. 锐角检查工具
说明: 在arcgis10.0以上版本使用,快速检查图斑的尖锐角,并定位到其存在尖锐角的位置(obtuse angle inspection tool)
说明: 在arcgis10.0以上版本使用,快速检查图斑的尖锐角,并定位到其存在尖锐角的位置(obtuse angle inspection tool)
说明: 用python语言调用了皮尔逊相关系数的应用,里面包含了文件的打开关闭程序(The application of Pearson correlation coefficient is called with Python language, which contains the program of opening and closing files)
说明: 是《Python语言在ABAQUS中的应用》书中源码,可以为学习Python和ABAQUS的同学提供很好的资料。(Is "Python language in ABAQUS application" book source code, can provide python and ABAQUS students very good information.)
说明: 基于CNN+CTC 隐马尔科夫模型的语音识别(base on CNN+CTC, AUTO SPEECH RECOGNIZATION)
说明: 地理信息处理和下载工具,基于QGIS 和GEE,希望对您有所帮助(based on Qgis and GEE)
说明: 去混响的一个很好用的文件,在github上面下载的(To reverb a very useful file, downloaded from GitHub)
说明: 读取.pacp文件,提取里面的icmp、ip、udp等字段信息。 。。。。(Read the .pacp file and extract the icmp, ip, udp and other field information.)
说明: 根据洗浴事件识别模型,对不同地区的用户的用水进行识别(According to the bathing event recognition model, the water consumption of users in different areas is identified)
说明: 机器学习的相关内容,通过数据训练,实现线性回归预测问题。(Through data training, the problem of linear regression prediction is realized.)
说明: 这是一个lammps示例,内容是Ti原子在金刚石基材上的溅射过程。包括了用python写的用于生成Ti原子初始能量的脚本,lammps的输入脚本使用了官方提供的Pylammps接口来。具体的过程见readme文件夹中的readme.md(This is an example of lammps in which Ti atoms are sputtered on a diamond substrate. The script written in Python is used to generate the initial energy of Ti atom. The input script of lammps uses the official pylammps interface. For details, see the readme.md)
根据文件名判断是json还是csv并进行相应的转化(Judge whether it is JSON or CSV according to the file name and translate it accordingly)
说明: 根据文件名判断是json还是csv并进行相应的转化(Judge whether it is JSON or CSV according to the file name and translate it accordingly)
说明: DNGR(Deep neural networks for learning graph representations) code
说明: 基于python的LSTM做股票预测源代码(Based on Python LSTM stock forecast source code)
说明: 对蘑菇是否有毒进行二分类,采用朴素贝叶斯算法(Whether mushrooms are poisonous or not is classified by naive Bayes algorithm)
说明: 用深度学习生成模型GAN实现时间序列预测,(Time series prediction is realized by using Gan model)
说明: 很好的python学习书籍,很适合新手学习,推荐(Very good Python learning books, very suitable for beginners to learn, recommended)
一个简单的LSTM神经网络训练的python代码(A simple LSTM neural network training Python code)