Surface Plot of Dini's Surface Using Mesh Command in MATLAB

使用stlread加载矩阵时，利用PatchSlim可以有效减小顶点矩阵的大小。表面网格通常包含重复顶点。此函数会解析点列表，查找并移除v（顶点）矩阵中的所有重复条目，并相应更新f（面）矩阵的索引。通常，这会显著减少补丁矩阵的大小。请注意，在非常大的网格上运行可能会需要较长时间。在加载STL文件后，我使用此工具来优化表面网格尺寸。用法：[v, f]=patchslim(v, f)。更多信息请访问： STL File Reader和Esmonde-White's Site

MATLAB 空间 散点插值 绘制 曲面 源代码示例： % 生成随机散点 x = rand(1, 100); y = rand(1, 100); z = sin(2*pi*x) + cos(2*pi*y); % 创建网格 [xq, yq] = meshgrid(linspace(0, 1, 100), linspace(0, 1, 100)); % 插值 zq = griddata(x, y, z, xq, yq, 'cubic'); % 绘制曲面 surf(xq, yq, zq); shading interp; colorbar; title('MATLAB 散点插值曲面'); 此代码使用 griddata 函数进行 散点插值，绘制出的 曲面 为插值结果的可视化。

该工具箱包含了各种绘制NURBS曲线和NURBS曲面的程序。对于从事曲面设计或相关领域的工作者来说，非常有用；同时，也为学习MATLAB编程提供了强大的支持，帮助用户更好地掌握该语言的应用。

FSSF2是一款用于在分散的3D数据上拟合2-D傅立叶级数表面的工具，支持系列配方优化拟合。该工具具备直观的GUI界面。

本模型用于捕捉球落在非理想表面的轨迹，具有一定的恢复系数。用户可以调整该系数，以查看不同情况下的运动结果。

PM_Solver_Matlab is an FEM solver developed using MATLAB for synchronous motors, with a focus on surface-mounted permanent magnet motors. Some of the code is based on or modified from Smeklib().

ESP-DNN: Graph Convolutional Deep Neural Network for Predicting Electrostatic Potential Surfaces from DFT Calculations This repository contains trained models and code designed for generating ligands and proteins, creating electrostatic potential (ESP) surfaces that closely resemble DFT-quality molecular surfaces. The PQR files generated by our model include atomic charges and dipole-like atomic features, such as lone pairs, σ-conjugation, and p-orbitals. To generate ligand PQR files, a graph convolutional deep neural network (DNN) model was trained on about 100,000 molecules with ESP surfaces derived from DFT calculations. For proteins, parameterized charges of amino acids were used, ensuring compatibility with the ligand ESP surfaces generated by the DNN model. For more detailed methods and validation information, refer to the full documentation. System Requirements The program can only run on 64-bit Linux operating systems. Installation Instructions To run ESP-DNN, you will need to:1. Clone this repository.2. Set up Python and required dependencies.3. (Optional) Install additional packages. The package has been developed and tested with Python 2.7 and the following third-party libraries:- rdkit == 2018.09.3- keras == 2.2.4- tensorflow == 1.10.0- num

Euler's Formula for Pi Calculation in MATLAB provides a versatile algorithm collection where users can contribute implementations in any language. This repository follows a structured format for adding algorithms in different languages. For example, if you are adding a Hamiltonian Path algorithm in Java, use the following folder structure: /BackTracking/HamiltonPath/ and name the file HamiltonPath.java or HamiltonPath.txt. Folder and File Structure for Algorithm Contributions: Specify Language: Clearly indicate the language used. Follow Folder Structure: Maintain folder hierarchy as specified. File Naming: Use descriptive file names, as shown in examples. Example Structure for MATLAB and Other Languages | Algorithm Type | Language | Path ||----------------|----------|------|| Euler Formula | MATLAB | /Calculus/EulerFormula/EulerFormula.m || Hamilton Path | Java | /BackTracking/HamiltonPath/HamiltonPath.java | Contribution Guide- Ensure all contributions adhere to the naming and directory conventions.- Structure code clearly and include relevant comments where necessary.

This program performs directional wave separation in a Discrete-Time Acoustic Pulse Reflectometry (APR) system, based on Louis et al.'s method (1993). The algorithm requires recordings from two microphones (pm1c and pm2c) positioned at axial intervals within the source tube. The microphone spacing (shift) represents the time samples needed for sound waves to travel between the two microphones. The outputs, pm2plus and pm2minus, represent forward and backward propagating waves at microphone 2 within the source tube. Key Reference: Louis, B.; Glass, G.; Kresen, B.; Fredberg, J. \"Airway Area by Acoustic Reflection: The Dual Microphone Technique,\" Journal of Biomechanical Engineering, 1993, 115, 278.