DAY03_Math 和 Date.md

MathEdit采用标准的JavaScript和DOM实现,使得数学公式能够以不同于传统交流的方法在Web上处理和传输.

计算机图形学的入门级书籍，几乎是必须接触的。下面是摘录： This edition of Fundamentals of Computer Graphics includes substantial rewrites of the chapters on textures and graphics hardware, as well as many corrections throughout. The figures are now in color throughout the book. The organization of the book remains substantially similar to the third edition. In our thinking, Chapters 2 through 8 constitute the “core core,” taking the straight and narrow path through what is absolutely required for understanding how images get onto the screen using the complementary approaches of ray tracing and rasterization. Ray tracing is covered first, since it is the simplest way to generate images of 3D scenes, followed by the mathematical machinery required for the graphics pipeline, then the pipeline itself. After that, the “outer core” covers other topics that would commonly be included in an introductory class, such as sampling theory, texture mapping, spatial data structures, and splines. Starting with Chapter 15 is a number of contributed chapters, authored by contributors we have chosen both for their expertise and for their clear way of expressing ideas. As we have revised this book over the years, we have endeavored to retain the informal, intuitive style of presentation that characterizes the earlier editions, while at the same time improving consistency, precision, and completeness. We hope the reader will find the result is an appealing platform for a variety of courses in computer graphics.

数学物理方程，英文教程 剑桥大学出版社 by Ken Riley, Michael Hobson Cambridge, 2002

NI Labview 2012 math script 模块，便于使用已有的matlab资料

大一的数学实验其中一部分，利用mathematica绘制空间曲面数学实验的两个例子及其代码

math.h just great,if you use this,don't shout it,please.

Doing Math with Python shows you how to use Python to delve into high school—level math topics like statistics, geometry, probability, and calculus. You'll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you've gotten the hang of things. Along the way, you'll discover new ways to explore math and gain valuable programming skills that you'll use throughout your study of math and computer science. Learn how to: Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots Explore set theory and probability with programs for coin flips, dicing, and other games of chance Solve algebra problems using Python's symbolic math functions Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You'll write an inequality solver, plot gravity's effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more.Whether you're interested in math but have yet to dip into programming or you're a teacher looking to bring programming into the classroom, you'll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Table of Contents Chapter 1: Working with Numbers Chapter 2: Visualizing Data with Graphs Chapter 3: Describing Data with Statistics Chapter 4: Algebra and Symbolic Math with SymPy Chapter 5: Playing with Sets and Probability Chapter 6: Drawing Geometric Shapes and Fractals Chapter 7: Solving Calculus Problems Appendix A: Software Installation Appendix B: Overview of Python Topics

东南大学计算方法复习总结

Applying-Math-with-Python-master. 源代码