whuawell的博客

双曲型差分(一维)

#coding:utf-8from mpl_toolkits.mplot3d import axes3dimport matplotlib.pyplot as pltimport numpy as npimport timedef createMatrix( m, n): A = np.zeros( (n + 2,m + 2)) Up = np.ones( (m+2,1)) * 1

// ImpMx.mfunction ImpMx = getImpMx()clear;clc; M = 4;N = 3;Up = zeros(1,M);Down = Up;Lf = zeros(1,N);Rt = Lf;rx = 0.1;ry = 0.3;r = rx + ry;ImpMatrix = diag( ones(1, M * N)) * ( 1 + 2 * r

椭圆型差分   //精确解function z = gFun(x,y)    z = (%e)^( %pi * ( x + y)) * sin( %pi * x) * sin( %pi * y);endfunction//外力function z = fFun(x,y)    z = 2 * %

双曲型偏微分（谱方法）  s //scilab code N = 128;h = 2 * %pi /N;x=  h * [1 :N];t = 0;dt = h /4;c = 0.2 + sin(x-1) .^2;v = exp(- 100 * ( x- 1).^2);vo

双曲型差分（二维）数值例子 数值解: 精确解: 注释：显示差分格式，隐式格式暂未考虑// scilab code //精确解t =linspace(0,1,100);t = t';x = linspace(0,1,100);z = cos( 4 * 3.141

抛物型差分（二维—ADI格式）example : 模拟四方边界 ， 上：100°、下：0°、左：75°、右：50° //getStart.m // simulatefunction getStart()clcX_INTERVAL = [0 20];Y_INTERVAL = [0 30];T = [ 0 10];deltax = 0.5;delta

抛物型差分（一维）从上到下依次为显式、隐式、精确解、六点差分得到的解//Explicit.mM = 10;h = 1/( M + 1);tao = 0.5 * h * h;r = tao /( h * h);I = [ 0 1 ];T = [ 0 4 ];init = zeros(1 , M +

偏微分方程的数值解1.     抛物型方程的差分方法2.     双曲型方程的差分方法3.     椭圆型方程的差分方法4.     有限元方法Introduction：

import matplotlib.pyplot as pltimport numpy as npfrom PIL import Imagedef np_from_img(fname): img = Image.open(fname) print img.format, img.size, img.mode img = img = img.convert('I') #pri