python 导入文件绘图代码

python语言提取odb文件中某个节点集合的应力值(get the mises stress for a node set)

sample python programs

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

Keras是一个高层神经网络库， Keras由纯Python编写而成并基Tensorflow或Theano。 Keras 为支持快 速实验而生，能够把你的idea迅速转换为结果，如果你有如下需求，请选择Keras： 简易和快速的原型设计（keras具有高度模块化，极简，和可扩充特性） 支持CNN和RNN，或二者的结合 支持任意的链接方案（包括多输入和多输出训练） 无缝CPU和GPU切换(Keras is a high-level neural network library. Keras is written from pure Python and is based on Tensorflow or Theano. Keras support fast Quick experimentation can transform your idea into results quickly. If you have the following requirements, please choose Keras: Simple and fast prototyping (keras is highly modular, minimized, and extensible). Support for CNN and RNN or the combination of the two Supports arbitrary link schemes (including multiple input and multiple output training). Seamless CPU and GPU handoff)

说明：  高斯羽烟模型python代码，模拟中质气体的连续泄漏扩散，瞬时源的是高斯烟团模型(Gaussion plume model in Python.)

cmod5 python code has been used in python to find out wind speed

说明：  平均场的python代码，大家有需要可以看看(Python code about mean field. You can download if you need.)

读取地震数据并进行SVM训练分类，针对特殊数据进行训练。输入：坐标，输出：标签(Read seismic data and conduct SVM training classification, training for special data. Input: coordinate, output: Label)

语音端点监测，用于检测一个单词或一段语音结束后的静默区间，主要用于人工智能语音识别(voice detection, used to detect the symbol of finish of one word or one graph, mainly for AI speech recognition)

基础的强化学习Q-learning算法，对初学者对Q-learning算法得理解比较有帮助，程序包括运行脚本，Q-learning算法脚本以及环境脚本。(Basic reinforcement learning Q-learning algorithm is helpful for beginners to understand Q-learning algorithm. Programs include running script, Q-learning algorithm script and environment script.)