Question

我想集成2维功能，但是当我使用Python和MATLAB进行操作时，会得到不同的结果。两种编程语言的实现如下：

MATLAB：

function [v] = RaisedC(t,alpha,trunc)
T=1;
if abs(t)<=trunc
  if abs(abs(alpha * t / T) - 0.5) > 1e-5
    v=sinc(t/T) .* cos(pi .* alpha .* t ./ T) ./ (1 - (2 .* alpha .* t ./ T).^2); % # typical case
  else
    v=sinc(t/T) .* pi .* sin(pi .* alpha .* t ./ T) ./ (8 .* alpha .* t ./ T);  % L'Hopital limit for alpha * tau = 0.5
  end
else
  v=0;
end

str='RaisedC';
alpha=0.25;
trunc=10;
snr=15;
sir=10;
L=1;
n=21;
dblquad(@An_test, 0,1, 0, 2*pi, 1e-6,[], str,alpha,trunc,snr,sir,L,n)
end

function R = An_test(Tau, Alpha, str,alpha,trunc,snr,sir,L,n)
fh=str2func(str);
Rs = 10^(snr/20);
Ri= Rs/(sqrt(L)*10^(sir/20));
P=10;
w=2*pi/60;
R=1;
  for kT=-P:1:P
    R=R.*[cos(n.*w.*fh(-Tau-kT,alpha,trunc).*datasample([1 -1],1).*Ri.*cos(Alpha)).*cos(n.*w.*fh(-Tau-kT,alpha,trunc).*datasample([1 -1],1).*Ri.*sin(Alpha))];
  end
end

Python

def RC(t,alpha,trunc):
    v=np.float64(0)
    T=1.0;
    if np.absolute(t)<=trunc:
        if np.abs(np.abs(alpha * t / T) - 0.5) > 1e-5:
            v=np.sinc(t/T) * np.cos(np.pi * alpha * t / T) / (1 - np.power((2 * alpha * t / T),2)) # typical case
        else:
            v=np.sinc(t/T) * np.pi * np.sin(np.pi * alpha * t / T) / (8 * alpha * t / T)  # asdasdL'Hopital limit for alpha * tau = 0.5
    else:
        v=0 # asd
    return v

def An(Tau_i,Alpha_i,str,alpha,trunc,snr,sir,L,n):
    Rs = 10**(snr/20);
    Ri = Rs/(np.sqrt(L)*10**(sir/20));
    P=10;
    w=2*np.pi/60;
    fh=eval(str)
    T=1
    y=np.float64(1)
    for k in range(-P,P+1):
        y=np.float64(y*np.cos(n*w*fh((-Tau_i-k*T),alpha,trunc)*(np.random.randint(0,2)*2-1)*Ri*np.cos(Alpha_i))*np.cos(n*w*fh((-Tau_i-k*T),alpha,trunc)*(np.random.randint(0,2)*2-1)*Ri*np.sin(Alpha_i)))
    return(y)

str='RC'
alpha=0.25
trunc=10
snr=15
sir=10
L=1
n=21
I = dblquad(An, 0,1,lambda x: 0, lambda x: 2*np.pi,args=    (str,alpha,trunc,snr,sir,L,n),epsabs=int(1e-12),epsrel=int( 1e-6))
print(I)

我的工作量非常小，积分的差异使最终结果有很大差异。另外，我在MATLAB中使用符号变量实现了函数integral2的实现，但其结果与dblquad的实现相同。

关于如何解决此问题的任何想法？

在Scipy与MATLAB中的集成产生不同的结果

0 个答案: