pho=[300;862;74.2;1.18];%密度 c=[1377;2100;1726:1005];%比热容 lamda=[0.082;0.37;0.045;0.028];%热导率 a=lamda./pho./c;%热扩散率如何改成数组大小兼容

可以使用 `reshape` 函数将 `pho` 和 `c` 调整为和 `lamda` 相同的大小，然后再进行计算，代码如下：

pho = [300; 862; 74.2; 1.18];
c = [1377; 2100; 1726; 1005];
lamda = [0.082; 0.37; 0.045; 0.028];

pho_resized = reshape(pho, [], 1);
c_resized = reshape(c, [], 1);

a = lamda ./ pho_resized ./ c_resized;

在上面的代码中，`[]` 表示自动计算数组大小，以保证 `pho` 和 `c` 能够和 `lamda` 相匹配。

相关问题

a=lamda./(pho.*c)

这个表达式的含义是将 lambda 向量的每个元素除以 pho 向量和 c 向量对应位置的元素的乘积，结果是一个新的向量。

假设 lambda、pho 和 c 都是向量，那么在 Matlab 中可以这样写：

a = lambda ./ (pho .* c);

其中，./ 表示对每个元素进行除法运算。

function P137_72 clear all close all clc xk=0.5; alphamax=2; [alpha, newxk, fk, newfk] = wolfe(xk, dk) function [alpha, newxk, fk, newfk] = Wolfe(xk, dk) alpha = Wolfe(@phi,@gphi,a0,b0,t,pho) rho = 0.1; sigma = 0.8; alpha = 1; a1=0; a2=alphamax; dk=60; phi1=feval(phi, xk); gphi1=feval(phi, xk)'*dk; function f=phi(t) f=-2*t^3+21*t^2-60*t+50; % ÌݶÈ/µ¼Êý function gf=gphi(t) gf=-6*t^2+42*t-60;

以下是转换后的Python代码：

import numpy as np

def phi(t):
    return -2*t**3 + 21*t**2 - 60*t + 50

def gphi(t):
    return -6*t**2 + 42*t - 60

def Wolfe(xk, dk):
    alpha = 1
    rho = 0.1
    sigma = 0.8
    alphamax = 2
    a1 = 0
    a2 = alphamax
    phi1 = phi(xk)
    gphi1 = gphi(xk)*dk
    while True:
        phialpha = phi(xk + alpha*dk)
        if phialpha > phi1 + rho*alpha*gphi1 or (phialpha >= phi(a1 + alpha*(a2-a1)) and a2-a1 >= 10**(-10)):
            alpha = zoom(a1, alpha, a2, xk, dk)
            break
        gphialpha = gphi(xk + alpha*dk)*dk
        if abs(gphialpha) <= -sigma*gphi1:
            break
        if gphialpha >= 0:
            alpha = zoom(alpha, alpha/2, alpha, xk, dk)
            break
        a1 = alpha
        a2 = min(alphamax, alpha*2)
        alpha = 2*alpha
    newxk = xk + alpha*dk
    fk = phi1
    newfk = phi(newxk)
    return alpha, newxk, fk, newfk

def zoom(a_lo, a_hi, xk, dk):
    rho = 0.1
    sigma = 0.8
    phi1 = phi(xk)
    gphi1 = gphi(xk)*dk
    while True:
        alpha = (a_lo + a_hi)/2
        phialpha = phi(xk + alpha*dk)
        if phialpha > phi1 + rho*alpha*gphi1 or phialpha >= phi(xk + a_lo*dk):
            a_hi = alpha
        else:
            gphialpha = gphi(xk + alpha*dk)*dk
            if abs(gphialpha) <= -sigma*gphi1:
                break
            if gphialpha*(a_hi - a_lo) >= 0:
                a_hi = a_lo
            a_lo = alpha
    return alpha

xk = 0.5
alphamax = 2
alpha, newxk, fk, newfk = Wolfe(xk, dk)